Restructuring of the power industry worldwide has brought the issue of market competitiveness to the forefront. While "vertical" market power has been limited by disaggregating generation and transmission, nondiscriminatory access to the transmission system by power suppliers, and the creation of the Independent System Operator (ISO), "horizontal" and localized market power still survives. In the last few years, the issue of a small number of generators exercising market power has received a great deal of attention, and much has been published on how to identify and mitigate such abuse by market management measures. This paper focuses on the analysis and mitigation of market power in electricity supply.

One of the challenges for power industry restructuring is to maintain sufficient generation installed capacity to meet demand in nowadays and in the future, and the electricity market failure in California has brought this subject to the forefront of extensive debates. This paper initiates a review, assessment and discussion on some important issues related to ensuring adequate generation capacity additions under a competitive electricity market environment.

stochastic optimization formulation is developed and two methods proposed for describing and solving this problem. A numerical example serves to illustrate the essential features of the approach and the results are used to investigate the potential market power.

A systematic and mathematically sound model and a refined genetic algorithm (RGA) based method for fault-section estimation in power systems is proposed. First, the probabilistic causality relationship among section fault, protective relay action and circuit breaker trip is formulated as a probabilistic causality matrix. Secondly, the well-developed parsimonious set covering theory is applied to the fault-section estimation problem, and a 0-1 integer programming model is then obtained. Thirdly, a RGA-based method for fault-section estimation is developed by using information on operations of protective relays and circuit breakers. The proposed method is versatile and can deal with uncertainties in fault-section estimation, such as protective relay failures and/or malfunction and circuit breaker failures and/or malfunction. Test results for a sample power system have shown that the probabilistic approach developed for fault-section estimation is feasible and efficient.

The new electricity market behaves more like an oligopoly than a laissez-faire market due to special features such as, a limited number of producers, large investment size (barrier to entry), transmission constraints and transmission losses which discourage purchase from distant suppliers. This makes it possible for only a few generating companies to service a given geographic region. In an imperfect market each power supplier can increase its own profit through strategic bidding. The problem of building optimally co-ordinated bidding strategies for competitive suppliers in energy and spinning reserve markets is addressed. Each supplier bids a linear energy supply function and a linear spinning reserve supply function to the energy and spinning reserve markets, respectively, and the two markets are dispatched separately to minimise customer payments. Each supplier chooses the coefficients in the linear energy and spinning reserve supply functions to maximise total benefits, subject to expectations about how rival suppliers will bid. A stochastic optimisation model is first developed to describe this problem and a genetic algorithm based method is then presented to solve it. A numerical example is utilised to illustrate the essential features of the method.