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Петков, Александр Александрович. "Стимулирование использования альтернативных источников энергии для энергоснабжения индивидуального дома." Thesis, Одеський національний політехнічний університет, 2018. http://repository.kpi.kharkov.ua/handle/KhPI-Press/34008.
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В работе предложен возможный вариант решения проблемы дальнейшего стимулирования развития нетрадиционной и возобновляемой энергетики в условиях Украины. Рассмотрены материалы применимые к альтернативным источникам энергии, которые сооружаются при индивидуальных строениях.The paper suggests a possible solution to the problem of further stimulating the development of unconventional and renewable energy in the conditions of Ukraine. Materials considered applicable to alternative energy sources that are constructed under individual structures are considered.
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Baek, Youngsun. "Responsiveness of residential electricity demand to changes in price, information, and policy." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/39581.
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This study analyzes consumers' behavioral responsiveness to changes in price and policy regarding residential electricity consumption, using a hybrid method of econometric analyses and energy market simulations with the National Energy Modeling System (NEMS). First, this study estimates price elasticities of residential electricity demand with the most recent Residential Energy Consumption Survey (RECS) data, collected in 2005, employing a conventional econometric model and a discrete/continuous choice model. Prior to the NEMS experiments with price shocks and consumers' behavioral features, this study uses NEMS to examine how energy policies would affect changes in retail electricity price in the future.
When climate policies are implemented nationally, electricity prices are estimated to increase by 17% in 2030 with a carbon cap and trade initiatives and by 4% with Renewable Electricity Standards (RES). The short-run elasticity of demand estimated from the 2005 RECS is found to be in a range of -0.81 ~ -0.66, which is more elastic than the current NEMS assumption of -0.15. The 2005 RECS dataset details information about American households' energy consumption. This rich source of micro-level data complements the existing econometric analysis based on time series data.
Electricity price (either census-division average price or household average price), annual income and number of rooms are found to be three major determinants of the level of electricity consumption. The difference in short-run price elasticity leads to a difference in social welfare estimates of energy policies and energy market forecasts. This study suggests that the estimate of social welfare loss caused by electricity price increase is overestimated if the elasticity is assumed to be smaller than the actual responsiveness. Supposing that 1) the short-run elasticity of -0.66 reflects the actual consumers' responsiveness to price changes in the present and future and 2) retail
electricity prices permanently increase by 10%, the welfare loss caused by the price increases would be estimated 0.9 billion dollars less than the current estimates with the elasticity of -0.15. This result suggests that if people are assumed to be more elastic to price signals, the time it takes for a policy to accomplish its goal could be shorter.
In addition to assessing potential savings expected from consumers' behavioral changes with the concept of price elasticity of demand in neoclassical economic theory, this study reviews economic and non-economic theories about behavioral features of energy consumers and discusses how existing information programs could be improved.
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KNUTZEN, DORIS MBIH. "SUSTAINABLE ENERGY STRATEGIES AND GREEN ELECTRICITY MARKET DEVELOPMENT : EMPIRICAL EVIDENCE FROM GERMANY." Thesis, Blekinge Tekniska Högskola, Sektionen för management, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-4711.
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Human misuse of environmental assets especially energy is causing environmental degradation, which hampers social and economic welfare for present as well as for future generations. A worldwide shift to sustainable energy sources is one of the required actions to solve the problem. Electricity from sustainable energy sources is called green electricity and has arose as one of the most motivating tools for developing the sustainable energy market. This has resulted in the restructuring of Germany's energy industry with a dramatic change in energy use in electricity. The change has been aided by the German renewable energies act (EEG), which is been criticized for its resulting high green electricity prices which consumers have to pay. Green electricity prices seem to call for more consumers' attention than threats posed by conventional energy because only a small fraction of energy is sold as green electricity neccesitating the rethinking of the energy market. Due to the need for future research on more factors influencing consumers buying behavior in the green electricity market, this thesis seeks to investigate the following research questions: Is green electricity price the major influencing factor for its market unattractivess? Does the concern about price really calls for more attention than environmental concerns? It specifically aims to describe German consumers' perceptions of factors influencing their green electricity buying behavior. The research methodology involves the use of secondary and primary data. The secondary data gives a background knowledge of Germany and its energy historical development, Germany's sustainable energy strategies and strategies for market development (electricity feed-in-tariffs, the renewable energy act and problems), green electricity marketing, consumers' purchasing behavior and factors influencing this behavior. The primary data is gotten through a questionnare survey and analysed using both excel and the statistical package for social sciences. Evidence is taken from Germany because of its ambitious goals of 20-30% green electricity by 2020 and 80-100% by 2050. The result of the study shows that, although price is the most influencing factor in choosing an electricity supplier and also calls for more attention than environmental concerns, it's not the major hindering factor for the green electricity market unattractivess. Most German electricity consumers (42%) have no idea about green electricity prices. In comparison to competitors, 27% of them assume the prices are higher while 31% say the prices are thesame and even lower. All green electricity consumers confirm the prices are moderate and even cheaper. Even when prices are the same, most respondents gave other reasons like conviniences before environmental friendliness as the first motive for their electricity choice. Despite Germany's ambitous goals, consumers selfinterest and ignorance about green electricity prices remain a problem for the market.
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Steward, Thomas William. "Governance for affordable energy : what is the impact of demand-side governance on affordability of energy for domestic consumers in Great Britain?" Thesis, University of Exeter, 2016. http://hdl.handle.net/10871/29915.
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Affordability of energy in the domestic sector is the product of three interrelated factors - level of household income, level of energy bills (which are a product of prices and levels of energy demand, mediated by tariffs and the retail market), and the amount of energy that a household needs to maintain a healthy living environment. This thesis focusses on the factors of affordability which are most relevant to the energy policy which are energy bills and energy efficiency, both of which are considered in the context of household income. Affordability of energy in Great Britain is important for separate, but over-lapping reasons. Firstly, it has important political impacts - as energy prices continue to rise, energy is repeatedly highlighted as one of the biggest financial concerns for households (uSwitch, 2013; YouGov, 2015; DECC, 2014f), leading affordability of energy to become an increasingly political issue (Lockwood, 2016). Secondly, affordability of energy has social implications which stem from the fact that the impact of rising energy bills is felt particularly strongly by those on low incomes and in inefficient homes – the fuel poor. In spite of it being twenty-five years since Brenda Boardman published her first book defining the issue of fuel poverty (Boardman, 1991), millions of households in Great Britain today still cannot afford adequate amounts of energy. This is significant because being able to afford access to basic levels of energy services such as warmth and light is essential for maintaining physical and mental health (Harrington et al., 2005; Stockton and Campbell, 2011). Thirdly, affordability has important implications for design of the energy system –a system focussed on minimising long-term costs, both through micro-scale features such as efficient network revenue regulation which keep costs down on a year-by-year basis, and macro-scale aspects such as through the development of a low-demand, highly flexible energy system which has the potential to bring costs down in the long term (Sanders et al., 2016), is likely to differ from one which in which affordability is less of a focus, or only a focus over the short term. This thesis responds to a gap in the literature in relation to the role that governance plays in affecting levels of affordability of energy for domestic consumers in Great Britain. It examines the impact of governance on energy prices and tariffs, and the impact of governance on energy efficiency of the housing stock in Great Britain. Both of these are examined in the context of levels of household income. Greater insight is gained by examining the impact of the energy governance structure in Denmark on Danish domestic energy efficiency standards, which are widely accepted to be very good (IEA, 2011). 7 This thesis makes use of existing academic and policy literature in tandem with data from fifty-six interviews with individuals from across the energy sectors in Great Britain and Denmark. The governance structure of energy in Great Britain is shown to be, on balance, not supportive of delivering affordable energy to domestic consumers. A number of specific issues within the current governance structure in Great Britain are identified. These include the presence of a limiting narrative, whereby policymakers consider affordability to be achieved principally through delivery of low prices; insufficient institutional capacity within OFGEM to keep network prices low, and monitor suppliers’ costs and profits; lack of wholesale market transparency; an anti-interventionist ideology leading to weak energy efficiency requirements for new-build and private rental properties; suppliers as poor executors of energy efficiency policy; weak demand-side interests; tariffs designed around the needs of suppliers, not consumers; an over-reliance on an uncompetitive retail market; a lack of institutional capacity amongst policy makers regarding energy efficiency, and network regulation; and weak consumer representation. A number of recommendations are put forward, including the fostering of a new narrative centred on energy efficiency; the redesign of tariffs to better protect the interests of consumers; the reallocation of responsibility for energy efficiency to local authorities; the development of greater institutional capacity among policymakers; the support for a more interventionist ideology supporting use of regulation; financial support for energy efficiency retrofit; the fostering of greater policy stability; development of new tariff structures; and the formation of a new consumer representative. Overall this thesis demonstrates that affordability of energy in unlikely to be delivered to domestic consumers in Great Britain unless significant changes are made to the governance structure of the energy sector.
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Martins, Ana Patrícia da Silva. "Impact of CO2 price in electricity price: MIBEL's case." Master's thesis, Universidade de Aveiro, 2012. http://hdl.handle.net/10773/10861.
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Mestrado em EconomiaO custo das licenças de emissão de dióxido de carbono é um custo de oportunidade para as industrias afetadas, uma vez que essas licenças de emissão podem ser transacionadas no mercado. Particularmente no sector elétrico esta questão tem despertado a atenção do público, devido à possibilidade de incluir este custo de oportunidade no preço da eletricidade, gerando lucros adicionais para as centrais. Para avaliar a existência desta passagem de custos no recém criado Mercado Ibérico de Eletricidade, recolhemos dados sobre os preços das licenças de emissão de CO2, do combustível e da eletricidade, e utilizamos o modelo do vetor autorregressivo (VAR). Concluímos que há evidencia de passagem de custos do CO2 para o preço da eletricidade, sendo este ligeiramente mais elevado em Portugal do que em Espanha. A passagem de custos do CO2 parece ser maior no pico da carga do que na carga base.
The cost of carbon emission allowances is an opportunity cost for industries affected, since these allowances can be traded in the market. Particularly in the electrical sector this issue has triggered public attention, due to the possibility of including this opportunity cost in the electricity prices, generating windfall profits for utilities. To assess the existence of this pass-through in the newly created Iberian Electricity Market, we collect data on prices of electricity, fuel and CO2 allowances, and we use a Vector Autoregressive (VAR) Model. We conclude that there is evidence of CO2 cost pass-through to the electricity price, being a slightly higher in Portugal than in Spain. The CO2 cost pass-through still seems to be higher at peak load than at base load.
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Giri, Suman. "A Framework for Estimating Energy Consumed by Electric Loads Through Minimally Intrusive Approaches." Research Showcase @ CMU, 2015. http://repository.cmu.edu/dissertations/564.
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This dissertation explores the problem of energy estimation in supervised Non-Intrusive Load Monitoring (NILM). NILM refers to a set of techniques used to estimate the electricity consumed by individual loads in a building from measurements of the total electrical consumption. Most commonly, NILM works by first attributing any significant change in the total power consumption (also known as an event) to a specific load and subsequently using these attributions (i.e. the labels for the events) to estimate energy for each load. For this last step, most proposed solutions in the field impart simplifying assumptions to make the problem more tractable. This has severely limited the practicality of the proposed solutions. To address this knowledge gap, we present a framework for creating appliance models based on classification labels and aggregate power measurements that can help relax many of these assumptions. Within the framework, we model the problem of utilizing a sequence of event labels to generate energy estimates as a broader class of problems that has two major components (i) With the understanding that the labels arise from a process with distinct states and state transitions, we estimate the underlying Finite State Machine (FSM) model that most likely generated the observed sequence (ii) We allow for the observed sequence to have errors, and present an error correction algorithm to detect and correct them. We test the framework on data from 43 appliances collected from 19 houses and find that it improves errors in energy estimates when compared to the case with no correction in 19 appliances by a factor of 50, leaves 17 appliances unchanged, and negatively impacts 6 appliances by a factor of 1.4. This approach of utilizing event sequences to estimate energy has implications in virtual metering of appliances as well. In a case study, we utilize this framework in order to substitute the need of plug-level sensors with cheap and easily deployable contacless sensors, and find that on the 6 appliances virtually metered using magnetic field sensors, the inferred energy values have an average error of 10:9%.
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Armada, Ramírez Ferran. "European energy markets integration and its effects on prices and efficiency of electricity producing firms." Doctoral thesis, Universitat de Barcelona, 2016. http://hdl.handle.net/10803/393928.
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In this work we investigate the effect of energy (electricity) market integration in Europe and its effects on electricity prices and efficiency improvements in electricity producing firms. We first describe at detail the electricity sector, the role of electricity markets, the main characteristics of electricity as a commodity as well as the main features of this particular and strategic sector, we speak about the evolution of consumption of electricity in developed countries and particularly in Spain. In the second chapter, we address extensively the most recent round of reforms approved for the European electricity markets, known as the third energy package. We speak of the actors that were relevant for such approval their preferred outcomes and the final result of the bargaining process. To do this we use qualitative methods to venture beyond description of what happened and to explain the conditions that rendered the entire process be favourable for the European Commission proposal of reform.
In the third chapter of the dissertation we deal with the issue of electricity prices in European countries. We propose a group of variables as drivers of electricity prices, we discuss the relationship that these variables might have with electricity prices and we conduct an analysis in which we set up a model to test the possible relation of these drivers with the prices paid by industrial and household costumers. In particular we test the relationship that might exist between the suppliers’ ownership and the prices charged to final consumers, as well as the quantity of primary energy available and the exchanges of electricity or the concentration of the electricity markets and the amount of renewable energy supplied in the different European countries. To test our model and the relationship of the proposed drivers with net prices we constructed a panel data that covers the years from 2001 to 2010 a few years before and after the second and the third energy packages, the last major reform packages in European countries.
Finally in Chapter 4 we focus on dealing with what we consider to be one of the most important consequences of liberalizing the electricity sector, which are the possible changes in the firms’ efficiency. Particularly we focus in internal efficiency, that is, the more efficient ways that power plants may find to continue with their activity in a more competitive context. Said in a different way, due the increasing competition because of the liberalization measures, producers of electricity must adjust their production methods to keep been competitive or even gain competitiveness, this, in turn, is connected with gains in consumers welfare. In this case we first make a review of the best and most used methods to assess changes in the performance (efficiency) of firms, we set up a database that takes in account three different years of 130 power plants in eighteen European countries, sixteen of them European Union members and two non-EU members but important partners in what concerns to electricity markets (Norway and Switzerland); the three years taken in account are 2004, 2009 and 2013, the database is not a panel data, but observations made in three different points in time to tests each of the years while the results are used to calculate the Malmquist indexes that will give tell us how firms move relative to the frontier and if the frontier is actually moving.
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Kwok, Ho King Calvin Actuarial Studies Australian School of Business UNSW. "Energy price modelling and risk management." Awarded by:University of New South Wales. Actuarial Studies, 2007. http://handle.unsw.edu.au/1959.4/40602.
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This thesis focuses on the development of a forecasting model for short- to medium-term electricity spot prices, based on modelling the dynamics of the supply and demand functions. It is found that the equilibrium assumption frequently adopted in electricity price models does not always hold; to overcome this problem, a notional demand process derived from the market clearing condition is proposed. Not only is this demand process able to capture all the price-affecting factors in one variable, but it also allows the equilibrium assumption to be satisfied and a spot price model to be built, using any appropriate form of hypothetical supply function. In addition, this thesis presents a model for approximating and modelling the bid stacks by capturing the points that govern their shape and location. Integrating these two models provides a realistic model that has a mean absolute percentage error of approximately 19% and 24% for week- and month-ahead forecasts respectively, when applied to the New South Wales (NSW) half-hourly electricity spot prices. Additionally, the density forecasting evaluation method proposed by Diebold et al. (1998) is employed in the thesis to assess the performance of the model. Besides the development of a spot price model, a two-part empirical study is made of the prices of NSW electricity futures contracts. The first part of the study develops a method based on the principle of certainty equivalence, which enables the market utility function to be recovered from a set of futures market quotes. The method is tested with two different sets of simulated data and works as expected. However, it is unable to obtain useful results from the NSW market quotes due to the poor data quality. The second part uses a regression method to investigate the relationship between futures prices and the descriptive statistics of the underlying spot prices. The result suggests that futures prices in NSW are linear combinations of the median and volatility of the final payoff.
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Breitenfellner, Andreas, Cuaresma Jesus Crespo, and Philipp Mayer. "Energy Inflation and House Price Corrections." Elsevier, 2015. http://dx.doi.org/10.1016/j.eneco.2014.08.023.
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We analyze empirically the role played by energy inflation as a determinant of downward
corrections in house prices. Using a dataset for 18 OECD economies spanning the last four
decades, we identify periods of downward house price adjustment and estimate conditional
logit models to measure the effect of energy inflation on the probability of these house price
corrections after controlling for other relevant macroeconomic variables. Our results give
strong evidence that increases in energy price inflation raise the probability of such corrective
periods taking place. This phenomenon could be explained by various channels: through the
adverse effects of energy prices on economic activity and income reducing the demand for
housing; through the particular impact on construction and operation costs and their effects on
the supply and demand of housing; through the reaction of monetary policy on inflation
withdrawing liquidity and further reducing demand; through improving attractiveness of
commodity versus housing investment on asset markets; or through a lagging impact of
common factors on both variables, such as economic growth. Our results contribute to the
understanding of the pass-through of oil price shocks to financial markets and imply that energy
price inflation should serve as a leading indicator for the analysis of macro-financial risks. (authors' abstract)
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SZCZERBACKI, CAROLINA FERREIRA. "ELECTRICAL ENERGY PRICE STRUCTURING FOR THE BRAZILIAN MARKET." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2007. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=10656@1.
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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOOs preços de energia elétrica, insumo básico para todo o Modelo Setorial, constituem uma das maiores incertezas do setor. Estas incertezas abrangem todos os elementos formadores de preços: a oferta, a demanda e as regras de mercado, tornando muitas vezes difícil ao agente a avaliação concreta e precisa do processo da formação de preços e do impacto que a variação de um dos elementos do processo produz no resultado final. O objetivo deste trabalho é apresentar a estrutura de formação de preços no mercado energético brasileiro de forma sistematizada, avaliando a composição das variáveis que afetam esta estrutura: a demanda por consumo, a expansão do sistema e as disponibilidades energéticas. O mercado é modelado em todos os seus detalhes físicos, e o cálculo é realizado a partir de todo o arcabouço regulatório, incluindo a reprodução do modelo de operação ótima responsável pelos preços de energia. Descreve-se inicialmente um modelo de previsão de demanda por subsistema, utilizando-se técnicas de Teoria de Análise Funcional. Focaliza-se em seguida o suprimento futuro de energia no país a partir da expansão da oferta. Finalmente, utiliza-se uma simulação da operação ótima do sistema a partir da reprodução dos resultados do modelo utilizado no setor - o Newave - a partir de uma implementação própria desenvolvida especialmente no escopo deste trabalho. De posse dos possíveis cenários futuros, pode-se mensurar o impacto que a variação de cada elemento formador (demanda, expansão e afluências) tem sobre os custos de energia. É possível observar que as incertezas nestas variáveis podem gerar grandes impactos nos custos marginais e, conseqüentemente, nos custos futuros de energia elétrica.
Energy Prices, essential input for the Sectorial Model, consist on the biggest uncertainties of the Electric Sector. These uncertainties enclose all price elements: the supply, the demand and the market rules, making sometimes difficult for the agents to evaluate the price process and the impact that the variation of each process element can produce on the result. The objective is to present Brazilian price process in a structuralized way, evaluating the variables composition that affects this structure: the demand, the electric system expansion and the energy supply availability. The market is modeled in all its physical details, and the calculation is done into the regulatory environment, including a reproduction of the optimal operation model responsible for energy prices. First, a demand forecast model is described, based on Functional Analysis Theory. Then, the focus is on the energy future supply, analyzing the supply expansion in Brazil. Finally, an optimal operation system is simulated, reproducing the sector model (Newave) results from an implementation developed in this work. From these possible future settings, each element (demand, expansion and energy supply availability) variation impact on energy prices can be measured. The simulations show that uncertainties about these variables can have big impacts on marginal costs and, consequently, on the energy future prices.
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Gong, Jian. "How U.S. Agriculture Adjusts to Energy Price Changes." Thesis, North Dakota State University, 2007. https://hdl.handle.net/10365/29849.
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The primary objective of this research is to measure the impacts of rising energy prices on U.S. agriculture and to analyze the capability of U.S. agricultural producers to adjust for energy price volatility. This study compares four different models of producer adjustment: the static model, the simple error correction model, the partial adjustment model, and the fully dynamic model. The first three models are nested within the fully dynamic model using ]948-2002 U.S. agriculture data. Morishima elasticities of substitution and price elasticities are estimated to investigate whether U.S. agriculture's responses to energy prices have changed over time. The elasticity estimates indicate that there are substitutions among production factors in U.S. agricultural production, and the substitution elasticities have increased over the 1948-2002 period. This finding suggests an increasing possibility for farmers to substitute other production inputs for energy to mitigate the effects of changing energy prices.Upper Great Plains Transportation Institute
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Skogfeldt, Alexander. "Energy efficiency measures and energy pricing : The effect of different price schemes on energy efficiency measures." Thesis, Uppsala universitet, Matematiska institutionen, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-325895.
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This project investigates the relationship between energy efficiency measures in the Swedish building stock and different price schemes based on energy prices. Data from different categories was gathered and used in a regression model. They were based on what type of pricing and fees that are behind the energy prices for electricity and district heating. These predictors were used to get an equation of the temperature corrected energy use which can be linked to how much energy efficiency measures have been implemented over the investigated time period. The result for the main equation, that includes all the studied building types, indicated that it is possible to predict energy efficiency measures with different price schemes,and therefore it is possible to increase the rate at which measures are implemented. It showed that there is a negative relationship between energy consumption and theprice of energy from district heating. If the price of district heating increases the temperature corrected energy use decreases. The other relationships between predictors and the dependent variable were positive. It also described the geographical location as a statistically significant variable, regarding all climate zones in Sweden.
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Dinçerler, Cantekin. "Futures risk premia and price dynamics in energy industry." Access restricted to users with UT Austin EID Full text (PDF) from UMI/Dissertation Abstracts International, 2001. http://wwwlib.umi.com/cr/utexas/fullcit?p3036593.
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GONZALES, JAVIER LINKOLK LOPEZ. "ENERGY PRICE SIMULATION IN BRAZIL THROUGH DEMAND SIDE BIDDING." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2015. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=26422@1.
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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIROCOORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE SUPORTE À PÓS-GRADUAÇÃO DE INSTS. DE ENSINO
A Eficiência Energética (EE) pode ser considerada sinônimo de preservação ambiental, pois a energia economizada evita a construção de novas plantas de geração e de linhas de transmissão. O Leilão de Eficiência Energética (LEE) poderia representar uma alternativa muito interessante para a dinamização e promoção de práticas de EE no Brasil. Porém, é importante mencionar que isso pressupõe uma confiança na quantidade de energia reduzida, o que só pode se tornar realidade com a implantação e desenvolvimento de um sistema de Medição e Verificação (M&V) dos consumos de energia. Neste contexto, tem-se como objetivo principal simular os preços de energia do Leilão de Eficiência Energética no ambiente regulado para conhecer se a viabilidade no Brasil poderia se concretizar. A metodologia utilizada para realizar as simulações foi a de Monte Carlo, ademais, antes se utilizou o método do Kernel com a finalidade de conseguir ajustar os dados a uma curva através de polinômios. Uma vez conseguida a curva melhor ajustada se realizou a análise de cada cenário (nas diferentes rodadas) com cada amostra (500, 1000, 5000 e 10000) para encontrar a probabilidade dos preços ficarem entre o intervalo de 110 reais e 140 reais (preços ótimos propostos no LEE). Finalmente, os resultados apresentam que a probabilidade de o preço ficar no intervalo de 110 reais e 140 reais na amostra de 500 dados é de 28,20 por cento, na amostra de 1000 é de 33,00 por cento, na amostra de 5000 é de 29,96 por cento e de 10000 é de 32,36 por cento.
The Energy Efficiency (EE) is considered a synonymous of environmental preservation, because the energy saved prevents the construction of new generating plants and transmission lines. The Demand-Side Bidding (DSB) could represent a very interesting alternative for the revitalization and promotion of EE practices in Brazil. However, it is important to note that this presupposes a confidence on the amount of reduced energy, which can only take reality with the implementation and development of a measurement system and verification (M&V) the energy consumption. In this context, the main objective is to simulate of the prices of the demand-side bidding in the regulated environment to meet the viability in Brazil that could become a reality. The methodology used to perform the simulations was the Monte Carlo addition, prior to the Kernel method was used in order to be able to adjust the data to a curve, using polynomials. Once achieved the best-fitted curve was carried out through an analysis of each scenario (in different rounds) with each sample (500, 1000, 5000 and 10000) to find the probability of the price falling between the 110 real range and 140 real (great prices proposed by the DSB). Finally, the results showed that the probability of staying in the price range from 110 real nd 140 real data 500 in the sample is 28.20 percent, the sample 1000 is 33.00 percent, the sample 5000 is 29.96 percent and 10000 is 32.36 percent.
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Melichar, Mark Alan. "Essays on the macroeconomic effects of energy price shocks." Diss., Kansas State University, 2013. http://hdl.handle.net/2097/15994.
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Doctor of PhilosophyDepartment of Economics
Lance Bachmeier
In the first chapter I study the effects of oil price shocks on economic activity at the U.S. state-level, an innovative feature of this dissertation. States which rely more heavily on manufacturing or tourism are more adversely affected by adverse oil price shocks, while states which are major energy producers either benefit or experience insignificant economic changes from historically large oil price increases. Additionally, oil price increases from 1986 to 2011 have not impacted state-level economies to the same degree as increases from 1976 to 1985. This discrepancy can be attributed to a fundamental change in the structure of the U.S. economy, for example, a declining manufacturing sector or an increase in the efficiency with which energy is used in the production process. In the second chapter I explore the effects of alternative measures of energy price shocks on economic activity and examine the relative performance of these alternative measures in forecasting macroeconomic activity. The alternative energy prices I consider are: gasoline, diesel, natural gas, heating oil and electricity. I find that alternative measures of energy price shocks produce different patterns of impulse responses than oil price shocks. The overwhelming evidence indicates that alternative energy price models, excluding a model containing gasoline prices, outperforms the baseline model containing oil prices for many states, particularly at short-to-mid forecast horizons. In the third chapter, which is coauthored with Lance Bachmeier, we determine whether accounting for oil price endogeneity is important when predicting state-level economic activity. We find that accounting for endogeneity matters for in-sample fit for most states. Specifically, in-sample fit would be improved by using a larger model which contains both regular oil price and endogenous oil price movements. However, we conclude that accounting for endogeneity is not important for out-of-sample forecast accuracy, and a simple model containing only the change in the price of oil produces equally accurate forecasts. Accounting for endogeneity is particularly important in an environment in which rising oil prices were caused by a growing global economy, such as in the years 2004-2007.
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Castagneto, Gissey Giorgio. "Electricity and energy price interactions in modern EU markets." Thesis, Imperial College London, 2014. http://hdl.handle.net/10044/1/24143.
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This thesis studies the interactions between wholesale electricity prices and various energy and fuel prices, including those of natural gas, coal, oil and EUA carbon permits, in both spot and forward EU markets, during the late years of the noughties boom and the start of the twenty-tens. Chapter 1 introduces the thesis, Chapter 2 provides the necessary background on EU electricity prices and markets, whereas Chapter 3 presents a review of the relevant literature. Chapter 4 uses a nonlinear AR-GARCH approach to analyse the impacts of euro and pound sterling exchange rates (against the USD) and crude oil prices on the levels and volatility of six electricity spot prices. The study finds that electricity price return volatility was asymmetrically affected by both exchange rate and oil price returns in all markets only after the 2008 subprime crisis, which provided a considerably more symmetric response of electricity prices to positive and negative system innovations. Chapter 5 investigates the year-forward interactions between electricity prices and carbon, coal and natural gas prices in four markets via a combination of VAR, Granger-causality and asymmetric AR-GARCH analyses. The study shows that average electricity generators in the Nord Pool and EEX markets pass their carbon costs through to consumers with a ca. 35% higher rate than justified by effective carbon intensity, implying non-competitive practices. Additionally, coal prices are found to be the most influential determinant of European electricity price levels and volatilities. Chapter 6 analyses the integration of a sample of thirteen electricity spot markets. The application of complex network theory enables the creation of an evolving Granger-causal network of electricity price interactions, informing us on the presence of any changes in the normal functioning of electricity markets at both the national and European-wide levels. Finally, Chapter 7 summarises the conclusions of this thesis.
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Agnolucci, Paolo. "Energy consumption and energy price : an assessment of persistency, asymmetry, non-linearity and volatility." Thesis, Birkbeck (University of London), 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.502453.
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Ferraz, Bibiana Maitê Petry. "Programa de resposta à demanda baseado em preços aplicado a consumidores de baixa tensão." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2016. http://hdl.handle.net/10183/149835.
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O incremento nos padrões de consumo de energia elétrica e o fácil acesso a diversas tecnologias eletroeletrônicas têm contribuído para a superação anual dos índices de consumo de eletricidade. Tendo em vista que esse insumo ainda não é economicamente armazenável em larga escala, se faz necessário manter o equilíbrio em tempo real entre a oferta/demanda mais perdas. Entretanto, a maioria dos consumidores brasileiros atendidos em baixa tensão paga tarifas baseadas nos custos médios, os quais ocultam os efeitos da alta concentração de consumo de eletricidade em determinados horários do dia. Nesse contexto, o presente estudo analisa o impacto que Programas de Resposta à Demanda (PRD), baseado em tarifas com diferenciação horária, exercem sobre o desempenho dos sistemas de distribuição. A metodologia proposta utiliza o conceito de elasticidade-preço da demanda de energia elétrica, por meio de uma abordagem matricial e permite representar diferentes tipos de consumidores. A partir de uma análise de sensibilidade dos estudos de casos, verificou-se a influência dos parâmetros que compõem as equações do PRD proposto. Para avaliar o desempenho do modelo, foram feitos estudos numéricos usando uma versão modificada do sistema teste IEEE de 34 nós. A análise de sensibilidade entre os estudos de caso apresentou uma avaliação do percentual de adesão dos consumidores, bem como o comportamento das perdas ativas mensais e do perfil de tensão. Os resultados obtidos no presente estudo evidenciam a validade da abordagem proposta, a partir de uma formulação simplificada, além de demonstrar a potencial aplicabilidade a casos reais.Power consumption behavior increase and easy access to electroelectronics technologies had contributed to annual power consumption rates surpass. As there is not yet an economically sustainable way to store electric power it is necessary to maintain the balance between offer and power demand (considering losses). Brazilian customers majority supplied in low voltage are charged by its mean power consumption masking peak consumption in certain periods of the day. Within this reality the present work analysis the impact of Demand Response Programs (DRP) using Time-Of-Use tariff (TOU) over the power distribution system’s performance. The proposed methodology applies the concept of Price Elasticity demand and uses the representation of different consumers’ types in a matrix approach. The DRP parameters’ variation impact was checked using a sensitivity analysis. In order to evaluate the performance of the proposed model numerical studies were done using the IEEE 34 modified node test feeder. A sensitivity analysis among the case studies presents the customers adherence percentage and the monthly active power losses and voltage profile. The methodology's results besides supporting the proposal approach from a simplified formulation show the potential use on real cases.
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Kuang, Chen, Jin Ying, and Li Yumin. "Energy Crisis : wind Power Market in China." Thesis, Högskolan Kristianstad, Sektionen för hälsa och samhälle, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hkr:diva-10865.
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Purpose/aim The aim is to explore which price policy of the Chinese wind power is the most suitable for the market. Design/methodology/approach Data has been collected through questionnaires. The analysis includes the statistical test in form of chi-square. Additionally the whole thesis followed the onion process put forward by Saunders. Findings The analysis showed that the price policy which is based on the local price of coal is more suitable for the market than the price policy decided by concession projects. Originality/value An original idea is given the relationship between ages, education levels and two policies. Further, the empirical data is collected from a comprehensive online-forum, so that the samples are randomly selected. The data shows that the businesses which want to enter the Chinese wind power market should choose the price policy which is based on the local price of coal. This choice should be useful in the real life.
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Legbedji, Alexis Motto. "Price schedules coordination for electricity pool markets." Thesis, McGill University, 2001. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=38456.
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We consider the optimal coordination of a class of mathematical programs with equilibrium constraints, which is formally interpreted as a resource-allocation problem. Many decomposition techniques were proposed to circumvent the difficulty of solving large systems with limited computer resources. The considerable improvement in computer architecture has allowed the solution of large-scale problems with increasing speed. Consequently, interest in decomposition techniques has waned. Nonetheless, there is an important class of applications for which decomposition techniques will still be relevant, among others, distributed systems---the Internet, perhaps, being the most conspicuous example---and competitive economic systems. Conceptually, a competitive economic system is a collection of agents that have similar or different objectives while sharing the same system resources. In theory, constructing a large-scale mathematical program and solving it centrally, using currently available computing power can optimize such systems of agents. In practice, however, because agents are self-interested and not willing to reveal some sensitive corporate data, one cannot solve these kinds of coordination problems by simply maximizing the sum of agent's objective functions with respect to their constraints. An iterative price decomposition or Lagrangian dual method is considered best suited because it can operate with limited information. A price-directed strategy, however, can only work successfully when coordinating or equilibrium prices exist, which is not generally the case when a weak duality is unavoidable. Showing when such prices exist and how to compute them is the main subject of this thesis. Among our results, we show that, if the Lagrangian function of a primal program is additively separable, price schedules coordination may be attained. The prices are Lagrange multipliers, and are also the decision variables of a dual program. In addition, we propose a new form of a
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Otunuga, Olusegun Michael. "Stochastic Modeling and Analysis of Energy Commodity Spot Price Processes." Scholar Commons, 2014. https://scholarcommons.usf.edu/etd/5289.
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Supply and demand in the World oil market are balanced through responses to price movement with considerable complexity in the evolution of underlying supply-demand
expectation process. In order to be able to understand the price balancing process, it is important to know the economic forces and the behavior of energy commodity spot price processes. The relationship between the different energy sources and its utility together with uncertainty also play a role in many important energy issues.
The qualitative and quantitative behavior of energy commodities in which the trend in price of one commodity coincides with the trend in price of other commodities, have always raised the questions regarding their interactions.
Moreover, if there is any interaction, then one would like to know the extent of influence on each other.
In this work, we undertake the study to shed a light on the above highlighted processes and issues. The presented study systematically deals with the development of stochastic dynamic models and mathematical, statistical and computational analysis of energy commodity spot price and interaction processes.
Below we list the main components of the research carried out in this dissertation.
(1) Employing basic economic principles, interconnected deterministic and stochastic models of linear log-spot and expected log-spot price processes coupled with non-linear volatility process are initiated. (2) Closed form solutions of the models are analyzed.
(3) Introducing a change of probability measure, a risk-neutral interconnected stochastic model is derived.
(4) Furthermore, under the risk-neutral measure, expectation of the square of volatility is reduced to a continuous-time deterministic delay differential equation. (5) The by-product of this exhibits the hereditary effects on the mean-square volatility process.
(6) Using a numerical scheme, a time-series model is developed and utilized to estimate the state and parameters of the dynamic model.
In fact, the developed time-series model includes the extended GARCH model as special case.
(7) Using the Henry Hub natural gas data set, the usefulness of the linear interconnected stochastic models is outlined.
(8) Using natural and basic economic ideas, interconnected deterministic and stochastic models in (1) are extended to non-linear log-spot price, expected log-spot price and volatility processes. (9) The presented extended models are validated. (10) Closed form solution and risk-neutral models of (8) are outlined.
(11) To exhibit the usefulness of the non-linear interconnected stochastic model, to increase the efficiency and to reduce the magnitude of error, it was essential to develop a modified version of extended Kalman filtering approach.
The modified approach exhibits the reduction of magnitude of error.
Furthermore, Henry Hub natural gas data set is used to show the advantages of the non-linear interconnected stochastic model.
(12) Parameter and state estimation problems of continuous time non-linear stochastic dynamic process is motivated to initiate an alternative innovative approach. This led to introduce the concept of statistic processes, namely, local sample mean and sample variance. (13) Then it led to the development of an interconnected discrete-time dynamic system of local statistic processes and (14) its mathematical model. (15) This paved the way for developing an innovative approach referred as Local Lagged adapted Generalized Method of Moments (LLGMM). This approach exhibits the balance between model specification and model prescription of continuous time dynamic processes. (16) In addition, it motivated to initiate conceptual computational state and parameter estimation and simulation schemes that generates a mean square sub-optimal procedure. (17) The usefulness of this approach is illustrated by applying this technique to four energy commodity data sets, the U. S. Treasury Bill Yield Interest Rate and the U.S. Eurocurrency Exchange Rate data sets for state and parameter estimation problems. (18) Moreover, the forecasting and confidence-interval problems are also investigated.
(19) The non-linear interconnected stochastic model (8) was further extended to multivariate interconnected energy commodities and sources with and without external random intervention processes. (20) Moreover, it was essential to extend the interconnected discrete-time dynamic system of local sample mean and variance processes to multivariate discrete-time dynamic system. (21) Extending the LLGMM approach in (15) to a multivariate interconnected stochastic dynamic model under intervention process, the parameters in the multivariate interconnected stochastic model are estimated. These estimated parameters help in analyzing the short term and long term relationship between the energy commodities. These developed results are applied to the Henry Hub natural gas, crude oil and coal data sets.
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Pirzada, Ahmed Jamal. "Intermediate materials and energy price uncertainty in new Keynesian models." Thesis, University of Bristol, 2017. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.723499.
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Luciuk, Dean Richard. "The price-independent trend in energy efficiency in Canada and the potential influence of non-price policies." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0022/MQ51401.pdf.
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Plante, Michael. "Three essays on monetary policy responses to oil price shocks." [Bloomington, Ind.] : Indiana University, 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3380121.
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Thesis (Ph.D.)--Indiana University, Dept. of Economics, 2009.Title from PDF t.p. (viewed on Jul 14, 2010). Source: Dissertation Abstracts International, Volume: 70-12, Section: A, page: 4803. Advisers: Edward F. Buffie; Eric M. Leeper.
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Ma, Hengyun. "China’s Energy Economy: Reforms, Market Development, Factor Substitution and the Determinants of Energy Intensity." Thesis, University of Canterbury. Economics and Finance, 2009. http://hdl.handle.net/10092/2739.
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The ongoing transition of former communist countries from planned to market economies has been one of the most important economic phenomena in the last few decades. Among these, China is one of the largest and fastest growing emerging economies in the world since the reforms initiated in the late 1980s. China’s economic growth has been phenomenal.
Therefore, understanding China’s energy economy is crucial in the new millennium for politicians, businessmen and energy economists. In particular, China’s energy policy directions will bring about both challenges and opportunities to the world in terms of an increasing share of primary energy consumption and investment in the energy industry. However, after surveying the literature, it is surprising to find that a few major areas of China’s energy economics are missing and the views on China’s energy economics are already out dated. Therefore, given the size and growth of its economy and the effect of its energy consumption on global energy markets, reviewing China’s energy situation and filling the missing literatures are essential for those who are interested in and concerned about China’s economic development in the new millennium.
This study was motivated after conducting a survey of the literature on the study of China’s energy economy and reviewing China’s energy situation in the new millennium. The goal of the research is focused on providing readers the most important and the newest information on China’s energy economy. The study consists of three introductory sections and three core sections. The former includes a survey of literature, China’s energy situation in the new millennium, institutional evolution and changing energy prices. The latter includes tests for the emergence of an energy market in China, factor substitution and demand for energy, and technological change and the determinants of energy intensity.
The main findings are as follows. China’s energy economy is still underdeveloped. It is crucial to review China’s energy situation in the new millennium. Energy, industrial deregulation and price reforms have been fast in China since the early 1990s. Empirical investigations have found evidence for the emergence of an energy market economy in China. The estimates demonstrate that there appears to be significant substitution possibilities between energy and labor when compared with international findings. Significant effects of substitution mainly come from the adoption of labor-intensive technology. Coal and electricity are significantly substitutable, while the demand for energy is elastic, in general. Finally, decomposing energy intensity shows that the budget constraint (a kind of price effect) reduces energy intensity while technological change increases energy intensity.
These findings bring us to the following major implications. Firstly, it is important to understand the potential effect of new energy regulation and pricing mechanism on the future directions of China’s energy economy, which suggests that former predictions of China’s energy demand may have to be significantly discounted, and the potential effect on the global energy markets and emissions may need to be re-evaluated. Secondly, significant substitution between energy and labor is potentially good news as China possesses some of the most abundant labor sources in the world. However, because capital more easily substitutes for energy than labor, more policy incentives are needed for labor to substitute for energy. Thirdly, significant substitution between coal-electricity suggests that the effects of environmental taxes, however, may be smaller than expected due to the fact that most primary energy coming from coal. Also any shift from coal to electricity implies more investment in transmission lines rather than railways. Fourthly, energy constraints on energy supply may only slightly impede economic growth in China because the elasticity of substitution between energy and other factors is quite large compared to internationally. Fifthly, while many factors are responsible for the inelasticity of demand for energy, rising income may be one of the most important given the high levels of energy prices. Increasing energy prices may be unable to constrain energy consumption at present. Thus other energy policies need to be considered to encourage or depress certain types of energy consumption. Finally, reducing exports of energy-intensive commodities, reducing the high-level energy-using sectors, lowering capital investment and constraining imports of second-hand and obsolete equipment, would all help reduce growth in energy intensity. Politically, however, this may be at an unacceptable cost to economic growth.
Although this study has conducted a series of investigations into the institutional changes and consumption behavior of China’s energy economy, continuous updating required as more data is continually added in a highly dynamic and changing environment.
JEL Classifications: D24, O33, Q41.
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Sjödin, Emma. "The Price of Synchrony:Evaluating Transient Power Losses inRenewable Energy IntegratedPower Networks." Thesis, KTH, Reglerteknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-133579.
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This thesis investigates the resistive losses incurred in returning a power network to a synchronous state following a transient stability event, or in maintaining this state in the presence of persistent stochastic disturbances. We quantify these transient power losses, the so-called “Price of Synchrony”, using the squared H2 norm of a linear system of generator and load dynamics subject to distributed disturbances. We first consider a large network of synchronous generators and use the classical machine model to form a system with coupled second order swing equations. We then extend this model to explicitly include dynamics of loads and asynchronous generators, which represent solar and wind power plants. These elements are modeled as frequency-dependent power injections (extractions), and the resulting system is one of coupled firstand second order dynamics. In both cases, the disturbance inputs represent power fluctuations due to transient stability events or the inherent variability of loads and intermittent energy sources. The network structure is captured through a weighted graph Laplacian of the network admittance. In order to simplify the analysis for both models, we use the concept of grounded graph Laplacians to obtain an asymptotically stable reduced system. We then evaluate the transient losses in the reduced system and show that this system’s H2 norm is in fact equivalent to the H2 norm of the original system. Furthermore we show that although the transient behaviours of the first order, second order or mixed dynamical systems are in general fundamentally different, for same-sized networks they may all have the same H2 norm if the damping coefficients are uniform. The H2 norms for both system models are shown to be a function of transmission line and generator properties and to scale with the network size. These transient losses do not, however, depend on the network connectivity. This is in contrast to related power system stability notions that predict better synchronous stability properties for highly connected networks. The equivalence of the norms for different order systems indicate that renewable energy sources will not increase transient power losses if their controllers can be adjusted to match the dampings of existing synchronous generators. However, since the losses scale linearly with the number of generators, our results also demonstrate that increased amounts of distributed generation in low-voltage grids will lead to larger transient losses, and that this effect cannot be alleviated by increasing the network connectivity.
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Sarkeyeva, Rosanna. "Kyrgyz energy policy in transition : price reforms and residential electricity demand." Thesis, University of Reading, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.487238.
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In the transition from a centrally planned system to a market economy many former socialist economies launched comprehensive reforms that involved liberalising energy markets. The extent to which energy utilities have been liheralised differs from country to country; in the case of Kyrgyzstan there are still many indications of market distortions due to the persistence of the soft budget constraints. In this context this study investigates possible effects of electricity price reforms on overall welfare, which includes the analysis of electricity demand elasticities, substitutability of electricity, ability and willingness to pay a higher price. The empirical study is based on a representative sample of Kyrgyz households' energy consumption in 1999, which consists of 2993 observations. Results show: first, that households' electricity demand is inelastic with respect to own price changes (-0.59) and to changes in income (0.21). The illustrated net welfare gains from a gradual decrease in electricity subsidy are significant (up to 2% of GDP). Second, there are no strong substitutes for electricity, whereas electricity is the flrst-best substitute of the other energy resources available to ; households. Third, two-thirds of households have a capacity to pay increased electricity prices, while the remaining one-third needs a targeted assistance in order to be able to pay. The most influential factors of the willingness to pay are income, quality ofelectricity supply and payment arrears. Results of this study suggest that efficiency distortions in the Kyrgyz energy market can be alleviated by abolishing subsidies and hardening the budget constraint. Equity concerns are best tackled by replacing subsidies and discounts with more targeted tools, such as direct cash transfers. Its findings are relevant for the current electric,ty sector reform debate because they suggest ample scope for improving the efficiency of electricity utilisation without hurting the poorest part ofthe population.
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SOUZA, RODRIGO LAJE DE. "STRUCTURAL MODELLING APPLIED TO FORECAST THE SPOT PRICE OF ELECTRICAL ENERGY." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2003. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=3722@1.
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COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIORNesta tese, apresentam-se estratégias de modelagem envolvendo modelos estruturais para a previsão do preço spot de energia elétrica do subsistema do Sudeste-Brasil. Foi utilizada a modelagem proposta por Harvey (1989), que extrai componentes não observáveis da série. Foram elaborados três modelos. No primeiro, utilizou-se somente o histórico da série. No segundo, inseriu-se uma variável de intervenção para o racionamento de energia ocorrido no Brasil no período de junho de 2001 a fevereiro de 2002. Por último, acrescentaram-se duas variáveis explicativas.
In this thesis, modelling strategies are presented involving structural models to forecast the spot price of electric energy of Brazil. It had been used the modelling proposal of Harvey (1989) that extracts non-observable components of the series. Three models had been elaborated. In the first one, was adjusted only with the historical of the series. In the second, an intervention variable for the rationing occurred in Brazil in the period of June of 2001 till February of 2002 was inserted. Finally, in the last one, two explanatory variables were introduced.
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Hermanson, Doug Matthew. "The Impact of Biofuel Production on Energy and Agricultural Price Relationships." The Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=osu1213203572.
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Saeidpour, Parizy Ehsan. "Electrical Energy Retail Price Optimization for an Interconnected/Islanded Power Grid." University of Akron / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=akron1512463830323059.
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Nguyen, Thi Hang. "Techniques to improve forecasting models : applications to energy demand and price." Thesis, Aston University, 2010. http://publications.aston.ac.uk/15780/.
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This thesis is a study of three techniques to improve performance of some standard fore-casting models, application to the energy demand and prices. We focus on forecasting demand and price one-day ahead. First, the wavelet transform was used as a pre-processing procedure with two approaches: multicomponent-forecasts and direct-forecasts. We have empirically compared these approaches and found that the former consistently outperformed the latter. Second, adaptive models were introduced to continuously update model parameters in the testing period by combining ?lters with standard forecasting methods. Among these adaptive models, the adaptive LR-GARCH model was proposed for the fi?rst time in the thesis. Third, with regard to noise distributions of the dependent variables in the forecasting models, we used either Gaussian or Student-t distributions. This thesis proposed a novel algorithm to infer parameters of Student-t noise models. The method is an extension of earlier work for models that are linear in parameters to the non-linear multilayer perceptron. Therefore, the proposed method broadens the range of models that can use a Student-t noise distribution. Because these techniques cannot stand alone, they must be combined with prediction models to improve their performance. We combined these techniques with some standard forecasting models: multilayer perceptron, radial basis functions, linear regression, and linear regression with GARCH. These techniques and forecasting models were applied to two datasets from the UK energy markets: daily electricity demand (which is stationary) and gas forward prices (non-stationary). The results showed that these techniques provided good improvement to prediction performance.
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Bahilo, Rodríguez Edgar. "Swedish and Spanish electricity market : Comparison, improvements, price forecasting and a global future perspective." Thesis, Högskolan i Gävle, Energisystem, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-24512.
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This report aims to make a comparison between the Swedish and Spanish electricity market, the design of new improvements that could achieve a better operation for both markets as well as the price forecasting for both spot markets. These enhancements are oriented to decrease electricity prices, energy use and the system CO2 emissions. Also, the main organizations of the market and their roles has been characterized, clarifying the functions of the Market Operator and the System Operator. In addition, the different markets, the trading products and the price formation have been explained and the picture of the market structure has been achieved with enough depth. Moreover, some of the most used methods in Time Series Analysis has been enumerated to understand which techniques are needed for forecast the electricity prices and the methodology used (Box-Jenkins Method) has been explained in detail. Later, all these methods have been implemented in an own code developed in Python 3.6 (TSAFTools .py) with the help of different statistics libraries mentioned during the method chapter. On the other hand, the description of the market situation has been carried out for both countries. Power installed capacity, electricity generation, average prices, main renewable technologies and policies to increase the renewable energy share has been analysed and corresponding described. Then, to estimate the market’s future spot electricity prices, ARIMA models have been selected to analyse the evolution of the day-ahead price using the TSAFTools.py. The final models show a proper performance in the two markets, especially in the Nordpool, achieving an RMSE: 37.68 and MAPE: 7.75 for the year in 2017 in Nordpool and a RMSE: 270.08 and MAPE: 20.24 in OMIE for 2017. Nordpool spot prices from 2015 to 2016 has been analysed too but obtaining a result not as good as the year 2017 with an RMSE: 49.01 and MAPE: 21.42. After this analysis, the strengths and weaknesses of both markets are presented and the main problems of the Spanish electricity system (power overcapacity, fuel dependency, non-cost-efficient renewable energies policies, lack of interconnexion capacity etc.) and the Swedish electricity system (dependency for nuclear power, uncertainty for solar electricity Generation) are presented. Finally, due to the quick development of the energy sector in the last years and the concern of the European Committee to reach a new design for the electricity market, different kinds of recommendations for the future have been considered.
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Coulon, Michael. "Modelling price dynamics through fundamental relationships in electricity and other energy markets." Thesis, University of Oxford, 2009. http://ora.ox.ac.uk/objects/uuid:ddc11641-920f-461f-85cd-a9e6351d9104.
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Energy markets feature a wide range of unusual price behaviour along with a complicated dependence structure between electricity, natural gas, coal and carbon, as well as other variables. We approach this broad modelling challenge by firstly developing a structural framework to modelling spot electricity prices, through an analysis of the underlying supply and demand factors which drive power prices, and the relationship between them. We propose a stochastic model for fuel prices, power demand and generation capacity availability, as well as a parametric form for the bid stack function which maps these price drivers to the spot electricity price. Based on the intuition of cost-related bids from generators, the model describes mathematically how different fuel prices drive different portions of the bid stack (i.e., the merit order) and hence influence power prices at varying levels of demand. Using actual bid data, we find high correlations between the movements of bids and the corresponding fuel prices (coal and gas). We fit the model to the PJM and New England markets in the US, and assess the performance of the model, in terms of capturing key properties of simulated price trajectories, as well as comparing the model’s forward prices with observed data. We then discuss various mathematical techniques (explicit solutions, approximations, simulations and other numerical techniques) for calibrating to observed fuel and electricity forward curves, as well as for pricing of various single and multi-commodity options. The model reveals that natural gas prices are historically the primary driver of power prices over long horizons in both markets, with shorter term dynamics driven also by fluctuations in demand and reserve margin. However, the framework developed in this thesis is very flexible and able to adapt to different markets or changing conditions, as well as capturing automatically the possibility of changes in the merit order of fuels. In particular, it allows us to begin to understand price movements in the recently-formed carbon emissions markets, which add a new level of complexity to energy price modelling. Thus, the bid stack model can be viewed as more than just an original and elegant new approach to spot electricity prices, but also a convenient and intuitive tool for understanding risks and pricing contracts in the global energy markets, an important, rapidly-growing and fascinating area of research.
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Yashkina, O. I., and I. A. Pedko. "Models of inventory management for industrial enterprises under energy resources price increase." Thesis, Sumy State University, 2016. http://essuir.sumdu.edu.ua/handle/123456789/49560.
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The paper provides an inventory management model for industrial enterprises under conditions of expected increase of energy prices. Different approaches to the formation of reserves will allow industrial enterprises to be aware of the risks of energy prices increase and, depending on the choice of a particular strategy of stockpiling of raw materials or components, to calculate the size and timing of deliveries while minimizing costs for shipping and storing.У статті запропоновано моделі управління запасами промислових підприємств в умовах очікуваного підвищення цін на енергоносії. Різні підходи до формування запасів дозволять промисловим підприємствам враховувати ризики щодо здорожчання енергоносіїв та за вибором певної стратегії накопичення запасів сировини або складових розраховувати розміри та терміни поставок за умовою мінімізації витрат на доставку та зберігання.
В статье предложены модели управления запасами для промышленных предприятий в условиях ожидаемого повышения цен на энергоносители. Различные подходы к формированию запасов позволят промышленным предприятиям учитывать риски подорожания энергоносителей и в зависимости от выбора определенной стратегии накопления запасов сырья или комплектующих рассчитывать размеры и сроки поставок при условии минимизации затрат на доставку и хранение.
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Landelius, Erik, and Magnus Åström. "DISTRICT HEAT PRICE MODEL ANALYSIS : A risk assesment of Mälarenergi's new district heat price model." Thesis, Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-44097.
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Energy efficiency measures in buildings and alternative heating methods have led to a decreased demand for district heating (DH). Furthermore, due to a recent increase in extreme weather events, it is harder for DH providers to maintain a steady production leading to increased costs. These issues have led DH companies to change their price models. This thesis investigated such a price model change, made by Mälarenergi (ME) on the 1st of August 2018. The aim was to compare the old price model (PM1) with the new price model (PM2) by investigating the choice of base and peak loads a customer can make for the upcoming year, and/or if they should let ME choose for them. A prediction method, based on predicting the hourly DH demand, was chosen after a literature study and several method comparisons were made from using weather parameters as independent variables. Consumption data from Mälarenergi for nine customers of different sizes were gathered, and eight weather parameters from 2014 to 2018 were implemented to build up the prediction model. The method comparison results from Unscrambler showed that multilinear regression was the most accurate statistical modelling method, which was later used for all predictions. These predictions from Unscrambler were then used in MATLAB to estimate the total annual cost for each customer and outcome. For PM1, the results showed that the flexible cost for the nine customers stands for 76 to 85 % of the total cost, with the remaining cost as fixed fees. For PM2, the flexible cost for the nine customers stands for 46 to 61 % of the total cost, with the remaining as fixed cost. Regarding the total cost, PM2 is on average 7.5 % cheaper than PM1 for smaller customer, 8.6 % cheaper for medium customers and 15.9 % cheaper for larger customers. By finding the lowest cost case for each customer their optimal base and peaks loads were found and with the use of a statistical inference method (Bootstrapping) a 95 % confidence interval for the base load and the total yearly cost with could be established. The conclusion regarding choices is that the customer should always choose their own base load within the recommended confidence interval, with ME’s choice seen as a recommendation. Moreover, ME should always make the peak load choice because they are willing to pay for an excess fee that the customer themselves must pay otherwise.
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Becker, James Bradley. "Energy Substitution in Agriculture: A Translog Cost Analysis of the U.S. Agricultural Sector, 1992-2007." Youngstown State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1288661653.
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Branquinho, Inês Pereira Silva. "Consequências da entrada de novos comercializadores no mercado da energia eléctrica." Master's thesis, Instituto Superior de Economia e Gestão, 2012. http://hdl.handle.net/10400.5/5421.
Full textAbstract:
Mestrado em Gestão e Estratégia IndustrialA presente dissertação tem por objectivo analisar as consequências da entrada de novos comercializadores no mercado da energia eléctrica no contexto do mercado europeu e português. Para ser possível detectar essas consequências analisá-las e, simultaneamente, não ultrapassar o limite exigido para a dissertação procedeu-se à verificação de quatro hipóteses e, por sua vez, ao seu desenvolvimento. A primeira hipótese testada foi a diminuição da concentração do mercado pois, apesar de ambos os mercados possuírem índices de concentração muito elevados, a sua tendência no contexto europeu não demonstra sinais visíveis de diminuição e no caso português são apenas verificados alguns indícios dessa tendência. No que se refere à verificação de perda de direitos dos consumidores, a hipótese testada verificou-se positiva, tendo sido tomadas medidas legislativas para a definição concreta dos direitos e a disponibilização dessa informação a toda a população. A terceira análise recaiu sobre o aumento da capacidade de intervenção das entidades reguladoras, verificando-se um aumento geral das suas competências principalmente na área do sancionamento de possíveis infracções. Por último, não foi possível realizar o teste da hipótese da diminuição dos preços praticados aos consumidores finais pela complexidade da construção de uma metodologia capaz de o fazer com exactidão. Conclui-se que a liberalização do mercado da energia eléctrica implicou diversas alterações, sendo algumas em áreas que não se pensavam inicialmente ser necessárias.
The present dissertation aims to analyze the consequences of the new traders’ entry in the electric energy market in the context of the European and Portuguese markets. To be able to detect these consequences, analyze them and, simultaneously, do not exceed the threshold required for the dissertation, four hypotheses were processed, checked and developed. The first hypothesis tested was the decrease in market concentration, because although both markets may have very high levels of concentration in its European context, trend shows no visible signs of decline and, in the Portuguese case, some evidence of this trend are only possible. With regard to the verification of loss of consumer rights, the hypothesis tested was found positive because of the legislative measures that have been taken to the real definition of the rights and the provision of such information to the entire population. The third analysis rested on increasing the power held by regulators which originated an overall increase of its powers, mainly in sanctioning offenses to be. Finally, it was not possible to do the test of the hypothesis of reduced prices to consumers because of the complexity of finding a methodology able to do so accurately. In conclusion - the liberalization of the electricity market implied several changes, and in some areas not initially thought to be necessary.
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Le, Minxian. "Prediction of large price changes in the energy market using extreme value statistics." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for matematiske fag, 2011. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-14146.
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In this project we have first and foremost been comparing the performance of the ACER method with the POT method in the prediction of extreme values from the heavy tailed distributions; especially for data from the energy markets. The energy market is an exciting dynamic market where small singularities can make large differences in the price. Therefore it is very important and challenging to analyse and make predictions in this market. We have also analysed a dataset which is not from the energy market, to compare and see the main differences between the two markets. We have also taken in consideration of removing the return value for the dates of maturity to see whether this will have any influence on the results.The main concept of the POT method is to find a threshold, $u$, and let the excesses be distributed by the Generalised Pareto Distribution. Whilst for the ACER method, we assume a specific shape of the tail, which in this project was of the kind Fréchet. We have done this analysis for five different data sets where two of them have been considered with and without their expiration dates. We have also filtrated the data sets with an AR-GARCH filter, and then used the POT and ACER on the residuals from the process. We have found out that both methods are not greatly influenced by the filtration, but we see the tendency of the POT method predicting a heavier tail than the ACER method. Further on, we can say that there are no significant large effects of removing the return values for the dates of maturity. Lastly, the data sets from the energy market prove themselves much more heavy tailed than for the data set from Norsk Hydro.
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Mao, Qi. "The elasticity of substitution for US energy price changes between 1947 and 2010." Thesis, Kingston University, 2017. http://eprints.kingston.ac.uk/41957/.
Full textAbstract:
Since energy price changes have been studies by much literature, this thesis tries to discuss it through the elasticity of substitution. More importantly, this thesis finds that the substitution effect itself cannot completely interpret the phenomenon of energy price changes. This is based on the results of the estimation of the AES, the MES and the CES, as well as some previous studies' results of negative substitution elasticities. This thesis adopts VECM, ADL and panel data as methodologies. Different data is also colelcted and analyzed. Most of the AES estimates are negative and the CES estimation shows many negative elasticities as well. The estimated elasticities from the MES and the Panel dta CES are positive. Out positive elasticities from the MES may are consistent with the previous literature that finds the MES estimation method is better than AES. The negative elasticities of susbtitution as the substitution effects are usually followed by income effects. Based on literature view, if income effects are involved in the energy price changes between energy exporting and importing countries, it may lead to new policy making and application. In addition, there are some other findings: (1) an application approach is used to test the cointegration when variables include I(0), I(1) and share variables. This approach is different from Pesaran, Shin and Smith's (2001) ARDL method which is involved I(0) and I(1) variables. However, in the application, the data being used covers share variables. Share variables sum to unity so they have collinearity. New procedures (ADL) are adopted to solve the problem of collinearity in econometric application. This then allows to analyze I(0), I(1) and share variables together in the model. This is one of our contributions in econometric VECM application. (2) By the literature review in Chapter 4, it's found that the elasticities of substitution vary from economies. Since some economies do not share free flow of capital, labor or energy, their substitution elasticities cannot be estimated as a whole. The different sustitution elasticities in each country show that, when selecting the data, we may refer to a region or a country with a common free flow market for capital, labor and energy. (3) Different data is used in the application. Previous literature uses the data of the UK or other countries to analyze the Allen's elasticity of substitution (AES), or the US data in the period different from that in this study, or uses the familiar data but in technology forecasting. Importantly, the empirical analysis uses the US data to test the Allen's elasticity of substitution (AES) and the constant elasticity of substitution (CES), in order to explore negative estimates of the substitution elasticity.
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DAVID, PEDRO AMERICO MORETZ-SOHN. "SPOT PRICE REGULATION, INVESTMENT ATTRACTION AND RISK MANAGEMENT IN THE BRAZILIAN ELECTRICAL ENERGY MARKET." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2004. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=5216@1.
Full textAbstract:
FURNAS CENTRAIS ELÉTRICAS S.AO mercado brasileiro de energia elétrica ainda não encontrou um modelo de mercado e de formação de preço que garanta a expansão auto-sustentada da oferta. Investigando em detalhe o modelo atual de despacho da geração e formação do preço, demonstramos a sua pouca eficácia na atração de investimentos, e identificamos a causa dessa falha como sendo a miopia do modelo de despacho, uma vez os estados críticos do sistema só aprecem de forma significativa quando o sistema já estiver degradado. São estudados três modelos alternativos que modificam a função-objetivo ou a regra de formação do preço, ajustados de modo a viabilizar e tornar suficientemente atrativos os investimentos na expansão da oferta. Finalmente, estes modelos são então comparados entre si e com o modelo atual, quanto ao valor para o investidor e quanto ao custo para o sistema e para o consumidor. Um mercado é dito completo se permite aos agentes alocar livremente seus recursos e demandas quando estiverem disponíveis e/ou forem necessários e permite que os agentes condicionem estes recursos / demandas ao estado (preço) do mercado. Estas funcionalidades são implementadas através dos derivativos financeiros, negociados no mercado futuro. Neste trabalho fazemos uma análise conceitual do mercado futuro de energia elétrica, indicando a diferença em relação ao de outras commodities e apresentando um modelo da oferta e demanda por contratos futuros de energia elétrica.
The Brazilian Market of Electrical Energy has not yet found a stable market and price model that ensues the feasibility and makes attractive a self-sustained investment for the expansion of electrical energy generation. Researching the current generation dispatch and spot price model, we show that it is ineffective to attract investments because the model is myopic, since the range of critical system states that is foreseen at the current state is not significant until the system is already too degraded. Stemming from this conclusion, we develop three alternative models, modifying the dispatch model objective and the price formation rule. These alternative models are tuned to make the investments in generation expansion feasible and attractive. The models are compared regarding their value to the investor and the cost to the system and to the consumer. A complete market allows the economic agents to freely allocate their resources and requirements whenever they are available and/or required. A complete market also allows conditional settlement, i.e., to condition the resource availability and/or requirement to a particular market state (price). These features are realized by financial derivatives, in the, so called, futures market. We present a conceptual analysis of the electrical energy s future market, pointing the differences to other commodities future markets that are due to economical unfeasibility of storing electricity. We also present an equilibrium model for the forward electrical energy contracts.
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Levy, Tal Z. (Tal Ze'ev). "Unexpected consequences of demand response : implications for energy and capacity price level and volatility." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/90054.
Full textAbstract:
Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2014.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 90-94).
Historically, electricity consumption has been largely insensitive to short term spot market conditions, requiring the equating of supply and demand to occur almost exclusively through changes in production. Large scale entry of demand response, however, is rapidly changing this paradigm in the electricity market located in the mid-Atlantic region of the US, called PJM. Greater demand side participation in electricity markets is often considered a low cost alternative to generation and an important step towards decreasing the price volatility driven by inelastic demand. Recent experience in PJM, however, indicates that demand response in the form of a peaking product has the potential to increase energy price level and volatility. Currently, emergency demand response comprises the vast majority of demand side participation in PJM. This is a peaking product dispatched infrequently and only during periods of scarcity when thermal capacity is exhausted. While emergency demand response serves as a cheaper form of peaking resource than gas turbines, it has recently contributed to increases in energy price volatility by setting price at the $1,800/MWh price cap, substantially higher than the marginal cost of most thermal generation. Additionally, the entry of demand response into the PJM capacity market is one of primary drivers for capacity prices declining by over fifty percent. This study investigates the large penetration of emergency demand response in PJM and the implications for the balance between energy and capacity prices and energy price volatility. A novel model is developed that dynamically simulates generation entry and exit over a long term horizon based on endogenously determined energy and capacity prices. The study finds that, while demand response leads to slight reductions in total generation cost, it shifts the bulk of capacity market revenues into the energy market and also vastly increases energy price volatility. This transition towards an energy only market will send more accurate price signals to consumers as costs are moved out of the crudely assessed capacity charge and into the dynamic energy price. However, the greater volatility will also increase the risk faced by many market participants. The new market paradigm created by demand response will require regulators to balance the importance of sending accurate price signals to consumers against creating market conditions that decrease risk and foster investment.
by Tal Z. Levy.
S.M. in Technology and Policy
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Badal, Lee, and Sebastian Franzén. "A Comparative Analysis of RNN and SVM : Electricity Price Forecasting in Energy Management Systems." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-259745.
Full textAbstract:
A trend in increasing electricity consumption and technological innovation has resulted in automated energy management systems. Forecasting movement of the electricity price with machine learning plays a role in the sustainability of these systems. The aim of the report is to compare two machine learning methods, namely Recurrent Neural Network (RNN) with LSTM, and Support Vector Machine (SVM). The metric to evaluate is percentage in prediction accuracy, additionally statistical analysis is applied for further evaluation. The models are built and optimized on a single historic dataset from an Australian electricity market where the major influencing attributes are price, demand and time. The training and test set are split 80/20 whereas the training is done in 10 folds for cross validation. Results of the experiment show that the SVM-model had a slightly higher accuracy and a lower standard error of the mean. Differences were seen in sensitivity and specificity when applied to a confusion matrix. The conclusion made was that in this specific case, SVM outperformed RNN in prediction accuracy, however, there is room for improvement of both implementations of these methods which could lead to a different result. In regard to specificity and sensitivity the choice of an SVM or RNN would be highly dependent on the implementation of real-world application.En trend i ökad elförbrukning och teknisk innovation har resulterat i automatiserade energiledningssystem. Prognos i förändringen av elpriser med maskininlärning spelar en roll för hållbarheten av dessa system. Syftet med denna rapport är att jämföra de två maskininlärningsmetoderna, Reccurent Neural Network (RNN) med LSTM och Support Vector Machine (SVM). De värden som utvärderas är procentenheter i förutsägbarhetsnoggrannhet där statistisk analys tillämpas för ytterligare utvärdering. Modellerna är byggda på historisk data från en australisk elmarknad där de väsentligaste egenskaperna är pris, efterfrågan och tid. Tränings- och testuppsättningen delas 80/20 och träningen görs med 10-delad korsvalidering. Resultaten från analysen visar att SVM-metoden hade en något högre noggrannhet och lägre standardfel. Från en diagnostisk beslutsmatris beräknades sensitivitet och specificitet, i dessa värden upptäcktes skillnader. Slutsatsen i vårt fall var att SVM är mer noggrann än RNN. Vi anser att utrymme för förbättring av båda modellerna finns, vilket kan leda till ett annat resultat. När det gäller sensitivitet och specificitet skulle valet av RNN eller SVM vara starkt beroende på tillämpningen av en verklig applikation.
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Amin, Sakib Bin. "The macroeconomics of energy price shocks and electricity market reforms : the case of Bangladesh." Thesis, Durham University, 2015. http://etheses.dur.ac.uk/11241/.
Full textAbstract:
Electricity is a vital instrument for economic growth and human development. The measure of growth in developing countries like Bangladesh is synonymous with the level of electricity use. Energy (oil) price shocks are often identified as a source of macroeconomic fluctuations since they affect economic development as well as business cycle. Accordingly, it has been argued that electricity market reforms are a possible tool to improve economic performance, efficiency, welfare and overall economic development. The Bangladesh economy is vulnerable to energy (oil) price shocks and the government has adopted different electricity reform policies in the past few years. However, there is a real gap in the energy literature with regard to the qualitative and quantitative analysis of the consequences of energy (oil) price shocks and electricity market reforms towards the Bangladesh economy. This thesis is divided into two main parts. The first part contains two chapters titled, “A Survey of Literature” and “Energy Scenario in Bangladesh” which extensively review the related literature and underline the research gaps that this thesis intends to address. The second part of this thesis includes three novel papers in the literature on energy (oil) prices, electricity market reforms and the macro economy, all applied to the case of Bangladesh: “Energy Price Shocks and Real Business Cycle”, “A DSGE Analysis of Oil Price Shocks” and “A DSGE Analysis of the Welfare Effects of Alternative Electricity Pricing Schemes”. The following research questions are addressed: 1. How important aggregate energy price shocks are to explain business cycle fluctuations for the Bangladesh economy? 2. How would oil price shocks affect the macro economy of a small, oil importing, developing country like Bangladesh? 3. How would electricity market reforms affect the Bangladesh Economy? To answer these questions we develop a Real Business Cycle (RBC) model and a Dynamic Stochastic General Equilibrium (DSGE) model for Bangladesh, the latter including a detailed model of the energy (electricity) sector which has not been attempted before in the literature. We conclude that the RBC model does a reasonable job in capturing the qualitative changes of selected endogenous variables considering the energy and productivity shocks. We find that oil price shocks have a negative welfare effect on consumers and GDP. However, industry expands to produce more exportable goods as higher oil price makes the country worse off with regard to Terms of Trade (TOT). Lower wage and capital interest rate allow industry to employ more labour and capital and increase production. Our results also reveal that electricity reform policies (restructuring of prices and subsidy arrangements) increase household welfare and GDP in Bangladesh. Given our results, it is advisable that policymakers carefully assess the overall welfare effect of oil price shocks and electricity market reforms and when appropriate take some measures to redistribute welfare across sectors. The heterogeneity nature of the households would be more appropriate for policy analysis and the analysis of these redistribution policies is left for future research. As some other developing countries face the same issues as Bangladesh, the novel framework and results of this thesis are of relevance not only for Bangladesh but also for developing countries in general.
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Mathaba, Tebello Ntsiki Don. "Energy and cost optimal scheduling of belt conveyor systems." Thesis, University of Pretoria, 2016. http://hdl.handle.net/2263/61311.
Full textAbstract:
This work deals with the energy management of belt conveyor systems (BCS) under various demandside
management (DSM) programmes. The primary objective of this work is to model the energy
consumption and energy related cost of operating troughed belt conveyor systems under different
electricity pricing tariffs. This research is motivated by the increasing need for energy efficiency and
energy cost reduction in the operation of BCS. This is as a result of technological improvements in
BCS technology leading to increasingly longer belts being commissioned and as a result of rapidly
rising electricity costs.
An energy model derived from established industry standards is proposed for long conveyors. The
newly proposed model uses a first-order partial differential equation (PDE) in order to capture the
state of material on the belt. This new model describes the conveyor's power requirement using
an equation with two parameters. A system identification set-up involving a recursive parameter
estimating algorithm is simulated for measurements with varying degrees of noise. The results show
that the proposed model estimates conveyor power and material delivered by long conveyors more
accurately than the existing steady-state models.
Downhill conveyors (DHCs) are important potential energy sources that can be tapped to improve the
overall energy efficiency of BCSs. A generic optimisation model that is able to optimally schedule three
configurations of BCS with DHC is proposed. The economic assessment of implementing dynamic
braking and regenerative drives technology on downhill conveyors is undertaken with the help of the
model. The assessment shows that combining regenerative drives and optimal operation of BCS with
DHC generates energy savings that give attractive payback period of less than 5 years.
A chance-constrained model predictive control (cc-MPC) algorithm is proposed for scheduling belt
conveyor systems with uncertain material demand on the output storage. The chance-constraints are
based on the modelling of material demand by a sum of known mean demand and, zero-mean and
normally distributed random component. The cc-MPC algorithm is shown to produce schedules that
give a smaller number and smaller magnitude of storage limit violations compared to normal MPC and
chance-constrained optimal control algorithms. An equation that gives the amount of effective storage
required to meet storage constraints for a given value of standard deviation is established.
The optimal scheduling of BCS under the real-time pricing (RTP) tariff is considered. This study
develops a methodology for establishing the economic value of price forecasting schemes for loads
capable of load-shifting. This methodology is used to show that the economic benefit obtained from
a forecast is highly dependent on the volatility of the electricity prices being predicted and not their
mean value. The methodology is also used to illustrate why the commonly used indices mean absolute
percentage error (MAPE) and root mean square error (RMSE) are poor indicators of economic benefit.
The proposed index using Kendall's rank correlation between the actual and predicted prices is shown
to be a good indicator of economic benefit, performing far better than RSME and MAPE.Thesis (PhD)--University of Pretoria, 2016.
Electrical, Electronic and Computer Engineering
PhD
Unrestricted
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Park, Haesun. "Essays on price dynamics, discovery, and dynamic threshold effects among energy spot markets in North America." Texas A&M University, 2005. http://hdl.handle.net/1969.1/2668.
Full textAbstract:
Given the role electricity and natural gas sectors play in the North American economy,
an understanding of how markets for these commodities interact is important. This
dissertation independently characterizes the price dynamics of major electricity and
natural gas spot markets in North America by combining directed acyclic graphs with
time series analyses. Furthermore, the dissertation explores a generalization of price
difference bands associated with the law of one price.
Interdependencies among 11 major electricity spot markets are examined in
Chapter II using a vector autoregression model. Results suggest that the relationships
between the markets vary by time. Western markets are separated from the eastern
markets and the Electricity Reliability Council of Texas. At longer time horizons these
separations disappear. Palo Verde is the important spot market in the west for price
discovery. Southwest Power Pool is the dominant market in Eastern Interconnected
System for price discovery.
Interdependencies among eight major natural gas spot markets are investigated
using a vector error correction model and the Greedy Equivalence Search Algorithm in
Chapter III. Findings suggest that the eight price series are tied together through sixlong-run cointegration relationships, supporting the argument that the natural gas market
has developed into a single integrated market in North America since deregulation.
Results indicate that price discovery tends to occur in the excess consuming regions and
move to the excess producing regions. Across North America, the U.S. Midwest region,
represented by the Chicago spot market, is the most important for price discovery. The
Ellisburg-Leidy Hub in Pennsylvania and Malin Hub in Oregon are important for eastern
and western markets.
In Chapter IV, a threshold vector error correction model is applied to the natural
gas markets to examine nonlinearities in adjustments to the law of one price. Results
show that there are nonlinear adjustments to the law of one price in seven pair-wise
markets. Four alternative cases for the law of one price are presented as a theoretical
background. A methodology is developed for finding a threshold cointegration model
that accounts for seasonality in the threshold levels. Results indicate that dynamic
threshold effects vary depending on geographical location and whether the markets are
excess producing or excess consuming markets.
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Johansson, Jim. "Utilizing Energy Storage Applied on Floating Wind Turbine Economics Using a Spot-Price Based Algorithm." Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-328934.
Full textAbstract:
In this paper, a new algorithm for utilizing energy storage is proposed and applied on floating wind turbine economics. The proposed algorithm’s decision making on storing energy or selling electricity onto the grid is based on the electricity price, which makes it unique and different from similar algorithms. From the literature review, it was concluded Ocean Renewable Energy Storage to be most suitable with the Spar-Type and Semi-Submersible floating wind turbine to which the paper is based upon. The objective of this paper is to find the suitable ratio of energy storage versus wind farm, find the product of increase in wholesale, and evaluate whether the proposed method makes the hybrid economically sound. The algorithm was applied on spot-price data from Denmark due to its large share of wind energy with wind data from off the coast of Morro Bay in California, USA. Additionally, a sensitivity analysis is applied to evaluate to energy storage cost impact as well as evaluate the algorithm by lowering the required energy storage size. Using the algorithm, the wind farm must account for nine days’ worth of energy production with a product of energy storage versus wind farm ratio of 1.42. The wholesale price increased with 11.9-21.5% for the four years studied, however, all financial results favored not utilizing energy storage. By the results derived from the sensitivity analysis, it was concluded that with future cost reductions, the algorithm will still favor no energy storage. However, by fine tuning the algorithm to reduce the need for storage, positive financial result might be achievable. The key to achieve a profitable result seems to rely on minimizing the need for energy storage, to which the proposed algorithm fail to achieve. Conclusively, spot-price decision-based energy storing is not economically sound.
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Flygare, Carl. "A market-based instrument for renewable energy : Modelling a dynamic price function for local areas." Thesis, Uppsala universitet, Institutionen för samhällsbyggnad och industriell teknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-403002.
Full textAbstract:
This thesis describes the current situation of the electrical grid on a general level and contemporary support policies for residents who feed renewably produced electricity into the grid within a Swedish context. It shows which issues currently exists and suggests a new way to value overproduced renewable electricity which is not self-consumed. This way is called a dynamic price function (DPF), and this thesis models, simulates and analyzes the DPF in order to create an economic incentive to support the balance of the electrical grid – one of its most important parameters. The suggested DPF could potentially work with any renewable source in any area, but the focus in this thesis has been on solar power-systems for households in local areas. While the currently support policies, which uses static models to value overproduced renewable electricity, have created important incentives for the initial penetration of solar power among local residents they do not scale well as the share of renewable production on a local level increase. This might cause negative impacts on the electrical grid. The thesis’ results show that by designing the DPF in certain ways it is possible to create an economic incentive for different behaviors. The most promising design incorporates three different incentives at the same time and they are: 1) to incentivize the initial penetration of solar power in local areas which do not have any production, 2) to incentivize a higher share of solar power, but not too high, and 3) to procure storage possibilities for overproduced electricity. These incentives do not only encourage a more even geographical distribution of solar power, but also allow for a higher share of solar power in the energy system without risking the balance of the grid.
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Flórez, García Luís Carlos. "Estudio del mecanizado asistido por vibración." Doctoral thesis, Universitat Politècnica de Catalunya, 2020. http://hdl.handle.net/10803/669565.
Full textAbstract:
The objective of this work is to analyze the influence of assisted vibration, VAM, in the process of turning steel. Initially, the surface finish generated in a lathe displacement is studied utilizing a geometric intersection software developed in Pascal programming language. The average and maximum roughness are calculated both linearly and superficially for different cutting parameters. The conclusion is synchronism between the vibration frequency and lathe spindle's speed reduce the roughness in the surface topography of the material. However, the values of the machining parameters are not easy to establish to generate synchronism on a conventional lathe.
Then, the VAM is analyzed by means of the finite element method, FEM, using explicit dynamics in the commercial software ANSYS. The 2D model is proposed and validated for conventional turning conditions; this model used as the basis for the study of assisted vibration simulating under different conditions of frequency and oscillation of the tool. It concluded that vibration assisted cutting reduces the value of the average force used in the cut.
Next, the energy efficiency of VAM turning is studied, using the specific cut-off energy, SCE, in the models assisted by vibration in EMF as an evaluation indicator. This indicator commonly used in the study of machining and therefore used as one of the validation variables of the conventional turning model. A comparison made through the specific relative cutting energy between machining using VAM and conventional cutting. It concluded that the machining by VAM is more energy-efficient than conventional machining, that it is even more if it vibrates in the direction of the cutting speed.
Then, the experimentation of the linear turning carried out using a new resonant tool that vibrates in the cutting direction; for this, the coil circuit configured to work in resonance with the tool. The coil vibrates the tool in its second natural mode and it oscillates in the direction of the cutting speed. Then proceed to carry out the tests on the lathe, the energy consumed by the lathe, the rate of material removed and the specific energy consumed is calculated. Finally, the results are analyzed and it concluded that the use of VAM reduces the specific energy consumed in the S235 alloy by an average of 13% and in the C45E 9%.El objetivo de este trabajo es analizar la influencia de la vibración asistida, VAM, en el proceso de torneado de acero. Inicialmente se estudia el acabado superficial generado en un cilindrado por torno, por medio de un software de intersección geométrica elaborado en lenguaje de programación Pascal. Se calcula la rugosidad media y máxima de manera tanto lineal como superficial para diferentes parámetros de corte. La conclusión es que el sincronismo entre la frecuencia de vibración y la velocidad del husillo del torno reducen la rugosidad en la topografía superficial del material. Sin embargo, los valores de los parámetros de mecanizado no son fáciles de establecer para generar el sincronismo en un torno convencional. Luego, se analiza el VAM por medio del método de elementos finitos, FEM, utilizando dinámica explicita en el software comercial ANSYS. Se plantea y valida el modelo 2D para las condiciones de torneado convencional, este modelo se utiliza como base para el estudio de vibración asistida simulando bajo diferentes condiciones de frecuencia y oscilación de la herramienta. Se concluye que el corte asistido por vibración reduce el valor de la fuerza media utilizada en el corte. A continuación, se estudia la eficiencia energética del torneado con VAM, utilizando como indicador de evaluación la energía especifica de corte, SCE, en los modelos asistidos por vibración en FEM. Este indicador es de uso común en el estudio de mecanizados y por tanto es utilizado como una de las variables de validación del modelo de torneado convencional. Se realiza una comparación por medio de la energía específica de corte relativa entre un mecanizado utilizando VAM y un corte convencional. Se concluye que el mecanizado por VAM es más eficiente energéticamente y que lo es aún más si vibra en la dirección de la velocidad de corte. Después, se realiza la experimentación del torneado lineal utilizando una nueva herramienta resonante que vibra en la dirección de corte, para ello, se configura el circuito de la bobina para trabajar en resonancia con la herramienta. La bobina hace vibrar la herramienta en su segundo modo natural y esta oscila en la dirección de la velocidad de corte. Luego, se realizan los ensayos en el torno, se mide la energía consumida por el torno, la tasa de material removido y se calcula la energía especifica consumida. Finalmente, se analizan los resultados y se concluye que el uso del VAM reduce la energía específica consumida en la aleación de acero S235 un promedio de 13% y en el C45E un 9%. Palabras clave: vibración asistida, mecanizado, energía específica de corte, energía específica consumida, método de elementos finitos, acabado superficial.
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Kapoor, Aanchal. "The Economic Impact of Oil Price Shocks on Emerging Markets." Scholarship @ Claremont, 2011. http://scholarship.claremont.edu/cmc_theses/139.
Full textAbstract:
Recent spikes in oil prices have thrown light on how economic activity in emerging markets may be impacted by oil price shocks. This paper conducts an empirical analysis of the effect of oil price shocks on emerging markets. It tests for the existence of an asymmetrical relationship between oil prices and economic activity using a model developed by James Hamilton. It also assesses the impact of structural shocks to the real price of oil on output as proposed by Lutz Kilian. While our models find no consistent pattern within emerging markets, they do suggest that oil price shocks have a greater significance in 2000-2009 than in the full sample of 1974-2009. We also find that emerging economies are impacted by changes in oil specific demand but unaffected by changes in aggregate demand for industrial commodities.
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Galindo, Luis Miguel, Joseluis Samaniego, Carbonell Jimy Ferrer, José Eduardo Alatorre, and Orlando Reyes. "Meta-Analysis of Income and Price Elasticities Energy Demand: Some Public Policy Implications for Latin America." Economía, 2015. http://repositorio.pucp.edu.pe/index/handle/123456789/117330.
Full textAbstract:
The aim of this paper is to analyze the variation in empirical estimates of the income and price elasticities of energy demand. The evidence presented, through a meta-analysis, allows identification of the weighted average of the income and price elasticities, shows that the estimates are very heterogeneous, that there is publication bias, and that factors such as region, energy sector, among others, affect its volatility. The evidence also indicates that income elasticity in Latin America is greater than in the OECD countries, and that the price elasticity of energy demand is lower in Latin America than in the OECD countries. Therefore, continued economic growth in Latin America will be accompanied by a growth in energy demand. Moreover, the establishment of a tax in Latin America, under the current elasticities, is less effective and will be insufficient to control the increase in energy consumption.El objetivo de este artículo es analizar la variación de las elasticidades ingreso y precio de la demanda de energía. La evidencia presentada, con un metaanálisis, permite identificar la media ponderada de estas elasticidades ingreso y precio, muestra que las estimaciones son muy heterogé- neas, que existe sesgo de publicación y que algunos factores como la región, el sector del consumo de energía, entre otros, inciden en su volatilidad. La evidencia también indica que la elasticidad ingreso en América Latina es mayor que aquella de los países de la OCDE y, simultáneamente, que la elasticidad precio de la demanda de energía es menor en América Latina que en los países de la OCDE. Así, un crecimiento económico continuo en América Latina vendrá acompañado de un crecimiento de la demanda de energía y que el establecimiento de un impuesto en América Latina, bajo las actuales elasticidades, es menos efectivo y en general sería insuficiente para controlar el aumento del consumo de energía.