Dynamic energy dispatch strategy for integrated energy system based on improved deep reinforcement learning
出版年份 2021 全文链接
标题
Dynamic energy dispatch strategy for integrated energy system based on improved deep reinforcement learning
作者
关键词
Dynamic energy dispatch, Integrated energy system, Deep reinforcement learning, Improved deep deterministic policy gradient, Uncertainties
出版物
ENERGY
Volume 235, Issue -, Pages 121377
出版商
Elsevier BV
发表日期
2021-07-02
DOI
10.1016/j.energy.2021.121377
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- Reinforcement learning in sustainable energy and electric systems: a survey
- (2020) Ting Yang et al. ANNUAL REVIEWS IN CONTROL
- Evaluating the impact of multi-carrier energy storage systems in optimal operation of integrated electricity, gas and district heating networks
- (2020) Mohammad Amin Mirzaei et al. APPLIED THERMAL ENGINEERING
- Operational optimization of wastewater reuse integrated energy system
- (2020) Yongli Wang et al. ENERGY
- Modified deep learning and reinforcement learning for an incentive-based demand response model
- (2020) Lulu Wen et al. ENERGY
- A hybrid short-term load forecasting model based on variational mode decomposition and long short-term memory networks considering relevant factors with Bayesian optimization algorithm
- (2019) Feifei He et al. APPLIED ENERGY
- A new quantitative life cycle sustainability assessment framework: Application to integrated energy systems
- (2019) Salim Moslehi et al. APPLIED ENERGY
- Investigating structural and occupant drivers of annual residential electricity consumption using regularization in regression models
- (2019) Aven Satre-Meloy ENERGY
- Generic modelling and optimal day-ahead dispatch of micro-energy system considering the price-based integrated demand response
- (2019) Zexing Chen et al. ENERGY
- Stochastic optimization of cost-risk for integrated energy system considering wind and solar power correlated
- (2019) Jiehui ZHENG et al. Journal of Modern Power Systems and Clean Energy
- Real-Time Energy Management of a Microgrid Using Deep Reinforcement Learning
- (2019) Ying Ji et al. Energies
- Optimal charging of Electric Vehicles in residential area
- (2019) Soumia Ayyadi et al. Sustainable Energy Grids & Networks
- A robust optimization approach for optimal load dispatch of community energy hub
- (2019) Xinhui Lu et al. APPLIED ENERGY
- Adaptive robust energy and reserve co-optimization of integrated electricity and heating system considering wind uncertainty
- (2019) Jin Tan et al. APPLIED ENERGY
- Integrated energy systems planning with electricity, heat and gas using particle swarm optimization
- (2019) Chao Qin et al. ENERGY
- Sizing of district heating systems based on smart meter data: Quantifying the aggregated domestic energy demand and demand diversity in the UK
- (2019) Zhikun Wang et al. ENERGY
- Deep Reinforcement Learning for Smart Home Energy Management
- (2019) Liang Yu et al. IEEE Internet of Things Journal
- Reinforcement learning-based real-time power management for hybrid energy storage system in the plug-in hybrid electric vehicle
- (2018) Rui Xiong et al. APPLIED ENERGY
- Reinforcement Learning Approach for Optimal Distributed Energy Management in a Microgrid
- (2018) Elham Foruzan et al. IEEE TRANSACTIONS ON POWER SYSTEMS
- Distributed Real-Time Energy Management in Data Center Microgrids
- (2018) Liang Yu et al. IEEE Transactions on Smart Grid
- Modeling and optimal operation of community integrated energy systems: A case study from China
- (2018) Chengshan Wang et al. APPLIED ENERGY
- Cost optimal scenarios of a future highly renewable European electricity system: Exploring the influence of weather data, cost parameters and policy constraints
- (2018) D.P. Schlachtberger et al. ENERGY
- Integrated Optimal Dispatch of a Rural Micro-Energy-Grid with Multi-Energy Stream Based on Model Predictive Control
- (2018) Xin Zhang et al. Energies
- Explore a deep learning multi-output neural network for regional multi-step-ahead air quality forecasts
- (2018) Yanlai Zhou et al. JOURNAL OF CLEANER PRODUCTION
- Optimal robust operation of combined heat and power systems with demand response programs
- (2018) Majid Majidi et al. APPLIED THERMAL ENGINEERING
- Model-Free Real-Time EV Charging Scheduling Based on Deep Reinforcement Learning
- (2018) Zhiqiang Wan et al. IEEE Transactions on Smart Grid
- Limitations in Energy Management Systems: A Case Study for Resilient Interconnected Microgrids
- (2018) Leong Kit Gan et al. IEEE Transactions on Smart Grid
- Development of an optimization based design framework for microgrid energy systems
- (2017) Tao Cao et al. ENERGY
- Integrated scheduling of energy supply and demand in microgrids under uncertainty: A robust multi-objective optimization approach
- (2017) Luhao Wang et al. ENERGY
- An Online Optimal Dispatch Schedule for CCHP Microgrids Based on Model Predictive Control
- (2017) Wei Gu et al. IEEE Transactions on Smart Grid
- A robust optimization method for energy management of CCHP microgrid
- (2017) Zhao LUO et al. Journal of Modern Power Systems and Clean Energy
- High-resolution stochastic integrated thermal–electrical domestic demand model
- (2016) Eoghan McKenna et al. APPLIED ENERGY
- Human-level control through deep reinforcement learning
- (2015) Volodymyr Mnih et al. NATURE
- Reinforcement learning for microgrid energy management
- (2013) Elizaveta Kuznetsova et al. ENERGY
- Uncertainties in the design and operation of distributed energy resources: The case of micro-CHP systems
- (2008) Michiel Houwing et al. ENERGY
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