Solving economic emission load dispatch problems using hybrid differential evolution

Authors:
Aniruddha Bhattacharya;Pranab Kumar Chattopadhyay
Affiliations:
Department of Electrical Engineering, Jadavpur University, Kolkata, West Bengal 700 032, India;Department of Electrical Engineering, Jadavpur University, Kolkata, West Bengal 700 032, India
Venue:
Applied Soft Computing
Year:
2011

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Abstract

This paper presents the combination of differential evolution (DE) and Biogeography-based Optimization (BBO) algorithm to solve complex economic emission load dispatch (EELD) problems of thermal generators of power systems. Emission substances like NO"X, SO"X, CO"X, power demand equality constraint and operating limit constraint are considered here. Differential evolution (DE) is one of the very fast and robust, accurate evolutionary algorithms for global optimization and solution of EELD problems. Biogeography-based Optimization (BBO) is another new biogeography inspired algorithm. Biogeography deals with the geographical distribution of different biological species. This algorithm searches for the global optimum mainly through two steps: migration and mutation. In this paper the combination of DE and BBO (DE/BBO) is proposed to accelerate the convergence speed of both the algorithm and to improve solution quality. To show the advantages of the proposed algorithm, it has been applied for solving multi-objective EELD problems in a 3 generator system with NO"X and SO"X emission, in a 6 generators system considering NO"X emission, in a 6 generator system addressing both valve-point loading and NO"X emission. The current proposal is found better in terms of quality of the compromising and individual solution obtained.