Review of machine learning techniques for power electronics control and optimization

M Bahrami, Z Khashroum - arXiv preprint arXiv:2310.04699, 2023 - arxiv.org
In the rapidly advancing landscape of contemporary technology, power electronics assume
a pivotal role across diverse applications, ranging from renewable energy systems to electric …

A new model of faults classification in power transformers based on data optimization method

A Abdo, H Liu, H Zhang, J Guo, Q Li - Electric Power Systems Research, 2021 - Elsevier
The current paper aims to present a hybrid model for classifying faults in power transformers.
The innovation of this paper can be shown by introducing a new method of data optimization …

[HTML][HTML] Smart home energy management systems: Research challenges and survey

A Raza, L Jingzhao, Y Ghadi, M Adnan, M Ali - Alexandria Engineering …, 2024 - Elsevier
Electricity is establishing ground as a means of energy, and its proportion will continue to
rise in the next generations. Home energy usage is expected to increase by more than 40 …

Adaptive mode switch strategy based on simulated annealing optimization of a multi-mode hybrid energy storage system for electric vehicles

B Wang, J Xu, B Cao, B Ning - Applied Energy, 2017 - Elsevier
This paper proposes an adaptive mode switch strategy (AMSS) based on simulated
annealing (SA) optimization of a multi-mode hybrid energy storage system (HESS) for …

[HTML][HTML] Design, analysis and implementation of bidirectional DC–DC converters for Hess in DC microgrid applications

S Punna, R Mailugundla, SR Salkuti - Smart Cities, 2022 - mdpi.com
This research proposes an enhanced converter for a hybrid energy storage system (HESS)
for a multi-input bidirectional DC–DC power converter (MIPC). When batteries are used for …

Aspects of balanced development of RES and distributed micro-cogeneration use in Poland: Case study of a µCHP with Stirling engine

A Chmielewski, R Gumiński, J Mączak… - … and Sustainable Energy …, 2016 - Elsevier
Distributed generation of electric energy in decentralized systems plays an increasingly vital
role in Europe. This constitutes a challenge in the development of new technologies with the …

Robust fractional-order PID control of supercapacitor energy storage systems for distribution network applications: A perturbation compensation based approach

B Yang, J Wang, J Wang, H Shu, D Li, C Zeng… - Journal of Cleaner …, 2021 - Elsevier
This study proposes a robust fractional-order PID (RFOPID) control approach for
supercapacitor energy storage (SCES) system applied on distribution network. At first …

[HTML][HTML] Solar irradiance prediction with machine learning algorithms: a Brazilian case study on photovoltaic electricity generation

G de Freitas Viscondi, SN Alves-Souza - Energies, 2021 - mdpi.com
Forecasting photovoltaic electricity generation is one of the key components to reducing the
impacts of solar power natural variability, nurturing the penetration of renewable energy …

Fast characterization of biomass and waste by infrared spectra and machine learning models

J Tao, R Liang, J Li, B Yan, G Chen, Z Cheng… - Journal of hazardous …, 2020 - Elsevier
Heterogeneity is a most serious obstacle for treatment and utilization of biomass and waste
(BW). This paper proposed a fast characterization method based on infrared spectroscopy …

[HTML][HTML] Short-term load forecasting for CCHP systems considering the correlation between heating, gas and electrical loads based on deep learning

R Zhu, W Guo, X Gong - Energies, 2019 - mdpi.com
Combined cooling, heating, and power (CCHP) systems is a distributed energy system that
uses the power station or heat engine to generate electricity and useful heat simultaneously …