Author
Listed:
- Yangyan Zhu
(College of Electrical Engineering, Shanghai Dian ji University, Shanghai 201306, China)
- Zhijie Wang
(College of Electrical Engineering, Shanghai Dian ji University, Shanghai 201306, China
Key Laboratory of Control of Power Transmission and Conversion (SJTU), Ministry of Education, Shanghai 200240, China)
- Yonghui Liu
(College of Electrical Engineering, Shanghai Dian ji University, Shanghai 201306, China)
- Hong Wang
(College of Electrical Engineering, Shanghai Dian ji University, Shanghai 201306, China)
- Nengling Tai
(Key Laboratory of Control of Power Transmission and Conversion (SJTU), Ministry of Education, Shanghai 200240, China)
- Xiuchen Jiang
(Key Laboratory of Control of Power Transmission and Conversion (SJTU), Ministry of Education, Shanghai 200240, China
Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)
Abstract
In the application of microgrid systems that include wind power, photovoltaic systems, diesel generators, and battery storage, the cooperative control and optimisation of power distribution between power sources is a major issue. Recently, the droop control has been used widely in microgrids. However, droop control relies mainly on the line parameter model between the grid and the load. Therefore, to improve the performance of the microgrid, the optimal control of microgrid operation based on the fuzzy sliding mode droop control method is considered in this paper. To begin, system parameters were obtained by modeling droop control with self-learning fuzzy control strategy. Then, to improve the accuracy of the power distribution in the multi-micro source system, the nonlinear differential smoothing control method was employed. Finally, by comparing the self-learning fuzzy sliding mode control based on drooping strategy and the traditional droop control method, it was demonstrated that the method proposed can effectively reduce the fluctuation of the bus voltage and improve the output voltage quality of the microgrid system.
Suggested Citation
Yangyan Zhu & Zhijie Wang & Yonghui Liu & Hong Wang & Nengling Tai & Xiuchen Jiang, 2019.
"Optimal Control of Microgrid Operation Based on Fuzzy Sliding Mode Droop Control,"
Energies, MDPI, vol. 12(19), pages 1-14, September.
Handle:
RePEc:gam:jeners:v:12:y:2019:i:19:p:3600-:d:269297
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Citations
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Cited by:
- Angelo Algieri & Pietropaolo Morrone & Sergio Bova, 2020.
"Techno-Economic Analysis of Biofuel, Solar and Wind Multi-Source Small-Scale CHP Systems,"
Energies, MDPI, vol. 13(11), pages 1-21, June.
- Miloud Rezkallah & Sanjeev Singh & Ambrish Chandra & Bhim Singh & Hussein Ibrahim, 2020.
"Off-Grid System Configurations for Coordinated Control of Renewable Energy Sources,"
Energies, MDPI, vol. 13(18), pages 1-25, September.
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