## 4 PV Systems--Implementation and Remote-Control Methods
### Use-Cases
The proposed method was experimented with in the laboratory under controlled conditions and using PV power fluctuations and failures of photovoltaic strings. In the event of fluctuations exceeding 20% per minute, the batteries enable the supercapacitor (SC) to handle the highest peaks during failure; at this point, the monitoring had a root mean squared error (RMSE) of 0.66-2.47. The smoothing method resulted in a reduction in computational effort: the initial execution time was four times shorter compared to the previous method. Based on the results obtained in this research, a power smoothing method could be used in energy control in photovoltaic systems. This method could add additional protection to physical photovoltaic systems, mitigating the issues related to the intermittency of power generation. The paper [31] presented the importance of power smoothing and battery behavior and lifecycle in the long term. Case 8: [PERSON] [32] proposed the implementation of a microgrid using the photovoltaic systems from four different buildings. There was a 25 kW rooftop solar PV system installed for each building, with Battery Energy Storage System (BESS) parameters of 180 V and 120 Ah for 2 h. The estimated rated load for each building was 20 kW. The interconnection of the clusters was facilitated by two-stage converters, comprising DC-DC boost converters and bidirectional single-phase voltage source converters (VSCs), which facilitate the distribution of power among the various buildings. Each cluster was equipped with its own BESS, and the four photovoltaic systems exhibited disparate behavior between 12:00 p.m. and 4:00 p.m. The control technique permitted the maintenance of equilibrium in each building integrated in the microgrid through the charging and discharging of the BESSs. Two control signals were employed for the purpose of controlling the system: feedback and feed-forward. The efficacy of the control techniques was validated and tested in a real-time environment using a Real-Time Digital Simulator. In the solution proposed, the electrical energy could be transferred from one building to another one easily, and in this way, the buildings with little sunlight could benefit from solar energy as much as possible. This research could be implemented easily for daily home-used photovoltaic systems. The research presented an automated control method. Case 9: [PERSON] et al. [33] used a photovoltaic system with solar panels, sensors, a battery charge module, and a simple monitoring system. The proposed monitoring method could be used for every type of solar system with low costs because it is based on an Arduino microcontroller and few sensors. The monitoring system was able to collect data in real-time from different locations and store them in the cloud. The data transfer is done using the HTTP protocol, which is not a secure port. For improving the safety of the data and avoiding data breaches, it is recommended to encrypt the data before sending it or storing it on the network or on the cloud [34]. Case 10: [PERSON] et al. [35] present a complete and versatile monitoring and control system which can be used in different conditions of PV systems, such as sizing and weather. ZigBee technology was configured, and for remote communications a 3G network was implemented. The proposed implementation used two inverters and both were remotely connected. The system measured the weather and electrical parameters and sent them to the control unit, which stored them and calculated the control signals. After that, it sent them back to the inverters DC/DC and DC/AC using 3G. The data were visualized and stored in the software named Gambas. It was not mentioned if the data were encrypted or stored in a safe manner, or who had access to the stored data. Additionally, the proposed software solution offered functions such as user authentication and control of the system.