The stability dispatch of the microgrid has an important impact on the safety of the power system, so the research on the stability dispatch of the microgrid is necessary. We have established a microgrid model with diesel engines, microturbines, fuel cells, wind turbines and photovoltaic arrays targeting the system load variance. The scheduling algorithm uses an improved particle swarm optimization algorithm based on dimensional learning. The global extremum in the algorithm is derived from the individual extremum of dimensional learning. Firstly, 13 standard test functions are applied to test the performance of the improved dimensional learning algorithm. The simulation results show the effectiveness of the improved algorithm. Then the algorithm and model are combined, and as a result the safety of the system with distributed power generation is better than the system without distributed power generation by comparing the two strategies with or without distributed power generation strategies.
Keywords Microgrid, stability dispatch, load variance, dimensional learning, particle swarm optimization algorithm