Cooperative optimization study of source network considering unbalanced power

Abstract

As dispersed power sources become more common and power markets open, power system operation becomes increasingly difficult. One is source-grid uncoordination. When several dispersed power sources are linked to the grid, their uncontrollability and unpredictability may cause an imbalanced power system, impacting grid security and stability. Hence, power system optimization research focuses on how to coordinate scattered power sources and power grids for synergistic source-grid optimization. This work addresses the imbalanced power issue generated by dispersed power sources linked to the grid and proposes a source-grid co-optimization strategy based on the two-layer hybrid optimization theory to ensure safe, dependable, and cheap power system operation. We will apply a hybrid particle swarm algorithm and genetic algorithm double-layer nested method to solve a two-layer optimization model with the integrated cost of distribution network on top and distributed power supply on bottom. With imbalanced power, cooperative source network optimization may increase power system operating efficiency and stability.