Research On Grid Reconstruction Path Optimization For Power System Partition Recovery

The operation of the interconnected system and the wide-scale integration of new energy pose uncertainties to the stable operation of the power system,and external factors such as human and natural disasters make largescale power outages difficult to avoid completely.In depth research on how to quickly restore power supply after a major blackout has important practical application value in reducing blackout losses.As an important stage in the power system restoration process,network reconfiguration plays a crucial role in determining and optimizing the restoration path for fast startup of the blackout units and restoring power supply to critical users.This paper investigates the path optimization problem of gird reconfiguration in two ways,establishes corresponding mathematical models,and uses partition recovery planning for complex large systems to deeply study the path optimization strategies of grid reconstruction in power system partition recovery.Firstly,combining with the segmented path optimization strategy in the network reconfiguration phase,a path optimization model considering the reactive power of the line charging is established.Based on the shortest path algorithm,the shortest power supply path from each segmented black start power source to the target unit is sought,and the weight of the line to be restored is dynamically adjusted.Taking the IEEE-39 node system as an example,it proves the correctness of the proposed method model and the rationality of the recovery path results after dynamic adjustment.Secondly,considering the shortcomings of the segmented path optimization method strategy and the complexity and multiple steps of the existing global optimization method solution process,a global path optimization method based on the Hopfield neural network algorithm is proposed.Considering the influence of line weight,node importance,and important load,a path optimization factor is formulated constructing an energy function that includes path optimization solution objectives and various strong constraints,and transforming the grid reconstruction path optimization problem into a "0-1" programming problem,the system’s optimal recovery path is obtained by solving the minimum value of the energy function.Using the IEEE-39 node system as an example,the results obtained have a 10%improvement in recovery time compared with other methods.The solution program for the proposed path optimization method is written based on Microsoft SQL Server and C++Builder10 software,which can directly obtain the system’s optimal recovery path by solving the energy function and visually present the results in the form of a simple network topology diagram.Finally,for complex power systems,a partition method considering subsequent path optimization is given in combination with the parallel recovery strategy of the power system,and the optimal recovery path for each partition subsystem is determined.The effectiveness of the proposed partitioning method is verified using the IEEE-39 nodes and IEEE-118 node systems.Comparing the results before and after partitioning,it shows that the proposed partition recovery path optimization method can improve the efficiency of path optimization problem solving in complex systems and accelerate the power system’s recovery speed.