| 引用本文: | 陈泽雄,张新民,王雪锋,等.分布式光伏电站接入配电网的分布鲁棒优化配置方法[J].电力系统保护与控制,2021,49(13):30-42.[点击复制] |
| CHEN Zexiong,ZHANG Xinmin,WANG Xuefeng,et al.A distributionally robust optimal allocation method for distributed photovoltaic generation stations integrated into a distribution network[J].Power System Protection and Control,2021,49(13):30-42[点击复制] |
|
| 摘要: |
| 随着分布式光伏(Distributed Photovoltaic, DPV)电站接入配电网的规模日益增大，光伏出力的不确定波动特性造成配电网运行状态的频繁波动，故对接入配电网的DPV电站进行合理规划对于配电网的安全运行尤为重要。针对DPV电站接入配电网的并网点和容量选择问题，以并网位置节点和配置容量同时作为决策变量，并考虑DPV出力的不确定性，建立了DPV电站接入配电网的并网点和容量选择的分布鲁棒优化配置模型。以当地光照强度和环境温度的历史数据计算出的DPV电站单位容量光伏的日出力曲线作为数据驱动构建出基于KL散度的模糊集。通过优化计算出模糊集中最大和最小期望的概率分布以得到单位容量光伏出力不确定波动的范围，将分布鲁棒优化模型转化为鲁棒优化模型，并采用Benders分解法求解得到优化配置方案。最后，以某个实际180节点配电网为例进行仿真计算，并与确定性优化和传统鲁棒优化方法进行对比分析。验证了所提出的分布鲁棒优化方法既能够保证在光伏出力不确定波动下配电网的安全运行，又能够克服鲁棒优化方法的保守性，使求得的配置方案在经济性和鲁棒性之间达到良好的平衡。 |
| 关键词: 分布式光伏 优化配置 分布鲁棒优化 模糊集 KL散度 |
| DOI：DOI: 10.19783/j.cnki.pspc.201082 |
| 投稿时间：2020-09-04修订日期：2020-09-27 |
| 基金项目:国家自然科学基金项目资助(51977080)；广东电网有限责任公司广州供电局科技项目资助(GZHKJXM20180053) |
|
| A distributionally robust optimal allocation method for distributed photovoltaic generation stations integrated into a distribution network |
| CHEN Zexiong1,ZHANG Xinmin1,WANG Xuefeng1,PENG Lingli1,WEN Weihong1,LIANG Weikun2,LIN Shunjiang2 |
| (1. Guangzhou Power Supply Bureau, Guangdong Power Grid Co., Ltd., Guangzhou 510000, China;
2. School of Electric Power, South China University of Technology, Guangzhou 510640, China) |
| Abstract: |
| With the increase of distributed photovoltaic (DPV) generation stations integrated into the distribution network, the uncertain fluctuation of PV output results in frequent fluctuations of the operating states of thenetwork. Thus planning of DPV generation stations integrated into the distribution network is important for secure operation. There is a problem of grid-connection buses and capacity selection of DPV generation stations integrated into a network. We take the grid-connected locations and configuration capacity as decision variables, and the uncertainty of DPV output is considered. From this a distributionally robust optimal allocation model for the grid-connection buses and capacity selection of DPV generation station integrated into the network is established. The daily photovoltaic output curve of unit capacity of DPV generation station calculated by the historical data of local illumination intensity and environmental temperature is used as data to construct an ambiguity set based on KL divergence. The uncertain fluctuation range of unit capacity PV output is obtained by the optimal calculation of the probability distributions with maximum and minimum expected values in the ambiguity set. Then the distributionally robust optimization model is transformed into a robust optimization model, and the optimal allocation scheme is obtained using the Benders decomposition method to solve the model. Finally, taking an actual 180-bus distribution network as an example, a simulation is performed and compared with the deterministic optimization and traditional robust optimization methods. It is verified that the proposed distributionally robust optimization method can not only ensure the secure operation of the distribution network under the uncertain fluctuation of PV output, but also can overcome the conservatism of the robust optimization method. Hence the obtained allocation scheme can achieve a good balance between economy and robustness.
This work is supported by the National Natural Science Foundation of China (No. 51977080) and the Science and Technology Project of Guangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd. (No. GZHKJXM20180053). |
| Key words: distributed photovoltaic optimal allocation distributionally robust optimization ambiguity set KL divergence |
