Energy Market

The energy system decarbonization leads to a decentralization of generation and flexibility. Among the new concepts to integrate the distributed flexibility are local energy markets. While a broad range of research investigates local energy markets on a distribution grid level in detail, research on their system impact has been limited. Therefore, we develop a framework to investigate different configurations of local markets and operation of distributed energy resources and their interaction with the wholesale markets. This framework is applied to a pan-European case study with detailed bottom-up modeling of local energy markets in France and Germany. Additionally, transmission grid simulations are carried out to investigate the impact of local trading on grid congestions. Our results show that a direct coordination of distributed flexibility within the wholesale market is more efficient than a preference of local trading. Nonetheless, local energy markets can be used as an incentive for expansion of distributed flexibility as well as a way to break down the complexity of coordinating millions of distributed assets in a single market. Additionally, our results show that local trading relieves the transmission grid.

The energy system decarbonization leads to a decentralization of generation and flexibility. Among the new concepts to integrate the distributed flexibility are local energy markets. While a broad range of research investigates local energy markets on a distribution grid level in detail, research on their system impact has been limited. Therefore, we develop a framework to investigate different configurations of local markets and operation of distributed energy resources and their interaction with the wholesale markets. This framework is applied to a pan-European case study with detailed bottom-up modeling of local energy markets in France and Germany. Additionally, transmission grid simulations are carried out to investigate the impact of local trading on grid congestions. Our results show that a direct coordination of distributed flexibility within the wholesale market is more efficient than a preference of local trading. Nonetheless, local energy markets can be used as an incenti...

The context and the policy objective guiding the liberalisation of the electricity industry have changed significantly over recent decades. Policy priorities in favour of decarbonisation and maintaining security of supply have taken centre stage on the policy agenda in many countries. The emergence of new decentralised and variable technologies and the change toward fixed cost technologies have profound implications for market dynamics. Yet the design of liberalised electricity markets has largely failed to evolve and be reconciled with these changes as well as with policy objectives. As a result the initial "energy market" model is being questioned and a number of reforms have been implemented around the world. The Chaire European Electricity Markets (CEEM) organised a conference at the Université Paris-Dauphine University in July 2015 in order to improve our understanding of the evolution required for electricity markets to satisfy the competing objectives of sustainability, security of supply and competitiveness, and to adapt to other changes including new technologies and change in the industry cost structure. For two days, leading scholars from Europe and the Americas discussed the issues raised by market failures and the short-comings of the initial "target model" market design. One of the key issues that emerged from the discussion is the question of the ability of market price signals to generate sufficient and adequate (i.e. in the optimal generation mix) investment, given the series of market and regulatory imperfections that prevail in current electricity markets, and the many types of policy interventions. Despite a great variety of points of view on specific issues, a consensus emerged that adding ad hoc "patches" to energy-only markets to address some market or regulatory failures and/or support some technologies is not a sustainable option. Reconciling public policy objectives and free price formation in electricity markets requires the theorisation and implementation of "hybrid market" regimes capable of reconciling public policy objectives and free price formation in a comprehensive and forward-looking fashion. The five articles in this special section all cover different aspects of these "hybrid market" regimes in order to respond to the issues raised by tensions between initial objectives of market liberalisation and the long-term policies goals of decarbonisation whilst maintaining security of supply. Since the liberalisation of the electricity industry in the 1990s in OECD countries, the underlying policy objectives have changed. The objective of the initial reforms was to improve the efficiency of the electricity industry which was then organised around public-or private vertically integrated monopolies. The rise of information technology and combined cycle gas turbines (CCGT) enabled fragmentation of the value chain possible and the introduction of competition in retail and production activities. In the European Union, the liberalisation was also driven by the objective of creating an internal integrated market as the networks were sufficiently developed to facilitate competition between various producers on a large territorial scale. Investment was facilitated by the low capital-intensive profile of CCGT, and there was not much focus on security of supply as often most markets were in an overcapacity situation. In this context, the main focus of the initial reforms was on the efficient functioning of energy markets and the extension of retail competition in industrialized countries with mature demand. The experience in some developing countries with significant growth of demand and need for new investment in the early 2000s casted some doubts on the ability of energy markets to provide timely and efficient investment incentives. This led a number of Latin American countries, for instance, to reform the initial market designs and adopt capacity remuneration mechanisms (CRM) and/or auctions for long term contracts to shift risks to consumers. Since the mid-2000s, new long term policy priorities have emerged in Europe and the US, as well as in other OECD countries: the decarbonisation of the electricity industry and security of supply. This has profound implications for the functioning and optimal design of electricity markets. Priority is given to investing in RES and low-carbon technologies and in peaking units and back-up technologies, whose share of CAPEX per MWh in the cost structure is high, casting a new light on the relationship between market design and the need to allocate risks efficiently in order to minimize financing costs. The use of long term arrangementsfeed in tariffs (FITs), fee-in-premium (FIPs), and contracts for difference (CfDs)to promote variable RES has enabled large-scale deployment of RES production with low variable cost. But as a result, the investment and coordination signals by market prices have been largely undermined, which raises a number of questions regarding the ability of the current market design to provide adequate operational and investment incentives. For this reason the market architectures of electricity markets must evolve and a number of countries have embarked on wide ranging reforms of their electricity markets. The energy, reserves and ancillary markets need to be improved to provide better scarcity signals in the short term, whilst mechanisms need to be introduced to facilitate risk transfers and provide long term signals to investors. Downstream, electricity demand must be made more priceresponsive to facilitate hourly adjustments and physical supply-demand equilibrium. On the grid side, price signals are needed which better indicate supply constraints in order to provide locational signals to new resources, and changes in the regulation of network tariffs are needed to facilitate their transformation into smart grids. In the conclusion of the workshop, the overarching question that remained was whether the different reforms point toward a common direction and reveal a structural mutation of the market regime of the power industry. Indeed we observe a great variety of reforms in response to regulatory

Climate change as a challenge we all are facing, varying degree of economic development as a result of COVID-19, the volatility in energy prices and political as well as other factors, most countries have restructured their electricity markets in order to facilitate the use of green renewable energy. The right energy mix in a period of energy transformation is the best strategy for achieving reduction of carbon emissions. Bulgaria is a special case because it has expanded the use of solar and wind energy exponentially, without conducting an adequate preliminary forecast analysis and formulating a parallel strategy for the development and expansion of the energy storage infrastructure. In this regard, the article is focused on how the power energy market is structured with the increasingly large-scale and global penetration of renewable energy sources as primary energy sources, observing several key factors influencing the energy transition. Due to the cyclical nature of energy production and the necessity for a smooth and efficient transition, a long-term seasonal storage plan should be considered. Furthermore, solar energy production facilities have a greater share of installed power, but wind power facilities generate a roughly equivalent amount of electric energy over the course of a year. One of the aims of this research is to discover an appropriate model for predicting the electricity output of wind and solar facilities located in Bulgaria that can be used to ease the transition process. Based on thorough data analysis of energy production over the past 11 years and 5 months, our findings suggest that a SARIMA model might be appropriate, as it takes into account the seasonal cycles in the production process.

The growing concern for the need to reduce the gap between power generated and power consumed in Nigeria is on the increase. Many measures and policy have been geared by Nigeria Electricity Regulatory Commission and Ministry of Power to revamp the generation aspect of the country power sector but the impact is yet to be felt as the amount of power still generated is far below par compared to other countries. Nigeria average power generation stands at an average of 5800MW. With the call to see the need of exploring Distributed generation in augmenting the power generated, this paper reviews the benefits and challenges of integrating Distributed generation into the present power system distribution network may pose.

In this work is proposed the design of a system to create and handle Electric Vehicles (EV) charging procedures, based on intelligent process. Due to the electrical power distribution network limitation and absence of smart meter devices, Electric Vehicles charging should be performed in a balanced way, taking into account past experience (spread in a social network). In order to allow information exchange and to help user mobility, it was also created a mobile application to assist the EV driver on these processes. This proposed Smart Electric Vehicle Charging System uses Vehicle-to-Grid (V2G) technology, in order to connect Electric Vehicles and also renewable energy sources to Smart Grids (SG). This system also explores the new paradigm of Electrical Markets (EM), with deregulation of electricity production and use, in order to obtain the best conditions for commercializing electrical energy.

Purpose: This paper sets out to explore the relationships between a sustainable energy market and a sustainable financial market and energy market. The specific research objectives were: to explore whether sustainable finance only correlates with a sustainable energy market, or perhaps this relationship also exists with the traditional energy market, to identify the groups of countries for which there are correlations between the study categories. Design/Methodology/Approach: The empirical analysis is based on data from 2008, 2014, and 2018, as related to the energy market, sustainable energy, and sustainable finance for 28 European countries belonging to the OECD. A taxonomic development measure based on the reference method in the positional approach using the Weber median was used. Findings: The results confirmed the existence of a positive correlation between the energy market and the financial market in a sustainable approach. No such relationship was demonstrated for all three categories at the same time, i.e. energy market, sustainable energy market and sustainable finance. Practical Implications: This research is important for the policies of financial institutions and financial markets from the point of view of developing products and services for sustainable financing, so as to change the structure and improve the effects related to social responsibility (ESG risk reduction). Originality/value: This study examines whether relationships exist between a sustainable energy market and sustainable finance and the energy market in the traditional approach.

This article models the dependence risk and resource allocation characteristics of two 20-stock coal-uranium and oil-gas sector portfolios from the Australian market in the context of the global financial crisis of 2008-2009. The modeling framework implemented consists of pair vine copulas and, linear and nonlinear portfolio optimization methods with respect to five risk measures. The paper's objectives are to find out if the oil and gas stocks are riskier than the coal and uranium stocks, to identify the optimization method and risk measure that produce the best risk-return trade-off, to recognize the stocks in which the optimal weight allocations converge on average, and to acknowledge the vine copula model that best accounts for the overall dependence of the energy portfolios. The research findings indicate that the oil stocks have higher dependence risk than the coal, uranium and gas stocks in financial crisis periods. The higher risk of the oil stocks is confirmed by the larger concentration of symmetric and asymmetric dependence they have in the negative tail. The canonical vine (c-vine) copula model is observed to better capture the overall dependence of the energy portfolios. The combination of a pair c-vine copula and nonlinear portfolio optimization produces the highest return relative to risk. The optimal weight allocations converge on average in some stocks.

Na marginesie Niedawno podjęto w Polsce, za zgodą Komisji Europejskiej [EC, C(2018) 601 final], próbę zaimplementowania dwutowarowego rynku energetycznego, składającego się z rynku energii elektrycznej oraz rynku mocy [Dz.U., 2018]. Wprowadzenie takiego dwutowarowego rynku energetycznego niesie ze sobą pewne potencjalne korzyści dla rachunkowości wzrostu gospodarczego. Jednocześnie jednak może powodować pewne asymetrie w relacjach z zagranicą, szczególnie w sytuacji, gdy sąsiadujące kraje takiego rynku nie wprowadzają i w najbliższym czasie wprowadzać nie zamierzają, co może być pewnym wyzwaniem dla regulatora.

In Poland, an attempt was made to implement a dual-energy market, consisting of the electricity and power market, with the consent of the European Commission. Introduction such a dual-energy market brings potential benefits to economic growth. However, it can cause asymmetries in relations with foreign countries, especially in a situation where neighboring countries do not introduce such a market. The inspiration for the discussion on this subject is the book by Dorota Niedziółka, The functioning of the Polish energy market, Difin, Warsaw 2018. According to the author of the article, this book provides a lot of very valuable information about the energy market in Poland, with the chapter devoted to the electricity market standing out particularly positively compared to other chapters.

Gateway to use HART transmitters from a DeviceNet network Este artículo demuestra la viabilidad de compatibilizar dos protocolos industriales con características muy diferentes, mediante la implementación de una interfaz hardwaresoftware. HART es un protocolo de muy baja velocidad que usa el paradigma maestroesclavo, no orientado a la conexión y con un conjunto de comandos definidos, mientras que DeviceNet tiene una velocidad al menos 100 veces superior, que funciona con el modelo productor-consumidor, es orientado a la conexión y no utiliza comandos sino objetos. El desarrollo se soporta en un sistema embebido TINI (Tiny InterNet Interface), programable en Java. La pasarela (gateway) actúa como esclavo de una red DeviceNet y como maestro de una red HART. Este novedoso equipo puede ser empleado para incluir equipos HART en procesos de manufactura que requieran pocas variables continuas.

The near- and long-term prospects for increasing the share of bioenergy in Poland's energy supply, and the policy implications, are assessed here. Bioenergy has played a negligible role in the Polish energy balance so far, accounting for perhaps 4 per cent (165 PJ) of primary energy supply (3900 PJ), mainly as firewood in the domestic sector. In 2001, Poland adopted targets to increase the share of renewable energy to 7.5% in 2010, in accordance with the EU accession treaty, and 14% in 2020. Biomass has been identified as the most promising and important renewable energy source in this time frame. We conclude that the most promising applications of bioenergy is found in small- and medium-scale applications for heat and CHP production. Co-firing with coal is an option for reaching the target on time, but also for creating demand and facilitate the development of a market for bioenergy. However, there is yet no coherent and effective policy for supporting the bioenergy development...

In this paper, the author are making an overview of the energy market in European Union (EU) countries. The present EU energy market and its evolution after price liberalization decision is also analyzed in this article. The steps made to assure national energy markets integration and the evolution of energy consumption and prices are also presented in the manuscript. The dependence of Russian imports is an important issue nowadays in the EU and the main conclusion of the paper is that the governments should develop more the renewable energy systems in order to decrease the dependence on the Russian energy.

Fossil fuels helped Putin build military power and attack Ukraine. Coal, gas and oil are being used by Putin’s regime as weapons against the countries that are contractors and consumers of Russian fuels. The aim of this paper is to present a methodology using Big Data analysis and to demonstrate the results, as well as to show trends and developments in relation to the response to the crisis on the fossil fuel market. At the same time, the EU institutions have taken on the burden of conducting energy policy in Europe. The research carried out, including the cluster analysis and the analysis of the variability of trends in relation to the real conditions in the market for strategic energy resources, indicates that the European Union (as an institution) has taken over the burden of policy-making in this area and national policies are far less important (indicating their weakness).

Energy is a fundamental factor for economic development. Although in recent years there is a development in studies on an energy economics they are focused on specific energy sources. In this study natural gas, electricity and oil consumption which are the energy sources that the greatest market share of world and Turkey are investigating. In this investigation multivariate linear regression model is used. MVR model is a system of linear regression equations having the same set of independent variables. In this model within-equation, linear restrictions are testable on an equation-by-equation basis using a standard F test. The aim of the study is estimating demand of these three energy sources which are mentioned above. For this purpose, the regression model estimated which has a natural gas, electricity and oil consumption as dependent variables and price of these sources, income and population as independent variables by using 2001:01-2010:06 monthly data. Except for oil prices, c...

The shift towards decentralized and sustainable energy frameworks is progressively propelled by innovations in technology and the imperative for energy democratization. Blockchain technology is a viable approach for facilitating peer-to-peer (P2P) energy trading, thereby diminishing dependence on intermediaries while augmenting transparency, security, and efficiency within energy transactions. Nevertheless, the application of blockchain-enabled energy trading continues to be constrained in Indonesia due to regulatory, technical, and economic challenges. This study aims to develop a smart implementation framework for integrating blockchain into P2P renewable energy trading in Indonesia. A qualitative research approach is employed, incorporating content analysis and thematic analysis of policy documents, technical reports, and stakeholder interviews. A blockchain simulation model is also designed to evaluate feasibility, efficiency, and scalability. The findings highlight that blockchain can significantly enhance renewable energy adoption by facilitating direct energy exchanges among prosumers, improving grid resilience, and reducing transaction costs. The proposed framework outlines essential components such as smart contracts, digital tokens, decentralized ledgers, and regulatory compliance mechanisms. Case studies from global implementations, including Power Ledger in Australia and LO3 Energy in the U.S., demonstrate the viability of blockchain-based energy trading. The study concludes that while blockchain has strong potential to transform Indonesia's energy landscape, successful implementation requires supportive policies, infrastructure investment, and public awareness. Future research should focus on optimizing smart contracts and developing consensus mechanisms tailored to Indonesia's regulatory and market conditions.

The recent liberalisation of the German energy market forced the energy industry to develop and install new information systems to support agents on the energy trading floors in their analytical tasks. Besides classical approaches of building a data warehouse to give insight into the time series to understand market and pricing mechanisms it is crucial to provide a variety of external data from the web. Weather information as well as political news or market rumors are relevant to give the right interpretation to the variables of a volatile energy market. Starting from a multidimensional data model and a collection of buy and sell transactions a data warehouse is built that gives analytical support to the agents. Following the idea of web farming we harvest the web, match the external information sources after a filtering and evaluation process to the data warehouse objects and present this qualified information on a user interface where market values are correlated with those external sources over the time axis.

The objective of this research is to show the capacity of Self-Organizing Maps to classify customer and their response potential from electrical demand databases with the help of Non-Parametric Estimation and Physically Load Based modelling as support tools. The searching of customer suitability is focussed to real time products, whose interest is growing in developed countries. In this way customer demand and response have been tested and compared with energy price curves extracting patterns from these curves. Results show the capability of this approach to improve data management and select coherent policies to accomplish cleared demand offers amongst different prices scenarios in an easy way.

has adversely affected all the nations and all the sectors of all nations. However, the effect of the same on all the sectors of the economy need not be uniform. Moreover, the severity of impact need not be the same across consequent waves. Knowing the severity of the impact across the waves as well as across the time periods shall be quite useful for the purpose of policy formulation. ARCH modelling helps us to gauge the intensity of shocks sustained across the sectors through heteroscedasticity which can be read as a proxy for shock. To understand the severity of shock across the sectors, the share value of the prominent companies across the sectors have been taken as a proxy for their performance. Evaluating the severity of shocks across the sectors shall help the government to note which sector needs greater support so as to create conducive fiscal and monetary initiatives to enable the economy to achieve the state of normality. This paper is designed to bridge the aforementioned research gap.

Fossil fuels helped Putin build military power and attack Ukraine. Coal, gas and oil are being used by Putin’s regime as weapons against the countries that are contractors and consumers of Russian fuels. The aim of this paper is to present a methodology using Big Data analysis and to demonstrate the results, as well as to show trends and developments in relation to the response to the crisis on the fossil fuel market. At the same time, the EU institutions have taken on the burden of conducting energy policy in Europe. The research carried out, including the cluster analysis and the analysis of the variability of trends in relation to the real conditions in the market for strategic energy resources, indicates that the European Union (as an institution) has taken over the burden of policy-making in this area and national policies are far less important (indicating their weakness).

Local energy markets (LEMs) are utilized in a bottom-up power systems approach for reducing the complexity of the traditional, centralized power system and to enable better integration of decentralized renewable energy resources (RES). Peer-to-peer (P2P) energy trading creates opportunities for prosumers to trade their RES with other prosumers in the LEM. Although several scenarios were proposed in the literature for modelling P2P energy trading, there is still a gap in the literature considering the heterogeneous characteristics of prosumers' bidding preferences during P2P matching in the LEM. In this paper, we present heterogeneous characteristics of bidding preferences for prosumers considering energy quantity, bid/offer price, geographic location, location of agents on the local community and cluster welfare. Moreover, this paper proposes an advanced clustering model for P2P matching in the energy community considering the heterogeneous characteristics of bidding preferences for prosumers. For evaluating our proposed model performance, two German real case scenarios of a small and large communities were studied. The simulations results show that using price preference, as the criterion for clustering, offers more technical and economic benefits to energy communities compared to other clustering scenarios. On the other hand, clustering scenarios based on location of prosumers ensure that energy is traded among prosumers who are closer to each other.

This work proposes a organization-based Multi-Agent System that models Local Electricity Market (MASLEM). A bottom-up approach is implemented to manage energy in this work. In this context, agents are able to connect to each other and the power grid to transact electrical energy, and manage their inside electrical energy independently. A Demand Response Program (DRP) based on Indirect Load Control (ILC) method is also used. The performance of our work is evaluated through an Agent Based Modeling (ABM) implementation.

We demonstrate progress on the deployment of two sets of technologies to support distribution grid operators integrating high shares of renewable energy sources, based on a market for trading local energy flexibilities. An artificial-intelligence (AI) grid modelling tool, based on probabilistic graphs, predicts congestions and estimates the amount and location of energy flexibility required to avoid such events. A scalable timeseries forecasting system delivers large numbers of short-term predictions of distributed energy demand and generation. We discuss the deployment of the technologies at three trial demonstration sites across Europe, in the context of a research project carried out in a consortium with energy utilities, technology providers and research institutions.

This study presents a possible process of simulating power plant generation planning. The process combines expected overall industry costs, associated cost uncertainty, and expected CO 2 emissions for different generations, variations of future fossil fuel costs, carbon prices, plant investment costs, and demand, including price elasticity impacts. Uncertainty in the decision stems from the elasticity of prices of fuel and electricity. The aim of this paper is to apply fuzzy numbers to power generation planning and to use a Monte Carlo simulation to check. Simulations are demonstrated through a case study of an electricity industry with coal and lignite, combined cycle gas turbines, and supercritical boilers facing future uncertainties. The same simulation was used in planning the generation of electricity from wind, solar, and hydro energy. Comparing the results, decisions were made about the profitability of investments in renewable energy. Based on the results, it can be concluded that the use of fuzzy numbers is a simple and flexible approach to planning and that it can be a serious competitor compared to other methods of planning.

The diffusion of distributed energy resources (DERs) has changed the supply-demand balance of power systems. One option to modernize the management of the electricity distribution is to operate the distribution system with interconnected micro-grids (MGs). However, the MG participation in wholesale energy and ancillary service markets creates several challenges in the interactions among the energy market managing entities. To solve these problems, local energy markets (LEMs) have been proposed, where the MGs can trade energy with each other under the management of the LEM manager (LEMM) to minimize their operation cost. In this paper, a local energy market is modeled for multi-MGs (MMGs) to minimize the operation cost of MGs individually and their social welfare in cooperation with each other. In such model, the optimal scheduling of the DERs in each MG is done through the market clearing process. To investigate the effectiveness of the proposed approach, the local energy market is applied to a distribution network with three MGs.

Table of contents Acknowledgements XV List of abbreviations XVII Table of cases XXI Table of legislation XXIII CHAPTER 1: INTRODUCTION 1 INTRODUCTION 1.1 Topic and Structure 1.2 Brexit 2 AIM, SCOPE, AND RESEARCH QUESTIONS 2.1 Aim and Scope 2.2 Research Question(s) and Research Path 2.3 Normative Criteria in Exploring the Research Question 2.3.1 Brexit Objectives A) Objectives expressed during the referendum campaign B) Objectives during the Brexit negotiations C) Energy-Specific Brexit Objectives of the UK Government D) Brexit Objectives in this manuscript 2.3.2 Legal Certainty A) Legal Certainty in English law B) Legal Certainty in EU law C) Legal Certainty in international law D) Meaning of Legal Certainty in this manuscript 2.3.3 Effective Implementation A) Effectiveness B) The concept of Implementation C) Effective Implementation in this dissertation 2.3.4 The normative criteria as intrinsically linked criteria 2.4 Market, Sector, and Industry 2.4.1 The energy sector 2.4.2 The energy market 2.4.3 The (energy) industry 3 METHODOLOGICAL FRAMEWORK VIII TAKING BACK CONTROL OF THE ENERGY SECTOR? 4 RELEVANCE 4.1 Societal Relevance 4.2 Scientific Relevance 4.2.1 The scientific debate on Brexit: State of the art 4.2.2 The scientific debate on Brexit and energy: State of the art A) Policy B) Economic perspectives C) Legal aspects of energy and Brexit D) Grey literature on Brexit 4.2.3 The scientific debate on EU energy law: State of the art 4.2.4 Adding to the scientific debate on Brexit and the energy sector 5 THE NORMATIVE MATERIAL AND GEOGRAPHICAL SCOPE OF THIS DISSERTATION 5.1 Normative Background 5.1.1 EU law 5.1.2 UK law A) Legislation to implement the Brexit process and/or agreements B) Consequential legislation C) Repeal of European Communities Act D) Retained EU law E) EU law falling away F) Constitutional and legislative consequences specific to Northern Ireland 5.1.3 Irish law 5.1.4 Policy notices 5.1.5 International agreements A) Withdrawal Agreement B) TCA C) EU-UK Nuclear Agreement

In 2013, the Mexican Constitution was amended to allow private firms to participate in the energy sector market. Consequently, the energy reform opened the energy market to private investors, ending the state monopoly of PEMEX and CFE. This article aims to assess the impact of the 2013 Mexican Energy Reform on energy household consumption and, if proven effective, explore its potential to help achieve SDG 7. This longitudinal study gathered data before and after the energy bill reform, from 2012 to 2018, with a non-experimental design. Data analysis to determine the effect of the price variance was estimated through price elasticities of demand, and a logarithmic model was used to determine the relationship between the price and cost of electricity, gas, and fuel. Findings suggest that the 2013 Mexican Energy Reform led to an increase in energy prices that, on the one hand, reduced the consumption of energy generated using fossil hydrocarbons but, on the other hand, affected the por...

This paper aims to give an overview of the Spanish Electric Market. This energy market is liberalized and complex due the new and modified rules along time. Due these circumstances the hourly energy prices may vary tremendously. The goal of this work is to analyze in detail the generation technologies, their strategies and energy mix to gain awareness and knowledge to evaluate energy price fluctuations. Two methods are used to forecast in different time horizons: ARIMAX and NARX. Both methods are homologous, using historical energy prices and optionally an explanatory variable. Three options are studied: no explanatory, energy demand and competitive market. Once the models are developed and trained, the results achieved are helpful to understand further changes in the market. These energy forecasts are competent to schedule energy generation and/or consumption.

This article models the dependence risk and resource allocation characteristics of two 20-stock coal-uranium and oil-gas sector portfolios from the Australian market in the context of the global financial crisis of 2008-2009. The modeling framework implemented consists of pair vine copulas and, linear and nonlinear portfolio optimization methods with respect to five risk measures. The paper's objectives are to find out if the oil and gas stocks are riskier than the coal and uranium stocks, to identify the optimization method and risk measure that produce the best risk-return trade-off, to recognize the stocks in which the optimal weight allocations converge on average, and to acknowledge the vine copula model that best accounts for the overall dependence of the energy portfolios. The research findings indicate that the oil stocks have higher dependence risk than the coal, uranium and gas stocks in financial crisis periods. The higher risk of the oil stocks is confirmed by the larger concentration of symmetric and asymmetric dependence they have in the negative tail. The canonical vine (c-vine) copula model is observed to better capture the overall dependence of the energy portfolios. The combination of a pair c-vine copula and nonlinear portfolio optimization produces the highest return relative to risk. The optimal weight allocations converge on average in some stocks.

For the purpose of the EU-DEEP project, a European co-funded project, which focuses on the European Energy market, a prototype was studied and developed for the management of resources that is based on transaction techniques. That is to say, the prototype examines all the possible cases and in order to make the decision, for the energy management system, which generator to use at a particular time depending from the result of negotiation with market terms using agent technologies between the energy managing system and the participating generator. The purpose of this study was to investigate the models of negotiation, the Software Agents with platforms as the JADE, as well as the requirements of the system and to develop a prototype and evaluate it.

The Treaty establishing the Energy Community in Southeastern (S.E.) Europe (2005), aims to facilitate the creation of a common, competitive energy market in the region. However, the signatory countries have not advanced in the same pace, to implement this undertaking. This paper ranks the nine Energy Community countries, according to their prospects for integration into a regional competitive wholesale gas market, using a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The method evaluates the state of technical and institutional framework and the actual functionality of their markets. Sensitivity analysis is used to examine the robustness of the final results.

The Treaty establishing the Energy Community in Southeastern (S.E.) Europe (2005), aims to facilitate the creation of a common, competitive energy market in the region. However, the signatory countries have not advanced in the same pace, to implement this undertaking. This paper ranks the nine Energy Community countries, according to their prospects for integration into a regional competitive wholesale gas market, using a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The method evaluates the state of technical and institutional framework and the actual functionality of their markets. Sensitivity analysis is used to examine the robustness of the final results.

Primeiramente, gostaria de agradecer aos meus pais Silas Eduardo Porte e Josiane Helena Alves Porte e a toda minha família, os quais me proveram os recursos econômicos e incentivos psicológicos para o desenvolvimento deste estudo. Em seguida agradeço aos amigos Luis Santos Proença e Silvia Grade, os quais me acolheram na cidade do Porto e estiveram sempre a disposição em eventuais necessidades durante o ano em que passei em

The primary focus of this paper is on favorable geographical and geopolitical position of Ukraine which provides good opportunities to unlock a vast nation’s potential for further sustainable socioeconomic development and efficient energy supply to all sectors of the national economy and the society. It is emphasized that Ukraine is one of the world's largest transporters of fuel and energy resources (FER) to Europe. This is confirmed by the availability of large coal and uranium reserves, a well-developed infrastructure for the transportation of oil, gas, electrical and thermal energy sources as well as installed capacity of power plants which is sought to ensure and meet all future needs of the country's economy for primary energy. Given the insufficiency of Ukraine's own oil and gas reserves, the research hypothesis is the need to harness the potential of diversification of primary energy supply, to promote energy efficiency methods and tools as well as to apply the l...

In the present paper we study the statistical properties of the Italian daily electricity load market, by mean of different statistical methods, such, e.g., the exponential smoothing model, the ARMA-ARIMA model and the ARIMA-GARCH model, also providing results about the goodness of each of the proposed approaches. Moreover, we show how the aforementioned models behave if exogenous regressors, as the day of the week or the temperature, are additionally taken into account. Analysed methods are then exploited to perform the one-day ahead energy load prediction, where the main focus is on guessing the right sign of the energy load unbalance.

In this paper we go over the literature that exists on the evolution of sustainability, development and corporate social responsibility (CSR) concepts. In addition, we identify the main competitive advantages for companies in the implementation of CSR, which are so crucial for their evolution and survival. Our main goal is to align sustainability with social responsibility actions. To do so, we obtain a new concept, the corporate citizen. We believe that its application based on the holistic paradigm can solve current and future concerns related to sustainable development, and the company can obtain competitive advantages.

Pumped storage hydroelectricity is the most natural and almost the only bulk energy storage technology available today. Due to the variability of energy demand, and recently also of the supply side of the energy market, there is a need to compensate these differences. In market reality this is usually done on the so-called balancing market where energy prices are significantly higher than on the power exchange market. In this paper we introduce a mathematical model for simulating the operation of photovoltaic-powered pumped storage hydroelectricity along with an optimization model and a procedure for operation on the balancing market. A simulation was performed based on data covering the year 2015 with an hourly time step. The results from the proposed approach were juxtaposed with an optimal solution generated from the optimization model.

In this paper, the author are making an overview of the energy market in European Union (EU) countries. The present EU energy market and its evolution after price liberalization decision is also analyzed in this article. The steps made to assure national energy markets integration and the evolution of energy consumption and prices are also presented in the manuscript. The dependence of Russian imports is an important issue nowadays in the EU and the main conclusion of the paper is that the governments should develop more the renewable energy systems in order to decrease the dependence on the Russian energy.

Complementarity models can represent the simultaneous optimization problems of one or several interacting decision-makers, and thus they have become an increasingly important and powerful tool for formulating and solving bottom-up energy market models. This paper provides an overview of the full range of complementarity-based formulations and how these can be applied to assist the different market participants and organizations with their decision-making processes. To this end, the first part of the paper introduces the mathematical formulation of some basic complementarity models, which are illustrated by highly simplified but illustrative energy market applications. Considering these models, the second part of the paper is devoted to describing in broad terms four areas of their potential application: electricity markets, emission markets, natural gas markets and economies comprising several interacting markets.

This paper presents a stochastic linear programming model that can be used for pricing in electrical energy and reserve markets. It addresses capacity, energy, and reserve dispatch problems that may arise from n-1 contingency scenarios. Possible market solutions focusing on generator compensation using realtime, day-ahead, and hybrid schemes are enumerated, along with opportunities for consumer pricing and transmission costing. This model is illustrated on a 6-bus test system as well as a larger 66-bus system representing the Ontario network. A key difference among schemes is the degree of risk to the generators, measured by variance in profit. Index Terms-Electricity markets, energy and reserve pricing, 1 contingency criterion, operating reserves, stochastic optimization. NOMENCLATURE The symbols used here follow the economic tradition of using for price and for quantity. A. Sets and Indices Scenario. Base scenario (most probable/ zero contingency). Actual (real-time) scenario. Set of scenarios. Node. Set of nodes in network.

Thermal solar power plants operating in a day-ahead market scheme aim to maximize the solar energy captured in the solar collector fields and the electric energy revenue in the power block according to the energy tariff. Classic control strategies are not able to obtain good performance for this kind of framework because of the variability of the energy tariff profile over the days. In this context, this work presents the assessment of the potential of an optimal controller to increase the profitability of the plants. Simulation results with energy tariffs and meteorological data from Spain are presented in order to illustrate the performance of the methodology. Finally, a comparative study with a classic control strategy shows the improvements in the energy revenue produced in this scenario.

e European Union is facing the highest natural gas prices in 15 years, owing largely to an upward trend in electricity prices, which is also on an uphill curve. However, the rise in electricity and natural gas prices is a widespread phenomenon that is being felt not only in Europe but also globally, as economic activity resumes and energy consumption returns to prepandemic levels. Consequently, this paper investigates how COVID-19 in uenced the Romanian energy market. To accomplish our goal, we used daily data for variables and market indices that characterize COVID-19 and the energy market from July 1 to December 21, 2021. e results of the GARCH (1, 1) model estimation show that the major performer in Romania's energy allocation and supply market had the highest conditional variance. In addition, the ARDL model was chosen because of the variable integration mix (order 0 and 1), as well as the VAR and the Granger causality framework. e empirical results of ARDL models provide the rst conclusion of the analysis, indicating that the number of short-term connections was greater than long-term connections, which is also explained by the presence of short episodes of high volatility recorded in the investigated time interval. Another conclusion drawn from this study is that COVID-19 cases registered in Europe and around the world have made a signi cant contribution to explaining the evolution of the energy market, owing to the large number of cases registered in these regions and the level of contagion transmitted from these markets to the energy market. Furthermore, based on the Granger causality test results, only one-way causal relationships were identi ed from the variables that capture the evolution of the COVID-9 pandemic to the yields of Romanian energy companies. e novelty of this article is the examination of the impact of COVID-19 on the energy market throughout the fourth wave of coronavirus using the GARCH framework, the ARDL model, which allows for the capture of both short-and long-term reactions, the variance decomposition, and the Granger causality test. Because of the ongoing changes in the pandemic's evolution, additional research on this topic is undoubtedly on the horizon in the near future.

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Multicriteria Selection of Optimal Location of TCSC in a Competitive Energy MarketThe paper investigates selection of the best location of thyristor-controlled series compensator (TCSC) in a transmission system from many candidate locations in a competitive energy market such that the TCSC causes a net valuable impact on congestion management outcome, transmission utilization, transmission losses, voltage stability, degree of fulfillment of spot market contracts, and system security. The problem is treated as a multicriteria decision-making process such that the candidate locations of TCSC are the alternatives and the conflicting objectives are the outcomes of the dispatch process, which may have different importance weights. The paper proposes some performance indices that the dispatch decision-making entity can use to measure market dispatch outcomes of each alternative. Based on agreed-upon preferences, the measures presented may help the decision maker compare and rank dispatch ...

We present a simulation analysis of the proposed Colombian firm energy market. The main purpose of the simulation is to assess the risk to suppliers of participation in the market. We also are able to consider variations in the market design, and assess the impact of alternative auction parameters. Three simulation models are developed and analyzed. The first model (Model 1) uses historical price data from October 1995 through May 2006 to assess the performance risk of hypothetical thermal and hydro generating units. The second model (Model 2) uses historical price and operating data to assess performance risk of the actual generating units in Colombia over the same period. This analysis allows us to assess company risk. The third model (Model 3) differs from the other models in that it explicitly models the firm energy auction and investments going forward. Thus, the model is able to assess how the distribution of firm energy purchases differs from the firm energy target, and how this distribution depends on the firm energy demand curve. Model 3 also studies the investment decisions of suppliers, the impact of lumpy investments, and the impact of a higher scarcity price. 1.1 Model 1: Simulated units facing historical prices An important output of Model 1 is the distribution of net firm energy payments for the hypothetical hydro and thermal units. A resource selling firm energy is selling a hedge for energy 1 This paper is an expansion of the paper we did in August with the same title. The main addition is the presentation of Model 3, the full simulation of the firm energy market going forward. This work was funded by XM Compañía de Expertos en Mercado S.A. E.S.P. (XM). We thank the XM staff and the commissioners and staff of Colombia's Comisión de Regulación de Energía y Gas (CREG) for many helpful comments.

The integration of renewable energy technologies is an important component to achieve the serious environmental objectives of different governments and institutions worldwide. However, there are several challenges along the way to continue increasing in capacity. The greater penetration of these technologies arises the need to provide the same reliability and services that conventional generators have made in the electricity grid. Energy storage provides one of the solutions. The purpose of the master's project was to develop a methodology that allows modeling and simulating energy storage systems coupled to photovoltaic fields, to optimize their integration in electricity networks. The methodology can model any location and any condition that a project of this type requires and calculate its optimal sizing. The parameters that can be varied are the following: power, DC / AC ratio, location, electricity prices, tariff pricing mechanisms (existing and proposed), and finally capital costs. In this model, in addition, a new configuration was proposed to benefit from the photovoltaic excesses produced from an oversized photovoltaic field, by connecting the battery system to a DC/DC converter of relatively high power. Different cases studies were analyzed, in order to show how this type of system can help to replace conventional generators and ensure the reliability and quality of the electrical network. The cases studies were: (i.) Storage of excesses by "clipping", (ii.) Power-shifting, (iii.) Primary and secondary regulation, and (iv.) Demand response coupling by electric vehicles.