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Dual-power PV-grid system was introduced to manipulate the lower tariff rate at off-peak period and to reduce the capital installation cost of PV energy system. In this paper, the system and simulation design of the system is discussed to evaluate the design parameters which affect the design performance of the power converter. It consists of a boost regulator to boost and regulate PV outputs to fixed voltage of 240V, 50Hz, a MPPT to derive maximum power from PV panels and a three operation modes of the battery converter to regulate charging current/discharging current under various PV output and load variation. The system utilizes 15 levels of cascaded multilevel inverter to invert DC voltage from solar panel to AC voltage. The simulation results certify the simulation model can emulate the real system.

This paper presents a modelling of Multiple Input-Single Output (MISO) model for tracking maximum point of Photovoltaic (PV) Systems. A system identification approach is used to obtain the model characteristics of existing structural systems through dynamic observations which incorporate with traditional direct control Maximum Power Point Tracking (MPPT) algorithm. The generate model characteristics was used in designing the MPPT of the Photovoltaic Systems. The need of an efficient mathematical model to characterize the dynamics system for PV is essential for implementing the system for control applications. In this paper, the transfer function relating the input parameters (Solar irradiance and cell temperature) and output parameter (DC current) of the PV module MF120EC3 was identify with the aid of MISO for Auto-Regressive with eXogenous input (ARX) model. The approach has concern on the estimation of the (Direct Current (DC) for photovoltaic system based on the real systems data from Pusat Tenaga Malaysia (Malaysia Energy Centre, MEC). A Fourth-order autoregressive (ARX) model using the ARX algorithm, (ARXQS) was chosen since the model output provide 93.42% best fit model criteria. The modelling is implemented using system identification toolbox of Matlab software.