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Solving the dynamic economic dispatch by a memory-based global differential evolution and a repair technique of constraint handling

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  • Zou, Dexuan
  • Li, Steven
  • Kong, Xiangyong
  • Ouyang, Haibin
  • Li, Zongyan

Abstract

In this paper, we propose a memory-based global differential evolution (MGDE) algorithm and a repair technique of constraint handling for the dynamic economic dispatch problems. On the one hand, MGDE modifies the mutation of DE/best/1, and uses a memory pool to provide more candidate solutions for this operation. Moreover, it adopts a randomly generated scale factor in the modified mutation to enhance its exploration capacity. In the crossover, a dynamical crossover rate is introduced to balance MGDE's global and local search capacities. On the other hand, a repair technique is designed for handling three kinds of constraints associated with generator capacity, power balance and generating unit ramp-rate. Moreover, a commonly used penalty function method is subsequently employed to handle the possible constraint violations associated with power balance and prohibited operation zones (POZs). To judge the performance of MGDE and the efficiency of the repair technique, we have solved six well-known DED problems taken from different sources. According to the experimental results, MGDE shows a superior performance in comparison with other improved DEs which also solve these problems. In the mean time, the repair technique of constraint handling has a high efficiency in eliminating or reducing the constraint violations.

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  • Zou, Dexuan & Li, Steven & Kong, Xiangyong & Ouyang, Haibin & Li, Zongyan, 2018. "Solving the dynamic economic dispatch by a memory-based global differential evolution and a repair technique of constraint handling," Energy, Elsevier, vol. 147(C), pages 59-80.
    • Handle: RePEc:eee:energy:v:147:y:2018:i:c:p:59-80
    DOI: 10.1016/j.energy.2018.01.029
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    References listed on IDEAS

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    1. Mohammadi-ivatloo, Behnam & Rabiee, Abbas & Soroudi, Alireza & Ehsan, Mehdi, 2012. "Imperialist competitive algorithm for solving non-convex dynamic economic power dispatch," Energy, Elsevier, vol. 44(1), pages 228-240.
    2. Meng, Anbo & Hu, Hanwu & Yin, Hao & Peng, Xiangang & Guo, Zhuangzhi, 2015. "Crisscross optimization algorithm for large-scale dynamic economic dispatch problem with valve-point effects," Energy, Elsevier, vol. 93(P2), pages 2175-2190.
    3. Zou, Dexuan & Li, Steven & Wang, Gai-Ge & Li, Zongyan & Ouyang, Haibin, 2016. "An improved differential evolution algorithm for the economic load dispatch problems with or without valve-point effects," Applied Energy, Elsevier, vol. 181(C), pages 375-390.
    4. Niu, Qun & Zhang, Hongyun & Li, Kang & Irwin, George W., 2014. "An efficient harmony search with new pitch adjustment for dynamic economic dispatch," Energy, Elsevier, vol. 65(C), pages 25-43.
    5. Sun, Zhe & Wang, Ning & Bi, Yunrui & Srinivasan, Dipti, 2015. "Parameter identification of PEMFC model based on hybrid adaptive differential evolution algorithm," Energy, Elsevier, vol. 90(P2), pages 1334-1341.
    6. Mohammad Rasoul Narimani & Maigha & Jhi-Young Joo & Mariesa Crow, 2017. "Multi-Objective Dynamic Economic Dispatch with Demand Side Management of Residential Loads and Electric Vehicles," Energies, MDPI, vol. 10(5), pages 1-18, May.
    7. Ouyang, Kwan & Wu, Horng-Wen & Huang, Shun-Chieh & Wu, Sheng-Ju, 2017. "Optimum parameter design for performance of methanol steam reformer combining Taguchi method with artificial neural network and genetic algorithm," Energy, Elsevier, vol. 138(C), pages 446-458.
    8. Wang, Long & Wang, Tongguang & Wu, Jianghai & Chen, Guoping, 2017. "Multi-objective differential evolution optimization based on uniform decomposition for wind turbine blade design," Energy, Elsevier, vol. 120(C), pages 346-361.
    9. Zhang, Huifeng & Zhou, Jianzhong & Fang, Na & Zhang, Rui & Zhang, Yongchuan, 2013. "Daily hydrothermal scheduling with economic emission using simulated annealing technique based multi-objective cultural differential evolution approach," Energy, Elsevier, vol. 50(C), pages 24-37.
    10. Lashkajani, Kazem Hasanzadeh & Ghorbani, Bahram & Amidpour, Majid & Hamedi, Mohammad-Hossein, 2016. "Superstructure optimization of the olefin separation system by harmony search and genetic algorithms," Energy, Elsevier, vol. 99(C), pages 288-303.
    11. Azaza, Maher & Wallin, Fredrik, 2017. "Multi objective particle swarm optimization of hybrid micro-grid system: A case study in Sweden," Energy, Elsevier, vol. 123(C), pages 108-118.
    12. Zhang, Jingrui & Lin, Shuang & Liu, Houde & Chen, Yalin & Zhu, Mingcheng & Xu, Yinliang, 2017. "A small-population based parallel differential evolution algorithm for short-term hydrothermal scheduling problem considering power flow constraints," Energy, Elsevier, vol. 123(C), pages 538-554.
    13. Chellaswamy, C. & Ramesh, R., 2016. "Parameter extraction of solar cell models based on adaptive differential evolution algorithm," Renewable Energy, Elsevier, vol. 97(C), pages 823-837.
    14. Shen, Peihong & Zhao, Zhiguo & Zhan, Xiaowen & Li, Jingwei, 2017. "Particle swarm optimization of driving torque demand decision based on fuel economy for plug-in hybrid electric vehicle," Energy, Elsevier, vol. 123(C), pages 89-107.
    15. Sivasubramani, S. & Swarup, K.S., 2010. "Hybrid SOA–SQP algorithm for dynamic economic dispatch with valve-point effects," Energy, Elsevier, vol. 35(12), pages 5031-5036.
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    Cited by:

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    6. Zhang, Yi & Cheng, Chuntian & Cao, Rui & Li, Gang & Shen, Jianjian & Wu, Xinyu, 2021. "Multivariate probabilistic forecasting and its performance’s impacts on long-term dispatch of hydro-wind hybrid systems," Applied Energy, Elsevier, vol. 283(C).

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