分小时建模误差对项目规模的敏感性

Christopher Hayes, A. Parikh, Mark Mikofski, Rounak Kharait
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引用次数: 0

摘要

来自NV、MT、SD、MS、PA、IL和CO站的地表辐射预算网络(SURFRAD)的太阳资源高频测量从1分钟降采样到1小时,并用于预测能量产量和亚小时建模误差。小波变异性模型(WVM)结合估计的太阳能发电厂布局,用于确定规模从1mw到1000mw的项目的亚小时建模误差依赖关系。此外,还评估了对逆变器过度建设、直流交流比、平均云速度、年际变化和地理位置的敏感性。通过合并WVM来平滑辐照度输入,我们发现随着项目规模的增加,年度次小时建模误差呈现出近乎对数的减少。平均而言,建模误差在前200mw迅速减小,并在200 - 1000mw开始渐近线。年模拟误差的大小受DC/AC比、平均云速和太阳资源年际变率的影响较大。本研究的结果被用于开发一个项目规模相关的分小时建模误差调整因子,用于施工前能源评估。
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Sensitivity of Sub-Hourly Modeling Error to Project Size
High-frequency measurements of solar resource from the Surface Radiation Budget Network (SURFRAD) from stations in NV, MT, SD, MS, PA, IL and CO were down-sampled from 1-minute to 1-hour and used to predict energy yield and sub-hourly modeling error. A Wavelet Variability Model (WVM) incorporating an estimated solar plant layout was used to determine the sub-hourly modeling error dependency for projects ranging in size from 1 MW to 1,000 MW. Additionally, sensitivity to inverter overbuild, DC to AC ratio, average cloud speed, interannual variability and geographic location were evaluated. By incorporating the WVM to smooth the irradiance inputs we found that annual sub-hourly modeling errors exhibited a nearly logarithmic decrease as project size increased. On average, the modeling error decreases quickly for the first 200 MW and begins to asymptote for 200 - 1,000 MW. The magnitude of annual modeling errors was highly influenced by DC/AC ratio, average cloud speed and the interannual variability of the solar resource. The results of this study were implemented to develop a project size dependent sub-hourly modeling error adjustment factor for pre-construction energy assessments.
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