Open Access

ARTICLE

Research on Multi-Objective Optimization Model of Industrial Microgrid Considering Demand Response Technology and User Satisfaction

by Junhui Li^1,*, Jinxin Zhong¹, Kailiang Wang¹, Yu Luo¹, Qian Han², Jieren Tan²

1 Dongguan Power Supply Bureau, Dongguan, 523000, China
2 Guangdong Electric Power Design and Research Institute, Guangzhou, 510000, China

* Corresponding Author: Junhui Li. Email:

Energy Engineering 2023, 120(4), 869-884. https://doi.org/10.32604/ee.2023.021320

Received 07 January 2022; Accepted 22 June 2022; Issue published 13 February 2023

Abstract

In the process of wind power, coal power, and energy storage equipment participating in the operation of industrial microgrids, the stable operation of wind-storage industrial microgrids is guaranteed by considering demand response technology and user satisfaction. This paper firstly sorts out the status quo of microgrid operation optimization, and determines the main requirements for user satisfaction considering three types of load characteristics, demand response technology, power consumption benefit loss, user balance power purchase price and wind power consumption evaluation indicators in the system. Secondly, the operation architecture of the windstorage industrial microgrid is designed, and the multi-objective optimization model of the wind-storage industrial microgrid is established with the comprehensive operating cost and user satisfaction as the target variables, and the corresponding solution method is mentioned. Finally, a typical wind-storage industrial microgrid is selected for simulation analysis, and the results show that, (1) Considering the demand response technology, the comprehensive operating cost of the wind-storage industrial microgrid per day is 5292.63 yuan, the user satisfaction index is 0.953, and the wind power consumption rate reaches 100%. (2) By setting four scenarios, it highlights that the grid-connected operation mode is superior to the off-grid operation mode. Considering the demand response technology, the load curve can be optimized, and the time-of-use electricity price can be fully used to coordinate the operation of each unit, which enhances the wind power consumption capacity. The compromise solution of the system comprehensive operating cost and user satisfaction under the confidence level of 0.95 is obtained, namely (5343.22, 0.94). (3) The frontier curve shows that in the process of model solving, it is impossible to optimize any sub-objective by changing the control variables, which proves that there is a close relationship between the comprehensive operating cost of the system and the confidence level, which can provide effective guidance for the optimal operation of industrial microgrids.

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