Готові списки джерел за темами / Electricity distribution in Italy

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Автор: Grafiati
Опубліковано: 14 березня 2023

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Статті в журналах з теми "Electricity distribution in Italy"

1

Cambini, Carlo, Annalisa Croce, and Elena Fumagalli. "Output-based incentive regulation in electricity distribution: Evidence from Italy." Energy Economics 45 (September 2014): 205–16. http://dx.doi.org/10.1016/j.eneco.2014.07.002.

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Ajodhia, Virendra, Luca Lo Schiavo, and Roberto Malaman. "Quality regulation of electricity distribution in Italy: an evaluation study." Energy Policy 34, no. 13 (September 2006): 1478–86. http://dx.doi.org/10.1016/j.enpol.2004.11.016.

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Cambini, Carlo, Elena Fumagalli, and Laura Rondi. "Incentives to quality and investment: evidence from electricity distribution in Italy." Journal of Regulatory Economics 49, no. 1 (October 8, 2015): 1–32. http://dx.doi.org/10.1007/s11149-015-9287-x.

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Fichera, Alberto, Alessandro Pluchino, and Rosaria Volpe. "Modelling Energy Distribution in Residential Areas: A Case Study Including Energy Storage Systems in Catania, Southern Italy." Energies 13, no. 14 (July 19, 2020): 3715. http://dx.doi.org/10.3390/en13143715.

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Complexity is a widely acknowledged feature of urban areas. Among the different levels to which this definition applies, the energy sector is one of the most representative of this way of conceiving cities. An evidence of this complexity can be detected in the growing impact of prosumers. Prosumers produce energy to meet their own demands, distribute it directly to neighbors and, eventually, store the energy neither consumed nor distributed. The modelling of distribution networks is a challenging task that requires ad hoc models to simulate the mutual energy exchanges occurring among prosumers. To serve at this scope, this paper proposes an agent-based model aiming at determining which operating conditions enhance the energy distribution among prosumers and diminish the supply from traditional power plants. An application of the model within a residential territory is then presented and simulations are conducted under two scenarios: the first investigating the distribution among prosumers equipped with photovoltaics (PV) systems, the second integrating energy storage systems to PV panels. Both scenarios are studied at varying the installed PV capacity within the territory, the allowed distance of connection among prosumers, as well as the rate of utilization of the links of the network. Results from the simulated case study reveal that the energy distribution among prosumers can be enhanced by providing short-range links for the electricity exchange. Similar advantages can be achieved by integrating storage systems to PV, along with a significant reduction in the electricity requested to the centralized grid.
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De Blasis, Riccardo, Giovanni Batista Masala, and Filippo Petroni. "A Multivariate High-Order Markov Model for the Income Estimation of a Wind Farm." Energies 14, no. 2 (January 12, 2021): 388. http://dx.doi.org/10.3390/en14020388.

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The energy produced by a wind farm in a given location and its associated income depends both on the wind characteristics in that location—i.e., speed and direction—and the dynamics of the electricity spot price. Because of the evidence of cross-correlations between wind speed, direction and price series and their lagged series, we aim to assess the income of a hypothetical wind farm located in central Italy when all interactions are considered. To model these cross and auto-correlations efficiently, we apply a high-order multivariate Markov model which includes dependencies from each time series and from a certain level of past values. Besides this, we used the Raftery Mixture Transition Distribution model (MTD) to reduce the number of parameters to get a more parsimonious model. Using data from the MERRA-2 project and from the electricity market in Italy, we estimate the model parameters and validate them through a Monte Carlo simulation. The results show that the simulated income faithfully reproduces the empirical income and that the multivariate model also closely reproduces the cross-correlations between the variables. Therefore, the model can be used to predict the income generated by a wind farm.
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Di Micco, Simona, Mariagiovanna Minutillo, Alessandra Perna, and Elio Jannelli. "On-site solar powered refueling stations for green hydrogen production and distribution: performances and costs." E3S Web of Conferences 334 (2022): 01005. http://dx.doi.org/10.1051/e3sconf/202233401005.

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Today, the hydrogen is considered an essential element in speeding up the energy transition and generate important environmental benefits. Not all hydrogen is the same, though. The “green hydrogen”, which is produced using renewable energy and electrolysis to split water, is really and completely sustainable for stationary and mobile applications. This paper is focused on the techno-economic analysis of an on-site hydrogen refueling station (HRS) in which the green hydrogen production is assured by a PV plant that supplies electricity to an alkaline electrolyzer. The hydrogen is stored in low pressure tanks (200 bar) and then is compressed at 900 bar for refueling FCHVs by using the innovative technology of the ionic compressor. From technical point of view, the components of the HRS have been sized for assuring a maximum capacity of 450 kg/day. In particular, the PV plant (installed in the south of Italy) has a size of 8MWp and supplies an alkaline electrolyzer of 2.1 MW. A Li-ion battery system (size 3.5 MWh) is used to store the electricity surplus and the grid-connection of the PV plant allows to export the electricity excess that cannot be stored in the battery system. The economic analysis has been performed by estimating the levelized cost of hydrogen (LCOH) that is an important economic indicator based on the evaluation of investment, operational & maintenance and replacement costs. Results highlighted that the proposed on-site configuration in which the green hydrogen production is assured, is characterized by a LCOH of 10.71 €/kg.
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Forouli, Aikaterini, Emmanouil A. Bakirtzis, Georgios Papazoglou, Konstantinos Oureilidis, Vasileios Gkountis, Luisa Candido, Eloi Delgado Ferrer, and Pandelis Biskas. "Assessment of Demand Side Flexibility in European Electricity Markets: A Country Level Review." Energies 14, no. 8 (April 20, 2021): 2324. http://dx.doi.org/10.3390/en14082324.

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Анотація:
Power systems in many countries have recently undergone a significant transition towards renewable and carbon-free generation sources. Those sources pose new challenges to the grid operation due to their intermittency and uncertainty. Consequently, advanced policy strategies and technologies offering new flexibility solutions on the inelastic demand side are required to maintain the reliability of power systems. Given the diversity of situations, legislation and needs across European countries and the varying nature of distribution system operators, this article reviews the deployment of demand side flexibility at national level to identify best practices and main barriers. The analysis concerns European countries of different progress in solutions that leverage flexibility towards offering electricity grid services. The scope is to explore the operation principles of European electricity markets, to assess the participation of emerging flexible resources, and to propose new approaches that facilitate the integration of flexible assets in the distribution grid. The countries reviewed are the United Kingdom, Belgium, Italy and Greece. These countries were selected owing to their diversity in terms of generation mix and market design. Barriers for market access of flexibility resources are also identified in order to form relevant country-specific recommendations.
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Battista, Frison, and Bolzonella. "Energy and Nutrients’ Recovery in Anaerobic Digestion of Agricultural Biomass: An Italian Perspective for Future Applications." Energies 12, no. 17 (August 26, 2019): 3287. http://dx.doi.org/10.3390/en12173287.

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Anaerobic digestion (AD) is the most adopted biotechnology for the valorization of agricultural biomass into valuable products like biogas and digestate, a renewable fertilizer. This paper illustrates in the first part the actual situation of the anaerobic digestion sector in Italy, including the number of plants, their geographical distribution, the installed power and the typical feedstock used. In the second part, a future perspective, independent of the actual incentive scheme, is presented. It emerged that Italy is the second European country for the number of anaerobic digestion plants with more than 1500 units for a total electricity production of about 1400 MWel. More than 60% of them are in the range of 200 kW–1 MW installed power. Almost 70% of the plants are located in the northern part of the Country where intensive agriculture and husbandry are applied. Most of the plants are now using energy crops in the feedstock. The future perspectives of the biogas sector in Italy will necessarily consider a shift from power generation to biomethane production, and an enlargement of the portfolio of possible feedstocks, the recovery of nutrients from digestate in a concentrated form, and the expansion of the AD sector to southern regions. Power to gas and biobased products will complete the future scenario.
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Miconi, Federico, and Giovanna Maria Dimitri. "A machine learning approach to analyse and predict the electric cars scenario: The Italian case." PLOS ONE 18, no. 1 (January 20, 2023): e0279040. http://dx.doi.org/10.1371/journal.pone.0279040.

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The automotive market is experiencing, in recent years, a period of deep transformation. Increasingly stricter rules on pollutant emissions and greater awareness of air quality by consumers are pushing the transport sector towards sustainable mobility. In this historical context, electric cars have been considered the most valid alternative to traditional internal combustion engine cars, thanks to their low polluting potential, with high growth prospects in the coming years. This growth is an important element for companies operating in the electricity sector, since the spread of electric cars is necessarily accompanied by an increasing need of electric charging points, which may impact the electricity distribution network. In this work we proposed a novel application of machine learning methods for the estimation of factors which could impact the distribution of the circulating fleet of electric cars in Italy. We first collected a new dataset from public repository to evaluate the most relevant features impacting the electric cars market. The collected datasets are completely new, and were collected starting from the identification of the main variables that were potentially responsible for the spread of electric cars. Subsequently we distributed a novel designed survey to further investigate such factors on a population sample. Using machine learning models, we could disentangle potentially new interesting information concerning the Italian scenario. We analysed it, in fact, according to different geographical Italian dimensions (national, regional and provincial) and with the final identification of those potential factors that could play a fundamental role in the success and distribution of electric cars mobility. Code and data are available at: https://github.com/GiovannaMariaDimitri/A-machine-learning-approach-to-analyse-and-predict-the-electric-cars-scenario-the-Italian-case.
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Barone, Giovanni, Annamaria Buonomano, Francesco Calise, and Adolfo Palombo. "Natural gas turbo-expander systems: A dynamic simulation model for energy and economic analyses." Thermal Science 22, no. 5 (2018): 2215–33. http://dx.doi.org/10.2298/tsci180109276b.

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Natural gas is typically transported for long distances through high pressure pipelines. Such pressure must be reduced before the gas distribution to users. The natural gas lamination process, traditionally adopted for this scope, may determine hydrate formation which may damagingly affect the system operation. Therefore, in order to avoid such circumstance, a suitable gas preheating is required. On the other hand, the available pressure drop can be recovered through a turbo-expansion system in order to provide mechanical energy to drive electricity generators. In this case a higher gas preheating is necessary. This paper presents a detailed simulation model capable to accurately analyse this process as well as the traditional decompression one. Such new model, implemented in a computer tool written in MATLAB, allows one to dynamically assess the energy, economic and environmental performance of these systems, by also taking into account hourly energy prices and weather conditions. Two turbo-expansion system layouts are modelled and simulated. In particular, the gas preheating is obtained by considering two different scenarios: gas-fired heater or solar thermal collectors. Another novelty of the presented dynamic simulation tool is the capability to take into account the time fluctuations of electricity feed-in and purchase tariffs. Finally, a suitable case study relative to a gas decompression station located in South Italy is also presented. Here, a remarkable primary energy savings and avoided CO2 emissions can be obtained through the examined turbo-expansion systems vs. traditional decompression ones. Results show that the economic profitability of the investigated novel technology depends on the available gas pressure drops and flow rates and on the produced electricity use.
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Більше джерел

Дисертації з теми "Electricity distribution in Italy"

1

Scarsi, Gian Carlo. "Electricity distribution in Italy : microeconomic efficiency analysis of local distributing units with methodological cross-checking." Thesis, University of Oxford, 1998. http://ora.ox.ac.uk/objects/uuid:ca322a0b-7fd0-4a02-a237-bb4b6f02eeda.

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This thesis analyses technical efficiency of local electricity distribution in Italy (1994, 1996) by using both econometric (deterministic frontier, stochastic frontier) and linear programming (Data Envelopment Analysis) tools. Cross-sectional data was examined with respect to (a) ENEL - the Italian electricity monopolist whose restructuring and privatisation is now under way - and its local distribution branches (Chapters 2, 3, and 5); (b) municipal authorities (MUNIs), i.e. town-based electric utilities which sometimes hold franchises for electricity distribution within city limits (Chapters 4 and 5). Estimation results from Chapters 2 and 3 highlighted non-exhaustion of scale economies at sample-mean values. Scope economies between medium and low-voltage distribution were also detected (Ch. 2). Efficiency score series stemming from both econometric and linear programming techniques in Chapters 3 and 5 showed that Southern distributors were relatively under-represented among top units even after allowing for several exogenous environmental variables. The external effects which proved to influence technical efficiency in electricity distribution were consumer density, the percentage of industrial customers, the geographical nature of areas served (metropolitan areas, mountains, etc.), and the interaction between ENEL's units and municipal utilities in those towns featuring ENEL and MUNIs bordering each other. Pooled ENEL-MUNI analysis from Chapter 4 failed to spot any systematic superiority of ENEL's units over municipalities. Generalisation on the ENEL-MUNI efficiency dispute was then discarded, in favour of case-by-case comparison. Paired-samples statistical testing (both parametric and non-parametric) from Chapter 5 showed limited agreement between Stochastic Frontier Estimation (SFE) and Data Envelopment Analysis (DEA) efficiency outcomes. Statistical concordance was more often found when comparing SFE and DEA models sharing the same input-output specification. Again, no apparent superiority of ENEL over MUNIs was found out by DEA linear programs. One-to-one comparisons confirmed that the outcomes were mixed, with ENEL's local branches outperforming MUNIs in metropolitan and (sometimes) rural areas, and MUNIs faring better in medium-sized, Po Valley towns (Northern Italy). Results were not clear-cut for Alpine and rural distributors. The latter however - should be considered on a separate basis in that they will probably need permanent subsidies to meet universal service obligations, irrespective of the future structure of electricity distribution in Italy. Comparable (e.g., urban) units might - on the other hand - be subject to yardstick regulation based upon DEA's 'efficient peer' outcomes. Apart from the main empirical work, this thesis also features institutional and theoretical overviews (Chapters 2 to 5) with relevant literature surveys, a DEA Numerical Appendix (Chapter 5), and a regional map of the Italian territory (end of thesis).
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SOROUSH, GOLNOUSH. "Three Essays in Energy Economics: Regulatory Aspects, Institutions and Innovation." Doctoral thesis, Politecnico di Torino, 2019. http://hdl.handle.net/11583/2742537.

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McFarlane, Andrew Ian. "Aged Electricity Distribution Asset Replacement." Thesis, University of Canterbury. Engineering Management, 2014. http://hdl.handle.net/10092/8941.

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Major segments of the Marlborough Lines Ltd (MLL) 11kV electricity distribution network are positioned within remote areas of the Marlborough region including the Marlborough Sounds, the Awatere and Wairau Valleys and the North Eastern cost of the South Island. The majority of these remote rural lines are due for replacement within the coming 20 years in order to maintain safety and reliability. The increased maintenance costs of operating rural electricity lines and the number of customers they serve often results in the line being uneconomic to operate. This investigation determines the current economical efficiency of the Sounds Feeder, a segment of line in the Marlborough Sounds. The financial, social and regulatory implications of the continued operation of this section of the network after performing distribution renewals are assessed in order to define the likely impacts of wide spread asset renewal to MLL and its customers across the coming 20 years.
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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.
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Neimane, Viktoria. "On Development Planning of Electricity Distribution Networks." Doctoral thesis, KTH, Electrical Systems, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3253.

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Future development of electric power systems must pursue anumber of different goals. The power system should beeconomically efficient, it should provide reliable energysupply and should not damage the environment. At the same time,operation and development of the system is influenced by avariety of uncertain and random factors. The planner attemptsto find the best strategy from a large number of possiblealternatives. Thus, the complexity of the problems related topower systems planning is mainly caused by presence of multipleobjectives, uncertain information and large number ofvariables. This dissertation is devoted to consideration of themethods for development planning of a certain subsystem, i.e.the distribution network.

The dissertation first tries to formulate the networkplanning problem in general form in terms of Bayesian DecisionTheory. However, the difficulties associated with formulationof the utility functions make it almost impossible to apply theBayesian approach directly. Moreover, when approaching theproblem applying different methods it is important to considerthe concave character of the utility function. Thisconsideration directly leads to the multi-criteria formulationof the problem, since the decision is motivated not only by theexpected value of revenues (or losses), but also by theassociated risks. The conclusion is made that the difficultiescaused by the tremendous complexity of the problem can beovercome either by introducing a number of simplifications,leading to the considerable loss in precision or applyingmethods based on modifications of Monte-Carlo or fuzzyarithmetic and Genetic Algorithms (GA), or Dynamic Programming(DP).

In presence of uncertainty the planner aims at findingrobust and flexible plans to reducethe risk of considerablelosses. Several measures of risk are discussed. It is shownthat measuring risk by regret may lead to risky solutions,therefore an alternative measure - Expected Maximum Value - issuggested. The general future model, called fuzzy-probabilistictree of futures, integrates all classes of uncertain parameters(probabilistic, fuzzy and truly uncertain).

The suggested network planning software incorporates threeefficient applications of GA. The first algorithm searchessimultaneously for the whole set of Pareto optimal solutions.The hybrid GA/DP approach benefits from the global optimizationproperties of GA and local search by DP resulting in originalalgorithm with improved convergence properties. Finally, theStochastic GA can cope with noisy objective functions.

Finally, two real distribution network planning projectsdealing with primary distribution network in the large city andsecondary network in the rural area are studied.

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Alvarez, Perez Manuel Alejandro. "Stochastic Planning of Smart Electricity Distribution Networks." Licentiate thesis, Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-60778.

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The penetration of intermittent Distributed Generation (DG) brought additional uncertainty to the system operation and planning. To cope with uncertainties the Distribution System Operator (DSO) could implement several strategies. These strategies range from the inclusion of smart technologies which will increment system’s flexibility and resiliency, to improvements in forecasting, modeling, and regulatory pledge that will facilitate the planning activity. Regardless of the nature of the solutions, they could be collected in a sort of toolbox. The planner will access the toolbox to conform cost effective plans, better able to deal with any uncertainty. The present work will address the problem of distribution system planning under uncertainties, considering smart solutions along with traditional reinforcements, in the short-term lead time up to 3 years ahead. The work will be focused on three aspects that are the cornerstones of this work:  • A planning facilitating strategy: Distribution Capacity Contracts (DCCs).  • A flexibility enabler technology: Energy Storage.  • A binding methodology: Multistage Stochastic Programming. Stochastic dual dynamic programming (SDDP).  Under the present directive of the European Parliament concerning common rules for the internal market in electricity, distribution companies are not allowed to own DG but entitled to include it as a planning option to differ investment in traditional grid reinforcements. An evaluation of the regulatory context will lead this work to consider DCCs as a planning alternative available in the toolbox. The impact of this type of contract on the remuneration of the DG owner will be assessed in order to provide insight on its willingness to participate. The DCCs might aid the DSO to defer grid i ii investments during planning stages and to control the network flows during operation.  Given that storage solutions help to match in time production from intermittent sources with load consumption, they will play a major role in dealing with uncertainties. A generic storage model (GSM) based on a future cost piecewise approximation will be developed. This model inspired by hydro-reservoirs will help assessing the impact of storage in planning decisions. This model will be tested by implementing it in short-term hydro scheduling and unit commitment studies.  To trace a path towards the future of this research work, a discussion on the planning problem formulation, under consideration of the lead time, the expansion options, the smart strategies, and the regulatory framework will be presented. Special focus will be given to multistage stochastic programming methods and in particular to the SDDP approach.
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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.

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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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8

Green, J. P. "Evaluation of electricity distribution system design strategies." Thesis, University of Manchester, 1997. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.617088.

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Commin, Andrew Neil. "Matching renewable electricity supply to electricity demand in Scotland." Thesis, University of Aberdeen, 2015. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=230176.

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The threat of climate change has led to many countries and regions adopting renewable targets. Scotland's is one of the most ambitious, with an aim to generate the equivalent to 100% of its electricity needs from renewable sources by 2020. Scotland has a very large renewable resource, primarily consisting of offshore and onshore wind, tidal stream, wave and hydro power; all of which are characterised by having variable output. Over a long period, such as a year, variability in renewable generation will average out and may meet or exceed total annual demand. This thesis investigates whether matching of demand and generation is possible within a timescale meaningful to electricity system users; that is whether renewable generation can meet electricity demand in any given hour. This was established by using historic data to create an hourly generation hindcast of Scotland's renewable generation over a 30 year climate “normal” period. These outputs are then compared to a hindcast of hourly demand based on observations over the most recent few years. The results demonstrated that it is possible for Scotland to rely entirely upon renewable generation to fulfil demand in any hour of the 30 year hindcast. However, it appears that the renewable capacity and storage currently built or within the Scottish planning system is only sufficient to match demand in 65% of the hours within the hindcast. The hindcast allows judgements to be made as to how 100% of demand could be met most effectively and provides the basis of a coherent planning strategy, with security of supply at its centre. Further wave and tidal stream capacity is shown to be of higher value than additional wind power but in the latter case, addressing the geographical diversity of wind power can enable maximise phasing between sites to increase the security of supply. Importantly this work provides a means of informing decision making about where best to develop wind, wave and tidal resources and what additional storage may be required in order to provide 100% security of supply. The results are also of particular importance to Scotland's renewable generation strategy in the case of assessing where new on- and off-shore wind farms should be developed, as wind is set to dominate Scotland's renewable portfolio for the foreseeable future.
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BONACINA, FAUSTO. "The optimal generation mix for an electricity producer: the case of Italy." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/49725.

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In this work we extend the model of Roques et al. (2008) for the construction of the optimal electricity generation portfolio. In our analysis we consider an electricity producer, who can choose to invest both in renewable and conventional sources. We build portfolios based on the Net Present Value generated by the investment in a particular technology. We use Monte Carlo simulations in order to compute the NPV distributions. As an extension to Roques et al. (2008), we consider the presence of incentives for renewable technologies. We apply our model to Italian data.
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Книги з теми "Electricity distribution in Italy"

1

Karampelas, Panagiotis, and Lambros Ekonomou, eds. Electricity Distribution. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49434-9.

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2

MarketLine, ed. Italy electricity. London: MarketLine, 1995.

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3

Institute, Electric Power Research, ed. Electricity technology roadmap: Electricity supply. Palo Alto, Calif: EPRI, 1999.

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4

Wang, Chengshan, Jianzhong Wu, Janaka Ekanayake, and Nick Jenkins. Smart Electricity Distribution Networks. Edited by Chengshan Wang, Jianzhong Wu, Janaka Ekanayake, and Nick Jenkins. Boca Raton : Taylor & Francis, a CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa, plc, [2017]: CRC Press, 2017. http://dx.doi.org/10.1201/9781315373324.

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5

Lakervi, E. Electricity distribution network design. London: P. Peregrinus on behalf of the Institution of Electrical Engineers, 1989.

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6

1928-, Holmes E. J., and Institution of Electrical Engineers, eds. Electricity distribution network design. 2nd ed. London: Peter Peregrinus Ltd., on behalf of the Institution of Electrical Engineers, 2003.

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7

1928-, Holmes E. J., and Institution of Electrical Engineers, eds. Protection of electricity distribution networks. London: Institution of Electrical Engineers, 1998.

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8

1928-, Holmes E. J., and Institution of Electrical Engineers, eds. Protection of electricity distribution networks. 2nd ed. London: Institution of Electrical Engineers, 2004.

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9

Gers, Juan M. Protection of electricity distribution networks. 2nd ed. London: The Institution of Electrical Engineers, 2004.

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10

1928-, Holmes E. J., and Institution of Electrical Engineers, eds. Protection of electricity distribution networks. 3rd ed. Herts, United Kingdom: Institution of Electrical Engineers, 2011.

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Частини книг з теми "Electricity distribution in Italy"

1

Lewiner, Colette. "Electricity Distribution." In European Energy Markets Observatory, 64–67. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-2753-3_10.

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2

Gómez, Tomás. "Electricity Distribution." In Power Systems, 199–250. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5034-3_5.

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3

Agamah, Simon, and Lambros Ekonomou. "A Methodology for Web-Based Power Systems Simulation and Analysis Using PHP Programming." In Electricity Distribution, 1–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49434-9_1.

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4

Moschakis, Marios N. "Advanced Short-Circuit Analysis for the Assessment of Voltage Sag Characteristics." In Electricity Distribution, 241–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49434-9_10.

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5

Abraham, Rajesh Joseph, and Aju Thomas. "A Genetic Proportional Integral Derivative Controlled Hydrothermal Automatic Generation Control with Superconducting Magnetic Energy Storage." In Electricity Distribution, 267–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49434-9_11.

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6

Pavlatos, C., and V. Vita. "Linguistic Representation of Power System Signals." In Electricity Distribution, 285–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49434-9_12.

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Pal, Kirti, Laxmi Srivastava, and Manjaree Pandit. "Levenberg-Marquardt Algorithm Based ANN for Nodal Price Prediction in Restructured Power System." In Electricity Distribution, 297–318. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49434-9_13.

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Serițan, George, Radu Porumb, Costin Cepișcă, and Sorin Grigorescu. "Integration of Dispersed Power Generation." In Electricity Distribution, 27–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49434-9_2.

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Kyritsis, Anastasios, Nick Papanikolaou, Stathis Tselepis, and Christos Christodoulou. "Islanding Detection Methods for Distributed PV Systems Overview and Experimental Study." In Electricity Distribution, 63–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49434-9_3.

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10

Chatzis, G., S. Livieratos, and P. G. Cottis. "The Use of PLC Technology for Smart Grid Applications Over the MV Grid: The DG Paradigm." In Electricity Distribution, 81–117. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49434-9_4.

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Тези доповідей конференцій з теми "Electricity distribution in Italy"

1

Maggiore, S., M. Gallanti, W. Grattieri, and M. Benini. "Impact of the enforcement of a time-of-use tariff to residential customers in Italy." In 22nd International Conference and Exhibition on Electricity Distribution (CIRED 2013). Institution of Engineering and Technology, 2013. http://dx.doi.org/10.1049/cp.2013.0673.

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2

Delfanti, M., M. S. Pasquadibisceglie, A. Silvestri, and M. Pezzaglia. "Attribution of losses to final customers in Italy: a new model to be applied in presence of dispersed generation." In 20th International Conference and Exhibition on Electricity Distribution (CIRED 2009). IET, 2009. http://dx.doi.org/10.1049/cp.2009.0944.

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3

Di Maio, L., C. Gemme, and P. Gritti. "Performance and refurbishment strategies for protection systems according to new quality requirements from Energy Authority, Enel DK5600 connection requirements and change of neutral earthing of MV distribution networks in Italy." In 18th International Conference and Exhibition on Electricity Distribution (CIRED 2005). IEE, 2005. http://dx.doi.org/10.1049/cp:20051163.

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4

Cazemajou, C., and C. Morzelle. "Gas Turbines Installations for EDF’s Island Grids." In ASME 1991 International Gas Turbine and Aeroengine Congress and Exposition. American Society of Mechanical Engineers, 1991. http://dx.doi.org/10.1115/91-gt-337.

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EDF is responsible for the production and distribution of electricity on the French islands in Europe and overseas, such as: - Corsica (in the Mediterranean), - Martinique (in the Caribbean), - Guadeloupe (in the Caribbean), - Reunion (in the Indian Ocean), - and French Guiana in South America. Technical and economic studies revealed the viability in these regions of single cycle gas turbine technology for supplying peak demand requirements, or providing transitory means of production pending the installation of heavier production units (conventional thermal power plants, diesel generators or hydropower). After consultations with the major European manufacturers, a list of machines with the capacity to meet the generation specifications, and their characteristics, was prepared. On mainland France EDF had equipped its production units with 24 MW Alsthom MS 5000 and MS 5001 gas turbines. These were little used and studies showed the economic viability of transferring these units to island regions. The program finally adopted was to install the following power generation facilities: JARRY SUD (GUADELOUPE): 2 ALSTHOM MS 5001 – 20 MW – 40 MW KOUROU (FRENCH GUIANA): 2 COOPER ROLLS – 13 MW – 26 MW; 1 ROLLS ROYCE – 11 MW – 11 MW LUCCIANA (CORSICA): 2 ALSTHOM MS 5000 – 24 MW – 48 MW LE PORT (REUNION): 2 ALSTHOM MS 5001 – 20 MW – 40 MW POINTE DES CARRIERES (MARTINIQUE): 2 ALSTHOM MS 5001 – 20 MW – 40 MW or total rated power of: 205 MW The technical details, costs and scheduling of these works are described in the paper. Finally, the authors describe the future development prospects for gas turbines in these regions, and especially certain combined cycle projects for Corsica coupled with a proposed Italy-Corsica-Sardinia natural gas link.
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Bialek, J. "Recent failures in US/Canada, Scandinavia and Italy." In IEE Seminar on "How Secure are Britain's Electricity Supplies?". IEE, 2004. http://dx.doi.org/10.1049/ic:20040150.

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Franzo, Simone, Federico Frattini, Vito Manfredi Latilla, Federica Foiadelli, and Michela Longo. "The electricity tariffs reform for the residential market in Italy." In 2017 6th International Conference on Clean Electrical Power (ICCEP). IEEE, 2017. http://dx.doi.org/10.1109/iccep.2017.8004773.

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7

Colasante, Maretta. "Biodiversity and distribution of Iridaceae in Italy." In The Fifth International Conference on the Comparative Biology of Monocotyledons. The New York Botanical Gardens Press, 2017. http://dx.doi.org/10.21135/893275341.013.

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8

Bruno, S., M. La Scala, and G. Gross. "Modeling and simulation of the interconnected see and italy electricity markets." In Energy Society General Meeting (PES). IEEE, 2009. http://dx.doi.org/10.1109/pes.2009.5275475.

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Massi Pavan, Alessandro, and Vanni Lughi. "Photovoltaics in Italy: Toward grid parity in the residential electricity market." In 2012 24th International Conference on Microelectronics (ICM). IEEE, 2012. http://dx.doi.org/10.1109/icm.2012.6471415.

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Smagina, Zemfira Andreevna. "INFORMATION SYSTEM FOR ELECTRICITY DISTRIBUTION." In Российская наука: актуальные исследования и разработки. Самара: Самарский государственный экономический университет, 2022. http://dx.doi.org/10.46554/russian.science-2022.02-1-60/63.

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Звіти організацій з теми "Electricity distribution in Italy"

1

Skone, Timothy J. Electricity Distribution (Primary). Office of Scientific and Technical Information (OSTI), April 2013. http://dx.doi.org/10.2172/1509156.

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2

Skone, Timothy J. Electricity Distribution (Secondary). Office of Scientific and Technical Information (OSTI), April 2013. http://dx.doi.org/10.2172/1509157.

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3

Graf, Christoph, Federico Quaglia, and Frank Wolak. Simplified Electricity Market Models with Significant Intermittent Renewable Capacity: Evidence from Italy. Cambridge, MA: National Bureau of Economic Research, May 2020. http://dx.doi.org/10.3386/w27262.

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4

Pena, Ivonne, Michael Ingram, and Maurice Martin. States of Cybersecurity: Electricity Distribution System Discussions. Office of Scientific and Technical Information (OSTI), March 2017. http://dx.doi.org/10.2172/1347682.

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Singh, Kavinesh, Andy Philpott, and Kevin Wood. Column-Generation for Design of Survivable Electricity Distribution Networks. Fort Belvoir, VA: Defense Technical Information Center, August 2004. http://dx.doi.org/10.21236/ada486857.

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Galen, P. S. Electricity distribution industry restructuring, electrification, and competition in South Africa. Office of Scientific and Technical Information (OSTI), July 1997. http://dx.doi.org/10.2172/515547.

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Jackson, Roderick K., Omer C. Onar, Harold Kirkham, Emily Fisher, Klaehn Burkes, Michael R. Starke, Olama Mohammed, and George Weeks. Opportunities for Efficiency Improvements in the U.S. Electricity Transmission and Distribution System. Office of Scientific and Technical Information (OSTI), April 2015. http://dx.doi.org/10.2172/1185870.

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Shirley, W., R. Cowart, R. Sedano, F. Weston, C. Harrington, and D. Moskovitz. State Electricity Regulatory Policy and Distributed Resources: Distribution System Cost Methodologies for Distributed Generation. Office of Scientific and Technical Information (OSTI), October 2002. http://dx.doi.org/10.2172/15001123.

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Rose, A., and O. Frias. Income distribution impacts of changes in Western Area Power Administration electricity prices. Final report. Office of Scientific and Technical Information (OSTI), June 1993. http://dx.doi.org/10.2172/10189277.

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Shirley, W., R. Cowart, R. Sedano, F. Weston, C. Harrington, and D. Moskovitz. State Electricity Regulatory Policy and Distributed Resources: Distribution System Cost Methodologies for Distributed Generation; Appendices. Office of Scientific and Technical Information (OSTI), October 2002. http://dx.doi.org/10.2172/15001124.

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