Computational intelligence on short-term load forecasting: A methodological overview
Electricity demand forecasting has been a real challenge for power system scheduling in
different levels of energy sectors. Various computational intelligence techniques and …
different levels of energy sectors. Various computational intelligence techniques and …
Residential load forecasting based on LSTM fusing self-attention mechanism with pooling
Day-ahead residential load forecasting is crucial for electricity dispatch and demand
response in power systems. Electrical loads are characterized by volatility and uncertainty …
response in power systems. Electrical loads are characterized by volatility and uncertainty …
Artificial intelligence and statistical techniques in short-term load forecasting: a review
Electrical utilities depend on short-term demand forecasting to proactively adjust production
and distribution in anticipation of major variations. This systematic review analyzes 240 …
and distribution in anticipation of major variations. This systematic review analyzes 240 …
Short-term load forecasting for microgrid energy management system using hybrid SPM-LSTM
Load forecasting in power microgrids and load management systems is still a challenge and
needs an accurate method. Although in recent years, short-term load forecasting is done by …
needs an accurate method. Although in recent years, short-term load forecasting is done by …
Smart energy management algorithm for load smoothing and peak shaving based on load forecasting of an island's power system
In this study, a novel algorithm for the management of the power flows of an islanded power
system was developed, capable of simultaneously achieving steadier conventional unit …
system was developed, capable of simultaneously achieving steadier conventional unit …
Hybrid short-term load forecasting using CGAN with CNN and semi-supervised regression
Accurate short-term load forecasting (STLF) is essential to improve secure and economic
operation of power systems. In this paper, a hybrid STLF model using the conditional …
operation of power systems. In this paper, a hybrid STLF model using the conditional …
A combined model based on multiple seasonal patterns and modified firefly algorithm for electrical load forecasting
L Xiao, W Shao, T Liang, C Wang - Applied energy, 2016 - Elsevier
Short-term load forecasting (STLF) plays an irreplaceable role in the efficient management
of electric systems. Particularly in the electricity market and industry, accurate forecasting …
of electric systems. Particularly in the electricity market and industry, accurate forecasting …
BP neural network with rough set for short term load forecasting
Z Xiao, SJ Ye, B Zhong, CX Sun - Expert Systems with Applications, 2009 - Elsevier
Precise Short term load forecasting (STLF) plays a significant role in the management of
power system of countries and regions on the grounds of insufficient electric energy for …
power system of countries and regions on the grounds of insufficient electric energy for …
Short-term forecasting of electric loads using nonlinear autoregressive artificial neural networks with exogenous vector inputs
J Buitrago, S Asfour - Energies, 2017 - mdpi.com
Short-term load forecasting is crucial for the operations planning of an electrical grid.
Forecasting the next 24 h of electrical load in a grid allows operators to plan and optimize …
Forecasting the next 24 h of electrical load in a grid allows operators to plan and optimize …
A combined model based on data pre-analysis and weight coefficients optimization for electrical load forecasting
L Xiao, J Wang, R Hou, J Wu - Energy, 2015 - Elsevier
Electrical load forecasting has always played a key role in power system administration,
planning for energy transfer scheduling and load dispatch. For electrical load forecasting …
planning for energy transfer scheduling and load dispatch. For electrical load forecasting …