论文标题
BESS最佳尺寸方法论 - 几个影响因素的影响的程度
BESS Optimal Sizing Methodology -Degree of Impact of Several Influencing Factors
论文作者
论文摘要
电池储能系统(BES)由于表现不断增加和成本降低而越来越具竞争力。尽管从技术角度来看,某些电池存储技术可能会成熟且可靠,但预计会进一步降低成本,但电池系统的经济关注仍然是要克服的主要障碍,然后才能将BESS充分利用为能源领域的主流存储解决方案。由于部署BES的投资成本很大,因此最关键的问题之一是在使用BESS来改善能源系统绩效和实现盈利投资之间的权衡方面进行最佳尺寸。确定特定应用程序的最佳BES大小是一项复杂的任务,因为它取决于应用程序本身,电池系统的技术特征和业务模型框架的许多因素。本文描述了一种基于通用模拟的分析方法,该方法已开发出来,以确定BESS最佳尺寸,同时考虑到其生命周期的应用程序和存储性能。它的实现和相关的结果介绍了两个不同的BES用例:PV注入和离网混合微电网病例的平滑和峰值剃须应用。为了更好地了解在BESS大小程序中要考虑的最有影响力的驱动因素,对这两个说明性案例进行了几项灵敏度分析。比较场景的使用导致量化以下主题中几个因素的最佳尺寸结果的影响程度:控制策略,预测质量,由于老化而导致的电池性能降解,技术建模的精度。
Battery Energy Storage Systems (BESS) are more and more competitive due to their increasing performances and decreasing costs. Although certain battery storage technologies may be mature and reliable from a technological perspective, with further cost reductions expected, the economic concern of battery systems is still a major barrier to be overcome before BESS can be fully utilized as a mainstream storage solution in the energy sector. Since the investment costs for deploying BESS are significant, one of the most crucial issues is to optimally size the battery system to balance the trade-off between using BESS to improve energy system performance and to achieve profitable investment. Determining the optimal BESS size for a specific application is a complex task because it relies on many factors, depending on the application itself, on the technical characteristics of the battery system and on the business model framework. This paper describes a generic simulation-based analytical method which has been developed to determine the BESS optimal size by taking into account both the application and the storage performance over its lifetime. Its implementation and the associated results are presented for two different BESS use cases: A smoothing and peak shaving application for PV injection and an off-grid hybrid microgrid case. In order to provide a better understanding of the most influencing drivers to consider during a BESS sizing procedure, several sensitivity analyses have been carried out on these two illustrative cases. The use of comparative scenarios led to quantify the degree of impact on optimal sizing results of several factors among the following topics: control strategy, forecast quality, degradation of battery performance due to ageing, precision of technical modelling.