Abstract: In modern industrialized society, it is mandatory to provide an uninterrupted high-quality supply of electric energy at modest cost while promoting a cleaner environment. This can only be realized through very sophisticated power system operation dealing with several contradictory factors, namely, economy, security and environment having trade-off relationship to each other. One class of problem that simultaneously satisfies several criteria in trade-off relationship is called "multiobjective optimization problem (MOP)." The paper proposes an interactive fuzzy satisfying method for solving MOP. The operating cost, emission pollutants and security index are taken as objectives to be minimized simultaneously. The line flows are obtained from generalized Z-bus distribution factors (GZBDF). The objective functions are quantified by eliciting the corresponding membership functions (MFs). Weighting method is employed to simulate the trade-off relation between conflicting objectives in non-inferior domain. The generation of complete non-inferior solution surface is a time consuming process and is a great burden on decision maker (DM) for more than two objectives. Therefore, the Evolutionary optimization method has been employed to search the optimal weights in the non-inferior domain. The applicability of the proposed method has been duly tested on 25-bus sample system having five generators.
Y. S. Brar , J. S. Dhillon and D. P. Kothari , 2004. Interactive Fuzzy Satisfying Multi-Objective Generation Scheduling . Asian Journal of Information Technology, 3: 999-1007.