Montaser Mahmoud , Salah Haridy , Ayman Mdallal , Abdul Hai Alami , Mohammad Ali Abdelkareem , Abdul Ghani Olabi
{"title":"光伏-抛物槽式聚光太阳能混合电站的建模与优化:技术、经济和环境","authors":"Montaser Mahmoud , Salah Haridy , Ayman Mdallal , Abdul Hai Alami , Mohammad Ali Abdelkareem , Abdul Ghani Olabi","doi":"10.1016/j.nexus.2025.100436","DOIUrl":null,"url":null,"abstract":"<div><div>This research presents detailed guidelines for modeling and optimizing an integrated photovoltaic-concentrated solar power (PV-CSP) plant using response surface methodology (RSM), tailored to the climate of Sharjah, UAE. Five factors are considered in the optimization, which are the percentage share of PV/CSP (A), PV tilt angle (B), PV spacing (C), CSP solar multiple (D), and thermal storage size (E), with corresponding ranges of 10–90% (equivalent to 10 to 90 MW), 20–40°, 1–7 m, 2.5–7.5, and 5–20 h, respectively. The research utilizes three software tools: System Advisor Model (SAM) for CSP, PV<sub>syst</sub> for PV, and Design-Expert for RSM. Based on the analysis of variance (ANOVA), seven factors (A, C, E, D², AC, AE, and DE) are significant for energy output, while eight (A, C, D, E, AC, AD, AE, and DE) are significant for LCOE. Through multi-objective optimization aimed at maximizing energy production while minimizing LCOE and land area, the results indicate that the optimal configuration comprises 38.6% CSP and 61.4% PV. This configuration achieves an energy output of 3.64 × 10<sup>8</sup> kWh/year, a LCOE of $0.033/kWh, and a land area of 743.46 acres. These results were achieved with B, C, D, and E of 27.18°, 5.45 m, 4.41, and 15.49 h, respectively.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100436"},"PeriodicalIF":8.0000,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modelling and optimization of a hybrid photovoltaic-parabolic trough concentrated solar power plant: Technical, economic, and environmental\",\"authors\":\"Montaser Mahmoud , Salah Haridy , Ayman Mdallal , Abdul Hai Alami , Mohammad Ali Abdelkareem , Abdul Ghani Olabi\",\"doi\":\"10.1016/j.nexus.2025.100436\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This research presents detailed guidelines for modeling and optimizing an integrated photovoltaic-concentrated solar power (PV-CSP) plant using response surface methodology (RSM), tailored to the climate of Sharjah, UAE. Five factors are considered in the optimization, which are the percentage share of PV/CSP (A), PV tilt angle (B), PV spacing (C), CSP solar multiple (D), and thermal storage size (E), with corresponding ranges of 10–90% (equivalent to 10 to 90 MW), 20–40°, 1–7 m, 2.5–7.5, and 5–20 h, respectively. The research utilizes three software tools: System Advisor Model (SAM) for CSP, PV<sub>syst</sub> for PV, and Design-Expert for RSM. Based on the analysis of variance (ANOVA), seven factors (A, C, E, D², AC, AE, and DE) are significant for energy output, while eight (A, C, D, E, AC, AD, AE, and DE) are significant for LCOE. Through multi-objective optimization aimed at maximizing energy production while minimizing LCOE and land area, the results indicate that the optimal configuration comprises 38.6% CSP and 61.4% PV. This configuration achieves an energy output of 3.64 × 10<sup>8</sup> kWh/year, a LCOE of $0.033/kWh, and a land area of 743.46 acres. These results were achieved with B, C, D, and E of 27.18°, 5.45 m, 4.41, and 15.49 h, respectively.</div></div>\",\"PeriodicalId\":93548,\"journal\":{\"name\":\"Energy nexus\",\"volume\":\"18 \",\"pages\":\"Article 100436\"},\"PeriodicalIF\":8.0000,\"publicationDate\":\"2025-04-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy nexus\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772427125000774\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy nexus","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772427125000774","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Modelling and optimization of a hybrid photovoltaic-parabolic trough concentrated solar power plant: Technical, economic, and environmental
This research presents detailed guidelines for modeling and optimizing an integrated photovoltaic-concentrated solar power (PV-CSP) plant using response surface methodology (RSM), tailored to the climate of Sharjah, UAE. Five factors are considered in the optimization, which are the percentage share of PV/CSP (A), PV tilt angle (B), PV spacing (C), CSP solar multiple (D), and thermal storage size (E), with corresponding ranges of 10–90% (equivalent to 10 to 90 MW), 20–40°, 1–7 m, 2.5–7.5, and 5–20 h, respectively. The research utilizes three software tools: System Advisor Model (SAM) for CSP, PVsyst for PV, and Design-Expert for RSM. Based on the analysis of variance (ANOVA), seven factors (A, C, E, D², AC, AE, and DE) are significant for energy output, while eight (A, C, D, E, AC, AD, AE, and DE) are significant for LCOE. Through multi-objective optimization aimed at maximizing energy production while minimizing LCOE and land area, the results indicate that the optimal configuration comprises 38.6% CSP and 61.4% PV. This configuration achieves an energy output of 3.64 × 108 kWh/year, a LCOE of $0.033/kWh, and a land area of 743.46 acres. These results were achieved with B, C, D, and E of 27.18°, 5.45 m, 4.41, and 15.49 h, respectively.
Energy nexusEnergy (General), Ecological Modelling, Renewable Energy, Sustainability and the Environment, Water Science and Technology, Agricultural and Biological Sciences (General)