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

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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Bibliographic Details
Main Authors: Kostas Bavarinos, Anastasios Dounis, Panagiotis Kofinas
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Energies
Subjects:
maximum power point tracking
reinforcement learning
q-learning
state–action-reward-state–action
evolutionary algorithms
optimization
Online Access:https://www.mdpi.com/1996-1073/14/2/335

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