Energy supply-demand interaction model integrating uncertainty forecasting and peer-to-peer energy trading

K Zhou, Y Chu, R Hu - Energy, 2023 - Elsevier
With the penetration of large amounts of renewable energy resources into energy system,
the interaction between energy supply and demand has become more complex and diverse …

An instance based multi-source transfer learning strategy for building's short-term electricity loads prediction under sparse data scenarios

B Wei, K Li, S Zhou, W Xue, G Tan - Journal of Building Engineering, 2024 - Elsevier
The use of transfer learning for building's electricity loads prediction has shown great
potential when in practice the available electricity consumption data in local energy …

A framework for electricity load forecasting based on attention mechanism time series depthwise separable convolutional neural network

H Xu, F Hu, X Liang, G Zhao, M Abugunmi - Energy, 2024 - Elsevier
Electricity load exhibits daily and weekly cyclical patterns as well as random characteristics.
At present, prevailing deep learning models cannot learn electricity load cyclical and …

Multi-type load forecasting model based on random forest and density clustering with the influence of noise and load patterns

S Deng, X Dong, L Tao, J Wang, Y He, D Yue - Energy, 2024 - Elsevier
Load forecasting (LF) models are essential for various smart grid applications, and their
accuracy heavily relies on the quality of input load data and load types. Previous LF studies …

Review of the opportunities and challenges to accelerate mass‐scale application of smart grids with large‐language models

H Shi, L Fang, X Chen, C Gu, K Ma, X Zhang… - IET Smart …, 2024 - Wiley Online Library
Smart grids represent a paradigm shift in the electricity industry, moving from traditional one‐
way systems to more dynamic, interconnected networks. These grids are characterised by …

Spatial weather, socio-economic and political risks in probabilistic load forecasting

M Zimmermann, F Ziel - arXiv preprint arXiv:2408.00507, 2024 - arxiv.org
Accurate forecasts of the impact of spatial weather and pan-European socio-economic and
political risks on hourly electricity demand for the mid-term horizon are crucial for strategic …

An IHPO-WNN-Based Federated Learning System for Area-Wide Power Load Forecasting Considering Data Security Protection

B Shi, X Zhou, P Li, W Ma, N Pan - Energies, 2023 - mdpi.com
With the rapid growth of power demand and the advancement of new power system
intelligence, smart energy measurement system data quality and security are also facing the …

Medium‐term load forecasting of power system based on BiLSTM and parallel feature extraction network

F Li, C Sun, W Han, T Yan, G Li… - IET Generation …, 2024 - Wiley Online Library
With the diversification of users' energy demands, accurate load forecasting is an important
prerequisite for optimal scheduling and economic operation of the system, but a single‐load …

Day-ahead load forecast based on Conv2D-GRU_SC aimed to adapt to steep changes in load

Y Chen, C Lin, Y Zhang, J Liu, D Yu - Energy, 2024 - Elsevier
With the significant increase in the proportion of volatile new energy in the power system in
recent years, the difficulty of system scheduling has increased. Accurate load forecasting is …

[HTML][HTML] Development of an Integrated Energy Management System for Off-Grid Solar Applications with Advanced Solar Forecasting, Time-of-Use Tariffs, and Direct …

TO Falope, L Lao, D Huo, B Kuang - Sustainable Energy, Grids and …, 2024 - Elsevier
Effectively managing and maximizing the integration of renewable energy sources is
essential for a sustainable power grid due to the stochastic and intermittent nature of …