MULTI-OBJECTIVE BASED ECONOMIC EMISSION DISPATCH PROBLEM IN THERMAL-WIND SYSTEM USING IFOA TECHNIQUE

Abstract

This paper proposed a multi-objective based hybrid methodology to understand Economic Emission Dispatch (EED) issue coordinates wind power with thermal units. The mixture approach is the joined execution of both the Improved Fruit Fly Optimization Algorithm (IFOA) and Artificial Neural Network (ANN) system. In this work, the IFOA is used for optimizing the blend of the thermal generators
in view of the wind power vulnerability. The ANN is used to catch the vulnerability occasions of wind power to the system is guaranteed the high use of wind power. Accordingly, a solution of the proposed optimization approach is limited the total fuel cost and emission cost. To approve the proposed strategy viability, the six generating units thermal system is considered with fuel and emission cost as two clashing targets to be upgraded in the meantime. The proposed strategy is executed in MATLAB working platform and the outcomes are inspected with thinking about generation units and which is contrasted and different solution procedures. The comparison happens uncovers the nature of the proposed approach and broadcasts its capacity for dealing with multi-objective optimization problems of power systems.