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Optimal Scheduling of Microgrid with Distributed Power Based on Water Cycle Algorithm

Author

Listed:
  • Xiaohui Yang

    (School of Information Engineering, Nanchang University, Nanchang 330031, China)

  • Jiating Long

    (School of Information Engineering, Nanchang University, Nanchang 330031, China)

  • Peiyun Liu

    (School of Information Engineering, Nanchang University, Nanchang 330031, China)

  • Xiaolong Zhang

    (School of Information Engineering, Nanchang University, Nanchang 330031, China)

  • Xiaoping Liu

    (Department of Systems and Computer Engineering, Carleton University, Ottawa, ON K1S 5B6, Canada)

Abstract

Microgrid, taking advantage of distributed power generation technology, plays an important role in maximizing the utilization of renewable energy. Based on the problems of the energy crisis, environmental contamination and the high operating cost of the microgrid, the microgrid model can effectively ease energy pressure. We can dispatch the output of each part in the microgrid to obtain the optimal economy. Since many traditional optimization algorithms have limitations of local optimization, multiple iterations, and slow convergence speed, this paper proposes a method that applies the Water Cycle Algorithm (WCA) to optimize the dispatch of the microgrid to minimize the operating cost. The mathematical model of each distributed power is established. The interactive power between the microgrid and large grid is also considered. The lowest generation cost considering environmental benefits is taken as the objective function. Water cycle algorithm is implemented to obtain the optimal solution under various constraints. Some optimization algorithms such as Genetic Algorithm (GA), Interior Search Algorithm (ISA), and Differential Search Algorithm (DSA) were used for results evaluation. By comparing the results obtained from four different algorithms, a case study shows the WCA possesses the advancements of better convergence performance, faster calculation and higher precision compared to the other algorithms. The results demonstrate that the WCA applied to determine the optimal scheduling of the microgrid can achieve a better result than some other algorithms with an acceptable accuracy and efficiency.

Suggested Citation

  • Xiaohui Yang & Jiating Long & Peiyun Liu & Xiaolong Zhang & Xiaoping Liu, 2018. "Optimal Scheduling of Microgrid with Distributed Power Based on Water Cycle Algorithm," Energies, MDPI, vol. 11(9), pages 1-17, September.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:9:p:2381-:d:168757
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    References listed on IDEAS

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    1. Deihimi, Ali & Keshavarz Zahed, Babak & Iravani, Reza, 2016. "An interactive operation management of a micro-grid with multiple distributed generations using multi-objective uniform water cycle algorithm," Energy, Elsevier, vol. 106(C), pages 482-509.
    2. Janghorban Esfahani, Iman & Yoo, ChangKyoo, 2016. "An optimization algorithm-based pinch analysis and GA for an off-grid batteryless photovoltaic-powered reverse osmosis desalination system," Renewable Energy, Elsevier, vol. 91(C), pages 233-248.
    3. Mohamed El-Hendawi & Hossam A. Gabbar & Gaber El-Saady & El-Nobi A. Ibrahim, 2018. "Control and EMS of a Grid-Connected Microgrid with Economical Analysis," Energies, MDPI, vol. 11(1), pages 1-20, January.
    4. Peter Makeen & R. A. Swief & T. S. Abdel-Salam & Noha H. El-Amary, 2018. "Smart Hybrid Micro-Grid Integration for Optimal Power Sharing-Based Water Cycle Optimization Technique," Energies, MDPI, vol. 11(5), pages 1-24, April.
    5. Yongli Wang & Yujing Huang & Yudong Wang & Fang Li & Yuanyuan Zhang & Chunzheng Tian, 2018. "Operation Optimization in a Smart Micro-Grid in the Presence of Distributed Generation and Demand Response," Sustainability, MDPI, vol. 10(3), pages 1-25, March.
    6. Deshmukh, M.K. & Deshmukh, S.S., 2008. "Modeling of hybrid renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(1), pages 235-249, January.
    7. Naderi, Yahya & Hosseini, Seyed Hossein & Ghassem Zadeh, Saeid & Mohammadi-Ivatloo, Behnam & Vasquez, Juan C. & Guerrero, Josep M., 2018. "An overview of power quality enhancement techniques applied to distributed generation in electrical distribution networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 201-214.
    8. Heba-Allah I. ElAzab & R. A. Swief & Noha H. El-Amary & H. K. Temraz, 2018. "Unit Commitment Towards Decarbonized Network Facing Fixed and Stochastic Resources Applying Water Cycle Optimization," Energies, MDPI, vol. 11(5), pages 1-21, May.
    9. Hui Wang & Tengxin Wang & Xiaohan Xie & Zhixiang Ling & Guoliang Gao & Xu Dong, 2018. "Optimal Capacity Configuration of a Hybrid Energy Storage System for an Isolated Microgrid Using Quantum-Behaved Particle Swarm Optimization," Energies, MDPI, vol. 11(2), pages 1-14, February.
    10. Qian Liu & Rui Wang & Yan Zhang & Guohua Wu & Jianmai Shi, 2018. "An Optimal and Distributed Demand Response Strategy for Energy Internet Management," Energies, MDPI, vol. 11(1), pages 1-16, January.
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    Cited by:

    1. Incheol Shin, 2020. "Approximation Algorithm-Based Prosumer Scheduling for Microgrids," Energies, MDPI, vol. 13(21), pages 1-16, November.

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