利用电池储能进行峰谷削减和频率调节：联合优化以实现超线性增益
Using Battery Storage for Peak Shaving and Frequency Regulation: Joint Optimization for Superlinear Gains
AI总结：
本文提出联合优化框架，通过考虑电池退化、运营约束和负荷及调节信号的不确定性，展示通过电池储能同时实现峰谷削减和频率调节可降低用户电费15%，并证明联合优化带来的收益大于单一应用的总和。
摘要：
我们考虑通过联合优化框架同时利用电池储能系统进行峰谷削减和频率调节，该框架捕捉电池退化、运营约束以及客户负荷和调节信号的不确定性。在此框架下，利用实际数据我们显示用户电费可降低高达15%。此外，我们证明当电池同时提供两种单独应用时，联合优化的节省通常大于单独应用的总节省。提出了一种简单的阈值实时算法，实现超线性增益。与之前专注于电池储能单一应用的研究相比，我们的结果表明，如果电池同时提供多种服务，其经济收益可能远超以往预期。
英文摘要：
We consider using a battery storage system simultaneously for peak shaving and frequency regulation through a joint optimization framework which captures battery degradation, operational constraints and uncertainties in customer load and regulation signals. Under this framework, using real data we show the electricity bill of users can be reduced by up to 15\%. Furthermore, we demonstrate that the saving from joint optimization is often larger than the sum of the optimal savings when the battery is used for the two individual applications. A simple threshold real-time algorithm is proposed and achieves this super-linear gain. Compared to prior works that focused on using battery storage systems for single applications, our results suggest that batteries can achieve much larger economic benefits than previously thought if they jointly provide multiple services.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
