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Solar Energy Assessments: When is a Typical Meteorological Year Good Enough?

机译:太阳能评估:典型气象年何时足够好?

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This study compares probability-of-exceedance values (P-values) for photovoltaic systems derived using multiple years of Vaisala's 3TIER Services weather data to those derived using a Typical Meteorological Year (TMY) based on the same resource data. Both approaches were used to estimate the year-1 yield of eighteen Megawatt-scale photovoltaic projects located in different parts of North America, South America and Asia. P-values in the TMY case were derived by using the standard deviation of annual global horizontal insolation as a proxy for inter-annual variability. All other uncertainties were treated identically in both approaches. Since our analysis included only eighteen case studies, we supplemented it by examining extreme cases where the differences between the two approaches should be maximum, namely cases where inter-annual variability dominates all other uncertainties. P50 values derived from a 3TIER Services TMY are usually within 0.5% of those derived using a full time series. Meanwhile, other P-values derived using a TMY exhibited a positive bias, indicating that this approach systematically underestimates uncertainty. A simple method for removing this bias was developed using ten projects as a training data set, and tested on the remaining eight projects. Overall, differences in P90 and P99 values are typically less than 1%, but can reach up to 2-5% in extreme cases. These results can serve as benchmarks for deciding whether and when TMY analysis is good enough.
机译:该研究比较了使用多年Vaisala的3Tier服务天气数据导出的光伏系统的概率(p值)到基于相同资源数据使用典型的气象年(TMY)的那些。两种方法都用于估计位于北美,南美洲和亚洲不同地区的十八兆瓦级光伏项目的十八级产量。通过使用年度全球水平展示的标准偏差作为年度可变异性的代理来源的TMY案例中的p值。所有其他不确定性都在两种方法中相同地治疗。由于我们的分析仅包括十八个案例研究,我们通过检查两种方法之间的差异应该最大的极端情况,即年度变异占主导地位所有其他不确定性的案例。从3Tier服务TMY导出的P50值通常在使用全时间序列的0.5%以内。同时,使用TMY导出的其他P值表现出积极的偏差,表明这种方法系统地低估了不确定性。使用十个项目作为培训数据集开发了一种删除此偏差的简单方法,并在剩余的八个项目上进行测试。总体而言,P90和P99值的差异通常小于1%,但在极端情况下可以达到2-5%。这些结果可以作为决定是否足够好的基准。

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