| 引用本文: | 严 晗,徐晓春,张 毅,等.基于特征匹配和灵敏度辅助决策的配电网优化调控技术[J].电力系统保护与控制,2025,53(02):112-124.[点击复制] |
| YAN Han,XU Xiaochun,ZHANG Yi,et al.Optimization and control technology of a distribution network based on feature matching and sensitivity-assisted decision making[J].Power System Protection and Control,2025,53(02):112-124[点击复制] |
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| 摘要: |
| 分布式电源、电动汽车和储能等高比例接入配电网，提高了配电网的智能性、可控性，同时也对配电网的优化调控提出了更复杂的经济安全要求。针对实时量测缺失的配电网在线优化调控问题，提出一种基于特征匹配和灵敏度辅助决策的配电网优化调控方案。首先，构建了考虑不同运行特性下的配电网历史特征库与策略库，提高特征匹配的精度和速度，通过源网荷储协调优化有效降低了网络损耗和电压波动。其次，提出了基于特征匹配的配电网匹配策略生成方法，摆脱了潮流模型的限制，大幅提升了实时优化效率。最后，为了修正特征匹配偏差引起的策略误差，提出了计及部分实时量测的配电网在线优化调控辅助决策方法，设计基于系统匹配偏差率的指令权重系数，提高了在线调控指令的精度。通过算例仿真验证了所提方案的准确性和可行性。 |
| 关键词: 配电网 源网荷储 数据驱动 特征匹配 辅助决策 |
| DOI：10.19783/j.cnki.pspc.240207 |
| 投稿时间：2024-02-26修订日期：2024-08-20 |
| 基金项目:国家电网有限公司科技项目资助(J2022054)；
国家自然科学基金项目资助(52077036) |
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| Optimization and control technology of a distribution network based on feature matching and sensitivity-assisted decision making |
| YAN Han1,XU Xiaochun1,ZHANG Yi2,YUAN Zhoumao2,TANG Tongfeng1,ZHOU Xin1,DAI Hui1,DOU Xiaobo1 |
| (1. Huai’an Power Supply Branch of State Grid Jiangsu Electric Power Co., Ltd., Huai’an 223001, China;
2. School of Electrical Engineering, Southeast University, Nanjing 210096, China) |
| Abstract: |
| Distributed power supply, electric vehicles and energy storage are connected to the distribution network at a high proportion. This improves the intelligence and controllability of the distribution network, and also brings forward more complex economic and security requirements for the optimization and regulation of the network. There is a problem of online optimal control of the distribution network without real-time measurement, so an optimal control scheme for the network based on feature matching and sensitivity-assisted decision making is proposed. First, a distribution network historical feature database and strategy database considering different operational characteristics are constructed to improve the accuracy and speed of feature matching. Network loss and voltage fluctuation are effectively reduced through source-network-load-storage coordination optimization. Secondly, the generation method of the network matching strategy based on feature matching is proposed. This removes the limitations of the power flow model and greatly improves the efficiency of real-time optimization. Finally, in order to correct the strategic error caused by the feature matching deviation, an auxiliary decision-making method for online optimization control of the network is proposed. A command weight coefficient based on the system matching deviation rate is designed to improve the accuracy of online control instructions. The accuracy and feasibility of the proposed scheme are verified by simulation examples. |
| Key words: distribution network source-network-load-storage data-driven feature matching auxiliary decision |
