The value of energy storage from intermittent renewables : an end user perspectives in Smart Grids

• Main Author: Granado, Pedro Crespo del
• Published: Lancaster University 2014
• Subjects: 333.79
• Online Access: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.732707

The widespread deployment of renewable energy in combination with smart grid technologies is creating the opportunity for energy storage to play a critical role in energy systems and be a more prevalent technology in the near future. This research adopts a bottom-up approach to model the in­teractions within the energy system, namely between renewable supply and storage technologies at the end-user level (e.g. in houses, buildings and com­munities). That is, the papers presented in this thesis investigate the value of energy storage in smart grids from an end-user perspective. Specifically, it focuses on the role of storage units in the regulation of the energy system’s supply-demand balance and the cost savings for the end-user. Hence, the contribution of this study lies in the perspective taken (end-user), as well as in the models developed for the valuation of energy storage. In this sense, it provides an understanding of different aspects associated with the valuation of storage technologies in smart grids. Particular attention is paid to the contribution of local wind energy supply as well as demand response (smart grids). Analytics data-driven optimization is central in this research. To analyze the interactions on complementing energy storage with decen­tralized energy system in smart grids, this thesis develops models for two real-life case studies: The first paper assess the value of batteries in domes­tic houses in sync with on-site renewable micro generation. A second paper extends the research, bottom-up, to a community dependent on its own hybrid decentralized generation coupled with energy storage units. As un­certainty of wind generation is not considered in these cases, a third paper investigates the storage valuation by a stochastic programming approach.