Fuzzy controlled genetic algorithm for environmental/economic dispatch with shunt FACTS devices

In recent year and with the growth in electricity demand, environmental considerations have become one of the major management concerns. This paper presents an hybrid Genetic Algorithm and Fuzzy Logic rules for solving the economic dispatch problem under constrained emission with multi shunt Flexible AC Transmission Systems (FACTS). The economic dispatch problem is formulated as a nonlinear constrained multi objective optimization problem with both equality and inequality constraints. The problem is decomposed into, the optimal power generation subproblem that is searched by a flexible Genetic Algorithm which crossover and mutation adjusted by Fuzzy practical rules and a simple practical reasoning fuzzy rules designed as a second subproblem to control the reactive power exchanged with the network. The proposed method guarantees the near optimal solution and remarkably reduces the computation time. A global database generated based in reactive index sensitivity (RIS) as a flexible tool to choose economically the size of the shunt FACTS devices. This proposed approach is implemented with Matlab program with various case studies, and compared with conventional method and genetic algorithm (GA). The results show that the approach proposed can converge to optimum solution faster than other methods, and obtains the solution with high accuracy.