| 引用本文: | 董运昌,刘世民,曲朝阳,宋佳骏,王蕾,薄小永.计及用户响应电价关联与多主体共赢的电动汽车充放电定价优化[J].电力自动化设备,2022,42(7): |
| DONG Yunchang,LIU Shimin,QU Zhaoyang,SONG Jiajun,WANG Lei,BO Xiaoyong.Charging and discharging pricing optimization of electric vehicles considering correlation of user response to electricity price and win-win results of multi-stakeholder[J].Electric Power Automation Equipment,2022,42(7): |
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| 摘要: |
| 针对电动汽车用户响应电价时存在的不确定行为，导致配电网负荷波动及运营商成本增加的问题，提出了一种计及用户响应电价关联与多主体共赢的电动汽车充放电定价优化方法。首先，根据用户对充放电电价的响应方式，分析了不同用户充放电转移与电价变化的关联关系；然后，定义了单位投入成本函数，以电网负荷峰谷差最小、运营商节省成本最大及用户用电满意度最大为优化目标，以电动汽车行驶里程、电池电量、充放电时间和车网互动放电电价为约束条件，构建了协调多主体利益的充放电定价多目标优化模型；最后，在人工鱼群算法的基础上，结合免疫算法和Pareto最优解集，提出了基于收缩空间的改进免疫鱼群算法对多目标优化模型进行求解。算例分析结果表明，所提定价优化方法在降低系统负荷峰谷差和运营商成本的同时，增强了对用户分时段有序接入电网的调控能力，验证了所提方法的有效性和优越性。 |
| 关键词: 电动汽车 充放电定价 有序充放电 多目标优化 改进免疫鱼群算法 |
| DOI：10.16081/j.epae.202202021 |
| 分类号:U469.72 |
| 基金项目:国家自然科学基金重点资助项目(51437003)；吉林省科技发展计划项目(20200401097GX)；国网内蒙古东部电力有限公司科技项目(SGMDXT00JSJS2000073) |
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| Charging and discharging pricing optimization of electric vehicles considering correlation of user response to electricity price and win-win results of multi-stakeholder |
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DONG Yunchang1, LIU Shimin2, QU Zhaoyang1,3, SONG Jiajun4, WANG Lei1, BO Xiaoyong1
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1.School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China;2.Information and Communication Branch of State Grid Inner Mongolia East Electric Power Co.,Ltd.,Hohhot 010000, China;3.Jilin Engineering Technology Research Center of Intelligent Electric Power Big Data Processing, Jilin 132012, China;4.Guangzhou Power Supply Bureau of Guangdong Power Grid Co.,Ltd.,Guangzhou 510000, China
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| Abstract: |
| Aiming at the problem that the uncertain behavior of electric vehicle users in response to electricity price leads to the load fluctuation of distribution network and the increase of operators’ costs, a charging and discharging pricing optimization method of electric vehicles considering the correlation of user response to electricity price and the win-win results of multi-stakeholder is proposed. Firstly, according to the response mode of users to the charging and discharging price, the correlation relationship between the charging and discharging transfer of different users and the change of electricity price is analyzed. Then, the unit input cost function is defined, and the multi-objective optimization model of charging and dischar-ging pricing to coordinate the interest of multi-stakeholder is established, taking the minimum peak-valley load difference of power grid, the maximum cost saving of operators and the maximum power consumption satisfaction degree of users as the optimization objectives, and taking the electric vehicles’ mileage, battery energy, charging and discharging time and vehicle-to-grid discharging price as the constraint conditions. Finally, on the basis of artificial fish swarm algorithm, combining with immune algorithm and Pareto optimal solution set, an improved immune fish swarm algorithm based on contraction space is proposed to solve the multi-objective optimization model. The results of an example show that the proposed pricing optimization method can not only reduce the peak-valley load difference of system and the operators’ cost, but also enhance the ability to regulate and control users’ ordered access to power grid in different time periods, which verifies the effectiveness and superiority of the proposed method. |
| Key words: electric vehicles charging and discharging pricing ordered charging and discharging multi-objective optimization improved immune fish swarm algorithm |
