Multiobjective Optimisation of integrated energy systems for remote communities considering economic and LCA factors

Resources both physical and financial are scarce in most developing countries while environmental concerns are growing requiring a greater effort to rationally plan investments. Nowadays the methods for designing, planning and managing integrated energy systems, while holistically considering the major economic and environmental factors, are still embryonic. However, the first phase of the design is often crucial if we want to aim at a better resource management and at the reduction of energy consumption together with reduced environmental impact. Considering integrated energy systems implies dealing with complex systems in which the synergy between the various components is exploited at best. The context of isolated communities further increases the difficulties when considering the long distance of transportation required to supply fossil fuels, the constraints of not being connected to a national network and the locations in very precarious environments, with limited or inexistent resources except for solar. This paper illustrates a holistic method to rationalize the design of energy integrated systems accounting for Life Cycle Analysis parameters (CST method). It is based on a superstructure (collection of models of all envisaged technologies) using a multi-modal and multi-objective evolutionary algorithm. The models include both solar power technologies as well as conventional Diesel electric generators. The approach is applied to the supply of energy services to an oasis in the Sahara desert. The study shows that the economic implementation of renewable energy (solar) is even more difficult, compared to Diesel based solutions, in cases of isolated communities with high load variations.