光伏系统
灵敏度(控制系统)
电容器
蒙特卡罗方法
分布式发电
电压
遗传算法
计算机科学
工程类
数学优化
控制理论(社会学)
电子工程
电气工程
数学
可再生能源
控制(管理)
人工智能
统计
标识
DOI:10.1109/tste.2016.2640239
摘要
This paper first studies the estimated distributed photovoltaic (PV) hosting capacities of 17 utility distribution feeders using the Monte Carlo simulation based stochastic analysis, and then analyzes the sensitivity of PV hosting capacity to both feeder and PV system characteristics. Furthermore, an active distribution network management approach is proposed to maximize PV hosting capacity by optimally switching capacitors, adjusting voltage regulator taps, managing controllable branch switches, and controlling smart PV inverters. The approach is formulated as a mixed-integer nonlinear optimization problem and a genetic algorithm is developed to obtain the solution. Multiple simulation cases are studied and the effectiveness of the proposed approach on increasing PV hosting capacity is demonstrated.
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