Techno-economic potential of battery energy storage systems in frequency response and balancing mechanism actions
Techno-economic potential of battery energy storage systems in frequency response and balancing mechanism actions
复制标题
电池储能系统在频率响应和平衡机制作用方面的技术经济潜力
DOI：
10.1049/joe.2019.1053
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发表时间：
2020
影响因子：
--
通讯作者：
Kirli D
中科院分区：
文献类型：
--
作者：
Kirli D
电池在智能电网中提供平衡和调节服务，以提高其弹性和灵活性。保持可接受的健康状态和最高的回报率需要对资产进行动态建模和严格的优化。作者比较了智能电网中动态频率和平衡机制作用下电池使用的技术成本和经济效益。他们使用英国国家电网采购的服务作为案例研究，但该方法适用于全球，包括开发电网基础设施。他们的方法产生的服务参与的最佳方案，占动态退化，并考虑到全天可变的电价。此外，它还采用粒子群优化算法和历史数据，为电池在一天和一年内提供最佳的发货时间表和价格申报。他们的研究结果表明，通常频率响应是首选，因为它的技术费用较低，而且是按可用性而不是发货支付费用。然而，包括这两种服务的建议发送时间表提供了最高的利润。他们预计这种方法将成为更复杂的电池模型的基础，这些模型将服务调度优化，动态寿命退化和经济分析集成在一起。
Batteries offer a combination of balancing and regulation services within a smart grid to improve its resilience and flexibility. Maintaining an acceptable state of health and the highest rate of return requires dynamic modelling of the asset and rigorous optimisation. The authors compare the technical cost and economic benefit of battery employment in dynamic frequency and balancing mechanism actions in a smart grid. They use the services procured by National Grid in the UK as a case study but the methodology is globally applicable, including developing grid infrastructures. Their methodology yields the most optimum scenario of service participation, accounting for the dynamic degradation and considering variable pricing of electricity throughout the day. Additionally, it advises the most optimal despatch schedule and price declarations for the battery over the course a day and a year, employing particle swarm optimisation algorithm and historic data. Their results demonstrate that ordinarily frequency response is preferred due to its lower technical toll and payments for availability rather than despatch. However, the proposed despatch schedule including both services provides the highest profit. They anticipate this methodology to become the basis for more sophisticated battery models that integrate the service despatch optimisation, dynamic lifetime degradation and economic analysis.