综合智慧能源2026，Vol.48Issue(9)：107-119,13.DOI:10.3969/j.issn.2097-0706.2026.09.009
计及算力负载时空特性的算-电-热系统协同优化调度
Optimal scheduling of integrated computation-electricity-thermal systems considering the spatiotemporal characteristics of computing workload
摘要
Abstract
The coordinated optimization and scheduling of power and computing resources help facilitate the local consumption of renewable energy,fully leverage the flexibility of data center energy usage,and effectively reduce data center energy costs.Existing research has not adequately quantified spatial scheduling models,and thermal-side scheduling models are overly simplified.Therefore,to enhance the operational efficiency of power systems and data centers,an optimal scheduling strategy for integrated computation-electricity-heat systems considering the spatiotemporal characteristics of computing loads was proposed.The conventional approach of treating each data center as a single node was overcome.When spatial migration of computing loads was considered,the dynamic transmission losses and fiber-optic transmission constraints of the optical communication network were finely quantified,and the corresponding transmission costs were incorporated into the objective function.Subsequently,the existing strategy of simultaneously increasing or decreasing the power of heat-generating and cooling equipment was changed.Indoor thermodynamic equations of data centers were established.Based on the tiered electricity pricing mechanism,the advance storage and delayed release of cooling energy were achieved by the thermal storage capacity of the building.With the aim of minimizing total cost while ensuring service quality,an optimal scheduling model for integrated computation-electricity-heat systems was constructed to separately investigate the effects of thermal-side scheduling and spatial scheduling.Two data centers were used as the research objects.Based on a 12-node system,the two regions operated under different peak-valley electricity pricing schemes and featured distinct wind and solar power output curves as well as summer outdoor temperatures.The system met the requirements of both batch and interactive computing loads by scheduling 120 servers,while satisfying indoor temperature and CPU temperature constraints through the scheduling of cooling and heating sources.Simulation results demonstrated that the proposed scheduling strategy achieved spatiotemporal scheduling of computing loads.Across all time periods,the proportion of tasks completed within 0-2 h of arrival increased,and service quality improved.The power balance chart showed a remarkably high degree of matching between source and load.Considering spatial scheduling,the strategy could perform peak shaving and valley filling for various types of computing loads,thereby optimizing the spatiotemporal distribution of regional power loads,avoiding concentrated task accumulation,and reducing the frequency of start-stop cycles of large-scale servers,thereby significantly extending hardware service life and reducing maintenance costs.Considering thermal-side scheduling,the strategy can significantly reduce economic costs while maintaining service quality,offering a reference for the economical and efficient operation of data centers.关键词
算电协同/数据中心/光纤传输约束/冷量优化调度/服务质量约束/优化调度策略Key words
computing-electricity coordination/data center/fiber-optic transmission constraints/optimized scheduling of cooling capacity/quality of service constraints/optimal scheduling strategy分类
能源科技引用本文复制引用
苏璇,于宗民,巨云涛,王碧清..计及算力负载时空特性的算-电-热系统协同优化调度[J].综合智慧能源,2026,48(9):107-119,13.基金项目
国家自然科学基金项目(52237008) National Natural Science Foundation of China(52237008) （52237008）
