Artificial intelligence techniques in smart grid: A survey
The smart grid is enabling the collection of massive amounts of high-dimensional and multi-
type data about the electric power grid operations, by integrating advanced metering …
type data about the electric power grid operations, by integrating advanced metering …
Integrating artificial intelligence Internet of Things and 5G for next-generation smartgrid: A survey of trends challenges and prospect
Smartgrid is a paradigm that was introduced into the conventional electricity network to
enhance the way generation, transmission, and distribution networks interrelate. It involves …
enhance the way generation, transmission, and distribution networks interrelate. It involves …
[HTML][HTML] Comprehensive review of load forecasting with emphasis on intelligent computing approaches
In this paper, a comprehensive review is presented for mid-term load forecasting. The basic
loads and effective factors are studied, and then several classifications are presented for …
loads and effective factors are studied, and then several classifications are presented for …
Performance evaluation of LSTM and Bi-LSTM using non-convolutional features for blockage detection in centrifugal pump
Blockages in the suction or discharge side of the pump adversely affect the pump's
performance by reducing the flow rate and head, increasing vibration, noise, and …
performance by reducing the flow rate and head, increasing vibration, noise, and …
A CNN-Assisted deep echo state network using multiple Time-Scale dynamic learning reservoirs for generating Short-Term solar energy forecasting
M Ishaq, S Kwon - Sustainable energy technologies and assessments, 2022 - Elsevier
The integration of renewable energy generation presented an important development
around the globe and conveys countless financial, commercial, and environmental …
around the globe and conveys countless financial, commercial, and environmental …
Time-series based prediction for energy consumption of smart home data using hybrid convolution-recurrent neural network
N Bhoj, RS Bhadoria - Telematics and Informatics, 2022 - Elsevier
The rapid increase in technological development has led to the rise in usage of IoT devices
for monitoring Electrical Energy Consumption. As countries around the world are committing …
for monitoring Electrical Energy Consumption. As countries around the world are committing …
A novel attLSTM framework combining the attention mechanism and bidirectional LSTM for demand forecasting
L Cui, Y Chen, J Deng, Z Han - Expert Systems with Applications, 2024 - Elsevier
Demand forecasting has become the most crucial part for supporting supply chain decisions.
However, accurate forecasting in time series demand forecasting, particularly within supply …
However, accurate forecasting in time series demand forecasting, particularly within supply …
A robust approach for industrial small-object detection using an improved faster regional convolutional neural network
With the increasing pace in the industrial sector, the need for a smart environment is also
increasing and the production of industrial products in terms of quality always matters. There …
increasing and the production of industrial products in terms of quality always matters. There …
[HTML][HTML] A multivariate time series analysis of electrical load forecasting based on a hybrid feature selection approach and explainable deep learning
F Yaprakdal, M Varol Arısoy - Applied Sciences, 2023 - mdpi.com
In the smart grid paradigm, precise electrical load forecasting (ELF) offers significant
advantages for enhancing grid reliability and informing energy planning decisions …
advantages for enhancing grid reliability and informing energy planning decisions …
Soil seismic response modeling of KiK-net downhole array sites with CNN and LSTM networks
Accurate prediction of soil seismic response is necessary for geotechnical engineering. The
conventional physics-based models such as the finite element method (FEM) usually fail to …
conventional physics-based models such as the finite element method (FEM) usually fail to …