[HTML][HTML] Forecasting data-driven system strength level for inverter-based resources-integrated weak grid systems using multi-objective machine learning algorithms

MO Qays, I Ahmad, D Habibi, MAS Masoum - Electric Power Systems …, 2025 - Elsevier
Shortage of grid-fault level, known as system strength inadequacy, impacts on grid instability
and can lead to blackouts. System strength is generally measured by short circuit ratio index …

A Deep Learning Approach Based on Novel Multi-Feature Fusion for Power Load Prediction

L Xiao, R An, X Zhang - Processes, 2024 - mdpi.com
Adequate power load data are the basis for establishing an efficient and accurate
forecasting model, which plays a crucial role in ensuring the reliable operation and effective …

Transformer-based probabilistic demand forecasting with adaptive online learning

J Wang, D Xu, Y Li, M Shahidehpour, T Yang - Electric Power Systems …, 2025 - Elsevier
Demand forecasting is crucial for the operation and planning of the energy and power
industry. Accurate demand forecasting can assist decision-makers in reducing operational …

Optimal peer-to-peer energy trading model with short-term load forecasting for energy market

AD Manchalwar, NR Patne, R Panigrahi… - Electrical …, 2024 - Springer
Energy trading and demand are key components of the electricity market, with accurate load
forecasting essential for predicting consumption and optimizing costs. This research aims to …

Analysis of big data from New York taxi trip 2023: revenue prediction using ordinary least squares solution and limitedmemory Broyden-Fletcher-Goldfarb-Shanno …

S Rhouas, N El Hami - International Journal of Electrical & …, 2025 - search.ebscohost.com
This study explores the prediction of taxi trip fares using two linear regression methods:
normal equations (ordinary least squares solution (OLS)) and limited-memory Broyden …

Reliability Test of Control Loop Information in New Power Load Management System

S Wang, Q Guo, K Chen, H Yu, M Ren… - 2024 5th International …, 2024 - ieeexplore.ieee.org
This paper discusses the application of stochastic forest in the detection of new power load
management system, and deals with regression and classification problems by integrating …

Ahc-Rf-Svm: An Adaptive Short-Term Power Load Forecasting Method Based on Concept Drifts

Y Wan, S Lv - Available at SSRN 4795204 - papers.ssrn.com
Accurate prediction of power load is crucial for governments and electricity companies
striving to enhance the security and stability of power grids. However, the volatility of …