Electricity Markets

The long-term electric power demand forecasting is
based on a set of basic premises that includes the macroeconomic
scenarios, the growth of the population and of the number of
households. The latter is the main determinant to calculate the
number of residential customers served by the utilities. This paper
presents the headship rate method and its projections for the
number of households in Brazil for the years 2010 and 2020. These
projections are based on the long term forecasting of the age
pyramid of the Brazilian population provided by the Brazilian
Institute of Geography and Statistics (IBGE). In order to forecast
the number of residential customers in the next ten years, the
projections for the number of households are combined with the
goals established by the Brazilian Electricity Regulatory Agency
(ANEEL) for universalization access to electricity.

More than 20% of the electricity generated in India is lost to rampant thefts. Drawing data from 28 states
of India over a time span of five years (2005–2009), this paper examines the role played by socio-economic and governance factors in determining the extent of electricity thefts in Indian states. Results from the Feasible Generalised Least Squares(FGLS) model demonstrate that lesser corruption, higher state tax to GDP ratio, greater collection efficiency of electricity bills by state utilities, higher share of private installed capacity, lesser poverty, greater literacy and greater income are closely associated with lesser power thefts. A better understanding of the key determinants of thefts in electricity distribution is vital for policymakers for designing policies.

The research is based on the impact of globalization and trade liberalization on textile exports of Pakistan. The era of globalization does not only evolved the global culture towards diversification but also its implications on global trade, business and country wise exports. In this research four variables are used as proxy to globalization (Global Internet Penetration, Regional Competition, FDI, and Openness to Trade) to find their impact on one independent variable (Pakistan Textile Exports). Quantitative research approach is used and co-relational research design is applied on 16 years data from year 2001 to 2016. Descriptive analysis, Correlation analysis and Regression analysis is performed on the arranged data to find the impact of Globalization on Textile exports of Pakistan.

KEYWORDS:
Globalization, Textile, Exports, Pakistan, Global internet penetration, Regional Competition, FDI, Openness to trade

By increasing renewable resource penetration, the need for developing fast and reliable market modeling approaches in the presence of these resources has gained greater attention. In this paper, fuzzy Q-learning approach is proposed for hour-ahead electricity market modeling in presence of renewable resources. The proposed approach is implemented on IEEE 30-bus test system. The effectiveness of the proposed approach is evaluated and compared with Q-learning approach for both normal and stressful cases. Simulation results indicate that the proposed approach is able to model electricity market for a range of continuous multidimensional renewable power penetration in considerably less iterations compared with Q-learning approach. Moreover, the probability of finding Nash equilibrium is becoming higher by using fuzzy Q-learning approach, while the other indices such as average social welfare, average of locational marginal prices (LMPs), and average standard of deviation of LMPs do not change considerably.

Unlike markets for storable commodities, electricity markets depend on the real-time balance of supply and demand. Although much of the present-day grid operates effectively without storage, cost-effective ways of storing electrical energy can help make the grid more efficient and reliable. We investigate the economics of two emerging electric energy storage (EES) technologies: sodium sulfur batteries and flywheel energy storage systems in New York state's electricity market. The analysis indicates that there is a strong economic case for EES installations in the New York City region for applications such as energy arbitrage, and that significant opportunities exist throughout New York state for regulation services. Benefits from deferral of system upgrades may be important in the decision to deploy EES. Market barriers currently make it difficult for energy-limited EES such as flywheels to receive revenue for voltage regulation. Charging efficiency is more important to the economics of EES in a competitive electricity market than has generally been recognized.

Electricity market activities and a growing demand for electricity have led to heavily stressed power systems. This requires operation of the networks closer to their stability limits. Cost effective solutions are preferred over network extensions. The flexible alternating current transmission system (FACTS), a new technology based on power electronics, offers an opportunity to enhance controllability, stability, and power transfer capability of ac transmission systems. This paper provides a comprehensive review and evaluation of FACTS controllers.

In an attempt to meet the ever-increasing electricity demand and reinforce inadequate state investments with private, in particular foreign investments, Turkey opted for liberalisation of its electricity market which had been vastly dominated by vertically integrated state economic enterprises for more than half a century. A new era has begun in the Turkish electricity market with the enactment of Electricity Market Law 2001, pursuing the goals of liberalising the market and promoting competition. Significant progress has been made in respect of these goals; however, some major challenges have given rise to problems precluding successful liberalisation attempts. This article evaluates the current state of Turkish electricity market by analysing the progress made and problems emerged in the aftermath of Turkish electricity liberalisation.

Starting from PES (primary energy saving) and CSR (cost saving ratio) definitions the work pinpoints a " grey area " in which CHP (combined heat and power e cogeneration) units can operate with profit and negative PES. In this case, CHP can be profitably operated with lower efficiency with respect to separate production of electrical and thermal energy. The work defines the R-index as the ratio between the cost of fuel and electricity. The optimal value of R-index for which CHP units operate with both environmental benefit (PES > 0) and economic profitability (CSR > 0) is the reference value of electrical efficiency, h el_ref , of separate production (national power grid mix). As a consequence, optimal R-index varies from Country to Country. The work demonstrates that the value of R corresponds to the minimum value of electrical efficiency for which any power generator operates with profit. The paper demonstrates that, with regard to the profitability of cogeneration, the ratio between the cost of commodities is more important than their absolute value so that different taxation of each commodity can be a good leverage for energy policy makers to promote high efficiency cogeneration, even in the absence of an incentive mechanism. The final part of the study presents an analysis on micro-CHP technologies payback times for different European Countries.

Storage devices effectively provide a similar service to peak generators. The capacity value of storage was found to be insensitive to the round trip efficiency. Storage devices may compete with traditional peak generation technologies. The ability to derive additional revenue from energy arbitrage provides a competitive advantage to storage devices. a b s t r a c t Price volatility and increasing renewable energy generation have raised interest in the potential opportunities for storage technologies in energy-only electricity markets. In this paper we explore the value of a price-taking storage device in such a market, the National Electricity Market (NEM) in Australia. Our analysis suggests that under optimal operation, there is little value in having more than six hours of storage in this market. However, an inability to perfectly forecast wholesale prices, particularly extreme price spikes, may warrant some additional storage. We found that storage devices effectively provide a similar service to peak generators and are similarly dependent on and exposed to extreme price events, with revenue for a merchant generator highly skewed to a few days of the year. As a consequence of this finding, and in contrast to previous studies, the value of storage was found to be relatively insensitive to the round trip efficiency. We also found that the variability of revenue and exposure to extreme prices could be reduced using common hedging strategies, such as those currently used by peak generators. We present a case study that demonstrates storage technologies using such strategies may have a competitive advantage over other peaking generators in the NEM, due to the ability to earn revenue outside of extreme peak events. Similar to traditional peak generators, a main driver for storage options in an energy-only electricity market is extreme prices, which in turn is dependent on capacity requirements. However storage technologies can receive additional revenue streams, which may be improved by increased integration of renewable energy.

As the volume and diversity of distributed energy resources (DER) on the electric system continue to grow, two clearly distinct visions or paradigms have emerged for how a decentralized, transactive electric system with high penetration of DER could be designed to operate. This article starts from a grid operations perspective and describes the two visions in some detail, compares them and draws implications for key market design and regulatory questions being debated today. One vision is based on a centralized, whole-system optimization performed by the transmission system operator (TSO), who may also operate wholesale spot markets as an independent system operator (ISO) or regional transmission organization (RTO). Under this model the TSO needs detailed information and visibility into all levels of the system, from the balancing authority area down to the meters on end-use customers and distribution-connected devices. The other vision involves a decentralized, layered-decomposition optimization structure, for which optimization at any given layer of the system only requires visibiity to the interface points with the next layers above and below, and does not need visibility to what’s inside those other layers. The TSO under this layered optimization paradigm would see a single virtual resource at each transmission-distribution interface and would not need to be concerned with the individual DER or customers below the interface.

In this paper, the data analysis and short term load forecasting (STLF) in Iran electricity market has been considered. The proposed method is an improved singular spectral analysis (SSA) method. SSA decomposes a time series into its principal components i.e. its trend and oscillation components, which are then used for time series forecasting, effectively. The employed data are the total load time series of Iran electricity market in its real size and is long enough to make it possible to take properties such as nonstationary and annual periodicity of the market into account. Simulation results show that the proposed method has a good ability in characterizing and prediction of the desired load time series in comparison with some other related methods.

This paper quantifies the increased green house gas emissions and negative effect on energy conservation (or “efficiency penalty”) due to electric rate structures that employ an unavoidable customer charge. First the extent of customer charges was determined from a nationwide survey of U.S. electric tariffs. To eliminate the customer charge nationally while maintaining a fixed sum for electric companies for a given amount of electricity, an increase of 7.12% in the residential electrical rate was found to be necessary. If enacted, this increase in the electric rate would result in a 6.4% reduction in overall electricity consumption, conserving 73 billion kW-hrs, eliminating 44.3 million metric tons of carbon dioxide, and saving the entire U.S. residential sector over $8 billion per year. As shown here, these reductions would come from increased avoidable costs thus leveraging an increased rate of return on investments in energy efficiency, energy conservation behavior, distributed energy generation, and fuel choices. Finally, limitations of this study and analysis are discussed and conclusions are drawn for proposed energy policy changes.

Después de analizar las experiencias internacionales relacionadas con el monitoreo y control de poder de mercado, se establece una metodología acorde a las características del pool eléctrico en Colombia, la cual permite hacer seguimiento sobre comportamientos estratégicos respecto al precio en bolsa en este mercado. Se propone un modelo exponencial para la función de oferta en el pool basado en un modelo de precios spot, explicado por los costos, las condiciones climáticas, las intervenciones de la Comisión de Regulación de Energía y Gas, la demanda diaria, las cantidades generadas y el precio histórico. Por medio de una convolución (técnica similar a la de un Filtro de Kalman) sobre los precios históricos se estiman los parámetros y elasticidades dinámicas asociadas a las cantidades que determinan el comportamiento del precio en bolsa. A su vez, estas estimaciones son utilizadas en la estructura de beneficios en un modelo de Cournot, de competencia en cantidades, que evidencia el efecto positivo, vía disminución del precio de bolsa, de mayores niveles de contratos a futuros en el pool eléctrico colombiano.

This paper proposes a pool-based demand response exchange (DRX) model in which economic demand response (DR) is traded among DR participants as an alternative for managing the variability of renewable energy sources (RES). Load curtailment bids are provided by individual DRX participants and the DRX is cleared by maximizing the total social welfare, which is subject to supply-demand balance and individual bidders' inter-temporal operation constraints. The proposed DRX model is further integrated in the current context of the ISO's day-ahead scheduling in electricity markets. A two-step sequential market clearing framework is presented in which the ISO's stochastic day-ahead scheduling is simulated first for calculating the expected locational marginal prices (LMPs) and then, the proposed DRX is cleared successively using the expected LMPs. The simulation of the ISO's stochastic day-ahead scheduling incorporates random outages of system components and forecast errors for hourly renewable generation and loads. The decompositionbased method is employed to solve the ISO's day-ahead scheduling in the base case and scenarios. Numerical tests are performed for a 6-bus system and an IEEE 118-bus system. The results demonstrate the benefit of utilizing the DRX model for customer market participation in the ISO's day-ahead market scheduling.

This paper empirically compares the predictive accuracy of a set of methods for day-ahead spot price forecasting in the Spanish electricity market. The methods come from time series analysis and artificial intelligence disciplines, and include univariate, multivariate, linear and nonlinear. Within the univariate methods, the double seasonal ARIMA and the recently proposed exponential smoothing for double seasonality are compared and used as benchmarks.

Addressing global challenges, such as climate change and other related environmental concerns requires a rethink in the organization of production and consumption processes. This also includes electricity production and consumption. The need for greater competitiveness in the provision of critical infrastructure (including electricity) is also a challenge. This has led to the liberalization of many electricity markets across the world. In this paper, following an exploratory study of nine countries across Africa, Asia and South America, the common features that characterize the electricity market liberalization process, as well as the key drivers of electricity sector reforms across the world, were established. These features were then used to highlight the main challenges of the Nigerian electricity sector and to provide an explanation of the key milestones that characterized Nigeria's electricity sector liberalization process (2001 – 2017). The paper further discusses five possible future models by which most electricity supply markets will be organized in the future. It concludes by proposing a new model for the organization of the Nigerian electricity industry that would not only aid in addressing the current electricity deficit challenge, but also pave the way for the creation of a market structure that can drive Nigeria towards a secure energy future.

c Market model to optimize CSP plant configuration in North African power systems. c Value of storage-based CSP plants compared to non-dispatchable configurations: 28-55 h/MWh. c Assessment of Morocco's and Algeria's renewable electricity targets until 2030. c CSP becomes more competitive with intermittent technologies when high RES-E quota are targeted.

In a competitive electricity market, price forecasts are important for market participants. However, electricity price is a complex signal due to its nonlinearity, nonstationarity, and time variant behavior. In spite of much research in this area, more accurate and robust price forecast methods are still required. In this paper, a combination of a feature selection technique and cascaded neuro-evolutionary algorithm (CNEA) is proposed for this purpose. The feature selection method is an improved version of the mutual information (MI) technique. The CNEA is composed of cascaded forecasters where each forecaster consists of a neural network (NN) and an evolutionary algorithm (EA). An iterative search procedure is also incorporated in our solution strategy to fine-tune the adjustable parameters of both the MI technique and CNEA. The price forecast accuracy of the proposed method is evaluated by means of real data from the Pennsylvania-New Jersey-Maryland (PJM) and Spanish electricity markets. The method is also compared with some of the most recent price forecast techniques.

The aim of this contribution is to take a closer look into the REMIT in order to assess how this initiative aims at ensuring a better integrated electricity market and effectively enhances market integrity and transparency at the wholesale level with a focus on the first two aspects of the REMIT mentioned above in relation to wholesale electricity trading. We first address the general scope of application of the REMIT to determine the range of business activities in the electricity sector that are impacted by the REMIT ('Part one'). We then look more closely into the provisions regarding market behaviour and integrity. After some introductory considerations on the concept of manipulative behaviour, we examine the approach of the REMIT in this respect ('Part two'). In a following section we examine how the REMIT addresses transparency in traded wholesale electricity markets ('Part three'). In a last section we will draw our conclusions in respect of the regime implemented by the REMIT.

h i g h l i g h t s " A two-stage stochastic offering model for a virtual power plant is presented. " The virtual power plant consists of an intermittent source, a dispatchable source and a storage unit. " The virtual power plant trades in the day-ahead and balancing markets. " Characteristic scenarios are thoroughly analyzed and relevant conclusions are drawn. a b s t r a c t A virtual power plant aggregates various local production/consumption units that act in the market as a single entity. This paper considers a virtual power plant consisting of an intermittent source, a storage facility, and a dispatchable power plant. The virtual power plant sells and purchases electricity in both the day-ahead and the balancing markets seeking to maximize its expected profit. Such model is mathematically rigorous, yet computationally efficient.

The scholarly literature on law and social movements has historically focused on public law issues like environmentalism, reproductive rights, and race relations, while staying far away from business and firm behavior. Business behavior was easily understood as that of self-interested profit-maximizers, and therefore left to the economists. Recently, however, social movement theorists have begun paying more attention to the business world. While traditional economic models can explain why businesses pursue higher profits, greater market shares, and superior regulatory climates, it is limited in its ability to explain how wish becomes reality. The formation and identification of market opportunities are products of social forces, and firms are part of that process—both shaping and being shaped by social dynamics which create and recreate the economic terrain.

This article joins that burgeoning literature by applying a social movements approach to the energy law field. Specifically, it looks to how voluntary Renewable Energy Credit (REC) sales—selling the “clean” in “clean electricity”—could restart the moribund movement towards increased electricity market competition (known as “restructuring”). While electricity restructuring gained considerable momentum from the late 1970s through the 1990s, the movement was crippled by the high-profile Enron collapse in 2001. Efforts to restart the debate have foundered as restructuring proponents have had no point of entry to connect with consumers or influence policymakers in states dominated by incumbent electricity monopolies. Voluntary REC sales, which entail sale of an electricity “product” that bypasses the physical transmission network, offers a “foot in the door” for new market entrants who can connect with consumers and reshape their public image free from interference by the extant monopoly. From a business standpoint, the benefit of entering the voluntary REC market is less about direct revenues or profits from the sale, the traditional economic markers of success. Rather, REC sales are valuable for reasons well-known to social movement theorists—they can establish relationships and alliances in previously untapped social arenas, and alter public understandings of concepts and ideologies critical to the firm’s overall interests.

Las fuentes no convencionales de energía renovable (FNCER) son fuentes de energía consideradas como una alternativa limpia para el suministro de electricidad frente a generación eléctrica a base de combustible fósiles. Además, son un medio por el cual se reduce el nivel de concentración en el mercado y la participación de la demanda se pueden dar. En este artículo se presenta diferentes mecanismos de integración de estas fuentes en el mercado, y se analiza su efecto sobre el precio de la electricidad en Colombia. Bajo las condiciones de simulación definidas, los resultados indican que una participación del 20% de las FNCER en el cubrimiento de la demanda de forma distribuida genera una reducción del 22% en el precio de la electricidad en el largo plazo.

Allocation of transmission loss between network users is a challenging and contentious issue in a fully deregulated system. Also, the cost of loss must be compensated in a fair manner by users which use the transmission network. Power flow tracing can find the extent of network usage by the users that can be used for loss allocation. In this paper, proportional tracing and optimal real power tracing methods are used for allocation of loss and its cost with presence of congestion in transmission lines. GAMS software is employed for solving optimal real power tracing as linear programming problem. The results obtained by proportional and optimal tracing are compared in the modified IEEE 14-bus system and the results show that optimal tracing is more fair approach than proportional tracing.

The following article is a thesis on the  European Union Emissions Trading Scheme from a legal aspect. This thesis will analyze the essential legal instruments to determine the legal framework applicable to the price intervention mechanism of the European Union Emissions Trading Scheme (EU ETS). Such an analysis will encompass the legal instruments of Directive 2003/87/EC  and the Auctioning Regulation 1031/2010/EU  as connected to the issue of price volatility in the carbon market and subsequently to the issue of price volatility in the electricity market .
The foremost research will be about the issue of price volatility in the carbon market as an important concern occurred upon the introduction of the EU ETS and secondarily the interaction of this concern to the volatile prices in the power sector.
Towards this endeavor, the price intervention mechanism as provided in the legal instruments will be criticized in regards to its efficiency and its proper functioning. As a result, the issue to be determined will be whether this mechanism is expected to achieve its purpose as designed to or not.
For this purpose, the backloading measure  as recently proposed by the European Commission will be brought up for analysis. The impact of the acceptability of such a measure by the different stakeholders will be reviewed, as has been set under public discussion the last few months.  Even if such measure constitutes a concern referring explicitly to low carbon prices, such an analysis will get us familiarized to the challenging acceptability of such policies as proposed, underlining, inter alia, the expectations and needs of the interested stakeholders concerning the volatile carbon prices.
What is more, an assessment will be made regarding the issue of price volatility in the power sector as an important problem occurred under the introduction of the EU ETS and the interaction of this problem to the volatile prices in the carbon market.  This challenging interaction will be stated and analyzed further in a succeeding chapter.
Furthermore, the need of redefinition of the current scheme will be pointed out regarding opportunities against potential market inefficiencies from price volatility. Such inefficiencies would be companies' increased production cost and the competitiveness  loss of their products  and the discouragement of business incentives .
Additionally, this thesis will come across the necessity to mitigate price volatility in the carbon market within European Union in the long run. For this purpose, a proposal will be made regarding the choice of an optimal policy instrument, through a comparison of different policy instruments either within the European Union or not.  This comparison will be of assistance to understand the dynamics of the current scheme and the potential of a modified scheme empowered with design features that could substantiate an efficient policy after all.

This paper presents a proposal for multiobjective Invasive Weed Optimization (IWO) based on nondominated sorting of the solutions. IWO is an ecologically inspired stochastic optimization algorithm which has shown successful results for global optimization. In the present work, performance of the proposed nondominated sorting IWO (NSIWO) algorithm is evaluated through a number of well-known benchmarks for multiobjective optimization. The simulation results of the test problems show that this algorithm is comparable with other multiobjective evolutionary algorithms and is also capable of finding better spread of solutions in some cases. Next, the proposed algorithm is employed to study the Pareto improvement model in two complex electricity markets. First, the Pareto improvement solution set is obtained for a three-player oligopolistic electricity market with a nonlinear demand function. Then, the IEEE 30-bus power system with transmission constraints is considered, and the Pareto improvement solutions are found for the model with deterministic cost functions. In addition, NSIWO algorithm is used to analyze this system with stochastic cost data in a risk management problem which maximizes the expected total profit but minimizes the profit risk in the market.

The main purpose of the article is to examine the causality relations of electricity consumption on economic growth in Turkey from a sectoral perspective. In this respect, the total electricity consumption and real gross domestic product series were used for the period 1970-2017 in Turkey as well as the electricity consumption of commercial, illumination, household, goverment, other and industrial sector on an annual basis. Toda-Yamamoto(1995) and Dolado-Lutkepohl(1996) tests using the MWALD test for the determination of causality relations between variables were used. According to the Toda-Yamamoto test results, it is observed that there is a two-way causality between electricity consumption and economic growth in commercial, household and industrial sectors. It has been determined that the growth hypothesis in terms of total electricity consumption with the government sector and the conservation hypothesis for the illumination sector are valid. In terms of the Dolado-Lutkepohl test, the conservation hypothesis for electricity consumption of other, household and illumination sectors is valid, while the remaining sectors have no causality. In addition, the validity of the conservation hypothesis for the illumination sector as a common result of both tests is noteworthy.

This paper considers the cost savings arising from wind generation through the merit order effect in gross pool electricity markets, using the Irish electricity market as a case study. The
Irish electricity market makes for a good testing ground due to the fact that it is a single market with very little interconnection to other markets, allowing impacts of wind to be more clearly identified than on a more interconnected system. Ireland also has extremely ambitious renewable energy targets, resulting in a high penetration of wind generation.  The authors estimate the historic cost savings arising from wind generation in the Irish electricity market using an hourly time series OLS regression model for 2009. We find that the value of wind to the market dispatch has resulted in savings of €141 million to the market dispatch. We find
that the total costs to the market would have been in the region of 12% higher over the course of the year had no wind output been available. These savings are significantly greater than the
subsidy received for wind-generated electricity over this time period, and as a result it can be seen that the positive externalities derived from wind generated electricity outweigh the cost of the subsidy; particularly when one considers the CO2 saving to the market and accepts that all forms of generation impose integration costs to electricity systems.

Price forecasting has been at the center of intense studies since the introduction of competition in Electricity industry. Price forecasts are a fundamental input to an energy company's decision making and strategy development. The present approach is an attempt to forecast day-ahead electricity prices using time series of historical data. A combination of Weighted nearest neighborhood and wavelets is used to forecast the next day electricity prices. The methodology is applied to historical data pertaining to California Electricity Market. The performance of the method is discussed with Mean Absolute Percentage Error (MAPE).

South America has been the most progressive region in the developing world in terms of deregulating the electricity industry. In this paper we compare the evolution of deregulation, from initiation to the current state, in four South American countries: Argentina, Brazil, Chile, and Colombia. These four countries are similar in many dimensions, such as culture, language and macro-economic development. They are also all depending, to a large extent, on hydro-generated electricity. All four countries have implemented different deregulated systems, allowing a unique possibility to compare the performance of different implementations of deregulation on one continent. We describe the course undertaken by these countries and the results attained so far, and also compare and contrast the development of the different electricity industries. Finally, we discuss what can be learned from these countries and what they can learn from each other.

In a competitive electricity market, a generation company (GenCo) optimizes its operation schedules, referred to as self-scheduling, in order to maximize its profit. However, various sources of uncertainty, such as market price fluctuations or forced outage of generating units, may impact the GenCo's profit. In this paper, a non-probabilistic information-gap model is proposed to model the uncertainties in short term scheduling of a GenCo. The self-scheduling problem is formulated for risk-neutral, risk-averse, and risk-seeker GenCos. Robustness of the decisions against low market prices are evaluated using a robustness model. Furthermore, windfall higher profit due to unpredicted higher market prices is modeled using an opportunity function. The proposed models are applied to a 54-unit thermal GenCo. His research focuses on economics, planning, and management of intelligent electric energy systems in a competitive electricity market environment.

This paper analyzes some unresolved pricing issues in security-constrained electricity markets subject to transmission flow limits. Although the notion of separate reserve types as proposed by FERC can be precisely and unambiguously defined, when transmission constraints are active, the very existence of separate reserve prices and markets is open to question when the prices are based on marginal costs. Instead, we submit here that the only products whose marginal costs can be separately and uniquely defined and calculated are those of energy and security at each node. Thus, under marginal pricing, at any given network bus all scheduled reserve types should be priced not at separate rates but at a common rate equal to the marginal cost of security at that bus. Furthermore, we argue that nodal or area reserves cannot be prespecified but must be obtained as by-products of the market-clearing process. Simulations back up these conclusions.

UK energy policy has evolved since the 2002 Energy Review (PIU, 2002) in which Tony Blair introduced the report and noted that "securing cheap, reliable, and sustainable sources of energy has long been a major concern for governments". The new Department of Energy and Climate Change, DECC, has rephrased its objectives 3 to "ensure our energy is secure, affordable and efficient" and "bring about a transition to a low-carbon Britain". The shift from "cheap" to "affordable" is significant, as meeting the low-carbon (low-C) targets will not be cheap, but should be affordable. We forget that in the interwar period electricity prices were three to four times more expensive than now in real terms. Since then dramatic improvements in efficiency have allowed costs and prices to fall. If one considers that real wages have improved by a factor of four over this period, electricity prices relative to earning power are now less than one tenth of their interwar level.

In a competitive electricity market, a generation company (GenCo) optimizes its operation schedules, referred to as self-scheduling, in order to maximize its profit. However, various sources of uncertainty, such as market price fluctuations or forced outage of generating units, may impact the GenCo's profit. In this paper, a non-probabilistic information-gap model is proposed to model the uncertainties in short term scheduling of a GenCo. The self-scheduling problem is formulated for risk-neutral, risk-averse, and risk-seeker GenCos. Robustness of the decisions against low market prices are evaluated using a robustness model. Furthermore, windfall higher profit due to unpredicted higher market prices is modeled using an opportunity function. The proposed models are applied to a 54-unit thermal GenCo. His research focuses on economics, planning, and management of intelligent electric energy systems in a competitive electricity market environment.

This paper studies the effects of learning and risk aversion on generation company (GenCo) bidding behavior in an oligopolistic electricity market. To this end, a flexible agent-based simulation model is developed in which GenCo agents bid prices in each period. Taking transmission grid constraints into account, the ISO solves a DC-OPF problem to determine locational prices and dispatch quantities. Our simulations show how, due to competition and learning, the change in the risk aversion level of even one GenCo can have a significant impact on all GenCo bids and profits. In particular, some level of risk aversion is observed to be beneficial to GenCos, whereas excessive risk aversion degrades profits by causing intense price competition. Our comprehensive study on the effects of Q-learning parameters finds the level of exploration to have a large impact on the outcome. The results of this paper can help GenCos develop bidding strategies that consider their rivals' as well as their own learning behavior and risk aversion levels. Likewise, the results can help regulators in designing market rules that take realistic GenCo behavior into account.

We discuss the modeling of electricity contracts traded in many deregulated power markets. These forward/ futures type contracts deliver (either physically or financially) electricity over a specified time period, and is frequently referred to as swaps since they in effect represent an exchange of fixed for floating electricity price. We propose to use the Heath-Jarrow-Morton approach to model swap prices since the notion of a spot price is not easily defined in these markets. For general stochastic dynamical models, we connect the spot price, the instantaneous-delivery forward price and the swap price, and analyze two different ways to apply the Heath-Jarrow-Morton approach to swap pricing: Either one specifies a dynamics for the non-existing instantaneousdelivery forwards and derives the implied swap dynamics, or one models directly on the swaps. The former is shown to lead to quite complicated stochastic models for the swap price, even when the forward dynamics is simple. The latter has some theoretical problems due to a no-arbitrage condition that has to be satisfied for swaps with overlapping delivery periods. To overcome this problem, a practical modeling approach is analyzed. The market is supposed only to consist of non-overlapping swaps, and these are modelled directly. A thorough empirical study is performed using data collected from Nord Pool. Our investigations demonstrate that it is possible to state reasonable models for the swap price dynamics which is analytically tractable for risk management and option pricing purposes, however, this is an area of further research.

This paper presents a proposal for multiobjective Invasive Weed Optimization (IWO) based on nondominated sorting of the solutions. IWO is an ecologically inspired stochastic optimization algorithm which has shown successful results for global optimization. In the present work, performance of the proposed nondominated sorting IWO (NSIWO) algorithm is evaluated through a number of well-known benchmarks for multiobjective optimization. The simulation results of the test problems show that this algorithm is comparable with other multiobjective evolutionary algorithms and is also capable of finding better spread of solutions in some cases. Next, the proposed algorithm is employed to study the Pareto improvement model in two complex electricity markets. First, the Pareto improvement solution set is obtained for a three-player oligopolistic electricity market with a nonlinear demand function. Then, the IEEE 30-bus power system with transmission constraints is considered, and the Pareto improvement solutions are found for the model with deterministic cost functions. In addition, NSIWO algorithm is used to analyze this system with stochastic cost data in a risk management problem which maximizes the expected total profit but minimizes the profit risk in the market.

This presentation reflects our findings regarding the impact of the Capacity Allocation and Capacity Management Regulation 2015/1222 on power  exchanges active in the electricity sector. CACM introduces a new framework for capacity allocation and capacity management through market coupling.

It assesses:
- the content of CACM against CACM's objectives
- the impact of CACM on the exercise of power exchanges activities
- the new rules CACM introduces regarding certain elements of the governance of single day-ahead and intraday market coupling  (terms, conditions or methodologies), cooperation, costs).

The presentation was given at the CREG conference on 24/3/2017 "New Governance and Regulation in the Energy Sector". For all presentations see: http://www.creg.be/sites/default/files/assets/News/2017/conference170324/presentationsconference2017.pdf

Over the last two decades, the electricity industry has shifted from regulation of monopolistic and centralized utilities towards deregulation and promoted competition. With increased competition in electric power markets, system operators are recognizing their pivotal role in ensuring the efficient operation of the electric grid and the maximization of social welfare. In this article, we propose a hypothetical new market of dynamic spatial network equilibrium among consumers, system operators and electricity generators as solution of a dynamic Stackelberg game. In that game, generators form an oligopoly and act as Cournot-Nash competitors who non-cooperatively maximize their own profits. The market monitor attempts to increase social welfare by intelligently employing equilibrium congestion pricing anticipating the actions of generators. The market monitor influences the generators by charging network access fees that influence power flows towards a perfectly competitive scenario. Our approach anticipates uncompetitive behavior and minimizes the impacts

The entire electricity infrastructure and associated socio-technical system including transmission and distribution networks, the system operator, suppliers, generators, consumers and market mechanisms will need to evolve to realize the full potential of smart-grids. At the heart of this evolution is the integration of information and communication technology (ICT) and energy infrastructures for increasingly decentralized development, monitoring and management of a resilient grid. This paper identifies the challenges of integration and four key areas of future research and development at the intersection of energy and ICT: standards-based interoperability, reliability and security, decentralized and self-organizing grid architecture, and innovative business models to unlock the potential of the energy value chain. The ideas postulated here are envisaged to act as a starting-point for future R&D direction.

The prerequisites for the development of Armenia's nuclear power industry are indicated. The main geopolitical problems of operation of the Armenian NPP are revealed through studying the electric power market of the South Caucasus with the definition of the export opportunities of Armenia. The main problems of nuclear fuel supplies to the Armenian NPP are studied. Recommendations are given on the long-term development of nuclear energy in Armenia.

The introduction of explicit demand response (DR) in the electricity markets for energy, capacity and ancillary services requires a definition of the customer baseline load (CBL). Such counterfactual – that is, what the customer would consume in the absence of demand response – is necessary to measure the effective performance of a demand resource and to properly compensate the DR provider. Methodologies for CBL estimation should strike an adequate balance between various desirable criteria, including accuracy, simplicity and integrity. The choice of the best methodology among the several available depends on factors such as the function the relevant DR product performs in the system, the broader regulatory framework for DR participation in wholesale markets, and the characteristics of the DR providers. In the US, organised electricity markets have acquired significant experience with explicit DR and tested several CBL methodologies. The North American Energy Standards Board (NAESB) has defined five types of CBL methodologies to foster harmonisation and remove market barriers for new DR providers. The five types are maximum base load, meter before / meter after, baseline type-I, baseline type-II, and metering generation output.  PJM has adopted different CBL methodologies, also depending on the specific market in which the demand resources are offered. To measure and verify the contribution of DR in day-ahead or in real-time energy markets , the default methodology belongs to the baseline type-I. Conversely, for frequency regulation and reserve, the adopted methodologies are of the meter before / meter after kind. Finally, to assess the contribution of DR in the capacity market, PJM resorts to maximum base load methodologies. European legislators currently debating the proposals of the Clean Energy Package could benefit from the lessons learnt in the past two decades by the organised markets in the US.

Turkish electricity industry is in a process of reform and restructuring; targeting competitive generation and supply markets. The very first steps of this process were vertical unbundling and creation of legislative framework. Moreover, the distribution companies and small part of the public generation facilities have been privatized. The next step is the privatization of the largest part of public generation facilities which are also have the largest market share in the country’s generation capacity. During this process, one of the most challenging issue before Turkish Competition Authority is determination of the dominance of the generation undertakings in wholesale markets. Therefore, “determination of dominant position in electricity generation” is chosen as the main title of this study. To determine dominance, first of all, the structure and design of the electricity markets are analyzed. Then, the role of market power –which could be interpreted as the economic base of the concept of dominance- within the wholesale markets, is studied. Especially using market power via strategic capacity withholding and raising the price above competitive levels is considered. The next part of the study focuses on relevant market determination where temporal dimension of the relevant markets is also analyzed. The last part is titled as “dominant position analysis” and focuses on the quantitative and qualitative evaluation methods, where pivotal supplier and residual supply indices studied besides the qualitative criterion like entry barriers, generation portfolio and collective dominance. Taking into account the parallelism of the design and legislative framework of the Turkish electricity industry with European countries; the study is made under the light of European Commission decisions.