Optimal control of storage under time varying electricity prices

Abstract

Abstract-End users equipped with storage may exploit time variations in electricity prices to earn profit by doing energy arbitrage, i.e., buying energy when it is cheap and selling it when it is expensive. We propose an algorithm to find an optimal solution of the energy arbitrage problem under given time varying electricity prices. Our algorithm is based on discretization of optimal Lagrange multipliers of a convex problem and has a structure in which the optimal control decisions are independent of past or future prices beyond a certain time horizon. The proposed algorithm has a run time complexity of O(N 2 ) in the worst case, where N denotes the time horizon. To show the efficacy of the proposed algorithm, we compare its runtime performance with other algorithms used in MATLAB's constrained optimization solvers. Our algorithm is found to be at least ten times faster, and hence has the potential to be used for in real-time. Using the proposed algorithm, we also evaluate the benefits of doing energy arbitrage over an extended period of time for which price signals are available from some ISO's in USA and Europe.

Limiting Energy Storage Cycles of Operation

“…Authors in [1] propose optimal energy arbitrage algorithm under time varying electricity prices. In this work it is shown that a time horizon of optimization can be subdivided into sub-horizons.…”

“…In Section II we describe the cycle and calendar life of battery and list the typical values for power grid batteries. Section III summarizes the optimal arbitrage algorithm proposed in [1]. Section IV presents the mechanism to limit cycles of operation of a battery.…”

Optimal Storage Arbitrage under Net Metering using Linear Programming

“…Most NEM policies indicate that consumers receive a rate at best equal to the buying price of electricity [4]. Authors in [5] consider storage operation under equal buy and sell price case. This framework is generalized in [6], covering cases where the ratio of buy and sell price could arbitrarily vary between 0 and 1.…”

“…This framework is generalized in [6], covering cases where the ratio of buy and sell price could arbitrarily vary between 0 and 1. For equal buying and selling price, the storage control becomes independent of inelastic load and renewable generation of the consumer [5], [7]. The cost function considered in this work includes inelastic load, renewable generation and storage charging and discharging efficiency, and ramping and capacity constraints.…”

“…Authors in [12] observe that the energy arbitrage problem for storage is convex in nature and under the price-taker assumption the cost function will have a piecewise linear structure [5] and hence LP tools could be used. LP techniques for energy storage arbitrage have been used in several prior works: [13], [14], [15], [16], [17], [18], [19].…”