光伏太阳能发电厂的年度相对性能下降

Alberto Boretti , Stefania Castelletto
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引用次数: 0

摘要

本研究旨在评估年度相对性能退化 σ,以用于计算基于标准年天气和太阳能资源的新发电厂的平准化能源成本 (LCOE)。评估基于不同年份的发电量、天气和资源的实验数据,以及使用美国国家可再生能源实验室(NREL)系统顾问模型(SAM)软件进行的发电量模拟。53 家不同发电厂约十年的发电原始数据显示,σ 的评估值为 <0.29%。因此,在 SAM 中假设 σ = 0 % 至 σ = 0.29 % 是合理的。这比目前 SAM 根据有限的过时数据使用的默认值 σ = 0.5 % 要低。更新后的性能下降系数减小到 σ = 0-0.29 %,使美国典型新项目的计算 LCOE 从 2.86 降至 2.74-2.80 ¢/kWh。考虑到模型和辅助数据的不准确性、管理部门对性能变化的缓解措施以及与天气和辐照度变化相关的、在不同方向上影响电力输出的复杂现象,只要涵盖足够长的运行年限,就没有必要根据天气和资源的年际变化对 σ 趋势进行校正。σ的降低是过去几十年来产品显著改进的结果,特别是对于大型发电厂而言,与之前提供性能退化相关数据的发电厂相比,以及对发电厂的管理和维护大大改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Annual relative performance degradation in photovoltaic solar plants
This study aims to assess annual relative performance degradation σ to be used in the computations of the Levelised Cost of Energy (LCOE) of new plants based on the standard year for weather and solar resource. The assessment is based on the experimental data of power generation, weather, and resource for different years, and simulations of power generation by using the National Renewable Energy Laboratory (NREL) System Advisor Model (SAM) software. The raw data of power generation for 53 different plants spanning about one decade show a σ assessed at <0.29 %. This makes it reasonable to assume in SAM σ = 0 % to σ = 0.29 %. This is less than the default σ = 0.5 % currently used in SAM based on limited outdated data. The updated performance degradation factor diminished to σ = 0–0.29 % reduces the computed LCOE for typical new projects in the United States from 2.86 to 2.74–2.80 ¢/kWh. Correction of the σ trends for interannual variability of weather and resource is unnecessary, providing enough years of operation are covered, given the inaccuracies in the model and the supporting data, the mitigation by management of the performance changes, and the complex phenomena correlated to the change of weather and irradiance affecting the power output in different directions. The reduced σ is the result of a significant product improvement over the last decades, especially for large power plants, compared to the plant which provided data for the prior correlation of performance degradation, and much better management and maintenance of the plants.
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