基于HPSO算法光伏并网逆变器MPPT技术研究

Study on maximum power tracking for photovoltaic array grid-connected system based on hybrid particle swarm optimization algorithm

为了解决光伏阵列最大功率点跟踪问题,提出一种基于神经网络与粒子群优化算法的最大功率点跟踪算法。在不同太阳辐射强度情况下,利用神经网络辨识光伏阵列的瞬时功率,并将此瞬时功率作为粒子群优化算法的粒子,利用粒子群优化算法求出最大功率点所对应的逆变器开关量。实验结果表明,将神经网络与粒子群优化算法相结合,可以准确实现光伏阵列最大功率点的跟踪。

In order to solve the problem of maximum power point tracking of PV array, a maximum power point tracking algorithm based on the combination of neural network and particle swarm optimization algorithm is proposed. Under the condition of different illumination and temperature,the use of neural network identification of photovoltaic array instantaneous power, and power as particles of particle swarm optimization algorithm, using particle swarm optimization algorithm to find the maximum power point. The experimental results show that the combination of neural network and particle swarm optimization algorithm can realize the maximum power point tracking of PV array accurately, with high tracking precision.