Improvement of load frequency control in a single shaft combined cycle power plant that can operate in island mode connected to the grid with dragonfly algorithm

With the increasing demand for electrical energy, it has become imperative to generate and transmit electrical energy in a safe, high quality and sustainable manner. The reliability of electricity systems depends on maintaining the balance between generation and consumption. In order to provide this balance, keeping the frequency within certain limits is of critical importance and this process is called Load Frequency Control (LFC). Especially with the integration of power plants containing Gas Turbines (GT) into the grid, LFC has gained a more complex and dynamic structure. Power plants containing GT are widely preferred due to their ease of installation, fast start-up and shutdown features and their economical and efficient energy generation. In combined gas cycle power plants, which can also be operated in island mode, the speed and temperature values are controlled using a Proportional-Integral-Derivative (PID) controller to prevent deviations in the frequency value against load variations. In this study, a simplified mathematical model is used for the LFC of a Rowen GT model gas cycle plant containing a single-shaft Heavy Duty Gas Turbine (HDGT). Heuristic algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Simulated Annealing Algorithm (SA) were used in the analysis of these control methods. In addition, the same analyses were also performed using the Dragonfly Algorithm (DA), which is proposed for the first time in this study. In the study, performance indexes such as Integral of Squared Error (ISE), Integral of Absolute Error (IAE), Integral of Time-weighted Squared Error (ITSE) and Integral of Time-weighted Absolute Error (ITAE) were analyzed comparatively in order to evaluate the error magnitudes expressing the frequency changes. The obtained results were evaluated by considering dynamic parameters such as maximum overshoot, rise time, peak time and settling time, which reflect the transient regime behavior of the system. According to the analysis results, it was determined that the adjustment of the proposed PID controller with the DA algorithm provided better solutions in terms of overshoot and settling time of the system frequency compared to other common algorithms. Thus, by effectively damping frequency oscillations in a shorter time with the DA algorithm, it is suggested as a reliable alternative method for frequency control in gas cycle power plants with this study. Keywords: Heavy Duty Gas Turbine, Load Frequency Control, Performance Indexes, Heuristic Algorithms, Dragonfly Algorithm