
数据中心园区能源互联网的关键技术与发展模式
Key Technologies and Development Modes of Park Energy Internet in Data Centers
数据中心作为“新基建”的重要方向之一,其节能降耗问题一直是领域的研究重点。园区能源互联网注重清洁能源消纳,强调能源利用效率的提升,其“源–网–荷–储–充”的协调技术是提升数据中心能效的关键,探索数据中心园区能源互联网的关键技术与发展模式具有现实意义,然而目前数据中心与园区能源互联网的研究各自独立,技术之间缺乏相互结合。本文针对目前两者融合研究的领域空白,首先分析了数据中心与园区能源互联网技术的结合点,探讨其在设备规划、直流配电、余热回收、多能调度、负荷管理以及储能调度6 方面的关键技术与融合方向。在此基础上提出数据中心园区能源互联网的基本建设架构,对商业与运营模式进行论证,并展望领域未来发展的重点。最后,针对我国数据中心园区能源互联网的进一步发展提出建议,技术融合、试点实践、政策扶持及三者的有机结合是保障发展的关键。
Data center is one of the important directions of the New Infrastructure initiative, and the energy efficiency of the data centers has always been a focus of research. Park Energy Internet (PEI) is a system that emphasizes the consumption of clean energy and the promotion of energy efficiency. The “generation, grid, load, storage, and charging” coordination technology of PEI will be the key to improving the energy efficiency of data centers. So exploring the key technologies and development modes of PEI in data centers will be significant. However, the current research on data centers and PEI is independent to each other. Therefore, this study analyzes the integration of data centers and PEI, and discusses the key technologies in equipment planning, DC power distribution, waste heat recovery, multi-energy dispatch, load management, and energy storage dispatch. On this basis, we proposes the infrastructure framework of the PEI in data centers, explores its business models, and prospects the priority of further development. Finally, suggestions for the further development of the PEI in data centers in China are proposed; technology integration, pilot practice, and policy support are the key elements which promote its development.
能源互联网 / 数据中心 / 设备规划 / 运行优化 / 商业模式
Energy Internet / data center / equipment planning / operation optimization / business model
[1] |
Cao Y J, Li Q, Tan Y, et al. A comprehensive review of energy Internet: Basic concept, operation and planning methods, and research prospects [J]. Journal of Modern Power Systems and Clean Energy, 2018, 6(3): 399–411.
|
[2] |
Basmadjian R, Botero J F, Giuliani G, et al. Making data centers fit for demand response: Introducing GreenSDA and GreenSLA contracts [J]. IEEE Transactions on Smart Grid, 2018, 9(4): 3453– 3464.
|
[3] |
程洁. 基于冷热电三联供系统的综合能源系统设计与研究 [D]. 北京: 华北电力大学(硕士学位论文), 2017. Cheng J. The design and research of comprehensive energy system based on the CCHP system [D]. Beijing: North China Electric Power University(Master’s thesis), 2017.
|
[4] |
刘高科, 沈国民, 徐新华, 等. 某车站综合体天然气冷热电联供 系统方案研究 [J]. 煤气与热力, 2018, 38(8): 22–27. Liu G K, Shen G M, Xu X H, et al. Design study on natural gas combined cooling, heating and power system for a station complex [J]. Gas & Heat, 2018, 38(8): 22–27.
|
[5] |
仇知, 王蓓蓓, 贲树俊, 等. 计及不确定性的区域综合能源系 统双层优化配置规划模型 [J]. 电力自动化设备, 2019, 39(8): 176–185. Qiu Z, Wang B B, Ben S J, et al. Bi-level optimal configuration planning model of regional integrated energy system considering uncertainties [J]. Electric Power Automation Equipment, 2019, 39(8): 176–185.
|
[6] |
赵瑾, 雍静, 郇嘉嘉, 等. 基于长时间尺度的园区综合能源系统 随机规划 [J]. 电力自动化设备, 2020, 40(3): 62–67. Zhao J, Yong J, Huan J J, et al. Stochastic planning of park-level integrated energy system based on long time-scale [J]. Electric Power Automation Equipment, 2020, 40(3): 62–67.
|
[7] |
姚钢, 茆中栋, 殷志柱, 等. 楼宇直流配电系统关键技术研究综 述 [J]. 电力系统保护与控制, 2019, 47(15): 156–170. Yao G, Mao Z D, Yin Z Z, et al. Key technologies of building DC power distribution system: An overview [J]. Power System Protection and Control, 2019, 47(15): 156–170.
|
[8] |
周京华, 吴杰伟, 陈亚爱, 等. 张北阿里云数据中心柔性直流输 配电系统 [J]. 电气应用, 2019, 38(1): 54–58. Zhou J H, Wu J W, Chen Y A, et al. Zhangbei Alicloud data center flexible DC transmission and distribution system [J]. Electrotechnical Application, 2019, 38(1): 54–58.
|
[9] |
张勇军, 刘子文, 宋伟伟, 等. 直流配电系统的组网技术及其应 用 [J]. 电力系统自动化, 2019, 43(23): 39–49. Zhang Y J, Liu Z W, Song W W, et al. Networking technology and its application of DC distribution system [J]. Automation of Electric Power Systems, 2019, 43(23): 39–49.
|
[10] |
Woodruff J Z, Brenner P, Buccellato A P C, et al. Environmentally opportunistic computing: A distributed waste heat reutilization approach to energy efficient buildings and data centers [J]. Energy and Buildings, 2014, 69: 41–50.
|
[11] |
Davies G F, Maidment G G, Tozer R M. Using data centers for combined heating and cooling: An investigation for London [J]. Applied Thermal Engineering, 2016, 94: 296–304.
|
[12] |
Zhang P L, Wang B L, Wu W, et al. Heat recovery from internet data centers for space heating based on an integrated air conditioner with thermosyphon [J]. Renewable Energy, 2015, 80: 396–406.
|
[13] |
林晓明, 张勇军, 肖勇, 等. 计及设备启停的含电转气园区能源 互联网两阶段优化调度模型 [J]. 广东电力, 2019, 32(10): 62–70. Lin X M, Zhang Y J, Xiao Y, et al. A two-stage dispatch model of park energy Internet with P2G devices considering start-up state of devices [J]. Guangdong Electric Power, 2019, 32(10): 62–70.
|
[14] |
白牧可, 王越, 唐巍, 等. 基于区间线性规划的区域综合能源系 统日前优化调度 [J]. 电网技术, 2017, 41(12): 240–247. Bai M K, Wang Y, Tang W, et al. Day-ahead economical dispatch of electricity-gas-heat integrated energy system based on distributionally robust optimization [J]. Power System Technology, 2017, 41(12): 240–247.
|
[15] |
Dolatabadi A, Jadidbonab M, Mohammadi-Ivatloo B. Shortterm scheduling strategy for wind-based energy hub: A hybrid stochastic/IGDT approach [J]. IEEE Transactions on Sustainable Energy, 2019, 10(1): 438–448.
|
[16] |
高晓松, 李更丰, 肖遥, 等. 基于分布鲁棒优化的电–气–热综合 能源系统日前经济调度 [J]. 电网技术, 2020, 44(6): 2245–2254. Gao X S, Li G F, Xiao Y, et al. Day-ahead economical dispatch of electricity–gas–heat integrated energy system based on distributionally robust optimization [J]. Power System Technology, 2020, 44(6): 2245–2254.
|
[17] |
Frederic B, Martin D, Jorg A, et al. Power model design for ICT systems—A generic approach [J]. Computer Communications, 2014, 50(1): 77–85.
|
[18] |
Dan X, Xin L, Bin F. Efficient server provisioning and offloading policies for Internet datacenters with dynamic load demand [J]. IEEE Transactions on Computers, 2015, 64(3): 682–697.
|
[19] |
Lei H T, Zhang T, Liu Y J, et al. SGEESS: Smart green energyefficient scheduling strategy with dynamic electricity price for data center [J]. The Journal of Systems and Software, 2015, 108: 23–38.
|
[20] |
刘继春, 周春燕, 高红均, 等. 考虑氢能–天然气混合储能的电– 气综合能源微网日前经济调度优化 [J]. 电网技术, 2018, 42(1): 170–179. Liu J C, Zhou C Y, Gao H J, et al. A day-ahead economic dispatch optimization model of integrated electricity–natural gas system considering hydrogen-gas energy storage system in microgrid [J]. Power System Technology, 2018, 42(1):170–179.
|
[21] |
练依情, 郭祚刚, 马溪原, 等. 考虑热备用的气–电耦合园区综合 能源系统弹性调度 [J]. 电力系统及其自动化学报, 2019, 31(11): 115–121. Lian Y Q, Guo Z G, Ma X Y, et al. Resilience scheduling of integrated electricity and gas community system considering hot reservation [J]. Proceedings of the CSU–EPSA, 2019, 31(11): 115–121.
|
[22] |
何畅, 程杉, 徐建宇, 等. 基于多时间尺度和多源储能的综合能 源系统能量协调优化调度 [J]. 电力系统及其自动化学报, 2020, 32(2): 77–84, 97. He C, Cheng S, Xu J Y, et al. Coordinated optimal scheduling of integrated energy system considering multi-time scale and hybrid energy storage system [J]. Proceedings of the CSU–EPSA, 2020, 32(2): 77–84, 97.
|
/
〈 |
|
〉 |