Nan Hu, Ting Huang, Geliang Chen, L. Dai, Wenting Huang, Miao Jia, Xinyu Luo, Jiaye Tuo
{"title":"A Risk-Sensitive Control Strategy for Frequency Stability of Edge Data Center","authors":"Nan Hu, Ting Huang, Geliang Chen, L. Dai, Wenting Huang, Miao Jia, Xinyu Luo, Jiaye Tuo","doi":"10.1109/ICEI52466.2021.00034","DOIUrl":null,"url":null,"abstract":"In the era of big data, the computing tasks of data are gradually decentralized to the edge data center which is close to the demand side. When massive amounts of data are processed at the edge data center, the uncertainty and randomness of its renewable energy supply and irregular operations of demand-side edge devices at the edge data center may cause an imbalance between energy supply and demand sides, resulting in drastic fluctuations in bus frequency deviation. In this paper, an optimal management strategy of the frequency stabilization is proposed on the basis of risk-sensitive control method. In the considered edge data center, which is considered as a microgrid, the renewable energy source (RES) is served as the main energy supplement with the subordination of the controllable generators and battery energy storage devices (BES). With the energy and data interaction between different edge data centers, the overloaded computing tasks can be transmitted to nearby edge data centers and the power imbalance can also be alleviated through the energy dispatching. The same as the data transmission process of Internet, transmission control protocol (TCP) model is applied to model the information and energy transmission process of different edge data centers, and the stochastic differential equations are utilized to model the power of wind turbines and photovoltaic panels. Then, the frequency stability issue is transformed into the risk-sensitive control problem considering the randomness of the system and the external disturbance. Finally, simulation results show the effectiveness of the proposed control strategy.","PeriodicalId":113203,"journal":{"name":"2021 IEEE International Conference on Energy Internet (ICEI)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Energy Internet (ICEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEI52466.2021.00034","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In the era of big data, the computing tasks of data are gradually decentralized to the edge data center which is close to the demand side. When massive amounts of data are processed at the edge data center, the uncertainty and randomness of its renewable energy supply and irregular operations of demand-side edge devices at the edge data center may cause an imbalance between energy supply and demand sides, resulting in drastic fluctuations in bus frequency deviation. In this paper, an optimal management strategy of the frequency stabilization is proposed on the basis of risk-sensitive control method. In the considered edge data center, which is considered as a microgrid, the renewable energy source (RES) is served as the main energy supplement with the subordination of the controllable generators and battery energy storage devices (BES). With the energy and data interaction between different edge data centers, the overloaded computing tasks can be transmitted to nearby edge data centers and the power imbalance can also be alleviated through the energy dispatching. The same as the data transmission process of Internet, transmission control protocol (TCP) model is applied to model the information and energy transmission process of different edge data centers, and the stochastic differential equations are utilized to model the power of wind turbines and photovoltaic panels. Then, the frequency stability issue is transformed into the risk-sensitive control problem considering the randomness of the system and the external disturbance. Finally, simulation results show the effectiveness of the proposed control strategy.