A Novel Energy Management Optimization Method for Commercial Users Based on Hybrid Simulation of Electricity Market Bidding

Jidong Wang, Jiahui Wu and Yingchen Shi
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Jidong Wang: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
Jiahui Wu: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
Yingchen Shi: Chengnan District Power Supply Company of State Grid Tianjin Electric Power Company, Tianjin 300201, China

Energies, 2022, vol. 15, issue 12, 1-24

Abstract: Energy management and utilization for commercial users is becoming increasingly intelligent and refined, fostering a closer and growing connection with the electricity market. In this paper, a novel energy management optimization theoretical framework for commercial users is proposed based on the hybrid simulation of electricity market bidding. The hybrid simulation model based on Multi-Agent Simulation (MAS) with reinforcement learning and System Dynamic Simulation (SDS) is established to solve the problem using a single simulation method: it cannot adjust the clearing price when considering the whole market; considering the uncertainty of Electric Vehicles (EVs) travel and Lighting Loads (LLs), the multi-objective optimization model of energy management for commercial users is constructed to minimize the total energy cost of commercial users, as well as maximize the lighting comfort of indoor office staff, which compensates for the lack of the single-objective optimization of the power consumption for commercial users. A multi-objective optimization model of energy management for commercial users is established based on the hybrid simulation of electricity market bidding. By running the multi-objective optimization model based on hybrid simulation, the results show that the proposed method can realize the optimization of energy management for commercial users considering electricity market bidding.

Keywords: energy management; multi-objective optimization; electricity market bidding; hybrid simulation (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: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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