Optimal Dynamic Dispatch of Wind Integrated Thermal Generators with Compressed Air Energy Storage

Fulfilling the growing demand for electricity at minimum cost while reducing the harmful gaseous emissions released by conventional power plants is a very challenging task. After the Kyoto protocol on climate change there is global focus on limiting emissions from fossil fuels. Increasing number of renewable energy resources are being integrated with existing power grids. Their intermittent and uncertain nature however creates difficulty in maintaining reliability particularly when large scale integration of these resources is planned. Efficient energy storage systems are therefore essential to store surplus power when renewable generation is in abundance and to release it during periods when renewable generation is insufficient. This paper explores the viability of operating wind farm coupled with compressed air energy storage (CAES) system to meet the demand and control the electricity prices during peak loads. The optimal dispatch of thermal units is computed using an improved particle swarm optimization (PSO) such that all thermal, wind generator and CAES system constraints are satisfied. A 24-hour dispatch period is considered by applying thermal generator ramp-rate limits between consecutive time periods. Two separate models are employed for maximizing cost and profit. The proposed method is tested on a test power system consisting of six thermal generating units integrated with 50 wind turbines.