Abstract

Integrating sector coupling technologies into Hydrogen (H2) based hybrid renewable energy systems (HRES) is becoming a promising way to create energy prosumers, despite the very little research work being done in this largely unexplored field. In this paper, a sector coupling strategy (building and transportation) is developed and applied to a grid-connected PV/battery/H2 HRES, to maximise self-sufficiency for a University campus and to produce power and H2 for driving electric tram in Ouargla, Algeria. A multi-objective size optimization problem is solved as a single objective problem using the ε-constraint method, in which the cost of energy (COE) is defined as the main objective function to be minimized, while both loss of power supply probability (LPSP) and non-renewable usage (NRU) are defined as constraints. Particle swarm optimization and HOMER software are then employed for simulation and optimization purposes. Prior to the two scenarios investigated, a sensitivity study is performed to determine the effects of H2 demand by tram and NRU on the techno-economic feasibility of the proposed system, followed by a new reliability factor introduced in the optimization, namely loss of H2 supply probability (LHSP). The results of the first scenario show that by setting NRUmax = 100%, the system without H2 provides the best solution with COE of 0.016 $/kWh that reaches grid parity and has 13% NRU. However, by setting NRUmax = 1% in the second scenario, an optimized configuration consisting of grid/PV/Electrolyzer/Fuel cell/Storage tank is obtained, which has 0% NRU and COE of 0.1 $/kWh. In the second scenario, it is also observed that an increased number of trams (i.e. increased H2 demands) causes a significant reduction in LHSP, COE, NRU and CO2 emissions. It is thus concluded that the grid/PV combination is the optimal choice for the studied system when considering economic aspects. However, taking into account the growing requirements of future energy systems, grid-connected PV with H2 will be the best solution.

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