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基于技术经济指标定义光伏电站寿命
Defining Solar Farm Lifetime From Techno-economic Indicators
| 作者 | Shakil Hossain · M. Rezwan Khan · M. Ryyan Khan |
| 期刊 | IEEE Journal of Photovoltaics |
| 出版日期 | 2026年1月 |
| 卷/期 | 第 16 卷 第 2 期 |
| 技术分类 | 光伏发电技术 |
| 技术标签 | 地面光伏电站 光伏逆变器 组串式逆变器 可靠性分析 |
| 相关度评分 | ★★★★ 4.0 / 5.0 |
| 关键词 |
语言:
中文摘要
本文提出一种技术经济驱动的光伏电站寿命优化框架,通过LCOE最小化确定最优运行年限。对比固定速率与真实退化模型,发现后者更准确;在特定经济参数下,最优寿命可能低于25年技术寿命,提示提前退役更优。
English Abstract
Photovoltaic (PV) system design and project viability are conventionally decided based on the assumptions: “end of life at 80% capacity” and “20–25 year system life.” These heuristic assumptions decouple the local financial context from long-term technical performance dynamics, obscuring the technoeconomic optimal in the decision aiding analyses. In this article, we present a technoeconomics driven framework to explain the project lifetime of PV farms. The levelized cost of energy (LCOE) varies with the chosen project lifetime, and we show that there is an optimum operational life of the PV system where LCOE is minimum. We compare the fixed-rate degradation (FRD) model to a realistic degradation (RD) profile to quantify LCOE and optimal project lifetimes. FRD significantly overestimates the optimum lifetime. For a baseline system reaching 80% capacity in 25 years (“technical lifetime”), the FRD model predicts an unrealistic optimum life of 58 years, whereas the RD model yields 32 years at 2.5% interest rate and 2% inflation rate. We study the variation in optimum lifetimes for different interest/discount rates, inflation, and technical lifetime. While optimum lifetime increases as each of these parameters increase, LCOE only goes up with the economic rates. Our results indicate, in certain local conditions, it may be possible that the optimum is lower than the technical lifetime—i.e., it would then be better to set the system decommissioning date even before the warranty. By bridging realistic system performance with LCOE analysis to identify the year of minimum LCOE, our approach provides investors and policymakers with a robust metric to maximize financial returns and decide when to decommission.
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SunView 深度解读
该研究对阳光电源组串式逆变器及iSolarCloud智能运维平台具有直接指导价值:真实退化建模可提升发电量预测精度,支撑LCOE动态评估;建议将RD模型嵌入iSolarCloud寿命预测模块,结合ST系列PCS的实时功率与温度数据,为PowerTitan光储项目提供退役决策支持,并优化全生命周期运维策略。