2022
DOI: 10.3390/s22010357
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Energy Management Strategy for an Autonomous Hybrid Power Plant Destined to Supply Controllable Loads

Abstract: This paper proposes an energy management strategy (EMS) for a hybrid stand-alone plant destined to supply controllable loads. The plant is composed of photovoltaic panels (PV), a wind turbine, a diesel generator, and a battery bank. The set of the power sources supplies controllable electrical loads. The proposed EMS aims to ensure the power supply of the loads by providing the required electrical power. Moreover, the EMS ensures the maximum use of the power generated by the renewable sources and therefore min… Show more

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Cited by 8 publications
(1 citation statement)
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References 32 publications
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“…In addition, various energy storage technologies (including supercapacitors, vanadium redox flow, pump storage and lithium-ion) were taken into account. For a hybrid off-grid system intended to power controllable loads, a different energy management strategy (EMS) is suggested by Yahyaoui and de la Peña (2022) the necessary electrical power while ‘ensuring the maximum use of energy produced by renewable sources, and ensuring that the battery bank operates at no cost and in the specified state values to ensure their safe operation’ in order to reduce the use of the genset. Using machine learning, predictive energy management for the grid is demonstrated (Refaai et al, 2022) to optimise the energy exchange with the supply network by means of logistic regression.…”
Section: Introductionmentioning
confidence: 99%
“…In addition, various energy storage technologies (including supercapacitors, vanadium redox flow, pump storage and lithium-ion) were taken into account. For a hybrid off-grid system intended to power controllable loads, a different energy management strategy (EMS) is suggested by Yahyaoui and de la Peña (2022) the necessary electrical power while ‘ensuring the maximum use of energy produced by renewable sources, and ensuring that the battery bank operates at no cost and in the specified state values to ensure their safe operation’ in order to reduce the use of the genset. Using machine learning, predictive energy management for the grid is demonstrated (Refaai et al, 2022) to optimise the energy exchange with the supply network by means of logistic regression.…”
Section: Introductionmentioning
confidence: 99%