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AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives
In theory, building automation and management systems (BAMSs) can provide all the
components and functionalities required for analyzing and operating buildings. However, in …
components and functionalities required for analyzing and operating buildings. However, in …
Load forecasting techniques and their applications in smart grids
The growing success of smart grids (SGs) is driving increased interest in load forecasting
(LF) as accurate predictions of energy demand are crucial for ensuring the reliability …
(LF) as accurate predictions of energy demand are crucial for ensuring the reliability …
A short-term load forecasting method using integrated CNN and LSTM network
In this study, a new technique is proposed to forecast short-term electrical load. Load
forecasting is an integral part of power system planning and operation. Precise forecasting …
forecasting is an integral part of power system planning and operation. Precise forecasting …
Load forecasting models in smart grid using smart meter information: a review
The smart grid concept is introduced to accelerate the operational efficiency and enhance
the reliability and sustainability of power supply by operating in self-control mode to find and …
the reliability and sustainability of power supply by operating in self-control mode to find and …
Smart City Data Science: Towards data-driven smart cities with open research issues
IH Sarker - Internet of Things, 2022 - Elsevier
Cities are undergoing huge shifts in technology and operations in recent days, and 'data
science'is driving the change in the current age of the Fourth Industrial Revolution (Industry …
science'is driving the change in the current age of the Fourth Industrial Revolution (Industry …
Short-term wind power forecasting model based on temporal convolutional network and Informer
M Gong, C Yan, W Xu, Z Zhao, W Li, Y Liu, S Li - Energy, 2023 - Elsevier
Wind power forecast remains challenging owing to the unpredictable peculiarity of wind. The
accuracy of wind power predictions is critical to the stability of the whole system. This …
accuracy of wind power predictions is critical to the stability of the whole system. This …
A novel sequence to sequence data modelling based CNN-LSTM algorithm for three years ahead monthly peak load forecasting
Long-term load forecasting (LTLF) models play an important role in the strategic planning of
power systems around the globe. Obtaining correct decisions on power network expansions …
power systems around the globe. Obtaining correct decisions on power network expansions …
Short-term load forecasting models: A review of challenges, progress, and the road ahead
Short-term load forecasting (STLF) is critical for the energy industry. Accurate predictions of
future electricity demand are necessary to ensure power systems' reliable and efficient …
future electricity demand are necessary to ensure power systems' reliable and efficient …
Predicting household electric power consumption using multi-step time series with convolutional LSTM
Energy consumption prediction has become an integral part of a smart and sustainable
environment. With future demand forecasts, energy production and distribution can be …
environment. With future demand forecasts, energy production and distribution can be …
[HTML][HTML] Machine learning for short-term load forecasting in smart grids
A smart grid is the future vision of power systems that will be enabled by artificial intelligence
(AI), big data, and the Internet of things (IoT), where digitalization is at the core of the energy …
(AI), big data, and the Internet of things (IoT), where digitalization is at the core of the energy …