Abstract
Energy storage systems are receiving considerable attention as potential means to exploit the benefits from extensive renewable energy growth in electric power systems by absorbing the variability of these intermittent generation sources. This paper focuses on the compressed air energy storage (CAES) which has high potential for grid-scale application. A hybrid approach is proposed which embeds a Monte-Carlo simulation (MCS) method in an analytical technique to develop a suitable reliability model of the CAES. The MCS technique is used to sequentially model the state of charge incorporating the important dependent variables. The analytical technique employs a period analysis utilizing suitable sub-periods to maintain the diurnal and seasonal correlation of the renewable resource, system load and the state of charge of the CAES and quantitatively assess the system adequacy and wind energy usage. The CAES model incorporates diurnal energy arbitrage for profit making. The proposed model is applied to a test system to investigate the economic and reliability benefits of CAES as well as its contribution in facilitating wind integration during different operating scenarios. The conclusions drawn from the study results provide valuable information to help utilities and policy makers in arriving at effective and efficient policies for planning and operation of large-scale energy storage, such as the CAES.
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