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Double Deep $Q$ -Learning-Based Distributed Operation of Battery Energy Storage System Considering Uncertainties

https://doi.org/10.1109/tsg.2019.2924025
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What this work says

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

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Reinforcement Learning
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Cooperative Multi-Agent Learning: The State of the Art
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Reinforcement learning for microgrid energy management
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Optimal control in microgrid using multi-agent reinforcement learning
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Microgrid supervisory controllers and energy management systems: A literature review
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Energy Management Systems in Microgrid Operations
inferredcites →https://doi.org/10.1016/s0925-2312(00)00324-6openalex-snapshot
Reinforcement Learning: An Introduction
inferredcites →https://doi.org/10.1049/iet-rpg.2010.0052openalex-snapshot
Smart energy management system for optimal microgrid economic operation
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Robust Optimal Operation of AC/DC Hybrid Microgrids Under Market Price Uncertainties
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Microgrids management
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A comparative study of policies in Q-learning for foraging tasks
inferredcites →https://doi.org/10.1109/pes.2010.5589633openalex-snapshot
Multi-agent reinforcement learning for microgrids
inferredcites →https://doi.org/10.1109/smartgridcomm.2012.6485964openalex-snapshot
Using smart devices for system-level management and control in the smart grid: A reinforcement learning framework
inferredcites →https://doi.org/10.1109/tie.2014.2356171openalex-snapshot
Distributed Optimal Resource Management Based on the Consensus Algorithm in a Microgrid
inferredcites →https://doi.org/10.1109/tnn.2004.842673openalex-snapshot
Reinforcement Learning: An Introduction
inferredcites →https://doi.org/10.1109/tnnls.2016.2514358openalex-snapshot
Dynamic Energy Management System for a Smart Microgrid
inferredcites →https://doi.org/10.1109/tpel.2013.2257857openalex-snapshot
Supervisory Control of an Adaptive-Droop Regulated DC Microgrid With Battery Management Capability
inferredcites →https://doi.org/10.1109/tpwrs.2013.2244104openalex-snapshot
Energy Management of Microgrid in Grid-Connected and Stand-Alone Modes
inferredcites →https://doi.org/10.1109/tpwrs.2013.2290006openalex-snapshot
Microgrid Optimal Scheduling With Multi-Period Islanding Constraints
inferredcites →https://doi.org/10.1109/tpwrs.2016.2568858openalex-snapshot
Energy Management in Multi-Microgrid Systems — Development and Assessment
inferredcites →https://doi.org/10.1109/tsg.2013.2294187openalex-snapshot
A Centralized Energy Management System for Isolated Microgrids
inferredcites →https://doi.org/10.1109/tsg.2016.2558517openalex-snapshot
Market-Based Versus Price-Based Microgrid Optimal Scheduling
inferredcites →https://doi.org/10.1109/tsg.2016.2585671openalex-snapshot
A Multiagent-Based Hierarchical Energy Management Strategy for Multi-Microgrids Considering Adjustable Power and Demand Response
inferredcites →https://doi.org/10.1109/tsg.2016.2607422openalex-snapshot
A Resilient and Privacy-Preserving Energy Management Strategy for Networked Microgrids
inferredcites →https://doi.org/10.1109/tsg.2018.2834219openalex-snapshot
On-Line Building Energy Optimization Using Deep Reinforcement Learning
inferredcites →https://doi.org/10.1109/tste.2013.2247428openalex-snapshot
Battery Energy Storage Station (BESS)-Based Smoothing Control of Photovoltaic (PV) and Wind Power Generation Fluctuations
inferredcites →https://doi.org/10.1137/s0363012901385691openalex-snapshot
OnActor-Critic Algorithms
inferredcites →https://doi.org/10.1609/aaai.v30i1.10295openalex-snapshot
Deep Reinforcement Learning with Double Q-Learning
inferredcites →https://doi.org/10.20508/ijrer.90564openalex-snapshot
Investigation on North American Microgrid Facility
inferredcites →https://doi.org/10.20508/ijrer.v5i2.2203.g6611openalex-snapshot
Investigation on North American Microgrid Facility
inferredcites →https://doi.org/10.3390/en10070903openalex-snapshot
Diffusion Strategy-Based Distributed Operation of Microgrids Using Multiagent System
inferredcites →https://doi.org/10.3390/en10101484openalex-snapshot
Optimal Operation of Microgrids Considering Auto-Configuration Function Using Multiagent System
inferredcites →https://doi.org/10.3390/en12091789openalex-snapshot
Q-Learning-Based Operation Strategy for Community Battery Energy Storage System (CBESS) in Microgrid System
inferredcites →https://doi.org/10.48550/arxiv.1312.5602openalex-snapshot
Playing Atari with Deep Reinforcement Learning
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A Generalized Path Integral Control Approach to Reinforcement Learning
inferredcites →https://doi.org/10.5555/3026877.3026899openalex-snapshot
TensorFlow: A system for large-scale machine learning

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

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Reinforcement-Learning-Based Energy Storage System Operation Strategies to Manage Wind Power Forecast Uncertainty
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A Multi-Timescale Two-Stage Robust Grid-Friendly Dispatch Model for Microgrid Operation
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Distributed Operation of Wind Farm for Maximizing Output Power: A Multi-Agent Deep Reinforcement Learning Approach
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Reinforcement Learning Techniques for Optimal Power Control in Grid-Connected Microgrids: A Comprehensive Review
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Emergency Load Shedding Strategy for Microgrids Based on Dueling Deep Q-Learning
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Optimal Reactive Power Dispatch With Time-Varying Demand and Renewable Energy Uncertainty Using Rao-3 Algorithm
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Deep Learning in Smart Grid Technology: A Review of Recent Advancements and Future Prospects
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Resilience Microgrid as Power System Integrity Protection Scheme Element With Reinforcement Learning Based Management
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Electric Water Heaters Management via Reinforcement Learning With Time-Delay in Isolated Microgrids
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Trading Off Environmental and Economic Scheduling of a Renewable Energy Based Microgrid Under Uncertainties
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SFNAS-DDPG: A Biomass-Based Energy Hub Dynamic Scheduling Approach via Connecting Supervised Federated Neural Architecture Search and Deep Deterministic Policy Gradient
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Artificial Intelligence in the Hierarchical Control of AC, DC, and Hybrid AC/DC Microgrids: A Review
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Data-Driven and Knowledge-Enhanced Approaches for Real-Time Grid Dispatch: A Comprehensive Survey
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Correlated Deep Q-learning based Microgrid Energy Management
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Smart home's energy management applying the deep deterministic policy gradient and clustering
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A bi-level multi-objective planning method for microgrid with offshore wind power
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A Survey on Application of Artificial Intelligence Techniques in Microgrid Control
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MicroPPO: Safe Power Flow Management in Decentralized Micro-Grids with Proximal Policy Optimization
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Development and Simulation of SOC Estimation, Thermal Management and Health Monitoring Algorithms for Optimized Battery Management Systems
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Optimal Coordination of Distributed Energy Resources Using Deep Deterministic Policy Gradient
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Multi-Agent Deep Deterministic Policy Gradient Algorithm Based on Classification Experience Replay
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Combining Genetic and Gravitational Search Algorithms for the Optimal Management of Battery Energy Storage Systems in Real-Time Pricing Markets
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Optimizing Demand Response in Multi-HVAC Systems by RL Control with Comfort Consideration
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Comparing SAC and DQN in Microgrid EMS: Baseline Results under Fixed Electricity Price
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Real-time Energy Management of a Low-Carbon Micro-Grid Based on Deep Reinforcement Learning
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Research on Frequency Regulation Market Application Strategy of Integrated Fire-Storage System Based on Q -Reinforcement Learning
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An Efficient Distributed Reinforcement Learning for Enhanced Multi-Microgrid Management
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Battery Control in a Smart Energy Network using Double Dueling Deep Q-Networks
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Multi agent deep Q-reinforcement learning for autonomous low voltage grid control
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Reinforcement Learning Based Energy Storage Units Scheduling Considering Point of Common Coupling Constraint
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Autonomous Micro-Grids: A Reinforcement Learning-Based Energy Management Model in Smart Cities
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Optimal Scheduled Control Operation of Battery Energy Storage System using Model-Free Reinforcement Learning
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Smart Online Charging Algorithm for Electric Vehicles via Customized Actor–Critic Learning
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Multiagent Bayesian Deep Reinforcement Learning for Microgrid Energy Management Under Communication Failures
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Smart Home’s Energy Management Through a Clustering-Based Reinforcement Learning Approach
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Combating Uncertainties in Smart Grid Decision Networks: Multiagent Reinforcement Learning With Imperfect State Information
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Multiagent Imitation Learning-Based Energy Management of a Microgrid With Hybrid Energy Storage and Real-Time Pricing
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Human-in-the-Loop Battery Scheduling in Buildings via Intent-Guided Rule-Reinforcement Learning
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A Transfer Reinforcement Learning Framework for Smart Home Energy Management Systems
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Unintentional Islanding Transition Control Strategy for Three-/Single-Phase Multimicrogrids Based on Artificial Emotional Reinforcement Learning
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Real-Time Energy Scheduling Applying the Twin Delayed Deep Deterministic Policy Gradient and Data Clustering
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LSTM-Aided Reinforcement Learning for Energy Management in Microgrid with Energy Storage and EV Charging
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Machine Learning Technique for Hydrogen Fuel Cell Based Microgrid Energy Management
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Soft Actor-Critic-Based MPPT Control of Solar PV Systems Under Partial Shading Conditions
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Intelligent Energy Management of a Microgrid Using Reinforcement Learning
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Constrained Reinforcement Learning for Stochastic Dynamic Optimal Power Flow Control
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Deep Reinforcement Learning-Based Operation of Distribution Systems Using Surrogate Model
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Deep Reinforcement Learning-Based Optimization of Second-Life Battery Utilization in Electric Vehicles Charging Stations
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Deep RL-Based Operation of Clustered EV Charging Stations Integrated with PV and Battery
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OIRL: Real-time Optimization of Peak Shaving and Energy Arbitrage in Industrial Microgrids with Offline Inverse Reinforcement Learning Framework
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Optimal Energy Scheduling of Flexible Industrial Prosumers via Reinforcement Learning
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Bi-Level Optimization for Energy Management of Networked Microgrid
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Smart Microgrid Optimization using Deep Reinforcement Learning by utilizing the Energy Storage Systems
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Energy Scheduling Optimization for Microgrids Based on Partially Observable Markov Game
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A Privacy-Preserving Federated Reinforcement Learning Method for Multiple Virtual Power Plants Scheduling
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Temporal-Aware Deep Reinforcement Learning for Energy Storage Bidding in Energy and Contingency Reserve Markets
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Evolutionary Multitasking via Reinforcement Learning
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Distributed BESS Scheduling for Power Demand Reshaping in 5G and Beyond Networks
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A Multi-Time Scale Reactive Power Optimization Model Considering Network Reconfiguration
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Safe Deep Reinforcement Learning for Active Distribution System Model Predictive Control With EVs and DERs
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A Novel Battery Integration Method of Modular Multilevel Converter With Battery Energy Storage System for Capacitor Voltage Ripple Reduction
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DIP-QL: A Novel Reinforcement Learning Method for Constrained Industrial Systems
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Optimal Operation of Microgrid Through Loss-Guided Neural Network-Based Approach
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An Energy Management Strategy Based on DDPG With Improved Exploration for Battery/Supercapacitor Hybrid Electric Vehicle
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A Real-Time Energy Management Strategy of Flexible Smart Traction Power Supply System Based on Deep Q-Learning
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Binocular Vision-Based Motion Planning of an AUV: A Deep Reinforcement Learning Approach
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Broad Learning With Reinforcement Learning Signal Feedback: Theory and Applications
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Intelligent Energy Scheduling in Renewable Integrated Microgrid With Bidirectional Electricity-to-Hydrogen Conversion
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Multi-Agent Energy Management Strategy for Multi-Microgrids Using Reinforcement Learning
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Many-Objective Distribution Network Reconfiguration Via Deep Reinforcement Learning Assisted Optimization Algorithm
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Bounding Regression Errors in Data-Driven Power Grid Steady-State Models
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A Novel Model-Free Deep Reinforcement Learning Framework for Energy Management of a PV Integrated Energy Hub
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Constrained Reinforcement Learning for Predictive Control in Real-Time Stochastic Dynamic Optimal Power Flow
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Cyber-Attack Recovery Strategy for Smart Grid Based on Deep Reinforcement Learning
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Deep Reinforcement Learning-Based Controller for SOC Management of Multi-Electrical Energy Storage System
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2020 Index IEEE Transactions on Smart Grid Vol. 11
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Deep-Reinforcement-Learning-Based Capacity Scheduling for PV-Battery Storage System
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Prioritized Replay Dueling DDQN Based Grid-Edge Control of Community Energy Storage System
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Online Optimal Power Scheduling of a Microgrid via Imitation Learning
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Reinforcement Learning for Selective Key Applications in Power Systems: Recent Advances and Future Challenges
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An Assessment of Multistage Reward Function Design for Deep Reinforcement Learning-Based Microgrid Energy Management
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