Multiobjective dynamic economic emission dispatch using evolutionary algorithm based on decomposition

Due to the pressures of energy and environment problems, the dynamic economic emission dispatch (DEED), which is more in line with actual dispatching requirements, has become an important research issue in recent years. In this paper, the highly dimensional, strongly coupled, nonlinear and nonconvex multiobjective DEED model is established considering both the fuel costs and pollution emissions objectives. Furthermore, an improved multiobjective evolutionary algorithm based on decomposition with constraints handling (IMOEA/D-CH) is proposed to obtain the optimal dispatching schemes. The IMOEA/D-CH method first decomposes the DEED problem into a number of scalar optimization subproblems and then evolves them simultaneously using the neighborhood information. The real-time heuristic constraints adjustment and modification methods and the adaptive threshold punishment mechanism are adopted in allusion to the complex constraints of the dispatching model. An evolutionary control strategy is also utilized to avoid excessive evolution of the algorithm toward a certain objective. In addition, the fuzzy decision-making strategy is used to provide the decision maker with the optimal compromise solutions. To validate the effectiveness of the IMOEA/D-CH method, the IEEE 30-bus 6-generator system and 10-generator system and 118-bus 14-generator system are studied as test cases. The simulation results indicate the validity and superiority of the proposed method compared with the other reported methods. (c) 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.