# Reducing the Operational Cost of Cloud Data Centers through Renewable Energy
## 5 Results  
This section is devoted to the evaluation of the benefits of the introduction of RE in a complex multi-site cloud computing infrastructure and of the effectiveness of EcoMultiCloud as an approach to maximize the performance of the system. The scenario under analysis is the same as in [38; 39], with four interconnected DCs and values of the PUE as reported in Table 1; time zones are also indicated with respect to UTC, assuming that the DC locations are, respectively, California, Ontario (Canada), the U.K. and Germany. Figure 4 reports energy prices in a 24-h interval; again, time is expressed in UTC. Energy prices are taken or extrapolated from the following websites:  
* California: www.pge.com/tariffs/IndustrialCurrent.xls
* Ontario:[[https://www.hydroone.com/rates-and-billing/rates-and-charges/electricity-pricing-and-costs](https://www.hydroone.com/rates-and-billing/rates-and-charges/electricity-pricing-and-costs)]([https://www.hydroone.com/rates-and-billing/rates-and-charges/electricity-pricing-and-costs](https://www.hydroone.com/rates-and-billing/rates-and-charges/electricity-pricing-and-costs))
* U.K.: www.westernpower.co.uk/docs/system-charges/LC14-v6-5-SWEB-Final-13-14.aspx
* Germany: www.iwr-institut.de/en/press/background-informations  
Figure 4: Energy price, expressed as $/kWh, for the 4 DCs, versus time of the day. To simplify the analysis, it is assumed that the prices repeat periodically for a few days. For the computation of the term \(C_{i}\), the PUE of DC \(i\) is considered as in Table 1.  
Each DC was equipped with a set of PV panels, made up by multiple modules enabling the conversion of solar radiation into electricity with an efficiency that depends on the adopted PV technology. The nominal capacity of a PV module corresponds to the maximum output power obtained by the PV device under standardized environmental conditions (including a light intensity of 1000 W/m\({}^{2}\) and a temperature of 25 \(\circ\)C) from the conversion of solar radiation into electricity, and it is commonly measured in peak Watts (\(W_{p}\)). The efficiency of currently available commercial modules may achieve 20% [40]. Considering some among the most efficient PV modules built with traditional technologies, i.e., crystalline silicon, and currently available on the market, a nominal capacity of 0.333 kWp was observed for modules with an area of 1.63 m\({}^{2}\), hence a PV panel surface of about 4.9 m\({}^{2}\) could be assumed per each kWp of PV panel capacity [41]. The PV panel capacity is denoted as \(S_{PV}\). Real RE generation profiles obtained from the tool PVWatts were used in the simulations. This tool allows one to retrieve real traces of RE production per kWp of PV panel capacity during the typical meteorological year in a given location [42]. In order to address the intermittent RE production, each DC was equipped with a variable number of lead-acid batteries for harvesting purposes, this being one of the most common storage technology adopted in PV systems [43]. Storage elements with a capacity of 200 Ah and voltage of 12 V were considered, corresponding to 2.4 kWh of nominal storage capability. In this work, the battery capacity, expressed in kWh, is denoted as \(B\). An average charge efficiency of 85% is commonly assumed for lead-acid batteries [44]; when considering also the discharging process, the total energy efficiency was estimated to be 75% [45], meaning that for each energy unit (1 kWh) drawn from the storage, around 1.33 kWh of RE must have been produced and harvested in the battery bank. Data about VMs and physical hosts were taken from the logs of a proof of concept performed by the company Eco4 Cloud srl (www.eco4 cloud.com), a spin-off from the National Research Council of Italy, on the DC of a telecommunication operator. The DC contained 112 servers virtualized with the platform VMware vSphere 5.0. Among the servers, 76 were equipped with processor Xeon 24 cores and 100-GB RAM and 36 with processor Xeon 16 cores and 64-GB RAM.