|
| 基于智能电网的电动汽车充放电分时电价及引导策略 |
| Research on time-of-use electricity price of electric vehicle charging and discharging and the guidance strategy based on smart grid |
| 投稿时间：2019-08-30 |
| DOI：10.13259/j.cnki.eri.2021.02.004 |
| 中文关键词: 分时电价 供求曲线 空闲率 粒子群算法 |
| 英文关键词:time-of-use electricity price supply and demand curve idleness rate particle swarm optimization |
| 基金项目: |
|
| 摘要点击次数: 1870 |
| 全文下载次数: 2956 |
| 中文摘要: |
| 为了以绿色、环保能源满足全球可持续发展的需求，可再生能源和电动汽车在全球范围内受到广泛推崇。在此情形下，高比例可再生能源发电和大规模电动汽车无序分散接入电网必将导致供求曲线的不稳定。为此，借助云存储技术和智能电网，提出了一种基于供求曲线的电动汽车充放电分时电价，并在制定充放电价格时考虑充电站的空闲率。以实现充电站和用户最大利益为目标函数，建立了电动汽车充放电价格模型。采用粒子群算法对该模型进行求解，并通过算例进行分析，验证了该模型的有效性和合理性。 |
| 英文摘要: |
| In order to meet the demands of global sustainable development with environment-friendly and green energy, renewable energy and electric vehicles have popularized worldwide. In this case, high proportion of renewable energy generation as well as the large-scale separated connection of electric vehicles to the grid will inevitably lead to the instability of the supply and demand curve. Therefore, time-of-use electricity price of electric vehicle charging and discharging according to supply and demand curve was proposed via smart grid and cloud storage. Additionally, the charging and discharging price was determined with the considerations of the idleness rate of the charging stations. In this paper, the charging and discharging price model of electric vehicles is established to realize the maximum benefits of both charging stations and users. Particle swarm optimization (PSO) was used to solve this model. The validity and rationality of the model are verified by an algorithm case. |
| HTML 查看全文 查看/发表评论 下载PDF阅读器 |
| 关闭 |
