摘要
高能耗的数据中心具有巨大的可调节潜力,其负荷可作为电网公司开展需求响应业务的重要载体。然而,多方不确定因素严重制约数据中心运营商的需求响应决策,并影响其可调节能力。对此,提出一种考虑托管式数据中心负荷调节不确定性的区间优化模型。首先,梳理负荷调节过程中存在的不确定因素。然后,解析不确定因素之间的耦合关联关系。在利用Stackelberg博弈解决租户以及数据中心运营商之间的利益分配问题时,解析出不确定因素之间的关系式,进而求解出不确定因素的分布区间。最后,利用区间优化模型构建数据中心负荷调节的上层乐观解模型和下层悲观解模型。经仿真结果验证,所提出的模型能反映多重不确定条件下的数据中心负荷调节范围以及运营商获利区间。
Data centers with high energy consumption have great regulation potential, which can be regarded as an important carrier for power grid companies to carry out demand response business. However, multiple uncertainties severely restrict the decision-making of the data center operators and affect their regulation potential. Given this context, this paper proposes an interval optimization model that considers the uncertainties of load regulation for the colocation data center. First, the uncertainty factors in the load regulation process are analyzed. Then, the coupling relationship between the uncertain factors is analyzed. When using the Stackelberg game to solve the problem of split incentives between the tenants and the data center operator, the association models between the uncertain factors are derived, and the distribution of uncertain factors are deduced. Finally, the interval optimization model is applied to construct the upper-level optimistic solution model and the lower-level pessimistic solution model for the load regulation of the colocation data center. The simulation results verify that the proposed model can formulate the optimization range of load regulation and the interval of operator’s profits under multiple uncertainties.
作者
祁兵
曹望璋
李彬
王京菊
田世明
石坤
QI Bing;CAO Wangzhang;LI Bin;WANG Jingju;TIAN Shiming;SHI Kun(School of Electrical and Electronic Engineering,North China Electric Power University,Changping District,Beijing 102206,China;China Electric Power Research Institute,Haidian District,Beijing 100192,China)
出处
《电网技术》
EI
CSCD
北大核心
2022年第1期39-46,共8页
Power System Technology
基金
国家电网有限公司科技项目“面向多能源协同的用户侧综合需求响应关键技术研究与应用”(SGFJJY00GHJS190004)。
关键词
需求响应
数据中心
不确定性
博弈论
区间优化
demand response
data center
uncertainty
game theory
interval optimization
