Examinando por Autor "Hasanien, Hany"
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Ítem A mixed-integer-linear-logical programming interval-based model for optimal scheduling of isolated microgrids with green hydrogen-based storage considering demand response(Elsevier, 2022-04) Tostado-Véliz, Marcos; Kamel, Salah; Hasanien, Hany; Turky, Rania; Jurado-Melguizo, FranciscoHydrogen 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.Ítem Optimal energy management of cooperative energy communities considering flexible demand, storage and vehicle-to-grid under uncertainties(Elsevier, 2022-09) Tostado-Véliz, Marcos; Kamel, Salah; Hasanien, Hany; Turky, Rania; Jurado-Melguizo, FranciscoWith the advent of smart cities, residential consumers have evolved towards the concept of prosumers. This paradigm calls for new businesses like energy communities. Energy management of such frameworks is essential to maximize the collective welfare. This paper addresses this issue by developing an energy management framework that accounts for flexible demand, storage devices and electric vehicles. Its two-level structure allows to address the energy exchanging among prosumers in the 1st stage, while the 2nd stage focuses on optimally schedule the different collective assets. A novel stochastic-interval model is proposed to handle with uncertainties from demand, renewable generation, vehicles’ behaviour and energy pricing. A case study is performed on a six-prosumer community. Results serve to validate the new tool and analyse the importance of smart devices. In addition, the new proposal allows to adopt different operating strategies. Actually, the total operating cost may increase by 90% if a pessimistic point of view is adopted while the importance of the vehicle-to-grid capability is marginal otherwise. Furthermore, the energy purchased could be reduced by 7% when adopting a community arrangement, supposing an improvement in the economy and environmental indicators of the network. Other relevant aspects are identified and discussed in depth.Ítem Risk-averse optimal participation of a DR-intensive microgrid in competitive clusters considering response fatigue(Elsevier, 2023-06) Tostado-Véliz, Marcos; Hasanien, Hany; Rezaee Jordehi, Ahmad; Turky, Rania; Jurado-Melguizo, FranciscoThe massive integration of renewable generators, energy storage systems, and demand response requires the development of smart power infrastructures. In this upcoming context, microgrids will be essential for the optimal integration of such assets. When different microgrids are located near each other, they can be centrally coordinated within a novel paradigm called Microgrid Cluster. In such structures, the microgrids involved can collaborate in a cooperative way or compete by developing internal market structures. This paper develops a novel optimal bidding strategy for a demand response-intensive microgrid partaking in competitive clusters. The new proposal is envisaged as a three-stage methodology that aims at reducing the effects of response fatigue. Uncertainties related to inflexible demand and renewable generation are modeled via scenarios, while the risk associated with uncertain parameters is handled by enforcing the Conditional Value at Risk. The resulting computational tool is effective and tractable, as shown in the results obtained on a benchmark three-microgrids cluster. Indeed, the developed methodology is able to reduce the total response signals by 88 % in some cases. Moreover, this case study allows analyzing the effect of response fatigue minimization in the overall cluster performance, showing that the collective welfare can be reduced by 32 % when response fatigue is taken into account.