Energy management strategies based on hybrid automata for islanded microgrids with renewable sources, batteries and hydrogen. (December 2020)

• Record Type: Journal Article
• Authors: Kafetzis, A.; Ziogou, C.; Panopoulos, K.D.; Papadopoulou, S.; Seferlis, P.; Voutetakis, S.
• Is Part Of: Renewable & sustainable energy reviews. Volume 134(2020)
• Publication Date: 2020-12
• Subjects: Hybrid energy storage -- Control strategy -- Renewable energy -- Load -- Off-grid -- Power to power; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.rser.2020.110118
• Languages: English
• ISSNs: 1364-0321

Abstract

Abstract: In this work, an energy management strategy is proposed for the control of islanded off-grid energy systems with energy storage based on renewable energy sources. The proposed supervisory control framework is based on a hybrid automata algorithm which is combined with propositional-based logic, describing the transitions between different operating states of the integrated system's components. The algorithm can be extended to a variety of cases without compromising the operational objectives. Within the paper, four example cases of application are given. These example cases correspond to different load demands (industrial & residential) as well as different renewable energy sources including solar, wind, hydropower and biomass. In all cases the energy is stored in a combination of batteries and hydrogen (via electrolysis) and then used back in a fuel cell. Compared to the current energy solutions in the example cases based on diesel generation sets, a 95.6%–99.4% curtailment of fossil fuel consumption is achieved. The control algorithm manages to supply power without interruption to the current loads while ensuring the health of the storage components. Highlights: Energy management systematic decision-making algorithm of off-grid storage. Four RES-based hybrid energy storage systems are demonstrated as example cases. Results show the systems' ability to store and exploit RES, safely and efficiently.