M. Trivedi and E. Makram (USA)
Environmental/economic power dispatch, multi-objective optimization, evolutionary algorithms, genetic algorithm, hydro-thermal system
The environmental/economic dispatch (EED) problem is a multi-objective nonlinear optimization problem with equality and inequality constraints. A multi-objective optimization problem requires a set of trade-off solutions to solve it. The ability of evolutionary algorithms to find the multiple Pareto optimal solutions in a single simulation run makes it attractive for solving problems with multiple and conflicting objectives. This paper presents a genetic algorithm based approach to solve multi-objective hydro-thermal generation scheduling problem. The proposed approach minimizes two conflicting objectives while allocating the electricity demand among the committed generating units subject to physical and technological constraints. Operating cost and SO2 emissions are the objectives undertaken to be minimized simultaneously. Fuzzy set theory is applied to extract the best compromise non-dominated solution. Simulation results for one hydro and three thermal generator sample power system have been presented to illustrate the performance and applicability of the proposed method. Effects of the hydro unit on the fuel cost and the SO2 emissions have been studied by the simulation results.
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