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We present a model for an energy market that includes a green certificate for suppliers of energy from renewables and a purchaser commitment to buy these certificates. We show that price and volume effects in the energy market are ambigous under a wide range of alternative levels of the purchaser commitment. We calibrate our model to data for the Norwegian economy. Simulations shows a downward movement in energy prices as the government starts increasing the level of the purchaser commitment. This implies that the producer of ordinary energy pays for the restriction in the market while energy consumption and consumer surplus increases. When the purchaser commitment increases above a certain level, the purchaser price increases and the volume effect is negative. Although the effects are sensitive to elasticities of demand and supply of both technologies, the main results are robust against a variety of combinations of elasticities. The article discusses effects both under autarky and free trade of both energy and green certificates. The results vary denpendent upon whether only one or a majority of actual countires introduces a domestic market or allows for international trade both in energy and the green certificate instrument.

The increase of distributed energy resources in energy systems and current legislation concerning the participation in energy markets, is causing a high wasted potential of energy supply and flexibility services. In this paper, it is proposed a methodology for the management and integration of distributed energy resources in energy systems and markets, through the application of an aggregator. Also, the aggregator provides demand response programs based on tariffs, thus enabling different types of participations. Aggregation is performed using K-Means clustering algorithm, and serves as basis for remuneration, where the aggregated energy and cost of resources is obtained. Given this methodology, the aggregator obtains the energy available and the minimum sell cost to negotiate in market, with the intent of obtaining profit in its operation. The methodology is validated through a case study, with 20 consumers and 25 distributed generators. ; This work has received funding from the following projects: NETEFFICITY Project (ANI | P2020 – 18015); and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013.

The increase of distributed energy resources in energy systems and current legislation concerning the participation in energy markets, is causing a high wasted potential of energy supply and flexibility services. In this paper, it is proposed a methodology for the management and integration of distributed energy resources in energy systems and markets, through the application of an aggregator. Also, the aggregator provides demand response programs based on tariffs, thus enabling different types of participations. Aggregation is performed using K-Means clustering algorithm, and serves as basis for remuneration, where the aggregated energy and cost of resources is obtained. Given this methodology, the aggregator obtains the energy available and the minimum sell cost to negotiate in market, with the intent of obtaining profit in its operation. The methodology is validated through a case study, with 20 consumers and 25 distributed generators. ; This work has received funding from the following projects: NETEFFICITY Project (ANI | P2020 – 18015); and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013. ; info:eu-repo/semantics/publishedVersion

The aim of the present master's thesis is to represent the evolution of energy markets in the European Union from a fragmented monopolistic structure to a unified competitive form and the way in which a single energy market in the Union is gradually being established, through the adoption of common rules and the development of interconnections. This internal energy market which is named Target Model and constitutes one of the major intentions of the European Union, is being examined from a legal perspective in the following chapters. Specifically, the first chapter of the thesis attempts to represent an overview of the legislative framework that has been adopted in succession by European Commission towards the liberalization and unification of the energy market, namely the four energy legislative packages that have determined the structure and the operation of the European electricity market. In the second chapter we examine the basic forms of power markets depending on their degree of competition, as well as we examine the transformation of the energy markets to mandatory pool systems or power exchange models. The third chapter of the thesis consists of an analytical overview of the Target model operation, which is mainly based on the power exchange model, as well as the coupling of national markets. Chapter four refers to the establishment of the network codes, which have been enacted in order to facilitate and secure the well-functioning of the single market through common rules on market integration, operation and interconnection procedures. In chapter five, a more specific reference to the electricity system of Greece is made, while chapter six consists of a general conclusion over the progress that has been made so far in the energy field regarding the unification of the market, as well as over the obstacles that have to be overcome by European Union in order to finally realize the goal of a fully integrated electricity market.

Currently the use of distributed energy resources, especially renewable generation, and demand response programs are widely discussed in scientific contexts, since they are a reality in nowadays electricity markets and distribution networks. In order to benefit from these concepts, an efficient energy management system is needed to prevent energy wasting and increase profits. In this paper, an optimization based aggregation model is presented for distributed energy resources and demand response program management. This aggregation model allows different types of customers to participate in electricity market through several tariffs based demand response programs. The optimization algorithm is a mixed-integer linear problem, which focuses on minimizing operational costs of the aggregator. Moreover, the aggregation process has been done via K-Means clustering algorithm, which obtains the aggregated costs and energy of resources for remuneration. By this way, the aggregator is aware of energy available and minimum selling price in order to participate in the market with profit. A realistic low voltage distribution network has been proposed as a case study in order to test and validate the proposed methodology. This distribution network consists of 25 distributed generation units, including photovoltaic, wind and biomass generation, and 20 consumers, including residential, commercial, and industrial buildings. ; This work has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAMGO). This work also received funding from the following projects: NETEFFICITY Project (ANI | P2020 – 18015); and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013.

Currently the use of distributed energy resources, especially renewable generation, and demand response programs are widely discussed in scientific contexts, since they are a reality in nowadays electricity markets and distribution networks. In order to benefit from these concepts, an efficient energy management system is needed to prevent energy wasting and increase profits. In this paper, an optimization based aggregation model is presented for distributed energy resources and demand response program management. This aggregation model allows different types of customers to participate in electricity market through several tariffs based demand response programs. The optimization algorithm is a mixed-integer linear problem, which focuses on minimizing operational costs of the aggregator. Moreover, the aggregation process has been done via K-Means clustering algorithm, which obtains the aggregated costs and energy of resources for remuneration. By this way, the aggregator is aware of energy available and minimum selling price in order to participate in the market with profit. A realistic low voltage distribution network has been proposed as a case study in order to test and validate the proposed methodology. This distribution network consists of 25 distributed generation units, including photovoltaic, wind and biomass generation, and 20 consumers, including residential, commercial, and industrial buildings. ; This work has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAMGO). This work also received funding from the following projects: NETEFFICITY Project (ANI | P2020 – 18015); and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013. ; info:eu-repo/semantics/publishedVersion

This work considers effects of energy market liberalisation in the countries of the former Soviet Union (FSU).Our analysis is based on a computable general equilibrium (CGE) model called the Global Trade Analysis Project (GTAP).This specialised model makes it possible to evaluate effects in a general equilibrium set-up. Energy market reforms are widely discussed in the literature, but the use of CGE models has been limited.In the main part of the paper, we perform two experiments.The first is a benchmark liberalisation experiment in which all government taxes and subsidies are removed.The second is an attempt to simulate an increase in the export capacity of energy commodities into the European markets.In general, we find that liberalisation of FSU energy markets would increase welfare in the EU countries, while in the FSU welfare would decrease.This result is mainly due to the terms of trade effect, as export prices of FSU countries decrease.

There is a global goal to reduce carbon emissions and create a more sustainable world. Over the past decades, a growing share of renewable energy resources have been developed to reach this goal. Due to their intermittent nature, these resources make it more difficult for an electrical grid to remain stable as it is designed for slow-reacting, constant, and predictable power plants. This issue can be solved through energy storage for load balancing without using power plants for this operation, and with a reaction time that is much faster than conventional power plants. The implementation of energy storage seems inevitable for a more sustainable future. Still, this market has only slowly started to move in the right direction, with implementation on both large- and small-scale applications awaiting their first successes. An innovative business model may be key to this success. This study investigated how business model innovation affects firm performance in the energy storage market, by measuring firm performance on firms acting in the energy storage market. Four cases were investigated: two large-scale applications using grid-level solutions and two small-scale applications on the consumer level. Results show that business model innovation affects firm performance in the energy storage market. With current legislation limiting a true new value proposition, for large-scale applications, the business model innovation with an efficiency design theme results in higher environmental performance and, therefore, increased customer satisfaction. For small-scale applications, a business model innovation with a complementarities theme results in increased numbers of partnerships, customer segments, and channels, contributing to higher customer satisfaction through a more complete and innovative product-value proposition to the customer.

Intro -- ENERGY MARKETS FEDERAL FINANCIAL INTERVENTIONS, SUBSIDIES AND TAX INCENTIVES -- ENERGY MARKETS FEDERAL FINANCIAL INTERVENTIONS, SUBSIDIES AND TAX INCENTIVES -- CONTENTS -- PREFACE -- Chapter 1 DIRECT FEDERAL FINANCIAL INTERVENTIONS AND SUBSIDIES IN ENERGY IN FISCAL YEAR 2010 -- PREFACE -- EXECUTIVE SUMMARY -- Background -- Not All Subsidies Impacting the Energy Sector Are Included in this Report -- Key Findings -- Energy Provisions Included in Legislation Responding to the Recent Financial Crisis -- Findings Regarding Electricity-Related Subsidies and Support -- Findings Regarding Subsidies and Support for Fuels Used Outside of the Electricity Sector -- 1. INTRODUCTION -- Background -- Not all Subsidies Impacting the Energy Sector are Included in this Report -- Organization of Report -- 2. TAX EXPENDITURE AND DIRECT EXPENDITURES -- Overview -- Tax Expenditures -- Tax Expenditure Caveats -- ENERGY-SPECIFIC TAX EXPENDITURE PROGRAMS -- Coal-Related Tax Expenditures -- Renewable-Related Tax Expenditures -- Natural Gas and Petroleum-Related Tax Expenditures -- Nuclear-Related Tax Expenditures -- Energy Efficiency and Conservation-Related Tax Expenditures -- Electricity Transmission-Related Tax Expenditures -- Direct Expenditures -- Energy-Specific Direct Expenditure Program Descriptions Department of Energy -- Department of Labor -- Department of Transportation -- Environmental Protection Agency -- General Services Administration -- Department of Housing and Urban Development -- Department of Health and Human Services -- Department of Agriculture -- Department of the Treasury -- 3. FEDERAL ENERGY RESEARCH AND DEVELOPMENT -- 4. FEDERAL ELECTRICITY PROGRAMS -- Introduction -- Measuring the Support -- Selection of a Market Interest Rate -- Tennessee Valley Authority -- Power Marketing Authorities -- BPA's Borrowing Costs

The co-evolution of techno-economic, societal, environmental and political-institutional systems towards sustainable energy transitions is largely influencing the disruptive reconfiguration of the energy sector across the globe. At the heart of this disruption is the peer-to-peer energy sharing concept. Nonetheless, peer-to-peer energy sharing business models are yet very little put into practice due to the rigid energy market structures and lagging regulatory frameworks across the globe. In view of this, this paper presents a novel peer-to-peer energy sharing business model developed specifically for the context of the Portuguese energy market, which was successfully trialed in three pilot projects in Portugal under real market conditions. All things considered, the novelty of this paper lies on an innovative approach for the collaborative use of the surplus electricity generation from photovoltaic systems between end-users under the same low voltage/medium voltage transformer substation, which resulted in direct financial benefits to them. While absent deregulation obstructs the implementation of effective peer-to-peer energy sharing markets in Portugal, such demonstration projects are essential to challenge restrictive regulatory frameworks that do not keep pace with techno-economic and societal innovations, thus helping to build the emerging consumer-centric energy regime and disrupt the old one.

This paper proposes a new model to allocate reserve costs among the involved players, considering the characteristics of the several entities, and the particular circumstances at each moment. The proposed model is integrated in the Multi-Agent Simulator of Competitive Electricity Markets (MASCEM), which enables complementing the multi-agent simulation of diverse electricity market models, by including the joint simulation of energy and reserve markets. In this context, the proposed model allows allocating the payment of reserve costs that result from the reserve market. A simulation based on real data from the Iberian electricity market - MIBEL, is presented. Simulation results show the advantages of the proposed model in sharing the reserve costs fairly and accordingly to the different circumstances. This work thus contributes the study of novel market models towards the evolution of power and energy systems by adapting current models to the new paradigm of high penetration of renewable energy generation. ; This work has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAM-GO) and a grant agreement No 703689 (project ADAPT); and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013