Optimizing the AGC system of a three-unequal-area hydrothermal system based on evolutionary algorithms

This paper focuses on expanding and evaluating an automatic generation control (AGC) system of a hydrothermal system by modelling the appropriate generation rate constraints to operate practically in an economic manner. The hydro area is considered with an electric governor and the thermal area is modelled with a reheat turbine. Furthermore, the integral controllers and electric governor parameters are optimized using integral squared error (ISE) criterion. Also, a novel Teaching-Learning-Based Optimization (TLBO) algorithm, Particle Swarm Optimization (PSO), and Gravitational Search Algorithm (GSA) with controller are proposed for optimizing AGC. Investigations have been conducted for the selection of a suitable value for governor speed regulation parameter R for the hydro and thermal areas, to explore the effect of tie-line power on the dynamic response. The advantages of the proposed approach are demonstrated by comparing the results of optimizing the AGC system of a three-unequal-area hydrothermal system with mentioned algorithms for the first one in comparison with other recently published techniques. The results confirm the flexibility and the suitability of the proposed AGC model for optimizing the different approaches. Moreover, it is more practical to use the proposed method to make a wide variety of changes in the system parameters using sensitivity analysis.

Keywords:

Automatic Generation Control (AGC) , Multi-Area Hydrothermal System , Teaching-Learning-Based Optimization (TLBO) , Particle Swarm Optimization (PSO) , Gravitational Search Algorithm (GSA)