计及风-光-蓄多电场竞价的电动汽车购电策略研究

Research on an electric vehicle electricity purchasing strategy based on wind-PV-pumped storage multiple electric fields bidding

大电网供电以火力发电为主,未来大规模电动汽车从大电网购电不能满足电动汽车低碳出行的理念,且充电费用昂贵。为了有效地解决这一问题,提出了一种风-光-蓄多电场参与日前市场竞价,通过与国网公司签订过网合约对电动汽车进行供电的电动汽车购电新策略。首先,针对充电方式不同的电动汽车进行负荷建模;而后,以电动汽车用户购电成本最小为目标建立购电策略优化数学模型,通过含有随机变异粒子的改进粒子群算法得到最终的购电策略。仿真结果表明,与传统模式和非竞价模式的购电策略相比,利用所提购电策略,各充电类型的电动汽车用户购电成本均有所降低,有助于推动清洁能源电场和电动汽车的发展。

China's power supply is mainly based on thermal power generation.In the future,large-scale electric vehicles purchasing electricity from large grids cannot meet the need for low-carbon travel of electric vehicles with high charging costs.In order to effectively improve this problem,this paper proposes a new strategy for wind-PV-pumped storage multiple electric fields to participate in the current market bidding and power supply for electric vehicles by signing grid contracts with State Grid Corporation of China.First,load modeling is performed for electric vehicles with different charging methods.Then,an optimized electricity purchasing strategy is established with the goal of minimizing the cost of purchasing electricity for electric vehicle users.Finally,a purchasing strategy result is obtained through an improved particle swarm algorithm containing randomly mutated particles.The simulation results show that compared with traditional and non-bidding power purchase strategies,the charging cost of electric vehicle users of each type is reduced,compared with the existing power purchase strategy.At the same time,it will help promote using of renewable power plants and electric vehicles.