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Safe Reinforcement Learning-Based Resilient Proactive Scheduling for a Commercial Building Considering Correlated Demand Response

机译：考虑相关需求响应的商业建筑的基于安全强化学习的弹性主动调度

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Zheming Liang; Can Huang; Wencong Su; Nan Duan; Vaibhav Donde; Bin Wang; Xianbo Zhao;
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年度 2021
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1. The "Proactive" Model of Learning: Integrative Framework for Model-Free and Model-Based Reinforcement Learning Utilizing the Associative Learning-Based Proactive Brain Concept [J] . Zsuga Judit, Biro Klara, Papp Csaba, Behavioral neuroscience . 2016,第1期

机译：“主动”学习模型：利用基于联合学习的主动脑概念进行无模型和基于模型的强化学习的集成框架
2. Price-Based Residential Demand Response Management in Smart Grids: A Reinforcement Learning-Based Approach [J] . Yanni Wan, Jiahu Qin, Xinghuo Yu, 自动化学报（英文版） . 2022,第001期

机译：Price-Based Residential Demand Response Management in Smart Grids: A Reinforcement Learning-Based Approach
3. Price-Based Residential Demand Response Management in Smart Grids:A Reinforcement Learning-Based Approach [J] . Yanni Wan, Jiahu Qin, Xinghuo Yu, 自动化学报：英文版 . 2022,第001期

机译：Price-Based Residential Demand Response Management in Smart Grids:A Reinforcement Learning-Based Approach
4. ESS Optimal Scheduling considering Demand Response For commercial Buildings [C] . Yunsun Jin, Minsu Park, Dongjun Won International Youth Conference on Energy . 2019

机译：考虑商业建筑需求响应的ESS最优调度
5. The Role of Commercial Buildings in China's Renewable Electricity Future: Forecasting Load and Demand Response Potential [D] . Sifuentes, Froylan Emilfer. 2018

机译：商业建筑在中国可再生电力未来中的作用：预测负荷和需求响应潜力
6. Deep Reinforcement Learning-Based Task Scheduling in IoT Edge Computing [O] . Shuran Sheng, Peng Chen, Zhimin Chen, 2021

机译：基于深度加强学习的IOT Edge Computing任务调度
7. Exploring the Potentialities of Deep Reinforcement Learning for Incentive-Based Demand Response in a Cluster of Small Commercial Buildings [O] . Davide Deltetto, Davide Coraci, Giuseppe Pinto, 2021

机译：探索小型商业建筑集群中激励基于激励的需求响应的深增强学习潜力

Safe Reinforcement Learning-Based Resilient Proactive Scheduling for a Commercial Building Considering Correlated Demand Response

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