Use of Forecasting in Energy Storage Applications: A Review

• Published in: IEEE access Vol. 9; pp. 114690 - 114704
• Main Authors: Sharma, Vinayak, Cortes, Andres, Cali, Umit
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Alternative energy sources; battery; control; energy forecasting; Energy limitation; Energy storage; Forecasting; Industries; Predictive models; Renewable energy sources; Renewable resources; State-of-the-art reviews; Training; Weather; Wind forecasting; Wind power generation
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2021.3103844

During the last decade there has been a major shift towards renewable energy sources to fulfill the increasing demand for energy in a sustainable manner. However, a major challenge with renewable energy generation is its dependency on weather conditions. Energy storage is deemed instrumental to harness renewable energy by providing a means to overcome stochasticity in renewable generation. Nonetheless, the operation of energy storage is not trivial due to its energy limitation and degradation behavior. Many works in literature consider forecasts as a cornerstone for effective management of energy storage for various grid applications. However, little work has been devoted to studying the actual value of forecast for energy storage management, which is highly dependent on the use case. This paper presents a review of the state of the art in the use of forecasts for energy storage management, identifying the estimated value of forecast with respect to baseline management approaches that do not rely on forecasts. The paper also discusses research pathways that would focus on improving forecast only on the energy storage applications that can benefit from it.