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1.现代电力系统仿真控制与绿色电能新技术教育部重点实验室(东北电力大学),吉林省吉林市 132012
2.白城师范学院机械与控制工程学院,吉林省白城市137000
Received:12 July 2024,
Revised:2024-11-05,
Published Online:02 January 2025,
Published:10 July 2025
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张虹,郑广宇,娄娟等.计及热电负荷不匹配的数据中心余热补偿系统调控策略[J].电力系统自动化,2025,49(13):156-165.
ZHANG Hong,ZHENG Guangyu,LOU Juan,et al.Regulation Strategy of Waste Heat Compensation System for Data Center Considering Thermo-Electric Load Mismatch[J].Automation of Electric Power Systems,2025,49(13):156-165.
张虹,郑广宇,娄娟等.计及热电负荷不匹配的数据中心余热补偿系统调控策略[J].电力系统自动化,2025,49(13):156-165. DOI: 10.7500/AEPS20240712003.
ZHANG Hong,ZHENG Guangyu,LOU Juan,et al.Regulation Strategy of Waste Heat Compensation System for Data Center Considering Thermo-Electric Load Mismatch[J].Automation of Electric Power Systems,2025,49(13):156-165. DOI: 10.7500/AEPS20240712003.
热电联产机组作为传统供暖系统的主要热源,采用以电定热的方式运行时系统会出现热电负荷不匹配的问题。因此,提出一种计及热电负荷不匹配的数据中心余热补偿系统调控策略。首先,对数据负载的时间可转移特性进行分析,构建含不确定性的数据负载模型,并计算服务器运行功率。然后,根据数据中心服务器的电热特性以及社区用户的热负荷特性,建立以数据中心余热为热源的余热补偿系统工作模型,并采用管式模型预测控制策略对模型进行调控。最后,通过算例验证了所提调控策略能够抑制数据负载不确定性影响,在保证供暖目标的同时有效提高了系统运行的经济性。
As the main heat source of the traditional heating system
the combined heat and power unit faces the problem of thermo-electric load mismatch of in the system when operating under the mode of determining heat by power. Therefore
a regulation strategy of waste heat compensation system for data center considering thermo-electric load mismatch is proposed. Firstly
the time-transferable characteristic of the data load is analyzed
a data load model with uncertainties is built and the operating power of the server is calculated. Then
based on the thermo-electric characteristics of the servers in the data center and the thermal load characteristics of community users
a working model of the waste heat compensation system with the waste heat of the data center as the heat source is established
and the tube-model predictive control (Tube-MPC) strategy is adopted to regulate and control the model. Finally
through numerical cases
it is verified that the proposed regulation strategy can suppress the influence of data load uncertainty
and effectively improve the economic operation of the system while ensuring the heating target.
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