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.

A tabu search (TS) based approach is proposed for alarming processing in power systems. First, several existing evaluation criteria describing the alarm processing problem are briefly discussed, and a new criterion is proposed. Secondly, a novel method is developed to solve this problem using a TS based method. Finally, two examples are used to demonstrate the feasibility and efficiency of the developed method. The paper also presents a comparison between the developed TS based and the more established genetic algorithm (GA) based approaches to the alarm processing problem. Many simulation results show that the TS-based approach is more efficient than the GA based approach. Key features of this proposed method are that it has solid mathematical foundation and can find multiple global optimal solutions directly and efficiently in a single run. This is very suitable for complex alarm processing problems especially for situations with missing or false alarms, because different combinations of events can produce the same set of alarms under these circumstances. The test results suggest that the developed TS based method is promising.

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.

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.

A new method for trouble call analysis in low voltage distribution systems based on set covering theory and the tabu search (TS) technique is proposed. First, a new mathematical model for the trouble call analysis is developed based upon customer trouble calls, taking into account the protective device location, selectivity and operation possibility in the distribution network protection schema. Secondly, a new method is presented to solve this problem using a TS-based method to efficiently search for the protective device(s) that was the most likely to have operated. Finally, a sample distribution system is used to demonstrate the feasibility and efficiency of the developed method. Test results suggest that the developed TS-based method is efficient.