For a successful transition to a renewable energy economy, optimisation of renewable energy systems must evolve to take into account not only technical and/or economic objectives, but also environmental and socio-political objectives. A Normalised Weighted Constrained Multi-Objective (NWCMO) meta-heuristic optimisation algorithm has been proposed for achieving a compromise between mutually conflicting technical, economic, environmental and socio-political objectives, in order to simulate and optimise a renewable energy system of any configuration. In this paper, an optimisation methodology based on these four classes of objective is presented. The methodology was implemented using Particle Swarm Optimisation and tested against data from the literature. In the Case Study the original results could be reproduced, but the newly-implemented algorithm was further able to find a more optimal design solution under the same constraints. The influence of additional quantified socio-political inputs was explored.