Maximum Power Point Tracking Based on Reinforcement Learning Using Evolutionary Optimization Algorithms

In this paper, two universal reinforcement learning methods are considered to solve the problem of maximum power point tracking for photovoltaics. Both methods exhibit fast achievement of the MPP under varying environmental conditions and are applicable in different PV systems. The only required kno...

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Autori principali:	Kostas Bavarinos, Anastasios Dounis, Panagiotis Kofinas
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	MDPI AG 2021-01-01
Serie:	Energies
Soggetti:	maximum power point tracking reinforcement learning q-learning state–action-reward-state–action evolutionary algorithms optimization
Accesso online:	https://www.mdpi.com/1996-1073/14/2/335
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