储能科学与技术2025，Vol.14Issue(2)：671-687,17.DOI:10.19799/j.cnki.2095-4239.2024.0828
基于i-C&CG求解算法的数据中心与储能协同规划
i-C&CG solving algorithm-driven collaborative planning of data center and battery energy storage
摘要
Abstract
The skyrocketing demand for AI computing has fueled a surge in energy consumption within internet data centers(IDCs),surpassing expectations.However,the unpredictable nature of renewable energy poses significant challenges for stable grid operation,which demand response from IDCs alone cannot fully solve.Configurable energy storage enhances flexibility.This paper presents a two-stage robust model for IDCs and battery energy storage(BES)planning,minimizing operational costs amidst wind power uncertainty.A lifespan constraint ensures realistic planning.The traditional C&CG algorithm's speed-accuracy dilemma is tackled with an Inexact C&CG(i-C&CG)algorithm,avoiding exact column/constraint generation.Simulations on IEEE 30-node and 118-node systems highlight the benefits of this approach.The proposed energy storage configuration reduces annual costs by 39785 CNY for storage systems and 289080 CNY for IDCs.The i-C&CG algorithm shortens iteration time by 3632 seconds,achieving a 0.18 precision and 0.46 relative error.These results match the traditional C&CG's convergence and optimality gaps.关键词
数据中心/储能寿命/不精确列和约束生成算法Key words
internet data centers/energy storage life/inexact column-and-constraint generation分类
动力与电气工程引用本文复制引用
王述祯..基于i-C&CG求解算法的数据中心与储能协同规划[J].储能科学与技术,2025,14(2):671-687,17.
