## 9 Discussion  
The previous analysis demonstrated that ORC systems driven by hot water offer higher efficiency than air-based systems and require lower flow rate input and size for the primary heat exchanger to evaporate the organic fluid. It is important to note that the temperatures of heat and cold sources significantly influence the ORC operating conditions. For example, if alternative cold sources were available, the condensation pressure could be significantly reduced, thereby expanding the pressure ratio and the operational range of the turbo-expander. A practical instance might include facilities that manage cold sources, such as those using refrigerants for food preservation or medical centers and hospitals equipped with cryogenic fluids like liquid nitrogen [103]. While this is just an example, it aptly demonstrates the potential for energy and mass waste recovery, contributing to the waste-to-energy chain and the circular energy economy, as well as clean energy production and decarbonization. Nonetheless, a comprehensive system feasibility assessment must consider economic factors. This study focuses on outlining the purely technical and energetic aspects, aiming to engineer a system that is as realistic as possible. The design approach outlined in this paper aligns with standard energy consumption metrics commonly used in data centers [104; 105]. For this purpose, the power usage effectiveness (PUE), the energy reuse effectiveness (ERE), and the energy reuse factor are adopted to evaluate the energy performance of data centers and the possible benefits of DC heat exploitation through the proposed ORC systems. The power usage effectiveness is as follows [105; 106]:  
\[\mathrm{PUE}=\frac{P_{IT}+P_{C}+P_{A}}{P_{IT}} \tag{25}\]  
where \(P_{IT}\) is the power consumption of the information technology (IT) system, \(P_{A}\) represents the power request of the auxiliary equipment (e.g., uninterrupted power supply units, highlighting system, control devices), and \(P_{C}\) is the power demand of the cooling apparatus. The energy reuse factor and the energy reuse effectiveness are as follows [104; 107; 108]:  
\[\mathrm{ERF}=\frac{P_{r}}{P_{IT}+P_{C}+P_{A}}=\frac{P_{ORC}}{P_{IT}+P_{C}+P_{ A}} \tag{26}\]  
\[\mathrm{ERE}=\frac{P_{IT}+P_{C}+P_{A}-P_{r}}{P_{IT}}=\mathrm{PUE}\ (1-\mathrm{ERF}) \tag{27}\]  
where \(P_{r}\) is the power reuse, equivalent to the ORC electric power for the investigated case. The analysis considers a reference data center, whose main characteristics are in Table 5[109], as a possible example of DC heat reuse based on the results of the previous sections. However, the main results can extend to similar configurations with different sizes. The reference data center presents a total area for IT rooms equal to about 5700 m\({}^{2}\), with a total power for IT equipment and auxiliary systems equal to 12.9 MW and 0.97 MW, respectively. The power usage effectiveness corresponds to 1.295. The data center heat exploitation assures an ORC installation with 665 kW as the maximum electric power at 3.7% electric efficiency, adopting isopentane as the working fluid, 41.7 \({}^{\circ}\)C as the evaporation temperature, and liquid cooling for the DC apparatus. The ERF index is 0.041, illustrating that the ORC electric power corresponds to 4.1% of the total DC power request for IT equipment, auxiliary systems, and cooling apparatus. The proposed organic Rankine cycle assures an energy reuse effectiveness equal to 1.242, compared to a PUE equal to 1.295 in the reference scenario without DC heat reuse, in line with the literature [110]. The ORC integration assures a yearly 5972 MWh electric generation and saves 3328 tons of equivalent carbon dioxide (\(\text{t}_{\text{CO2,eq}}\)) in terms of greenhouse gas (GHG) emissions, adopting the 2023 emission factors for electric generation in China [111].