[PDF][PDF] Methods and models for electric load forecasting: a comprehensive review

MA Hammad, B Jereb, B Rosi… - Logist. Sustain …, 2020 - intapi.sciendo.com
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 …

Data analytics in the supply chain management: Review of machine learning applications in demand forecasting

A Aamer, LP Eka Yani… - Operations and Supply …, 2020 - journal.oscm-forum.org
In today's fast-paced global economy coupled with the availability of mobile internet and
social networks, several business models have been disrupted. This disruption brings a …

Applications of random forest in multivariable response surface for short-term load forecasting

GF Fan, LZ Zhang, M Yu, WC Hong, SQ Dong - International Journal of …, 2022 - Elsevier
Accurate load forecasting is helpful for optimizing the use of power resources. To this end,
this investigation proposes a hybrid model for short-term load forecasting, namely the RF …

Electrical load forecasting using LSTM, GRU, and RNN algorithms

M Abumohsen, AY Owda, M Owda - Energies, 2023 - mdpi.com
Forecasting the electrical load is essential in power system design and growth. It is critical
from both a technical and a financial standpoint as it improves the power system …

Long short-term memory network-based metaheuristic for effective electric energy consumption prediction

SK Hora, R Poongodan, RP De Prado, M Wozniak… - Applied Sciences, 2021 - mdpi.com
The Electric Energy Consumption Prediction (EECP) is a complex and important process in
an intelligent energy management system and its importance has been increasing rapidly …

Efficient bootstrap stacking ensemble learning model applied to wind power generation forecasting

MHDM Ribeiro, RG da Silva, SR Moreno… - International Journal of …, 2022 - Elsevier
The use of wind energy plays a vital role in society owing to its economic and environmental
importance. Knowing the wind power generation within a specific time window is useful for …

Short-term electricity price and load forecasting in isolated power grids based on composite neural network and gravitational search optimization algorithm

A Heydari, MM Nezhad, E Pirshayan, DA Garcia… - Applied Energy, 2020 - Elsevier
Electricity price forecasting is a key aspect for market participants to maximize their
economic efficiency in deregulated markets. Nevertheless, due to its non-linearity and non …

Short-term solar power predicting model based on multi-step CNN stacked LSTM technique

N Elizabeth Michael, M Mishra, S Hasan, A Al-Durra - Energies, 2022 - mdpi.com
Variability in solar irradiance has an impact on the stability of solar systems and the grid's
safety. With the decreasing cost of solar panels and recent advancements in energy …

Multivariate empirical mode decomposition based hybrid model for day-ahead peak load forecasting

Y Huang, N Hasan, C Deng, Y Bao - Energy, 2022 - Elsevier
Accurate day-ahead peak load forecasting is crucial not only for power dispatching but also
has a great interest to investors and energy policy maker as well as government. Literature …

A novel hybrid load forecasting framework with intelligent feature engineering and optimization algorithm in smart grid

G Hafeez, I Khan, S Jan, IA Shah, FA Khan, A Derhab - Applied Energy, 2021 - Elsevier
Real-time, accurate, and stable forecasting plays a vital role in making strategic decisions in
the smart grid (SG). This ensures economic savings, effective planning, and reliable and …