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A Simple Cloud Simulator for Investigating the Correlation Scaling Coefficient Used in the Wavelet Variability Model (WVM)

机译:一种简单的云模拟器,用于研究小波变异模型(WVM)中使用的相关缩放系数

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A wavelet variability model (WVM) for simulating solar photovoltaic (PV) powerplant output given a single irradiance sensor as input has been developed and has tested well against powerplants in Ota City, Japan and Copper Mountain, Nevada [1-3]. Central to this method is a correlation scaling coefficient (A) that calibrates the decay of correlation as a function of distance and timescale, and varies by day and geographic location. For Ota City and Copper Mountain, this A value has been determined using the network of irradiance sensors located at each powerplant. However, for applying the WVM to arbitrary locations where an irradiance sensor network is not readily available, it is necessary to estimate the A value. In this paper, we examine the dependence of A values on wind speed (at cloud altitude) and cloud size using a simple cloud motion simulator.
机译:为输入的单个辐照传感器的模拟太阳能光伏(PV)动力输出的小波变异模型(WVM)已经开发出来,并对内华达州Ota市,日本和铜山的动力植物进行了测试。[1-3]。该方法的核心是一种相关缩放系数(a),其作为距离和时间尺度的函数校准相关性的衰减,并且在日间和地理位置时变化。对于OTA市和铜山,该值已经使用位于每个动力装置的辐照度传感器网络确定。然而,为了将WVM应用于辐照传感器网络不容易获得的任意位置,需要估计值。在本文中,我们使用简单的云运动模拟器检查风速(在云高度)和云大小上的依赖性。

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