Fushuan Wen

Conjectural variation based bidding strategy in spot markets: fundamentals and comparison with classical game theoretical bidding strategies

Abstract In this paper, the concept of conjectural variation (CV) and its applications in electricity spot markets are introduced. The conjecture of a firm is defined as its belief or expectation of how its rivals will react to the change of its output. CV based bidding strategy (CVBS) method can help generation firms to improve their strategic bidding and maximize their profits in real electricity spot markets with imperfect information. In real applications, a firm using CVBS will integrate its rivals into one fictitious competitor and estimate its generation and reaction to the firms change of output so that an optimal decision can be made accordingly. It is shown that classical game theoretic bidding strategies (GTBS) are special cases of CVBS families, and the system equilibrium reached via CVBS is a Nash equilibrium. Computer test results support the analytic conclusions very well.

A cost allocation method for reactive power service based on power flow tracing

Abstract In this paper, a novel cost allocation method for reactive power service based on power flow tracing is suggested. The corresponding reactive power price contains two parts: the production cost of reactive power and the transmission cost of reactive power. The principle and procedure of reactive power tracing are presented. The detailed formulation for the calculation of each part is derived. Computer tests are conducted using the IEEE 14-bus system and the results show that the suggested method is reasonable and practical.

On-line fault section estimation in power systems with radial basis function neural network

Fault section estimation is of great importance to the restoration of power systems. Many techniques have been used to solve this problem. In this paper, the application of radial basis function neural network (RBF NN) to fault section estimation is addressed. The orthogonal least square (OLS) algorithm has been extended to optimize the number of neurons in hidden layer and the connection weights of RBF NN. A classical back-propagation neural network (BP NN) has been developed to solve the same problem for comparison. Computer test is conducted on a four-bus test system and the test results show that the RBF NN is quite effective and superior to BP NN in fault section estimation.

Review of transmission fixed costs allocation methods

In the context of competitive electricity markets, transmission fixed costs should be fairly allocated to transmission users. A reasonable allocation method could lead to efficient utilizations of existing transmission facilities and, at the same time, provide economic signals for guiding future generation planning and load sitting. In this paper, a comprehensive literature survey is made on available methods of transmission fixed cost allocations. The review is conducted from several different aspects including: costs to be allocated, entities to pay the costs, system states to be based on, cost allocations of unused capacities, pricing of counter flow and that of reactive power, and allocation principles and methods. In addition, the characteristics of each method are analyzed and compared with those of the others.

Analysis of strategic interactions among generation companies using conjectured supply function equilibrium model

In this paper, a novel conjectured supply function equilibrium (CSFE) based model is presented for simulating strategic interactions among generation companies (GenCos) in an electricity market under incomplete information. The model is derived theoretically from the well-acknowledged supply function equilibrium theory, and a general supply function for a GenCo is obtained based on its conjectural variation of the rivals accumulated response to a change in the market price. The CSFE is a general and flexible model for simulating strategic behaviors of GenCos in an electricity market with inelastic demand. Supply functions will be linear when GenCos hold constant conjectures, and a unique equilibrium exists when linear supply functions are provided to the market. Finally, the IEEE 30-bus system is used to show the essential features of the proposed model.

Optimal bidding strategies for generation companies in electricity markets with transmission capacity constraints taken into account

In the electricity market environment, how to build optimal bidding strategies has become a major concern for generation companies. The deficiency of transmission capacity could lead to congestion, and as a result, the whole electricity market can then be actually divided into two or more submarkets. A direct consequence of transmission congestion is the change of competitive positions of generation companies concerned in the electricity market, and the optimal bidding strategies of them should accordingly be changed. In this paper, the problem of developing optimal bidding strategies for generation companies is systematically investigated with transmission capacity constraints taken into account. A stochastic optimization model is first formulated under the presumption that the bidding behaviors of rival generation companies could be modeled as normal probability distributions. An approach is next presented for solving the optimization problem using the well-known Monte Carlo simulation method and the genetic algorithm. Finally, a simple sample example and the modified IEEE 14-bus system are employed to illustrate the essential features of the proposed model and method.

Conjectural variation based learning of generator's behavior in electricity market

In this paper, a conjectural variation based learning method is proposed for generation firms to improve their strategic bidding performance in a spot electricity market taking account of the expected reaction of their rivals. With the application of conjecture, each firm can make its optimal generation decision in the learning process according to available information published in the electricity market. Examples are used to illustrate that motivation is existed for each firm to start learning, and learning of all firms will decrease the market clearing price of electricity and improve the total social welfare.

Generation planning and investment under deregulated environment: comparison of USA and China

The electric power industry all over the world has gone through a fundamental restructuring in recent years from regulated or state-owned monopolies to competitive markets. In many developed countries, such as the USA, where power companies are mostly investor-owned private enterprises, the changes are brought about in a large part because the generators of the independent power producers, originally introduced for environmental and conservation reasons in 1070s, that use newer technologies, can compete favorably with the generation from the traditional power companies. As a matter of fact, the guaranteed rate-of-return regulation has resulted on oversupply of generation in many developed countries. The developing countries in Asia, such as China, on the other hand, with their rapid economic development, face totally different pressures. Economic growth has driven up even higher growth in electricity. These countries are hard pressed to come up with the necessary capital to build the huge demand of additional generators. As a result, countries are changing the laws and rules to encourage private investment in electric generation. Private generators are then demanding open markets for fair competition and potential expansion of capacity in all three sectors, i.e. generation, higher return. The promise of the competitive market is a more efficient and responsive industry. The electric power industry is an established industry. Its investment, especially in generation, is relatively high and takes a long period of commitment. Electricity plays a tremendously important and indispensable role in the modern society: in individuals daily life and societys economic well-being. Policy makers are straddled with the difficult issue of balancing the adequacy and cost of power supply. Different rules and processes have been devised for generation planning and investment as part of the experiment in restructuring. There is no clear winner of an ideal or optimal solution. In this paper, after a brief introduction of the power industry and the current status of restructuring in China, we first discuss the process for generation planning and investment in the well as in China and then compare the impact of such different approaches in terms of the goals of deregulation, i.e., efficiency incentive, economic signaling and risk distribution

Distributed fault section estimation system using radial basis function neural network and its companion fuzzy system

The distributed radial basis function neural networks (RBF NN) can effectively solve fault section estimation (FSE) in large-scale power networks. However, when network expands or topology changes, the RBF NN has to be totally retrained, which is time-consuming and becomes a bottleneck in its applications. In this paper, functional equivalence between a RBF NN and a companion fuzzy system (CFS) is built up throughout the neural network training process, therefore the black-box-like knowledge in a RBF NN will be rule-based and transparent in its CFS. Through useful knowledge extraction from the old CFS and insertion back to the new CFS piece by piece, the RBF NN retraining issue under network expansion and topology change can be solved effectively and efficiently. In the paper, the conditions for equivalence of a RBF NN and its CFS are illustrated. The novel procedure for RBF NN retraining under network expansion and topology change is presented. The corresponding FSE system has been implemented and tested in the IEEE 118-bus power system. The simulation results show that the suggested approach for RBF NN retraining works successfully and efficiently in the case of power network expansion and topology change, which significantly improves the application potential of RBF NN in FSE of practical power systems.

Transmission planning in restructured electric power systems

Transmission planning in a restructured electric power system involves complex interplay between economics and engineering. To bridge the gap between economic and engineering considerations, this paper suggests a framework to clarify the interactions among various economic and engineering issues by reviewing recent theoretical and practical progress in transmission investment and transmission planning methodology.