Scheduling Strategy Considering Wind and Photovoltaic Power Consumption and the Flexibility of Electric Vehicles

As a clean means of transport, electric vehicles (EVs) can improve the peak-to-valley difference of grid load and promote renewable energy consumption while facilitating users' travelling, and the scale of their application is constantly expanding. However, the disorderly charging of large-scale EVs will increase the burden on the power grid, which will have a counterproductive effect in load regulation or renewable energy consumption. The orderly charging and discharging of EVs can be effectively guided by time-of-use (TOU) price. At present, with stochastic large and some extreme situations of the renewable energy, the wind curtailment, photovoltaic curtailment and thermal power unit regulation capacity under the existing TOU price under are insufficient to lead to the larger cost of load-shedding, which remains a more prominent phenomenon. Therefore, proposing a scheduling strategy considering wind and photovoltaic power consumption and the flexibility of EVs. Firstly, based on the wind power and photovoltaic output values and load information of each time period predicted in the day-ahead, the equivalent load of wind power, photovoltaic and base load and their average values are derived, and the peak-valley difference of the equivalent load in this time period is calculated. Based on the average value of the equivalent load and the peak-valley difference, the peak-valley price is formulated; when the equivalent load is lower than the minimum output of the thermal power unit, it will increase the phenomenon of wind and photovoltaic curtailment, resulting in a waste of resources, which will be formulated as the sunken valley price; when the equivalent load is larger than the maximum output of the thermal power unit, or the neighbouring difference in the equivalent load exceeds the ramping capacity of the thermal power unit, it will be insufficient to supply electricity, and it will be formulated as the sharp peak price. At the same time, the price elasticity coefficient is introduced to quantitatively describe the response of EVs to the sunken valley and sharp peak price. Secondly, an EV charging and discharging model is established based on the TOU price information to determine the electricity information for EV charging and discharging scheduling. Then, an optimal EV charging and discharging scheduling model is constructed with the goal of minimizing load fluctuation and wind and photovoltaic curtailment costs, minimizing the cost of electricity for users and maximizing the revenue for the aggregator, taking into account the interests of the power grid, the EV aggregator and the EV users. Finally, conducting an analysis of a specific power system, compared to the TOU price strategy in the peak-to-valley period, the TOU price strategy in this paper can attract more EVs to participate in the charging scheduling. The phenomenon of wind and photovoltaic curtailment can be reduced through the sunken valley TOU price in the period of renewable energy surplus. In the period of insufficient regulation capacity of thermal power unit, more EVs are attracted to participate in discharge scheduling through sharp peak TOU price to provide load resource for the power grid and reduce load shedding. Meanwhile, the price strategy can improve the revenue of aggregators and reduce the electricity cost of users while reducing the load fluctuation of power grid. © 2024 China Machine Press. All rights reserved.