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Geographic smoothing of solar PV: results from Gujarat

机译:太阳能光伏的地理平滑:古吉拉特邦的结果

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We examine the potential for geographic smoothing of solar photovoltaic (PV) electricity generation using 13 months of observed power production from utility-scale plants in Gujarat, India. To our knowledge, this is the first published analysis of geographic smoothing of solar PV using actual generation data at high time resolution from utility-scale solar PV plants. We use geographic correlation and Fourier transform estimates of the power spectral density (PSD) to characterize the observed variability of operating solar PV plants as a function of time scale. Most plants show a spectrum that is linear in the log–log domain at high frequencies f, ranging from to (slopes of ?1.23 and ?1.56), thus exhibiting more relative variability at high frequencies than exhibited by wind plants. PSDs for large PV plants have a steeper slope than those for small plants, hence more smoothing at short time scales. Interconnecting 20 Gujarat plants yields a spectrum, reducing fluctuations at frequencies corresponding to 6 h and 1 h by 23% and 45%, respectively. Half of this smoothing can be obtained through connecting 4–5 plants; reaching marginal improvement of 1% per added plant occurs at 12–14 plants. The largest plant (322 MW) showed an spectrum. This suggests that in Gujarat the potential for smoothing is limited to that obtained by one large plant.
机译:我们使用从印度古吉拉特邦的公用事业规模工厂进行的13个月观察到的发电量,研究了太阳能光伏(PV)发电的地理平滑潜力。据我们所知,这是首次公开发表的利用公用事业规模太阳能光伏电站在高分辨率下使用实际发电数据的太阳能光伏地理平滑分析。我们使用功率谱密度(PSD)的地理相关性和傅立叶变换估计来表征观测到的运行中的太阳能光伏电站随时间变化的变化性。大多数植物在高频f处在对数-对数域中显示线性光谱,范围从到(斜率分别为?1.23和?1.56),因此与风力发电厂相比,在高频处表现出更大的相对变化性。大型光伏电站的PSD斜率比小型光伏电站的PSD陡,因此在短时间范围内更平滑。将20个古吉拉特邦植物相互连接产生一个频谱,将与6 h和1 h对应的频率上的波动分别减少了23%和45%。通过连接4-5个工厂可以获得一半的平滑处理。每12到14棵植物,每增加1株植物就达到1%的边际改善。最大的发电厂(322兆瓦)显示出频谱。这表明在古吉拉特邦,平滑的潜力仅限于一家大型工厂获得的平滑潜力。

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