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储能系统技术
★ 5.0
基于Copula的整体系统模型研究电网级储能的环境与经济影响
A copula-based whole system model to understand the environmental and economic impacts of grid-scale energy storage
| 作者 | Fan He · Matthew Leach · Michael Short · Yurui Fan · Lirong Liu |
| 期刊 | Applied Energy |
| 出版日期 | 2025年1月 |
| 卷/期 | 第 379 卷 |
| 技术分类 | 储能系统技术 |
| 相关度评分 | ★★★★★ 5.0 / 5.0 |
| 关键词 | Developed a novel model integrates optimisation IO model and copula function. |
语言:
中文摘要
摘要 能源储能在未来电力系统中具有重要作用。然而,电网级储能于电力系统乃至整个社会经济系统中的作用尚不明确。本文构建了一种基于Copula函数的整体系统模型,以探究电网级储能的经济与环境效应,从而为微观和宏观层面的决策提供支持。该模型将电力系统优化模型与投入产出模型相耦合,并嵌入Copula函数以刻画电力需求、排放约束以及部门细分所带来多重且相互关联的不确定性。本文以2025年的中国和英国为案例,考虑不同的储能技术(抽水蓄能、电池储能、飞轮储能),分析不同电力系统与经济结构下的差异。研究发现,增加储能容量将促进可再生能源装机容量的增长(在中国主要促进太阳能发电,在英国则主要促进风力发电),从而有助于降低两国全社会范围内的碳排放总量。在某些极端情况下,部门细分的不确定性会对碳排放产生显著影响,尤其是在那些与电力部门联系紧密且碳排放强度较高的产业部门中。
English Abstract
Abstract Energy storage is important in future power systems. However, the role of grid-scale energy storage in the power system and in the whole socio-economic system is unclear. A copula-based whole system model is developed to explore the economic and environmental effects of grid-scale energy storage, thus supporting the decision-making at micro and macro levels. A power system optimisation model is linked with an input-output model, and the copula function is embedded in the model to reflect the multiple and interactive uncertainties from electricity demand, emission constraints, and sector disaggregation. We conducted case studies on China and the UK in 2025 considering different storage technologies (Pumped hydro, Battery, Flywheels storage) to show the differences related with power systems and economic structures. We find that increasing energy storage capacity leads to increase in renewable generation capacity (solar generation in China and wind generation in the UK). Thus, it can reduce their total economy-wide carbon emissions. Uncertainty in sector disaggregation will have a large impact on carbon emissions in some extreme cases, especially in those sectors closely linked to the power sector and with high emission intensity.
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SunView 深度解读
该研究验证了储能系统在电力系统优化和碳减排中的关键作用,与阳光电源ST系列PCS和PowerTitan储能解决方案的战略定位高度契合。研究揭示的储能-可再生能源协同效应,为我们的光储一体化方案(SG逆变器+ST储能)提供了理论支撑。基于Copula模型的多重不确定性分析方法,可启发iSolarCloud平台在需求预测、容量配置优化和经济性评估方面的算法升级,特别是针对不同区域电力结构差异的定制化储能方案设计,提升全生命周期价值。