RHEIA: Robust design optimization of renewable Hydrogen and dErIved energy cArrier systems DOI Creative Commons
Diederik Coppitters,

Panagiotis Tsirikoglou,

Ward De Paepe

et al.

The Journal of Open Source Software, Journal Year: 2022, Volume and Issue: 7(75), P. 4370 - 4370

Published: July 5, 2022

Climate change is a constant call for the massive deployment of intermittent renewable energy sources, such as solar and wind.However, to cover demand at all times, these sources require storage over more extended periods.In this framework, in form hydrogen gaining ground on leading transition today's economy towards decarbonization.Among others, can be integrated into multiple sectors: converted back electricity (power-to-power), it used produce low-carbon fuels (power-to-fuel), fuel vehicles (power-tomobility).The performance hydrogen-based systems subject uncertainties, uncertainty irradiance, consumption hydrogen-powered buses, price grid electricity.Disregarding uncertainties design process result drastic mismatch between simulated real-world performance, thus lead kill-by-randomness system.The Robust optimization Hydrogen dErIved cArrier (RHEIA) framework provides robust pipeline that considers yields designs, i.e., designs with less sensitive uncertainties.Moreover, RHEIA includes models evaluate hydrogen's techno-economic environmental power-tofuel, power-to-power, power-to-mobility context.When combined, unlocks systems.As system black box, applied existing open-source closed-source models.To illustrate, an interface EnergyPLAN software included framework.

Language: Английский

Digital twins-based smart manufacturing system design in Industry 4.0: A review DOI
Jiewu Leng,

Dewen Wang,

Weiming Shen

et al.

Journal of Manufacturing Systems, Journal Year: 2021, Volume and Issue: 60, P. 119 - 137

Published: May 25, 2021

Language: Английский

Citations

494
Machine Learning for Design Optimization of Electromagnetic Devices: Recent Developments and Future Directions DOI Creative Commons
Yanbin Li, Gang Lei, Gerd Bramerdorfer

et al.

Applied Sciences, Journal Year: 2021, Volume and Issue: 11(4), P. 1627 - 1627

Published: Feb. 11, 2021

This paper reviews the recent developments of design optimization methods for electromagnetic devices, with a focus on machine learning methods. First, advances in multi-objective, multidisciplinary, multilevel, topology, fuzzy, and robust devices are overviewed. Second, review is presented to performance prediction based algorithms, including artificial neural network, support vector machine, extreme random forest, deep learning. Last, meet modern requirements high manufacturing/production quality lifetime reliability, several promising topics, application cloud services digital twin, discussed as future directions devices.

Language: Английский

Citations

64
Digital Twin in Electrical Machine Control and Predictive Maintenance: State-of-the-Art and Future Prospects DOI Creative Commons
Georgios Falekas, Athanasios Karlis

Energies, Journal Year: 2021, Volume and Issue: 14(18), P. 5933 - 5933

Published: Sept. 18, 2021

State-of-the-art Predictive Maintenance (PM) of Electrical Machines (EMs) focuses on employing Artificial Intelligence (AI) methods with well-established measurement and processing techniques while exploring new combinations, to further establish itself a profitable venture in industry. The latest trend industrial manufacturing monitoring is the Digital Twin (DT) which just now being defined explored, showing promising results facilitating realization Industry 4.0 concept. While PM efforts closely resemble suggested DT methodologies would greatly benefit from improved data handling availability, lack combination regarding two concepts detected literature. In addition, next-generation-Digital-Twin (nexDT) definition yet ambiguous. Existing reviews discuss broader definitions include citations often irrelevant PM. This work aims redefine nexDT concept by reviewing descriptions literature establishing specialized denotation for EM manufacturing, PM, control, encapsulating most relevant process, providing specifically catered serving as foundation future endeavors. A brief review both research state-of-the-art spanning last five years presented, followed conjunction core into definitive description. Finally, surmised benefits prospects are reported, especially focused enabling AI techniques.

Language: Английский

Citations

60
An Investigation on Hybrid Particle Swarm Optimization Algorithms for Parameter Optimization of PV Cells DOI Open Access
Abha Singh, Abhishek Sharma, Shailendra Rajput

et al.

Electronics, Journal Year: 2022, Volume and Issue: 11(6), P. 909 - 909

Published: March 15, 2022

The demands for renewable energy generation are progressively expanding because of environmental safety concerns. Renewable is power generated from sources that constantly replenished. Solar an important source and clean initiative. Photovoltaic (PV) cells or modules employed to harvest solar energy, but the accurate modeling PV confounded by nonlinearity, presence huge obscure model parameters, nonattendance a novel strategy. efficient parameter estimation becoming more significant scientific community. Metaheuristic algorithms successfully applied valuation systems. Particle swarm optimization (PSO) metaheuristic algorithm inspired animal behavior. PSO derivative methods tackle different issues. Hybrid were developed improve performance basic ones. This review presents comprehensive investigation hybrid assessment cells. paper how much work conducted in this field, can additionally be performed strategy create ideal arrangements issue. Algorithms compared on basis used objective function, type diode model, irradiation conditions, types panels. More importantly, qualitative analysis computational time, complexity, convergence rate, search technique, merits, demerits.

Language: Английский

Citations

46
Evaluation of 3D-Printed Magnetic Materials For Additively-Manufactured Electrical Machines DOI
Ahmed Selema,

Margherita Beretta,

Matty Van Coppenolle

et al.

Journal of Magnetism and Magnetic Materials, Journal Year: 2023, Volume and Issue: 569, P. 170426 - 170426

Published: Jan. 21, 2023

Language: Английский

Citations

23
Grid Integration for Electric Vehicles: A Realistic Strategy for Environmentally Friendly Mobility and Renewable Power DOI Creative Commons
Pradeep Vishnuram, A. Sureshkumar

World Electric Vehicle Journal, Journal Year: 2024, Volume and Issue: 15(2), P. 70 - 70

Published: Feb. 16, 2024

The promotion of electric vehicles (EVs) as sustainable energy sources for transportation is advocated due to global considerations such consumption and environmental challenges. recent incorporation renewable into virtual power plants has greatly enhanced the influence in industry. Vehicle grid integration offers a practical economical method improve sustainability, addressing requirements consumers on user side. effective utilisation stationary applications highlighted by technological breakthroughs sector. continuous advancement science industry confirming growing efficiency plants. Nonetheless, thorough inquiry imperative elucidate principles, integration, conjunction with automobiles, specifically targeting academics researchers this field. examination emphasises generation storage components used vehicles. In addition, it explores several vehicle–grid (VGI) configurations, single-stage, two-stage, hybrid-multi-stage systems. This study also considers various types connections factors related them. detailed investigation seeks offer insights facets incorporating It takes account technology improvements, ramifications users.

Language: Английский

Citations

9
Review of surrogate model assisted multi-objective design optimization of electrical machines: New opportunities and challenges DOI
Liyang Liu, Zequan Li,

Haoyu Kang

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2025, Volume and Issue: 215, P. 115609 - 115609

Published: March 20, 2025

Language: Английский

Citations

1
A Novel Application of Improved Marine Predators Algorithm and Particle Swarm Optimization for Solving the ORPD Problem DOI Creative Commons
Mohamed A. M. Shaheen, Dalia Yousri, Ahmed Fathy

et al.

Energies, Journal Year: 2020, Volume and Issue: 13(21), P. 5679 - 5679

Published: Oct. 30, 2020

The appropriate planning of electric power systems has a significant effect on the economic situation countries. For protection and reliability system, optimal reactive dispatch (ORPD) problem is an essential issue. ORPD non-linear, non-convex, continuous or non-continuous optimization problem. Therefore, introducing reliable optimizer challenging task to solve this This study proposes robust flexible algorithm with minimum adjustable parameters named Improved Marine Predators Algorithm Particle Swarm Optimization (IMPAPSO) algorithm, for dealing non-linearity ORPD. IMPAPSO evaluated using various test cases, including IEEE 30 bus, 57 118 bus systems. An effectiveness proposed was verified through rigorous comparative other methods. There noticeable enhancement in networks behavior when method. Moreover, high convergence speed observed feature comparison its peers.

Language: Английский

Citations

53
AC Magnetic Loss Reduction of SLM Processed Fe-Si for Additive Manufacturing of Electrical Machines DOI Creative Commons
Hans Tiismus, Ants Kallaste, Anouar Belahcen

et al.

Energies, Journal Year: 2021, Volume and Issue: 14(5), P. 1241 - 1241

Published: Feb. 24, 2021

Additively manufactured soft magnetic Fe-3.7%w.t.Si toroidal samples with solid and novel partitioned cross-sectional geometries are characterized through measurements. This study focuses on the effect of air gaps annealing temperature AC core losses at 50 Hz frequency. In addition, DC electromagnetic material properties presented, showing comparable results to conventional other 3D-printed, high-grade, materials. The magnetization 1.5 T was achieved 1800 A/m, exhibiting a maximum relative permeability 28,900 hysteresis 0.61 (1 T) 1.7 (1.5 W/kg. A clear trend total loss reduction observed in relation segregation specimen topology. lowest were measured for four internal annealed 1200 °C, 1.2 5.5 is equal an 860% 1 510% compared bulk-printed material. Based findings, advantages disadvantages printed air-gapped structures discussed detail.

Language: Английский

Citations

45
Research on speed sensor fusion of urban rail transit train speed ranging based on deep learning DOI Creative Commons

Xuemei Zhan,

Zhong Hua Mu,

Rajeev Kumar

et al.

Nonlinear Engineering, Journal Year: 2021, Volume and Issue: 10(1), P. 363 - 373

Published: Jan. 1, 2021

Abstract The speed sensor fusion of urban rail transit train ranging based on deep learning builds a user-friendly structure but it in-turn increases the risk traffic that significantly challenges its safety and transportation efficacy. In order to improve operation efficiency trains, system embedded multi-sensor information is proposed in this article. status acquired by axle Doppler radar sensor; however, query transponder collects train, used system. Various other modules like adaptive correction, idling/sliding detection compensation transition/sliding are methodology reduce vehicle positioning errors due factors such as wheel wear, idling, sliding, environment. results show running time 1000s, output period 0.005s accelerometer 0.01s. cycle doppler observed be 0.1s, 1s main filter 1s. article can effectively accuracy positioning.

Language: Английский

Citations

44