Abstract
The indiscriminate nature of renewable energy sources does not help the stability of the Micro Grid (MG), especially the power balance: equilibrium of produced and consumed power. MG uses one or multiple sources of renewable energy, even if it is connected to the electrical main grid the need to add auxiliary sources is explained due to some unexpected main grid power outages. In this setting, this paper proposes the management of the energy production in the MG considering: (i) consumption and weather predictions, and the main grid fees (ii) charging mode strategy of the energy storage system (ESS); (iii) energy buying or selling decision from/to the main grid. The objectives of this paper are: (i) reducing the daily energy bill of the MG; (ii) optimizing CO\(_2\) emissions. This management is done using a Genetic Algorithm which is an evolutionary computation, and the obtained results are compared to a conventional management system.
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Zahraoui, F.Z., Chakir, H.E., Ouadi, H. (2022). Cost Reduction in Smart Grid Considering Greenhouse Gas Emissions Using Genetic Algorithm. In: Saidi, R., El Bhiri, B., Maleh, Y., Mosallam, A., Essaaidi, M. (eds) Advanced Technologies for Humanity. ICATH 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 110. Springer, Cham. https://doi.org/10.1007/978-3-030-94188-8_5
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