## 2 Materials and Methods  
### System Description  
The logistics center adopted was a logistics and service center specializing in the food industry located in Spain. It provides services to other companies in the sector such as renting spaces equipped with proper refrigeration chambers if required, offices, 24/7 security services, parking lots, waste separation, and treatment, among others. Figure 2 shows the plan of the whole site with the distribution of the available spaces. The specific units of interest for this study are highlighted and specified in the legend. This study aimed to provide a more in-depth analysis into the energy and power consumption patterns of the main units of the logistics center and highlight some recommendations for improvement by reducing the costs associated with the electric energy consumed from the grid. Among the units in Figure 2, we emphasized the administration building; warehouses 1, 2, and 3; the fish processing unit; the waste treatment and pressure units; and the parking lots of the logistics center, which had an overall electricity consumption of about 650 MWh/year. The share of the annual electric energy consumption required for the operation of each unit are provided Figure 3, where 24.4% corresponded to the wastewater treatment, 24.9% to cooling in refrigeration chambers, and 37.7% to lighting the spaces. Figure 3: Annual energy consumption shares of the studied units. Figure 2: Plan of the logistics center with highlighted units in the scope of this study. The granularity of the dataset from the logistics center energy consumption (mainly its individualization by each of the main eleven units) allowed us to envisage the benefits of combining multiple loads into a single load, and verify the potential of improving the cost-effectiveness and the solar fraction for the different simulated PV sizing. The average solar irradiation at the location of the logistics center is about 1.77 MWh/m\({}^{2}\)/year, which represents a potential of 188 kWh/m\({}^{2}\)/year of electrical energy using typical PV panels/inverters, with an average efficiency of 11% (considering typical efficiency rates of PV panels of around 13%, around 90% for inverters, and that the efficiency decreases over its lifetime). Figure 4a illustrates the summary of the hourly energy consumption (red), resulting in the annual consumption. The period of highest solar radiation, between 10 h and 16 h (yellow), represents 25% of the 650 MWh for the whole year. Preliminary calculations that do not consider the energy surplus (green) showed that PV panels distributed over an area of 911 m\({}^{2}\) could supply this amount of energy with a solar fraction around 27%, however, the detailed modeling and optimization revealed that these numbers could be further improved. A hypothetical situation is shown in Figure 4b that aims to clarify the need for detailed calculations where PV panels distributed over an area of 3340 m\({}^{2}\) would be able to supply the total annual energy consumption of the studied logistics center (650 MWh). This amount of energy would represent a solar fraction of around 40%, meaning that the 60% of energy surplus, produced between 9 h and 17 h (green), must have its allocation carefully planned. This work included the study of the electricity consumption for eleven units of the logistics center (see Figure 3). The electricity in these units is consumed mainly for two different purposes: lighting and the operation of specific equipment, namely the energy consumed by the refrigeration chambers, the wastewater treatment equipment, and the pressure unit equipment. The total demanded energy  
Figure 4: (a) PV supplying partial energy demand, no surplus; (b) PV supplying partial energy demand with a surplus. was considered initially to be obtained exclusively from the grid, and this situation constituted our base case. Every one of the eleven units had their own consumption pattern, and therefore, specifically contracted electricity and power.