Related references
Note: Only part of the references are listed.Short-term Solar Power Prediction Learning Directly from Satellite Images With Regions of Interest
Lilin Cheng et al.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY (2022)
Day-Ahead Optimal Economic Dispatching of Integrated Port Energy Systems Considering Hydrogen
Xiaobo Wang et al.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS (2022)
Residential load forecasting based on LSTM fusing self-attention mechanism with pooling
Haixiang Zang et al.
ENERGY (2021)
AlphaBuilding ResCommunity: A multi-agent virtual testbed for community-level load coordination
Zhe Wang et al.
ADVANCES IN APPLIED ENERGY (2021)
Deep Reinforcement Learning for Smart Home Energy Management
Liang Yu et al.
IEEE INTERNET OF THINGS JOURNAL (2020)
Differential Dynamic Programming Based Home Energy Management Scheduler
Babak Jeddi et al.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY (2020)
Real-Time Residential Demand Response
Hepeng Li et al.
IEEE TRANSACTIONS ON SMART GRID (2020)
Short-term global horizontal irradiance forecasting based on a hybrid CNN-LSTM model with spatiotemporal correlations
Haixiang Zang et al.
RENEWABLE ENERGY (2020)
Real-Time Scheduling of Operational Time for Smart Home Appliances Based on Reinforcement Learning
Murad Khan et al.
IEEE ACCESS (2020)
Online Energy Management for a Sustainable Smart Home With an HVAC Load and Random Occupancy
Liang Yu et al.
IEEE TRANSACTIONS ON SMART GRID (2019)
On-Line Building Energy Optimization Using Deep Reinforcement Learning
Elena Mocanu et al.
IEEE TRANSACTIONS ON SMART GRID (2019)
Reinforcement learning for demand response: A review of algorithms and modeling techniques
Jose R. Vazquez-Canteli et al.
APPLIED ENERGY (2019)
Energy optimization associated with thermal comfort and indoor air control via a deep reinforcement learning algorithm
William Valladares et al.
BUILDING AND ENVIRONMENT (2019)
Model-Free Real-Time EV Charging Scheduling Based on Deep Reinforcement Learning
Zhiqiang Wan et al.
IEEE TRANSACTIONS ON SMART GRID (2019)
Real-Time Scheduling of Demand Response Options Considering the Volatility of Wind Power Generation
Saber Talari et al.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY (2019)
A Real-Time Electricity Scheduling for Residential Home Energy Management
Shenglin Li et al.
IEEE INTERNET OF THINGS JOURNAL (2019)
Demand Response for Home Energy Management Using Reinforcement Learning and Artificial Neural Network
Renzhi Lu et al.
IEEE TRANSACTIONS ON SMART GRID (2019)
A Dynamic pricing demand response algorithm for smart grid: Reinforcement learning approach
Renzhi Lu et al.
APPLIED ENERGY (2018)
Chance Constrained Optimization in a Home Energy Management System
Yantai Huang et al.
IEEE TRANSACTIONS ON SMART GRID (2018)
Convolutional Neural Networks for Automatic State-Time Feature Extraction in Reinforcement Learning Applied to Residential Load Control
Bert J. Claessens et al.
IEEE TRANSACTIONS ON SMART GRID (2018)
Energy Management Strategy for a Hybrid Electric Vehicle Based on Deep Reinforcement Learning
Yue Hu et al.
APPLIED SCIENCES-BASEL (2018)
Efficient energy management for a grid-tied residential microgrid
Amjad Anvari-Moghaddam et al.
IET GENERATION TRANSMISSION & DISTRIBUTION (2017)
Residential Demand Response of Thermostatically Controlled Loads Using Batch Reinforcement Learning
Frederik Ruelens et al.
IEEE TRANSACTIONS ON SMART GRID (2017)
Efficient Computation for Sparse Load Shifting in Demand Side Management
Chaojie Li et al.
IEEE TRANSACTIONS ON SMART GRID (2017)
A multi-agent based energy management solution for integrated buildings and microgrid system
Amjad Anvari-Moghaddam et al.
APPLIED ENERGY (2017)
User satisfaction-induced demand side load management in residential buildings with user budget constraint
A. S. O. Ogunjuyigbe et al.
APPLIED ENERGY (2017)
A real-time evaluation of energy management systems for smart hybrid home Microgrids
Mousa Marzband et al.
ELECTRIC POWER SYSTEMS RESEARCH (2017)
Smart home energy management systems: Concept, configurations, and scheduling strategies
Bin Zhou et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2016)
An Optimal and Learning-Based Demand Response and Home Energy Management System
Dong Zhang et al.
IEEE TRANSACTIONS ON SMART GRID (2016)
Cost-effective and comfort-aware residential energy management under different pricing schemes and weather conditions
Amjad Anvari-Moghaddam et al.
ENERGY AND BUILDINGS (2015)
Optimal Household Appliances Scheduling Under Day-Ahead Pricing and Load-Shaping Demand Response Strategies
Nikolaos G. Paterakis et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2015)
Automated Demand Response From Home Energy Management System Under Dynamic Pricing and Power and Comfort Constraints
Sereen Althaher et al.
IEEE TRANSACTIONS ON SMART GRID (2015)
Optimal Smart Home Energy Management Considering Energy Saving and a Comfortable Lifestyle
Amjad Anvari-Moghaddam et al.
IEEE TRANSACTIONS ON SMART GRID (2015)
Optimal Demand Response Using Device-Based Reinforcement Learning
Zheng Wen et al.
IEEE TRANSACTIONS ON SMART GRID (2015)
Demand response for residential buildings based on dynamic price of electricity
Ji Hoon Yoon et al.
ENERGY AND BUILDINGS (2014)