الفهرس 
Introduction
PrefaceOnly 14 pages are availabe for public view
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Abstract
In this thesis a Fuzzy Based Approach (FBA) is proposed to solve the large scale unit commitment. The suggested approach treats the drawbacks in the previous fuzzy methods such as ignoring both of the unit ramp rate and minimum up/down time constraints. In the proposed solution methodology, the load balance constraint, spinning reserve constraint, and cost function are represented by fuzzy membership functions. While, the unit generation limits, ramp rate limits, and minimum up/down time limits are handled as crisp constraints. Then, a fuzzy optimization based algorithm is presented to solve the problem by using fuzzy operations and ?if then? rules. Some heuristics such as, classifying both of the hourly loads and generating units into three categories; base, medium, and peak to fasten the solution. A computer program is written to describe the suggested method and implemented on different two test systems. The results are compared with the results obtained by famous methods such as Dynamic Programming {DP), Lagrangiane Relaxation (LR), Artificial Neural Networks (ANN), and Genetic Algorithms (GA). Then, the proposed method is applied to the thermal generation system in Egyptian Utility. The results are compared with that obtained by the National Control Center (NCC). The thesis also studies effects of unit ramp rate, spinning reserve, and minimum up/down time constraints on the UC problem solutions. Conclusions about the work and the advantages of the suggested method are offered at the end of the thesis.