Reduced desalination carbon footprint on islands with weak electricity grids. The case of Gran Canaria.

The aim of this paper is to present options to make low-carbon footprint large-scale desalination a reality on arid islands with weak electrical grids. Through these options, the goal is to reconfigure on-grid wind energy/desalination systems for large- and medium-scale water production. In this context, it is proposed to use lithium-ion batteries for stationary energy storage together with management strategies aimed at avoiding the wind energy/desalination systems having to consume energy from the conventional grid they are connected to. The control strategy is based on ensuring that the power provided by the wind farm and batteries remains in synchrony with the power demand of the desalination plant throughout the system's useful life. The interannual variation of wind energy is considered when sizing the renewable energy system and processes for its estimation are proposed. The case study is centred on the Canary Archipelago, a region that is especially vulnerable to the impacts of climate change, but which enjoys exceptional characteristics for the exploitation of wind energy. The results obtained show the optimal wind farm and energy storage system capacities of the analysed configurations. The approach presented allows a low-carbon operational footprint. If the control strategy were to be put into practice today, the current grid restrictions and a life cycle assessment of the system carried out in a societal context that continues to be fossil fuel dependent indicate a potential reduction of 77.4% of the footprint. However, the remaining 22.6% could be eliminated in the future when the manufacturing processes of wind turbines, batteries and desalination plants receive the benefits of carbon-neutral societies. [Display omitted] • A method for achieving large-scale, low-carbon desalination is presented. • Optimal wind farm and storage capacities for the system are determined. • The method offers substantial CO2 emission reduction potential. • Using climate ERA5 reanalysis data, enhances robustness by addressing wind variability. • Proposed adjustments enhance adaptability to technological advances and future scenarios. [ABSTRACT FROM AUTHOR]