Goddard, RohanZhang, LijunXia, Xiaohua2020-08-132020-08-132019-02Goddard, R., Zhang, L. & Xia, X. 2019, 'Optimal sizing and power sharing of distributed hybrid renewable energy systems considering socio-demographic factors', Energy Procedia, vol. 159, pp. 340-345.1876-6102 (online)10.1016/j.egypro.2019.01.005http://hdl.handle.net/2263/75673Applied Energy Symposium and Forum, Renewable Energy Integration with Mini/Microgrids, REM 2018, 29–30 September 2018, Rhodes, GreeceWhen sizing distributed hybrid renewable energy systems (HRESs) it has been found that capital costs can significantly be reduced when socio-demographic factors are considered. Unique electricity usage patterns have previously been classified using users’ socio-demographic factors and used to optimize the size of individual stand-alone HRESs. An optimization model is formulated where an individual HRES is assigned to each of the six socio-demographic classifications and power sharing is implemented with neighboring sites in a specific configuration. Solving the optimization problem with a hybrid approach using Matlab’s genetic algorithm and fmincon results in an 82,10% reduction in capital costs compared to the system without power sharing.en© The Authors. This is an open access article under CC BY-NC-ND license.SizingOptimizationPower sharingSocio-demographic factorsHybrid renewable energy system (HRES)Article