Data-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review
Meteorological changes urge engineering communities to look for sustainable and clean
energy technologies to keep the environment safe by reducing CO 2 emissions. The …
energy technologies to keep the environment safe by reducing CO 2 emissions. The …
Day-ahead load demand forecasting in urban community cluster microgrids using machine learning methods
SNVB Rao, VPK Yellapragada, K Padma, DJ Pradeep… - Energies, 2022 - mdpi.com
The modern-day urban energy sector possesses the integrated operation of various
microgrids located in a vicinity, named cluster microgrids, which helps to reduce the utility …
microgrids located in a vicinity, named cluster microgrids, which helps to reduce the utility …
Analysis and prediction of carbon emission in the large green commercial building: A case study in Dalian, China
Reducing carbon emissions from the construction industry has been vital to addressing the
growing global environmental change challenge. Building energy consumption data is …
growing global environmental change challenge. Building energy consumption data is …
Application of deep learning techniques and Bayesian optimization with tree parzen Estimator in the classification of supply chain pricing datasets of health …
From the development and sale of a product through its delivery to the end customer, the
supply chain encompasses a network of suppliers, transporters, warehouses, distribution …
supply chain encompasses a network of suppliers, transporters, warehouses, distribution …
A new deep learning Restricted Boltzmann Machine for energy consumption forecasting
A Xu, MW Tian, B Firouzi, KA Alattas… - Sustainability, 2022 - mdpi.com
A key issue in the desired operation and development of power networks is the knowledge
of load growth and electricity demand in the coming years. Mid-term load forecasting (MTLF) …
of load growth and electricity demand in the coming years. Mid-term load forecasting (MTLF) …
An ensemble-based approach for short-term load forecasting for buildings with high proportion of renewable energy sources
The increasing integration of renewable energy sources into large buildings and structures
has emphasized the importance of effective control systems to optimize resource use, grid …
has emphasized the importance of effective control systems to optimize resource use, grid …
Forecasting daily electricity consumption in Thailand using regression, artificial neural network, support vector machine, and hybrid models
W Pannakkong, T Harncharnchai, J Buddhakulsomsiri - Energies, 2022 - mdpi.com
This article involves forecasting daily electricity consumption in Thailand. Electricity
consumption data are provided by the Electricity Generating Authority of Thailand, the …
consumption data are provided by the Electricity Generating Authority of Thailand, the …
Self-updating machine learning system for building load forecasting-method, implementation and case-study on COVID-19 impact
Y Besanger, QT Tran - Sustainable Energy, Grids and Networks, 2022 - Elsevier
Accurate building load forecasting is a challenging task due to the large volume of input
information, their non-linearity and variant nature due to human activities. In this study, we …
information, their non-linearity and variant nature due to human activities. In this study, we …
Energy use forecasting with the use of a nested structure based on fuzzy cognitive maps and artificial neural networks
K Poczeta, EI Papageorgiou - Energies, 2022 - mdpi.com
The aim of this paper is to present a novel approach to energy use forecasting. We propose
a nested fuzzy cognitive map in which each concept at a higher level can be decomposed …
a nested fuzzy cognitive map in which each concept at a higher level can be decomposed …
Data-Driven Short-Term Load Forecasting for Multiple Locations: An Integrated Approach
A Baul, GC Sarker, P Sikder, U Mozumder… - Big Data and Cognitive …, 2024 - mdpi.com
Short-term load forecasting (STLF) plays a crucial role in the planning, management, and
stability of a country's power system operation. In this study, we have developed a novel …
stability of a country's power system operation. In this study, we have developed a novel …