单户建筑分散式电池储能系统的经济可行性,直至跨建筑利用

IF 5.4 Q2 ENERGY & FUELS
Albert Hiesl, Jasmine Ramsebner, Reinhard Haas
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引用次数: 0

摘要

由于光伏发电和电池储能的成本大幅降低,特别是在分散式家庭储能领域,近年来安装的并网电池支持光伏发电系统的数量正在稳步增长。然而,科学界已经深入探讨过,在大多数情况下,锂电池储能系统还不能经济地运行。本文探讨了锂电池储能的成本需要降低到什么程度才具有经济可行性。为此,本文基于线性优化模型和内部收益率方法,分析了单户建筑、多公寓建筑和跨建筑电池储能系统的经济可行性。根据发电量和消耗量,对不同电池容量和光伏容量的储能系统利用率进行了优化。内部收益率法用于比较减少电网消耗所节省的费用与投资成本以及运行和维护成本。为了估算最重要参数的影响,还进行了敏感性分析。分析得出的结论是,根据光伏发电和电池储能的容量组合以及与负荷曲线的关系,电池储能成本必须至少降低 85%,才能在 25 年的折旧期内获得一定的预定回报。此外,光伏发电可以直接覆盖的不同负载情况越多,例如在多公寓楼或跨楼中,需要储存的电量就越少,这就降低了蓄电池的效益和利用率,因此具体的投资成本必须进一步降低。敏感性分析得出的另一个结论是,电价以及电价与上网电价之间的价差对投资成本和盈利能力的影响最大。由于光伏发电的空间有限,同时耗电量又很高,在跨楼利用的情况下,自耗电量已经相当高,电池储能系统已经无法在必要的程度上提高自耗电量,因此投资成本也必须降低。本文的新颖之处尤其在于,它探讨了电池储能系统在不同情况下的目标成本,并给出了一定的回报率。本文的分析旨在让人们更深入地了解上述情况下电池储能系统经济运行的框架条件。不过,本文并未考虑除节省电网消耗之外的其他收入来源。例如,本文也没有详细考虑时间可变(电网)电价的可能性,应在今后的工作中进一步分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Economic viability of decentralised battery storage systems for single-family buildings up to cross-building utilisation

Economic viability of decentralised battery storage systems for single-family buildings up to cross-building utilisation
Due to the great cost decrease of photovoltaics as well as battery storage, especially in the segment of decentralised home storage, the number of grid-connected battery-supported photovoltaic systems being installed in recent years is steadily increasing. However, the scientific community has intensively discussed that lithium-based battery storage systems cannot yet be operated economically in most cases. This paper addresses the level to which the cost of lithium battery storage needs to decrease in order to be economically viable. For this purpose, the economic viability of battery storage systems in single-family buildings, multi-apartment buildings and across-buildings is analysed on the basis of a linear optimisation model and the method of the internal rate of return. The utilisation of the storage system is optimised for different battery and photovoltaic capacities on the basis of generation and consumption. The internal rate of return method is used to compare the savings resulting from the reduced consumption from the electricity grid with the investment costs and the operation and maintenance costs. In order to be able to estimate the influence of the most important parameters a sensitivity analysis is also carried out. The analysis concludes that, depending on the combination of capacities of photovoltaics, battery storage and in relation to the load profile, the battery storage costs would have to drop by at least 85% in order to generate a certain predefined return over a depreciation period of 25 years. Furthermore, the more different load profiles can be covered directly with photovoltaic electricity, e.g. in a multi-apartment building or across buildings, the less electricity needs to be stored and this reduces the benefit and the utilisation of the battery storage and therefore the specific investment costs must further decrease. Another conclusion that emerges from the sensitivity analysis is that the electricity price and the spread between the electricity price and the feed-in tariff have the greatest influence on the investment costs and profitability. Due to limited space for photovoltaics and simultaneously high consumption, self-consumption is already quite high with cross-building utilisation and can no longer be increased to the necessary extent by the battery storage system, which is why the investment costs must also be lower. The novelty of this paper lies in particular in the fact that it deals with the target costs of battery storage systems in various scenarios for certain rates of return. The analyses in this paper are intended to provide a deeper understanding of the framework conditions for the economic operation of a battery storage system in the aforementioned scenarios. However, this paper does not take into account alternative sources of income other than savings on grid consumption. The possibility of time-variable (grid) tariffs, for example, is also not considered in detail in this paper and should be analysed further in future work.
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来源期刊
Smart Energy
Smart Energy Engineering-Mechanical Engineering
CiteScore
9.20
自引率
0.00%
发文量
29
审稿时长
73 days
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