Optimizing Weight Factors in Multi-Objective Simulated Annealing for Dynamic Economic/Emission Dispatch ZIANE ISMAIL, BENHAMIDA FARID, AND AMEL GRAA Department of Electrotechnics Irecom laboratory, UDL university of Sidi Bel Abbes Sidi Bel Abbes, P.B. 22000 ALGERIA ziane_ismail2005@yahoo.fr, farid.benhamida@yahoo.fr, graa_amel@yahoo.fr Abstract: - This paper presents a Simulated Annealing Optimization to solve a Dynamic Economic/Emission Dispatch problem. In this work, the problem is formulated as a multi-objective one with two competing functions, namely economic cost and emission functions, subject to different constraints. The inequality constraints considered are the generating unit capacity limits while the equality constraint is generation-demand balance. To show the advantages of the proposed algorithm, it has been applied for solving multi-objective EELD problems in a 6-generators system considering NO x , SO 2 , and CO 2 emission. This technique is compared with other techniques which reveals the superiority of the proposed approach and confirms its potential for solving other power systems problems. Key-Words: - Economic dispatch, multi-objective optimization, weight factors, simulated annealing. 1 Introduction Economic Dispatch (ED) optimization is the most important issue which is to be taken into consideration in power systems. The problem of ED in power systems is to plan the power output for each devoted generator unit in such a way that the operating cost is minimized and simultaneously, matching load demand, power operating limits and maintaining stability. The gaseous pollutants emitted by the power stations cause harmful effects with the human beings and the environment like the sulphur dioxide (SO 2 ), nitrogen oxide (NO x ) and the carbon dioxide (CO 2 ), etc [1]. Thus, the optimization of production cost should not be the only objective but the reduction of emission must also be taken into account. Thus, the ED problem can be handled as a multi- objective optimization problem that the objective functions are the total cost of electrical energy and the total emission function [2]. In general, multi-objective optimization problems are solved by reducing them to a scalar equivalent. This is achieved by aggregating the objective functions into a single function [3]. Recently, multi-objective algorithms have also been used to solve the Dynamic Generation Dispatch problem. IBPVT approach [4], particle swarm optimization (PSO) [5], genetic algorithm (GA) [6], linear programming [7], and new multi-objective stochastic search [8] are proposed to solve EED multi-objective problem by generating the Pareto optimal solution. 2 Dispatch Problem Formulation The objective of solving the economic dispatch problem in electric power system is to determine the generation levels for all on-line units which minimize the total fuel cost and minimizing the emission level of the system, while satisfying a set of constraints. 2.1 Economic /Emission Dispatch The present formulation treats the EELD problem as a multi-objective mathematical programming problem which is concerned with the attempt to minimize each objective simultaneously. The equality and inequality constraints of the system must meanwhile, be satisfied. The following objectives and constraints are taken into account in the formulation of the EELD problem. The economic dispatch problem can be modeled by 1 min ( ) ( ) n T i i i F P FP = = ∑ (1) where F T is the total fuel cost; F T (P i ) is the fuel cost of generating unit i; n is the no. of generator. WSEAS TRANSACTIONS on POWER SYSTEMS Ziane Ismail, Benhamida Farid, Amel Graa E-ISSN: 2224-350X 89 Volume 10, 2015