Multiobjective Joint Economic Dispatching of a Microgrid with Multiple Distributed Generation

Hui Hou, Mengya Xue, Yan Xu, Jinrui Tang, Guorong Zhu, Peng Liu and Tao Xu
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Hui Hou: School of Automation, Wuhan University of Technology, Wuhan 430070, Hubei, China
Mengya Xue: School of Automation, Wuhan University of Technology, Wuhan 430070, Hubei, China
Yan Xu: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 637551, Singapore
Jinrui Tang: School of Automation, Wuhan University of Technology, Wuhan 430070, Hubei, China
Guorong Zhu: School of Automation, Wuhan University of Technology, Wuhan 430070, Hubei, China
Peng Liu: School of Automation, Wuhan University of Technology, Wuhan 430070, Hubei, China
Tao Xu: School of Automation, Wuhan University of Technology, Wuhan 430070, Hubei, China

Energies, 2018, vol. 11, issue 12, 1-19

Abstract: Based on the operation characteristics of each dispatch unit, a multi-objective hierarchical Microgrid (MG) economic dispatch strategy with load level, source-load level, and source-grid-load level is proposed in this paper. The objective functions considered are to minimize each dispatching unit’s comprehensive operating cost (COC), reduce the power fluctuation between the MG and the main grid connect line, and decrease the remaining net load of the MG after dispatch by way of energy storage (ES) and clean energy. Firstly, the load level takes electric vehicles (EVs) as a means of controlling load to regulate the MG’s load fluctuation using its energy storage characteristics under time-of-use (TOU) price. Then, in order to minimize the remaining net load of the MG and the COC of the ES unit through Multiobjective Particle Swarm Optimization (MPSO), the source-load level adopts clean energy and ES units to absorb the optimized load from the load level. Finally, the remaining net load is absorbed by the main grid and diesel engines (DE), and the remaining clean energy is sold to the main grid to gain benefits at the source-grid-load level. Ultimately, the proposed strategy is simulated and analyzed with a specific example and compared with the EVs’ disorderly charging operation and MG isolated grid operation, which verifies the strategy’s scientificity and effectiveness.

Keywords: Microgrid; economic dispatch; distributed generation; Multiobjective Particle Swarm Optimization; Electrical Vehicle (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 (4)

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