[HTML][HTML] A systematic review of machine learning applications in the operation of smart distribution systems
Due to climate changes happening in the past few years, the necessity for the integration of
renewable energy sources and other low-carbon technologies is ever-growing. With the …
renewable energy sources and other low-carbon technologies is ever-growing. With the …
Secure and resilient demand side management engine using machine learning for IoT-enabled smart grid
The national security, economy, and healthcare heavily rely on the reliable distribution of
electricity. The incorporation of communication technologies and sensors in the power …
electricity. The incorporation of communication technologies and sensors in the power …
[HTML][HTML] Advances in power quality analysis techniques for electrical machines and drives: A review
AD Gonzalez-Abreu, RA Osornio-Rios… - Energies, 2022 - mdpi.com
The electric machines are the elements most used at an industry level, and they represent
the major power consumption of the productive processes. Particularly speaking, among all …
the major power consumption of the productive processes. Particularly speaking, among all …
A machine learning decision-support system improves the internet of things' smart meter operations
J Siryani, B Tanju, TJ Eveleigh - IEEE Internet of Things Journal, 2017 - ieeexplore.ieee.org
An Internet of Things'(IoT) connected society and system represents a tremendous paradigm
shift. We present a framework for a decision-support system (DSS) that operates within the …
shift. We present a framework for a decision-support system (DSS) that operates within the …
Syncretic use of smart meters for power quality monitoring in emerging networks
MM Albu, M Sănduleac… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
Operation of distribution networks undergoes dramatic changes in the era of smart grid
deployment, due to the higher penetration of distributed generation (usually from intermittent …
deployment, due to the higher penetration of distributed generation (usually from intermittent …
A two-stage deep convolutional model for demand response energy management system in IoT-enabled smart grid
HS Shreenidhi, NS Ramaiah - Sustainable Energy, Grids and Networks, 2022 - Elsevier
Abstract Home Energy Management System (HEMS) plays an integral role in SG that
optimally schedules the appliances to achieve energy savings, cost reduction, Peak …
optimally schedules the appliances to achieve energy savings, cost reduction, Peak …
Data-driven multi-hidden markov model-based power quality disturbance prediction that incorporates weather conditions
F Xiao, Q Ai - IEEE Transactions on Power Systems, 2018 - ieeexplore.ieee.org
Power quality (PQ) disturbance in power systems has been a concern for operators and
customers. The purpose is to locate and forecast the presence of PQ disturbances to …
customers. The purpose is to locate and forecast the presence of PQ disturbances to …
An optimizing and differentially private clustering algorithm for mixed data in SDN-based smart grid
Software-defined network (SDN) is widely used in smart grid for monitoring and managing
the communication network. Big data analytics for SDN-based smart grid has got increasing …
the communication network. Big data analytics for SDN-based smart grid has got increasing …
[HTML][HTML] Machine learning-based management of electric vehicles charging: Towards highly-dispersed fast chargers
Coordinated charging of electric vehicles (EVs) improves the overall efficiency of the power
grid as it avoids distribution system overloads, increases power quality, and decreases …
grid as it avoids distribution system overloads, increases power quality, and decreases …
[HTML][HTML] Advanced distribution measurement technologies and data applications for smart grids: A review
The integration of advanced measuring technologies in distribution systems allows
distribution system operators to have better observability of dynamic and transient events. In …
distribution system operators to have better observability of dynamic and transient events. In …