Adaptive Setting Method for Inverse-time Overcurrent Protection of Active Distribution Network in Complex Scenarios

With the continuous increase of grid-connected permeability of distributed power supply (DG), the power flow direction and fault current characteristics of active distribution networks have changed essentially compared with a traditional radial distribution network of a single power source. The randomness and uncertainty of distributed power output also make the operation scenarios of the distribution network complex and diverse. It brings significant challenges to the relay protection setting of the distribution network, but also reduces the applicability and reliability of the conventional three-stage protection. This paper first investigates the representative operation scenarios of active distribution networks (ADNs). Based on various DG output probability models, the generation method of representative operation scenarios of ADNs is proposed based on Latin hypercube sampling and the K-Medoids clustering algorithm. Then, an ADN model integrated with multiple types of DGs is used to analyze the impact of DG grid integration on the overcurrent protection of the ADN. Afterwards, an optimization-based method is proposed to generate the inverse-time overcurrent protection setting template for ADNs, and an adaptive multi-population elite strategy based Jaya algorithm is applied as the optimization solver. Based on that, a template library for the overcurrent protection settings under representative operation scenarios of the active distribution network can be constructed. Finally, a cosine similarity based scenario matching method is used to carry out the adaptive setting of the protection values of active distribution networks. The simulation results prove that the proposed method can significantly improve the reliability of ADN protection.