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In this paper the power supplied to the grid is regulated with the help of Discrete Sliding Mode Controlled (DSMC) CUK converter and Sinusoidal Pulse Width Modulation (SPWM) topology controlled 3-phase Inverter. The CUK converter is used in the input side to Buck or Boost the PV (Photo Voltaic) array voltage to the required value of the 3 -phase Inverter. Natural isolation of source and load is obtained in the CUK converter with the help of capacitor energy transfer so that the ripple content is less in both load and source side. These CUK converters are operating in continuous current mode so that regulation of power from the solar panel is easy and efficient compared to Buck-Boost converters. In this paper DSMC CUK converter topology is implemented so that converter is feasible to incorporate with any digital controller with less hardware requirements, it has flexibility in control characteristics and guaranteed stability of highly fluctuating solar power under different climate conditions. The simulation model has battery back-up which is charged during high irradiation time and provides power to load during less irradiation climate conditions. The 3-phase Inverter is controlled by SPWM technique to reduce the switching losses of the Inverter so that the harmonics in the load side is less and it is easy to implement. So that the overall system is efficient, ease of implementation, robust and economical.

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In the modeling and designing of PhotoVoltaic (PV) systems, parameter characterization in PV cell/module models remains a crucial field of research. Diode‐based models, such as single‐diode model (SDM), double‐diode model (DDM), and the three‐diode model, are frequently employed, and SDM and DDM are the most significant models. As a result, the difference between the estimated and experimental current can be minimized by using an objective function to solve the parameter characterization of such models. Metaheuristic optimization algorithms have recently been employed to get around the difficulty of finding accurate and highly reliable outcomes quickly. As a result, this research modifies the fundamental SDM and DDM and considers an objective function based on the modified models. Additionally, an improved version of a novel metaheuristic algorithm called White Shark Optimizer (WSO) is proposed by modifying the force control parameters of the WSO, and a chaotic generator is infused to improve the exploitation ability of WSO. The modified algorithm is named IWSO and applied to extract the PV parameters. This paper uses the new objective function to compare the conventional and the modified PV models. The outcomes of the experiment demonstrated IWSO's dominance over competing algorithms. With an average Freidman's ranking test value of 1.171, the proposed IWSO is superior to all selected algorithms. The average accuracy of modified SDM and DDM is 12% better than the traditional PV models. According to the findings, IWSO's estimated parameter values are the best, with the smallest difference between estimated and experimental current.