Research on optimization configuration of distributed power flow controllers in distribution networks with distributed photovoltaics

Introduction This study aims to optimize the location and capacity determination of distributed power flow controllers, in order to enhance the safety and stability of power grid operation and reduce operational costs. Methods Firstly, the concept of weighted power flow entropy is introduced to calculate the weighted power flow entropy values at different installation locations in the power grid. Based on the principle of minimizing this index, the optimal installation location of the distributed power flow controller is determined. Secondly, when considering the economic efficiency of power grid operation, the benefits brought by the improvement of transmission capacity after installing DPFC are quantitatively evaluated along with the cost required for equipment laying. On this basis, a genetic algorithm is used for capacity optimization, where the capacity of the distributed state flow processor chain verification unit is taken as the optimization step size, and the maximization of power grid operation economy is taken as the objective, to search for the optimal configuration capacity of DPFC. Results The proposed location and capacity determination method was validated in the IEEE 30-bus standard test system. Simulation results indicate that the location method based on minimum weighted power flow entropy can effectively identify key vulnerable links in the power grid. Meanwhile, the capacity optimization using genetic algorithms combined with economic analysis can significantly improve the overall economic efficiency of power grid operation while ensuring safety and stability, confirming the effectiveness of the proposed method. Conclusion The method for selecting and sizing distributed power flow controllers proposed in this study, based on weighted power flow entropy and genetic algorithms, can coordinate the safety and economic goals of the power grid, effectively enhance the stability level of power grid operation, and reduce operational costs.