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Volume 6 Issue 5
Sep.  2019

IEEE/CAA Journal of Automatica Sinica

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Junqing Li, Quanke Pan, Peiyong Duan, Hongyan Sang and Kaizhou Gao, "Solving Multi-Area Environmental/Economic Dispatch by Pareto-Based Chemical-Reaction Optimization Algorithm," IEEE/CAA J. Autom. Sinica, vol. 6, no. 5, pp. 1240-1250, Sept. 2019. doi: 10.1109/JAS.2017.7510454
Citation: Junqing Li, Quanke Pan, Peiyong Duan, Hongyan Sang and Kaizhou Gao, "Solving Multi-Area Environmental/Economic Dispatch by Pareto-Based Chemical-Reaction Optimization Algorithm," IEEE/CAA J. Autom. Sinica, vol. 6, no. 5, pp. 1240-1250, Sept. 2019. doi: 10.1109/JAS.2017.7510454

Solving Multi-Area Environmental/Economic Dispatch by Pareto-Based Chemical-Reaction Optimization Algorithm

doi: 10.1109/JAS.2017.7510454
Funds:

the National Natural Science Foundation of China 61773192

the National Natural Science Foundation of China 61773246

the National Natural Science Foundation of China 61603169

the National Natural Science Foundation of China 61803192

Shandong Province Higher Educational Science and Technology Program J17KZ005

Special Fund Plan for Local Science and Technology Development Lead by Central Authority, and Major Basic Research Projects in Shandong ZR2018ZB0419

More Information
  • In this study, we present a Pareto-based chemical-reaction optimization (PCRO) algorithm for solving the multi-area environmental/economic dispatch optimization problems. Two objectives are minimized simultaneously, i.e., total fuel cost and emission. In the proposed algorithm, each solution is represented by a chemical molecule. A novel encoding mechanism for solving the multi-area environmental/economic dispatch optimization problems is designed to dynamically enhance the performance of the proposed algorithm. Then, an ensemble of effective neighborhood approaches is developed, and a self-adaptive neighborhood structure selection mechanism is also embedded in PCRO to increase the search ability while maintaining population diversity. In addition, a grid-based crowding distance strategy is introduced, which can obviously enable the algorithm to easily converge near the Pareto front. Furthermore, a kinetic-energy-based search procedure is developed to enhance the global search ability. Finally, the proposed algorithm is tested on sets of the instances that are generated based on realistic production. Through the analysis of experimental results, the highly effective performance of the proposed PCRO algorithm is favorably compared with several algorithms, with regards to both solution quality and diversity.

     

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    Highlights

    • we present a Pareto-based chemical-reaction optimization (PCRO) algorithm for solving the multi-area environmental/economic dispatch optimization problems.
    • a novel encoding mechanism for solving the multi-area environmental/economic dispatch optimization problems is developed.
    • an ensemble of effective neighborhood approaches is developed, and a self-adaptive neighborhood structure selection mechanism is also embedded.
    • a grid-based crowding distance strategy is introduced, which can obviously enable the algorithm to easily converge near the Pareto front.
    • a kinetic-energy-based search procedure is developed to enhance the global search ability.

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