Dynamic control of wind/photovoltaic hybrid power systems based on an advanced particle swarm optimization

As a clean and renewable energy source, wind/photovoltaic hybrid power generation, which will contribute to adjusting energy structures and protecting environments, has attracted lots of countries and organizations. But it is very hard to model with strong nonlinearity, multiple objectives, and multiple extreme values, and very difficult to be handled with traditional methods. This paper makes a mathematical model, which is used to control the operation of wind/photovoltaic hybrid power systems, designs a new particle swarm optimization based on uniform designs and inertia mutation, which is used to solve the made mathematical model to control the operation of hybrid power systems dynamically. The experimental results show that this particle swarm optimization can trace varieties of load, wind velocity and solar irradiation to optimize the power output of generation devices, which makes hybrid power systems run steadily, safely and also economically.