Pub Date : 2023-01-01DOI: 10.20508/ijrer.v13i2.14191.g8730
{"title":"Thermal Conductivity of a Vacuum Fractal Solar Collector","authors":"","doi":"10.20508/ijrer.v13i2.14191.g8730","DOIUrl":"https://doi.org/10.20508/ijrer.v13i2.14191.g8730","url":null,"abstract":"","PeriodicalId":14385,"journal":{"name":"International Journal of Renewable Energy Research","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67638913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.20508/ijrer.v13i3.14163.g8799
A Photovoltaic-Thermal-Solar-Collector (PVT) is a technology that combines the benefits of photovoltaic panels (PV) and solar-thermal-collectors. It can enhance the efficiency of PV by reducing its surface temperature while producing hot water. The PVT's photovoltaic, thermal, and combined-photovoltaic-thermal efficiencies with parallel twisted absorber tubes and nanofluids as working fluids have been determined. A total of 11 parallel twisted absorber riser tubes with headers were used. The optimum header tube diameter was 51mm using Computational-Fluid-Dynamics (CFD) simulations. The utilization of twisted tubes significantly improved the photovoltaic, thermal, and combined-photovoltaic-thermal efficiencies, with the combined-photovoltaic-thermal efficiency rising from 61.2% to 84.6% at a mass-flow-rate of 0.04kg/s and solar-irradiance-level of 800W/m 2 . The effect of employing nanofluids on the PVT system was investigated, with nanofluids contributing to even greater gains in combined photovoltaic-thermal efficiency, which increased from 84.6% to 88.2%. These findings provide valuable insights into the design of high-performance fluid-based PVT systems, highlighting the potential of twisted tubes and nanofluids for enhancing system efficiency.
{"title":"Enhancing the Performance of Photovoltaic Thermal Solar Collectors using Twisted Absorber Tubes and Nanofluids with Optimal Design Parameters","authors":"","doi":"10.20508/ijrer.v13i3.14163.g8799","DOIUrl":"https://doi.org/10.20508/ijrer.v13i3.14163.g8799","url":null,"abstract":"A Photovoltaic-Thermal-Solar-Collector (PVT) is a technology that combines the benefits of photovoltaic panels (PV) and solar-thermal-collectors. It can enhance the efficiency of PV by reducing its surface temperature while producing hot water. The PVT's photovoltaic, thermal, and combined-photovoltaic-thermal efficiencies with parallel twisted absorber tubes and nanofluids as working fluids have been determined. A total of 11 parallel twisted absorber riser tubes with headers were used. The optimum header tube diameter was 51mm using Computational-Fluid-Dynamics (CFD) simulations. The utilization of twisted tubes significantly improved the photovoltaic, thermal, and combined-photovoltaic-thermal efficiencies, with the combined-photovoltaic-thermal efficiency rising from 61.2% to 84.6% at a mass-flow-rate of 0.04kg/s and solar-irradiance-level of 800W/m 2 . The effect of employing nanofluids on the PVT system was investigated, with nanofluids contributing to even greater gains in combined photovoltaic-thermal efficiency, which increased from 84.6% to 88.2%. These findings provide valuable insights into the design of high-performance fluid-based PVT systems, highlighting the potential of twisted tubes and nanofluids for enhancing system efficiency.","PeriodicalId":14385,"journal":{"name":"International Journal of Renewable Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135213710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.20508/ijrer.v13i3.14033.g8810
{"title":"Design and Experimental Investigation of Three-Phase Inductive Type Superconducting Fault Current Limiter based on Current Injection Method","authors":"","doi":"10.20508/ijrer.v13i3.14033.g8810","DOIUrl":"https://doi.org/10.20508/ijrer.v13i3.14033.g8810","url":null,"abstract":"","PeriodicalId":14385,"journal":{"name":"International Journal of Renewable Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135214211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.20508/ijrer.v13i3.13946.g8791
The utilization of renewable energy sources, such as solar and wind power, has gained significant momentum in recent years due to concerns about the environmental impact of traditional fossil fuels and the desire for energy independence. Governments, organizations, and individuals around the world are investing in and implementing renewable energy systems at an increasing rate. One such issue is the uneven power generation in large solar panel farms, where different zones are affected by varying weather and sun irradiance conditions. This results in a disparity in power generation between zones. In order to address this problem, this paper proposes a solution of incorporating small PV panels that will act like a PV detector in each zone, which are affected by the same weather and irradiance conditions and have the same azimuth and tilt angles to estimate the output power of PV panels. The PV detector will be loaded to their maximum capacity using a Power Electronic Controller (PEC) of MPPT algorithms cascaded with a well-designed topology that maintain the MPPT is working at its maximum load in all cases. By comparing the instantaneous power generated and the maximum power that can be delivered by the PV detector to the PEC, the power of the zone can be accurately determined. In addition, to our MATLAB simulation that allow us to implement in real life our theory and being industry applicable with results approximately equal to results shown in MATLAB.
{"title":"A Power Electronic Controller Based Algorithm for Output Power Prediction of a PV Panel","authors":"","doi":"10.20508/ijrer.v13i3.13946.g8791","DOIUrl":"https://doi.org/10.20508/ijrer.v13i3.13946.g8791","url":null,"abstract":"The utilization of renewable energy sources, such as solar and wind power, has gained significant momentum in recent years due to concerns about the environmental impact of traditional fossil fuels and the desire for energy independence. Governments, organizations, and individuals around the world are investing in and implementing renewable energy systems at an increasing rate. One such issue is the uneven power generation in large solar panel farms, where different zones are affected by varying weather and sun irradiance conditions. This results in a disparity in power generation between zones. In order to address this problem, this paper proposes a solution of incorporating small PV panels that will act like a PV detector in each zone, which are affected by the same weather and irradiance conditions and have the same azimuth and tilt angles to estimate the output power of PV panels. The PV detector will be loaded to their maximum capacity using a Power Electronic Controller (PEC) of MPPT algorithms cascaded with a well-designed topology that maintain the MPPT is working at its maximum load in all cases. By comparing the instantaneous power generated and the maximum power that can be delivered by the PV detector to the PEC, the power of the zone can be accurately determined. In addition, to our MATLAB simulation that allow us to implement in real life our theory and being industry applicable with results approximately equal to results shown in MATLAB.","PeriodicalId":14385,"journal":{"name":"International Journal of Renewable Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135214219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.20508/ijrer.v13i3.14070.g8806
Wind resource assessments are required to identify a specific area capable of producing valuable energy from wind speeds. This paper aims to optimize wind assessment through wind farm siting and layout in Indonesia’s semi-arid region. Wind data collected on Sumba Island over a one-year period was analyzed to assess the area's wind energy potential. Wind Atlas Analysis and Application Programme (WAsP) and Windographer were used to generate a generalized wind climate and resource maps for the area. Wind farm layout and preliminary turbine micro-sitting were completed with various scenarios in mind to achieve the best possible result. Four different scenarios are considered to maximize power output. There are 34 identical wind turbines with a unit capacity of 90 kW in Scenario 1. Scenario 2 includes 20 identical wind turbines with a total capacity of 3000 kW. In Scenario 3, 14 identical wind turbines with 225 kW of unit capacity are used. There are 12 identical wind turbines with a unit capacity of 250 kW in Scenario 4. The results showed that scenario 1 produced the highest total net Annual Energy Production (AEP) of 11,287 MWh/year with a 3.73 % wake loss. The minimum wake loss seemed to be 2.62 % in scenario 4, with a total net AEP of 10,22MWh/year.
需要对风力资源进行评估，以确定能够从风速中产生有价值能源的特定区域。本文旨在通过印尼半干旱地区风电场的选址和布局来优化风力评价。研究人员分析了在松巴岛上收集的一年来的风能数据，以评估该地区的风能潜力。利用Wind Atlas Analysis and Application program (WAsP)和Windographer生成了该地区的广义风气候和资源图。风电场布局和初步的涡轮机微安装在不同的场景中完成，以达到最好的结果。考虑了四种不同的场景来最大化功率输出。在情景1中，有34台相同的风力涡轮机，单位容量为90千瓦。场景2包括20台相同的风力涡轮机，总容量为3000千瓦。在方案3中，使用14台相同的风力涡轮机，单位容量为225千瓦。在情景4中，有12台相同的风力涡轮机，单位容量为250千瓦。结果表明，情景1产生的年净能源产量(AEP)最高，为11,287 MWh/年，尾迹损失为3.73%。在方案4中，最小尾迹损失似乎为2.62%，总净AEP为10,22兆瓦时/年。
{"title":"Optimizing Turbine Siting and Wind Farm Layout in Indonesia","authors":"","doi":"10.20508/ijrer.v13i3.14070.g8806","DOIUrl":"https://doi.org/10.20508/ijrer.v13i3.14070.g8806","url":null,"abstract":"Wind resource assessments are required to identify a specific area capable of producing valuable energy from wind speeds. This paper aims to optimize wind assessment through wind farm siting and layout in Indonesia’s semi-arid region. Wind data collected on Sumba Island over a one-year period was analyzed to assess the area's wind energy potential. Wind Atlas Analysis and Application Programme (WAsP) and Windographer were used to generate a generalized wind climate and resource maps for the area. Wind farm layout and preliminary turbine micro-sitting were completed with various scenarios in mind to achieve the best possible result. Four different scenarios are considered to maximize power output. There are 34 identical wind turbines with a unit capacity of 90 kW in Scenario 1. Scenario 2 includes 20 identical wind turbines with a total capacity of 3000 kW. In Scenario 3, 14 identical wind turbines with 225 kW of unit capacity are used. There are 12 identical wind turbines with a unit capacity of 250 kW in Scenario 4. The results showed that scenario 1 produced the highest total net Annual Energy Production (AEP) of 11,287 MWh/year with a 3.73 % wake loss. The minimum wake loss seemed to be 2.62 % in scenario 4, with a total net AEP of 10,22MWh/year.","PeriodicalId":14385,"journal":{"name":"International Journal of Renewable Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135214228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.20508/ijrer.v13i1.13388.g8678
{"title":"A Review of Voltage Stability Issues in Distribution System Influenced By High PV Penetration and Its Mitigation Techniques","authors":"","doi":"10.20508/ijrer.v13i1.13388.g8678","DOIUrl":"https://doi.org/10.20508/ijrer.v13i1.13388.g8678","url":null,"abstract":"","PeriodicalId":14385,"journal":{"name":"International Journal of Renewable Energy Research","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67637426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.20508/ijrer.v13i1.13810.g8677
{"title":"Renewable Energy Literature in Turkey: Mapping Analysis of the Field and Future Study Suggestions on Overlooked Issues","authors":"","doi":"10.20508/ijrer.v13i1.13810.g8677","DOIUrl":"https://doi.org/10.20508/ijrer.v13i1.13810.g8677","url":null,"abstract":"","PeriodicalId":14385,"journal":{"name":"International Journal of Renewable Energy Research","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67637882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.20508/ijrer.v13i1.13548.g8671
{"title":"Energy Management System and Enhancement of Power Quality with Grid Integrated Micro-grid using Adaptive Fuzzy Logic Controller","authors":"","doi":"10.20508/ijrer.v13i1.13548.g8671","DOIUrl":"https://doi.org/10.20508/ijrer.v13i1.13548.g8671","url":null,"abstract":"","PeriodicalId":14385,"journal":{"name":"International Journal of Renewable Energy Research","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67637970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.20508/ijrer.v13i2.13530.g8753
Noureddine Akoubi, J. B. Salem, L. E. Amraoui
-This paper proposes an approach based on artificial neural networks (ANN) to control a grid-connected photovoltaic system (PVS) under partial shading (PS) conditions. In PS conditions, the P-V curve exhibits multiple peaks, with only one representing the global maximum power point (GMPP), and the others representing local maximum power points (LMPP). Traditional Maximum Power Point Tracking (MPPT) methods are unable to identify the GMPP and get stuck around an LMPP, which results in reduced productivity of the PVS. The proposed approach combines supervised learning (SL) and deep reinforcement learning (DRL) techniques to design a controller with a hierarchical structure that can overcome the problem of identifying the GMPP in PVSs under PS conditions. The PVS under study consists of four identical solar panels. At the first control level, each solar panel has a sub-controller designed using ANN and the SL technique, which determines the appropriate duty cycle to extract the maximum power from the solar panel based on real-time weather conditions. At the second level, a DRL agent identifies the optimal duty cycle for the DC/DC converter from the duty cycles generated by the sub-controllers. The Deep Deterministic Policy Gradient (DDPG) and Twin Delayed DDPG (TD3) agents are implemented and evaluated for the second level of control. Simulation results using MATLAB/Simulink demonstrate the effectiveness of the proposed controller in tracking the GMPP.
{"title":"Combination of artificial neural network-based approaches to control a grid-connected photovoltaic source under partial shading condition","authors":"Noureddine Akoubi, J. B. Salem, L. E. Amraoui","doi":"10.20508/ijrer.v13i2.13530.g8753","DOIUrl":"https://doi.org/10.20508/ijrer.v13i2.13530.g8753","url":null,"abstract":"-This paper proposes an approach based on artificial neural networks (ANN) to control a grid-connected photovoltaic system (PVS) under partial shading (PS) conditions. In PS conditions, the P-V curve exhibits multiple peaks, with only one representing the global maximum power point (GMPP), and the others representing local maximum power points (LMPP). Traditional Maximum Power Point Tracking (MPPT) methods are unable to identify the GMPP and get stuck around an LMPP, which results in reduced productivity of the PVS. The proposed approach combines supervised learning (SL) and deep reinforcement learning (DRL) techniques to design a controller with a hierarchical structure that can overcome the problem of identifying the GMPP in PVSs under PS conditions. The PVS under study consists of four identical solar panels. At the first control level, each solar panel has a sub-controller designed using ANN and the SL technique, which determines the appropriate duty cycle to extract the maximum power from the solar panel based on real-time weather conditions. At the second level, a DRL agent identifies the optimal duty cycle for the DC/DC converter from the duty cycles generated by the sub-controllers. The Deep Deterministic Policy Gradient (DDPG) and Twin Delayed DDPG (TD3) agents are implemented and evaluated for the second level of control. Simulation results using MATLAB/Simulink demonstrate the effectiveness of the proposed controller in tracking the GMPP.","PeriodicalId":14385,"journal":{"name":"International Journal of Renewable Energy Research","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67638312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.20508/ijrer.v13i2.13892.g8726
{"title":"Spatial Modeling for Determining Electric Vehicle Charging Station Allocation in North Jakarta","authors":"","doi":"10.20508/ijrer.v13i2.13892.g8726","DOIUrl":"https://doi.org/10.20508/ijrer.v13i2.13892.g8726","url":null,"abstract":"","PeriodicalId":14385,"journal":{"name":"International Journal of Renewable Energy Research","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67638594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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