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This paper presents a mixed-integer linear programming (LP) formulation for the long-term transmission expansion planning problem in a competitive pool-based electricity market. To achieve optimal expansion planning while modeling market functioning, we define a number of scenarios based on the future demand in the system and we simulate the maximization of the aggregate social welfare. Investment and operating costs, transmission losses and generator offers, and demand bids are considered. We propose to use a set of metrics to rate the effect of the expansion on the generators, demands, and the system as a whole. The proposed model is applied to the Garver six-bus system and to the IEEE 24-bus Reliability Test System. Simulation results can be interpreted in economic terms based on the values of the metrics obtained for different scenarios, parameters, and topologies. Index Terms--Electricity market, mixed-integer linear programming, social welfare, transmission expansion planning.

This paper addresses the problem of allocating the cost of the transmission network to generators and demands. A physically-based network usage procedure is proposed. This procedure exhibits desirable apportioning properties and is easy to implement and understand. A case study based on the IEEE 24-bus system is used to illustrate the working of the proposed technique. Some relevant conclusions are finally drawn. Index Terms--Network usage, transmission cost allocation, [Z.sub.bus]

The expansion of transmission systems impacts many entities in the market environment. Each entity may fare better or worse as a result of congestion relief in the presence of new investments. Negatively affected firms exert their influence to prevent the expansion from taking place. The opposition of these firms and the lack of appropriate incentives results in insufficient investments in transmission assets. The network is being frequently used at its maximum limits, leading to economic inefficiencies and reduced reliability. Hence, there is a need for effective incentive schemes for network expansion. In this paper, we propose a game theory-based scheme for the allocation of transmission expansion costs among market entities. The allocation takes into account both the physical and economic impacts of the new transmission assets and the influence of each firm on the expansion decision. This is the first scheme designed to give all market participants explicit incentives to support the expansion. The application of the allocation solution to the Garver six-bus system is presented to illustrate the capabilities of the proposed method. Index Terms--Cooperative game theory, cost allocation, investment incentives, Shapley value, social welfare, transmission expansion.

Price forecasting is becoming increasingly relevant to producers and consumers in the new competitive electric power markets. Both for spot markets and long-term contracts, price forecasts are necessary to develop bidding strategies or negotiation skills in order to maximize profits. This paper provides an approach to predict next-day electricity prices based on the Generalized Autoregressive Conditional Heteroskedastic (GARCH) methodology that is already being used to analyze time series data in general. A detailed explanation of GARCH models is presented and empirical results from the mainland Spain and California deregulated electricity-markets are discussed. Index Terms--Electricity markets, forecasting, GARCH models, time series analysis, volatility.

Pool-based electricity markets can be simulated with various degrees of accuracy. When compared to actual markets, most of the simulators produce outcomes than cannot be extrapolated beyond the specific scenario analyzed. This is most critical for regulators and market participants which need tools to analyze market power and bidding strategies, respectively, for a broad range of scenarios. Both objectives can be tackled if the possible equilibria of a pool-based multiperiod market are determined. This paper presents a three-step methodology to find these equilibria. First, a detailed model of an electricity market is presented, considering multiperiod bidding, price elasticity, and network modeling. Second, an iterative simulation process is run to detect participants' bidding strategies implicit in the optimized production resulting from the simulation. Finally, output data from the simulator are analyzed to obtain Nash equilibria. Iterated deletion is used in the last step to remove strategies that are dominated by others that generate higher profits. A realistic case study illustrates the proposed technique. Index Terms--Electricity markets, market power, market simulation, Nash equilibrium.

A numerical method based on a relaxation algorithm and the Nikaido--Isoda function is presented for the calculation of Nash--Cournot equilibria in electricity markets. Nash equilibrium is attained through a relaxation procedure applied to an objective function, the Nikaido--Isoda function, which is derived from the existing profit maximization functions calculated by the generating companies. We also show how to use the relaxation algorithm to compute, and enforce, a coupled constraint equilibrium, which occurs if regulatory, generation, and distribution (and more) restrictions are placed on the companies and entire markets. Moreover, we use the relaxation algorithm to compute players' payoffs under several player configurations. This is needed for the solution of our game under cooperative game theory concepts, such as the bilateral Shapley value and the kernel. We show that the existence of both depends critically on demand price elasticity. The numerical method converges to a unique solution under rather specific but plausible concavity conditions. A case study from the IEEE 30-bus system, and a three-bus bilateral market example with a dc model of the transmission line constraints are Presented and discussed. Index Terms--Bilateral Shapley value, coalition formation, coupled constraints, electricity markets, kernel, Nash-Cournot equilibrium, Nikaido-Isoda function, relaxation algorithm.

Price forecasting is becoming increasingly relevant to producers and consumers in the new competitive electric power markets. Both for spot markets and long-term contracts, price forecasts are necessary to develop bidding strategies or negotiation skills in order to maximize benefit. This paper provides a method to predict next-day electricity prices based on the ARIMA methodology. ARIMA techniques are used to analyze time series and, in the past, have been mainly used for load forecasting, due to their accuracy and mathematical soundness. A detailed explanation of the aforementioned ARIMA models and results from mainland Spain and Californian markets are presented. Index Terms--ARIMA models, electricity markets, forecasting, market clearing price, time series analysis.

This paper addresses the self-scheduling of a hydro generating company in a pool-based electricity market. This company comprises several cascaded plants along a river basin. The objective is to maximize the profit of the company from selling energy in the day-ahead market. This paper proposes a 0/1 mixed-integer linear programming model to account, in every plant, for the nonlinear and nonconcave three-dimensional (3-D) relationship between the power produced, the water discharged, and the head of the associated reservoir. Additionally, start-up costs due mainly to the wear and tear are considered. Finally, different realistic case studies are analyzed in detail. Index Terms--Hydroelectric producer, mixed-integer LP, pool-based electricity market.

This paper addresses the self-scheduling problem faced by a price-maker to achieve maximum profit in a pool-based electricity market. An exact and computationally efficient mixed-integer linear programming (MILP) formulation of this problem is presented. This formulation models precisely the price-maker capability of altering market-clearing prices to its own benefits, through price quota curves. No assumptions are made on the characteristics of the pool and its agents. A realistic case study is presented and the results obtained are analyzed in detail. Index Terms--Electricity pool market, market power, mixed-integer linear programming (MILP), price maker.

The target of an oligopolistic generating company in a pool-based electric power market is to maximize its profits using two related instruments at hand: 1) its ability to modify the market-clearing price and 2) its capability to alter its own production level. Power balance is not an issue for the generating company; the independent system operator ensures power balance considering generator and demand bids through any market-clearing procedure. This paper proposes a mathematical model to determine the output of the generators owned by an oligopolistic generating company so that its profit is maximized for a one-day to one-week time horizon. An efficient solution technique to solve the resulting large-scale discontinuous nonlinear mixed-integer optimization problem is reported. A case study that illustrates the proposed model and the solution technique developed is analyzed in detail. Index Terms--Electric power market, market power, oligopolistic generating company, power pool, price-quota function, stepwise nonlinear mixed-integer optimization.

In the framework of competitive electricity markets, power producers and consumers need accurate price forecasting tools. Price forecasts embody crucial information for producers and consumers when planning bidding strategies in order to maximize their benefits and utilities, respectively. This paper provides two highly accurate yet efficient price forecasting tools based on time series analysis: dynamic regression and transfer function models. These techniques are explained and checked against each other. Results and discussions from real-world case studies based on the electricity markets of mainland Spain and California are presented. Index Terms--Electricity markets, forecasting, market clearing price, time series analysis.

The new competitive framework that has been established in several electricity markets all over the world has changed the way that electric companies attain benefits. Under this new scenario, generation companies need to develop bidding models not only for the sake of achieving a feasible dispatch of their units, but also for maximizing their benefits. This paper presents a new bidding strategies model which considers the global policy of a company, but also specifies the bid of each generating unit. The proposed model produces a maximum price bid and an optimal bidding quantity by means of an iterative procedure using the generating company's residual demand curve. It is based on an economic principle known as the cobweb theorem, frequently used to study stability in trading markets. A realistic case study from the Spanish daily electric market is presented to illustrate the methodology. Index Terms--Bidding strategies, cobweb theorem, electricity markets, Nash--Cournot equilibrium, residual demand.

Deregulation in electricity markets requires fast and robust optimization tools for a secure and efficient operation of the electric power system. In addition, there is the need of integrating and coordinating operational decisions taken by different utilities acting in the same market. Distributed Energy Management Systems (DEMS) may help to fulfill these requirements. The design of a DEMS requires detailed simulation results for the evaluation of its performance. To simulate the operation of a DEMS from the optimization standpoint, a general purpose distributed optimization software tool, DistOpt, is used, and its capabilities are extended to handle power system problems. The application to the optimal power flow problem is presented. Index Terms--Deregulation, distributed energy management systems (DEMS), distributed optimization.

The study of a decentralized coalition formation scheme in a specific power systems transmission expansion scenario is the purpose of this paper. We define first who are the agents in the expansion game and provide a decentralized coalition scheme based on Bilateral Shapley values. Finally, we allocate the total costs of expansion amongst the agents, based on the coalition history, and we compare our method with a centralized scheme. Keywords: Transmission planning, power systems, cooperative game theory, multi-agent systems

Competition in day-ahead electricity markets has been established through auctions where generators and loads bid prices and quantities. Different approaches have been discussed regarding the market auction design. Multi-round auctions, despite its implementation complexity, allow market participants to adapt their successive bids to market prices considering their operational and economic constraints. However, most of the day-ahead electricity market implementations use noniterative single-round auctions. This paper presents a market simulator to compare both auction models. Different auction alternatives, such as the Spanish single-round auction that takes into account special conditions included in the generator bids, and multi-round auctions with different stopping rules, are analyzed. The results and acquired experience in the simulation of the Spanish market, started in January 1998, are presented. Hourly market prices, average daily price, price/demand correlation and several economic efficiency indicators, such as generator surplus, consumer surplus and social welfare, are compared to derive conclusions regarding the performance of the auction alternatives. Editor's note: 'This paper originally appeared in the IEEE Transactions on Power Systems, vol. 16, no. 1, pp. 88-96, Feb. 2001. It is being republished due to typesetting errors.'-M. P. Bhavaraju Index Terms--Auctions, bidding strategies, electricity markets, market clearing price.

With deregulation sweeping all over electrical systems around the world, transmission planning has undergone dramatic changes during this decade. Centralized cost allocation methods have become obsolete and new procedures are needed to deal with intelligent and self-sufficient players. In this paper we study the allocation of transmission costs in a decentralized manner. For this purpose we have developed a multi-agent system that is based on a well known cooperative game theory procedure, the kernel. Using our approach, the agents are able to form kernel-stable coalitions and the cost allocation procedure is performed at every step of the kernel- algorithm. A six bus example and an IEEE 24 bus case illustrate our model. Index Terms--Cooperative game theory, kernel, multi-agent systems, transmission planning.

This paper presents a new approach for the joint energy and reserves scheduling and unit commitment with n-K reliability constraints for the day-ahead market. The proposed method includes a novel n-K criterion where demand must be met with a specified probability under any simultaneous loss of K generating units. A chance-constrained method is proposed with an \alpha-quantile measure to determine the confidence level to meet the demand under K simultaneous contingencies. The chance-constrained optimization problem is recast as a mixed integer linear programming optimization problem. Wind and demand uncertainty are included into the model. The methodology proposed is illustrated with several case studies where the effect of increasing wind power penetration is analyzed showing the performance of our model. [ABSTRACT FROM PUBLISHER]

This paper addresses the problem of allocating the cost of the transmission network to generators and demands. A physically-based network usage procedure is proposed. This procedure exhibits desirable apportioning properties and is easy to implement and understand. A case study based on the IEEE 24-bus system is used to illustrate the working of the proposed technique. Some relevant conclusions are finally drawn. [ABSTRACT FROM AUTHOR]

Discusses a study which presented a solution to the problem of assigning the expansion cost of a transmission system operating in multilateral access. How algorithms of assignment of transmission costs operate; Results of the study. INSET: Closure to Discussion of 'A Kernel-Oriented Algorithm for....