Sammanfattning Elförsörjning är en av samhällets mest vitala funktioner och el förbrukas daligen av konsumenter. För att konsumentens ska kunna elförsörjas krävs det bland annat att denne ingår avtal om köp av el med elhandelsbolaget. Avtalet ålägger konsumenten en betalningsskyldighet för den förbrukade elen. Försummar konsumenten sin betalningsskyldighet kan elhandelsbolaget, i enlighet med 11 kapitlet ellagen och avtalet, vara berättigat att vidta avbrott i elöverföringen. För att rätten till avbrott i elöverföringen ska få vidtas krävs att vissa förutsättningar är uppfyllda. Dessa förutsättningar utgör en del av konsumentskyddet på elmarkanaden och elhandelsbolaget hindras därmed från att hur som helst vidta avbrott i elöverföringen. Detta konsumentskydd består av ett antal förutsättningar och är alla förutsättningar inte uppfyllda får avbrott i elöverföringen inte vidtas. Exempel på när avbrott i elöveföringen inte får vidtas är när socialnämnden åtar sig betalningsansvaret för elskulden. I realiten torde enbart vissa ekonomiskt utsatta konsumenter beröras av bestämmelserna om avbrott i elöverföringen. Därmed torde socialnämndens betalningsåtagande vara avgörande för dennes fortsatta rätt till el. Socialnämnden beviljar enbart ekonomiskt bistånd som sista möjliga utväg. Därmed kommer enbart vissa av de ekonomiskt utsatta konsumenterna att behålla rätten till el medan övriga berövas denna rätt. Elhandelsbolagets rätt till avbrott i elöverföringen tillförsäkras redan genom lag vilket innebär att standardavtalet är överflödigt. Avtalets grundläggande funktion är att kunna garantera att konsumenten betalar. Därmed bör konsumentens betalningsskyldighet lagstadgas. / Abstract Electricity supply is one of society's most vital functions and electricity is daily consumed by consumers. To be supplied with electricity the consumer must enter into a contract agreement with the electricity trading company. The contract imposes the consumer to pay for the consumed electricity. If the consumer neglects to pay the electricity trading compa-ny may be, in accordance with chapter 11 The Electricy Act and the contract, entitled to discontinue the electricity transmission. Before the company terminates the electricity transmission certain conditions must be met. These conditions are part of the consumer protection on the electricity market and consequently the electricity trading company is hindered from taking unfound disconnection. This protection consists of a set of condi-tions and for the disconnection to be justified all of those conditions must be met. An ex-ample of a condition that hinders the electricity company from pursuing disconnection is if the Social Welfare Board agrees to take on the liability for the electricity debt. In reality on-ly some economically vulnerable consumers are going to be affected by the provisions re-garding disconnection of transmission of electricity. In such cases the Social Welfare Boards’ commitment to pay is crucial for the consumers’ right to continuing consuming electricity. The Social Welfare Board grants the financial assistance as a last possible resort. Therefore only some of the most financially vulnerable consumers will be able to retain electricity, while others are deprived of this right. The Electricity Trading Company’s right to disconnect the transmission of electricity is en-sured already by law which means that the contract is superfluous. The Contracts’ basic function is to ensure that the consumer pays. Therefore the consumers’ obligation to pay should in an explicit manner be legislated.

Through integrated modeling of power system operations and market risks, this thesis addresses a variety of important issues on market signals modeling, generation capacity scheduling, and electricity forward trading. The first part of the thesis addresses a central problem of transmission investment which is to model market signals for transmission adequacy. The proposed system simulation framework, combined with the stochastic price model, provides a powerful tool for capturing the characteristics of market prices dynamics and evaluating transmission investment. We advocate the use of an AC power flow formulations instead since it allocates transmission losses correctly and reveals the economic incentives of voltage requirements. By incorporating reliability constraints in the market dispatch, the resulting market prices yield incentives for market participants to invest in additional transmission capacity. The second part of the thesis presents a co-optimization modeling framework that incorporates market participation and market price uncertainties into the capacity allocation decision-making problem through a stochastic programming formulation. Optimal scenario-dependent generation scheduling strategies are obtained. The third part of the thesis is devoted to analyzing the risk premium present in the electricity day-ahead forward price over the real-time spot price. This study establishes a quantitative model for incorporating transmission congestion into the analysis of electricity day-ahead forward risk premium. Evidences from empirical studies confirm the significant statistical relationship between the day-ahead forward risk premium and the shadow price premiums on transmission flowgates.

Emerging integration of renewable energy has prompted a wide range of research on the use of energy storage to compensate for the added uncertainty that accompanies these resources. In the Electric Reliability Council of Texas (ERCOT), compressed air energy storage (CAES) has drawn particular attention because Texas has suitable geology and also lacks appropriate resources and locations for pumped hydroelectric storage (PHS). While there have been studies on incorporation of renewable energy, utilization of energy storage, and dispatch optimization, this is the first body of work to integrate all these subjects along with the proven ability to recreate historical dispatch and price conditions. To quantify the operational behavior, economic feasibility, and environmental impacts of CAES, this work utilized sophisticated unit commitment and dispatch (UC&D) models that determine the least-cost dispatch for meeting a set of grid and generator constraints. This work first addressed the ability of these models to recreate historical dispatch and price conditions through a calibration analysis that incorporated major model improvements such as capacity availability and sophisticated treatment of combined heat and power (CHP) plants. These additions appreciably improved the consistency of the model results when compared to historical ERCOT conditions. An initial UC&D model was used to investigate the impacts on the dispatch of a future high wind generation scenario with the potential to utilize numerous CAES facilities. For all future natural gas prices considered, the addition of CAES led to reduced use of high marginal cost generator types, increased use of base-load generator types, and average reductions in the total operating costs of 3.7 million dollars per week. Additional analyses demonstrated the importance of allowing CAES to participate in all available energy and ancillary services (AS) markets and that a reduction in future thermal capacity would increase the use of CAES. A second UC&D model, which incorporated advanced features like variable marginal heat rates, was used to analyze the influence of future wind generation variability on the dispatch and resulting environmental impacts. This analysis revealed that higher amounts of wind variability led to an increase in the daily net load ramping requirements which resulted in less use of coal and nuclear generators in favor of faster ramping units along with reductions in emissions and water use. The changes to the net load also resulted in increased volatility of the energy and AS prices between daily minimum and maximum levels. These impacts were also found to increase with compounding intensity as higher levels of wind variability were reached. Lastly, the advanced UC&D model was also used to evaluate the operational behavior and potential economic feasibility of a first entrant conventional or adiabatic CAES system. Both storage systems were found to operate in a single mode that enabled very high utilization of their capacity indicating both systems have highly desirable characteristics. The results suggest that there is a positive case for the investment in a first entrant CAES facility in the ERCOT market. / text

The integration of dispatchable renewable energies like biomass, geothermal and reservoir hydro technologies into an electrical network present no greater challenge than the integration of conventional power technologies for which are well understood by Eskom engineers. However, renewable energies that are based on resources that fluctuate throughout the day and from season to season, like wind and solar, introduce a number of challenges that Eskom engineers have not dealt with before. It is current practice for Eskom‟s generation to follow the load in order to balance the demand and supply. Through Eskom‟s load dispatching desk at National Control, generator outputs are adjusted on an hourly basis with balancing reserves making up only a small fraction of the total generation. Through the Integrated Resource Plan for Electricity of 2010, the Department of Energy has set some targets towards integrating renewable energy, including wind and solar generation, into the South African electricity market consequently introducing variability on the supply side. With demand that varies continually, maintaining a steady balance between supply and demand is already a challenging task. When the supply also becomes variable and less certain with the introduction of non-dispatchable renewable energy, the task becomes even more challenging. The aim of this research study is to determine whether the resources that previously helped to balance the variability in demand will still be adequate to balance variability in both demand and supply. The study will only concentrate on variable or non-dispatchable renewable energies as will be added to the South African electrical network according to the first two rounds of the Department of Energy‟s Renewable Energy Independent Power Producer Procurement Programme. This research study only looks into the balancing challenge and does not go into an analysis of voltage stability or network adequacy, both of which warrant in depth analysis. / Thesis (MIng (Development and Management Engineering))--North-West University, Potchefstroom Campus, 2013.

The integration of dispatchable renewable energies like biomass, geothermal and reservoir hydro technologies into an electrical network present no greater challenge than the integration of conventional power technologies for which are well understood by Eskom engineers. However, renewable energies that are based on resources that fluctuate throughout the day and from season to season, like wind and solar, introduce a number of challenges that Eskom engineers have not dealt with before. It is current practice for Eskom‟s generation to follow the load in order to balance the demand and supply. Through Eskom‟s load dispatching desk at National Control, generator outputs are adjusted on an hourly basis with balancing reserves making up only a small fraction of the total generation. Through the Integrated Resource Plan for Electricity of 2010, the Department of Energy has set some targets towards integrating renewable energy, including wind and solar generation, into the South African electricity market consequently introducing variability on the supply side. With demand that varies continually, maintaining a steady balance between supply and demand is already a challenging task. When the supply also becomes variable and less certain with the introduction of non-dispatchable renewable energy, the task becomes even more challenging. The aim of this research study is to determine whether the resources that previously helped to balance the variability in demand will still be adequate to balance variability in both demand and supply. The study will only concentrate on variable or non-dispatchable renewable energies as will be added to the South African electrical network according to the first two rounds of the Department of Energy‟s Renewable Energy Independent Power Producer Procurement Programme. This research study only looks into the balancing challenge and does not go into an analysis of voltage stability or network adequacy, both of which warrant in depth analysis. / Thesis (MIng (Development and Management Engineering))--North-West University, Potchefstroom Campus, 2013.

In a deregulated electricity market, offering the appropriate amount of electricity at the right time with the right bidding price is of paramount importance. The forecasting of electricity market clearing price (MCP) is a prediction of future electricity price based on given forecast of electricity demand, temperature, sunshine, fuel cost, precipitation and other related factors. Currently, there are many techniques available for short-term electricity MCP forecasting, but very little has been done in the area of mid-term electricity MCP forecasting. The mid-term electricity MCP forecasting focuses electricity MCP on a time frame from one month to six months. Developing mid-term electricity MCP forecasting is essential for mid-term planning and decision making, such as generation plant expansion and maintenance schedule, reallocation of resources, bilateral contracts and hedging strategies. Six mid-term electricity MCP forecasting models are proposed and compared in this thesis: 1) a single support vector machine (SVM) forecasting model, 2) a single least squares support vector machine (LSSVM) forecasting model, 3) a hybrid SVM and auto-regression moving average with external input (ARMAX) forecasting model, 4) a hybrid LSSVM and ARMAX forecasting model, 5) a multiple SVM forecasting model and 6) a multiple LSSVM forecasting model. PJM interconnection data are used to test the proposed models. Cross-validation technique was used to optimize the control parameters and the selection of training data of the six proposed mid-term electricity MCP forecasting models. Three evaluation techniques, mean absolute error (MAE), mean absolute percentage error (MAPE) and mean square root error (MSRE), are used to analysis the system forecasting accuracy. According to the experimental results, the multiple SVM forecasting model worked the best among all six proposed forecasting models. The proposed multiple SVM based mid-term electricity MCP forecasting model contains a data classification module and a price forecasting module. The data classification module will first pre-process the input data into corresponding price zones and then the forecasting module will forecast the electricity price in four parallel designed SVMs. This proposed model can best improve the forecasting accuracy on both peak prices and overall system compared with other 5 forecasting models proposed in this thesis.

Electrical energy is one of the most common forms of energy these days. Consequently, electric power system is an indispensable part of any society. However, due to the deregulation of electricity markets and the growth in the share of power generation by uncontrollable renewable energies such as wind and solar, power system simulations are more challenging than earlier. Thus, new techniques for simplifying these simulations are needed. One important example of such simplification techniques is the power system reduction. Power system reduction can be used at least for four different purposes: a) Simplifying the power system simulations, b) Reducing the computational complexity, c) Compensating the data unavailability, and d) Reducing the existing uncertainty. Due to such reasons, power system reduction is an important and necessary subject, but a challenging task to do. Power system reduction is even more essential when system operators are facing very large-scale power systems and when the renewable energy resources like hydro, wind, and solar have a high share in power generation. This thesis focuses on the topic of large-scale power system reduction with high penetration of renewable energy resources and tries to pursue the following goals: • The thesis first reviews the different methods which can be used for simplifying the power system studies, including the power system reduction. A comparison among three important simplification techniques is also performed to reveal which simplification results in less error and more simulation time decrement. • Secondly, different steps and methods for power system reduction, including network aggregation and generation aggregation, are introduced, described and discussed. • Some improvements regarding the subject of power system reduction, i.e. on both network aggregation and generation aggregation, are developed. • Finally, power system reduction is applied to some power system problems and the results of these applications are evaluated. A general conclusion is that using power system simplification techniques and specially the system reduction can provides many important advantages in studying large-scale power systems with high share of renewable energy generations. In most of applications, not only the power system reduction highly reduces the complexity of the power system study under consideration, but it also results in small errors. Therefore, it can be used as an efficient method for dealing with current bulk power systems with huge amounts of renewable and distributed generations. / <p>The Doctoral Degrees issued upon completion of the programme are issued by Comillas Pontifical University, Delft University of Technology and KTH Royal Institute of Technology. The invested degrees are official in Spain, the Netherlands and Sweden, respectively. QC 20150116</p>

The growth of electricity markets around the world has introduced new challenges in which one of the challenges is the uncertainty that has become a structural element in this new environment. Market players have to deal with it to guarantee the appropriate power system planning and operation as well as its own economical liquidity. Under an open access environment in a deregulated power system, transmission management holds a vital role in supporting transactions between suppliers and customers. Nevertheless, a transmission network has some constraints that should be addressed in order to ensure sufficient control to maintain the security level of a power system while maximizing market efficiency. The most obvious drawback of transmission constraints is a congestion problem that becomes an obstacle of perfect competition among the market participants since it can influence spot market pricing. The system becomes congested when the supplier and customer agree to produce and consume a particular amount of electric power, but this can cause the transmission network to exceed its thermal limits. Congestion can cause the market players to exercise market power that can result in price volatility beyond the marginal costs. Thus, it is important to manage congestion efficiently in the design of a power market. One mechanism that has direct correlation with transmission management is market clearing price (MCP). Under an open access environment, energy prices throughout the network will be different and measured based on transmission constraint and network losses. When network losses are ignored and there is no congestion on the transmission lines, the power price will be the same at all nodes. This is known as uniform marginal pricing (UMP). However, as the power flow violates transmission constraints, redispatching generating units is required and this will cause the price at every node to vary. This phenomenon is defined as locational marginal pricing (LMP). Therefore, the market clearing price has a strong relationship with transmission management, which is needed to be assessed in order to obtain an efficient and transparent price but satisfying all market participants. This project investigates an alternative solution to the dispatch mechanism, and then formulates a new Locational Marginal Price scheme using optimization technique that may well control congestion as the main issue. The model will vary and be improved, to be distilled into energy price, congestion revenue, cost of losses, as well as transmission usage tariff. The objective of the project is to support developing standard market design (SMD) in managing transmission systems which promotes economic efficiency, lowers delivered energy costs, maintains power system reliability and mitigates exercising market power.

The growth of electricity markets around the world has introduced new challenges in which one of the challenges is the uncertainty that has become a structural element in this new environment. Market players have to deal with it to guarantee the appropriate power system planning and operation as well as its own economical liquidity. Under an open access environment in a deregulated power system, transmission management holds a vital role in supporting transactions between suppliers and customers. Nevertheless, a transmission network has some constraints that should be addressed in order to ensure sufficient control to maintain the security level of a power system while maximizing market efficiency. The most obvious drawback of transmission constraints is a congestion problem that becomes an obstacle of perfect competition among the market participants since it can influence spot market pricing. The system becomes congested when the supplier and customer agree to produce and consume a particular amount of electric power, but this can cause the transmission network to exceed its thermal limits. Congestion can cause the market players to exercise market power that can result in price volatility beyond the marginal costs. Thus, it is important to manage congestion efficiently in the design of a power market. One mechanism that has direct correlation with transmission management is market clearing price (MCP). Under an open access environment, energy prices throughout the network will be different and measured based on transmission constraint and network losses. When network losses are ignored and there is no congestion on the transmission lines, the power price will be the same at all nodes. This is known as uniform marginal pricing (UMP). However, as the power flow violates transmission constraints, redispatching generating units is required and this will cause the price at every node to vary. This phenomenon is defined as locational marginal pricing (LMP). Therefore, the market clearing price has a strong relationship with transmission management, which is needed to be assessed in order to obtain an efficient and transparent price but satisfying all market participants. This project investigates an alternative solution to the dispatch mechanism, and then formulates a new Locational Marginal Price scheme using optimization technique that may well control congestion as the main issue. The model will vary and be improved, to be distilled into energy price, congestion revenue, cost of losses, as well as transmission usage tariff. The objective of the project is to support developing standard market design (SMD) in managing transmission systems which promotes economic efficiency, lowers delivered energy costs, maintains power system reliability and mitigates exercising market power.

Of the findings, the European Commission established in its report on Energy Sector Inquiry, market manipulation constituted a major concern for the functioning and integrity of EU energy sectors. The Commission argued that the responsibility for high prices in wholesale energy markets could be attributed to manipulative practices of energy incumbents and the trust in the operation of operation of sector was largely compromised, due to these practices. Remedies, EU competition law provided, were considered as insufficient to resolve these shortcomings and thus should be supplemented with regulatory-based tools. The findings of the Energy Sector Inquiry and subsequent consultation documents by multiple EU institutions paved the way for the adoption of the Regulation on wholesale energy market integrity and transparency, REMIT, which incorporated into an anti-manipulation rule, specifically designed to prohibit and prosecute manipulative practices in EU wholesale energy markets. Nevertheless, as EU case law on market manipulation has yet to develop and there are uncertainties with respect to the concept of market manipulation. Furthermore REMIT does not preclude the jurisdiction of EU competition law, questions arise as to the scope and the extent of the application of this prohibition. Throughout its chapters, this book explores the scope of and the case law on market manipulation to determine what types of market practices are regarded as manipulative and thus prohibited under anti-manipulation rules. It also focuses on the interplay between REMIT and EU competition law and evaluates factors and circumstances that determine when and what market misconduct can be subject to enforcement proceedings under both anti-manipulation and antitrust rules. As the development of a single, coherent, rulebook that can be relied upon by market participant is fundamental for the functioning of EU wholesale energy markets, the book, finally, provides proposals and measures that can mitigate and resolve the legal uncertainties regarding the regulatory framework REMIT established.