Advanced Technologies and Methods in the Energy System

Topic Information

Dear Colleagues,

Traditional fossil fuels such as coal, oil, and natural gas have contributed the most to the sustainable economic development for the industrial sectors in the past few decades. The negative environmental and economic impacts, however, should be considered since fossil fuels will trigger many problems, such as environmental pollution, global warming, and economic security. For example, CO₂ and other pollutant emissions, due to the burning of hydrocarbon fossil fuels, are among the main contributors to atmospheric pollution and climate change. In order to cope with the energy and environment crisis, the energy systems, which generate fewer CO₂ and pollutant emissions, are becoming one of the hot spots in the industry and academia. For both traditional and renewable energy systems, advanced technologies and methods are investigated in order to improve the efficiency of the energy system. Artificial intelligence and other technologies could be used in the energy system. An increasing number of researchers have entered the field in the recent years, and the number of related papers has grown significantly. Thus, we are committed to providing the platform for high-quality papers in this field. This topic focuses on advanced technologies and methods in the energy system. The topic includes but is not limited to: 

• Hydrogen energy systems;
• Fuel cell technologies;
• Advanced combustion theory;
• Methanol and other clean alternative fuels;
• Solar photovoltaic and thermal systems;
• Safety issues in the use of clean energies;
• Energy management systems;
• Advanced test technologies in energy systems;
• Energy conversion in the aerospace field;
• Measurement.

Dr. Yongliang Xie
Dr. Liang Gong
Dr. Chang’e Cai
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Aerospace aerospace	2.660	3.4	2014	21.8 Days	1800 CHF	Submit
Clean Technologies cleantechnol	-	-	2019	21 Days	1600 CHF	Submit
Energies energies	3.252	5.0	2008	15.5 Days	2200 CHF	Submit
Sensors sensors	3.847	6.4	2001	15 Days	2400 CHF	Submit
Solar solar	-	-	2021	13.9 Days	1000 CHF	Submit

Published Papers (5 papers)

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Journals

All Aerospace Clean Technol. Energies Sensors Solar

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Open AccessArticle

Buckling Analysis and Structure Improvement for the Afterburner Cylinder of an Aero-Engine

by

Xiaoxia Zheng

,

Yu Zou

,

Bohan He

,

Jixin Xiang

,

Zhiqiang Li

and

Qiao Yang

Aerospace 2023, 10(5), 484; https://doi.org/10.3390/aerospace10050484 - 20 May 2023

Viewed by 294

Abstract

The buckling failure of the afterburner cylinder is a serious safety concern for aero-engines. To tackle this issue, the buckling simulation analysis of the afterburner cylinder was carried out by using finite element method (FEM) software to obtain the buckling mode and critical [...] Read more.

The buckling failure of the afterburner cylinder is a serious safety concern for aero-engines. To tackle this issue, the buckling simulation analysis of the afterburner cylinder was carried out by using finite element method (FEM) software to obtain the buckling mode and critical buckling loads. It was found that the afterburner cylinder was susceptible to buckling when subjected to differential pressure or the compressive force of the rear flange. Buckling would occur when the differential pressure reached 0.4 times the atmospheric pressure or when the axial compressive force on the rear flange reached 222.8 kN. Buckling was also found at the front of the cylinder under the auxiliary mount load. Additionally, under various loads on the rear flange, buckling occurred in the rear section, with the buckling mode being closely related to the load characteristics. Based on the simulation results and structural design requirements, two structural improvements were proposed, including the wall-thickening scheme and the grid reinforcement scheme. FEM simulation analysis results showed that both schemes would improve the rigidity and stability of the afterburner cylinder. For the 0.3 mm increase in the wall thickness scheme, the critical buckling load increased by 17.86% to 66.4%; for the grid reinforcement scheme, the critical buckling load increased by 169% to 619%. Therefore, the grid reinforcement scheme had a stronger anti-buckling ability and was deemed the optimal solution. The findings of this paper could provide technical support for the structural design of large-sized and thin-walled components of aero-engines. Full article

(This article belongs to the Topic Advanced Technologies and Methods in the Energy System)

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Open AccessArticle

An Overall Linearized Modeling Method and Associated Delay Time Model for the PV System

by

Xianping Zhu

,

Shaowu Li

and

Jingxun Fan

Energies 2023, 16(10), 4202; https://doi.org/10.3390/en16104202 - 19 May 2023

Viewed by 220

Abstract

There are some significant nonlinearity and delay issues in photovoltaic (PV) system circuits. Therefore, it is very difficult for the existing classic linear control theories to be used in PV systems; this hinders the design of the optimal energy dispatch by considering real-time [...] Read more.

There are some significant nonlinearity and delay issues in photovoltaic (PV) system circuits. Therefore, it is very difficult for the existing classic linear control theories to be used in PV systems; this hinders the design of the optimal energy dispatch by considering real-time generation power forecasting methods. To solve this problem, an overall linearized model with variable weather parameters (OLM-VWP) of the PV system is proposed on the basis of small-signal modeling. Meanwhile, a corresponding simplified overall linearized model with variable weather parameters (SOLM-VWP) is presented. The SOLM-VWP avoids analyzing delay characteristics of the complex high-order PV system. Moreover, it can reduce hardware cost and computation time, which makes analysis of the transient performance index of the PV system more convenient. In addition, on the basis of the OLM-VWP and SOLM-VWP, a delay-time model with variable weather parameters (DTM-VWP) of the PV system is also proposed. The delay time of the system can be accurately calculated using the DTM-VWP, and it provides a preliminary theoretical basis for carrying out real-time energy scheduling of the PV system. Finally, simulations are implemented using the MATLAB tool, and experiments are conducted. The results verify that the proposed linearization model of the PV system is accurate and reasonable under varying irradiance and temperature conditions. Meanwhile, the results also verify that the proposed SOLM-VWP and DTM-VWP of the PV system are feasible. Additionally, the results show that some transient performance indexes (delay time, rise time, settling time, and peak time) can be solved by means of equations when the circuit parameters and real-time weather parameters are given. Full article

(This article belongs to the Topic Advanced Technologies and Methods in the Energy System)

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Open AccessArticle

Application of Magnetic Adaptive Testing for Nondestructive Investigation of 2507 Duplex Stainless Steel

by

Gábor Vértesy

,

István Mészáros

and

Bálint Bögre

Sensors 2023, 23(7), 3702; https://doi.org/10.3390/s23073702 - 03 Apr 2023

Viewed by 555

Abstract

Duplex stainless steels are two-phase alloys, which contain ferritic and austenitic phases in their microstructure. Their duplex structure provides exceptional resistance to pitting and chloride stress corrosion cracking, and their strength is about twice that of austenitic stainless steels. Due to their good [...] Read more.

Duplex stainless steels are two-phase alloys, which contain ferritic and austenitic phases in their microstructure. Their duplex structure provides exceptional resistance to pitting and chloride stress corrosion cracking, and their strength is about twice that of austenitic stainless steels. Due to their good properties, they are widely used in chemical and petrochemical industries as a base material in pressure vessels, pipelines and containers. Duplex stainless steel samples were nondestructively investigated by measuring sets of magnetic minor hysteresis loops using the method called magnetic adaptive testing (MAT). Several series of heat-treated and cold-rolled 2507 duplex stainless steels were measured, and the magnetic parameters were compared with the results of the DC magnetometry of the samples. It was found that the changes in the material properties that were generated by heat treatment and mechanical deformation could easily be followed by magnetic measurements. In contrast to DC magnetic measurements, good correlation was found with the magnetic parameters determined by MAT method and Vickers hardness. Based on our experiments, MAT seems to be a powerful tool for the nondestructive characterization of duplex stainless steels. Full article

(This article belongs to the Topic Advanced Technologies and Methods in the Energy System)

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Open AccessArticle

DiffNILM: A Novel Framework for Non-Intrusive Load Monitoring Based on the Conditional Diffusion Model

by

Ruichen Sun

,

Kun Dong

and

Jianfeng Zhao

Sensors 2023, 23(7), 3540; https://doi.org/10.3390/s23073540 - 28 Mar 2023

Viewed by 923

Abstract

Non-intrusive Load Monitoring (NILM) is a critical technology that enables detailed analysis of household energy consumption without requiring individual metering of every appliance, and has the capability to provide valuable insights into energy usage behavior, facilitate energy conservation, and optimize load management. Currently, [...] Read more.

Non-intrusive Load Monitoring (NILM) is a critical technology that enables detailed analysis of household energy consumption without requiring individual metering of every appliance, and has the capability to provide valuable insights into energy usage behavior, facilitate energy conservation, and optimize load management. Currently, deep learning models have been widely adopted as state-of-the-art approaches for NILM. In this study, we introduce DiffNILM, a novel energy disaggregation framework that utilizes diffusion probabilistic models to distinguish power consumption patterns of individual appliances from aggregated power. Starting from a random Gaussian noise, the target waveform is iteratively reconstructed via a sampler conditioned on the total active power and encoded temporal features. The proposed method is evaluated on two public datasets, REDD and UKDALE. The results demonstrated that DiffNILM outperforms baseline models on several key metrics on both datasets and shows a remarkable ability to effectively recreate complex load signatures. The study highlights the potential of diffusion models to advance the field of NILM and presents a promising approach for future energy disaggregation research. Full article

(This article belongs to the Topic Advanced Technologies and Methods in the Energy System)

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Open AccessArticle

Fault Detection and Classification of CIGS Thin-Film PV Modules Using an Adaptive Neuro-Fuzzy Inference Scheme

by

Reham A. Eltuhamy

,

Mohamed Rady

,

Eydhah Almatrafi

,

Haitham A. Mahmoud

and

Khaled H. Ibrahim

Sensors 2023, 23(3), 1280; https://doi.org/10.3390/s23031280 - 22 Jan 2023

Viewed by 893

Abstract

The use of artificial intelligence to automate PV module fault detection, diagnosis, and classification processes has gained interest for PV solar plants maintenance planning and reduction in expensive inspection and shutdown periods. The present article reports on the development of an adaptive neuro-fuzzy [...] Read more.

The use of artificial intelligence to automate PV module fault detection, diagnosis, and classification processes has gained interest for PV solar plants maintenance planning and reduction in expensive inspection and shutdown periods. The present article reports on the development of an adaptive neuro-fuzzy inference system (ANFIS) for PV fault classification based on statistical and mathematical features extracted from outdoor infrared thermography (IRT) and I-V measurements of thin-film PV modules. The selection of the membership function is shown to be essential to obtain a high classifier performance. Principal components analysis (PCA) is used to reduce the dimensions to speed up the classification process. For each type of fault, effective features that are highly correlated to the PV module’s operating power ratio are identified. Evaluation of the proposed methodology, based on datasets gathered from a typical PV plant, reveals that features extraction methods based on mathematical parameters and I-V measurements provide a 100% classification accuracy. On the other hand, features extraction based on statistical factors provides 83.33% accuracy. A novel technique is proposed for developing a correlation matrix between the PV operating power ratio and the effective features extracted online from infrared thermal images. This eliminates the need for offline I-V measurements to estimate the operating power ratio of PV modules. Full article

(This article belongs to the Topic Advanced Technologies and Methods in the Energy System)

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