Online Adaptive Real-Time Optimal Dispatch of Privately Owned Energy Storage Systems Using Public-Domain Electricity Market Prices

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Abstract
This paper aims to evaluate and improve the usefulness of publicly available electricity market prices for real-time optimal dispatching (RTOD) of a privately owned energy storage system (ESS) in a competitive electricity market. The RTOD algorithm seeks to maximize the revenue by exploiting arbitrage opportunities available due to the inter-temporal variation of electricity prices in the day-ahead market. The pre-dispatch prices, issued by the Ontario independent electricity system operator, and the corresponding ex-post hourly Ontario energy prices are employed as the forecast and the actual prices. A compressed-air ESS is sized and employed for evaluations due to its lower capital expenditure and its ability to be positively influenced by the availability of waste heat. First, the conventional RTOD algorithm is developed by formulating a mixed integer linear programming problem. It is demonstrated that the forecast inaccuracy of publicly available market prices significantly reduces the ESS revenue. Then, a new adaptive algorithm is proposed and evaluated which adapts the objective function of the optimization problem online based on historical market prices available before real-time. The outcomes reveal that the proposed adaptive RTOD can significantly increase the ESS revenue compared to the conventional algorithm as well as the back-casting method proposed in prior studies.

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