Multi-Agent attention-based deep reinforcement learning for demand response in grid-responsive buildings

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Energy management for demand response in networked greenhouses with multi-agent deep reinforcement learning

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Energy management in integrated energy system with electric vehicles as mobile energy storage: An approach using bi-level deep reinforcement learning

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Perspectives for artificial intelligence in sustainable energy systems

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Building electrification and carbon emissions: Integrated energy management considering the dynamics of the electricity mix and pricing

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Multiscale wildfire and smoke detection in complex drone forest environments based on YOLOv8

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BuildingGym: An open-source toolbox for AI-based building energy management using reinforcement learning

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Demand flexibility and cost-saving potentials via smart building energy management: Opportunities in residential space heating across the US

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Variational quantum circuit learning-enabled robust optimization for AI data center energy control and decarbonization

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Review of optimization control methods for HVAC systems in Demand Response (DR): Transition from model-driven to model-free approaches and challenges

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Multi-agent deep reinforcement learning-based cooperative energy management for regional integrated energy system incorporating active demand-side management

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Multi-agent deep reinforcement learning based demand response and energy management for heavy industries with discrete manufacturing systems

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Physically consistent deep learning-based day-ahead energy dispatching and thermal comfort control for grid-interactive communities

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Review and Evaluation of Multi-Agent Control Applications for Energy Management in Buildings

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Sustainable energy management and control for Decarbonization of complex multi-zone buildings with renewable solar and geothermal energies using machine learning, robust optimization, and predictive control

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Integrating few-shot personalized thermal comfort model and reinforcement learning for HVAC demand response optimization

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Towards intelligent management of regional building energy systems: A framework combined with deep reinforcement learning for hybrid energy storage

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A scalable demand-side energy management control strategy for large residential districts based on an attention-driven multi-agent DRL approach

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Leveraging the machine learning techniques for demand-side flexibility – A comprehensive review

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Multi agent framework for consumer demand response in electricity market: Applications and recent advancement

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Artificial intelligence and machine learning for distributed energy resource management systems: Applications, frameworks, and future directions

Satpathy, P. R., & Ramachandaramurthy, V. K. (2025) · Applied Energy · doi:10.1016/j.apenergy.2025.127109 · Cited by 21

Demand Response Program Toward Sustainable Power Supply: Current Status, Challenges, and Prospects in Malaysia

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Multiagent Hierarchical Deep Reinforcement Learning for Operation Optimization of Grid-Interactive Efficient Commercial Buildings

Chen, Z., Yu, L., Zhang, S., Hu, S., & Shen, C. Q. (2024) · IEEE Transactions on Artificial Intelligence · doi:10.1109/tai.2024.3366869 · Cited by 13

Energy‐Sharing Economy with Renewable Integration and Management in Communities—a State‐of‐the‐Art Review

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Multi-layer double deep Q network for active distribution network equivalent modeling with internal identification for EV loads

Zheng, J., Wang, W. H., Li, Z., & Wu, Q. (2023) · Applied Soft Computing · doi:10.1016/j.asoc.2023.110834 · Cited by 12

Predicting and publishing accurate imbalance prices using Monte Carlo Tree Search

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Price-responsive control using deep reinforcement learning for heating systems: Simulation and living lab experiment

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Hydrogen-electricity coupling energy storage systems: Models, applications, and deep reinforcement learning algorithms

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A Distributed ADMM-Based Deep Learning Approach for Thermal Control in Multi-Zone Buildings Under Demand Response Events

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Towards Resilient Energy Infrastructures: A Comprehensive Review on the Role of Demand Response in Smart Grids

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Coordinated Operation Optimization of Grid-Interactive Residential Buildings Based on Neural Network-Assisted Hierarchical Model Predictive Control

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Residential demand response online optimization based on multi-agent deep reinforcement learning

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A Comprehensive Review of Building-to-Grid Interaction

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Exploration-enhanced multi-agent reinforcement learning for distributed PV-ESS scheduling with incomplete data

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Optimizing grid-interactive buildings demand response: Sequence-based decision-making multi-agent policy decomposition deep reinforcement learning

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Demand response with incomplete information: A systematic review

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A study on challenges and solutions in artificial intelligence-driven demand side optimization and security enhancement for smart grids

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Dynamic resource allocation in 5G networks using hybrid RL-CNN model for optimized latency and quality of service

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Survey on Demand Response in the Landscape of Adaptive and Intelligent Building Energy Management Systems

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Two-level deep reinforcement learning approach for energy management of integrated energy system considering deep peak shaving for combined heat and power and coordinated scheduling of electric vehicles

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Agentic AI Across Technologies, Applications, and Development Domains: A Systematic Literature Review

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Real-World Implementation of Reinforcement Learning Based Energy Coordination for a Cluster of Households

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Adaptive Decentralized Policies With Attention for Large-Scale Multiagent Environments

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Optimizing organic Rankine cycle systems: a hierarchical reinforcement learning approach to design and control

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Artificial Intelligence Applications in Smart Cities: Integrating Communication, Energy Management, Cybersecurity and Internet of Things

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Energy efficient hierarchical multi-agent graph transformer architecture for decentralized demand response and energy trading in blockchain-coordinated smart grids

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Deep Reinforcement Learning Based HVAC Optimization Control Algorithm Application

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Improving the learning process of deep reinforcement learning agents operating in collective heating environments

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From Simulation to Reality: A Study of Reinforcement Learning Control in Operational Building Environments

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Designing A WSNs-based Smart Home Monitoring System through Deep Reinforcement Learning

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Collaborative Encirclement of Multiple UAVs Based on Deep Reinforcement Learning

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Enhancing Grid Stability through Grid-Interactive Efficient Buildings with Deep Reinforcement Learning: Innovations and Challenges

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Networked Multi-Agent Deep Reinforcement Learning Framework for the Provision of Ancillary Services in Hybrid Power Plants

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Empowering sustainable energy systems with AI : Opportunities, challenges, and strategic solutions

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Optimization Strategies in Residential Energy Management Systems: A Comprehensive Review

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Achieving SDGs Using AI Techniques and Digital Twins for Nuclear Power Plants: A Review

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Demand Response in Building Microgrids with Variational Quantum Circuit Enabled Hybrid Control Strategy

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Hierarchical control strategy for heating systems using multi-agent deep reinforcement learning

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A Custom Reinforcement Learning Environment for Hybrid Renewable Energy Systems: Design and Implementation

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Actor-Critic Decision-Making in Wsns-Based Water Reservoir Monitoring SystemPreprint

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SAC-Based Distributed Optimal Control of Generation Cost in DC Microgrids

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Optimal Carbon Emission Reduction Modeling Considering Energy Consumer Satisfaction in Cyber-Physical Energy System

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Deep Reinforcement Learning for Scheduling of a Steel Plant in the Electricity Spot Market

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Artificial intelligence in electric cars connected to grid

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A Control-Centric Systematic Review of MARL for EV–Grid Coordination: From Predictive Input to Verifiable Feedback

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A Review Informed Translation Framework for Mapping Smart Building Services into Smart Readiness Indicator Aligned Assessment

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Decarbonizing livestock villages: Synergistic electricity-heat-fertilizer systems with demand response

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Artificial intelligence technologies for electric vehicle charging and hydrogen refueling systems: A transition of sustainable energy transportation

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Reinforcement Learning for Optimizing Renewable Energy Utilization in Smart Grids: Recent Advances in Power Grids, Microgrids, and Building Energy Systems

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Multi-agent Deep Reinforcement Learning for Energy Management in Grid-Responsive Networked Greenhouses

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Energy Scheduling and Control of Grid-Interactive Communities with Physically Consistent Deep Learning

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Implementing Aggregated Demand Response in Malaysia’s Commercial Sector

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Energy cost and emission optimization in food industry using deep reinforcement learning and Transformer-based load forecasting

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Pre-optimization-based deep reinforcement learning for autonomous economic and exergy management of stochastic H2/CO ratio syngas switching downstream processes

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