A hybrid model of energy scheduling for integrated multi-energy microgrid with hydrogen and heat storage system
To increase the energy utilization efficiency, it becomes fairly promising to convert the surplus electricity from renewable generation to other forms of energy for multi-dimensional consumption. In this paper, we propose a hybrid energy scheduling model for a multi-energy microgrid with the integra...
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| Autores principales: | , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Elsevier
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/a5b3fb3f5ea34762a2afc3262c3f4f4d |
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| Sumario: | To increase the energy utilization efficiency, it becomes fairly promising to convert the surplus electricity from renewable generation to other forms of energy for multi-dimensional consumption. In this paper, we propose a hybrid energy scheduling model for a multi-energy microgrid with the integration of the hydrogen energy storage system (HESS) and the heat storage system (HSS). In our study, the operational uncertainties induced by renewables and loads (including electrical, hydrogen, and heat demand) are comprehensively considered. We investigate such an operating regime that HESS stores the surplus electricity in case of abundant renewable generation and generates electricity through hydrogen fuel cells otherwise. Further, heat units including HESS, combined heat and power (CHP), and external heat suppliers are modeled in this paper. We split the decision-makings of energy scheduling for both the day-ahead stage and real-time stage to tackle the power balancing issues. To effectively solve the aforementioned optimization model, a flexible weighted Model Predictive Control (weighted-MPC) strategy is proposed, in which the receding horizon can be suitably adjusted according to the forecasting accuracy of system uncertainties. The effectiveness of the proposed hybrid model for microgrid energy scheduling is comprehensively verified through extensive case studies. |
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