HYBRID ENERGY STORAGE SYSTEM CAPACITY PLANNING METHOD BASED ON IMPROVED PARTICLE SWARM OPTIMIZATION ALGORITHM

摘要

A hybrid energy storage system capacity planning method based on an improved particle swarm optimization algorithm. The method comprises the following steps: step 1, respectively acquiring a typical daily load curve of a cold load, in an area where energy storage is applied, in a cool supply season, a typical daily load curve of a heat load in the area in a heat supply season, a typical daily load curve of a power load in the area in a non-heat-and-cool-supply season, a typical daily price trend curve of the cold load in the area in the cool supply season, a typical daily price trend curve of the heat load in the area in the heat supply season, and a typical daily price trend curve of the power load in the area in the non-heat-and-cool-supply season; step 2, respectively acquiring the service lives, initial investments and annual maintenance costs of a power storage device system, a heat storage device system and a cold storage device system, and then respectively computing the annualized costs of the power storage device system, the heat storage device system and the cold storage device system; step 3, according to the capacity of the power storage device system, the capacity of the heat storage device system, the capacity of the cold storage device system, load requirements and the economic efficiency, establishing a particle swarm optimization algorithm; and step 4, performing evolutionary computation on energy storage capacities according to the particle swarm optimization algorithm established in step 3. By using an improved particle swarm optimization algorithm, the problem of the optimized configuration of a comprehensive energy storage capacity in one area is solved, thereby achieving economic and stable energy utilization.