A synthetic, spatially decorrelating solar irradiance generator and application to a LV grid model with high PV penetration
A synthetic, spatially decorrelating solar irradiance generator and application to a LV grid model with high PV penetration
复制标题
DOI：
10.1016/j.solener.2017.03.018
复制
发表时间：
2017-05
期刊：
影响因子：
6.7
通讯作者：
Jamie M. Bright;Oytun Babacan;J. Kleissl;P. Taylor;R. Crook
中科院分区：
文献类型：
--
作者：
Jamie M. Bright;Oytun Babacan;J. Kleissl;P. Taylor;R. Crook
住宅光伏（PV）技术预计将在全球大规模部署。随着光伏在配电网中的广泛应用，必须了解太阳能资源的可变性，以促进可靠的运行。这项研究表明，合成的，1分钟分辨率的辐照度时间序列，在空间维度上的变化，可以生成以下输入的基础上：平均每小时的气象观测okta，风速，云高和大气压力。合成的时间序列时间验证对观察到的1分钟辐照度数据为四个位置-Cambourne，英国;勒威克，英国;圣地亚哥，美国加利福尼亚州;和Oakland，美国HI-当分析4个指标的变化指数，斜坡率大小，辐照度幅度频率和晴空指数频率。计算每个位置的建模和观测数据的每个指标，比较CDF曲线相关性，并应用Kolmogorov-Smirnov（K-S）检验（置信限为99%）。各指标的CDF相关系数均在R ≥ 0.908以上，最低有90.96%的日辐照度时间序列通过了K-S检验。将模型输出与真实的观测数据进行比较，进行空间验证。空间相关系数与站点分离的回归被成功地重建，MAPE= 0.865%，RMSE= 0.01和R= 0.955。在固定云向时，空间瞬时相关性表现为各向异性，在沿着风向和横风向时，空间瞬时相关性不同。40-60%的云覆盖状态显示出最大的空间去相关性，而0%和100%的云覆盖状态则最小。该模型的输出应用到配电网的影响模型，使用IEEE-8500节点测试馈线。在1.5× 1.5 km的网格上模拟了25%、50%和75%吸收的光伏情景。严重的抽头变换事件的幅度和频率被发现是显着更高时，使用一个单一的辐照度时间序列的所有光伏系统与单独分配空间去相关的时间序列。
Residential photovoltaic (PV) technology is expected to have mass global deployment. With widespread PV in the electricity distribution grids, the variable nature of the solar resource must be understood to facilitate reliable operation. This research demonstrates that synthetic, 1-min resolution irradiance time series that vary on a spatial dimension can be generated based on the following inputs: mean hourly meteorological observations of okta, wind speed, cloud height and atmospheric pressure. The synthetic time series temporally validate against observed 1-min irradiance data for four locations—Cambourne, UK; Lerwick, UK; San Diego, CA USA; and Oahu, HI USA—when analysing 4 metrics of variability indices, ramp-rate size, irradiance magnitude frequency and clear-sky index frequency. Each metric is calculated for the modelled and observed data at each location and CDF profile correlation compared as well as applying the Kolmogorov-Smirnov (K–S) test with 99% confidence limits. CDF correlation coefficients of each metric are all above R⩾ 0.908, and a minimum of 90.96% of daily irradiance time series passed the K–S test. A spatial validation was performed comparing the model outputs to real observation data. The spatial correlation coefficient regression with site separation was successfully recreated with MAPE= 0.865%, RMSE= 0.01 and R= 0.955. The spatial instantaneous correlation was shown to behave anisotropically when using fixed cloud direction, with different correlation in along and cross wind directions. Cloud cover states of 40–60% showed the most spatial decorrelation while 0% and 100% had the least. The model outputs are applied to a distribution grid impact model using the IEEE-8500 node test feeder. PV scenarios of 25%, 50%, and 75% uptake were modelled across a 1.5× 1.5 km grid. The magnitude and frequency of severe tap changing events are found to be significantly higher when using a single irradiance time series for all PV systems versus individually assigning spatially decorrelating time series.