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Energy Management Based on Safe Multi-Agent Reinforcement Learning for Smart Multi-Energy Buildings in Distribution Networks

https://doi.org/10.2139/ssrn.4691482
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inferredcites →https://doi.org/10.1007/s10462-021-10085-1openalex-extracted
Model-free reinforcement learning from expert demonstrations: a survey
inferredcites →https://doi.org/10.1016/j.apenergy.2021.118403openalex-extracted
Safe reinforcement learning for real-time automatic control in a smart energy-hub
inferredcites →https://doi.org/10.1016/j.apenergy.2022.118762openalex-extracted
Model-augmented safe reinforcement learning for Volt-VAR control in power distribution networks
inferredcites →https://doi.org/10.1016/j.artint.2023.103905openalex-extracted
Safe multi-agent reinforcement learning for multi-robot control
inferredcites →https://doi.org/10.1016/j.enbuild.2023.112941openalex-extracted
Inverse Reinforcement Learning Control for Building Energy Management
inferredcites →https://doi.org/10.1016/j.epsr.2022.108521openalex-extracted
GridLearn: Multiagent reinforcement learning for grid-aware building energy management
inferredcites →https://doi.org/10.1109/cac57257.2022.10054852openalex-extracted
Multi-Agent Reinforcement Learning for Active Voltage Control on Multi-Hybrid Microgrid Interconnection System
inferredcites →https://doi.org/10.1109/ccta54093.2023.10253019openalex-extracted
Attention Based Multi-Agent Reinforcement Learning for Demand Response in Grid-Responsive Buildings
inferredcites →https://doi.org/10.1109/tcss.2021.3096824openalex-extracted
Explainable AI in Deep Reinforcement Learning Models for Power System Emergency Control
inferredcites →https://doi.org/10.1109/tnn.1998.712192openalex-extracted
Reinforcement Learning: An Introduction
inferredcites →https://doi.org/10.1109/tnnls.2018.2801880openalex-extracted
Distributed Economic Dispatch in Microgrids Based on Cooperative Reinforcement Learning
inferredcites →https://doi.org/10.1109/tpwrs.2018.2829021openalex-extracted
Pandapower—An Open-Source Python Tool for Convenient Modeling, Analysis, and Optimization of Electric Power Systems
inferredcites →https://doi.org/10.1109/tpwrs.2019.2941134openalex-extracted
Deep-Reinforcement-Learning-Based Autonomous Voltage Control for Power Grid Operations
inferredcites →https://doi.org/10.1109/tpwrs.2019.2948132openalex-extracted
Optimal Tap Setting of Voltage Regulation Transformers Using Batch Reinforcement Learning
inferredcites →https://doi.org/10.1109/tpwrs.2022.3159825openalex-extracted
Target-Value-Competition-Based Multi-Agent Deep Reinforcement Learning Algorithm for Distributed Nonconvex Economic Dispatch
inferredcites →https://doi.org/10.1109/tsg.2016.2629450openalex-extracted
Convolutional Neural Networks for Automatic State-Time Feature Extraction in Reinforcement Learning Applied to Residential Load Control
inferredcites →https://doi.org/10.1145/3427773.3427869openalex-extracted
A Centralised Soft Actor Critic Deep Reinforcement Learning Approach to District Demand Side Management through CityLearn
inferredcites →https://doi.org/10.1145/3486611.3492226openalex-extracted
The citylearn challenge 2021
inferredcites →https://doi.org/10.1145/3538637.3539616openalex-extracted
PowerGridworld
inferredcites →https://doi.org/10.1609/aaai.v35i10.17062openalex-extracted
Decentralized Policy Gradient Descent Ascent for Safe Multi-Agent Reinforcement Learning
inferredcites →https://doi.org/10.23919/acc53348.2022.9867652openalex-extracted
Computationally Efficient Safe Reinforcement Learning for Power Systems
inferredcites →https://doi.org/10.23919/ccc58697.2023.10240322openalex-extracted
Multi-Agent Q-Value Mixing Network with Covariance Matrix Adaptation Strategy for the Voltage Regulation Problem
inferredcites →https://doi.org/10.48550/arxiv.1512.01629openalex-extracted
Risk-Constrained Reinforcement Learning with Percentile Risk Criteria
inferredcites →https://doi.org/10.48550/arxiv.1801.08757openalex-extracted
Safe Exploration in Continuous Action Spaces
inferredcites →https://doi.org/10.48550/arxiv.2003.04310openalex-extracted
Advancing Renewable Electricity Consumption With Reinforcement Learning
inferredcites →https://doi.org/10.48550/arxiv.2011.09533openalex-extracted
Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?
inferredcites →https://doi.org/10.48550/arxiv.2110.02793openalex-extracted
Multi-Agent Constrained Policy Optimisation
inferredcites →https://doi.org/10.48550/arxiv.2110.14300openalex-extracted
Multi-Agent Reinforcement Learning for Active Voltage Control on Power Distribution Networks
inferredcites →https://doi.org/10.48550/arxiv.2202.06558openalex-extracted
Saute RL: Almost Surely Safe Reinforcement Learning Using State Augmentation
inferredcites →https://doi.org/10.5555/3122009.3242024openalex-extracted
Risk-constrained reinforcement learning with percentile risk criteria
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