电力系统保护与控制2024，Vol.52Issue(22)：22-33,12.DOI:10.19783/j.cnki.pspc.240581
考虑风光荷时空互补的多能源绿色数据中心多目标配置方法
A multi-objective allocation method for multi-energy green data centers considering wind,solar and load spatial-temporal complementarity
摘要
Abstract
To solve the problem of high energy consumption and high carbon emission in data centers,this paper proposes a multi-objective capacity configuration model for wind-photovoltaic-storage multi-energy sources in green data centers.It considers the spatio-temporal complementarity of wind,solar and load.First,a mathematical model of flexibility resources in the multi-energy architecture of green data centers is established based on the spatial-temporal transfer characteristics of data centers and the operational characteristics of energy storage devices.Then,based on the flexible operation of data centers and energy storage,a complementarity index is proposed to describe the supply-demand difference between sources and loads.A capacity optimization model is established with the average kilowatt-hour cost and the minimum supply-demand difference as the optimization objectives.Finally,the annual output forecast data of wind power and photovoltaic are used for simulation and the capacity allocation model is analyzed using the Benders algorithm to obtain the optimal investment and construction plan for each data center.Case study analysis verifies the validity of the proposed model,and the results show that the introduction of renewable energy-energy storage power supply and data center spatio-temporal flexibility can reduce electricity costs and increase the penetration rate of renewable energy.关键词
绿色数据中心/风光荷互补/容量配置/Benders分解Key words
green data center/wind-photovoltaic-load complementarity/capacity allocation/Benders decomposition引用本文复制引用
可思为,董萍,马铭宇,王春玲,刘明波..考虑风光荷时空互补的多能源绿色数据中心多目标配置方法[J].电力系统保护与控制,2024,52(22):22-33,12.基金项目
This work is supported by the National Natural Science Foundation of China(No.52077083). 国家自然科学基金项目资助(52077083) （No.52077083）
广东省自然科学基金海上风电联合基金项目资助(2022A1515240076) （2022A1515240076）
