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基于犹豫直觉模糊语言决策的电池技术综合性能评价与可持续性排序
Comprehensive performance evaluation and sustainability ranking of battery technologies based on hesitant intuitionistic fuzzy linguistic decision-making
| 作者 | Sayan Das · Manuel Baumann · Marcel Weil |
| 期刊 | Energy Conversion and Management |
| 出版日期 | 2025年1月 |
| 卷/期 | 第 328 卷 |
| 技术分类 | 储能系统技术 |
| 技术标签 | 储能系统 |
| 相关度评分 | ★★★★★ 5.0 / 5.0 |
| 关键词 | Methodology to identify sustainable [battery](https://www.sciencedirect.com/topics/engineering/battery-electrochemical-energy-engineering "Learn more about battery from ScienceDirect's AI-generated Topic Pages") by overcoming linguistic uncertainty. |
语言:
中文摘要
摘要 电池储能系统,特别是基于钠、钾等丰富材料的新兴系统,被视为当前锂基系统的可持续替代方案。然而,对这些系统的可持续性评估以及潜在改进潜力的识别需要对多个因素进行复杂评估,包括技术、经济、环境以及社会政治等方面。这些准则之间存在相互依赖性和不确定性,尤其是涉及处于不同技术成熟度(TRL)水平的技术时所关联的定性数据,给稳健评估带来了重大挑战。本研究提出了一种新的犹豫直觉模糊框架,用于选择储能技术并识别关键的改进潜力,该框架在语言犹豫与不确定性的条件下涵盖可持续性的所有维度。该方法独特地整合了详细的定量环境影响数据,并识别出基于原材料的社会子因素作为影响决策的关键要素。通过另一种模糊决策方法验证了结果的稳健性。最后,开展了各准则及子准则的障碍度分析,并结合不确定性分析以确定需要改进的领域。本研究以三种不同的电池化学体系为例进行评估:LiFePO₄作为当前先进技术,KFeSO₄F和NaNMMT作为新兴技术。初步结果显示,在不考虑社会政治因素的情况下,NaNMMT电池是最具可持续性的选项,其次为LiFePO₄和KFeSO₄F;而当将社会政治因素与其他因素一并考虑时,LiFePO₄则成为最优选择。研究表明,环境因素是影响决策最具影响力的因子。此外,电池电压、能量密度、正极比容量、资本成本、价格波动、需求增长以及全球变暖等子因素也显著影响决策过程。
English Abstract
Abstract Battery energy storage systems, in particular emerging systems based on abundant materials such as sodium and potassium are considered as sustainable alternatives to current lithium-based systems. However, sustainability assessment as well as the identification of potential improvement potentials require a complex assessment of multiple factors, including technical, economic, environmental and socio-political aspects. The interdependence and uncertainty of these criteria, particularly with qualitative data related to very different technology readiness levels (TRL), pose a significant challenge for robust assessments. The study proposes a new hesitant-intuitionistic framework for selecting energy storage technologies and to identify relevant improvement potentials, addressing all dimensions of sustainability under linguistic hesitancy and uncertainty. It uniquely incorporates detailed quantitative environmental impact data and raw material-based social sub-factors are also identified as the key factors that influence decision-making. The robustness of the results is validated with an additional fuzzy-decision making approach. Finally, the obstacle degree of each criterion and sub-criteria is conducted along with an uncertainty analysis to identify fields for improvement. The study exemplarily evaluates three different battery chemistries LiFePO 4 as state-of-the-art technology, and KFeSO 4 F and NaNMMT as emerging technologies. First results indicate that the NaNMMT battery is the most sustainable option followed by LiFePO 4 and KFeSO 4 F when socio-political factors are not considered. Whereas LiFePO 4 leads when this factor is included with other factors. The study identifies the environmental factor as the most influential in decision-making. Additionally, sub-factors such as cell voltage, energy density, cathode specific capacity, capital cost, price fluctuations, demand growth, and global warming also significantly impact the decision-making process.
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SunView 深度解读
该研究的多维度电池技术可持续性评估框架对阳光电源ST系列储能系统选型具有重要参考价值。研究揭示环境因素、能量密度、资本成本和全球变暖潜势是关键决策因子,可指导PowerTitan等储能产品在LFP技术路线基础上,前瞻性布局钠离子等新兴技术。模糊决策方法可集成至iSolarCloud平台,为客户提供基于技术成熟度、经济性和环境影响的智能化储能方案推荐,提升ESS解决方案的全生命周期可持续性评估能力。