A mixed-integer-linear-logical programming interval-based model for optimal scheduling of isolated microgrids with green hydrogen-based storage considering demand response. (April 2022)

• Record Type: Journal Article
• Authors: Tostado-Véliz, Marcos; Kamel, Salah; Hasanien, Hany M.; Turky, Rania A.; Jurado, Francisco
• Is Part Of: Journal of energy storage. Volume 48(2022)
• Publication Date: 2022-04
• Subjects: Demand response -- Electrolyser -- Fuel cell -- Green hydrogen -- Microgrid -- Renewable energy; Energy storage -- Periodicals; Energy storage -- Research -- Periodicals; 621.3126
• DOI: 10.1016/j.est.2022.104028
• Languages: English
• ISSNs: 2352-152X

Abstract

Highlights: Hydrogen produced from renewable sources (green hydrogen). Green hydrogen can be effectively stored from surplus renewable energy. A novel optimal scheduling model for robust optimal scheduling of isolated microgrids. Logical rules are incorporated into the conventional optimal scheduling tool. A case study serves to validate the model and highlight the paper. Abstract: Hydrogen produced from renewable sources (green hydrogen) will be recognized as one of the main trends in future decarbonized energy systems. Green hydrogen can be effectively stored from surplus renewable energy to thus reducing dependency of fossil fuels. As it is entirely produced from renewable sources, green hydrogen generation is strongly affected by intermittent behaviour of renewable generators. In this context, proper uncertain modelling becomes essential for adequately management of this energy carrier. This paper deals with this issue, more precisely, a novel optimal scheduling model for robust optimal scheduling of isolated microgrids is developed. The proposal encompasses a green hydrogen-based storage system and various demand-response programs. Logical rules are incorporated into the conventional optimal scheduling tool for modelling green hydrogen production, while uncertain character of weather and demand parameters is added via interval-based formulation and iterative solution procedure. The developed tool allows to perform the scheduling plan under pessimistic or optimistic point of views, depending on the influence assumed by uncertainties in the objective function. A case study serves to validate the model and highlight the paper of green hydrogen-based storage facilities in reducing fossil fuel consumptions and further exploit renewable sources.