Adaptive Control of Solid State Transformer Using Type-2 Fuzzy Neural System

Moreover, the rapid reduction of fossil fuel resources requires the search for alternative sources of energy to find a solution for future energy production. With the developing technology, the rising living standards and the increasing population, the requirement of electric energy is increasing day by day [1,3]. It is well-known that electricity is provided to consumers by passive transformers, transmission lines, and substations. Classic transformers are one of the most indispensable devices in modern electrical distribution systems. These transformers possess various superior features such as low cost, simple construction, high reliability and efficiency. But these transformers have many disadvantages such as large size and weight, power quality problems, sensitivity to harmonics, lack of self-protection, environmental problems related to oil leaks, and voltage and current uncontrollability. New technological solutions are required to eliminate these problems. In addition, efforts to develop transformers with technological advances have been increasing rapidly in recent years [1, 4, 6, 10]. New type transformers, which are considered as one of these technological developments, are called as solid state transformer (SST), intelligent universal transformer (IUT) or electronic power transformer (EPT) [11]. When compared to conventional transformers, SSTs possess many important characteristic features such as reduced size and weight, instantaneous voltage regulation, voltage sag and swell compensation, power factor correction, fault isolation, harmonic isolation and environmental benefit [9, 10].