## 2 Modeling of Novel Electrical Load Resources in UDNs
### Idc  
IDCs possess substantial computing resources and storage devices, which can be flexibly scheduled according to UDNs' demands [6]. Through demand response programs, IDCs can reduce energy consumption during peak electricity demand periods or increase energy consumption during off-peak periods, providing flexible resources for UDNs [24]. The total load \(P_{\text{IDC}}^{t}\) of the IDC is expressed as follows:  
\[P_{\text{IDC}}^{t}=P_{\text{ITM}}^{t}+P_{\text{ITM}}^{t}+P_{\text{C}}^{t}+e_{ O}^{t} \tag{8}\]  
where \(P_{\text{ITM}}^{t}\) represents the power of information technology (IT) equipment at time \(t\) to meet the minimum quality of service (QoS); \(P_{\text{ITM}}^{t}\) represents the additional power of IT equipment at time \(t\) to enhance QoS; \(P_{\text{C}}^{t}\) represents the power of the cooling system at time \(t\); and \(e_{O}^{t}\) represents the power of other equipment at time \(t\). When developing the regulation potential of IDCs as internal resources of a VPP, it is essential to consider constraints such as IT equipment power constraints, cooling system power constraints, and demand response strategy constraints within the IDC. Regarding IT equipment power constraints, IDCs must maintain a certain level of IT equipment power to handle interactive and batch workloads. This portion of power is a necessary condition to meet QoS requirements and cannot be reduced, which is expressed as follows:  
\[P_{\text{ITM}}^{t}=\left(\frac{n_{\text{E}}e_{\text{E}}+n_{\text{A}}e_{\text{A }}+n_{\text{C}}e_{\text{C}}}{n_{\text{S}}}+e_{\text{I}}\right)\left(m_{\text{ IM}}^{t}+\sum_{q=1}^{n_{\text{B}}}m_{\text{BM}}^{q,t}\right) \tag{9}\]  
where \(n_{\text{E}}\) is the number of edge switches; \(e_{\text{E}}\) is the rated power consumption of each edge switch; \(n_{\text{A}}\) is the number of aggregation switches; \(e_{\text{A}}\) is the rated power consumption of each aggregation switch; \(n_{\text{C}}\) is the number of core switches; \(e_{\text{C}}\) is the rated power consumption of each core switch; \(n_{\text{S}}\) is the total number of servers; \(e_{\text{I}}\) is the idle/peak power of each active server; \(m_{\text{IM}}^{t}\) is the minimum number of active servers serving interactive workloads in the IDC at time \(t\); \(m_{\text{BM}}^{q,t}\) is the minimum number of active servers serving the \(q\)-th type of batch workloads in the IDC at time \(t\); and \(n_{\text{B}}\) is the total number of batch workload types. To enhance QoS, IDCs configure additional IT equipment power. This portion of power can be adjusted according to demand response strategies but must maintain a certain redundancy to handle sudden workloads, which is constrained as follows:  
\[P_{\text{ITH}}^{t}\leq\left(n_{\text{E}}e_{\text{E}}+n_{\text{A}}e_{\text{A}} +n_{\text{C}}e_{\text{C}}+n_{\text{S}}e_{\text{P}}\right)-P_{\text{ITM}}^{t} \tag{10}\]  
where \(e_{\text{P}}\) is the peak power of each active server. Regarding cooling system power constraints, the cooling system's power needs to be adjusted according to the heat dissipation of IT equipment and indoor temperature but cannot exceed its upper power limit. The expression for the cooling system power \(P_{\text{C}}^{t}\) at time \(t\) is as follows:  
\[P_{\text{C}}^{t}=b_{1}h^{t}+b_{2} \tag{11}\]  
where \(b_{1}\) is the cooling efficiency coefficient; \(h^{t}\) is the thermal cooling power of the data center at time \(t\); and \(b_{2}\) is the base power consumption of the cooling system without thermal load. The constraint for the cooling system power is as follows:  
\[b_{2}\leq P_{\text{C}}^{t}\leq P_{\text{C,max}} \tag{12}\]  
where \(P_{\text{C,max}}\) is the maximum power of the cooling system. In addition, the indoor temperature of the IDC must be maintained within a reasonable range to ensure the regular operation of the equipment.