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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.

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