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Energy Management in Solar Microgrid via Reinforcement Learning

https://doi.org/10.1145/2903220.2903257
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-319-33509-4_8openalex-snapshot
Factored MDPs for Optimal Prosumer Decision-Making in Continuous State Spaces
inferredcites →https://doi.org/10.1007/s00521-011-0711-6openalex-snapshot
A self-learning scheme for residential energy system control and management
inferredcites →https://doi.org/10.1016/j.enbuild.2014.12.055openalex-snapshot
An Intelligent MPPT controller based on direct neural control for partially shaded PV system
inferredcites →https://doi.org/10.1016/j.enconman.2014.03.010openalex-snapshot
DC microgrid power flow optimization by multi-layer supervision control. Design and experimental validation
inferredcites →https://doi.org/10.1016/j.energy.2013.05.060openalex-snapshot
Reinforcement learning for microgrid energy management
inferredcites →https://doi.org/10.1016/j.procs.2015.02.016openalex-snapshot
Distributed Optimization of Solar Micro-grid Using Multi Agent Reinforcement Learning
inferredcites →https://doi.org/10.1016/j.renene.2013.04.014openalex-snapshot
Adaptive fuzzy gain scheduling PID controller for maximum power point tracking of photovoltaic system
inferredcites →https://doi.org/10.1016/j.solener.2015.02.004openalex-snapshot
A direct adaptive neural control for maximum power point tracking of photovoltaic system
inferredcites →https://doi.org/10.1109/72.159061openalex-snapshot
Learning and tuning fuzzy logic controllers through reinforcements
inferredcites →https://doi.org/10.1109/ghtc-sas.2014.6967580openalex-snapshot
Reinforcement learning for optimal energy management of a solar microgrid
inferredcites →https://doi.org/10.1109/icict11087.2005openalex-snapshot
2005 International Conference on Information and Communication Technologies
inferredcites →https://doi.org/10.1109/pesgm.2015.7285661openalex-snapshot
Multi agent system for distributed management of microgrids
inferredcites →https://doi.org/10.1109/tpwrs.2014.2322622openalex-snapshot
Multi-Agent System for Distributed Management of Microgrids
inferredcites →https://doi.org/10.1109/tsmc.1983.6313077openalex-snapshot
Neuronlike adaptive elements that can solve difficult learning control problems
inferredcites →https://doi.org/10.3390/en5093347openalex-snapshot
An Intelligent Multiagent System for Autonomous Microgrid Operation
inferredcites →https://doi.org/10.3763/aber.2009.0408openalex-snapshot
Artificial intelligence for energy conservation in buildings
inferredcites →https://doi.org/10.4236/eng.2013.51b001openalex-snapshot
Distributed Intelligent Microgrid Control Using Multi-Agent Systems
inferredcites →https://doi.org/10.5860/choice.33-1577openalex-snapshot
Artificial intelligence: a modern approach

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4196519openalex-extracted
Energy Efficient Behavior Modelling for Demand Side Recommender System in Solar Microgrid Applications Using Multi Agent Reinforcement Learning Model
inferred← citeshttps://doi.org/10.1002/est2.104openalex-snapshot
Synergic integration of desalination and electric vehicle loads with hybrid micro‐grid sizing and control: An Island Case Study
inferred← citeshttps://doi.org/10.1002/tee.23651openalex-snapshot
Dynamic Optimization of on‐Grid Integrated Energy System Considering Peak‐Shaving Demand Via Learning Methods
inferred← citeshttps://doi.org/10.1016/j.apenergy.2018.03.017openalex-snapshot
Fuzzy Q-Learning for multi-agent decentralized energy management in microgrids
inferred← citeshttps://doi.org/10.1016/j.resconrec.2025.108440openalex-snapshot
Deep Reinforcement Learning Based Optimization of an Island Energy-Water Microgrid System
inferred← citeshttps://doi.org/10.1016/j.scs.2023.104392openalex-snapshot
Energy efficient behavior modeling for demand side recommender system in solar microgrid applications using multi-agent reinforcement learning model
inferred← citeshttps://doi.org/10.1080/17512549.2017.1314832openalex-snapshot
Energy management in solar microgrid via reinforcement learning using fuzzy reward
inferred← citeshttps://doi.org/10.1109/isgteurope.2019.8905520openalex-snapshot
Sharing of Energy Among Cooperative Households Using Distributed Multi-Agent Reinforcement Learning
inferred← citeshttps://doi.org/10.1109/isgteurope.2019.8905538openalex-snapshot
Energy Management for Microgrids: a Reinforcement Learning Approach
inferred← citeshttps://doi.org/10.20944/preprints202011.0482.v1openalex-snapshot
Design and Simulation of Adaptive PID Controller Based on Fuzzy Q-Learning Algorithm for a BLDC Motor
inferred← citeshttps://doi.org/10.3390/app12178721openalex-snapshot
Intelligent Deep-Q-Network-Based Energy Management for an Isolated Microgrid
inferred← citeshttps://doi.org/10.3390/app9194001openalex-snapshot
Control Strategy of a Hybrid Renewable Energy System Based on Reinforcement Learning Approach for an Isolated Microgrid
inferred← citeshttps://doi.org/10.3390/w17142054openalex-snapshot
Decentralized Renewable-Energy Desalination: Emerging Trends and Global Research Frontiers—A Comprehensive Bibliometric Review
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