A Fast Algorithm for Multi-Objective Fault Reconfiguration of Distribution Network Considering Source-Load Uncertainty

Aiming at the traditional distribution network fault reconstruction strategy lacks of consideration of the distributed new energy instability factor influence, as well as the problem of slow calculation speed. A fast reconfiguration method for distribution network faults combining accurate optimization and decision tree algorithm is proposed. First, a multi-time deterministic fault reconstruction model is constructed. The model takes system sufficiency, minimum number of switching operations, and restoration of important loads as far as possible as the main optimization objectives, and system operation economy as the sub-optimization objectives. Second, the deterministic model is modified based on fuzzy mathematical theory to obtain a model considering source-load uncertainty. Then, in order to improve the solution speed of the fault reconstruction problem, a fast fault reconstruction algorithm based on AdaBoost improved decision tree is proposed. Finally, the proposed method is validated by arithmetic simulation with an IEEE 69-bus distribution network system. The results show that the proposed optimization model can guarantee the power supply of important loads, and realize the multi-objective optimization of power regulation adequacy and economy. The proposed fast algorithm significantly improves the solution speed of the fault reconfiguration problem.