Wind power performance improvements using artificial neural network controller for DC–DC converter

Abstract

Pakistan is nowadays facing serious energy crises, especially in power sector due to increase in load demand. To bridge the gap between load demand and generation of electricity, the wind power is a cheapest indigenous solution. Wind power these days is gaining popularity as a growing renewable energy source in the world because of its environmentally clean and safe usage. For generation of wind power, the trend is to install large wind farms either onshore or offshore. These wind farms consist of a large number of wind turbines. Onshore wind farms cover large areas of land but an interesting option is to build offshore wind farms because of higher average wind speeds at sea. In wind power generation, power electronics converters are widely used because of their manifold advantage. DC–DC topologies are most commonly used in wind farms because of their high efficiency and compact size. A single-active bridge (SAB) converter being simple in topology has recently drawn attraction of many researchers. Such converter despite its simple design and number of attractive features produces oscillations. Therefore, it is imperative to design an appropriate controller to minimize the oscillations. The artificial neural network is proposed for the SAB converter and it is believed to handle oscillations.