# Charge Management of Electric Vehicles from Undesired Dynamics in Solar Photovoltaic Generation
## 5 Application Scenario in a Low-Voltage Network Feeder  
To test the performance of the algorithm and its contribution to an electrical distribution network, a simulation was carried out in OpenDSS and Matlab of the IEEE European Low-Voltage Test Feeder case, analyzing two cases: (1) distributed photovoltaic generation and electric vehicles and (2) single PV and EV (see Figure 10). EVs are modeled as 7.2 kW \(\times\) 14 loads and PV systems have powers of 5 kW \(\times\) 14 for case 1 and 70 kW \(\times\) 1 for case 2. The values were selected for illustrative purposes and the simulation can be downloaded at [[https://github.com/davilamds/EVRampControl](https://github.com/davilamds/EVRampControl)]([https://github.com/davilamds/EVRampControl](https://github.com/davilamds/EVRampControl)) (accessed on 31 May 2022).  
By simulating the two cases indicated cases, the results of the power of the substation and the busbar voltages in the bars of the for customer 349 were obtained. Tests included the test of the base case (Base); test of the base case where EVs are connected without PV generation and without control (Only EVs); tests from case 1 of EVs connected to the system with photovoltaic generation and without the charge control algorithm (EV without control  
Figure 9: (a) Photovoltaic and injected power (most critical day); (b) photovoltaic, injected, and EV charging power (average day), applying the control strategy.  
and PV case 1); and tests with connected Evs, PV generation, and control algorithm for both case 1 as for case 2.  
The following scenarios were analyzed:  
* Base case;
* Base case only with connected Evs, no PV generation and no control;
* Case 1 (distributed EV and PV) without charge control;
* Case 1 (distributed EV and PV) with charge control;
* Case 2 (distributed EV and PV) with charge control.  
The power of the substation was analyzed in the mentioned cases, where the effect of PV generation and Evs on the network was observed (see Figure 10(a)). It is observed that the base power has its maximum in the case where only Evs are connected without the contribution of PV generation around 10:00, and that it reaches negative values that correspond to the fact that PV generation covers the system demand. For case 1, it is observed that the power generated by several PV systems allows for the power to be delivered by the substation to be the lowest of all scenarios, and in case 2, it is observed that the power delivered by the PV system is not enough to supply the demand, requiring the contribution of the main system.  
Figure 11: Cont.  
Figure 10: Test cases: (**a**) distributed EV and PV (**b**) distributed EV single PV.  
Additionally, when reviewing the behavior of the voltage at the customer bus (see Figure 11b), a similar behavior is observed, where the voltage at the terminals improves both in case 1 and case 2 with respect to the base case; however, for the case 2, the maximum voltages are lower.  
Table 1 shows a summary of the results of the simulations. It is observed that the maximum power at the substation considering EVs and PV generation occurs in case 2 when the PV generation is located at a single point of the system, and the minimum power in case 1 where the generation is better distributed. Regarding the voltage at the customer terminals, case 2 has a better performance, having maximum and minimum voltages with less variation.