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Abstract

Energy Storage Systems (ESS) are expected to play a critical role in future energy grids. ESS technologies are primarily employed for reducing the stress on grid and the use of hydrocarbons for electricity generation. However, in order for ESS option to become economically viable, proper sizing is highly desired to recover the high capital cost. In this paper we propose a system architecture that enables us to optimally size the ESS system according to the number of users. We model the demand of each customer by a two-state Markovian fluid and the aggregate demand of all users are multiplexed at the ESS. The proposed model also draws a constant power from the grid and it is used to accommodate the customer demand and charge the storage unit, if required. Then, given the population of customers and their stochastic demands, and the power drawn from the grid we provide an analytical solution for ESS sizing using the underflow probability as the main performance metric, which is defined as the percentage of time that the system resources fall short of demand. Such insights very important in designing the system planning phases of future energy grid infrastructures.

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/content/papers/10.5339/qfarc.2014.ITPP0516
2014-11-18
2019-12-06
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