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Trends in performance factors of large photovoltaic solar plants

机译:大型光伏太阳能厂的性能因素趋势

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This short communication discusses the two parameters recently emerged as a Key Performance Indicator of solar energy facilities, the mean capacity factor over a year, and the standard deviation of the capacity factor computed with high-frequency sampling. Both parameters impact directly and indirectly on the Levelised Cost Of Electricity (LCOE), permitting to quantify the energy production by the specific facility, and the attribution of the grid energy storage costs to the specific facility. The annual average capacity factors of the latest, largest, 53 photovoltaic (PV) solar energy facilities in the US, vary between 10% and 36%, with a mean value of 27% and a standard deviation of 5%. There are large differences also in between plants located in areas of a similar solar resource. Inference of long term performance degradation or O&M costs is difficult. We know from Australia that solar PV facilities work with high-frequency capacity factors' standard deviations larger than the mean, for coefficients of variability above unity, and significant variability also at the grid level. This variability necessitates of energy storage. High-frequency data to assess the standard deviation of the individual US facility contribution to the different grids, as well as the energy storage needed for every grid, is unavailable. Construction cost data are less reliable than energy production data and mostly missing. Based on data for 15 plants, completed between 2014 and 2017, the construction cost dramatically varies between different facilities. The specific cost varies between 1,719 [US$/kW] and 7,143 [US$/kW], an average of 3,983 [US$/kW]. Considering the actual generating power vs. the nominal generating power, the specific cost varies between 6,374 and 22,806, an average 14,006 [US$/kW]. Hence, an accurate prediction of the LCOE of large PV facilities in the US is presently difficult.
机译:这种短期通信讨论了最近作为太阳能设施的关键性能指标,平均容量因子超过一年的两个参数,以及使用高频采样计算的容量因子的标准偏差。参数直接和间接地影响电力(LCoE)的机制成本,允许量化特定设施的能源生产,以及网格储能成本对特定设施的归因。最新,最大,53个光伏(PV)太阳能设施的年平均容量因素在美国,含量为10%至36%,平均值为27%,标准差为5%。位于类似太阳能资源的地区的植物之间也存在巨大差异。长期性能降级或O&M成本的推动很困难。我们知道来自澳大利亚的太阳能光伏设备与高于平均值的高频容量因素的标准偏差,对于统一的变异系数,以及栅格级别的显着变异性。这种变化需要储能。高频数据,以评估各个美国设施对不同网格的标准偏差,以及每个网格所需的能量存储,不可用。施工成本数据不如能源生产数据可靠,大多数缺失。根据2014年至2017年之间完成的15个植物的数据,建筑成本在不同的设施之间大大变化。具体成本在1,719 [美元/ kW]和7,143 [美元/ kW]之间,平均为3,983 [US $ / kW]。考虑到实际发电功率与标称发电功率,特定成本在6,374和22,806之间变化,平均为14,006 [US $ / kW]。因此,目前困难地对美国大型光伏设施的LCOE的准确预测。

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