Smart Local Energy Systems: Optimal Planning of Stand-Alone Hybrid Green Power Systems for On-Line Charging of Electric Vehicles

Multi-vector smart local energy systems are playing an increasingly importantly role in the fast-track decarbonisation of our global energy services. An emergent contributor to global decarbonisation is green hydrogen. Green hydrogen can remove or reduce the burden of electrification of heat and tra...

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Bibliographic Details
Published in:IEEE access 2023, Vol.11, p.7398-7409
Main Authors: Ahangar, Hani Gharavi, Yew, Weng Kean, Flynn, David
Format: Article
Language:English
Subjects:
Clean energy
Cost analysis
Costs
Economic analysis
economics
Electric power demand
Electric power systems
Electric vehicle charging
Electric vehicles
Electrification
Energy
Energy sources
Fuel cells
Green hydrogen
Green products
Hybrid systems
Hydrogen
optimization
Particle swarm optimization
Photovoltaic cells
Power system reliability
Reliability
Reliability analysis
Renewable energy sources
Smart local energy system
Wind speed
Wind turbines
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Summary:Multi-vector smart local energy systems are playing an increasingly importantly role in the fast-track decarbonisation of our global energy services. An emergent contributor to global decarbonisation is green hydrogen. Green hydrogen can remove or reduce the burden of electrification of heat and transport on energy networks and provide a sustainable energy resource. In this paper, we explore how to optimally design a standalone hybrid green power system (HGPS) to supply a specific load demand with on-line charging of Electric Vehicles (EV). The HGPS includes wind turbine (WT) units, photovoltaic (PV) arrays, electrolyser and fuel cell (FC). For reliability analysis, it is assumed that WT, PV, DC/AC converter, and EV charger can also be sources of potential failure. Our methodology utilises a particle swarm optimization, coupled with a range of energy scenarios as to fully evaluate the varying interdependences and importance of economic and reliability indices, for the standalone HGPS. Our analysis indicates that EV charging with peak loading can have significant impact on the HGPS, resulting in significant reductions in the reliability indices of the HGPS, therefore enhance the operation of HGPS and reduces the overall cost. Our analysis demonstrates the importance of understanding local demand within a multi-vector optimization framework, as to ensure viable and resilient energy services.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2023.3237326