Title: A decision model for combining energy storage technologies
Authors: Emilio Lopez Cano - Universidad Rey Juan Carlos (Spain) [presenting]
Javier Martinez Moguerza - Rey Juan Carlos University (Spain)
Antonio Alonso Ayuso - Rey Juan Carlos University (Spain)
Abstract: In recent years, energy storage came at the forefront of mainstream discussions about how to reach a global sustainable energy future. In fact, energy storage and related technologies are increasingly playing a prominent role in the global energy debate. Thus, decision models are needed at several levels in order to tackle the societal challenge of providing efficient, scalable, secure, and robust energy storage solutions. The optimization model for energy storage systems presented considers, in addition to existing technologies, emerging or forecast ones. It envisages an heterogeneous set of technologies working as silos of energy, connected to resources and final uses. Moreover, it scales from the short term to the long term, allowing to use cooperation mechanisms such as statistical transfer in order to support policy making. The model is suitable for different objectives and, hence, multiple agents' risks, that are to be managed within the own optimization model. Thus, different risk management options, including Bayesian ones, are discussed.