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Site-specific adjustment of a NWP-based photovoltaic production forecast

机译:基于NWP的光伏制作预测的现场特异性调整

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Despite the increased share of photovoltaic (PV) systems, several integration challenges are still present. For small-scale PV, the incentives for monitoring and forecasting the output are generated from the gains of optimizing of local electricity usage. PV output can often be the only measured parameter available from a PV site. Thereby, its efficient utilization in adjusting the PV conversion model is essential. The aim of this study is to develop a straightforward and explicit approach for utilizing PV output data in adjusting a site-specific PV output forecast. A parametric PV output conversion model is utilized as the baseline model for 23 PV sites in Finland, implemented on top of five summer months of day-ahead Numerical Weather Prediction (NWP) forecasts, provided by the MetCoOp system. The proposed approach is validated by comparing the performance of the baseline and adjusted forecasts against actual PV output. The method is shown to provide a solution for adjusting a generic PV output forecast to any specific site, reducing the hourly Mean Absolute Error (MAE) of the aggregated forecast from 0.08 to 0.06 W/Wp, while reducing bias from 0.05 to 0.01 W/Wp, respectively. The adjustment increases modeling accuracy by capturing potential systematic biases of the NWP forecast and sitespecific conditions, e.g., variable shadowing and conversion losses, affecting the output of the PV system. Due to the fact that the approach can be implemented both for observations and forecast input data, the method is considered to be a helpful approach for several different PV modeling applications.
机译:尽管光伏(PV)系统的份额增加,但仍然存在几种整合挑战。对于小规模的PV,监测和预测产量的激励是从优化本地电力使用的收益产生的。 PV输出通常可以是PV站点可获得的唯一测量参数。由此,其在调整光伏转换模型时的有效利用率至关重要。本研究的目的是开发一种直接和明确的方法,用于利用PV输出数据调整特定于站点的PV输出预测。参数化PV输出转换模型用作芬兰23个PV站点的基线模型,在由MetCoop系统提供的前一年的数字天气预报(NWP)预测之上实施。通过比较基线的性能和对实际PV输出的调整预测来验证所提出的方法。该方法显示为将通用PV输出预测调整到任何特定部位的方法,将聚合预测的每小时平均值(MAE)降低0.08至0.06W / WP,同时将偏差从0.05降低至0.01W / 0.01分别为WP。该调整通过捕获NWP预测和鉴别条件的潜在系统偏差,例如可变阴影和转换损耗来提高建模精度,影响PV系统的输出。由于该方法可以实现观察和预测输入数据,该方法被认为是几种不同的PV建模应用的有用方法。

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