4.6 Article

A Multiobjective Approach for the Optimal Placement of Protection and Control Devices in Distribution Networks With Microgrids

期刊

IEEE ACCESS
卷 10, 期 -, 页码 41776-41788

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2022.3166918

关键词

Circuit faults; Fuses; Microgrids; Uncertainty; Renewable energy sources; Distribution networks; Reliability; Distribution systems; microgrids; protection system planning; non-dominated sorting genetic algorithm; compromise programming

资金

  1. Brazilian Federal Agency for Support and Evaluation of Graduate Education (CAPES) [88887.310463/2018-00, 88887.569912/2020-00, 88887.570741/2020-00]
  2. Sao Paulo Research Foundation (FAPESP) [2015/21972-6, 2019/07436-5, 2017/02831-8]

向作者/读者索取更多资源

This study proposes a multi-objective optimization approach for sizing and allocating protection and control devices in distribution networks with microgrids supplied by renewable energy sources. The non-dominated sorting genetic algorithm is applied to solve the allocation problem, and compromise programming is performed to achieve the best solution. The results demonstrate interesting setups for the protection system and the feasibility of islanding operation.
Protection and control systems represent an essential part of distribution networks by ensuring the physical integrity of components and by improving system reliability. Protection devices isolate a portion of the network affected by a fault, while control devices reduce the number of de-energized loads by transferring loads to neighboring feeders. The integration of distributed generation has the potential to enhance the continuity of energy services through islanding operation during outage conditions. In this context, this study presents a multi-objective optimization approach for sizing and allocating protection and control devices in distribution networks with microgrids supplied by renewable energy sources. Reclosers, fuses, remote-controlled switches, and directional relays are considered in the formulation. Demand and generation uncertainties define the islanding operation and the load transfer possibilities. A non-dominated sorting genetic algorithm is applied in the solution of the allocation problem considering two conflicting objectives: cost of energy not supplied and equipment cost. The compromise programming is then performed to achieve the best solution from the Pareto front. The results show interesting setups for the protection system and viability of islanding operation.

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