Optimal portfolio design of energy storage devices with financial and physical right market

With the continuous development of the spot market, in the multi-stage power market environment with the day-ahead market and right market, the study associated with the portfolio of energy storage devices requires that attention should be paid to transmission congestion and power congestion. To maximize the profit of energy storage and avoid the imbalance of power supply and consumption and the risk of node price fluctuation caused by transmission congestion, this paper presents a portfolio strategy of energy storage devices with financial/physical contracts. First, the concepts of financial/physical transmission rights and financial/physical storage rights are proposed. Then, the portfolio models of financial contract and physical contract are established with the conditional value-at-risk to measure the risks. Finally, the portfolio models are verified through the test data of the Pennsylvania-New Jersey-Maryland (PJM) electric power spot market, and the comparison between the risk aversion of portfolios based on financial/physical contract with the portfolio of the market without rights. The simulation results show that the portfolio models proposed in this paper can effectively avoid the risk of market price fluctuations.     

Optimal generation and reserve dispatch in a multi-area competitive market using a hybrid direct search method

With restructuring of the power industry, competitive bidding for energy and ancillary services are increasingly recognized as an important part of electricity markets. It is desirable to optimize not only the generator’s bid prices for energy and for providing minimized ancillary services but also the transmission congestion costs. In this paper, a hybrid approach of combining sequential dispatch with a direct search method is developed to deal with the multi-product and multi-area electricity market dispatch problem. The hybrid direct search method (HDSM) incorporates sequential dispatch into the direct search method to facilitate economic sharing of generation and reserve across areas and to minimize the total market cost in a multi-area competitive electricity market. The effects of tie line congestion and area spinning reserve requirement are also consistently reflected in the marginal price in each area. Numerical experiments are included to understand the various constraints in the market cost analysis and to provide valuable information for market participants in a pool oriented electricity market.     

Congestion management enhancing transient stability of power systems

In a competitive electricity market, where market parties try to maximize their profits, it is necessary to keep an acceptable level of power system security to retain the continuity of electricity services to customers at a reasonable cost. Congestion in a power system is turned up due to network limits. After relieving congestion, the network may be operated with a reduced transient stability margin because of increasing the contribution of risky participants. In this paper, a novel congestion management method based on a new transient stability criterion is introduced. Using the sensitivity of corrected transient stability margin with respect to generations and demands, the proposed method so alleviates the congestion that the network can more retain its transient security compared with earlier methods. The proposed transient stability index is constructed considering the likelihood of credible faults. Indeed, market parties participate by their security-effective bids rather than raw bids. Results of testing the proposed method along with the earlier ones on the New-England test system elaborate the efficiency of the proposed method from the viewpoint of providing a better transient stability margin with a lower security cost.     

The effect of sociodemographic diversity of residential customers on the financial risk experienced in the retail electricity market

The sociodemographic diversity of residential customers can affect the level of financial risk that an electricity provider experiences in the retail market. To demonstrate the relationship between sociodemographic diversity and financial risk, electricity consumption data drawn from the United Kingdom Power Networks ‘Low Carbon London’ project was analyzed to explore the relationship between sociodemographic diversity and financial risk experienced by electricity retailers. The results show that when increasing the sociodemographic diversity amongst a group of residential customers the effect on financial risk depends on the electricity consumption patterns of individual customers and the relationship of consumption patterns between residential customers. Increasing sociodemographic diversity amongst residential customers with very distinct energy consumption patterns can decrease the overall financial risk associated with the aggregated revenue received from these customers. However, the results showed that adding customers to a customer base without consideration for their sociodemographic background can cause the overall financial risk associated with the aggregated revenue received to change erratically. Whilst previous studies have considered customer diversity and its influence on peak electricity demand, this research advances the state-of-the-art by showing the importance of customer diversity to the financial quantity risk experienced by electricity retailers. This finding has serious implications for electricity providers seeking to mitigate financial risk in the retail electricity market.     

An agent-based analysis of the German electricity market with transmission capacity constraints

While some agent-based models have been developed for analyzing the German electricity market, there has been little research done on the emerging issue of intra-German congestion and its effects on the bidding behavior of generator agents. Yet, studies of other markets have shown that transmission grid constraints considerably affect strategic behavior in electricity markets. In this paper, the implications of transmission constraints on power markets are analyzed for the case of Germany. Market splitting is applied in the case of congestion in the grid. For this purpose, the agent-based modeling of electricity systems (AMES) market package developed by Sun and Tesfatsion is modified to fit the German context, including a detailed representation of the German high-voltage grid and its interconnections. Implications of transmission constraints on prices and social welfare are analyzed for scenarios that include strategic behavior of market participants and high wind power generation. It can be shown that strategic behavior and transmission constraints are inter-related and may pose severe problems in the future German electricity market.     

Optimal electricity market for wind power

This paper is about electricity market operation when looking from the wind power producers’ point of view. The focus in on market time horizons: how many hours there is between the closing and delivering the bids. The case is for the Nordic countries, the Nordpool electricity market and the Danish wind power production. Real data from year 2001 was used to study the benefits of a more flexible market to wind power producer. As a result of reduced regulating market costs from better hourly predictions to the market, wind power producer would gain up to 8% more if the time between market bids and delivery was shortened from the day ahead Elspot market (hourly bids by noon for 12–36 h ahead). An after sales market where surplus or deficit production could be traded 2 h before delivery could benefit the producer almost as much, gaining 7%.     

Energy price forecasting - problems and proposals for such predictions

This paper discusses the value of price forecasting in the electricity market during bidding or hedging against volatility. When bidding in a pool system, the market participants are requested to express their bids in terms of prices and quantities. Since the bids are accepted in order of increasing price until the total demand is met, a company that is able to forecast the pool price can adjust its own price/production schedule depending on hourly pool prices and its own production costs. This paper also discusses the challenges of price forecasting and describes some of the proposed methods for meeting these challenges.     

Transmission capacities and competition in Western European electricity market

The integration of national electricity markets into a single European one is expected to reduce the ability of dominant players to exercise market power. This paper investigates whether or not existing transmission capacities of cross-border interconnectors are sufficient to achieve this result and create vigorous competition in the market. A model with two decision levels is used. On the first level profit maximizing generators play Cournot game against each other. On the last level the system operator clears the market and determines flows in the network to maximize social welfare subject to a set of physical constraints. As each strategic generator anticipates her impact on equilibrium prices and congestion in the system, her optimization problem is subject to equilibrium constraints from the system operator's problem.The analysis demonstrates that interconnector capacities in Western Europe are insufficient for integration alone to reduce the exercise of market power. I compare several possible competition-enhancing policies: expansion of interconnectors and different scenarios of national markets’ restructuring. I show that although increase of line capacity is a useful tool to stimulate competition in an integrated market, it is not a substitute for the restructuring of large players.     

Real-world market representation with agents

As power markets are relatively new and still continue to evolve, there is a growing need for advanced modeling approaches that simulate the behavior of electricity markets over time and how market participants may act and react to the changing economic, financial and regulatory environments in which they operate. A new and rather promising approach is to model the electricity market as a complex adaptive system using an agent-based modeling and simulation (ABMS) approach. The purpose of an ABMS model is not necessarily to predict the outcome of a system but to reveal and understand the complex and aggregate system behaviors that emerge from the interactions of the heterogeneous individual entities. Emergent behavior is a key feature of ABMS and is not easily inferred from the simple sum of the behavior of its components. By relying on both established engineering modeling techniques as well as advanced quantitative economic market principles, the ABMS approach is uniquely suited to addressing the strategic issues of interest to different market participants as well as those of market monitors and regulators.     

Supply curve bidding of electricity in constrained power networks

This paper presents a Supply Curve Bidding (SCB) approach that complies with the notion of the Standard Market Design (SMD) in electricity markets. The approach considers the demand-side option and Locational Marginal Pricing (LMP) clearing. It iteratively alters Supply Function Equilibria (SFE) model solutions, then choosing the best bid based on market-clearing LMP and network conditions. It has been argued that SCB better benefits suppliers compared to fixed quantity-price bids. It provides more flexibility and better opportunity to achieving profitable outcomes over a range of demands. In addition, SCB fits two important criteria: simplifies evaluating electricity derivatives and captures smooth marginal cost characteristics that reflect actual production costs. The simultaneous inclusion of physical unit constraints and transmission security constraints will assure a feasible solution. An IEEE 24-bus system is used to illustrate perturbations of SCB in constrained power networks within the framework of SDM. By searching in the neighborhood of SFE model solutions, suppliers can obtain their best bid offers based on market-clearing LMP and network conditions. In this case, electricity producers can derive their best offering strategy both in the power exchange and the long-term contractual markets within a profitable, yet secure electricity market.     

Price formation in electricity forward markets and the relevance of systematic forecast errors

Since the liberalisation of the European electricity sector, forward and futures contracts have gained significant interest of market participants due to risk management reasons. For pricing of these contracts an important fact concerns the non-storability of electricity. In this case, according to economic theory, forward prices are related to the expected spot prices which are built on fundamental market expectations. In the following article the crucial impact parameters of forward electricity prices and the relationship between forward and future spot prices will be assessed by an empirical analysis of electricity prices at the European Energy Exchange and the Nord Pool Power Exchange. In fact, price formation in the considered markets is influenced by historic spot market prices yielding a biased forecasting power of long-term contracts. Although market and risk assessment measures of market participants and supply and demand shocks can partly explain the futures-spot bias inefficiencies in the analysed forward markets cannot be ruled out.     

Multi-objective congestion management incorporating voltage and transient stabilities

Congestion in a power system is turned up due to operating limits. To relieve congestion in a deregulated power market, the system operator pays to market participants considering their bids to alter their active powers. After relieving congestion, the network may be operated with a reduced voltage or transient stability margin because of hitting security limits or increasing the contribution of risky participants. The proposed multi-objective framework for congestion management in this paper simultaneously optimizes competing objective functions of congestion management cost, voltage security, and dynamic security. The voltage stability margin and corrected transient energy margin are employed as indices to be incorporated into the multi-objective congestion management. A fuzzy decision maker is proposed to derive the most efficient solution among Pareto-optimal solutions of multi-objective mathematical programming problem. Results of testing the proposed method on the New-England test system elaborate the efficiency of the proposed method.     

Extending the bidding format to promote demand response

We propose an extended bidding structure to allow more realistic demand characteristics and behaviors to be expressed via flexible bids. In today's ISO-run energy markets, demand bid formats are all separable over time. However, a significant and growing segment of demand can be shifted across time and therefore has no way to bid its true valuation of consumption. We propose additional bid types that allow deferrable, adjustable and storage-type loads to better express their value, and thus elicit demand response in the most natural way – via direct participation in the market. We show that the additional bid types are easily incorporated into the existing market with no technological barrier and that they preserve the market's efficiency and incentive-compatibility properties. Using real market data, we give a numerical demonstration that the extended bid format could substantially increase social welfare, and also present additional insight on storage expansion scenarios.     

Potential of trading wind power as regulation services in the California short-term electricity market

A short-term electricity market is usually composed of the energy market and ancillary service market. However, wind power is not allowed to be traded in ancillary service markets although it has been proven technically feasible to be regulation services. This paper aims to explore the market potential of trading wind power as regulation services in the California electricity market. A model for wind power trade in the day-ahead (DA) market is established considering the uncertainties of market prices and wind power. An optimal trading strategy for wind power producers is derived by using an analytical algorithm. Trading wind power as regulation is tested by using actual data and the impacts of market control on the market outcome are discussed. The results show that, based on the current framework of the California electricity market, wind power producers can earn much more money if they bid in the DA energy and regulation markets than if they only bid in the DA energy market. The results also show that the potential to enhance profit for wind power producers is larger in the regulation down market than in the regulation up market.     

An approach to locational marginal price based zonal congestion management in deregulated electricity market

Congestion of transmission line is a vital issue and its management pose a technical challenge in power system deregulation. Congestion occurs in deregulated electricity market when transmission capacity is not sufficient to simultaneously accommodate all constraints of power transmission through a line. Therefore, to manage congestion, a locational marginal price (LMP) based zonal congestion management approach in a deregulated electricity market has been proposed in this paper. As LMP is an economic indicator and its difference between two buses across a transmission line provides the measure of the degree of congestion, therefore, it is efficiently and reliably used in deregulated electricity market for congestion management. This paper utilizes the difference of LMP across a transmission line to categorize various congestion zones in the system. After the identification of congestion zones, distributed generation is optimally placed in most congestion sensitive zones using LMP difference in order to manage congestion. The performance of the proposed methodology has been tested on the IEEE 14-bus system and IEEE 57-bus system.     

Trading behaviour on the continuous intraday market Elbas

Intraday markets for electricity allow for trading of energy until shortly before the period of delivery. This offers market participants a possibility to reduce their expected imbalances and to offer own unused flexibility. Because this form of distributed balancing before the period of delivery can be profitable for market participants as well as beneficial for system operations, intraday trading is expected to gain more importance in future, especially with increasing shares of variable renewable energy sources in the generation mix.So far, intraday markets are still a research field with many open questions. This paper contributes by a first analysis of intraday trades on Elbas, one of the European intraday markets. The analysis gives a detailed picture on trading activity and price development and is intended to improve understanding of continuous intraday trading.Findings include that trading activity differs significantly between price zones, that most trades occur in the last hours before gate closure and that market participants have to handle substantial price variations during the trading period. The paper also investigates the imbalance settlement rules in the Nordic countries and studies which effects one- and two-price imbalance settlement systems have on the market participants' profitability of intraday trading.     

Competitive and risk-adequate auction bids for onshore wind projects in Germany

In recent years, auction mechanisms have gained in significance in the context of renewable energy deployment. An increasing number of countries have adopted auctions for the allocation of permits and financial support for renewable energy projects, thereby increasing competition among project developers. As a result, profit margins have decreased significantly while sensitivity to risks and uncertainty has increased. The adequate quantification of bid prices is a key challenge. We present a modeling approach to determine competitive and risk-adequate auction bids. The contribution of this paper is an improved method for quantifying marginal cost, which is the minimum sales price per unit of electricity through which the investment criteria of all project stakeholders are fulfilled. In our financial model, the risk-adequateness is determined through the investment criteria of equity investors by means of the adjusted present value, and those of debt investors by means of the debt service cover ratio, through Monte Carlo simulations. The resulting marginal cost serve as the starting point for strategic bidding optimization, regardless of the pricing rule in the contemplated auction design. To demonstrate the integrability of our mathematical model with strategic bidding optimization, we check its applicability in a case study, which shows how a German project developer should bid to realize an onshore wind farm project. We show that our model enables the quantification of bid prices that are both competitive and risk-adequate.     

Photovoltaic electricity production of a grid-connected urban house in Serbia

A technically attractive solution for sustainable present and future is to integrate photovoltaic (PV) panels into building fabric of urban houses as an alternative to grid electricity, however, in Serbia this technology is rarely applied. To contribute to sustainability and create success conditions for renewable energy sources (RES) applications due its wish to join EU, Serbian government currently integrated RES into its new energy policy framework. In the near future in the separate law, the government will identify financial conditions to apply this policy and start RES use. To adequately inform this law, we calculated the electricity revenue during entire life of a two-floor house in Belgrade, Serbia and investment in PV panels (currently available on Serbian market) integrated in its entire envelope. It was discussed what are the current degree of economic viability of this solution and suggested level of state subventions needed to support the solar electricity production either by feed-in tariffs or other financial instruments.     

Welfare implications of capacity payments in a price-capped electricity sector: A case study of the Texas market (ERCOT)

The aim of this paper is to analyze the welfare consequences of introducing capacity compensation payments in restructured and liberalized electricity markets. For that purpose, we set up a two-stage framework in which two kinds of electricity generators, peak load and base load generators, choose their capacity investment levels first and then compete on the basis of bids in a centralized market to sell electricity to consumers. We use data from the Texas ERCOT to evaluate consumers' welfare. We find that the introduction of capacity payments has two countervailing effects. On the one hand, it increases the wholesale electricity price. On the other hand, it reduces price volatility and increases the reliability of the system. We find that capacity payments are more beneficial for consumers in a perfectly competitive market than in the presence of certain degree of market power.     

Trading wind energy on the basis of probabilistic forecasts both of wind generation and of market quantities

Wind power is not easily predictable and non‐dispatchable. Nevertheless, wind power producers are increasingly urged to participate in electricity market auctions in the same manner as conventional power producers. The aim of this paper is to propose an operational strategy for trading wind energy in liberalized electricity markets and to assess its performance. At first, the so‐called optimal quantile strategy is revisited. It is proved that without market power, i.e. under the price‐taker assumption, this strategy maximizes expected market revenues. Forecasts of wind power production, of day‐ahead and real‐time market prices and of the system imbalance are inputs to this strategy. Subsequently, constraining of the bid that maximizes the expected revenues is proposed as a way to overcome the strategy's disregard of practical limitations and, at the same time, of risk. Two constraining techniques are introduced: constraining in the decision space and in the probability space. Finally, the trade of a wind power producer is simulated in a test case for the Eastern Danish (DK‐2) price area of the Nordic Power Exchange (Nord Pool) during a 10 month period in 2008. The results of the test case show the financial benefits of the aforementioned strategy as well as the consequent interaction with the electricity market. This study will support a demonstration in the framework of the EU project ANEMOS.plus. Copyright © 2012 John Wiley & Sons, Ltd.