用于离网光伏应用的锂离子超级电容器和电池:寿命和尺寸

Tarek Ibrahim, T. Kerekes, D. Sera, Abderezak Lashab, D. Stroe
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摘要

光伏(PV)发电的间歇性需要可靠的储能解决方案。在户外使用储能系统会使其暴露在多变的温度下,从而影响其储能能力和使用寿命。考虑到气候的变化和新的储能技术,利用和优化储能仍是一个研究空白。因此,本文提出了一种基于黄金分割搜索法的改进型选型算法,旨在优化储能装置中的电池数量,并特别关注丹麦的独特条件。所考虑的储能解决方案是锂离子电容器(LiCs)和锂离子电池(LiBs),并在不同温度和 C 率条件下进行了测试。该算法旨在最大限度地提高自主循环次数,自主循环是指系统独立于电网运行的时间段,以连续两次充电状态(SoC)为 0% 的时间间隔为标志。测试场景包括动态温度和动态负载、25 ° C 的恒温和恒定负载,同时考虑了辐照和温度效应以及电池容量在十年内的衰减。对比分析表明,在各种情况下,锂电池储电量平均为锂电池储电量的 70-80%。值得注意的是,在恒温情况下,降解速度加快,尤其是锂电池。通过利用改进的黄金分割搜索算法,本研究提供了一种解决大小问题的有效方法,优化了电池数量,从而为离网光伏系统中的储能提供了一种潜在的解决方案。
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Lithium-Ion Supercapacitors and Batteries for Off-Grid PV Applications: Lifetime and Sizing
The intermittent nature of power generation from photovoltaics (PV) requires reliable energy storage solutions. Using the storage system outdoors exposes it to variable temperatures, affecting both its storage capacity and lifespan. Utilizing and optimizing energy storage considering climatic variations and new storage technologies is still a research gap. Therefore, this paper presents a modified sizing algorithm based on the Golden Section Search method, aimed at optimizing the number of cells in an energy storage unit, with a specific focus on the unique conditions of Denmark. The considered energy storage solutions are Lithium-ion capacitors (LiCs) and Lithium-ion batteries (LiBs), which are tested under different temperatures and C-rates rates. The algorithm aims to maximize the number of autonomy cycles—defined as periods during which the system operates independently of the grid, marked by intervals between two consecutive 0% State of Charge (SoC) occurrences. Testing scenarios include dynamic temperature and dynamic load, constant temperature at 25 °C, and constant load, considering irradiation and temperature effects and cell capacity fading over a decade. A comparative analysis reveals that, on average, the LiC storage is sized at 70–80% of the LiB storage across various scenarios. Notably, under a constant-temperature scenario, the degradation rate accelerates, particularly for LiBs. By leveraging the modified Golden Section Search algorithm, this study provides an efficient approach to the sizing problem, optimizing the number of cells and thus offering a potential solution for energy storage in off-grid PV systems.
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