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考虑不确定性风险及结构脆弱性的配电网网架规划 被引量:1

A distribution network frame optimization planning considering uncertain risk and structural vulnerability
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摘要 高比例分布式新能源不确定性特征增加系统运行风险,易引发电压与支路功率越限问题,增大系统网架结构脆弱性。因此提出双层多目标配电网网架规划模型,以满足多元用户对供电可靠性及电能质量要求。首先,建立源荷概率模型,并基于概率潮流量化计算配电网节点线路越限风险;其次,基于复杂网络理论,对配电网结构进行脆弱性评估;然后,提出综合考虑不确定性风险与脆弱性影响的配电网网架结构双层多目标规划模型,上层优化网络拓扑,下层规划光伏容量,采用非支配排序遗传算法与改进粒子群算法分别对上、下层模型进行优化求解;最后,采用IEEE14节点系统对方法进行验证。结果表明,该方法可以得到满足不同光伏渗透率接入要求的经济稳定的网络结构。 The uncertainty of high proportion distributed new energy increases the operation risk of the system,which easily leads to the problem of voltage and branch power exceeding limit,and increases vulnerability of the system grid structure.Therefore,a double-layer multi-objective distribution network planning model is proposed to meet the requirements of multiple users for power supply reliability and power quality.Firstly,the source load probability model is established,and the node line out of limit risk of distribution network is calculated quantitatively based on probabilistic power flow.Secondly,based on the complex network theory,the vulnerability of distribution network structure is evaluated.Then,a bi-level multi-objective programming model of distribution network structure is proposed,which comprehensively considers the effects of uncertainty risk and vulnerability.The upper layer optimizes the network topology,the lower layer plans the photovoltaic capacity,and uses the non-dominated sorting genetic algorithm and the improved particle swarm optimization algorithm to optimize the upper and lower models respectively;Finally,the IEEE14 node system is used to verify the method.The results show that this method can obtain an economically stable network structure that meets the access requirements of different PV penetration rates.
作者 赵辰宇 俞永春 刘明林 左新斌 王奉冲 李道宇 ZHAO Chenyu;YU Yongchun;LIU Minglin;ZUO Xinbin;WANG Fengchong;LI Daoyu(State Grid Shandong Electric Power Company,Ji’nan 250001,China;Power Reliability Management and Project Quality Supervision Center,National Energy Administration,Beijing 100031,China;State Grid Qingdao Power Supply Company,Qingdao 266002,China;School of Electrical Engineering,Shandong University,Ji’nan 250061,China)
出处 《应用科技》 CAS 2023年第2期86-92,共7页 Applied Science and Technology
关键词 配电网 分布式光伏 概率潮流 风险性 脆弱性 优化算法 遗传算法 网架规划 distribution network distributed photovoltaic probabilistic power flow risk vulnerability optimization algorithm genetic algorithm grid planning
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