Machine learning based energy management model for smart grid and renewable energy districts

W Ahmed, H Ansari, B Khan, Z Ullah, SM Ali… - IEEE …, 2020 - ieeexplore.ieee.org
The combination of renewable energy sources and prosumer-based smart grid is a
sustainable solution to cater to the problem of energy demand management. A pressing …

Intelligent optimization framework for efficient demand-side management in renewable energy integrated smart grid

HW Khan, M Usman, G Hafeez, FR Albogamy… - IEEE …, 2021 - ieeexplore.ieee.org
The implementation of real-time price-based demand response program and integration of
renewable energy resources (RESs) improves efficiency and ensure stability of electric grid …

Genetic algorithm based optimized feature engineering and hybrid machine learning for effective energy consumption prediction

PW Khan, YC Byun - Ieee Access, 2020 - ieeexplore.ieee.org
Smart grids are developing rapidly, leading to the need for accurate forecasts of power
consumption. However, developing a precise time series model for energy forecasting is …

Stochastic energy management and scheduling of microgrids in correlated environment: A deep learning-oriented approach

T Cheng, X Zhu, X Gu, F Yang… - Sustainable Cities and …, 2021 - Elsevier
Regarding the operation, reliability, security, and cost-effectiveness of microgrids (MGs),
optimal energy management and data security are essential issues that must be taken into …

[HTML][HTML] An artificial-intelligence-based renewable energy prediction program for demand-side management in smart grids

V Arumugham, HMA Ghanimi, DA Pustokhin… - Sustainability, 2023 - mdpi.com
Technology advancements have enabled the capture of Renewable Energy Sources (RES)
on a massive scale. Smart Grids (SGs) that combine conventional and RES are predicted as …

Data-driven probabilistic machine learning in sustainable smart energy/smart energy systems: Key developments, challenges, and future research opportunities in the …

T Ahmad, R Madonski, D Zhang, C Huang… - … and Sustainable Energy …, 2022 - Elsevier
The current trend indicates that energy demand and supply will eventually be controlled by
autonomous software that optimizes decision-making and energy distribution operations …

[HTML][HTML] Evaluation of machine learning models for smart grid parameters: performance analysis of ARIMA and Bi-LSTM

Y Chen, MS Bhutta, M Abubakar, D Xiao… - Sustainability, 2023 - mdpi.com
The integration of renewable energy resources into smart grids has become increasingly
important to address the challenges of managing and forecasting energy production in the …

[PDF][PDF] Smart Energy Management System Using Machine Learning

A Akram, S Abbas, M Khan, A Athar… - … , Materials & Continua, 2024 - researchgate.net
Energy management is an inspiring domain in developing of renewable energy sources.
However, the growth of decentralized energy production is revealing an increased …

An intelligent integrated approach for efficient demand side management with forecaster and advanced metering infrastructure frameworks in smart grid

A Nawaz, G Hafeez, I Khan, KU Jan, H Li… - IEEE …, 2020 - ieeexplore.ieee.org
The development of advanced metering infrastructure (AMI) in smart grid (SG) had enabled
consumers to participate in demand-side management (DSM) using the price-based …

[HTML][HTML] Microgrid-level energy management approach based on short-term forecasting of wind speed and solar irradiance

M Alhussein, SI Haider, K Aurangzeb - Energies, 2019 - mdpi.com
Background: The Distributed Energy Resources (DERs) are beneficial in reducing the
electricity bills of the end customers in a smart community by enabling them to generate …