# Charge Management of Electric Vehicles from Undesired Dynamics in Solar Photovoltaic Generation
## 1 Introduction  
The use of solar photovoltaic technology (PV) has been widely promoted for power generation due to its free greenhouse gas (GHG) emission during operation, and its high cost competitiveness versus fossil fuel power plants [1]. However, its use is limited by the discontinuity of production due to non-deterministic seasonal variations and complex predictability since it depends mainly on weather conditions. Therefore, a high level of penetration of this technology in distribution networks can negatively affect the quality and reliability of electric power service. The high intermittency of the solar resource presents variations in time periods of hours, minutes, and even seconds. This dynamic behavior causes fluctuations in the power output of PV systems, which can be analyzed from several perspectives. A regulatory framework that defines the requirements for connecting PV plants to the grid, and the incorporation of energy storage systems at the point of common connection (PCC), can help to reduce VA- ratios at this node [2]. From a regulatory point of view, several countries have established policies that limit the technical aspects of PV systems. These regulations define a range for the active power variation, also called the ramp rate [3]. This ramp rate is the percentage of the nominal capacity of the PV plant in time intervals of minutes or seconds. For instance, the German Association of Energy and Water Industries (BDEW) sets a ramp rate of 1% of the nominal power per minute. The Romanian Energy Regulatory Agency (ANRE), the Federal Regulatory Commission of United States Energy (FERC), and the Puerto RicoElectric Power Authority (PREPA) consider a ramp equal to 10%/min of the nominal power of the PV plant [4]. On the other hand, energy storage systems (ESS) can also contribute to managing and controlling the dynamic behavior of PV generation. With the increasing implementation of PV systems in distribution networks, there is a need for large-capacity ESS temporarily connected to the PCC as well. For instance, a study has developed an analysis of the impact of introducing both PV systems and electric vehicles in the Portuguese grid [5]. The results indicate a remarkable decrease of the generated surplus energy due to the excellent match between the charging process and the PV production. Therefore, to ensure grid stability and large-scale dissemination of PV systems, a good management of the charging system of the battery bank of electric vehicles is necessary. For this purpose, different techniques have been developed to control the electric vehicle charging to smooth PV variations. The most commonly used techniques to smooth the PV power output are the ramp-rate, moving average, and low pass filter techniques [6]. There are also studies that allow for PV power output smoothing using moving window averaging techniques, which can be used in renewable generation to provide ancillary services for more than 15 min [7]. In addition, there are studies based on the use of metaheuristics that allow for smoothing PV power variations by determining the optimal filtering times using battery storage systems (BES) [8]; however, this type of technique may require high computational resources in implementation cases [9]. Regarding the ramp-rate control, studies have been carried out using simple, symmetrical, exponential, and hierarchical moving average. Algorithms based on Kalman filters and lease square estimators, among others, are also used [10]. Among these methods, the exponential moving average has been shown to require more battery capacitance, which is required for PV power to be delivered to the grid with minimal losses [11]. The current study evaluates the dynamic behavior of PV solar energy generation under conditions of high variability of solar irradiation caused by the characteristic cloudiness of the mountainous region of the Andes.