In order to better schedule distributedenergyresources (DERs) to improve the recovery ability of the distribution network, the optimal recovery strategy is proposed in this study. The strategy can be applied to spee...
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In order to better schedule distributedenergyresources (DERs) to improve the recovery ability of the distribution network, the optimal recovery strategy is proposed in this study. The strategy can be applied to speed up the recovery process and reduce the power shortage of shedding loads in the distribution network when a power outage occurs. The scheduling coefficient is defined to quantify the rationality of each scheduling resource. Based on this index, this study establishes an optimal scheduling model, which consists of three objectives. The non-dominated sorting genetic algorithm-II is applied to search this multi-objective optimal recovery solution in this study. Then, the modified IEEE 39-node system is used as the case study to verify the feasibility of the proposed model and the test results prove the effectiveness and efficiency of the proposed model.
distributedenergy Resource (DER) scheduling is usually performed while considering lumped load models in an unbalanced distribution system (UDS). However, it is not necessary that lumped load models represent the act...
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ISBN:
(纸本)9781665495011
distributedenergy Resource (DER) scheduling is usually performed while considering lumped load models in an unbalanced distribution system (UDS). However, it is not necessary that lumped load models represent the actual characteristics of the distribution system. Therefore, in this paper, DERs scheduling is performed while considering time-varying loading characteristics of each phase of UDS. Grasshopper Optimization Algorithm (GOA) is used to optimize the performance of UDS. The proposed methodology is implemented on IEEE 37 node feeder, and its comparison with recent studies demonstrates the effectiveness of the approach.
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