Ismail Abazine, Mustapha Elyaqouti, El Hanafi Arjdal, Driss Saadaoui, Dris Ben Hmamou, Abdelfattah Elhammoudy, Souad Lidaighbi, Imade Choulli
{"title":"增强单二极管模型,提高光伏电池表征的准确性","authors":"Ismail Abazine, Mustapha Elyaqouti, El Hanafi Arjdal, Driss Saadaoui, Dris Ben Hmamou, Abdelfattah Elhammoudy, Souad Lidaighbi, Imade Choulli","doi":"10.1016/j.prime.2025.100935","DOIUrl":null,"url":null,"abstract":"<div><div>The single-diode model (SDM) is widely used to simulate the behavior of photovoltaic (PV) cells. In the conventional approach, these models, referred to as voltage-independent SDM (SDMvi), assume that their parameters remain constant regardless of the PV cell's operating voltage. While SDMvi models are fundamental for PV system analysis and design, this assumption may limit prediction accuracy, particularly when dealing with nonlinear and dynamic PV characteristics. This paper introduces an enhanced single-diode model (SDMvd) that accounts for the voltage dependence of its five parameters. To achieve this, two new variables, P1 and P2, are introduced to segment the I-V curve into three regions, each containing the three characteristic points: maximum power point (MPP), open-circuit voltage (Voc), and short-circuit current (Isc). A novel hybrid method, combining analytical and numerical approaches, is then proposed for parameter extraction in each segment. The effectiveness of the proposed model is evaluated using five PV cells/modules from different technologies and under various environmental conditions. The results demonstrate that the SDMvd significantly improves accuracy, achieving a Root Mean Square Error (RMSE) of 6.161168E-04 A for the PVM 752 GaAs and 1.15378E-03 A for the STM6–40/36 module.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"11 ","pages":"Article 100935"},"PeriodicalIF":0.0000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhanced single-diode model for improved accuracy in photovoltaic cell characterization\",\"authors\":\"Ismail Abazine, Mustapha Elyaqouti, El Hanafi Arjdal, Driss Saadaoui, Dris Ben Hmamou, Abdelfattah Elhammoudy, Souad Lidaighbi, Imade Choulli\",\"doi\":\"10.1016/j.prime.2025.100935\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The single-diode model (SDM) is widely used to simulate the behavior of photovoltaic (PV) cells. In the conventional approach, these models, referred to as voltage-independent SDM (SDMvi), assume that their parameters remain constant regardless of the PV cell's operating voltage. While SDMvi models are fundamental for PV system analysis and design, this assumption may limit prediction accuracy, particularly when dealing with nonlinear and dynamic PV characteristics. This paper introduces an enhanced single-diode model (SDMvd) that accounts for the voltage dependence of its five parameters. To achieve this, two new variables, P1 and P2, are introduced to segment the I-V curve into three regions, each containing the three characteristic points: maximum power point (MPP), open-circuit voltage (Voc), and short-circuit current (Isc). A novel hybrid method, combining analytical and numerical approaches, is then proposed for parameter extraction in each segment. The effectiveness of the proposed model is evaluated using five PV cells/modules from different technologies and under various environmental conditions. The results demonstrate that the SDMvd significantly improves accuracy, achieving a Root Mean Square Error (RMSE) of 6.161168E-04 A for the PVM 752 GaAs and 1.15378E-03 A for the STM6–40/36 module.</div></div>\",\"PeriodicalId\":100488,\"journal\":{\"name\":\"e-Prime - Advances in Electrical Engineering, Electronics and Energy\",\"volume\":\"11 \",\"pages\":\"Article 100935\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"e-Prime - Advances in Electrical Engineering, Electronics and Energy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772671125000427\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772671125000427","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Enhanced single-diode model for improved accuracy in photovoltaic cell characterization
The single-diode model (SDM) is widely used to simulate the behavior of photovoltaic (PV) cells. In the conventional approach, these models, referred to as voltage-independent SDM (SDMvi), assume that their parameters remain constant regardless of the PV cell's operating voltage. While SDMvi models are fundamental for PV system analysis and design, this assumption may limit prediction accuracy, particularly when dealing with nonlinear and dynamic PV characteristics. This paper introduces an enhanced single-diode model (SDMvd) that accounts for the voltage dependence of its five parameters. To achieve this, two new variables, P1 and P2, are introduced to segment the I-V curve into three regions, each containing the three characteristic points: maximum power point (MPP), open-circuit voltage (Voc), and short-circuit current (Isc). A novel hybrid method, combining analytical and numerical approaches, is then proposed for parameter extraction in each segment. The effectiveness of the proposed model is evaluated using five PV cells/modules from different technologies and under various environmental conditions. The results demonstrate that the SDMvd significantly improves accuracy, achieving a Root Mean Square Error (RMSE) of 6.161168E-04 A for the PVM 752 GaAs and 1.15378E-03 A for the STM6–40/36 module.