Sizing Storage for Reliable Renewable Integration: A Large Deviations Approach

Abstract

• This paper addresses the problem of sizing of energy storage for reliable grid integration of renewables. • Demand and supply uncertainty are jointly modelled as functions of a (background) Markov process. • Crisp sizing estimates are obtained using large deviations theory. • We present a case study using real world wind power data to demonstrate the applicability of our results in practice. The inherent intermittency of wind and solar generation presents a significant challenge as we seek to increase the penetration of renewable generation in the power grid. Increasingly, energy storage is being deployed alongside renewable generation to counter this intermittency. However, a formal characterization of the reliability of renewable generators bundled with storage is lacking in the literature. The present paper seeks to fill this gap. We use a Markov modulated fluid queue to model the loss of load probability ( LOLP ) associated with a renewable generator bundled with a battery, serving an uncertain demand process. Further, we characterize the asymptotic behavior of the LOLP as the battery size scales to infinity. Our results shed light on the fundamental limits of reliability achievable, and also guide the sizing of the storage required in order to meet a given reliability target. Finally, we present a case study using real-world wind power data to demonstrate the applicability of our results in practice.