Design and Simulation of Fuzzy, Neuro Fuzzy based Optimizer and Comparative Analysis of Unit Commitment Problem

摘要

This paper describes the application of fuzzy logic concept to unit commitment problem. The main objective of unit commitment is to minimize the total production cost over the study period and to satisfy the constraints imposed on the system, such as, power generation-load balance, spinning reserve, operating constraints, minimum up time and minimum down time, etc. Several conventional methods are available to solve the unit commitment problem, but all these methods need the exact mathematical model of the system and there may be a chance of getting stuck at the local optimum. In this paper, fuzzy logic approach is described which achieves a logical and feasible economic cost of operation of power system without the need of exact mathematical for mulation. Efficient methods of production can help reduce this cost In this work, DP method is combined with fuzzy logic to obtain the production cost of thermal power plant The system demand, the reserve requirements and the operational cost will serve as fuzzy quantities. Two fuzzy logic methods have been employed to combine with DP method. These methods are fuzzy logic approach and fuzzy neural approach. The results obtained from the fuzzy logic approach (FLA) are compared with the solution obtained from fuzzy neural approach. From the comparison, it is proved that the fuzzy neural approach is a powerful tool for solving such highly non-linear problems.