The effect of uncertainty in modeling coefficients used to predict energy production using the Sandia Array Performance Model

L. Pratt, D. King
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引用次数: 11

Abstract

Predicting photovoltaic array performance is an important part of system design and monitoring, so it's important to quantify the uncertainty associated with the predictions. The Sandia Array Performance Model [1] is one of many tools used to predict annual energy production, but the effect of the uncertainty in model coefficients has not been fully investigated. This paper quantifies the relative importance of voltage and current temperature coefficients, as well as the coefficients relating voltage and current to solar irradiance, for crystalline silicon modules. Using the coefficient variation observed in the Sandia module database and computer simulation, the effect of the uncertainty was quantified in terms of the range in predicted annual energy production relative to actual energy production by three small grid-connected PV systems. The relative importance of each coefficient by month of the year was also determined in order to understand the seasonal behavior of the performance model.
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利用桑迪亚阵列性能模型预测能源产量时,建模系数不确定性的影响
光伏阵列性能预测是系统设计和监测的重要组成部分,因此量化与预测相关的不确定性非常重要。Sandia阵列性能模型[1]是用于预测年发电量的众多工具之一,但模型系数不确定性的影响尚未得到充分研究。本文量化了晶体硅组件的电压和电流温度系数的相对重要性,以及与太阳辐照度有关的电压和电流系数。利用在Sandia模块数据库和计算机模拟中观察到的系数变化,根据三个小型并网光伏系统的预测年发电量相对于实际发电量的范围,对不确定性的影响进行了量化。为了了解性能模型的季节性行为,还确定了每个系数在一年中每个月的相对重要性。
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