基于群灰狼优化的光伏逆变器最优无源分数阶PID控制

针对并网光伏逆变器(PV)设计最优无源分数阶PID(PFoPID)控制,其可在不同天气条件下,通过扰动观测(P&O)技术实现最大功率追踪(MPPT).首先,基于跟踪误差构建储能函数,保留系统阻尼有益项以提高跟踪速率,并完全补偿其他的系统非线性以实现全局一致的控制性能.然后,引入分数阶PID(FoPID)控制作为附加控制输入,对储能函数进行能量重塑,并通过群灰狼优化算法(GGWO)获取最优控制参数.对3种算例进行研究,即光照强度变化、温度变化和电网电压跌落,仿真结果表明,与常规PID控制、FoPID控制和无源控制(PBC)相比, PFoPID控制在各类工况下能够实现最大功率追踪并具有较好的动态特性.最后,基于dSpace的硬件在环(HIL) 实验验证了所提出方法的硬件可行性.

Grouped grey wolf optimizer based optimal passive fractional-order PID control of photovoltaic inverters

This paper aims to design an optimal passive fractional-order proportional-integral-derivative(PFoPID) controller for grid connected photovoltaic inverters(PV), which can achieve maximum power point tracking(MPPT) under different atmospheric conditions via the perturb and observe(P&O) technique. Firstly, a storage function is constructed based on the tracking errors, in which the beneficial terms are retained to increase the tracking rate. Meanwhile, other system nonlinearities are fully compensated to realize globally consistent control performance. Then, the fractional-order PID(FoPID) control framework is introduced as the additional input to reshape the storage function, and optimal control parameters are tuned by using the grouped grey wolf optimizer(GGWO). Three case studies are carried out, e.g., solar irradiation variation, temperature variation, and power grid voltage drop. Simulation results verify that the PFoPID control outperforms the conventional PID control, FoPID control, and passive-based control(PBC) under different operation conditions. Finally, a hardware-in-loop(HIL) test based on dSpace is undertaken to validate the implementation feasibility of the proposed approach.