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New Management Algorithms for Smart Electricity Network: Designing and Working Principles

Abstract : The energy needs considerably increase with the economic development of a country. The promotion of renewable energy sources was enhanced because of global awareness of fossil fuel depletion and climate changes induced by their use. The renewable energy sources are, however, intermittent in nature. Alternative solutions such as the integration of renewable energy systems into the conventional electric grids have been recommended. The integration approach uses photovoltaic, wind, and other renewable energy sources to supply sustainable energy to the built spaces during peak loads or electric backup. In this article, we proposed a new approach to manage the energy flow in a smart grid. Two algorithms were developed to manage the integration of renewable sources combined into a storage system into a conventional power grid. The first algorithm aims to smooth the consumption peak and reduce the extraction from the conventional grid while the second aims to maximize the use of renewable energy depending on the energy demand. Reliability tests of the algorithm behavior have been conducted in comparison to the HOMER software and the results show a maximum relative error of 4.78% on the management of grid extraction. These algorithms are based on scenarios and operational parameters to optimize the integration of renewable energy in the current electricity network. Their application will reduce the negative impact of fossil energy and enhance the energy transition.
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Contributor : Damien Ali Hamada Fakra <>
Submitted on : Thursday, April 22, 2021 - 9:55:14 AM
Last modification on : Wednesday, June 30, 2021 - 9:40:12 PM
Long-term archiving on: : Friday, July 23, 2021 - 6:02:44 PM


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Ando Ny Aina Randriantsoa, Ali Hamada Fakra, Manitra Pierrot Ranjaranimaro, Mohamed Nasroudine Mohamed Rachadi, Jean Claude Gatina. New Management Algorithms for Smart Electricity Network: Designing and Working Principles. Progress in Advanced Computing and Intelligent Engineering (SPRINGER), pp.671-682, 2021, ⟨10.1007/978-981-33-4299-6_55⟩. ⟨hal-03202785⟩



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