Review and prospect of data-driven techniques for load forecasting in integrated energy systems
With synergies among multiple energy sectors, integrated energy systems (IESs) have been
recognized lately as an effective approach to accommodate large-scale renewables and …
recognized lately as an effective approach to accommodate large-scale renewables and …
Voltage regulation in distribution grids: A survey
Environmental and sustainability concerns have caused a recent surge in the penetration of
distributed energy resources into the power grid. This may lead to voltage violations in the …
distributed energy resources into the power grid. This may lead to voltage violations in the …
Residential energy consumption forecasting using deep learning models
The energy sector plays an important role in socioeconomic and environmental
development. Accurately forecasting energy demand across various time horizons can yield …
development. Accurately forecasting energy demand across various time horizons can yield …
[HTML][HTML] Short-term electricity load forecasting—A systematic approach from system level to secondary substations
MG Pinheiro, SC Madeira, AP Francisco - Applied Energy, 2023 - Elsevier
Energy forecasting covers a wide range of prediction problems in the utility industry, such as
forecasting demand, generation, price, and power load over time horizons and different …
forecasting demand, generation, price, and power load over time horizons and different …
Short-term power load forecasting system based on rough set, information granule and multi-objective optimization
J Wang, K Wang, Z Li, H Lu, H Jiang - Applied Soft Computing, 2023 - Elsevier
Accurately forecasting power load is essential for utilities to effectively manage their
resources, reduce operational costs, and provide improved customer service. However, the …
resources, reduce operational costs, and provide improved customer service. However, the …
Ten questions concerning data-driven modelling and forecasting of operational energy demand at building and urban scale
Buildings account for over a third of end energy demand in many countries worldwide.
Modelling this demand accurately marks the first step in producing forecasts that can help …
Modelling this demand accurately marks the first step in producing forecasts that can help …
[HTML][HTML] Short-term electric net load forecasting for solar-integrated distribution systems based on Bayesian neural networks and statistical post-processing
The increasing integration of variable renewable technologies at distribution feeders, mainly
solar photovoltaic (PV) systems, presents new challenges to grid operators for accurately …
solar photovoltaic (PV) systems, presents new challenges to grid operators for accurately …
[HTML][HTML] Total and thermal load forecasting in residential communities through probabilistic methods and causal machine learning
L Massidda, M Marrocu - Applied Energy, 2023 - Elsevier
Indoor heating and cooling systems largely influence the power demand of residential
buildings and can play a significant role in the Demand Side Management for energy …
buildings and can play a significant role in the Demand Side Management for energy …
A residential labeled dataset for smart meter data analytics
Smart meter data is a cornerstone for the realization of next-generation electrical power
grids by enabling the creation of novel energy data-based services like providing …
grids by enabling the creation of novel energy data-based services like providing …
Harmonic and supraharmonic emissions of plug-in electric vehicle chargers
A Mariscotti - Smart Cities, 2022 - mdpi.com
Electric vehicle (EV) charging represents a relevant electric load with a rapid evolution in
terms of number, power rating and distortion, in particular, considering the connection to the …
terms of number, power rating and distortion, in particular, considering the connection to the …