Among the list of reliability issues in Photovoltaic (PV) systems, partial shading is one of the crucial issues that affect the row current creating a wide range of current differences between rows these results in reduced output power and panel life span by creating hotspots. It also creates difficulty in tracking the power, because of multiple hotspot peaks obtainable in PV and IV (Current-Voltage) curves. Physical relocation of panels during shade occurrence is not an encouraging solution because of rooftop solar and domestic PV systems, where the area for PV installation is a ceiling. The optimization-based controller is retrofitted for the electrical relocation of panels. It is developed based on the Cuckoo Search Algorithm (CSA), which aims to reduce the row current difference with a minimum reposition of panels as constraints. For the 9*9 PV arrangement, the row current ranges from 3.747 A to 8.424 A. It is reduced and almost made zero. Hence, the Fill factor raises from 38.073 to 51.707%. The power output is enhanced by about 20%. To prove the algorithm’s novelty a shading case for 4*3 asymmetric array arrangement is also considered for simulation studies. The proposed system proves to be economically beneficent for PV users. The performance of CSA is compared with PSO, Skyscraper, and SuDoKu. An economic analysis is carried out that adds the PV efficiency value to the proposed CSA algorithm. The real-time experimental validation holds good for 3*3 solar array agreement with theoretically simulated results.

Nowadays, <span>many firms have started producing electric vehicles (EVs). One of the biggest challenges to broad acceptance of electric vehicles is their limited range EVs. Forecasting future energy usage is one of the way to calculate the driving range. In this paper, a simulation model of the drivetrain has been developed to evaluate the energy flow of a vehicle for the given torque and speed conditions. The energy consumption of an electric vehicle is determined by the vehicle's attributes. Road torque, road speed, motor model, motor controller model, battery model, and PI controller are the primary components of the model. The overall resistive force offered by the vehicle, as well as energy consumption owing to resistive force during motoring and regeneration has been validated through the simulation results. Here, the vehicle model, Mercedes Benz Class C Saloon has been considered</span>.