Dual search maximum power point algorithm based on mathematical analysis under partially-shaded conditions

Solar energy has drawn much attention in recent years because of high demand for green energy resources. Electrical power can be generated by using semiconductors in photovoltaic (PV) cells to convert solar irradiance into DC current. Each PV module has its own optimum point at which the power delivered from the PV is at its maximum value. Since the initial cost for using PV is high, it is essential to make the PV module to operate at its maximum power point (MPP). However, the non-linear relation between current and voltage for the PV system is a challengeable issue that results in a unique MPP for its power-voltage (P-V) curve. Under uniform conditions or without shading, there is a unique MPP on the P-V curve. By changing the irradiance and temperature, the value of MPP will be changed. The PV system is troubled with the weakness of nonlinearity between current and voltage under partially shaded conditions PSCs). Under PSCs, there are multi-peak powers. Only one of these peak powers has the highest power, which is called global maximum power point (GMPP), and other peak powers are the local maximum power point (LMPP).The maximum power point tracking (MPPT) algorithms under PSCs can be categorized generally in two groups. In the first group, the conventional techniques are combined with other techniques and the second group is based on the optimization methods. One of the main challenges of MPPT techniques under PSCs is ability of the algorithms to find the GMPP faster with minimal oscillation in power. Moreover, it is very important that the algorithms should be general and not so complicated which could be implemented for all systems.Therefore, this research presents design and development of a novel method, which is called dual search maximum power point (DSMPP) algorithm, for tracking the GMPP under PSCs. The proposed method is based on mathematical analysis that reduces the search zone and simultaneously identifies the possible MPPs in the specified zone that leads to determining the GMPP in minimum time. In this work, the perturb and observation (P&O) method based on duty cycle adjustment is introduced, which is modified to increase speed of the search and also to reduce the oscillation.The simulation and experimental works have been performed to investigate behavior and performance of the proposed algorithm. The PV array in series-parallel (SP)configuration is considered as an input of the standalone system and mathematical model of this PV array under PSC has been developed. Moreover, the load sizing method for PSCs is also presented to avoid controller failure when detecting the GMPP. In evaluation part, the DSMPP algorithm has been compared with two other methods.According to both simulation and experimental results, by implementing the DSMPP technique, the GMPP can be obtained faster. Moreover, the oscillation in power is reduced significantly. Interestingly, the experimental results under different irradiances also show that the proposed algorithm can detect the GMPP faster in comparison with other methods. The significant reduction of oscillation in power is observed to be due to implementation of the modified P&O.As a conclusion, the DSMPP algorithm has successfully been performed to detect the GMPP under PSCs in minimum time, with low oscillation in power, and high accuracy as detecting the GMPP for different scenarios of shadowing.

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