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Diagnosis and Prognostics of New and Renewable Energy Systems for Safety

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A: Sustainable Energy".

Deadline for manuscript submissions: closed (18 November 2022) | Viewed by 16207

Special Issue Editors

Dr. Soo-Bin Han

E-Mail Website
Guest Editor
Korea Institute of Energy Research, Yuseong-gu, Daejeon 34129, Korea
Interests: power electronics; smart grid; renewable energy; prognostics and health management; energy storage system; real time simulation
Dr. Won-Yong Lee

E-Mail Website
Guest Editor
Korea Institute of Energy Research, Yuseong-gu, Daejeon 34129, Korea
Interests: new and renewable energy; fuel cell systems; combined power system; energy system integration; fault detection and diagnosis

Special Issue Information

Dear Colleagues,

Renewable energy has been rapidly spreading around the world. The share of renewables in global electricity generation is expected to reach up to 49% by 2030 according to the IEA scenario. ESS also continues to increase in use with renewables to resolve the grid problems caused by intermittent renewables and the imbalance problems between supply and demand of electricity. Additionally, new sources of energy such as hydrogen and fuel cell are also continuously attracting attention.

There are cases of failure and explosion of renewables and ESS, which threaten energy security with the increase in renewables. Therefore, PHM (prognostics and health management), which has been researched in many industry areas, such as aerospace and electronics, should be actively researched in the energy area as well, especially renewables. Energy system facilities are systems belonging to complex systems, so the study of PHM and safety becomes more important and challenging.

This Special Issue invites various forms of contribution to PHM and safety of complex energy systems to explore the latest advances. The topics of interest include PHM and safety related (but not limited) to:

  • Renewable energy;
  • Hydrogen energy and fuel cell;
  • All kind of energy storage system;
  • Battery and PCS (power conditioning system);
  • Algorithms for energy system operation;
  • Fault detection and diagnosis;
  • Predictive maintenance;
  • Cloud computing and services;
  • Real time simulation for energy systems;
  • CPS (cyberphysical system) applications;
  • Practical applications to energy systems.

Dr. Soo-Bin Han
Dr. Won-Yong Lee
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Renewable energy
  • Solar energy
  • Wind energy
  • Hydrogen energy
  • Fuel cell
  • Energy storage system (ESS)
  • Fault tolerance control
  • Fault diagnosis
  • Prognostics and health management (PHM)
  • Remaining useful life
  • Energy safety and reliability.

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Published Papers (5 papers)

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Research

16 pages, 3614 KiB  
Article
Selecting Surface Inclination for Maximum Solar Power
by Ioannis-Panagiotis Raptis, Anna Moustaka, Panagiotis Kosmopoulos and Stelios Kazadzis
Energies 2022, 15(13), 4784; https://doi.org/10.3390/en15134784 - 29 Jun 2022
Cited by 6 | Viewed by 2681
Abstract
Maximum efficiency of surfaces that exploit solar energy, including Photovoltaic Panels and Thermal collectors, is achieved by installing them in a certain inclination (tilt). Most common approach is to select an inclination angle equal to the location’s latitude. This is based on the [...] Read more.
Maximum efficiency of surfaces that exploit solar energy, including Photovoltaic Panels and Thermal collectors, is achieved by installing them in a certain inclination (tilt). Most common approach is to select an inclination angle equal to the location’s latitude. This is based on the astronomical calculations of the sun’s position throughout the year but ignores meteorological factors. Cloud coverage and aerosols tend to change the direct irradiance but also the radiance sky distribution, thus horizontal surfaces receive larger amounts than tilted ones in specific atmospheric conditions (e.g., cases of cloud presence). In the present study we used 15 years of data, from 25 cities in Europe and North Africa in order to estimate the optimal tilt angle and the related energy benefits based in real atmospheric conditions. Data were retrieved from Copernicus Atmospheric Monitoring Service (CAMS). Four diffuse irradiance, various models are compared, and their differences are evaluated. Equations, extracted from solar irradiance and cloud properties regressions, are suggested to estimate the optimal tilt angle in regions, where no climatological data are available. In addition, the impact of cloud coverage is parameterized using the Cloud Modification Factor (CMF) and an equation is proposed to estimate the optimal tilt angle. A realistic representation of the photovoltaic energy production and a subsequent financial analysis were additionally performed. The results are able to support the prognosis of energy outcome and should be part of energy planning and the decision making for optimum solar power exploitation into the international clean energy transitions. Finally, results are compared to a global study and differences on the optimal tilt angle at cities of Northern Europe is presented. Full article
(This article belongs to the Special Issue Diagnosis and Prognostics of New and Renewable Energy Systems for Safety)
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17 pages, 6634 KiB  
Article
Power Generation Prediction of Building-Integrated Photovoltaic System with Colored Modules Using Machine Learning
by Woo-Gyun Shin, Ju-Young Shin, Hye-Mi Hwang, Chi-Hong Park and Suk-Whan Ko
Energies 2022, 15(7), 2589; https://doi.org/10.3390/en15072589 - 1 Apr 2022
Cited by 6 | Viewed by 2294
Abstract
The building-integrated photovoltaic (BIPV) system is provoking mention as a technology for generating the energy consumed in cities with renewable sources. As the number of BIPV systems increases, performance diagnosis through power-generation predictions becomes more essential. In the case of a colored BIPV [...] Read more.
The building-integrated photovoltaic (BIPV) system is provoking mention as a technology for generating the energy consumed in cities with renewable sources. As the number of BIPV systems increases, performance diagnosis through power-generation predictions becomes more essential. In the case of a colored BIPV module that has been installed on a wall, it is more difficult to predict the amount of power generation because the shading loss varies based on the entrance altitude of the irradiance. Recently, artificial intelligence technology that is able to predict power by learning the output data of the system has begun being used. In this paper, the power values of colored BIPV systems that have been installed on walls are predicted, and the system output values are compared. The current-voltage (I–V) curve data are measured to predict the power required changing the intensity of the irradiance, and the linear regression model is derived for the changes in the voltage and current at a maximum power operating point and during irradiance changes. To improve the power prediction accuracy by considering the shading loss of colored BIPVs, a new model is proposed via neural network machine learning (ML). In addition, the accuracy of the proposed prediction models is evaluated by comparing the metrics such as RMSE, MAE, and R2. As a result of testing the linear regression model and the proposed ML model, the R2 values for the voltage and current values of the proposed ML model were 5% higher for voltage and 2% higher for current. From this result, the proposed ML model of the RMSE about real power improved by more than 50% (0.0754 kW) compared to the simulation model (0.1581 KW). The proposed model demonstrates high-accuracy power estimations and is expected to help diagnose the performance of BIPV systems with colored modules. Full article
(This article belongs to the Special Issue Diagnosis and Prognostics of New and Renewable Energy Systems for Safety)
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12 pages, 536 KiB  
Article
Russia’s Policy Transition to a Hydrogen Economy and the Implications of South Korea–Russia Cooperation
by Kim Youngok, Yi Eunkyung and Son Hyunik
Energies 2022, 15(1), 127; https://doi.org/10.3390/en15010127 - 24 Dec 2021
Cited by 6 | Viewed by 3932
Abstract
Leading countries are developing clean energy to replace fossil fuels. In this context, Russia is changing its energy policy towards fostering new energy resources, such as hydrogen and helium. Hydrogen will not only contribute to Russia’s financial revenue by replacing natural gas, but [...] Read more.
Leading countries are developing clean energy to replace fossil fuels. In this context, Russia is changing its energy policy towards fostering new energy resources, such as hydrogen and helium. Hydrogen will not only contribute to Russia’s financial revenue by replacing natural gas, but will also provide a basis for it to maintain its dominance over the international energy market by pioneering new energy markets. Russia is aiming to produce more than two million tons of hydrogen fuel for export to Europe and Asia by 2035. However, it is facing many challenges, including developing hydrogen fuel storage systems, acquiring the technology required for exporting hydrogen, and building trust in the fuel market. Meanwhile, South Korea has a foundation for developing a hydrogen industry, as it has the highest capacity in the world to produce fuel cells and the ability to manufacture LNG: (liquefied natural gas) carriers. Therefore, South Korea and Russia have sufficient potential to create a new complementary and reciprocal cooperation model in the hydrogen fuel field. This study examines the present and future of Russia’s energy policy in this area as well as discusses South Korea and Russia’s cooperation plans in the hydrogen fuel sector and the related implications. Full article
(This article belongs to the Special Issue Diagnosis and Prognostics of New and Renewable Energy Systems for Safety)
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18 pages, 10913 KiB  
Article
Health Monitoring and Diagnosis System for a Small H-Type Darrieus Vertical-Axis Wind Turbine
by Sungmok Hwang and Cheol Yoo
Energies 2021, 14(21), 7246; https://doi.org/10.3390/en14217246 - 3 Nov 2021
Cited by 2 | Viewed by 2338
Abstract
As the wind power market grows rapidly, the importance of technology for real-time monitoring and diagnosis of wind turbines is increasing. However, most of the developed technologies and research mainly focus on large horizontal-axis wind turbines, and research conducted on small- and medium-sized [...] Read more.
As the wind power market grows rapidly, the importance of technology for real-time monitoring and diagnosis of wind turbines is increasing. However, most of the developed technologies and research mainly focus on large horizontal-axis wind turbines, and research conducted on small- and medium-sized wind turbines is rare. In this study, a novel low-cost and real-time health monitoring and diagnosis system for the small H-type Darrieus vertical axis wind turbine is proposed. Turbine operating conditions were classified into parked/idle and power production. In the case of the power production condition, abnormality diagnosis was performed using key monitoring parameters, including vibration, fundamental frequency, the bending stress of the tower and generator vibration. The turbine abnormalities were diagnosed in two stages by applying the alert and alarm limits, determined by referring to international standards and material properties and the long-term measurement data together. Full article
(This article belongs to the Special Issue Diagnosis and Prognostics of New and Renewable Energy Systems for Safety)
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14 pages, 4840 KiB  
Article
On-Line EIS Measurement for High-Power Fuel Cell Systems Using Simulink Real-Time
by Soo-Bin Han, Hwanyeong Oh, Won-Yong Lee, Jinyeon Won, Suyong Chae and Jongbok Baek
Energies 2021, 14(19), 6133; https://doi.org/10.3390/en14196133 - 26 Sep 2021
Cited by 4 | Viewed by 3614
Abstract
Impedance measurements by EIS are used to build a physical circuit-based model that enables various fault diagnostics and lifetime predictions. These research areas are becoming increasingly crucial for the safety and preventive maintenance of fuel cell power systems. It is challenging to apply [...] Read more.
Impedance measurements by EIS are used to build a physical circuit-based model that enables various fault diagnostics and lifetime predictions. These research areas are becoming increasingly crucial for the safety and preventive maintenance of fuel cell power systems. It is challenging to apply the impedance measurement up to commercial applications at the field level. Although EIS technology has been widely used to measure and analyze the characteristics of fuel cells, EIS is applicable mainly at the single-cell level. In the case of stacks constituting a power generation system in the field, it is difficult to apply EIS due to various limitations in the high-power condition with uncontrollable loads. In this paper, we present a technology that can measure EIS on-line by injecting the perturbation current to fuel cell systems operating in the field. The proposed EIS method is developed based on Simulink Real-Time so that it can be applied to embedded devices. Modeling and simulation of the proposed method are presented, and the procedures from the simulation in virtual space to the real-time application to physical systems are described in detail. Finally, actual usefulness is shown through experiments using two physical systems, an impedance hardware simulator and a fuel cell stack with practical considerations. Full article
(This article belongs to the Special Issue Diagnosis and Prognostics of New and Renewable Energy Systems for Safety)
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