Research on Intelligent Algorithm Optimization for Voltage Hierarchy Coordinated Planning and Power Supply Capacity Improvement Based on Adaptive Weight Hybrid PSO-GA
TL;DR
The study provides an optimization path for voltage hierarchy coordination in new power and electromagnetic systems by constructing a multidimensional coordinated planning model and a power-supply capacity coupling evaluation system.
Abstract
With the increasing proportion of new energy integration and the diversified development of loads, the traditional “ vertical decoupling and horizontal fragmentation” power-grid planning model can no longer satisfy requirements for power-supply reliability and flexibility. This paper focuses on voltage hierarchy coordinated planning and power-supply capacity improvement. A multidimensional coordinated planning model and a power-supply capacity coupling evaluation system are constructed, and an intelligent optimization scheme integrating an Adaptive Weight Hybrid Particle Swarm Optimization-Genetic Algorithm with an LSTM prediction module is proposed. Simulation verification based on an IEEE extended node system shows that the model realizes power-flow coordination and optimal equipment configuration across high voltage, medium voltage, and low voltage levels. The convergence speed of the improved algorithm is 42.3% higher than that of traditional PSO, and the global optimal solution acquisition rate is increased by 35.7%. Under multiple scenarios, the maximum load carrying capacity of power supply is increased by 18.9%, and the new energy consumption rate is improved by 22.1%. The study provides an optimization path for voltage hierarchy coordination in new power and electromagnetic systems.