Service restoration in distribution systems considering priority customers and microgrids

被引:1
|
作者
Campoverde, Eduardo L. [1 ]
Torres, Santiago P. [1 ]
Ochoa-Correa, Danny [1 ]
Giraldo, Juan S. [2 ]
机构
[1] Univ Cuenca, Fac Engn, Dept Elect Engn Elect & Telecommun, Cuenca, Ecuador
[2] Netherlands Org Appl Sci Res TNO, Energy Transit Studies Grp, Radarweg 60, NL-1043 NT Amsterdam, Netherlands
关键词
Distributed generation; Hybrid metaheuristics; Microgrids; Network reconfiguration; Priority customers; Service restoration;
D O I
10.1016/j.epsr.2024.110988
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
Service restoration (SR) consists of automatically generating and executing a plan to restore the service in healthy zones using the least number of maneuvers after detecting and isolating a permanent fault in the distribution system zone. This component is essential to self-healing functionality in smart grids and allows customers to reconnect quickly to the distribution grid after a power outage. Distributed generation (DG) supports the distribution network when there is insufficient capacity to restore all zones out of service or supply the loads locally through microgrids. The power supply must be restored to the highest priority customers in case of partial restoration. Also, most research works use simplified or linearized models to propose restoration algorithms. This paper proposes a complete AC formulation for the service restoration problem in distribution systems considering network reconfiguration (NR), the integration of distributed generation (DG), and priority customers (PCs) into the solution. The optimization problem is solved by a centralized algorithm based on combining the Differential Evolution (DE) and Continuous Population-Based Incremental Learning (PBILc) metaheuristics techniques. Simulation results are presented for three case studies in which the IEEE 33-bus distribution system is tested for different fault scenarios. The numerical results show the robustness and efficiency of the proposed algorithm.
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收藏
页数:10
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