B. M. L, T. Sripriya, B. Muthuraj, D. Kumar, V. Venkatesh, Badireddy Satya Sridevi, Munaga Masthan Siva Krishna, K. Rajan, Abdi Diriba
Currently, we are trying to get electricity in alternative ways. Many solar powered water heaters have come up to use water heaters. However, these tools are not 100 percent fully effective. The device we have manufactured is an automatic device that runs in the direction of sunlight. The device runs automatically in the morning facing east and in the evening facing west. In this instrument, the defective one-inch tube lamp and the three-quarter-inch tube lamp are put together and connected in series. In this paper, a smart deep learning model was proposed to improve the performance of the solar water heater. The gap between the tube lights is filled with methane gas, and the tube inside is filled with water. The water thus filled is heated by sunlight. Methane gas acts as a fast conductor of solar heat. An electronic control device is placed to determine the temperature of the hot water and to expel the hot water. This device can heat at least 10 liters of water in 15 minutes. Increasing the number of incandescent tube lights can heat up a large amount of water when this device is set up, or it can be designed by replacing tube lights with a series of large glass tubes using the same technology. This tool can be manufactured at low cost so that people from all walks of life can use it.
{"title":"Deep Learning-Based Smart Hybrid Solar Water Heater Erection Model to Extract Maximum Energy","authors":"B. M. L, T. Sripriya, B. Muthuraj, D. Kumar, V. Venkatesh, Badireddy Satya Sridevi, Munaga Masthan Siva Krishna, K. Rajan, Abdi Diriba","doi":"10.1155/2022/2943386","DOIUrl":"https://doi.org/10.1155/2022/2943386","url":null,"abstract":"Currently, we are trying to get electricity in alternative ways. Many solar powered water heaters have come up to use water heaters. However, these tools are not 100 percent fully effective. The device we have manufactured is an automatic device that runs in the direction of sunlight. The device runs automatically in the morning facing east and in the evening facing west. In this instrument, the defective one-inch tube lamp and the three-quarter-inch tube lamp are put together and connected in series. In this paper, a smart deep learning model was proposed to improve the performance of the solar water heater. The gap between the tube lights is filled with methane gas, and the tube inside is filled with water. The water thus filled is heated by sunlight. Methane gas acts as a fast conductor of solar heat. An electronic control device is placed to determine the temperature of the hot water and to expel the hot water. This device can heat at least 10 liters of water in 15 minutes. Increasing the number of incandescent tube lights can heat up a large amount of water when this device is set up, or it can be designed by replacing tube lights with a series of large glass tubes using the same technology. This tool can be manufactured at low cost so that people from all walks of life can use it.","PeriodicalId":14195,"journal":{"name":"International Journal of Photoenergy","volume":"1 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64774267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Eugen Zimmermann, K. Wong, T. Seewald, J. Kalb, J. Steffens, G. Hahn, L. Schmidt‐Mende
Atmospheric Pressure Spatial Atomic Layer Deposition (AP-SALD) is an upcoming deposition technique suitable for a variety of materials and combines the benefits of a regular atomic layer deposition with a significantly increased deposition rate at ambient conditions. In this work, amorphous and anatase TiO2 layers are fabricated by AP-SALD via systematic variation of process conditions such as temperature, reactant (H2O and O3), and posttreatment. The formed layers are characterized for their structural and optoelectronic properties and utilized as a hole-blocking layer in hybrid perovskite solar cells. It is found that TiO2 layers fabricated at elevated deposition temperatures possess strong anatase character but expose an unfavorable interface to the perovskite layer, promoting recombination and lowering the shunt resistance and open circuit voltage of the solar cells. Therefore, the interface is essential for efficient charge extraction, which can be significantly improved by controlling the process parameters.
{"title":"Controlled Crystallinity of TiO2 Layers Grown by Atmospheric Pressure Spatial Atomic Layer Deposition and their Impact on Perovskite Solar Cell Efficiency","authors":"Eugen Zimmermann, K. Wong, T. Seewald, J. Kalb, J. Steffens, G. Hahn, L. Schmidt‐Mende","doi":"10.1155/2022/1172871","DOIUrl":"https://doi.org/10.1155/2022/1172871","url":null,"abstract":"Atmospheric Pressure Spatial Atomic Layer Deposition (AP-SALD) is an upcoming deposition technique suitable for a variety of materials and combines the benefits of a regular atomic layer deposition with a significantly increased deposition rate at ambient conditions. In this work, amorphous and anatase TiO2 layers are fabricated by AP-SALD via systematic variation of process conditions such as temperature, reactant (H2O and O3), and posttreatment. The formed layers are characterized for their structural and optoelectronic properties and utilized as a hole-blocking layer in hybrid perovskite solar cells. It is found that TiO2 layers fabricated at elevated deposition temperatures possess strong anatase character but expose an unfavorable interface to the perovskite layer, promoting recombination and lowering the shunt resistance and open circuit voltage of the solar cells. Therefore, the interface is essential for efficient charge extraction, which can be significantly improved by controlling the process parameters.","PeriodicalId":14195,"journal":{"name":"International Journal of Photoenergy","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43555569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ahmad S. Almadhor, K. Mallikarjuna, R. Rahul, G. Chandra Shekara, Rishu Bhatia, Wesam Shishah, V. Mohanavel, S. Suresh Kumar, Sojan Palukaran Thimothy
Presently, photovoltaic systems are an essential part of the development of renewable energy. Due to the inherent dependence of solar energy production on climate variations, forecasting power production using weather data has a number of financial advantages, including dependable proactive power trading and operation planning. Megacity electricity generation is regarded as a current research problem in the modern features of urban administration, particularly in developing nations such as Iran. Machine learning could be used to identify renewable resources like transformational participation (TP) and photovoltaic (PV) technology; based on resident motivational strategies, the smart city concept offers a revolutionary suggestion for supplying power in a metropolitan region. The sustainable development agenda is introduced at the same time as this approach. Therefore, the article’s goals are to estimate Mashhad, Iran’s electrical power needs using machine learning technologies and to make innovative suggestions for motivating people to generate renewable energy based on the expertise of experts. The potential of solar power over the course of a year is then assessed in our research study in Mashhad, Iran, using the solar photovoltaic modelling tool. The present idea in this research uses linear regression techniques to forecast utilising artificial neural networks (ANN). The most important factor in sizing the installation of solar power producing units is the daily mean sun irradiation. The amount of power that will be produced by solar panels can be estimated using the mean sun irradiance at a particular spot. A precise prediction can also be used to determine the complexity of the system, return on investment (ROI), and system load metrics. Several regression techniques and solar irradiance-related metrics have been combined to forecast the mean sun irradiation in terms of kilowatt hours per square metre. Azimuth and zenith factors considerably enhance the performance of the model, as demonstrated by the proposed method. The results of this study demonstrate 99.9% reliability rate for ANN model prediction of the electrical power usage during the summer and winter seasons. Thus, the maximum of power requirement during the hottest and coolest periods can be managed by using the photovoltaic system’s renewable power projections.
{"title":"Solar Power Generation in Smart Cities Using an Integrated Machine Learning and Statistical Analysis Methods","authors":"Ahmad S. Almadhor, K. Mallikarjuna, R. Rahul, G. Chandra Shekara, Rishu Bhatia, Wesam Shishah, V. Mohanavel, S. Suresh Kumar, Sojan Palukaran Thimothy","doi":"10.1155/2022/5442304","DOIUrl":"https://doi.org/10.1155/2022/5442304","url":null,"abstract":"Presently, photovoltaic systems are an essential part of the development of renewable energy. Due to the inherent dependence of solar energy production on climate variations, forecasting power production using weather data has a number of financial advantages, including dependable proactive power trading and operation planning. Megacity electricity generation is regarded as a current research problem in the modern features of urban administration, particularly in developing nations such as Iran. Machine learning could be used to identify renewable resources like transformational participation (TP) and photovoltaic (PV) technology; based on resident motivational strategies, the smart city concept offers a revolutionary suggestion for supplying power in a metropolitan region. The sustainable development agenda is introduced at the same time as this approach. Therefore, the article’s goals are to estimate Mashhad, Iran’s electrical power needs using machine learning technologies and to make innovative suggestions for motivating people to generate renewable energy based on the expertise of experts. The potential of solar power over the course of a year is then assessed in our research study in Mashhad, Iran, using the solar photovoltaic modelling tool. The present idea in this research uses linear regression techniques to forecast utilising artificial neural networks (ANN). The most important factor in sizing the installation of solar power producing units is the daily mean sun irradiation. The amount of power that will be produced by solar panels can be estimated using the mean sun irradiance at a particular spot. A precise prediction can also be used to determine the complexity of the system, return on investment (ROI), and system load metrics. Several regression techniques and solar irradiance-related metrics have been combined to forecast the mean sun irradiation in terms of kilowatt hours per square metre. Azimuth and zenith factors considerably enhance the performance of the model, as demonstrated by the proposed method. The results of this study demonstrate 99.9% reliability rate for ANN model prediction of the electrical power usage during the summer and winter seasons. Thus, the maximum of power requirement during the hottest and coolest periods can be managed by using the photovoltaic system’s renewable power projections.","PeriodicalId":14195,"journal":{"name":"International Journal of Photoenergy","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42917946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Komala C R, S. Vimal, G. Ravindra, P. Hariramakrishnan, S. Razia, S. Geerthik, K. Raja, V. Mohanavel, Nedumaran Arappali
The outer surface of the building is the same size as its premises, with greater heat loss. Therefore, when building, renovating, or expanding apartment, if possible, avoid all kinds of spaces, ledges, and lodges in the walls. It makes sense to build unheated exterior buildings on the north side of the apartment. The storage rooms for garden tools and bicycles, technical buildings protect the warm part of the house from wind and cold. In the most common design of a private apartment, the energy consumption for heating is 110-130 kW per 1 m2 per year. In this paper, an energy distribution model was proposed to estimate the photo energy with the help of deep learning model. A small apartment not only uses less energy but also requires lower construction costs. An energy-efficient apartment is a building with a low-energy consumption and comfortable microclimate. Energy savings in such homes can be up to 90%. Annual heat demand can be less than 15 kWh per square meter of energy-efficient home.
{"title":"Deep Learning for an Innovative Photo Energy Model to Estimate the Energy Distribution in Smart Apartments","authors":"Komala C R, S. Vimal, G. Ravindra, P. Hariramakrishnan, S. Razia, S. Geerthik, K. Raja, V. Mohanavel, Nedumaran Arappali","doi":"10.1155/2022/1048378","DOIUrl":"https://doi.org/10.1155/2022/1048378","url":null,"abstract":"The outer surface of the building is the same size as its premises, with greater heat loss. Therefore, when building, renovating, or expanding apartment, if possible, avoid all kinds of spaces, ledges, and lodges in the walls. It makes sense to build unheated exterior buildings on the north side of the apartment. The storage rooms for garden tools and bicycles, technical buildings protect the warm part of the house from wind and cold. In the most common design of a private apartment, the energy consumption for heating is 110-130 kW per 1 m2 per year. In this paper, an energy distribution model was proposed to estimate the photo energy with the help of deep learning model. A small apartment not only uses less energy but also requires lower construction costs. An energy-efficient apartment is a building with a low-energy consumption and comfortable microclimate. Energy savings in such homes can be up to 90%. Annual heat demand can be less than 15 kWh per square meter of energy-efficient home.","PeriodicalId":14195,"journal":{"name":"International Journal of Photoenergy","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2022-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43362017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ahmed A. S. Alothman, M. Ahmed, S. Radjarejesri, G. Ramkumar, R. Prasad, P. Lakshmi, M. Sillanpaa, Subash Thanappan
<jats:p>This study takes place in year of 2021 during the premonsoon and postmonsoon seasons and twenty water samples were collected. Chemical factors like chloride, fluoride, sulphate, nitrate, and phosphate were measured in water samples. There is a significant difference in anion dominance between pre- and postmonsoonal (PRM and POM) water samples. The following anions are <jats:inline-formula> <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <mtext>HC</mtext> <msub> <mrow> <mtext>O</mtext> </mrow> <mrow> <mn>3</mn> </mrow> </msub> <mo>></mo> <mtext>TDS</mtext> <mo>></mo> <mtext>C</mtext> <msup> <mrow> <mtext>l</mtext> </mrow> <mrow> <mo>−</mo> </mrow> </msup> <mo>></mo> <mtext>S</mtext> <msup> <mrow> <msub> <mrow> <mtext>O</mtext> </mrow> <mrow> <mn>4</mn> </mrow> </msub> </mrow> <mrow> <mn>2</mn> <mo>−</mo> </mrow> </msup> <mo>></mo> <mtext>TH</mtext> <mo>></mo> <mtext>N</mtext> <msub> <mrow> <mtext>O</mtext> </mrow> <mrow> <mn>3</mn> </mrow> </msub> <mo>></mo> <msup> <mrow> <mtext>F</mtext> </mrow> <mrow> <mo>−</mo> </mrow> </msup> <mo>></mo> <mtext>P</mtext> <msub> <mrow> <mtext>O</mtext> </mrow> <mrow>
本研究于2021年季风前和季风后季节进行，收集了20个水样。在水样中测量了氯化物、氟化物、硫酸盐、硝酸盐和磷酸盐等化学因素。阴离子优势在季风前和季风后(PRM和POM)水样中有显著差异。 下面的阴离子是HC O 3 > TDS >c1−> 0 0 42 - >0 - > n - 3 >F−> p o 4TDS b> h3c3−> 0 0 42−> C 1−> TH > NO 3−>F−> p o 4− . 在这两个季节里，阳离子的特殊方式是Na + > + ca2 +Mg 2 + K+ .利用SAR、凯利比、剩余碳酸钠、潜在盐度、渗透指数和钠含量对灌溉水水质进行评价。为了调查地下水的地球化学规律和水文地球化学，采用了两种方法:根据调查结果，确定了各调查地区的地下水不适合人类使用。
{"title":"Estimation of Groundwater Quality in Arid Region or Semiarid Region by Using Statistical Methods and Geographical Information System Technique","authors":"Ahmed A. S. Alothman, M. Ahmed, S. Radjarejesri, G. Ramkumar, R. Prasad, P. Lakshmi, M. Sillanpaa, Subash Thanappan","doi":"10.1155/2022/7902301","DOIUrl":"https://doi.org/10.1155/2022/7902301","url":null,"abstract":"<jats:p>This study takes place in year of 2021 during the premonsoon and postmonsoon seasons and twenty water samples were collected. Chemical factors like chloride, fluoride, sulphate, nitrate, and phosphate were measured in water samples. There is a significant difference in anion dominance between pre- and postmonsoonal (PRM and POM) water samples. The following anions are <jats:inline-formula>\u0000 <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M1\">\u0000 <mtext>HC</mtext>\u0000 <msub>\u0000 <mrow>\u0000 <mtext>O</mtext>\u0000 </mrow>\u0000 <mrow>\u0000 <mn>3</mn>\u0000 </mrow>\u0000 </msub>\u0000 <mo>></mo>\u0000 <mtext>TDS</mtext>\u0000 <mo>></mo>\u0000 <mtext>C</mtext>\u0000 <msup>\u0000 <mrow>\u0000 <mtext>l</mtext>\u0000 </mrow>\u0000 <mrow>\u0000 <mo>−</mo>\u0000 </mrow>\u0000 </msup>\u0000 <mo>></mo>\u0000 <mtext>S</mtext>\u0000 <msup>\u0000 <mrow>\u0000 <msub>\u0000 <mrow>\u0000 <mtext>O</mtext>\u0000 </mrow>\u0000 <mrow>\u0000 <mn>4</mn>\u0000 </mrow>\u0000 </msub>\u0000 </mrow>\u0000 <mrow>\u0000 <mn>2</mn>\u0000 <mo>−</mo>\u0000 </mrow>\u0000 </msup>\u0000 <mo>></mo>\u0000 <mtext>TH</mtext>\u0000 <mo>></mo>\u0000 <mtext>N</mtext>\u0000 <msub>\u0000 <mrow>\u0000 <mtext>O</mtext>\u0000 </mrow>\u0000 <mrow>\u0000 <mn>3</mn>\u0000 </mrow>\u0000 </msub>\u0000 <mo>></mo>\u0000 <msup>\u0000 <mrow>\u0000 <mtext>F</mtext>\u0000 </mrow>\u0000 <mrow>\u0000 <mo>−</mo>\u0000 </mrow>\u0000 </msup>\u0000 <mo>></mo>\u0000 <mtext>P</mtext>\u0000 <msub>\u0000 <mrow>\u0000 <mtext>O</mtext>\u0000 </mrow>\u0000 <mrow>\u0000 ","PeriodicalId":14195,"journal":{"name":"International Journal of Photoenergy","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2022-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41543889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Perovskite solar cells (PSCs) were fabricated using a two-step spin-coating method with MACl added to the inorganic layer. The properties of the perovskite films were characterized by SEM, XRD, PL, UV-vis spectra, etc. The morphology of the PbI2 film was significantly changed, and the formation of MACl-related intermediate phase was observed at the grain boundaries. The grain size and crystallinity of the perovskite film increased, and the morphology at grain boundaries was optimized, while the composition of perovskite remained unchanged. The introduction of MACl improved the open circuit voltage ( V OC ) and fill factor ( FF ) of PSCs, and the optimal device efficiency reached 21.59%. This paper presents a new approach using additives in inorganic layers to optimize the crystallization process for efficient PSCs.
{"title":"Methylammonium Chloride Additive in Lead Iodide Optimizing the Crystallization Process for Efficient Perovskite Solar Cells","authors":"Hongqiao Wang, Jingquan Zhang","doi":"10.1155/2022/5288400","DOIUrl":"https://doi.org/10.1155/2022/5288400","url":null,"abstract":"Perovskite solar cells (PSCs) were fabricated using a two-step spin-coating method with MACl added to the inorganic layer. The properties of the perovskite films were characterized by SEM, XRD, PL, UV-vis spectra, etc. The morphology of the PbI2 film was significantly changed, and the formation of MACl-related intermediate phase was observed at the grain boundaries. The grain size and crystallinity of the perovskite film increased, and the morphology at grain boundaries was optimized, while the composition of perovskite remained unchanged. The introduction of MACl improved the open circuit voltage (\u0000 \u0000 \u0000 \u0000 V\u0000 \u0000 \u0000 OC\u0000 \u0000 \u0000 \u0000 ) and fill factor (\u0000 \u0000 FF\u0000 \u0000 ) of PSCs, and the optimal device efficiency reached 21.59%. This paper presents a new approach using additives in inorganic layers to optimize the crystallization process for efficient PSCs.","PeriodicalId":14195,"journal":{"name":"International Journal of Photoenergy","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2022-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45937945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Prasad, J. Samson Isaac, P. Ponsudha, N. Nithya, S. Shinde, S. Gopal, Atul Sarojwal, K. Karthikumar, Kibrom Menasbo Hadish
Performance, cost, and aesthetics are all difficult to beat in today’s expanding distributed rooftop solar sector, and flat-plate PV is no exception. Photovoltaics will be able to take advantage of some of their most significant advantages as a result of this marketplace, including the elimination of transmission losses and the generation of power at the point of sale. Concentrated photovoltaic (CPV) technology, on the other hand, represents a viable alternative in the quest for ever-lower normalised energy costs and ever-shorter energy payback times. Material, components, and manufacturing techniques from allied sectors, particularly the power electronics industry, have been adapted to lower system costs and time-to-market for the system under development. The LFR is less than 30 mm wide to maximise thermal efficiency, and a densely packed cell array has been used to maximise electrical output. The Matlab simulations show that the proposed machine learning-based LFR technique has a greater concentration rate than the present LFR method, as demonstrated by the results.
{"title":"A Machine Learning-Based Novel Energy Optimization Algorithm in a Photovoltaic Solar Power System","authors":"K. Prasad, J. Samson Isaac, P. Ponsudha, N. Nithya, S. Shinde, S. Gopal, Atul Sarojwal, K. Karthikumar, Kibrom Menasbo Hadish","doi":"10.1155/2022/2845755","DOIUrl":"https://doi.org/10.1155/2022/2845755","url":null,"abstract":"Performance, cost, and aesthetics are all difficult to beat in today’s expanding distributed rooftop solar sector, and flat-plate PV is no exception. Photovoltaics will be able to take advantage of some of their most significant advantages as a result of this marketplace, including the elimination of transmission losses and the generation of power at the point of sale. Concentrated photovoltaic (CPV) technology, on the other hand, represents a viable alternative in the quest for ever-lower normalised energy costs and ever-shorter energy payback times. Material, components, and manufacturing techniques from allied sectors, particularly the power electronics industry, have been adapted to lower system costs and time-to-market for the system under development. The LFR is less than 30 mm wide to maximise thermal efficiency, and a densely packed cell array has been used to maximise electrical output. The Matlab simulations show that the proposed machine learning-based LFR technique has a greater concentration rate than the present LFR method, as demonstrated by the results.","PeriodicalId":14195,"journal":{"name":"International Journal of Photoenergy","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44507998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Srimathi, J. Meenakshi, R. Vijayabhasker, Semagn Shifere Belay
In this paper, the effectiveness of two grid-connected photovoltaic (PV) techniques up of copper indium selenium (CIS) and monocrystalline silicon (m-Si) arrays has been examined. In order to determine whether the technology is suitable for the actual winter and summer climatic conditions in Thoothukudi, Tamil Nadu, the observed and calculated performances have been compared. The final yield, photovoltaic (PV) effectiveness, array yield, performance ratio, and capacity utilisation factor seem to be the variables used to evaluate performance. Using recorded meteorological data at the selected location, PVsyst software predicts both PV systems’ year-round performances. These predictions are then contrasted to the outcomes of the actual measurements. The outcome showed that with a maximal observed performance ratio, both PV systems function marginally better in the winters than those in the summers. The performance indicators of the PV mechanisms are contrary with those of other PV systems with comparable capacities that are located in different places.
{"title":"Performance Evaluation and Estimation of Energy Measures of Grid-Connected PV Module","authors":"R. Srimathi, J. Meenakshi, R. Vijayabhasker, Semagn Shifere Belay","doi":"10.1155/2022/7228470","DOIUrl":"https://doi.org/10.1155/2022/7228470","url":null,"abstract":"In this paper, the effectiveness of two grid-connected photovoltaic (PV) techniques up of copper indium selenium (CIS) and monocrystalline silicon (m-Si) arrays has been examined. In order to determine whether the technology is suitable for the actual winter and summer climatic conditions in Thoothukudi, Tamil Nadu, the observed and calculated performances have been compared. The final yield, photovoltaic (PV) effectiveness, array yield, performance ratio, and capacity utilisation factor seem to be the variables used to evaluate performance. Using recorded meteorological data at the selected location, PVsyst software predicts both PV systems’ year-round performances. These predictions are then contrasted to the outcomes of the actual measurements. The outcome showed that with a maximal observed performance ratio, both PV systems function marginally better in the winters than those in the summers. The performance indicators of the PV mechanisms are contrary with those of other PV systems with comparable capacities that are located in different places.","PeriodicalId":14195,"journal":{"name":"International Journal of Photoenergy","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47591290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abdelkhalek Chellakhi, S. El Beid, Y. Abouelmahjoub
The purpose of this paper is to enhance the performance and tracking efficiency of solar photovoltaic systems. This aim can be achieved by operating the photovoltaic array at its optimum power and reducing the output ripple problem of DC-DC converters that affect and stress sensible electronic loads. In view of that, an advanced maximum power point (MPP) tracking (MPPT) scheme, which can guarantee zero oscillation tracking of the accessible MPP and less ripple magnitude on the output side of the DC-DC boost converter, is used. Various simulations are carried out under three conditions of solar irradiance variation, namely, standard test conditions (STC), rapid, and Sin scenarios, using the MATLAB/Simulink® environment, to assess and benchmark the robustness of the tracking of the new MPPT scheme over the celebrated Increment of Conductance (INC) MPPT scheme. Based on the simulation results, the proposed scheme can significantly improve tracking accuracy and reduce the magnitude of ripples on both sides of the boost converter compared to the INC scheme. Certainly, the proposed scheme can provide a shorter time response (0.011 seconds) to locate and track the expected MPP, which is 2.55 times less than that of the INC scheme; a zero power magnitude oscillation instead of 15.9 watts of the INC scheme; and six-time minimization of the magnitude of output voltage ripples compared to the INC scheme. Furthermore, the suggested MPPT scheme has the better tracking efficiency in all scenarios; 99.86%, 99.60%, and 99.62% in the STC, rapid, and Sin scenarios, respectively, with an average value of 99.69% compared to the INC MPPT scheme, which has 94.23%, 95.28%, and 97.87% in the STC, rapid, and Sin scenarios, respectively, with a moderate average tracking efficiency of 95.79%. Finally, the accuracy and tracking performance of the proposed MPPT scheme are verified by real-time examination using the RT-LAB simulator. According to the results obtained, the proposed scheme provides the highest tracking efficiency of 99.80% and 97.77% under the STC and sudden insolation change scenarios, respectively, compared to the INC scheme, which shows, respectively, 97.8% and 96.5% under both scenarios.
{"title":"An Advanced MPPT Scheme for PV Systems Application with Less Output Ripple Magnitude of the Boost Converter","authors":"Abdelkhalek Chellakhi, S. El Beid, Y. Abouelmahjoub","doi":"10.1155/2022/2133294","DOIUrl":"https://doi.org/10.1155/2022/2133294","url":null,"abstract":"The purpose of this paper is to enhance the performance and tracking efficiency of solar photovoltaic systems. This aim can be achieved by operating the photovoltaic array at its optimum power and reducing the output ripple problem of DC-DC converters that affect and stress sensible electronic loads. In view of that, an advanced maximum power point (MPP) tracking (MPPT) scheme, which can guarantee zero oscillation tracking of the accessible MPP and less ripple magnitude on the output side of the DC-DC boost converter, is used. Various simulations are carried out under three conditions of solar irradiance variation, namely, standard test conditions (STC), rapid, and Sin scenarios, using the MATLAB/Simulink® environment, to assess and benchmark the robustness of the tracking of the new MPPT scheme over the celebrated Increment of Conductance (INC) MPPT scheme. Based on the simulation results, the proposed scheme can significantly improve tracking accuracy and reduce the magnitude of ripples on both sides of the boost converter compared to the INC scheme. Certainly, the proposed scheme can provide a shorter time response (0.011 seconds) to locate and track the expected MPP, which is 2.55 times less than that of the INC scheme; a zero power magnitude oscillation instead of 15.9 watts of the INC scheme; and six-time minimization of the magnitude of output voltage ripples compared to the INC scheme. Furthermore, the suggested MPPT scheme has the better tracking efficiency in all scenarios; 99.86%, 99.60%, and 99.62% in the STC, rapid, and Sin scenarios, respectively, with an average value of 99.69% compared to the INC MPPT scheme, which has 94.23%, 95.28%, and 97.87% in the STC, rapid, and Sin scenarios, respectively, with a moderate average tracking efficiency of 95.79%. Finally, the accuracy and tracking performance of the proposed MPPT scheme are verified by real-time examination using the RT-LAB simulator. According to the results obtained, the proposed scheme provides the highest tracking efficiency of 99.80% and 97.77% under the STC and sudden insolation change scenarios, respectively, compared to the INC scheme, which shows, respectively, 97.8% and 96.5% under both scenarios.","PeriodicalId":14195,"journal":{"name":"International Journal of Photoenergy","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2022-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45629423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I. Kathīr, S. Shinde, C. Parswajinan, Sudheer Hanumanthakari, K. Loganathan, S. Madhavarao, A. Seikh, M. H. Siddique, Manikandan Ganesan
Single-junction polymer solar cells have demonstrated exceptional power conversion efficiency. Interlayer adhesion will be critical in building flexible polymer solar cells since inorganic conveyance layers would surely break. Aluminium-doped zinc oxide modified by polydopamine has emerged as a viable electron transportation layer in polymer solar cells, enhancing mechanical qualities by offering a high degree of flexibility and adhesion to the active layer. Power conversion efficiency of 12.7% is achieved in nonfullerene polymer solar cells built on PBDB-T2F:IT-4F with aluminium-doped zinc oxide 1.5% polydopamine electron transporting layer. Furthermore, the device based on Ag-mesh wire-wound electrodes has a power conversion efficiency of 11.5% and retains more than 90% of original power conversion efficiency afterward 1500 cycles of bending. For implantable and adaptable polymer solar cells for wide areas, roll-to-roll fabrication of inorganic electron transport layers is advantageous because of their mechanical resilience and thickness insensitivity.
{"title":"Flexible Polymer Solar Cells with High Efficiency and Good Mechanical Stability","authors":"I. Kathīr, S. Shinde, C. Parswajinan, Sudheer Hanumanthakari, K. Loganathan, S. Madhavarao, A. Seikh, M. H. Siddique, Manikandan Ganesan","doi":"10.1155/2022/4931922","DOIUrl":"https://doi.org/10.1155/2022/4931922","url":null,"abstract":"Single-junction polymer solar cells have demonstrated exceptional power conversion efficiency. Interlayer adhesion will be critical in building flexible polymer solar cells since inorganic conveyance layers would surely break. Aluminium-doped zinc oxide modified by polydopamine has emerged as a viable electron transportation layer in polymer solar cells, enhancing mechanical qualities by offering a high degree of flexibility and adhesion to the active layer. Power conversion efficiency of 12.7% is achieved in nonfullerene polymer solar cells built on PBDB-T2F:IT-4F with aluminium-doped zinc oxide 1.5% polydopamine electron transporting layer. Furthermore, the device based on Ag-mesh wire-wound electrodes has a power conversion efficiency of 11.5% and retains more than 90% of original power conversion efficiency afterward 1500 cycles of bending. For implantable and adaptable polymer solar cells for wide areas, roll-to-roll fabrication of inorganic electron transport layers is advantageous because of their mechanical resilience and thickness insensitivity.","PeriodicalId":14195,"journal":{"name":"International Journal of Photoenergy","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2022-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41982184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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