Multi-objective optimisation for hybrid electric system setup in a remote island

Abstract This paper assesses the optimum configuration of a hybrid electric system, incorporating different forms of marine renewable energy. The efficiency of three multi-objective optimisation approaches—Multi-objective Pareto Search, Multi-Objective Genetic Algorithm (MOGA) and a hybrid MOGA is assessed and compared when utilised to define the Pareto front of optimal trade-off configurations, balancing low environmental impact with cost-effectiveness. This method is implemented in the electricity market of the Portuguese island of Porto Santo, where current conventional and renewable energy power plants (such as thermal, onshore wind, and photovoltaic) are analysed alongside other marine energy sources (wave and offshore wind). Various linear and non-linear constraints restrict the optimisation. Results point to a system dimensioned with a 63% share of renewable energies (Res), the optimal configuration with the cheapest electric generation cost (3.7 M€/year), in a trade-off of the highest environmental impact. The lowest environmental impact is linked to a system wholly composed of RE sources, although it is also associated with the most expensive cost of electricity (4.6 M€/year). Overall, configurations in the Pareto optima present higher installed capacities of offshore wind technology, followed sequentially by lower penetrations of onshore wind, thermoelectric, wave and solar photovoltaic energies.