Towards a Robust, Distributed and Decentralised Smart Energy Management of Microgrids

Modern energy systems comprise different entities that interact to allow an intelligent production, distribution, and consumption of energy. They need efficient and distributed demand-response management mechanisms to find optimised configurations of parameters of the grid components. When working with time schedules, optimisation algorithms used for this purpose usually rely on forecasts. However, forecasts bring uncertainty, which is rarely considered in optimisation. This work presents a robust and decentralised optimisation approach that deals also with such uncertainty by searching for optimal power schedule solutions, which are also reliable in unexpected circumstances. Based on message passing, our approach uses meta-heuristics for performing local optimisations. The implementation and validation of our proposal was conducted by means of a distributed multi-agent system, where the obtained results have shown the efficiency of our approach.