## 5 Results and Discussion
As a result, it can be concluded that the energy management system properly controls the charging and discharging power rates and it enables B2G and G2B services in sizing the DG optimization process. Therefore, the proposed technique provides successful coordination between a RES with PV and ESS with stationary battery. To guarantee the global optimal solution and avoid any local solutions, the optimization process has been run three times, as shown in Figure 15. As it can be seen, after 800 function evaluations,  
Figure 14: Simulation and optimization results. Figure 13: Voltage profile of the load. the cost has reached the same value of 1094 \(\times\) 10\({}^{3}\) euros. Therefore, it can be concluded that the solution is globally optimum for the defined problem. To analyze the economic assessment of the proposed system, the total yearly costs are calculated over 20 years for both cases; without the PV-battery and with the PV-battery system that is optimized by the GA. Subsequently, profitability is obtained based on the calculated yearly costs for both scenarios. Note that different drivers influence the profitability with solar PV and battery storage systems, which are broadly grouped into 'finance-related' factors, such as market-based characteristics and DG costs, and 'quantity-related' factors, such as the amount of demand and supply and weather conditions [51]. As shown in Figure 16, the proposed system is profitable from the first year. Moreover, Table 4 presents the total yearly profits from PV production while considering a total DG cost of 0.3 Million Euros. The resulted payback time and the yearly profits from PV generation could provide society with an initial indication of economic viability of such systems and incite consumers to purchase PV and battery systems and make the most financially sound investment decision. Figure 16: Total yearly cost with/without PV-battery system. Figure 15: Evaluation of Total Cost of Ownership (TCO) over Number of Evaluation Function (NFE) in optimization process. The cost of batteries is one of the main factors that influence the profitability. Especially, the battery costs could affect the payback time and provide economic benefits. The high capital cost of battery is still the primary barrier to its widespread implementation under the current energy market [56]. In this regard, the further decreasing cost of battery will make battery investment more attractive and highly beneficial to consumers. The used battery prices for the residential and commercial levels range from 120 \(\epsilon\)/kWh (absolute minimum) to 450 \(\epsilon\)/kWh (absolute maximum) [47]. Moreover, the pack price of new Li-ion batteries ranges from 400 \(\epsilon\)/kWh to 600 \(\epsilon\)/kWh for the residential and commercial/industrial systems, while taking into consideration that the cost of the actual installed systems in 2015 was in the range of 800 \(\epsilon\)/kWh to 1000 \(\epsilon\)/kWh, including charges, such as inverter, software, and other installation costs [47]. For these reasons, the system profitability is analyzed and discussed in this section with different cost scenarios for BESSs, varying the investment cost C\({}_{\text{InVESS}}\) (see Table 5). Please note that 10 years is the assumed life-time of the battery. Table 5 provides the profits over 20 years. According to the projective studies, it has been predicted that the price of Li-ion batteries will be substantially reduced by the end of 2030 [58]. Therefore, providing a clear picture of how the battery prices can affect profitability with designers and battery cell manufactures could be helpful and useful. In this regard, [PERSON] et al. [45] performed a sensitivity analysis on a PV-battery system with PV installation costs of 2500, 2000 (base case), 1500 and 1000 \(\epsilon\)/kWh, and battery storage costs of 1000 (base case), 750, 500, and 250 \(\epsilon\)/kWh, and demonstrated that the battery will only improve the profitability of the system with a price of 250 \(\epsilon\)/kWh.