Application of battery-based energy storage in grid-connected wind farms in order to improve economical utilization

In presence of wind farms in a power system, operators will encounter more complexity in system utilization than before, because of the stochastic and fluctuating nature of the wind farm output. The presence of some constraints in power systems utilization may cause some restrictions in wind energy injection to the power system. Therefore, wind farm utilization may become non-cost effective in presence of these constraints. Using energy storage systems (ESS) in wind farms will have positive effects on power system utilization, which depend on regional wind regime and hourly energy prices. In this research, a new method is proposed to change the direction of wind farms' capacity allocation studies towards increasing wind farms' capacity. In fact, in this study, the capacity of ESS and the wind farm hourly output power are determined in a way that wind farm total income in one year and its capacity factor are increased as much as possible. So, power system utilizers' tendency towards increasing wind power penetration in power system will be raised as total income and wind farm capacity factor increase. In this paper, particle swarm optimization (PSO) is applied to find optimal ESS capacity and hourly energy management. Results demonstrate that despite high cost of energy storage systems, by using the proposed method in energy management optimization, the total income from wind energy sales will increase. Also, these results acknowledge all justifications proposed towards increasing the wind farm capacity in primary planning studies.