| 考虑需求响应不确定性的光伏微电网储能系统优化配置 |
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| 引用本文： | 李姚旺,苗世洪,刘君瑶,叶畅,尹斌鑫,杨炜晨.考虑需求响应不确定性的光伏微电网储能系统优化配置[J].电力系统保护与控制,2018,46(20):69-77. |
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| 作者姓名： | 李姚旺 苗世洪 刘君瑶 叶畅 尹斌鑫 杨炜晨 |
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| 作者单位： | 华中科技大学电气与电子工程学院强电磁工程与新技术国家重点实验室华中科技大学电力安全与高效湖北省重点实验室 |
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| 基金项目： | 国家重点研发计划项目(2017YFB0903601);国家自然科学基金(51777088);国家电网公司科技项目(SGHADK00PJJS1500060) |
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| 摘 要： | 将分布式光伏以微电网的形式接入配电网运行是应对大规模分布式光伏并网问题的有效手段之一。以含储能装置和需求响应资源的并网型光伏微电网为研究对象,研究考虑价格型需求响应(Demand Response, DR)不确定性的并网型光伏微电网储能系统优化配置方法。首先,同时考虑价格需求弹性曲线和基线负荷不确定性对价格型DR不确定性的影响,建立了价格型DR响应量模糊模型。在此基础上,以用户负荷与光伏出力总差异最小为目标,建立了基于模糊机会约束规划的价格型DR优化运行模型。之后,以价格型DR的优化结果为基础,建立了基于模糊机会约束规划的并网型光伏微电网储能系统优化配置模型。通过对模糊机会约束的清晰等价处理,将模糊机会优化问题转换为确定性优化问题进行求解。最后,通过仿真算例验证了模型的有效性。
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| 关 键 词： | 光伏微电网 储能系统优化配置 需求响应 不确定性 模糊优化 |
| 收稿时间： | 2017/9/25 0:00:00 |
| 修稿时间： | 2018/2/8 0:00:00 |
Optimal allocation of energy storage system in PV micro grid considering uncertainty of demand response |
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| LI Yaowang,MIAO Shihong,LIU Junyao,YE Chang,YIN Binxin and YANG Weichen.Optimal allocation of energy storage system in PV micro grid considering uncertainty of demand response[J].Power System Protection and Control,2018,46(20):69-77. |
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| Authors: | LI Yaowang MIAO Shihong LIU Junyao YE Chang YIN Binxin and YANG Weichen |
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| Affiliation: | State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Hubei Electric Power Security and High Efficiency Key Laboratory, Huazhong University of Science and Technology, Wuhan 430074, China,State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Hubei Electric Power Security and High Efficiency Key Laboratory, Huazhong University of Science and Technology, Wuhan 430074, China,State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Hubei Electric Power Security and High Efficiency Key Laboratory, Huazhong University of Science and Technology, Wuhan 430074, China,State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Hubei Electric Power Security and High Efficiency Key Laboratory, Huazhong University of Science and Technology, Wuhan 430074, China,State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Hubei Electric Power Security and High Efficiency Key Laboratory, Huazhong University of Science and Technology, Wuhan 430074, China and State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Hubei Electric Power Security and High Efficiency Key Laboratory, Huazhong University of Science and Technology, Wuhan 430074, China |
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| Abstract: | Connecting distributed photovoltaic (PV) to the distribution network through the grid-connected micro grid is one of effective ways to solve large-scale distributed PV integration problem. Taking the gird-connected PV micro gird with the energy storage system and demand response resources as the study object, this paper studies the optimal allocation strategy of energy storage system in PV micro grid considering uncertainty of price-based demand response (DR). Firstly, the impacts of price-demand elastic curve and based load uncertainty on the price-based DR uncertainty are considered, and the price-based DR fuzzy response model is established. Based on the price-based DR fuzzy response model, the price-based DR fuzzy chance optimal operation model, which is to minimize the difference between the system load and the PV output, is proposed. After that, based on the optimal results of the optimal operation model, the optimal allocation model of the energy storage system in grid-connected PV micro grid is established based on the fuzzy chance constrained program. By transferring the fuzzy chance constrains into their clear equivalents, the fuzzy chance optimal problem can be converted to a deterministic optimal problem to solve. Finally, the simulation results verify the validity of the proposed model. This work is supported by National Key Research and Development Program of China (No. 2017YFB0903601), National Natural Science Foundation of China (No. 51777088) and Science and Technology Project of State Grid Corporation of China (No. SGHADK00PJJS1500060). |
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| Keywords: | PV micro grid optimal allocation of energy storage system demand response uncertainty fuzzy optimization |
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