Abstract
In this paper, proper scheduling of the operation of multiple storage devices is sought so as to minimize the expected total cost (of conventional generation) in a power network with intermittent renewable generation. Since the power network constraints make it intractable to compute optimal storage operation policies through dynamic programming-based approaches, a Lyapunov optimization-based online algorithm (LOPN) is proposed, which makes decisions based only on the current state of the system (i.e., the current demand and renewable generation). The proposed algorithm is computationally simple and achieves asymptotic optimality (as the capacity of energy storage grows large). To improve the performance of the LOPN algorithm for the case with limited storage capacity, a threshold-based energy storage management (TESM) algorithm is proposed that utilizes the forecast information (on demand and renewable generation) over the next few time slots to make storage operation decisions. Numerical experiments are conducted on IEEE 6- and 9-bus test systems to validate the asymptotic optimality of LOPN, and compare the performance of LOPN and TESM. Numerical results show that TESM significantly outperforms LOPN when the storage capacity is relatively small.