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

Xiaohui Yang, Jiating Long, Peiyun Liu, Xiaolong Zhang and Xiaoping Liu
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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

Energies, 2018, vol. 11, issue 9, 1-17

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.

Keywords: microgrid; distributed generation; optimal scheduling; WCA; DSA; ISA; GA (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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