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A Variable-Weather-Parameter Optimization Strategy Based on an Irradiance and Temperature Estimation Method for PV System

The variable-weather-parameter (VWP) methods have the fastest maximum power point tracking (MPPT) speed because their control signals are directly calculated by the measured weather data (including irradiance and temperature (I&T) data). However, they are suffering from the high hardware cost of the I&T sensors. To solve this problem, an estimation method to estimate the real-time I&T values is proposed. In this method, an equation set and two empirical equations are established to match the changeless and varying weather conditions, respectively. Based on them, a VWP optimization strategy (VWPOS) is proposed. It is without using I&T sensors (or external I&T data) that the advantage of the MPPT rapidity is inherited from the VWP methods. Finally, some simulation experiments involving the VWPOS are conducted, and the results show that the estimation method is accurate and workable regardless of the changeless or varying weather conditions. Meanwhile, simulation results also show that the tracking speed of an existing MPPT method can be greatly optimized by the VWPOS even if the I&T sensors or external I&T data are not used. In addition, simulation results still show that, when the conventional P&O method is optimized by the VWPOS, the average error of its control signal at the MPP can be decreased from 0.025% to 0.005%, and the settling time of its output power can be decreased to at least one-third of the original value. With this work, for the existing VWP methods, the trouble arising from the hardware cost of the I&T sensors can be prevented, which is beneficial to their widespread use.