| 引用本文: | 可思为,董 萍,马铭宇,王春玲,刘明波.考虑风光荷时空互补的多能源绿色数据中心多目标配置方法[J].电力系统保护与控制,2024,52(22):22-33.[点击复制] |
| KE Siwei,DONG Ping,MA Mingyu,WANG Chunling,LIU Mingbo.A multi-objective allocation method for multi-energy green data centers considering wind,solar and load spatial-temporal complementarity[J].Power System Protection and Control,2024,52(22):22-33[点击复制] |
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| 摘要: |
| 为解决数据中心高能耗、高碳排放的问题，提出了一种考虑风光荷时空互补的绿色数据中心“风-光-储”多种能源多目标容量配置模型。首先，根据数据中心的时空转移特性及储能设备的运行特性，建立绿色数据中心多能架构中灵活性资源的数学模型。接着，在数据中心与储能的灵活性运行基础上，提出一种源荷互补性指标来描述源荷间的供需差异，并以平均度电成本与供需差异最小作为优化目标建立容量优化配置模型。最后，采用风电、光伏的全年出力预测数据进行模拟，利用Benders算法对容量配置模型进行求解，得到各数据中心的最优投资建设方案。算例分析验证了所提模型的有效性，结果表明引入新能源-储能供电以及数据中心时空灵活性能够降低用电成本，并提高了新能源的渗透率。 |
| 关键词: 绿色数据中心 风光荷互补 容量配置 Benders分解 |
| DOI：10.19783/j.cnki.pspc.240581 |
| 投稿时间：2024-05-11修订日期：2024-07-24 |
| 基金项目:国家自然科学基金项目资助(52077083)；广东省自然科学基金海上风电联合基金项目资助(2022A1515240076) |
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| A multi-objective allocation method for multi-energy green data centers considering wind,solar and load spatial-temporal complementarity |
| KE Siwei,DONG Ping,MA Mingyu,WANG Chunling,LIU Mingbo |
| (College of Electric Power, South China University of Technology, Guangzhou 510640, China) |
| Abstract: |
| To solve the problem of high energy consumption and high carbon emission in data centers, this paper proposes a multi-objective capacity configuration model for wind-photovoltaic-storage multi-energy sources in green data centers. It considers the spatio-temporal complementarity of wind, solar and load. First, a mathematical model of flexibility resources in the multi-energy architecture of green data centers is established based on the spatial-temporal transfer characteristics of data centers and the operational characteristics of energy storage devices. Then, based on the flexible operation of data centers and energy storage, a complementarity index is proposed to describe the supply-demand difference between sources and loads. A capacity optimization model is established with the average kilowatt-hour cost and the minimum supply-demand difference as the optimization objectives. Finally, the annual output forecast data of wind power and photovoltaic are used for simulation and the capacity allocation model is analyzed using the Benders algorithm to obtain the optimal investment and construction plan for each data center. Case study analysis verifies the validity of the proposed model, and the results show that the introduction of renewable energy-energy storage power supply and data center spatio-temporal flexibility can reduce electricity costs and increase the penetration rate of renewable energy. |
| Key words: green data center wind-photovoltaic-load complementarity capacity allocation Benders decomposition |
