Abstract
With the development of society, the demand for energy keeps increasing. Solar energy has received widespread concern for its renewable and environmentally friendly advantages. As one of the most efficient solar energy devices, the output power of photovoltaic (PV) cells is easily affected by the external environment. In order to solve the problem of the maximum power output of PV cells, this paper proposed a maximum power point tracking (MPPT) method. Based on the online particle swarm optimization (PSO) variable step length algorithm, the pulse width modulation (PWM) control module parameters are set according to the parameters of the PV cells’ output voltage. By dynamically adjusting the output voltage step of the PV cells online, the output of the PV cells is stabilized near the maximum power point (MPP). The simulation results concluded that the method and model could accurately adjust the output voltage according to the external environment changes in real time and reduce the voltage fluctuation at the MPP, providing a new idea to solve the problem of MPPT of PV cells.
Highlights
The energy demand increases with society’s development, yet the increasing depletion of fossil fuels cannot meet long-term growth
In order to better solve the problem of maximum power point tracking (MPPT) of PV cells, this paper proposed a pulse width modulation (PWM) variable carrier PV cells power optimization control method based on the online particle swarm optimization (PSO) variable step length
I 1, 2, . . . , n and n is the size of the population. d is the dimension of the search space. k represents the iteration number. c1 is the individual optimal coefficient, c2 is the individual global coefficient. ω represents the weight of inertia. r1 and r2 are random numbers which are uniformly distributed in (0,1). p1 represents the local optimum and pg represents the best individual among all the particles at every generation
Summary
The energy demand increases with society’s development, yet the increasing depletion of fossil fuels cannot meet long-term growth. The main methods of PV cells maximum power point tracking (MPPT) technology can divide into three categories: 1) mathematical models; 2) self-optimizing control algorithms; 3) intelligent algorithms (Ishaque and Salam, 2013). In (Danandeh and Mousavi, 2018), compared with the traditional P and O method, the fuzzy logic control algorithm improves the tracking efficiency, and it has advantages in robustness and environmental adaptability. In order to better solve the problem of MPPT of PV cells, this paper proposed a PWM variable carrier PV cells power optimization control method based on the online PSO variable step length. Compared to the fixed step method, the step-length of the voltage value optimized with the above control strategy is not static but based on actual conditions.
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