Automation of Electric Power SystemsVol. 40, Issue 20, Pages: 13-19(2016)
作者机构:
电力电子节能与传动控制河北省重点实验室(燕山大学),河北省,秦皇岛市,066004
作者简介:
基金信息:
DOI:
CLC:
Published:2016
稿件说明:
移动端阅览
YANG Lijun. [J]. Automation of electric power systems, 2016, 40(20): 13-19.
DOI:
YANG Lijun. [J]. Automation of electric power systems, 2016, 40(20): 13-19.DOI:
含分布式电源的配电网多故障抢修与恢复协调优化策略
摘要
针对含分布式电源(DG)的配电网发生多故障时的快速故障抢修和供电恢复问题
根据动态规划原理
建立了含DG的配电网多故障分阶段、分层的抢修与恢复协调优化模型。在紧急抢修与恢复阶段
以负荷恢复价值最大和综合经济损失最小分别作为内、外层优化目标;在抢修与恢复网架阶段
以网损最小和抢修时间最短分别作为内、外层优化目标
得到最优抢修顺序和供电恢复方案。针对内、外层模型的不同特点
分别采用了改进蚁群算法和离散化处理的细菌群体趋药性(DBCC)算法进行模型求解。同时
在抢修与恢复过程中
利用DG孤岛、可控负荷联盟及应急发电车的动态调度优先恢复重要负荷的供电
并采用馈线等效法及故障等效法来简化求解流程。以改进的IEEE 69节点系统为例
验证了所述策略的可行性和有效性。
Abstract
For the fast fault repair and power supply recovery from multi-fault in the distribution network with distributed generators(DGs)
a phased and hierarchical coordination strategy of the repair and recovery optimization model is proposed based on the dynamic programming principle. In the emergency repair and recovery stage
the maximum load recovery value and minimum comprehensive economic loss are taken as the inner and outer optimization objective
respectively in the stages of emergency recovery; in the repair and recovery network structure stage
the minimum network loss and shortest repair time are taken as the inner and outer optimization objective
respectively in the stages of network reconfiguration to solve the optimal repair and recovery strategy. According to the different characteristics of the inner and outer optimization models
the improved ant colony algorithm and improved bacterial chemotaxis(DBCC)algorithm are used respectively to solve the inner and outer optimization models. Meanwhile
DG islanding
controllable load alliance and dynamic scheduling of emergency generators are used to restore the important load
and the methods of feeder equivalence to virtual DG and fault equivalence model are adopted to simplify the optimization process. The feasibility and validity of the method proposed are verified by modeling and simulation of the improved IEEE 69-bus system. This work is supported by National Natural Science Foundation of China(No. 61573302)and Hebei Provincial Natural Science Foundation of China(No. E2014203254).