Improving islanded distribution system stability with adaptive decision-making framework

被引:0
|
作者
Sanaullah, Kaka [1 ]
Xia, Mingchao [1 ]
Hussain, Arif [1 ]
Hussain, Kashif [1 ]
机构
[1] Beijing Jiaotong Univ, Elect Engn, Beijing 100044, Peoples R China
关键词
Distributed generation (DGs); voltage stability; load-curtailment; Black Widow Optimization (BWO); voltage stability index (VSI); voltage stability margin (VSM); SERVICE RESTORATION; NETWORK RECONFIGURATION;
D O I
10.1515/ijeeps-2024-0061
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In an integrated distribution system incorporating distributed generation (DG), various technical challenges must be addressed when the grid becomes disconnected and transforms into an islanded system. The main focus in such circumstances revolves around ensuring the stability of the islanded network. This study presents an advanced decision-making framework for supporting islanded networks by integrating metaheuristic Black Widow Optimization (BWO) and the rate of change of the voltage stability index (RoCVSI). The Rate of Change of the Voltage Stability Index (RoCVSI) detects instability in islanded networks by continuously monitoring rapid changes in the voltage stability margin. Upon identifying potential instability, an advanced decision-making strategy utilizing the Black Widow Optimization (BWO) algorithm is deployed. BWO generates multiple load-shedding scenarios and evaluates their impact on system stability, iteratively refining the solutions through processes similar to selection and cannibalism in black widow spiders. The optimal load-shedding strategy is then implemented to selectively shed specific loads, thereby reducing demand and enhancing island stability. The proposed scheme's effectiveness for islanded network stability is assessed by extensively analyzing the IEEE 33-bus system. The efficiency of the proposed approach is confirmed through a comparative analysis, with results indicating the better efficiency of the proposed method in the islanded network.
引用
收藏
页数:14
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