Optimal scheduling of micro-energy grid with integrated demand response based on chance-constrained programming. (January 2023)

• Record Type: Journal Article
• Authors: Wang, Hang; Xing, Haijun; Luo, Yangfan; Zhang, Wenbo
• Is Part Of: International journal of electrical power & energy systems. Volume 144(2023)
• Publication Date: 2023-01
• Subjects: Micro-energy grid -- Integrated demand response -- Electric vehicles -- Power to gas -- Chance-constrained programming; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2022.108602
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: Integrated demand response mechanism (IDR) in the micro-energy grid can reduce the peak-valley difference of load, promote supply–demand balance and improve the economy of system operation. Power to gas (P2G) and combined heat and power (CHP) devices can effectively improve the coupling relationship of electricity, gas, and heat in the micro-energy grid. Through various devices in this paper, the inflexible operation strategy of the traditional micro-energy grid is decoupled, and the determining electricity by heat characteristic limitation of CHP units is relieved. The simulation results show that the ladder-type carbon trading mechanism has a more potent binding force on carbon emissions and can effectively improve the environmental protection of the system. In the process of solving, the sequence operation theory (SOT) methods can be used to solve the model quickly and accurately. Abstract: The micro-energy grid can meet various load demands and realize the complementary advantages of different energy sources, which provides a new way to solve the problems of energy utilization efficiency and environmental pollution. However, how coordinating multiple energy sources and improving the flexibility of the micro-energy grid is an urgent problem to be solved. This paper proposes an optimal scheduling model based on chance-constrained programming (CCP), which considers electric vehicle (EV) charging characteristics, integrated electricity-heat demand response, and ladder-type carbon trading in the background of various renewable uncertainty. Firstly, this paper uses power to gas (P2G) technology and combined heat and power (CHP) technology to improve the flexibility of the system and realize the coupling between different energy sources. Secondly, integrated demand response (IDR) is used to explore potential interaction capabilities between electric-heat flexible load and micro-energy grid. Then, the ladder-type carbon trading mechanism is introduced in the optimization scheduling model to reduce the carbon emissions of the system. Finally, sequence operation theory (SOT) transforms the original CCP model into a conveniently solvable mixed-integer linear programming (MILP) model. The simulation results show that all subsystems are closely coupled due to the participation of P2G and CHP, which reduces the operation cost of the system by 3.9 %. The results also indicate that the IDR mechanism improves energy efficiency and reduces operating costs by 7.8 %. Finally, the results substantiate that the ladder-type carbon trading mechanism reduces the carbon emissions of the system by 18.1 % and improves the environmental benefits of the system.