An enhanced flower pollinated algorithm with a modified fluctuation rate for global optimisation and load frequency control system

Abstract

This paper proposes a new hybridised approach comprising the flower pollination algorithm and pathfinder algorithm (FPAPFA), in order to address optimisation problems and for load frequency control system. Although the FPA is a popular algorithm that has been widely used in diverse applications, its implementation is met with the tendency to be trapped in local optimal due to an imbalance between the exploration and exploitation process. Consequently, the FPA's exploration functionality can be enhanced by using the PFA features to shift certain pollens to moderately enhanced locations rather than leading them to random positions. Furthermore, a modified fluctuation rate is incorporated into the PFA to reinforce the exploitative competence of the FPAPFA. Compared to other popular techniques, the proposed algorithm's performance was evaluated against 23 standard mathematical optimisation functions and statistically tested using the Wilcoxon rank-sum and Friedman rank tests. Moreover, the FPAPFA is applied to regulate two unequal multiarea interconnected power systems with different generating units (thermal, hydro, diesel, and wind power plants) while also integrating redox flow batteries (RFBs) and interline power flow controller (IPFC). Simulation results show that the proposed FPAPFA delivered better results than other algorithms with improved convergence speed, stability, and robustness.

Maiden Application of a Modified HBA-Optimized Cascaded (2DOF + FOPIDN)-PD Controller for Load Frequency Control of Diverse Source Power System

“…Te total number of runs, population size (NP), and the total number of iterations are 10, 30, and 50, respectively. Te performance of the proposed control scheme is compared with other methods such as PSO : PID [6], GA : PID, HBA : PID, TLBO : PID [6], and MFO : PID. Dynamic response performance is analysed using the ITSE index, settling time, and undershoot.…”

“…Previous works indicate that a variety of nature-inspired optimization techniques were applied in LFC studies in order to gain maximum beneft from the controllers. For instance, works in references [6,35] have recently applied nature-inspired algorithms for a multisource IPS using a setpoint weighted fractional-order PID controller. However, one of the major distinctions between the reference [35] and the present work is that whereas the former work considered unequal areas with multisource power systems with the incorporation of GRC and GDB, this present work considered a more complex power system which incorporates both nonlinearities and the IPFC-RFBs coordination to enhance the system dynamic performance.…”

“…However, one of the major distinctions between the reference [35] and the present work is that whereas the former work considered unequal areas with multisource power systems with the incorporation of GRC and GDB, this present work considered a more complex power system which incorporates both nonlinearities and the IPFC-RFBs coordination to enhance the system dynamic performance. In addition, whereas reference [6] applied a hybridized algorithm with a set-point weighted fractional-order PID controller, this study explored the use of a single and more recent algorithm that utilizes a coordinated Lévy fight and a modifed inertia weight strategy.…”

“…As the adoption of dynamic and intermittent nature, renewable energy sources (RES) has increased, designing a PS with sufcient frequency management has become a more signifcant challenge. Terefore, for the stable operation of power exchange in a complex power system with scores of utilities cross-connected through tie-lines and RES penetration, it is imperative to apply smart and intelligent approaches [5,6]. Faced with these enormous challenges, the LFC system is considered the most notable alternative to delivering highquality electricity to end users because of the complexities of the electrical network [7].…”

Optimum Reactive Power Dispatch Solution using Hybrid Particle Swarm Optimization and Pathfinder Algorithm

“…The best individual is trying to improve intensification, but too much intensification stocks into local search and converges to local optimal minimal. However, balancing diversification and intensification is essential in presenting effective algorithms [35][36][37][38].…”