The mediation effect of land surface temperature in the relationship between land use-cover change and energy consumption under seasonal variations

P Wang, P Yu, J Lu, Y Zhang - Journal of Cleaner Production, 2022 - Elsevier
Increasing temperatures in urban areas have brought about a series of prevalent
environmental and energy shortage problems. Many studies have focused on the …

A variance inflation factor and backward elimination based robust regression model for forecasting monthly electricity demand using climatic variables

DH Vu, KM Muttaqi, AP Agalgaonkar - Applied Energy, 2015 - Elsevier
Selection of appropriate climatic variables for prediction of electricity demand is critical as it
affects the accuracy of the prediction. Different climatic variables may have different impacts …

Short-term load-forecasting method based on wavelet decomposition with second-order gray neural network model combined with ADF test

B Li, J Zhang, Y He, Y Wang - IEEE Access, 2017 - ieeexplore.ieee.org
Improving the accuracy of power system load forecasting is important for economic dispatch.
However, a load sequence is highly nonstationary and hence makes accurate forecasting …

A multiple time series-based recurrent neural network for short-term load forecasting

B Zhang, JL Wu, PC Chang - Soft Computing, 2018 - Springer
Electricity, an indispensable resource in daily life and industrial production, is hard to store,
so accurate short-term load forecasting (STLF) plays a vital role in resource allocation …

A two-stage multistep-ahead electricity load forecasting scheme based on LightGBM and attention-BiLSTM

J Park, E Hwang - Sensors, 2021 - mdpi.com
An efficient energy operation strategy for the smart grid requires accurate day-ahead
electricity load forecasts with high time resolutions, such as 15 or 30 min. Most high-time …

Short-term electric load forecasting in Tunisia using artificial neural networks

R Houimli, M Zmami, O Ben-Salha - energy Systems, 2020 - Springer
The accuracy of short-term electricity load forecasting is of great interest since it allows
avoiding unexpected blackouts and lowering operating costs. In this paper, we aim to …

Short-term load forecasting using regression based moving windows with adjustable window-sizes

DH Vu, KM Muttaqi… - 2014 IEEE Industry …, 2014 - ieeexplore.ieee.org
This paper presents a regression based moving window model for solving the short-term
electricity forecasting problem. Moving window approach is employed to trace the demand …

Curve fitting and regression line method based seasonal short term load forecasting

MB Jain, MK Nigam, PC Tiwari - 2012 World Congress on …, 2012 - ieeexplore.ieee.org
Short term load forecasting in this paper is done by considering the sensitivity of the network
load to the temperature, humidity, day type parameters (THD) and previous load and also …

Bootstrap aggregating approach to short-term load forecasting using meteorological parameters for demand side management in the North-Eastern Region of India

D Sarkar, T Ao, SK Gunturi - Theoretical and Applied Climatology, 2022 - Springer
Electricity is an essential commodity that must be generated in response to demand.
Hydroelectric power plants, fossil fuels, nuclear energy, and wind energy are just a few …

Development of Brazilian multi region short-term load forecasting model considering climate variables weighting in ANN model

LN Silva, AR Abaide, IC Figueiró… - 2017 52nd …, 2017 - ieeexplore.ieee.org
The short-term load forecasting study is characterized as an estimative of the consumption
pattern ranging from a day to a few months ahead, related to the operation planning, mainly …