A Novel Intelligent Scheme for Building Energy Prediction Based On Machine Learning and Deep Learning Algorithms DOI

M Jayashankara,

Prasenjit Chanak, Sanjay Kumar Singh

et al.

Published: Jan. 1, 2024

Language: Английский

Dynamic pricing for load shifting: Reducing electric vehicle charging impacts on the grid through machine learning-based demand response DOI

P. Balakumar,

Senthil Kumar R,

Vinopraba Thirumavalavan

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 103, P. 105256 - 105256

Published: Feb. 7, 2024

Language: Английский

Citations

17

Active power filter module function to improve power quality conditions using GWO and PSO techniques for solar photovoltaic arrays and battery energy storage systems DOI
Mohamad Abou Houran, Kiomars Sabzevari, Alaaeldien Hassan

et al.

Journal of Energy Storage, Journal Year: 2023, Volume and Issue: 72, P. 108552 - 108552

Published: Aug. 9, 2023

Language: Английский

Citations

25

Low-carbon urban–rural modern energy systems with energy resilience under climate change and extreme events in China—A state-of-the-art review DOI
Yuekuan Zhou

Energy and Buildings, Journal Year: 2024, Volume and Issue: 321, P. 114661 - 114661

Published: Aug. 10, 2024

Language: Английский

Citations

14

Optimal Adaptive Fractional Order Integral Sliding Mode Controller-Energy Management Strategy for Electric Vehicles Based on Bald Eagle Search Algorithm DOI Creative Commons

Houssam Eddine Ghadbane,

Said Barkat, Azeddine Houari

et al.

International Journal of Energy Research, Journal Year: 2024, Volume and Issue: 2024, P. 1 - 22

Published: Feb. 20, 2024

This research presents an optimal energy management system (EMS) for a lithium-ion battery-supercapacitor hybrid storage used to power electric vehicle. The systems are connected in parallel the DC bus by bidirectional DC-DC converters and feed synchronous reluctance motor through inverter. proposed strategy is built on idea take full benefits of two combined methods: bald eagle search algorithm fractional order integral sliding mode control. To evaluate effectiveness suggested strategy, urban dynamometer driving schedule (UDDS) cycle considered. obtained results compared classical control-based terms voltage ripples, overshoots, battery final state charge. ultimate approve ability enhance quality consumption at same time. Comprehensive processor-in-the-loop (PIL) cosimulations were conducted vehicle using C2000 launchxl-f28379d digital signal processing (DSP) board assess practicability EMS.

Language: Английский

Citations

9

A Review on Machine/Deep Learning Techniques Applied to Building Energy Simulation, Optimization and Management DOI Creative Commons

Francesca Villano,

Gerardo Maria Mauro,

Alessia Pedace

et al.

Thermo, Journal Year: 2024, Volume and Issue: 4(1), P. 100 - 139

Published: March 6, 2024

Given the climate change in recent decades and ever-increasing energy consumption building sector, research is widely focused on green revolution ecological transition of buildings. In this regard, artificial intelligence can be a precious tool to simulate optimize performance, as shown by plethora studies. Accordingly, paper provides review more than 70 articles from years, i.e., mostly 2018 2023, about applications machine/deep learning (ML/DL) forecasting performance buildings their simulation/control/optimization. This was conducted using SCOPUS database with keywords “buildings”, “energy”, “machine learning” “deep selecting papers addressing following applications: design/retrofit optimization, prediction, control/management heating/cooling systems renewable source systems, and/or fault detection. Notably, discusses main differences between ML DL techniques, showing examples use The aim group most frequent ML/DL techniques used field highlighting potentiality limitations each one, both fundamental aspects for future approaches considered are decision trees/random forest, naive Bayes, support vector machines, Kriging method neural networks. investigated convolutional recursive networks, long short-term memory gated recurrent units. Firstly, various explained divided based methodology. Secondly, grouping aforementioned occurs. It emerges that efficiency issues while management systems.

Language: Английский

Citations

9

Advancing smart net-zero energy buildings with renewable energy and electrical energy storage DOI
Dong Luo, Jia Liu, Huijun Wu

et al.

Journal of Energy Storage, Journal Year: 2025, Volume and Issue: 114, P. 115850 - 115850

Published: Feb. 22, 2025

Language: Английский

Citations

1

Optimizing electric vehicle charging in distribution networks: A dynamic pricing approach using internet of things and Bi-directional LSTM model DOI

P. Balakumar,

Senthil Kumar R,

Vinopraba Thirumavalavan

et al.

Energy, Journal Year: 2024, Volume and Issue: 294, P. 130815 - 130815

Published: Feb. 29, 2024

Language: Английский

Citations

6

Wasserstein generative adversarial networks-based photovoltaic uncertainty in a smart home energy management system including battery storage devices DOI
Shaza H. Mansour, Sarah M. Azzam, Hany M. Hasanien

et al.

Energy, Journal Year: 2024, Volume and Issue: 306, P. 132412 - 132412

Published: July 14, 2024

Language: Английский

Citations

6

Hilbert-Huang Transform and machine learning based electromechanical analysis of induction machine under power quality disturbances DOI Creative Commons

V. Indragandhi,

R. Senthil Kumar,

R. Saranya

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: 24, P. 103075 - 103075

Published: Oct. 9, 2024

Language: Английский

Citations

6

Supply-demand side management of a building energy system driven by solar and biomass in Stockholm: A smart integration with minimal cost and emission DOI Creative Commons
Amirmohammad Behzadi, Eva Thorin, Christophe Duwig

et al.

Energy Conversion and Management, Journal Year: 2023, Volume and Issue: 292, P. 117420 - 117420

Published: July 20, 2023

As part of the transition to a sustainable future, energy-efficient buildings are needed secure users' comfort and lower built environment's energy footprint associated emissions. This article presents novel, realistic affordable solution minimize smart building systems enable higher renewable use in sector. For this, an intelligent system is being developed using rule-based automation approach that considers thermal comfort, prices, meteorological data, primary use. In order installation cost environmental footprint, batteries not used, heat pump's size decreased via component integration. Also, different resources effectively hybridized photovoltaic panels innovative biomass heater increase share energy, enhance reliability, shave peak load. feasibility, suggested framework assessed from techno-economic standpoints for 100 residential apartments Stockholm, Sweden. Our results show 70.8 MWh electricity transferred local grid, remaining 111.5 used supply building's needs power electrically-driven components. The meets more than 65% space heating demand, mainly at low solar high illustrating value integration strategies reduce system's dependability on grid. further reveal most purchases during cloudy days nights repaid through sale excess production warmer hours, with bidirectional connection monthly less 140 $/MWh years. can be held due exclusion minimizing pump size. proposed has emission index 11.9 kgCO2/MWh carbon dioxide emissions by 70 TCO2/year compared Swedish mix.

Language: Английский

Citations

16