[HTML][HTML] Artificial intelligence and machine learning approaches to energy demand-side response: A systematic review
Recent years have seen an increasing interest in Demand Response (DR) as a means to
provide flexibility, and hence improve the reliability of energy systems in a cost-effective way …
provide flexibility, and hence improve the reliability of energy systems in a cost-effective way …
[HTML][HTML] Blockchain-based management of demand response in electric energy grids: A systematic review
The complexities associated with modern energy grids, including high penetration levels of
renewable energy sources at the end use customers, the proliferation of electric vehicles …
renewable energy sources at the end use customers, the proliferation of electric vehicles …
Demand response for home energy management using reinforcement learning and artificial neural network
Ever-changing variables in the electricity market require energy management systems
(EMSs) to make optimal real-time decisions adaptively. Demand response (DR) is the latest …
(EMSs) to make optimal real-time decisions adaptively. Demand response (DR) is the latest …
Smart households' aggregated capacity forecasting for load aggregators under incentive-based demand response programs
The technological advancement in the communication and control infrastructure helps those
smart households (SHs) that more actively participate in the incentive-based demand …
smart households (SHs) that more actively participate in the incentive-based demand …
A stochastic home energy management system considering satisfaction cost and response fatigue
M Shafie-Khah, P Siano - IEEE Transactions on Industrial …, 2017 - ieeexplore.ieee.org
Home energy management (HEM) systems enable residential consumers to participate in
demand response programs (DRPs) more actively. However, HEM systems confront some …
demand response programs (DRPs) more actively. However, HEM systems confront some …
Artificial intelligence enabled demand response: Prospects and challenges in smart grid environment
Demand Response (DR) has gained popularity in recent years as a practical strategy to
increase the sustainability of energy systems while reducing associated costs. Despite this …
increase the sustainability of energy systems while reducing associated costs. Despite this …
Optimal integration of a hybrid solar-battery power source into smart home nanogrid with plug-in electric vehicle
X Wu, X Hu, Y Teng, S Qian, R Cheng - Journal of power sources, 2017 - Elsevier
Hybrid solar-battery power source is essential in the nexus of plug-in electric vehicle (PEV),
renewables, and smart building. This paper devises an optimization framework for efficient …
renewables, and smart building. This paper devises an optimization framework for efficient …
Residential demand response strategies and applications in active distribution network management
Electricity distribution is moving towards active, more flexible, smarter and decentralized
energy systems. This transition requires System Operators (SO) to dynamically monitor and …
energy systems. This transition requires System Operators (SO) to dynamically monitor and …
Time-varying price elasticity of demand estimation for demand-side smart dynamic pricing
The rapid development of the smart energy system promotes bidirectional communications
between the supply-side and demand-side. End users can handily receive real-time prices …
between the supply-side and demand-side. End users can handily receive real-time prices …
Stochastic optimization of home energy management system using clustered quantile scenario reduction
Recent proliferation of renewable energy has increased the installation of residential energy
sources (eg, roof-top photovoltaic (PV) panel and residential wind turbine) in households. To …
sources (eg, roof-top photovoltaic (PV) panel and residential wind turbine) in households. To …