Multiobjective Optimisation of integrated energy systems for remote communities considering economic and CO2 emissions

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 manage resources better resource and reduce energy consumption and pollution. Considering integrated energy systems implies dealing with complex systems in which the synergy between the various components is best exploited (for example the thermal energy of a diesel engine produced during the night is complimented by the Ranking Organic Cycle of a solar thermal plant). The context of isolated communities further increases the difficulties when considering the long distance of transport required to supply fossil fuels. These sites are often located in very precarious environments, with limited or nonexistent resources except for solar energy, and with frequent additional needs for desalination (in arid zones). This paper illustrates a holistic method to rationalize the design of energy integrated systems. It is based on a superstructure (collection of models of all envisaged technologies) and a multi-objective optimisation (resources, demand, energy, emission, cost) using an evolutionary algorithm. The approach proposed allows the identification of more complete and more coherent integrated configurations characterizing the most promising designs (also taking into account the time dependency aspects). It also allows to better structure the information in view of a participative decision approach. 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. New infrastructure or retrofit cases are considered.