Industry 4.0 and demand forecasting of the energy supply chain: A literature review
The number of publications in demand forecasting of the energy supply chain augmented
meaningfully due to the 2008 global financial crisis and its consequence on the global …
meaningfully due to the 2008 global financial crisis and its consequence on the global …
Energy demand forecasting in China: A support vector regression-compositional data second exponential smoothing model
C Rao, Y Zhang, J Wen, X **ao, M Goh - Energy, 2023 - Elsevier
Analyzing the drivers of energy demand and predicting energy consumption can help to
shape national policies on energy transformation and energy security. This paper estimates …
shape national policies on energy transformation and energy security. This paper estimates …
Deep clustering of Lagrangian trajectory for multi-task learning to energy saving in intelligent buildings using cooperative multi-agent
The intelligent buildings provided various incentives to get highly inefficient energy-saving
caused by the non-stationary building environments. In the presence of such dynamic …
caused by the non-stationary building environments. In the presence of such dynamic …
Effect of different building envelope materials on thermal comfort and air-conditioning energy savings: A case study in Basra city, Iraq
RZ Homod, A Almusaed, A Almssad, MK Jaafar… - Journal of Energy …, 2021 - Elsevier
Recently, a numerous number of houses has been built using AAC materials, which
consume the most amount of energy in the building sector by Heating, ventilation, and air …
consume the most amount of energy in the building sector by Heating, ventilation, and air …
A review of energy consumption forecasting in smart buildings: Methods, input variables, forecasting horizon and metrics
Buildings are among the largest energy consumers in the world. As new technologies have
been developed, great advances have been made in buildings, turning conventional …
been developed, great advances have been made in buildings, turning conventional …
Hybrid ensemble intelligent model based on wavelet transform, swarm intelligence and artificial neural network for electricity demand forecasting
Availability of electrical energy affects many facets of an entire economy of a country. This
has made short-term electrical load forecasting an important area in recent years for policy …
has made short-term electrical load forecasting an important area in recent years for policy …
Fuzzy compromised solution-based novel home appliances scheduling and demand response with optimal dispatch of distributed energy resources
Due to environmental issues and smart grid development, distributed energy resources,
energy storage systems, and demand response (DR) are gaining attention to reduce the …
energy storage systems, and demand response (DR) are gaining attention to reduce the …
Household-level energy forecasting in smart buildings using a novel hybrid deep learning model
Forecasting of energy consumption in Smart Buildings (SB) and using the extracted
information to plan and operate power generation are crucial elements of the Smart Grid …
information to plan and operate power generation are crucial elements of the Smart Grid …
Comparative study of machine learning-based multi-objective prediction framework for multiple building energy loads
Buildings are one of the significant sources of energy consumption and greenhouse gas
emission in urban areas all over the world. Lighting control and building integrated …
emission in urban areas all over the world. Lighting control and building integrated …
Short-term load forecasting of multi-energy in integrated energy system based on multivariate phase space reconstruction and support vector regression mode
In order to alleviate the energy crisis and improve the energy utilization rate, the integrated
energy system (IES) has become an important way of energy utilization. IES integrates …
energy system (IES) has become an important way of energy utilization. IES integrates …