Forecasting power demand in China with a CNN-LSTM model including multimodal information

D Wang, J Gan, J Mao, F Chen, L Yu - Energy, 2023 - Elsevier
Accurate forecasting of social power demand is the country's primary task in making
decisions on power overall planning, coal power withdrawal, and renewable energy …

[HTML][HTML] Deep neural network with empirical mode decomposition and Bayesian optimisation for residential load forecasting

A Lotfipoor, S Patidar, DP Jenkins - Expert Systems with Applications, 2024 - Elsevier
In the context of a resilient energy system, accurate residential load forecasting has become
a non-trivial requirement for ensuring effective management and planning strategy/policy …

Accurate deep model for electricity consumption forecasting using multi-channel and multi-scale feature fusion CNN–LSTM

X Shao, CS Kim, P Sontakke - Energies, 2020 - mdpi.com
Electricity consumption forecasting is a vital task for smart grid building regarding the supply
and demand of electric power. Many pieces of research focused on the factors of weather …

Domain fusion CNN-LSTM for short-term power consumption forecasting

X Shao, C Pu, Y Zhang, CS Kim - IEEE Access, 2020 - ieeexplore.ieee.org
Short-term power consumption forecasting plays a critical role in the process of building the
smart grid. However, it is very challenging as the power consumption series has strong …

Incorporating causality in energy consumption forecasting using deep neural networks

K Sharma, YK Dwivedi, B Metri - Annals of Operations Research, 2024 - Springer
Forecasting energy demand has been a critical process in various decision support systems
regarding consumption planning, distribution strategies, and energy policies. Traditionally …

Assessment of SAARC nations' solar energy potential for sustainable development

A Mittal - Energy & Environment, 2023 - journals.sagepub.com
Energy is very vital for the economic development and prosperity of any nation. Expanding a
country's use of renewable energy sources can help it meet its current and future energy …

Load forecasting for different prediction horizons using ann and arima models

I Zuleta-Elles, A Bautista-Lopez… - 2021 IEEE CHILEAN …, 2021 - ieeexplore.ieee.org
Accurate forecasting of renewable energy resources and load has a crucial role in the
overall operation efficiency and energy system integration of microgrids. In addition to this, in …

The forecasting of electrical energy consumption in Morocco with an autoregressive integrated moving average approach

M Jamii, M Maaroufi - Mathematical Problems in Engineering, 2021 - Wiley Online Library
The national demand for primary energy has experienced an average increase of almost 5%
in recent years, driven by the growth in electricity consumption, which grew by an average of …

Collaborative energy price computing based on sarima-ann and asymmetric stackelberg games

T Zhang, Y Wu, Y Chen, T Li, X Ren - Symmetry, 2023 - mdpi.com
The energy trading problem in smart grids has been of great interest. In this paper, we focus
on two problems: 1. Energy sellers' inaccurate grasp of users' real needs causes information …

Cambodia mid-term transmission system load forecasting with the combination of seasonal ARIMA and Gaussian process regression

P Nop, Z Qin - 2021 3rd Asia Energy and Electrical Engineering …, 2021 - ieeexplore.ieee.org
Mid-term load forecasting (MTLF) is crucial for power transmission system planning, safe
operation, and maintenance. It's very significant in a developing country like Cambodia. In …