An overview of Indian power sector and its Energy Management
India's power sector has undergone significant changes in recent years, driven by various
policy initiatives aimed at promoting competition, improving efficiency, and increasing the …
policy initiatives aimed at promoting competition, improving efficiency, and increasing the …
Short-term load forecasting of an integrated energy system based on STL-CPLE with multitask learning
Multienergy loads in integrated energy systems (IESs) exhibit strong volatility and
randomness, and existing multitask sharing methods often encounter negative migration …
randomness, and existing multitask sharing methods often encounter negative migration …
Performance analysis of machine learning algorithms for estimation of EV penetration
The escalating threat of global warming poses a formidable challenge to sustainability,
necessitating a transformative shift in the transportation sector. A pivotal solution is …
necessitating a transformative shift in the transportation sector. A pivotal solution is …
Short-Term Load Forecasting Based on Optimized Random Forest and Optimal Feature Selection
B Magalhães, P Bento, J Pombo, MR Calado… - Energies, 2024 - mdpi.com
Short-term load forecasting (STLF) plays a vital role in ensuring the safe, efficient, and
economical operation of power systems. Accurate load forecasting provides numerous …
economical operation of power systems. Accurate load forecasting provides numerous …
Short-term load analysis and forecasting using stochastic approach considering pandemic effects
The COVID-19 pandemic and its containment have changed the pattern of electricity load.
Hence, accurate forecasting of load for shorter interval of time during pandemic has become …
Hence, accurate forecasting of load for shorter interval of time during pandemic has become …
Regression Models and Shape Descriptors for Building Energy Demand and Comfort Estimation
T Storcz, G Várady, I Kistelegdi, Z Ercsey - Energies, 2023 - mdpi.com
Optimal building design in terms of comfort and energy performance means designing and
constructing a building that requires the minimum energy demand under the given …
constructing a building that requires the minimum energy demand under the given …
Active power load data dimensionality reduction using autoencoder
V Veeramsetty, P Kiran, M Sushma, AM Babu… - Power Quality in …, 2023 - Springer
Dimensionality reduction is a machine learning based technique used to convert the data
from higher dimensionality space to lower dimensionality space. This technique helps to …
from higher dimensionality space to lower dimensionality space. This technique helps to …
Power quality disturbances classification using autoencoder and radial basis function neural network
V Veeramsetty, A Dhanush… - International Journal of …, 2024 - degruyter.com
The classification of power quality (PQ) disturbances is a critical task for both utilities and
industry. PQ issues cause power system equipment to fail. PQ disruptions also cause …
industry. PQ issues cause power system equipment to fail. PQ disruptions also cause …
Effective Voting-based Ensemble Learning for Segregated Load Forecasting with Low Sampling Data
In power system planning and operation, load forecasting is an important task as it helps
ensure a reliable and efficient electricity supply. For effective operation of the smart grid …
ensure a reliable and efficient electricity supply. For effective operation of the smart grid …
Optimization of power system load forecasting and scheduling based on artificial neural networks
J Jing, H Di, T Wang, N Jiang, Z Xiang - Energy Informatics, 2025 - Springer
This study seeks to enhance the accuracy and economic efficiency of power system load
forecasting (PSLF) by leveraging Artificial Neural Networks. A predictive model based on a …
forecasting (PSLF) by leveraging Artificial Neural Networks. A predictive model based on a …