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1.浙江大学电气工程学院,浙江省杭州市 310027
2.国网浙江省电力有限公司杭州供电公司,浙江省杭州市 310007
Received:18 May 2023,
Revised:2023-09-19,
Published Online:10 November 2023,
Published:25 December 2023
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王雨欣,陆海波,叶承晋等.考虑多类型市场协同的互联数据中心运营策略[J].电力系统自动化,2023,47(24):121-131.
WANG Yuxin,LU Haibo,YE Chengjin,et al.Operation Strategy for Internet Data Centers Considering Collaboration of Multi-type Markets[J].Automation of Electric Power Systems,2023,47(24):121-131.
王雨欣,陆海波,叶承晋等.考虑多类型市场协同的互联数据中心运营策略[J].电力系统自动化,2023,47(24):121-131. DOI: 10.7500/AEPS20230518007.
WANG Yuxin,LU Haibo,YE Chengjin,et al.Operation Strategy for Internet Data Centers Considering Collaboration of Multi-type Markets[J].Automation of Electric Power Systems,2023,47(24):121-131. DOI: 10.7500/AEPS20230518007.
随着云计算的发展和新型基础设施建设的推进,为满足海量数据的存储与处理需求,互联数据中心用电量增长快速。在新型电力系统和全国统一电力市场体系建设背景下,负载可调的互联数据中心作为主体可参与电能量和辅助服务市场。此外,数据中心运行中会产生大量余热,具备提供区域供热服务的潜力。基于此,文中首先分析拥有多区域互联数据中心的云服务提供商在多类型市场耦合环境下的价值形成过程,并建立相应的市场行为模型。然后,构建互联数据中心参与多类型电力市场及供热服务的双层决策框架与模型。上层模型为以工作负载为直接决策变量,以市场竞标电量、热量为间接决策变量,以用能成本最小为目标的云服务提供商决策模型;下层模型为以社会福利最大化为目标的市场出清模型。最后,结合算例进行仿真,验证了所提多市场耦合决策机制对提升互联数据中心效益、降低用能成本的有效性。
With the development of cloud computing and the advancement of new infrastructure construction
the electricity consumption of Internet data centers (IDCs) is growing rapidly to meet the storage and processing needs of massive data. In the context of the construction of the new power system and the national unified electricity market
IDCs with adjustable loads can participate as the main body in electricity energy and auxiliary service markets. In addition
the operation of IDC generates a large amount of waste heat
which has the potential to provide regional heating services. On this basis
this paper first analyzes the value formation process of the Internet service provider (ISP) with multi-regional IDCs in a multi-type market coupling environment and establishes the corresponding market behavior model. Then
a bi-level decision-making framework and model for IDCs to participate in multi-type electricity markets and heating service are constructed. The upper-level model is an ISP decision-making model that takes workload as the direct decision variable
market bidding electricity and heat as indirect decision variables
and aims to minimize energy costs. The lower-level model is a market clearing model with the objective of maximizing social welfare. Finally
simulation is conducted using a case to verify the effectiveness of the proposed multi-market coupling decision-making mechanism in improving the benefit of IDCs and reducing energy costs.
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