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1
Beggs, Clive. "The use of ice thermal storage with real time electricity pricing." Thesis, De Montfort University, 1995. http://hdl.handle.net/2086/10674.
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The thesis investigates the application of ice thermal storage technology to situations where the price of electricity varies continuously with instantaneous network demand. A central hypothesis is postulated in chapter 1, which states: "A variable electricity pricing structure, in which unit price continuously varies in response to instantaneous network demand, enhances the opportunities and benefits of ice thermal storage. The benefits both financial and environmental are dependent on the establishment of control and design strategies which optimise performance by matching refrigeration load with the instantaneous electricity price. " For ease of reference, the form of pricing described above is referred to in the thesis as 'real time' electricity pricing. The 'pool price' which is used to facilitate the competitive electricity awkct in England and Wales, is one of the foremost examples of real time pricing. The thesis therefore uses the electricity supply industry in the UK as its research vehicle. Notwithstanding this, the work contained in the thesis can be applied to any country which applies real time electricity pricing mechanisms. The validity of the hypothesis is assessed in the thesis through the development of a variety of numerical and computer models. These models fall into two distinct categories; those concerned with predicting and optimising the financial benefits of ice thermal storage, and those concerned with predicting and optimising the environmental benefits of ice thermal storage. Chapters 2,3 and 4 should be treated as support chapters, which equip the reader with the prerequisite knowledge necessary to understand the research work contained in the later chapters. As such, these chapters contain, respectively, a description of the electricity supply industry in the UK, a discussion of demand side management in the UK, and a description of the technology involved in ice thermal storage. The parametric study contained in chapter 4 is however an original piece of research work by the author. The models developed to evaluate and optimise the economic benefits of ice thermal storage are presented in chapters 5 and 6, and are applied to contrasting theoretical case study applications, namely an office building and a dairy. In chapter 5a 'long hand' numerical analysis technique is used. In chapter 6 this technique is rationalised and developed into a computer model for optimising both the design and control of ice storage installations in real time electricity pricing applications. The environmental studies are presented in chapter 7. These concentrate on the ability of ice thermal storage to reduce carbon dioxide emissions. Although the overall objective of the chapter is to evaluate the carbon dioxide emissions associated with ice thermal storage, the bulk of the chapter is concerned with the development of a model for predicting the carbon dioxide emissions per kWh of delivered electrical energy in England and Wales on a time related basis. The development of this 'time of day' carbon dioxide model is one of the main objectives of the thesis. Having established this model, it is then used to analyse the carbon dioxide emissions associated with the dairy case study.
2
Kinnunen, Kaisa. "Network pricing in the Nordic countries an empirical analysis of the local electricity distribution utilities' ; efficiency and pricing /." [S.l. : s.n.], 2003. http://deposit.ddb.de/cgi-bin/dokserv?idn=969288670.
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Mullen, Christopher. "Interactions between demand side response, demand recovery, peak pricing and electricity distribution network capacity margins." Thesis, University of Newcastle upon Tyne, 2018. http://hdl.handle.net/10443/4170.
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The operation of the electricity system is subject to: charges comprised of energy, capacity, use of system, peak demand and balancing components; payments for services that influence the timing and magnitude of demand; and regulatory and physical network constraints. This work explores the interactions of these characteristics in the GB system. The revenue flows associated with energy demand, balancing and use of system charges are mapped for generators, transmission and distribution network operators (TNO and DNOs), system operator (SO), electricity retailers and electricity users. Triads are part of the transmission network use of service charges and are a form of peak demand pricing. The cost-benefit of Triad avoidance using emergency standby generation is evaluated. Demand Side Response (DSR) provision by commercial electricity users on the network is modelled and simulated. The research determines the impacts of DSR timing, location and penetration level, demand recovery and incidence of Triad periods. A suite of software models was developed including: network demand agents which can be populated with demand profiles and include a model of energy recovery; an interface to Matpower [1] to allow for time-domain based power flow calculations and a model of Short Term Operating Reserve (STOR) which synthesizes calls at representative dates and times. The network demand agents are linked to bus-bars on a network model. The software suite is used to investigate the impacts of STOR provision by demand reduction with and without energy recovery on Triad demand using a Monte Carlo simulation. The total cost benefit of participation in STOR is evaluated. It is also used to conduct timeaware power-flow analysis on a distribution network model with STOR provision by demand reduction. The impact on network capacity headroom is quantified. The cost effectiveness of using standby generation for Triad avoidance was found to depend on the cost of the grid compliant connection. For a payback time of 4 years or less, with the size of generator considered, the grid compliant connection would have to cost less than £5,600. The probability of decreased Triad demand due STOR provision by demand reduction with energy recovery is up to 4 % for the parameters considered. This compares to a probability of up to 1.6 % that the Triad demand would be increased. The most likely outcome is that Triad demand remains unaffected. The total cost benefit of STOR Abstract 2 provision by demand reduction for the 1st percentile may be negative compared to not participating. The impact of DSR provision by demand reduction with energy recovery on the distribution network capacity overhead varies significantly with time of day and with the distribution of DSR over the network. For evenly distributed DSR, demand recovery peaks greater than 40 kW cause a reduction in capacity overhead. However, for a case where the DSR is not evenly distributed the capacity overhead does not decrease for recovery peaks less than 800 kW.
4
Wang, Ji. "Long-run marginal cost pricing methodologies in open access electricity networks." Thesis, University of Bath, 2007. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.760866.
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Electricity network pricing methodologies play a key role in determining whether providing network services is economically beneficial to both the utilities and other m arket participants. There are many pricing methodologies that have been developed since the late 80's, especially for transmission networks. Compared to transmission pricing methods, distribution pricing methods are unsophisticated and pose a significant barrier to embedded generators. Hence, more efficient and executable methodologies are still desirable in open access electricity networks. This thesis presents a series of new long-run marginal cost (LRMC) pricing methodologies for both transmission and distribution networks, and demonstrates the processes o f evaluating and allocating the network asset costs. New reactive power pricing methods, based on the perpendicular approach and arc approach, have been proposed and demonstrated in these LRMC pricing process. Compared with other proposed LRMC pricing schemes, the novel long-run marginal cost with utilisation consideration (LRM C-Util%) pricing methodology aims to evaluate the network asset costs based on the usage o f the network facilities. It can reflect the future network investment and indicate the future location o f network users. The advantages o f LRMC-Util% include the ability to reflect the forward looking costs, to distinguish between the costs o f siting at different locations, to recognize o f the reactive power, and to derive charges for both generation and demand users.
5
Martin, De Lagarde Cyril. "Promoting renewable energy : subsidies, diffusion, network pricing, and market impacts Drivers and diffusion of residential photovoltaics in France Network connection schemes for renewable energy: a spatial analysis." Thesis, Paris Sciences et Lettres (ComUE), 2018. http://www.theses.fr/2018PSLED076.
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Cette thèse s'intéresse à différents aspects relatifs à l'économie des énergies renouvelables (EnR) électriques. Celles-ci ont été choisies par de nombreux pays, désireux de réduire leur empreinte carbone, dans le cadre de la lutte contre le changement climatique.N'étant la plupart du temps pas compétitives face aux moyens de production conventionnels, les EnR nécessitent des subventions publiques, à la fois nationales et locales, pour être rentables. J'analyse l'efficacité de ces aides dans le cas du photovoltaïque chez les particuliers français, en tenant compte des phénomènes de communication, qui participent fortement à la diffusion. Je montre combien ces derniers peuvent être un levier supplémentaire dans le développement des EnR.Ensuite, j'étudie l'impact des schémas régionaux de raccordement au réseau des EnR, dans le cas de l'éolien terrestre en France. Ces schémas introduisent une différenciation spatiale des frais de raccordement. Cela permet de réorienter les investissements vers les régions dans lesquelles le réseau est moins contraint, ce que je quantifie.Les réseaux jouent également un rôle dans le développement des EnR via leur tarification. Celle-ci est essentielle dans le cas de l'autoconsommation, qui fait peser des risques sur l'équilibre budgétaire du gestionnaire de réseau. Ainsi, je détermine notamment les prix à l'optimum économique de second rang dans le cas d'un tarif binôme énergie-puissance.Enfin, j'analyse l'impact de la production renouvelable sur les prix de gros de l'électricité en Allemagne. Je montre que les EnR induisent une baisse des prix différenciée en fonction de l'équilibre offre-demande. Ceci pénalise les centrales de pointe nécessaires à la sécurité d'approvisionnement, ainsi que les EnR de demain, qui devront se passer de subventionsThis thesis deals with several aspects of the economics of electric renewable energy sources (RES). These have been chosen by many countries, willing to reduce their carbon footprint, in order to fight climate change.As RES are usually not competitive against conventional power plants, they rely on national and local subsidies in order to be profitable. I analyse the efficiency of such support schemes in the case of solar photovoltaics for residential households in France. Communication phenomena also take a huge part in the diffusion process. My work shows in how far these are an additional driver of RES development.Then, I study the impact of regional network connection schemes for renewables in France, in the field of onshore wind energy. These schemes introduce a spatial differentiation of network connection charges. They enable to reallocate investments in regions in which the electricity network is less constrained, and I quantify this reallocation.Electricity networks also play a role in the development of RES through their tarification. The latter is fundamental in the case of self-consumption (or "prosumption"), that puts the budget balance of the network operator at risk. Thus, I derive second-best prices in the case of a two-part energy-capacity tariff.Finally, I analyse the impact of renewable generation on electricity wholesale prices in Germany. I show that RES induce a decrease in prices, which depends on the supply-demand equilibrium. This penalises peaking power plants that are necessary to the security of supply, as well as future renewables, which shall progressively become profitable without subsidies
6
Lowrey, Craig. "Electricity pricing and regulation." Thesis, Brunel University, 1999. http://bura.brunel.ac.uk/handle/2438/7390.
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This work aims to assess the development of competition in the electricity industry of England and Wales, emphasising one of the key elements of the restructured industry, the pool - a centralised day ahead electricity spot market. The pool's structure is examined, along with the relationship that the pool has with the market for electricity forward contracts. However, the key to this work is the relationship between the major electricity generators and the industry's regulator. This is introduced through two theoretical models, and undertaken through a series of econometric models using pool prices, forward prices, electricity demand, and the sharep rices of the major generators: National Power and Powergen. The work tests the hypotheses put forward by Green( 1992) and Helm & Powell (1992) of an inverse relationship between the volume of output that a generator sells forward through contracts and the general level of pool prices. The break-up of the first and second sets of forward contracts - which expired in 1991 and 1993 - and their impact on pool prices are assessed By using the market model, this work examines the impact of a series of both regulatory and nonregulatory events on the share returns of National Power and Powergen. Given the existence of spot and forward markets for electricity, one would expect a relationship between the prices in these markets The relationship is examined for England and Wales by a synthetic data set that approximates the prices at which the contracts were sold. The relationship is then examined using actual and forecast electricity prices for California, this latter analysis forming part of an overview of electricity deregulation in America. Ultimately, this research hopes to add to the growing amount of material on energy privatisation - a topic that continues to promote interest and controversy in academic and industrial circles.
7
Vamos, Eugene. "Long run electricity pricing in a deregulated competitive electricity market." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/35461.
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Makawa-Mbewe, Patrick. "Rationalisation of electricity pricing in South Africa's electricity distribution industry." Thesis, Stellenbosch : Stellenbosch University, 2000. http://hdl.handle.net/10019.1/51893.
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Thesis (MBA)--Stellenbosch University, 2000.ENGLISH ABSTRACT: The South African Electricity Distribution Industry is riddled with tariffs. Every utility in South Africa probably uses some method for allocating cost, whether it is theoretically founded or not. There are currently over 2000 different tariffs in South Africa and the need for rationalisation has been widely recognised and acknowledged. Many of these tariffs have not been the outflow of accepted methodologies but rather a function of individual utility policy and practices. There is however a dire need to standardise such methodologies in the future. A standardised methodology might be the only way to eventually rationalise the thousands of tariffs that exist in the electricity industry. Government has emphasised the importance of tariffs to be cost reflective in the future. The only possible way to reach this objective would be to determine clear and concise methods of allocating cost that can be utilised by the entire industry. This study project describes a standardised methodology for determining the cost to supply different customer categories in an electricity distributor. The methodology offers enough flexibility not to bind any party into laboursome, complex and time consuming costing activities. It does however require that the costs of a distributor are carefully investigated and all functions performed in the utility are isolated. This is referred to as ringfencing of costs.
AFRIKAANSE OPSOMMING: Die Suid-Afrikaanse Elektrisiteitverspreidingsbedryf het veelvuldige tariewe. Elke utiliteit in Suid-Afrika gebruik waarskynlik 'n metode vir kostetoedeling, wat nie noodwendig teoreties gebaseer is nie. Huidiglik is daar meer as 2000 verskillende tariewe in Suid-Afrika en dit word alom besef en erken dat gronde vir rasionalisering bestaan. Baie van die tariewe het nie ontstaan uit die gebruik van aanvaarbare berekeningsmetodes nie, maar was eerder die gevolg van individuele beleid en praktyke van utiliteite. Daar is 'n dringende behoefte om hierdie berekeningsmetodes in die toekoms te standardiseer. 'n Standaard metode mag die enigste manier wees om uiteindelik die duisende tariewe wat in die elektrisiteitsbedryf bestaan te rasionaliseer. Die regering het die belangrikheid dat tariewe in die toekoms koste reflekterend moet wees benadruk. Die enigste moontlike manier om hierdie doelwit te bereik, is om helder en duidelike metodes vir koste toedeling te bepaal vir gebruik deur die hele bedryf. Hierdie verhandeling beskryf 'n standaard metodologie om die koste te bepaal om verskillende klantegroepe in 'n elektrisiteitsverspreider van krag te voorsien. Die metodologie bied voldoende plooibaarheid om geen party aan arbeidintensiewe, kompleks en tydrowende kostebepalings te verbind nie. Dit vereis egter dat die koste van 'n verspreider noukeurig ondersoek word en dat alle funksies wat verrig word uitgelig word. Hierna word verwys as afbakening van kostes.
9
Aydin, Nadi Serhan. "Pricing Power Derivatives: Electricity Swing Options." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/3/12612122/index.pdf.
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The Swing options are the natural outcomes of the increasing uncertainty in the power markets, which came along with the deregulation process triggered by the UK government&rsquos action in 1990 to privatize the national electricity supply industry. Since then, the ways of handling the risks in the price generation process have been explored extensively. Producer-consumers of the power market felt confident as they were naturally hedged against the price fluctuations surrounding the large consumers. Companies with high power consumption liabilities on their books demanded tailored financial products that would shelter them from the upside risks while not preventing them from benefiting the low prices. Furthermore, more effective risk management practices are strongly dependent upon the successful parameterization of the underlying stochastic processes, which is also key to the effective pricing of derivatives traded in the market. In this thesis, we refer to the electricity spot price model developed jointly by Hambly, Howison and Kluge ([13]), which incorporates jumps and still maintains the analytical tractability. We also derive the forward curve dynamics implied by the spot price model and explore the effects on the forward curve dynamics of the spikes in spot price. As the main discussion of this thesis, the Grid Approach, which is a generalization of the Trinomial Forest Method, is applied to the electricity Swing options. We investigate the effects of spikes on the per right values of the Swing options with various number of exercise rights, as well as the sensitivities of the model-implied prices to several parameters.
10
Hegazy, Youssef. "Reliability-based pricing of electricity service /." The Ohio State University, 1993. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487841975356122.
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Perera, B. L. P. P. "Optimal pricing of transmission services." Thesis, Imperial College London, 1994. http://hdl.handle.net/10044/1/8425.
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Kluge, T. "Pricing swing options and other electricity derivatives." Thesis, University of Oxford, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.432362.
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The deregulation of regional electricity markets has led to more competitive prices but also higher uncertainty in the future electricity price development. Most markets exhibit high volatilities and occasional distinctive price spikes, which results in demand for derivative products which protect the holder against high prices. A good understanding of the stochastic price dynamics is required for the purposes of risk management and pricing derivatives. In this thesis we examine a simple spot price model which is the exponential of the sum of an Ornstein-Uhlenbeck and an independent pure jump process. We derive the moment generating function as well as various approximations to the probability density function of the logarithm of this spot price process at maturity T. With some restrictions on the set of possible martingale measures we show that the risk neutral dynamics remains within the class of considered models and hence we are able to calibrate the model to the observed forward curve and present semi-analytic formulas for premia of path-independent options as well as approximations to call and put options on forward contracts with and without a delivery period. In order to price path-dependent options with multiple exercise rights like swing contracts a grid method is utilised which in turn uses approximations to the conditional density of the spot process. Further contributions of this thesis include a short discussion of interpolation methods to generate a continuous forward curve based on the forward contracts with delivery periods observed in the market, and an investigation into optimal martingale measures in incomplete markets. In particular we present known results of q-optimal martingale measures in the setting of a stochastic volatility model and give a first indication of how to determine the q-optimal measure for q=0 in an exponential Ornstein-Uhlenbeck model consistent with a given forward curve.
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Rubin, Ofir D. "Equilibrium pricing in electricity markets with wind power." [Ames, Iowa : Iowa State University], 2010. 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:3403856.
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Xia, Zhendong. "Pricing and Risk Management in Competitive Electricity Markets." Diss., Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/7528.
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Electricity prices in competitive markets are extremely volatile with salient features such as mean-reversion and jumps and spikes. Modeling electricity spot prices is essential for asset and project valuation as well as risk management. I introduce the mean-reversion feature into a classical variance gamma model to model the electricity price dynamics as a mean-reverting variance gamma (MRVG) process. Derivative pricing formulae are derived through transform analysis and model parameters are estimated by the generalized method of moments and the Markov Chain Monte Carlo method.
A real option approach is proposed to value a tolling contract incorporating operational characteristics of the generation asset and contractual constraints. Two simulation-based methods are proposed to solve the valuation problem. The effects of different electricity price assumptions on the valuation of tolling contracts are examined. Based on the valuation model, I also propose a heuristic scheme for hedging tolling contracts and demonstrate the validity of the hedging scheme through numerical examples.
Autoregressive Conditional Heteroscedasticity (ARCH) and Generalized ARCH (GARCH) models are widely used to model price volatility in financial markets. Considering a GARCH model with heavy-tailed innovations for electricity price, I characterize the limiting distribution of a Value-at-Risk (VaR) estimator of the conditional electricity price distribution, which corresponds to the extremal quantile of the conditional distribution of the GARCH price process. I propose two methods, the normal approximation method and the data tilting method, for constructing confidence intervals for the conditional VaR estimator and assess their accuracies by simulation studies. The proposed approach is applied to electricity spot price data taken from the Pennsylvania-New Jersey-Maryland market to obtain confidence intervals of the empirically estimated Value-at-Risk of electricity prices.
Several directions that deserve further investigation are pointed out for future research.
15
Parikh, Kirtida. "Electricity demand and pricing in India, 1947-1986." Thesis, London School of Economics and Political Science (University of London), 1992. http://etheses.lse.ac.uk/1190/.
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Over the years 1947-86, electricity has become an important source of energy. The social, political, economic and institutional conditions under which the electricity industry has evolved in India are studied in this thesis. Though electricity demand has increased in India, due to electricity supply shortages after 1972 it was difficult to study electricity demand since no data are available on unconstrained demand. Hence, the factors affecting electricity sales are studied at all-India level for three consumer groups: i) industrial ii) agricultural and iii) "other" consumers. Since states in India differ in their characteristics, electricity sales to industrial and agricultural consumers were studied for the States of Bihar, Kerala, Maharashtra and Punjab. In this analysis, economic and econometric principles are applied to historical data. On the basis of demand theory, income elasticities were expected to be positive and the price elasticities were expected to be negative. From the analysis, it was found that income and price elasticities varied across States and across different consumer groups. Income elasticities were found to be positive and high in each case. Price elasticities were negative and very low in each case with the exception of industrial consumers in Punjab. The time-of-day ("unrestricted") demand for power in Gujarat was studied for the years 1985-86 to 1988-89. The expectation of an hourly and seasonal pattern in the ("unrestricted") demand for power was confirmed. A series of 24 seemingly unrelated equations testing the effects of employment and price on "unrestricted" demand for power at each hour of the day were analysed. It was found that the observed hourly pattern of power demand could not be affected in the desired manner with the existing pricing policy and structure in Gujarat. Pricing remains an important practical tool for managing electricity demand. Pricing also directly affects the performance of the State Electricity Board. The financial performance of Gujarat State Electricity Board was examined and found to be poor due to its pricing policy. On the basis of the literature on the theory of pricing in public enterprises, a method of calculating prices in Gujarat was derived. Due to data constraints, the estimation of prices in the period 1961-86 was limited to prices charged to all consumers of the Gujarat Electricity Board taken as a group. For similar reasons, it also ignored the response of consumers at different time of the day. The prices charged by Gujarat Electricity Board were then compared with the estimated prices. It was found that the estimated prices were higher than the prices charged by Gujarat Electricity Board in the period 1961-86. One of the consequences of low electricity prices was Gujarat Electricity Board's poor financial performance. The study concludes that it is important for the State Electricity Boards in India to study their costs and demand in order to derive a pricing policy that allows the consumer to be aware of the costs and helps the State Electricity Boards to eliminate financial losses.
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Shrinivas, V. Prasanna. "Pricing Multicast Network Services." Thesis, Indian Institute of Science, 2001. http://hdl.handle.net/2005/270.
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Multicast has long been considered an attractive service for the Internet for the provision of multiparty applications. For over a decade now multicast has been a proposed IETF standard. Though there is a strong industry push towards deploying multicast, there has been little multicast deployment by commercial Internet Service Providers (ISPs) and more importantly most end-users still lack multicast capabilities. Depending on the underlying network infrastructure, the ISP has several options of implementing his multicast capabilities. With significantly faster and more sophisticated protocols being designed and prototyped, it is expected that a whole new gamut of applications that are delay sensitive will come into being. However, the incentives to resolve the conflicting interests of the ISPs and the end-users have to be provided for successful implementation of these protocols. Thus we arrive at the following economic questions: What is the strategy that will enable the ISP recover his costs ? How can the end-user be made aware of the cost of his actions ? Naturally, the strategies of the ISP and the end-user depend on each other and form an economic game. The research problems addressed in this thesis are:
A pricing model that is independent of the underlying transmission protocols is prefered. We have proposed such a pricing scheme for multicast independent of the underlying protocols, by introducing the concept of pricing points* These pricing points provide a range of prices that the users can expect during a particular time period and tune their usage accordingly. Our pricing scheme makes both the sender and receiver accountable. Our scheme also provides for catering to heterogeneous users and gives incentive for differential pricing.
We explore a number of formulations of resource allocation problems arising in communication networks as optimization models. Optimization-based methods were only employed for unicast congestion control. We have extended this method for single rate multicast. We have also devised an optimization-based approach for multicast congestion control that finds an allocation rate to maximize the social welfare. Finally we also show that the session-splitting problem can also be cast as an optimization problem.
The commonly used "max-min" fairness criteria suffers from serious limitations like discriminating sessions that traverse large number of links and poor network utilization. We provide an allocation scheme that reduces discrimination towards multicast sessions that traverse many links and also improves network utilization.
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Celebi, Emre. "MODELS OF EFFICIENT CONSUMER PRICING SCHEMES IN ELECTRICITY MARKETS." Thesis, University of Waterloo, 2005. http://hdl.handle.net/10012/811.
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Suppliers in competitive electricity markets regularly respond to prices that change hour by hour or even more frequently, but most consumers respond to price changes on a very different time scale, i. e. they observe and respond to changes in price as reflected on their monthly bills. This thesis examines mixed complementarity programming models of equilibrium that can bridge the speed of response gap between suppliers and consumers, yet adhere to the principle of marginal cost pricing of electricity. It develops a computable equilibrium model to estimate the time-of-use (TOU) prices that can be used in retail electricity markets. An optimization model for the supply side of the electricity market, combined with a price-responsive geometric distributed lagged demand function, computes the TOU prices that satisfy the equilibrium conditions. Monthly load duration curves are approximated and discretized in the context of the supplier's optimization model. The models are formulated and solved by the mixed complementarity problem approach. It is intended that the models will be useful (a) in the regular exercise of setting consumer prices (i. e. , TOU prices that reflect the marginal cost of electricity) by a regulatory body (e. g. , Ontario Energy Board) for jurisdictions (e. g. , Ontario) where consumers' prices are regulated, but suppliers offer into a competitive market, (b) for forecasting in markets without price regulation, but where consumers pay a weighted average of wholesale price, (c) in evaluation of the policies regarding time-of-use pricing compared to the single pricing, and (d) in assessment of the welfare changes due to the implementation of TOU prices.
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Wrobel, Andrzej Jerzy. "The formal theory of pricing and investment for electricity." Thesis, London School of Economics and Political Science (University of London), 2006. http://etheses.lse.ac.uk/1912/.
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The Thesis develops the framework of competitive equilibrium in infinite-dimensional commodity and price spaces, and applies it to the problems of electricity pricing and investment in the generating system. Alternative choices of the spaces are discussed for two different approaches to the price singularities that occur with pointed output peaks. Thermal generation costs are studied first, by using the mathematical methods of convex calculus and majorisation theory, a.k.a. rearrangement theory. Next, the thermal technology, pumped storage and hydroelectric generation are studied by duality methods of linear and convex programming. These are applied to the problems of operation and valuation of plants, and of river flows. For storage and hydro plants, both problems are approached by shadow-pricing the energy stock, and when the given electricity price is a continuous function of time, the plants' capacities, and in the case of hydro also the river flows, are shown to have definite and separate marginal values. These are used to determine the optimum investment. A short-run approach to long-run equilibrium is then developed for pricing a differentiated good such as electricity. As one tool, the Wong-Viner Envelope Theorem is extended to the case of convex but nondifferentiable costs by using the short-run profit function and the profit-imputed values of the fixed inputs, and by using the subdifferential as a multi-valued, generalised derivative. The theorem applies readily to purely thermal electricity generation. But in general the short-run approach builds on solutions to the primal-dual pair of plant operation and valuation problems, and it is this framework that is applied to the case of electricity generated by thermal, hydro and pumped-storage plants. This gives, as part of the long-run equilibrium solution, a sound method of valuing the fixed assets-in this case, the river flows and the sites suitable for reservoirs.
19
Nobaza, Linda. "Efficient Monte Carlo methods for pricing of electricity derivatives." Thesis, University of the Western Cape, 2012. http://hdl.handle.net/11394/4634.
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>Magister Scientiae - MScWe discuss efficient Monte Carlo methods for pricing of electricity derivatives. Electricity derivatives are risk management tools used in deregulated electricity markets. In the past,research in electricity derivatives has been dedicated in the modelling of the behaviour of electricity spot prices. Some researchers have used the geometric Brownian motion and the Black Scholes formula to offer a closed-form solution. Electricity spot prices however have unique characteristics such as mean-reverting, non-storability and spikes that render the use of geometric Brownian motion inadequate. Geometric Brownian motion assumes that changes of the underlying asset are continuous and electricity spikes are far from being continuous. Recently there is a greater consensus on the use of Mean-Reverting Jump-Diffusion (MRJD) process to describe the evolution of electricity spot prices. In this thesis,we use Mean-Reverting Jump-Diffusion process to model the evolution of electricity spot prices. Since there is no closed-form technique to price these derivatives when the underlying electricity spot price is assumed to follow MRJD, we use Monte Carlo methods to value electricity forward contracts. We present variance reduction techniques that improve the accuracy of the Monte Carlo Method for pricing electricity derivatives.
20
Fuloria, Shailendra. "Robust security for the electricity network." Thesis, University of Cambridge, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.610100.
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Khajjayam, Ramesh Kumar V. "Impact of optimally placed VAR support on electricity spot pricing." Morgantown, W. Va. : [West Virginia University Libraries], 2006. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=4895.
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Thesis (M.S.)--West Virginia University, 2006.Title from document title page. Document formatted into pages; contains x, 105 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 99-105).
22
Afanador, Delgado Catalina. "Analysis on various pricing scenarios in a deregulated electricity market." Texas A&M University, 2006. http://hdl.handle.net/1969.1/4376.
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The electricity pricing structure in Texas has changed after deregulation (January
2002). The Energy Systems Laboratory has served as a technical consultant on
electricity purchases to several universities in the Texas A&M University System since
2001. In the fiscal year of 2006 Stephen F. Austin State University joined with the
TAMU campuses and agencies, and there are now 183 accounts in the Electric
Reliability Council of Texas (ERCOT) North, Northeast, South, West, and Houston
areas of Texas. From the 183 accounts, 9 Interval Data Recorder (IDR) accounts
consume 92% of the total load. The objective of this research is to find the most
economic price structure to purchase electricity for the Texas A&M System and Stephen
F. Austin University by analyzing various pricing scenarios: the spot market, forward
contracts, take or pay contracts and on/off season (tiered) contracts. The analysis was
based on the 9 IDR accounts. The prices for the spot market were given by ERCOT and
the other prices by Sempra. The energy charges were calculated every 15 minute using
the real historical consumption of each facility and the aggregated load of all facilities.
The result for the analysis was given for each institution separately, as well as for the aggregated load of all facilities. The results of the analysis showed that the tiered price
was the most economical structure to purchase electricity for each individual university
and for the total aggregated load of all 9 IDR accounts. From March 1, 2005 to February
28, 2006, purchasing electricity on the tiered price would have cost $13,810,560. The
forward contract, that is, purchasing electricity on a fixed rate, was the next cheapest
with an energy cost of $14,266,870 from March 1, 2005 to February 28, 2006, 3%
higher than purchasing electricity at the tiered price. The most expensive method to
purchase electricity would have been the spot market. Its energy costs would have been
approximately $18,171,610, 36% and 31% higher, respectively, than purchasing
electricity at the tiered price and the fixed rate.
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Guo, Matilda, and Maria Lapenkova. "Numerical Methods for Pricing Swing Options in the Electricity Market." Thesis, Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-13931.
Full textAbstract:
Since the liberalisation of the energy market in Europe in the early 1990s, much opportunity to trade electricity as a commodity has arisen. One significant consequence of this movement is that market prices have become more volatile instead of its tradition constant rate of supply. Spot price markets have also been introduced, affecting the demand of electricity as companies now have the option to not only produce their own supply but also purchase this commodity from the market. Following the liberalisation of the energy market, hence creating a greater demand for trading of electricity and other types of energy, various types of options related to the sales, storage and transmission of electricity have consequently been introduced. Particularly, swing options are popular in the electricity market. As we know, swing-type derivatives are given in various forms and are mainly traded as over-the-counter (OTC) contracts at energy exchanges. These options offer flexibility with respect to timing and quantity. Traditionally, the Geometric Brownian Motion (GBM) model is a very popular and standard approach for modelling the risk neutral price dynamics of underlyings. However, a limitation of this model is that it has very few degrees of freedom, as it does not capture the complex behaviour of electricity prices. In short the GBM model is inefficient in the pricing of options involving electricity. Other models have subsequently been used to bridge this inadequacy, e.g. spot price models, futures price models, etc. To model risk-neutral commodity prices, there are basically two different methodologies, namely spot and futures or so-called term structure models. As swing options are usually written on spot prices, by which we mean the current price at which a particular commodity can be bought or sold at a specified time and place, it is important for us to examine these models in order to more accurately inculcate their effect on the pricing of swing options. Monte Carlo simulation is also a widely used approach for the pricing of swing options in the electricity market. Theoretically, Monte Carlo valuation relies on risk neutral valuation and the technique used is to simulate as many (random) price paths of the underlying(s) as possible, and then to average the calculated payoff for each path, discounted to today's prices, giving the value of the desired derivative. Monte Carlo methods are particularly useful in the valuation of derivatives with multiple sources of uncertainty or complicated features, like our electricity swing options in question. However, they are generally too slow to be considered a competitive form of valuation, if any analytical techniques of valuation exist. In other words, the Monte Carlo approach is, in a sense, a method of last resort. In this thesis, we aim to examine a numerical method involved in the pricing of swing options in the electricity market. We will consider an existing and widely accepted electricity price process model, use the finite volume method to formulate a numerical scheme in order to calibrate the prices of swing options and make a comparison with numerical solutions obtained using the theta-scheme. Further contributions of this thesis include a comparison of results and also a brief discussion of other possible methods.
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Valitov, Niyaz [Verfasser]. "Pricing and risk premia in German electricity markets / Niyaz Valitov." Wuppertal : Universitätsbibliothek Wuppertal, 2019. http://d-nb.info/1188421832/34.
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Lu, Yuhao. "Pricing and competition in the Swedish retail market for electricity." Thesis, Högskolan Dalarna, Nationalekonomi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:du-19869.
Full textAbstract:
Sweden, together with Norway, Finland and Denmark, have created a multi-national electricity market called NordPool. In this market, producers and retailers of electricity can buy and sell electricity, and the retailers then offers this electricity to end consumers such as households and industries. Previous studies have shown that pricing at the NordPool market is functioning quite well, but no other study has to my knowledge studied if pricing in the retail market to consumers in Sweden is well functioning. If the market is well functioning, with competition and low transaction costs when changing electricity retailer, we would expect that a homogeneous good such as electricity would be sold at the approximately same price, and that price changes would be highly correlated, in this market. Thus, the aim of this study is to test whether the price of Vattenfall, the largest energy firm in the Swedish market, is highly correlated to the price of other firms in the Swedish retail market for electricity. Descriptive statistics indicate that the price offered by Vattenfall is quite similar to the price of other firms in the market. In addition, regression analysis show that the correlation between the price of Vattenfall and other firms is as high as 0.98.
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Huang, Yalin. "Electricity Distribution Network Planning Considering Distributed Generation." Licentiate thesis, KTH, Elektriska energisystem, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-141482.
Full textAbstract:
One of EU’s actions against climate change is to meet 20% of our energy needs from renewable resources. Given that the renewable resources are becoming more economical to extract electricity from, this will result in that more and more distributed generation (DG) will be connected to power distribution. The increasing share of DG in the electricity networks implies both increased costs and benefits for distribution system operators (DSOs), customers and DG producers. How the costs and benefits will be allocated among the actors will depend on the established regulation. Distribution networks are traditionally not designed to accommodate generation. Hence, increasing DG penetration is causing profound changes for DSOs in planning, operation and maintenance of distribution networks. Due to the unbundling between DSOs and electricity production, DSOs can not determine either the location or the size of DG. This new power distribution environment brings new challenges for the DSOs and the electric power system regulator. The DSOs are obliged to enable connection of DG meanwhile fulfilling requirements on power quality and adequate reliability. Moreover, regulatory implications can make potential DG less attractive. Therefore regulation should be able to send out incentives for the DSOs to efficiently plan the network to accommodate the increasing levels of DG. To analyze the effects of regulatory polices on network investments, risk analysis methods for integrating the DG considering uncertainties are therefore needed. In this work, regulation impact on network planning methods and network tariff designs in unbundled electricity network is firstly analyzed in order to formulate a realistic long-term network planning model considering DG. Photovoltaic (PV) power and wind power plants are used to demonstrate DG. Secondly, this work develops a deterministic model for low-voltage (LV) networks mainly considering PV connections which is based on the worst-case scenario. Dimension the network using worst-case scenario is the convention in the long-term electricity distribution network planning for the reliability and security reason. This model is then further developed into a probabilistic model in order to consider the uncertainties from DG production and load. Therefore more realistic operation conditions are considered and probabilistic constrains on voltage variation can be applied. Thirdly, this work develops a distribution medium-voltage (MV) network planning model considering wind power plant connections. The model obtains the optimal network expansion and reinforcement plan of the target network considering the uncertainties from DG production and load. The model is flexible to modify the constraints. The technical constraints are respected in any scenario and violated in few scenarios are implemented into the model separately. In LV networks only PV connections are demonstrated and in MV networks only wind power connections are demonstrated. The planning model for LV networks is proposed as a practical guideline for PV connections. It has been shown that it is simple to be implemented and flexible to adjust the planning constraints. The proposed planning model for MV networks takes reinforcement on existing lines, new connection lines to DG, alternatives for conductor sizes and substation upgrade into account, and considers non-linear power flow constraints as an iterative linear optimization process. The planning model applies conservative limits and probabilistic limits for increasing utilization of the network, and the different results are compared in case studies. The model’s efficiency, flexibility and accuracy in long-term distribution network planning problems are shown in the case studies.QC 20140217
Elforsk Risknanlys II
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Oladeji, Olamide. "Network partitioning algorithms for electricity consumer clustering." Thesis, Massachusetts Institute of Technology, 2018. https://hdl.handle.net/1721.1/122917.
Full textAbstract:
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Program, 2018
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 97-103).
In many developing countries, access to electricity remains a significant challenge. Electrification planners in these countries often have to make important decisions on the mode of electrification and the planning of electrical networks for those without access, while under resource constraints. To facilitate the achievement of universal energy access, the Reference Electrification Model (REM), a computational model capable of providing techno-economic analysis and data-driven decision support for these planning efforts, has been developed. Primary among REM's capabilities is the recommendation of the least-cost mode of electrification - i.e by electric grid extension or off-grid systems - for non-electrified consumers in a region under analysis, while considering technical, economic and environmental constraints.
This is achieved by the identification of consumer clusters (either as clusters of off-grid microgrids, stand-alone systems or grid-extension projects) using underlying clustering methods in the model. This thesis focuses on the development and implementation of partitioning algorithms to achieve this purpose. Building on previously implemented efforts on the clustering and recommendation capabilities of REM, this work presents the development, analysis and performance evaluation of alternative approaches to the consumer clustering process, in comparison with REM's previously incorporated clustering methodology. Results show that the alternative methodology proposed can compare favorably with the hitherto implemented method in REM. Consequently, the integration of the pro- posed network partitioning procedures within REM, as well as some potential future research directions, is discussed.
Finally, this thesis concludes with a discourse on the social and regulatory aspects of energy access and electricity planning in developing countries, providing some perspectives on the development policies and business models that complement the technological contributions of this work.
by Olamide Oladeji.
S.M. in Technology and Policy
S.M.
S.M.inTechnologyandPolicy Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Program
S.M. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
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Dudley, Paul. "Optimal time-related charging in competitive markets with particular reference to electricity." Thesis, Loughborough University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.297117.
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Madrigal, Marcelino. "Optimization models and techniques for implementation and pricing of electricity markets." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/NQ60555.pdf.
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Mendes, Dilcemar de Paiva. "Generation scheduling,pricing mechanisms and bidding strategies in competitive electricity markets." Thesis, University of Manchester, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.488217.
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Sarhan, Alaa A. "Equity and efficiency considerations in electricity pricing : the case of Egypt." Thesis, University College London (University of London), 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.307073.
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Rashidi-Nejad, Masoud. "Procurement and pricing of reserves via joint dispatch and financial derivatives." Thesis, Brunel University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.247542.
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Tilley, Brian. "Competition and efficiency issues in electricity supply in England and Wales." Thesis, Loughborough University, 2001. https://dspace.lboro.ac.uk/2134/33827.
Full textAbstract:
The thesis examines competition and efficiency in the liberalised electricity industry of England and Wales after 1990. Literature review and economic analysis is undertaken for four activities: generation and trading arrangements; transmission pricing; comparative efficiency in distribution; and competition and access in supply. In trading arrangements and distribution, the analysis is supplemented by empirical work using both event study models and non-parametric efficiency analysis. Broad conclusions are that there is some evidence of generators behaving strategically in the pool, and productivity is variable among the distribution companies, with the increase attributable to the industry as a whole.
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Urquhart, Andrew J. "Accuracy of low voltage electricity distribution network modelling." Thesis, Loughborough University, 2016. https://dspace.lboro.ac.uk/2134/21799.
Full textAbstract:
The connection of high penetrations of new low carbon technologies such as PV and electric vehicles onto the distribution network is expected to cause power quality problems and the thermal capacity of feeder cables may be exceeded. Replacement of existing infrastructure is costly and so feeder cables are likely to be operated close to their hosting capacity. Network operators therefore require accurate simulation models so that new connection requests are not unnecessarily constrained. This work has reviewed recent studies and found a wide range of assumptions and approximations that are used in network models. A number of these have been investigated further, focussing on methods to specify the impedances of the cable, the impacts of harmonics, the time resolution used to model demand and generation, and assumptions regarding the connectivity of the neutral and ground conductors. The calculation of cable impedances is key to the accuracy of network models but only limited data is available from design standards or manufacturers. Several techniques have been compared in this work to provide guidance on the level of detail that should be included in the impedance model. Network modelling results with accurate impedances are shown to differ from those using published data. The demand data time resolution has been shown to affect estimates of copper losses in network cables. Using analytical methods and simulations, the relationship between errors in the loss estimates and the time resolution has been demonstrated and a method proposed such that the accuracy of loss estimates can be improved. For networks with grounded neutral conductors, accurate modelling requires the resistance of grounding electrodes to be taken into account. Existing methods either make approximations to the equivalent circuit or suffer from convergence problems. A new method has been proposed which resolves these difficulties and allows realistic scenarios with both grounded and ungrounded nodes to be modelled. In addition to the development of models, the voltages and currents in a section of LV feeder cable have been measured. The results provide a validation of the impedance calculations and also highlight practical difficulties associated with comparing simulation models with real measurement results.
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Winicki, Elliott. "ELECTRICITY PRICE FORECASTING USING A CONVOLUTIONAL NEURAL NETWORK." DigitalCommons@CalPoly, 2020. https://digitalcommons.calpoly.edu/theses/2126.
Full textAbstract:
Many methods have been used to forecast real-time electricity prices in various regions around the world. The problem is difficult because of market volatility affected by a wide range of exogenous variables from weather to natural gas prices, and accurate price forecasting could help both suppliers and consumers plan effective business strategies. Statistical analysis with autoregressive moving average methods and computational intelligence approaches using artificial neural networks dominate the landscape. With the rise in popularity of convolutional neural networks to handle problems with large numbers of inputs, and convolutional neural networks conspicuously lacking from current literature in this field, convolutional neural networks are used for this time series forecasting problem and show some promising results.
This document fulfills both MSEE Master's Thesis and BSCPE Senior Project requirements.
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Green, Richard John. "Essays in the electricity industry in England and Wales." Thesis, University of Cambridge, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.337997.
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Yang, Weilai. "Pricing Network Resources for Differentiated Service Networks." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/5227.
Full textAbstract:
We developed a price-based resource allocation scheme for Differentiated Service (DiffServ) data networks. The DiffServ framework was proposed to provide multiple QoS classes over IP networks. Since the provider supports multiple service classes, we need a differentiated pricing scheme, as supposed to the flat-rate scheme employed by the Internet service providers of today. Charging efficiently is a big issue. The utility of a client correlates to the amount of bandwidth allocated. One difficulty we face is that determining the appropriate amount of bandwidth to provision and allocate is problematic due to different time scales, multiple QoS classes and the unpredictable nature of users.
To approach this problem, we designed a pricing strategy for Admission Control and bandwidth assignment. Despite the variety of existing pricing strategies, the common theme is that the appropriate pricing policy rewards users for behaving in ways to improve the overall utilization and performance of the network. Among existing schemes, we chose auction because it is scalable, and efficiently and fairly shares resources. Our pricing model takes the system's availability and each customer's requirements as inputs and outputs the set of clients who are admitted into the network and their allocated resource. Each client proposes a desired bandwidth and a price that they are willing to pay for it. The service provider collects this information and produces parameters for each class of service they provide. This information is used to decide which customers to admit.
We proposed an optimal solution to the problem of maximizing the provider's revenue for the special case where there is only one bottleneck link in the network. Then for the generalized network, we resort to a simple but effective heuristic method. We validate both the optimal solution and the heuristic algorithm with simulations driven by a real traffic scenario. Finally, we allow customers to bid on the duration for which the service is needed. Then we study the performance of those heuristic algorithms in this new setting and propose possible improvements.
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Ahn, Ki-Jung. "Road pricing, modal choice and road network." Kyoto University, 2008. http://hdl.handle.net/2433/136104.
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Liu, Zixu. "Integrated demand and supply side management and smart pricing for electricity market." Thesis, University of Manchester, 2018. https://www.research.manchester.ac.uk/portal/en/theses/integrated-demand-and-supply-side-management-and-smart-pricing-for-electricity-market(2d675c1f-9dc1-469d-9a86-b4c4398154de).html.
Full textAbstract:
On the one hand, the demand response management and dynamical pricing supported by the smart grid had started to lead to fundamentally different energy consumption behaviours; On the other hand, energy supply has gone through a dramatic new pattern due to the emergence and development of renewable energy resources. Facing these changes, this thesis investigates one of the resulting challenges, which is how to integrate the wholesale market and the retail market into one framework in order to achieve optimal balancing between demand and supply. Firstly, based on the existing mechanisms of the wholesale and retail electricity markets, a simulation tool is proposed and developed. This enables the ISO to find the best balance between supply and demand, by taking into account the different objectives of the generators, retailers and customers. Secondly, a new market mechanism based on the interval demand is proposed in order to address the challenges of the unpredictable demand due to the demand response management programs. Under the proposed new market mechanism, the corresponding approaches are investigated in order to support the retailers to find their profit-optimal pricing strategies, the generators to develop their best bidding strategies, and the ISO to identify the market clearing price function in order to best balance supply and demand. In particular: 1) For the ISO, our designed mechanism could effectively handle unpredictable demand under the dynamic retail pricing. It also enables the realisation of the goals of dynamic pricing by utilising smart meters; 2) In the retail market, we extend the smart pricing model in the current research in order to enable the retailers to find the most-profitable pricing scheme under the proposed new mechanism with the demand-based piecewise cost (i.e., market clearing price) function; 3) For the wholesale market, we developed a pricing forecasting model in order to forecast a market clearing price. Based on this model, we analysed the optimal bidding strategies for a generator under an interval demand from the ISO. Simulation results are provided in order to verify the effectiveness of the proposed approaches.
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Gözüm, Özge Nadia 1979. "Decision tools for electricity transmission service and pricing : a dynamic programming approach." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/33158.
Full textAbstract:
Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2001.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (leaves 104-107).
For a deregulated electricity industry, we consider a general electricity market structure with both long-term bilateral agreements and short-term spot market such that the system users can hedge the volatility of the real-time market. From a Transmission Service Provider's point of view, optimal transmission resource allocation between these two markets poses a very interesting decision making problem for a defined performance criteria under uncertainties. In this thesis, the decision-making is posed as a stochastic dynamic programming problem, and through simulations the strength of this method is demonstrated. This resource allocation problem is first posed as a centrally coordinated dynamic programming problem, computed by one entity at a system- wide level. This problem is shown to be, under certain assumptions, solvable in a deterministic setup. However, implementation for a large transmission system requires the algorithm to handle stochastic inputs and stochastic cost functions. It is observed that the curse of dimensionality makes this centralized optimization infeasible. Thesis offers certain remedies to the computational issues, but motivates a partially distributed setup and related optimization functions for a better decision making in large networks where the intelligent system users drive the use of network resources. Formulations are introduced to reflect mathematical and policy constraints that are crucial to distributed network operations in power systems.
by Özge Nadia Gözüm.
M.Eng.
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Connolly, Jeremiah P. (Jeremiah Peter). "Effect of real-time electricity pricing on renewable generators and system emissions." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/42938.
Full textAbstract:
Thesis (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2008.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 127-130).
Real-time retail pricing (RTP) of electricity, in which the retail price is allowed to vary with very little time delay in response to changes in the marginal cost of generation, offers expected short-run and long-run benefits at the societal level. While the effects of RTP on most market participants have been examined previously, its effects on a) renewable generator revenues and b) power sector emissions are not well understood. This thesis presents a counterfactual model of the new England wholesale power market, including within-hour consumer price response, to analyze revenues under RTP for four renewable test cases and emissions of CO2, SO2, and NOx. Assuming a moderate consumer price-response ( e = -0.3), I find that revenues for both wind and solar cases will decrease by about 3%, a smaller loss than that expected by the generation sector as a whole (~ 6%) or by peak generators ( ~ 55%). In the same scenario, RTP is expected to decrease emissions of CO2, SO2, and NOx by 2-3% in the short-run. These results are qualitatively robust across a range of elasticities and other input parameters. A discussion of the political barriers to RTP highlights interest group pressure from peak generators and the framing of gains and losses for consumers. These barriers are likely to attract significant policymaker attention in RTP discussions, but the results of my empirical analysis show the need to also consider how RTP may interfere with the ability to achieve other policy objectives, including promoting renewable energy and reducing emissions.
by Jeremiah P. Connolly.
S.M.
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Jose, Anita Ann. "Economic evaluation of small wind generation ownership under different electricity pricing scenarios." Thesis, Kansas State University, 2011. http://hdl.handle.net/2097/7075.
Full textAbstract:
Master of ScienceDepartment of Electrical and Computer Engineering
Anil Pahwa
With the Smart Grid trend setting in, various techniques to make the existing grid smarter are being considered. The price of electricity is one of the major factors, which affects the electric utility as well as the numerous consumers connected to the grid. Therefore deciding the right price of electricity for the time of day would be an important decision to make. Consumers’ response to this change in price will impact peak demand as well as their own annual energy bill. Owning a small wind generator under the Critical Peak Pricing (CPP) and Time of Use (TOU) price-based demand response programs could be a viable option. Economic evaluation of owning a small wind generator under the two pricing schemes, namely Critical Peak Pricing (CPP) and Time of Use (TOU), is the main focus of this research. Analysis shows that adopting either of the pricing schemes will not change the annual energy bill for the consumer. Taking into account the installed cost of the turbine, it may not be significantly economical for a residential homeowner to own a small wind turbine with either of the pricing schemes in effect under the conditions assumed.
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Reynolds, Stephanie. "Power, policy and pricing: an analysis of free basic electricity in Khayelitsha." Master's thesis, University of Cape Town, 2012. http://hdl.handle.net/11427/9795.
Full textAbstract:
Includes bibliographical references.This study focuses on the economic rationale for increased electrification in Khayelitsha and for enhanced Free Basic Electricity (FBE) policies. Air quality readings in Khayelitsha have shown high readings of pollution and a particularly high incidence of coarse particulate matter (PM10). These are on average 25 per cent higher than Goodwood and 70 per cent higher than in central Cape Town. PM10s are particularly harmful pollutants and impose an increasing marginal external cost; the health implications of exposure varying directly with exposure levels. Open fires, traditional and paraffin stoves, and flame based lighting are major contributors to respiratory disease and altered lung function. Low birth-weight, nutritional deficiency, tuberculosis, cardiovascular disease and cataracts have also been associated with the prevalence of PM10. It was found in this dissertation that PM10 readings are significantly higher than allowed by national standards and that a 100 per cent increase in Free Basic Electricity, from 50kWh per month to 100kWh, would be appreciably beneficial to health outcomes. Dose-response functions were used to evaluate the effect of a 10 per cubic metre μɡ//m³ decrease in PM10 for lung diseases, Lower Respiratory Illness in children, Chronic Obstructive Pulmonary Disease (COPD), cardiovascular and respiratory mortality and other related symptoms. It was seen that all of these adverse health episodes would decrease to varying extents, for example between 13 and 14 lives could be saved from COPD, cardiovascular mortality could decrease by around 468 deaths and respiratory deaths could decrease by about 2 491. Added to this, between 721 665 and 1 237 140 annual sick days would be saved annually and ambient pollution readings would drop, although the extent to which this would happen is unknown.
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Liu, Kui. "Performance Evaluation of ZigBee Network for Embedded Electricity Meters." Thesis, KTH, Reglerteknik, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-105711.
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ZigBee is an emerging wireless technology for low-power, low data rate and short range communications between wireless nodes, which is showing a promising future. This research provides an overview of 802.15.4 and ZigBee standard. A test bench was created to evaluate the performance of ZigBee network for electricity meters applications. The results from the test show that ZigBee supports a large network size, a range of 75m within line of sight, a fairly large effective data rate that is enough for metering traffic and very low power consumption devices. These characteristics are very suitable for electricity meters applications where cost and power consumption is the major concern.
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Alsaedi, Yasir H. "An Investigation of the Effects of Solar and Wind Prices on the Australia Electricity Spot and Options Markets: A Time Series Analysis." Thesis, Griffith University, 2021. http://hdl.handle.net/10072/410472.
Full textAbstract:
Electricity pricing is recognised as being among the most important contemporary policy issues in Australia, and it also represents a critical component of current discussions concerning energy and climate-change policies. Attempts to move forward with energy and climate-change policies have been mostly stymied by concerns regarding potential increases in electricity prices. In relation to such policy discussions, renewable electricity generation is currently considered to be a fundamental factor influencing electricity prices. Due to the increasing penetration of both wind and solar power generation in Australia, which happens to be coinciding with increasing wholesale and retail electricity prices, there is now a widely held belief that the observed wholesale electricity price increases are related to the increased penetration of renewable energy sources.
Overall, the present study aims to investigate the nature and influence of the solar and wind electricity prices on the Australian spot and options markets. To accomplish this aim, the study begins by investigating wind, solar, spot and options pricing and then developing relevant models on the basis of a univariate state-by-state analysis of Australia’s electricity markets. Next, the study investigates the effects of the solar and wind prices on the Australian spot and options markets by means of a multivariate analysis. In addition, the study investigates the impacts of solar and wind pricing on the “global” electricity spot and options markets, with a particular focus on the Australian, German and American electricity markets. Moreover, the study examines how energy companies develop and manage policies concerning electricity production and pricing, as well as the use of solar and wind power, in the Australian markets.
More specifically, the first part of this study (Paper 1) involves a univariate analysis of the solar, wind, spot and options electricity prices intended to facilitate a more in-depth understanding of the nature of each variable in terms of forecasting, correlations and volatilities with regard to the Australian electricity markets. Quantitative data concerning the electricity markets in five Australian states, namely New South Wales (NSW), Queensland (QLD), South Australia (SA), Victoria (VIC) and Tasmania (TAS), are considered in this study. The results of the analyses reveal increases of between 30.46% and 40.42% in relation to the spot electricity prices as well as between 14.80% and 15.13% in relation the options electricity prices within the Australian National Electricity Market (ANEM) with a two-year horizon. The results also show that wind prices are expected to increase by an average of 5.43%, while the average solar electricity price is expected to decrease by 67.7%.
The second part of this study (Paper 2) involves a multivariate analysis designed to examine the dynamics within the Australian electricity markets, particularly those that may exist between the solar and wind prices and the electricity spot and options markets in each Australian state. The results of the Granger causality analysis indicate there to be a significant unidirectional Granger causal relationship between the solar and wind electricity prices and the spot prices in NSW, QLD, VIC and TAS at the 1% significance level, while in the case of SA, the relationship appears to be significant at less than the 10% level. Moreover, the forecast results suggest that the solar and wind electricity prices reduce the spot and options electricity market prices within the ANEM.
The third part of this study (Paper 3) involves a multivariate analysis conducted to investigate the movements within the international electricity markets. The aim was to examine the impacts of the solar and wind prices on the global electricity spot and options markets, with a particular focus on the Australian, German and US or American markets. The results indicate that the electricity markets in Australia, Germany and the United States are interdependent and related to any changes in solar and wind pricing, which means that all the investigated electricity markets are influenced by movements in other electricity markets.
The fourth part of this study (Paper 4) involves the application of in-depth qualitative technique of analysis. This part was used to investigate the nature and influence of policies and regulations concerning solar and wind pricing and their relationship to the Australian electricity spot and options markets. The analysis was based on data gathered through interviews conducted with chief executive officers, energy managers and other significant personnel from within the Australian electricity industry. The interviewees’ responses regarding the solar and wind policies that were considered relevant to the Australian electricity markets were analysed, and the “thick and in-depth” content data was derived data from the interviews. This set was then used to examine how their views and personal politics tend to influence pricing within the electricity markets. The results suggest that renewable energy policies lower the electricity prices, reduce the risk for investors and result in larger deployment mechanisms.Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Environment and Sc
Science, Environment, Engineering and Technology
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Chieng, H. T. "A framework for provisioning network network resources based-on agent-enhanced service level agreements." Thesis, Queen's University Belfast, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.246460.
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Murdter, Michael J. "Utility cost accounting and market pricing of electricity at the Naval Postgraduate School." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1994. http://handle.dtic.mil/100.2/ADA283400.
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Yang, Kun. "Optimal procurement and pricing of reactive power ancillary services in competitve electricity market." Thesis, University of Strathclyde, 2010. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=14337.
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McDonald, James R. "On spot-pricing based electricity tariffs and the modelling of consumer load response." Thesis, University of Strathclyde, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.506615.
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Leow, Woei Ling. "Zoning and occupancy-moderation for residential space-conditioning under demand-driven electricity pricing." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/78480.
Full textAbstract:
Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2012.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 138-144).
Occupancy-moderated zonal space-conditioning (OZS) refers to the partitioning of a residence into different zones and independently operating the space-conditioning equipment of each zone based on its occupancy. OZS remains largely unexplored in spite of its potential to reduce the cost of space-conditioning. Despite the excitement surrounding cloud-connected devices like mobile phones and tablet computers, the benefit of using them to aid energy management agents (EMAs) in reducing space-conditioning cost under demand-driven pricing of electricity is not well understood. We develop a novel framework and the algorithms to enable an EMA to implement OZS for multiple inhabitants under a demand-driven pricing scheme for electricity. We further investigate the effects that influencing factors can have on the effectiveness of OZS under different scenarios using Monte Carlo simulations. The simulation results demonstrate that OZS is realizable on a simple home computer and can achieve significant space-conditioning cost reductions in practice. In our studies, both the financial operating cost of space-conditioning and the cost associated with discomfort are included in a single aggregate cost function. We then expand the simulations to study the cost reduction that is achievable when using cloud-connected devices to provide remote schedule updates to an EMA. This part of the study reveals that reduction in space-conditioning cost is appreciable if a working resident remotely updates an EMA at mid-day of his return time in the evening. In addition, we establish a directly proportional relationship between the level of space-conditioning cost reduction achievable and the variance of return time. Based on the research findings, we further offer recommendations and ideas for future research on the use of OZS and remote schedule updates to different stakeholders like policy-makers and homeowners.
by Woei Ling Leow.
Ph.D.