Adaptive fuzzy PID controller for wind generation unit with energy storage feature

Abstract

In general energy is a hot topic in the news nowadays: increased consumption, increased cost, depleted natural resources, our dependence on foreign sources, and the impact on the environment and the danger of global warming. Therefore, wind energy has great potential to lessen our dependence on traditional resources like oil, gas and coal and to do it without as much damage to the environment. Moreover, wind energy is playing a critical role in the establishment of an environmentally sustainable low carbon economy. The purpose of this thesis is to give wind turbine engineers information about a controller design and simulations of autonomous wind turbine system with variable-speed for permanent magnet synchronous generator (PMSG) and a system for storing energy based on appropriate controller. The proposed stand-alone hybrid wind/energy storage system is mainly consisting of a (PMSG) driven by wind turbine and feeds isolated load through DC-link. The DC-link is considered as uncontrolled rectifier, DC/DC converter and DC/AC converter. A lead-acid battery (LAB) is connected in parallel to the DC-link through charge/discharge controller. Adaptive fuzzy PID (AFPID) controller is used to control the duty ratio of the DC/DC converter and maintaining the DC-link voltage constant at its desired value. Also, another AFPID controller is used to control the battery charge/discharge regulator when the wind power and/or load varies. The power desired by the connected loads can be successfully supplied and delivered by the assumed wind generation unit and energy storage system using the adaptive fuzzy proportional-integral-derivative controller. The suggested hybrid wind-storage energy system with the proposed AFPID controller is examined through a step changes in both load and wind speed. Moreover, the system is examined in case of without control and in case of applying conventional PID controller. Simulation results are presented that there a better prediction of the electrical parameter waveforms especially in case of applying the proposed adaptive fuzzy PID controller.