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Recent Advanced Technologies on Renewable Energy (AFORE 2021)

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy Science and Technology".

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 17919

Special Issue Editors

Prof. Dr. Hwachang Song

E-Mail Website
Guest Editor
Department of Electrical Engineering, Seoul National University of Science and Technology, Seoul 139-743, Korea
Interests: energy storage application; renewable energy integration; renewable energy forecasting; smart grids
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Jang-Ho Lee

E-Mail Website
Guest Editor
The Department of Mechanical Engineering, Kunsan Nat’l University, Miryong-dong, Gunsan-si, Jeollabuk-do, Jeolla-do 573-701, Korea
Interests: wind turbine technologies; wind-heat generation; application of carbon composite materials; renewable energy technologies; wind-photo voltaic hybrid system; diesel free islands; aerodynamics of turbomachinery; wind energy potential
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The journal Applied Sciences is currently running a Special Issue entitled “Recent Advanced Technologies on Renewable Energy (AFORE 2021)”. Prof. Dr. Hwachang Song (Seoul National University of Science and Technology, Seoul, South Korea) and Prof. Dr. Jangho Lee (Kunsan National University) are serving as Guest Editors for this issue, and we think you could make an excellent contribution based on your expertise. One of most important strategies for achieving the goal of sustainable environment, according to the international climate action initiatives, is to increase the portion of renewable energy in energy use. Renewable energy resources, however, have the characteristics of intermittence and fluctuation, and there are several technical and economical issues that we need to find solutions.

This Special Issue will bring together those experts, from academic researchers and industrial engineers who present in AFORE 2021, to discuss practical methods and advanced technologies in the renewable energy. The Special Issue covers the whole topics related to renewable energy technologies, including photovoltaics, wind energy, hydrogen & fuel cell, bioenergy, geothermal energy, marine energy, and energy storage application.

Prof. Dr. Hwachang Song
Prof. Dr. Jang-Ho 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. Applied Sciences 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 2400 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

  • photovoltaics
  • wind energy
  • hydrogen & fuel cell
  • bioenergy
  • geothermal energy
  • marin energy
  • energy storage application

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Published Papers (7 papers)

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Editorial

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2 pages, 157 KiB  
Editorial
Special Issue on Recent Advanced Technologies on Renewable Energy (AFORE2021)
by Hwachang Song and Jangho Lee
Appl. Sci. 2023, 13(1), 122; https://doi.org/10.3390/app13010122 - 22 Dec 2022
Viewed by 951
Abstract
One of the most important strategies for achieving the goal of a sustainable environment, according to the international climate action initiatives, is to increase the proportion of renewable energy in energy use [...] Full article
(This article belongs to the Special Issue Recent Advanced Technologies on Renewable Energy (AFORE 2021))

Research

Jump to: Editorial

33 pages, 12518 KiB  
Article
Analysis of Vertical Wind Shear Effects on Offshore Wind Energy Prediction Accuracy Applying Rotor Equivalent Wind Speed and the Relationship with Atmospheric Stability
by Geon Hwa Ryu, Dongjin Kim, Dae-Young Kim, Young-Gon Kim, Sung Jo Kwak, Man Soo Choi, Wonbae Jeon, Bum-Suk Kim and Chae-Joo Moon
Appl. Sci. 2022, 12(14), 6949; https://doi.org/10.3390/app12146949 - 8 Jul 2022
Cited by 9 | Viewed by 3184
Abstract
If the wind speed that passed through a wind turbine rotor disk area is constant, the hub height wind speed (HHWS) could be representative of the wind speed over the rotor disk area. However, this assumption cannot be applied to the large wind [...] Read more.
If the wind speed that passed through a wind turbine rotor disk area is constant, the hub height wind speed (HHWS) could be representative of the wind speed over the rotor disk area. However, this assumption cannot be applied to the large wind turbine, because of the wind shear effect by atmospheric stability. This is because the hub height wind speed cannot represent the vertical wind shear effect from the aerodynamics characteristic on the wind turbine. Using SCADA and offshore LiDAR observation data of the Anholt offshore wind farm, it is investigated whether the rotor equivalent wind speed (REWS) introduced in IEC61400-12-1 can contribute to the improvement of power output forecasting accuracy. The weighted value by separated sector area and vertical wind shear effect by difference between heights can explain the role of energy flux and atmospheric stability on the exact wind energy calculation. The commercial CFD model WindSim is used to calculate power production according to the HHWS and the REWS, and to compare them with the actual AEP of the local wind farm. The classification of atmospheric stability is carried out by Richardson number, which well represents the thermal and physical properties of the atmosphere below the atmospheric boundary layer, along with the wind shear coefficient and turbulence intensity. When atmospheric stability was classified by each stability index, the REWS-based predicted power output was sometimes more accurate than HHWS, but sometimes inferior. However, in most cases, using the REWS, it was possible to calculate an estimate closer to the actual power output. Through the results of this study, it is possible to provide a rationale for which method, REWS or HHWS, can more accurately calculate the expected power output and effectively derive the economic feasibility of the project by identifying the characteristics of local atmospheric stability before the wind farm project. Full article
(This article belongs to the Special Issue Recent Advanced Technologies on Renewable Energy (AFORE 2021))
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17 pages, 2060 KiB  
Article
A Study on Comparison of Temperature Distribution between Aluminum and GFRP Mold under Carbon Spar-Cap Manufacturing Process
by Joong-Hoon Yoon, Jang-Ho Lee and Sang-Il Lee
Appl. Sci. 2022, 12(10), 5220; https://doi.org/10.3390/app12105220 - 21 May 2022
Cited by 1 | Viewed by 1809
Abstract
In this study, temperature distribution as a function of the spar-cap thickness was numerically analyzed using a 20 kW wind carbon blade model. “Realizable k-ε”, which was adopted as a turbulence model for heat transfer analysis, was effective in convection and diffusion calculations. [...] Read more.
In this study, temperature distribution as a function of the spar-cap thickness was numerically analyzed using a 20 kW wind carbon blade model. “Realizable k-ε”, which was adopted as a turbulence model for heat transfer analysis, was effective in convection and diffusion calculations. SC/TETRA, a commercial thermal fluid analysis software, was used to calculate the heat flow from the heat panel to the outside boundary of the simulation model. In order to derive the equation for the temperature between the mold surface and the top surface of the spar-cap, the temperature interval of the heat panel was 10 °C, and the range was from 60 °C to 110 °C. As a result, the temperature distribution of the top surface of the spar-cap was insufficient to cure the Carbon Fiber Reinforced Plastic (CFRP) because the heat did not reach from the mold heat panel to the top surface of the carbon spar-cap. To resolve the problem of heat loss, the equation was derived by dividing the temperature boundary conditions between the mold surface and the spar-cap top surface as a function of the thickness of the carbon laminates. The temperature unevenness in the spar-cap curing process was reduced using the improved boundary condition. In addition, the cases where GFRP and aluminum were applied to the upper mold of the heat panel were compared using the same analysis method. An improvement to reduce the temperature non-uniformity of the spar-cap top surface was studied to solve the non-curing issue of the carbon spar-cap under the manufacturing process. Full article
(This article belongs to the Special Issue Recent Advanced Technologies on Renewable Energy (AFORE 2021))
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13 pages, 5165 KiB  
Article
Allowable Pitch Angle of Aerodynamic Imbalance Due to Individual Pitch Movement for Ultimate Loads on Offshore Wind Turbine Using Artificial Neural Network
by Bae-Sung Kim, Dae-Yi Jung, Yun-Jung Jang and Ki-Weon Kang
Appl. Sci. 2022, 12(10), 5177; https://doi.org/10.3390/app12105177 - 20 May 2022
Cited by 1 | Viewed by 1890
Abstract
This study aims to calculate the ultimate loads through integrated load analysis under aerodynamic imbalance by individual pitch movement of offshore wind turbines, and based on this, to identify the allowable region of the individual pitch angle of the blade. For this, 5 [...] Read more.
This study aims to calculate the ultimate loads through integrated load analysis under aerodynamic imbalance by individual pitch movement of offshore wind turbines, and based on this, to identify the allowable region of the individual pitch angle of the blade. For this, 5 MW offshore wind turbines were modeled using GH-BladedTM based on jacket type substructure data of the NREL-5 MW generic model and Upwind reports. For integrated load analysis, wind speeds were selected: 11 m/s, 14 m/s, 17 m/s, 20 m/s, 22 m/s, and 24 m/s. Ultimate load analysis was performed through the fixed pitch control mode with the individual pitch angles at an interval of 2°, ranging from 0° to 30°. Analysis was performed for the collective pitch control under the same environmental conditions as IPC. Through the comparison of loads at hub for CPC and the individual pitch movement states calculated through integrated load analysis, we identified the allowable pitch angle region where the ultimate loads of the individual pitch movement conditions were less than those of the CPC conditions. Furthermore, pattern analysis was performed using the artificial neural network for numerical modeling of the allowable pitch angle region. The results confirmed a high success rate of over 99%. Based on these results, this study suggested a new model according to the wind speed for the allowable pitch angle region. Full article
(This article belongs to the Special Issue Recent Advanced Technologies on Renewable Energy (AFORE 2021))
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17 pages, 4798 KiB  
Article
Maximization of the Power Production of an Offshore Wind Farm
by Raj Kiran Balakrishnan and Sung-ho Hur
Appl. Sci. 2022, 12(8), 4013; https://doi.org/10.3390/app12084013 - 15 Apr 2022
Cited by 9 | Viewed by 3218
Abstract
Operating wind turbines together as a wind farm can be more advantageous and economical. As a result, onshore and offshore wind farms are being built at a rapid pace around the world. Wake effects, which have a negative impact on overall wind farm [...] Read more.
Operating wind turbines together as a wind farm can be more advantageous and economical. As a result, onshore and offshore wind farms are being built at a rapid pace around the world. Wake effects, which have a negative impact on overall wind farm electricity generation, are one of the key concerns in wind farms. This work concentrates on the maximization of power output from wind farms by ameliorating the wake effect. This work introduces a dynamic wind farm controller that adjusts turbines’ yaw angles or axial induction factors following the flow field conditions to maximize the overall power output of the wind farm. This research examines a real-life offshore wind farm in South Korea and the wind farm controller is evaluated in Wind Farm Simulator (WFSim), a control-oriented dynamic wind farm model environment built by Delft University of Technology. The main contribution of this work includes investigating the impact of wind farm control methods on the power production of a wind farm model that simulates a real-life wind farm. Full article
(This article belongs to the Special Issue Recent Advanced Technologies on Renewable Energy (AFORE 2021))
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19 pages, 1502 KiB  
Article
Distribution System State Estimation Using Model-Optimized Neural Networks
by Doyun Kim, Justin Migo Dolot and Hwachang Song
Appl. Sci. 2022, 12(4), 2073; https://doi.org/10.3390/app12042073 - 16 Feb 2022
Cited by 9 | Viewed by 2925
Abstract
Maintaining reliability during power system operation relies heavily on the operator’s knowledge of the system and its current state. With the increasing complexity of power systems, full system monitoring is needed. Due to the costs to install and maintain measurement devices, a cost-effective [...] Read more.
Maintaining reliability during power system operation relies heavily on the operator’s knowledge of the system and its current state. With the increasing complexity of power systems, full system monitoring is needed. Due to the costs to install and maintain measurement devices, a cost-effective optimal placement is normally employed, and as such, state estimation is used to complete the picture. However, in order to provide accurate state estimates in the current power system climate, the models must be fully expanded to include probabilistic uncertainties and non-linear assets. Recognizing its analogous relationship with state estimation, machine learning and its ability to summarily model unseen and complex relationships between input data is used. Thus, a power system state estimator was developed using modified long short-term (LSTM) neural networks to provide quicker and more accurate state estimates over the conventional weighted least squares-based state estimator (WLS-SE). The networks are then subject to standard polynomial scheduled weight pruning to further optimize the size and memory consumption of the neural networks. The state estimators were tested on a hybrid AC/DC distribution system composed of the IEEE 34-bus AC test system and a 9-bus DC microgrid. The conventional WLS-SE has achieved a root mean square error (RMSE) of 0.0151 p.u. for voltage magnitude estimates, while the LSTM’s were able to achieve RMSE’s between 0.0019 p.u. and 0.0087 p.u., with the latter having 75% weight sparsity, estimates about ten times faster, and half of its full memory requirement occupied. Full article
(This article belongs to the Special Issue Recent Advanced Technologies on Renewable Energy (AFORE 2021))
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22 pages, 7250 KiB  
Article
Leakage Current Mitigation of Photovoltaic System Using Optimized Predictive Control for Improved Efficiency
by Abhinandan Routray and Sung-Ho Hur
Appl. Sci. 2022, 12(2), 643; https://doi.org/10.3390/app12020643 - 10 Jan 2022
Cited by 6 | Viewed by 2651
Abstract
This paper proposes an optimized predictive control strategy to mitigate the potential leakage current of grid-tied photovoltaic (PV) systems to improve the lifespans of PV modules. In this work, the PV system is controlled with an optimized predictive control algorithm that selects the [...] Read more.
This paper proposes an optimized predictive control strategy to mitigate the potential leakage current of grid-tied photovoltaic (PV) systems to improve the lifespans of PV modules. In this work, the PV system is controlled with an optimized predictive control algorithm that selects the switching voltage vectors intelligently to reduce the number of computational burdens. Thus, it improves the dynamic performance of the overall system. This is achieved through a specific cost function that minimizes the change in common-mode voltage generated by the parasitic capacitance of PV modules. The proposed controller does not require any additional modulation schemes. Normalization techniques and weighting factors are incorporated to obtain improved results. The steady state and dynamic performance of the proposed control scheme is validated in this work through simulations and a 600 W experimental laboratory prototype. Full article
(This article belongs to the Special Issue Recent Advanced Technologies on Renewable Energy (AFORE 2021))
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