Differential evolution algorithm based tilt integral derivative control for LFC problem of an interconnected hydro-thermal power system

Abstract

Conventional control techniques such as proportional integral (PI) control and proportional integral derivative (PID) control are widely used as the load frequency controller in power system control applications; however, the increase in complexity of the power system is degrading the performance of classical control. Therefore, in this paper a new control approach using fractional calculus has been proposed for the load frequency control problem of two-area hydro-thermal power system. The paper presents an interconnected hydro-thermal power system working under different operating conditions introduced in the form of various nonlinearities. Four case studies have been presented in this paper considering transient analysis with (i) different loading conditions, (ii) parameter variations, (iii) different nonlinearities (governor dead band nonlinearity, time delay and generation rate constraints), and (iv) superconducting magnetic energy storage (SMES) device. A tilt integral derivative (TID) control has been presented as a secondary controller to stabilize the frequency deviations occurring in the two-area power system with the above-mentioned different operating conditions. The parameters of TID controller have been optimized using a differential evolution algorithm which solves an optimization problem formulated using the integral of time-weighted absolute error (ITAE) performance index. In addition, a comparison of dynamic system response obtained using TID control and PID control has been presented, which focusses on the better performance of TID control over PID control in an interconnected power system.

Robust Control of Frequency Variations for a Multi-Area Power System in Smart Grid Using a Newly Wild Horse Optimized Combination of PIDD2 and PD Controllers

“…The benefits of a TID controller are that it is easier to tune, has a higher disturbance rejection ratio, and has fewer plant effects. Consequently, the TID controller was introduced as an alternative to the LFC issues in various research works [18][19][20]. In addition, refs.…”

“…As a consequence, choosing an appropriate optimization technique in the design procedure of the controller is a basic and crucial challenge. Classical optimization procedures were previously utilized to find the best frequency controller settings [18,33]. Additionally, ref.…”

A Complete Affordable Control System for Remote Astronomical Observing Accompanied by an Intelligent Controller

“…FO controllers are distinguished with more expanded freedom in tuning for system stabilizing, so researchers have a great interest in such controllers [27]. Moreover, the TID family is potentially one of the best FO controllers [28]. They have robustness in estimating the parameters of a system with a closed-loop enhancing the system response [29].…”

Whale Optimization Algorithm Based Tilt Integral Derivative Control for Frequency Regulation in AC Microgrid with and without SMES

“…The use of various evolutionary algorithms [18][19][20][21] for optimal tuning of controller gain parameters has been reported in respect of microgrid systems. For instance, Differential Evolution (DE) [18], Particle Swarm Optimization (PSO) [19], Hybrid Dragonfly (HDF), and Pattern Search (PS) [20] algorithms have been reported to have been used to optimize the gains of TID controller whereas Grey Wolf Optimizer (GWO) [21] to optimize the gains of fractional-order controller.…”

“…The use of various evolutionary algorithms [18][19][20][21] for optimal tuning of controller gain parameters has been reported in respect of microgrid systems. For instance, Differential Evolution (DE) [18], Particle Swarm Optimization (PSO) [19], Hybrid Dragonfly (HDF), and Pattern Search (PS) [20] algorithms have been reported to have been used to optimize the gains of TID controller whereas Grey Wolf Optimizer (GWO) [21] to optimize the gains of fractional-order controller. Likewise, WOA, recently proposed by Mirjalili et.al [22], has found number of applications in many different areas such as Ladumor et al [23] demonstrated the use of WOA in determining the solution of single area unit commitment problem, authors in [24] proposed optimal sizing and sitting of capacitors in the radial distribution network by the use WOA resulting in improvement of system stability, performance, and network reliability.…”