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


This paper aims to judge and improve the usefulness of publicly accessible 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 out there due to the inter-temporal variation of electricity prices within the day-ahead market. The pre-dispatch prices, issued by the Ontario freelance electricity system operator, and the corresponding ex-post hourly Ontario energy costs are used as the forecast and the particular prices. A compressed-air ESS is sized and utilized for evaluations because of its lower capital expenditure and its ability to be completely influenced by the supply of waste heat. Initial, the standard RTOD algorithm is developed by formulating a mixed integer linear programming downside. It is demonstrated that the forecast inaccuracy of publicly obtainable market costs considerably reduces the ESS revenue. Then, a brand new adaptive algorithm is proposed and evaluated that adapts the objective perform of the optimization drawback online based on historical market prices obtainable before real-time. The outcomes reveal that the proposed adaptive RTOD will considerably increase the ESS revenue compared to the conventional algorithm as well as the back-casting technique proposed in prior studies.

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