A new type of power system stabiliser based on fuzzy set theory is proposed to improve the dynamic performance of a multimachine power system. To have good damping characteristic over a wide range of operating conditions, speed deviation (Am) and acceleration (Ah) of a machine are chosen as the input signals to the fuzzy stabiliser on that particular machine. These input signals are first characterised by a set of linguistic variables using fuzzy set notations. The fuzzy relation matrix, which gives the relationship between stabiliser inputs and stabiliser output, allows a set of fuzzy logic operations that are performed on stabiliser inputs to obtain the desired stabiliser output. Since only local measurements are required by the fuzzy stabiliser on each generating unit, the proposed stabiliser is of decentralised output feedback form and is easy for practical implementation. The effectiveness of the proposed fuzzy stabiliser is demonstrated by a multimachine system example.

A probabilistic approach to examining the effect of operating reserve on the reliability and security of the Taiwan power system is developed. To evaluate the probability of failure to carry load in system operation, an extension of the original PJM (Pennsylvania-New Jersey-Maryland) method is presented. System security is analysed using the reliable emergency output power (REOP) index. The proposed methods are applied to evaluate the reliability and security of the Taiwan power system using the operating records of the past five years. 32 load patterns are examined for each year to cover the different seasons of the year, the different days of the week and the peak and off-peak periods of the day. The factors affecting system reliability and security such as the amount and type of spinning reserves and the availability of rapid-start units are extensively examined. It is found that the presented probabilistic approach can provide valuable information which can assist the system operators to reach a secure and reliable, as well as economical, unit commitment strategy.

Contingency selection is important for the security analysis of a large scale power system since it can reduce the required computational effort by ranking the various outage events according to their severities. Among the three aspects of power system security, i.e., transient security, dynamic security, and steady-state security, contingency selection for dynamic security assessment is of concern in this paper. The proposed method is to use an iterative method to compute the eigenvalues of the system under outage conditions. The initial values for the iterative procedure are the eigenvalues for the normal operating condition (base case eigenvalues). T o reduce the computational burden, the eigenvalues of the system under outage conditions from the first iteration are employed for contingency ranking. From the results obtained from the study on Taiwan power system, it is concluded that contingency ranking using the eigenvalues from the first iteration is both accurate and efficient. It is also found that only the eigenvalues for the worst-damped mode must be considered in contingency ranking. T o further improve the efficiency of the proposed method, results obtained from the first iteration of the fast decoupled load flow (FDLF) are also used to model the operating conditions after contingencies. Again, it is observed that satisfactory dynamic contingency selection can be achieved by using the first iteration of FDLF with much less computational effort than that required by full AC power flow. It is thus concluded that accurate dynamic contingency selection can be performed efficiently by first computing the operating conditions after contingencies using the first iteration of FDLF and then calculating the eigenvalues for the worst-damped mode by using the first iteration of eigenvalue computations.

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