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光伏发电技术 ★ 5.0

热光伏性能指标与技术经济性:效率与功率密度的权衡

Thermophotovoltaic performance metrics and techno-economics: Efficiency vs. power density

语言:

中文摘要

摘要 热光伏(TPV)是一种将热能转化为电能的新兴有前景的技术。其性能主要由两个指标来表征:效率和功率密度。尽管近期的研究已实现了较高的效率,但随着该技术商业化进程的推进,理解这两个指标如何共同影响TPV系统的技术经济性显得尤为重要。在本研究中,我们首次将效率和功率密度统一为一个基于平准化度电成本(LCOE)的综合技术经济指标。我们发现,LCOE可分解为两部分:供热成本,包括为TPV电池提供热能所需的基础设施和投入;以及电池成本,即TPV电池的资本支出。我们指出,在供热成本较高的系统中,应优先提高TPV效率;而在电池成本较高的系统中,则应优先提升功率密度。随后,我们建立了一个模型,用以识别哪些电池特性对改善关键性能指标和降低系统LCOE最具影响力。具体而言,在基础设施成本较高的系统中,通过提高背表面反射率来增强光谱调控效果最为显著;而在TPV电池成本较高的系统中,增大视角因子并降低前表面反射率则最为关键。仅改进上述特性中的一至两项,即可使LCOE降低25%–75%,达到约8美分/千瓦时的具有竞争力的水平,低于美国电力的平均成本。因此,本研究阐明了在系统技术经济性中哪个TPV性能指标更为重要,以及如何最大化该指标。

English Abstract

Abstract Thermophotovoltaics (TPV) are a promising new approach for converting heat to electricity. Their performance is primarily characterized by two metrics: efficiency and power density. While recent works have shown high efficiency, it is important to understand how both of these metrics impact the techno-economics of a TPV system as efforts to commercialize the technology advance. In this work, we develop the first unification of efficiency and power density into a single techno-economic metric based on the levelized cost of electricity (LCOE). We find that the LCOE can be broken into two parts: heating cost, including infrastructure and inputs for providing heat to the TPV cells, and cell cost, the capital cost of the TPV cells. We show that systems with high heating costs should prioritize TPV efficiency, while systems with high cell costs should prioritize power density. We then develop a model to identify the most impactful cell properties in improving the important performance metric and reducing system LCOE. Namely, improving spectral control with increased back-surface reflectance is the most effective to reduce LCOE in systems with high infrastructural costs, while increasing the view factor and reducing front-surface reflectance are most critical in systems with high TPV cell cost. Improving just one or two of these properties can reduce the LCOE by 25–75 %, reaching competitive values ∼8 ¢/kWh-e, less than the average cost of electricity in the US. This study thus elucidates which TPV performance metric is more important for system techno-economics and how to maximize it.
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SunView 深度解读

该热光伏(TPV)技术经济性分析对阳光电源储能系统具有重要参考价值。研究揭示的效率与功率密度权衡原则可应用于ST系列PCS和PowerTitan储能方案的成本优化:高基础设施成本场景应优先提升转换效率,高设备成本场景则应提升功率密度。其光谱控制、背反射率优化等方法可启发SG系列光伏逆变器的MPPT算法改进,通过动态调节工作点平衡系统效率与输出功率,降低度电成本(LCOE)至8美分/kWh竞争水平,为iSolarCloud平台提供智能优化策略依据。