Abstract
This manuscript deals with the implementation of adaptive neuro-fuzzy inference system (ANFIS) approach to automatic load frequency control (ALFC) of six unequal areas’ multi-generation hybrid interconnected power system. ANFIS controller has the advantages of fuzzy as well as neural network and stands for adaptive neuro-fuzzy inference system. Areas 1 and 2 comprise thermal and reheat thermal plants, area 3 consists of hydro plant with hydraulic governor system whereas areas 4, 5 and 6 comprise nuclear, diesel and gas turbine power plants, respectively. The hybrid model of interconnected power plant is developed with intelligent ANN (artificial neural network) and hybrid neuro-fuzzy controllers, i.e. proposed ANFIS and existing proportional and integral (PI) controller separately. The simulation work was carried out and the performance evaluation is checked by the proposed control approaches with similar step load change in each areas. Sliding surface is introduced with each controller to enhance the performance of controllers. Evaluation of ANN, ANFIS and PI-based approaches exhibits the advantage of the proposed ANFIS controller over conventional PI controller and ANN controller for tie-line power and frequency deviation in all six areas of interconnected hybrid power system.
Published Version
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