  Microgrids with energy storage systems and distributed renewable energy
sources play a crucial role in reducing the consumption from traditional power
sources and the emission of $CO_2$. Connecting multi microgrid to a
distribution power grid can facilitate a more robust and reliable operation to
increase the security and privacy of the system. The proposed model consists of
three layers, smart grid layer, independent system operator (ISO) layer and
power grid layer. Each layer aims to maximise its benefit. To achieve these
objectives, an intelligent multi-microgrid energy management method is proposed
based on the multi-objective reinforcement learning (MORL) techniques, leading
to a Pareto optimal set. A non-dominated solution is selected to implement a
fair design in order not to favour any particular participant. The simulation
results demonstrate the performance of the MORL and verify the viability of the
proposed approach.

Neural and Evolutionary Computing