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

Junqing Li; Quanke Pan; Peiyong Duan; Hongyan Sang; Kaizhou Gao

doi:10.1109/JAS.2017.7510454

Volume 6 Issue 5

Sep. 2019

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2019 > 6(5): 1240-1250

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

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

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

doi: 10.1109/JAS.2017.7510454

Junqing Li^{1, 3
,},
Quanke Pan^2
,,
Peiyong Duan^3
,,
Hongyan Sang^1
,,
Kaizhou Gao^4
,

1.
School of Computer Science, Liaocheng University, Liaocheng 252059, China
2.
School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China
3.
School of Information Science and Engineering, Shandong Normal University, Jinan 250014, China
4.
Macau Institute of Systems Engineering, Macau University of Science and Technology, Macau 999078, China

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

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Author Bio:

Junqing Li (M'08) received the master degree of computer science and technology in 2004 from Shandong Economic University, Shandong, China, and Ph.D. degree in 2016 from Northeastern University, Shenyang, China. Since 2004, he has been with the School of Computer Science Department, Liaocheng University, where he became an Associate Professor in 2008. He is also with the School of Information Science and Engineering, Shandong Normal University, where he became a Professor in 2017. His current research interests include intelligent optimization and scheduling. He has authored more than 60 refereed papers.(e-mail: lijunqing@lcu-cs.com)

Quanke Pan received the B.Sc. degree and the Ph.D. degree from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 1993 and 2003, respectively. Since 2003, he has been with the School of Computer Science Department, Liaocheng University, where he became a Full Professor in 2006. He has been with the State Key Laboratory of Synthetical Automation for Process Industries (Northeastern University) since 2011. He is now with the School of Mechatronic Engineering and Automation, Shanghai University. His current research interests include intelligent optimization and scheduling. He has authored more than 200 refereed papers.(e-mail: panquanke@shu.edu.cn)

Peiyong Duan received the B.Sc. degree in 1996 from Shandong University of Technology (merged into Shandong University in 2000), Shandong, China, and Ph.D. degree in 1999 from Shanghai Jiao Tong University, Shanghai, China. From 1999 through 2014, he was with the School of Information and Electrical Engineering, Shandong Jianzhu University where he is appointed as an Associate Professor and a Full Professor in 1999 and 2002, respectively. Since 2014, he has been with the School of Computer Science, Liaocheng University, Shandong, China. Since 2017, he has been with the School of Information Science and Engineering, Shandong Normal University. His current research interests include discrete optimization and scheduling. He has authored more than 60 refereed papers. (e-mail: duanpeiyong@sdnu.edu.cn)

Hongyan Sang received the master degree of computer science and technology in 2010 from Liaocheng University, Shandong, China, and Ph.D. degree in 2013 from Huazhong University of Science Technology, Wuhan China. Since 2003, she has been with the School of Computer Science Department, Liaocheng University, where she became an Associate Professor in 2016. Her current research interests include intelligent optimization and scheduling. She has authored more than 30 refereed papers.(e-mail: sanghongyan@lcu-cs.com)

Kaizhou Gao received the bachelor and master degrees from the Computer School of Liaocheng University and School of Information and Engineering of Yangzhou University, in 2005 and 2008, respectively. He received the Ph.D. degree from Nanyang Technological University, in 2016. He is now with the Macau Institute of Systems Engineering, Macau University of Science and Technology. His current research interests include intelligent optimization, heuristics and meta-heuristics, planning and scheduling, and intelligent traffic.(e-mail: gaokaizhou@lcu-cs.com)
Corresponding author:
Peiyong Duan, e-mail: duanpeiyong@sdnu.edu.cn
Received Date: 2015-10-25
Revised Date: 2016-03-01
Accepted Date: 2016-07-11

Available Online: 2019-08-16

Publish Date: 2019-08-16

Abstract

Abstract

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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References

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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.

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

doi: 10.1109/JAS.2017.7510454

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通讯作者: 陈斌, bchen63@163.com

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