表后数据中心微电网中电池储能系统的韧性设计与优化运行

中文摘要 AI 辅助

本文提出了一种高保真超大规模数据中心负载建模框架，该框架将设施需求分解为IT和非IT组件，并以秒级和分钟级分辨率表示负载行为。在此基础之上，开发了一个综合性的多阶段优化框架，用于表后（BTM）数据中心微电网中电池储能系统（BESS）的规划与韧性设计。该框架在负载侧部署BESS，作为随机需求与发电资产之间的动态缓冲。通过在燃气轮机观察到负载尖峰和越限之前对其进行平滑处理，负载侧BESS减少了运行压力，并限制了可能导致次同步扭转相互作用（SSTI）问题、轴疲劳、系统跳闸、设备损坏和强制停机的条件。同时，发电侧BESS资源被优化配置以提供旋转备用并增强系统韧性。所提出的方法将BESS与太阳能、风能、天然气燃料电池、简单循环燃气轮机和联合循环燃气轮机进行协同优化，同时纳入运行、可靠性、韧性和技术特定约束。仿真结果证明了所提方法能够识别出满足下一代超大规模数据中心严苛可靠性要求和能源市场挑战的具有成本效益、韧性且运行可行的设计方案，同时为投资者、开发商和系统运营商提供规划见解。

英文摘要

This paper proposes a high-fidelity hyperscale data center load modeling framework that disaggregates facility demand into IT and non-IT components and represents load behavior at second- and minute-level resolutions. Building upon this foundation, a comprehensive multi-phase optimization framework is developed for the planning and resilient design of BESS for BTM data center microgrids. The framework deploys BESS on the load side to act as a dynamic buffer between stochastic demand and generation assets. By smoothing the load spikes and excursions before they are observed by gas turbines, the load-side BESS reduces operational stress and limits conditions that can contribute to SSTI issues, shaft fatigue, system trips, equipment damage, and forced outages. Simultaneously, generation-side BESS resources are optimally sized to provide spinning reserves and enhance system resilience. The proposed methodology co-optimizes BESS with solar, wind, natural gas fuel cells, simple-cycle gas turbines, and combined-cycle gas turbines while incorporating operational, reliability, resiliency, and technology-specific constraints. Simulation results demonstrate the proposed methodology's ability to identify cost-effective, resilient, and operationally feasible designs that satisfy the demanding reliability requirements and energy market challenges of next-generation hyperscale data centers while providing planning insights for investors, developers, and system operators.

发表机构

• WSP USA Inc（WSP美国公司）

机构由 AI 辅助整理，请以论文原文为准。

补充信息

备注

Under Review