Sizing of a stand-alone microgrid considering electric power, cooling/heating, hydrogen loads and hydrogen storage degradation

•The design of a combined cooling/heat/power and hydrogen microgrid system.•The integration of a degradation model of the fuel cell and the electrolyzer.•Three operation strategies are compared to analyze the influence on sizing results.•A 1-h resolution rolling-horizon simulation is used to check t...

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Bibliographic Details
Published in:Applied energy Vol. 205; pp. 1244 - 1259
Main Authors: Li, Bei, Roche, Robin, Paire, Damien, Miraoui, Abdellatif
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.11.2017
Elsevier
Subjects:
algorithms
Automatic
batteries
Degradation
Electric power
Engineering Sciences
Evolutionary algorithm
Fluid mechanics
fuel cells
heat
hydrogen
linear programming
Mechanics
Microgrid
Multi-energy
Physics
rolling
Sizing
Thermics
uncertainty
Unit commitment
Degradation
Multi-energy
Microgrid
Sizing
Evolutionary algorithm
Unit commitment
ISSN:0306-2619, 1872-9118
Online Access:Get full text
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Summary:•The design of a combined cooling/heat/power and hydrogen microgrid system.•The integration of a degradation model of the fuel cell and the electrolyzer.•Three operation strategies are compared to analyze the influence on sizing results.•A 1-h resolution rolling-horizon simulation is used to check the results.•A robust method is used to assess the impact of the forecasting errors. Microgrids are small-scale power systems with local generation, storage systems and load demands, that can operate connected to the main grid or islanded. In such systems, optimal components sizing is necessary to make the system secure and reliable, while minimizing costs. In this paper, a stand-alone microgrid considering electric power, cooling/heating and hydrogen consumption is built. A unit commitment algorithm, formulated as a mixed integer linear programming problem, is used to determine the best operation strategy for the system. A genetic algorithm is used to search for the best size of each component. The influence of three factors (operation strategy, accuracy of load and renewable generation forecasts, and degradation of fuel cell, electrolyzer and battery) on sizing results is discussed. A 1-h rolling horizon simulation is used to check the validity of the sizing results. A robust optimization method is also used to handle the uncertainties and evaluate their impact on results.
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ISSN:0306-2619
1872-9118
DOI:10.1016/j.apenergy.2017.08.142