Tackling climate change with machine learning
Climate change is one of the greatest challenges facing humanity, and we, as machine
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …
A review of deep learning with special emphasis on architectures, applications and recent trends
Deep learning (DL) has solved a problem that a few years ago was thought to be intractable—
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
Deep learning framework to forecast electricity demand
J Bedi, D Toshniwal - Applied energy, 2019 - Elsevier
The increasing world population and availability of energy hungry smart devices are major
reasons for alarmingly high electricity consumption in the current times. So far, various …
reasons for alarmingly high electricity consumption in the current times. So far, various …
Probabilistic electric load forecasting: A tutorial review
T Hong, S Fan - International Journal of Forecasting, 2016 - Elsevier
Load forecasting has been a fundamental business problem since the inception of the
electric power industry. Over the past 100 plus years, both research efforts and industry …
electric power industry. Over the past 100 plus years, both research efforts and industry …
A review and analysis of regression and machine learning models on commercial building electricity load forecasting
Electricity load forecasting is an important tool which can be utilized to enable effective
control of commercial building electricity loads. Accurate forecasts of commercial building …
control of commercial building electricity loads. Accurate forecasts of commercial building …
On recent advances in PV output power forecast
In last decade, the higher penetration of renewable energy resources (RES) in energy
market was encouraged by implementing the energy polices in several developed and …
market was encouraged by implementing the energy polices in several developed and …
On heat pumps in smart grids: A review
This paper investigates heat pump systems in smart grids, focussing on fields of application
and control approaches that have emerged in academic literature. Based on a review of …
and control approaches that have emerged in academic literature. Based on a review of …
Stochastic control of smart home energy management with plug-in electric vehicle battery energy storage and photovoltaic array
Energy management strategies are instrumental in the performance and economy of smart
homes integrating renewable energy and energy storage. This article focuses on stochastic …
homes integrating renewable energy and energy storage. This article focuses on stochastic …
[PDF][PDF] Methods and models for electric load forecasting: a comprehensive review
Electric load forecasting (ELF) is a vital process in the planning of the electricity industry and
plays a crucial role in electric capacity scheduling and power systems management and …
plays a crucial role in electric capacity scheduling and power systems management and …
[HTML][HTML] Privacy-preserving federated learning for residential short-term load forecasting
With high levels of intermittent power generation and dynamic demand patterns, accurate
forecasts for residential loads have become essential. Smart meters can play an important …
forecasts for residential loads have become essential. Smart meters can play an important …