Power grid peak shaving strategies based on electric vehicles and thermal storage electric boilers

3rd International Conference on Energy Engineering and Environmental Protection

能源学;生态环境科学

Hu, Bo^1 ; Wang, Shicheng^1 ; Zhang, Xiaoheng^2 ; Wang, Tao^1 ; Qu, Fei^1 ; Zheng, Wei^1 ; Zhou, Bowen^2

State Grid Huludao Electric Power Supply Company, Huludao

125000, China^1

Northeastern University, Shenyang

110000, China^2

关键词: Charge and discharge;    Controllable loads;    Daily load curves;    Electric vehicle charging;    Operational characteristics;    Optimization problems;    Particle swarm optimization algorithm;    Renewable energies;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/227/3/032026/pdf
DOI  :  10.1088/1755-1315/227/3/032026

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Due to the rapid progress of electrification and the rising accommodation of renewable energy, the peak-to-valley difference of power grids has been increasing, and the peak loading pressure of power grids has arised. It has become a trend to use controllable loads to participate in power grid peak shaving. At present, electric vehicles and thermal storage electric boilers, which are widely implemented in northern China, provide a reliable source for controllable loads. Based on the analysis of the operational characteristics of electric vehicles and thermal storage electric boilers, this paper studies the charge and discharge control strategies for auxiliary peak shaving. The Monte Carlo method is used to simulate the charging behavior of electric vehicle users. Under the premise of considering the constraints of electric vehicle charging and discharging power, battery capacity and the power consumption of the thermal storage electric boilers, the mathematical model is established with the goal of suppressing the daily load curve, and the particle swarm optimization algorithm is used to solve the optimization problem. The simulation results show that electric vehicles and thermal storage electric boilers are jointly involved in load balancing, and the daily load curve is significantly levelled compared with the original curve.