With the explosive growth of online services, the Internet Data Center (IDC) has become an emerging load demand . The power consumption of IDCs are believed suitable for demand response (DR) purposes due to its temporal-spatial flexibility properties. To what extent IDCs could be used as candidate DR resources to provide capacity support are dependent both on the technical property and the willingness of data end-users . To address the above issue, this paper presents a methodological framework for quantifying the potential value of IDC-based DR in distribution grids. To achieve this, the concept of capacity credit (CC) is introduced and extended into the IDC scenario. The proposed framework explicitly considered the impacts of uncertainty of user participation intention and the reliability of basic information in the DR process. A novel Z-number based price elasticity uncertainty model is introduced, and a more realistic evaluation of IDC capacity credit is obtained. Finally, the effectiveness of the proposed model and method is illustrated on a modified IEEE-33 node network, and the obtained results verify the significance of IDC-based DR in enhancing the adequacy of supply in distribution grids.

With the explosive growth of online services, the Internet Data Center (IDC) has been constantly growing, and becoming an emerging load demand in modern power systems. The power consumption of IDCs is believed suitable for demand response (DR) purposes. However, to what extent IDCs could be used as candidate DR resources to provide capacity support are not only dependent on the technical property of IDC equipment but also affected by the willingness of data end-users to participate in the DR program. To address the above issue, this paper presents a methodological framework for quantifying the potential value of IDC-based DR in smart distribution grids. To achieve this, through comprehensive consideration of operational constraints for both data center and power systems, the concept of capacity credit (CC) is introduced and extended into the IDC scenario. The proposed framework explicitly considered the impacts of both uncertainty of user participation intention and the reliability of basic information in the DR process. A novel Z-number based price elasticity uncertainty model is introduced, and then a more realistic evaluation of IDC capacity credit is obtained. Finally, the effectiveness of the proposed model and method is illustrated on a modified IEEE-33 node network, and the obtained results verify the significance of IDC-based DR in enhancing the adequacy of supply in distribution grids.