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1.沈阳工业大学电气工程学院,辽宁省沈阳市 110870
2.东北大学信息科学与工程学院,辽宁省沈阳市 110167
3.丹麦奥尔堡大学计算机系,奥尔堡 92200,丹麦
4.中国南方电网电力调度控制中心,广东省广州市 510663
5.国网辽宁省电力有限公司抚顺供电公司,辽宁省抚顺市 113008
Received:20 June 2025,
Revised:2025-12-30,
Online First:04 March 2026,
Published:10 September 2026
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ZHENG Fangfang,HUANG Yujia,SUN Qiuye,et al.Computing Power-Electric Power Integrated Dispatch Based on Reward-Penalty Balance Mechanism[J].Automation of Electric Power Systems,2026,50(17):52-61.
郑芳芳,黄雨佳,孙秋野等.基于激励惩罚平衡机制的算电一体化调度[J].电力系统自动化,2026,50(17):52-61. DOI: 10.7500/AEPS20250620010.
ZHENG Fangfang,HUANG Yujia,SUN Qiuye,et al.Computing Power-Electric Power Integrated Dispatch Based on Reward-Penalty Balance Mechanism[J].Automation of Electric Power Systems,2026,50(17):52-61. DOI: 10.7500/AEPS20250620010.
数据中心作为新型灵活性资源参与需求响应,可有效促进风光消纳,但会引发数据中心与租户的利益冲突,阻碍算力负荷的灵活调度,降低算电一体化的优化效果。为此,设计激励和惩罚机制,提出基于混合博弈的算电一体化调度方法。首先,对数据中心能耗特性建模,使批处理式数据负荷参与需求响应,并针对最大延迟时间对服务质量的影响考虑惩罚成本。其次,设计激励机制并基于Shapley值对激励进行再分配,同时设计惩罚机制,再根据边际贡献平衡二者,合理分配收益与风险。然后,构建算电一体化两阶段调度模型。第1阶段,微网运营商以最小化运行成本为目标;第2阶段,租户以最大化净收益为目标。租户间为合作博弈,阶段间为主从博弈,整体形成混合博弈架构。最后,通过算例验证了所提方法的有效性。
As a new flexibility resource participating in demand response
data centers can effectively promote the accommodation of wind and photovoltaic power. However
this may lead to conflicts of interest between data centers and tenants
hinder the flexible scheduling of computing-power loads
and reduce the optimization effect of computing power-electric power integration. To address this
this paper designs a reward-penalty mechanism and proposes a mixed game based computing power-electric power integrated dispatch method. Firstly
the energy consumption characteristics of the data center are modeled to enable batch-processing data loads to participate in demand response. Penalty costs are considered for the impact of maximum latency on service quality. Secondly
a reward mechanism is designed and rewards are redistributed based on Shapley values. Meanwhile
a penalty mechanism is established. Then
the reward and penalty are balanced according to marginal contributions to achieve a reasonable allocation of benefits and risks. After that
a two-stage computing power-electric power integrated dispatch model is constructed. In the first stage
the microgrid operators aim at minimizing the operating cost. In the second stage
the tenant aims to maximize the net income. The relationship among tenants constitutes a cooperative game
while the relationship between phases forms a Stackelberg game
collectively forming a mixed game framework. Finally
the effectiveness of the proposed method is validated through cases.
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