Journal ArticleDOI
Optimal mileage-based PV array reconfiguration using swarm reinforcement learning
TLDR
Simulation results demonstrate that the proposed swarm reinforcement learning (SRL) can obtain a larger total benefit than genetic algorithm (GA), particle swarm optimization (PSO), grasshopper optimization algorithm (GOA), harris hawks optimizer (HHO), butterfly optimization algorithms (BOA), and Q-learning, in which the benefit increment can reach from 2.12% ( against PSO) to 10.62% (against Q- learning).About:
This article is published in Energy Conversion and Management.The article was published on 2021-03-15. It has received 45 citations till now. The article focuses on the topics: Continuous optimization & Discrete optimization.read more
Citations
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Journal ArticleDOI
Using machine learning in photovoltaics to create smarter and cleaner energy generation systems: A comprehensive review
Ali Sohani,Hoseyn Sayyaadi,Cristina Cornaro,Mohammad Hassan Shahverdian,Marco Pierro,David Moser,Nader Karimi,Mohammad Hossein Doranehgard,Larry K.B. Li +8 more
TL;DR: A comprehensive review of machine learning techniques applied to photovoltaic (PV) systems can be found in this article , where the authors discuss the challenges and future directions of using machine learning to analyze PV systems.
Journal ArticleDOI
A multi-agent deep reinforcement learning approach enabled distributed energy management schedule for the coordinate control of multi-energy hub with gas, electricity, and freshwater
TL;DR: In this article , an attention mechanism-based multi-agent deep reinforcement learning algorithm is applied, where multi-agents are centrally trained to obtain the coordinate energy management strategy while being executed in a decentralized manner to provide the dispatch instruction for each energy hub with only local states.
Journal ArticleDOI
Partial shading mitigation in PV arrays through dragonfly algorithm based dynamic reconfiguration
TL;DR: In this article , a Dragonfly algorithm (DA) based reconfiguration for shaded PV arrays is proposed for unwanted shading losses reduction in arrays, which has a higher power enhancement capability, lower computational time, and hasty convergence.
Journal ArticleDOI
Photovoltaic array reconfiguration under partial shading conditions for maximum power extraction: A state-of-the-art review and new solution method
Sevda Rezazadeh,Arash Moradzadeh,Kazem Pourhossein,Mohammadreza Akrami,Behnam Mohammadi-Ivatloo,Amjad Anvari-Moghaddam +5 more
TL;DR: In this article , the authors proposed an 8-Queen's technique for reconfiguring the PV modules corresponding to the total-cross-tied (TCT) interconnection PV array, based on the movement of 8 queens on the chessboard so that none of the queens can attack the others.
Journal ArticleDOI
Power losses mitigation through electrical reconfiguration in partial shading prone solar PV arrays
TL;DR: In this paper , a new module electrical reconfiguration technique is proposed to disperse the effect of partial shading power generation improvement and reduce the losses in the PV arrays, which requires no sensors and switches.
References
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Journal ArticleDOI
Technical Note : \cal Q -Learning
Chris Watkins,Peter Dayan +1 more
TL;DR: This paper presents and proves in detail a convergence theorem forQ-learning based on that outlined in Watkins (1989), showing that Q-learning converges to the optimum action-values with probability 1 so long as all actions are repeatedly sampled in all states and the action- values are represented discretely.
Journal ArticleDOI
Mastering the game of Go without human knowledge
David Silver,Julian Schrittwieser,Karen Simonyan,Ioannis Antonoglou,Aja Huang,Arthur Guez,Thomas Hubert,Lucas Baker,Matthew Lai,Adrian Bolton,Yutian Chen,Timothy P. Lillicrap,Fan Hui,Laurent Sifre,George van den Driessche,Thore Graepel,Demis Hassabis +16 more
TL;DR: An algorithm based solely on reinforcement learning is introduced, without human data, guidance or domain knowledge beyond game rules, that achieves superhuman performance, winning 100–0 against the previously published, champion-defeating AlphaGo.
Journal ArticleDOI
Technical Note Q-Learning
Chris Watkins,Peter Dayan +1 more
TL;DR: In this article, it is shown that Q-learning converges to the optimum action-values with probability 1 so long as all actions are repeatedly sampled in all states and the action values are represented discretely.
Journal ArticleDOI
Enhanced Power Generation From PV Array Under Partial Shading Conditions by Shade Dispersion Using Su Do Ku Configuration
TL;DR: In this paper, the physical location of the modules in a total cross-tied (TCT) connected PV array is arranged based on the Su Do Ku puzzle pattern so as to distribute the shading effect over the entire array.
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