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

Abstract

This paper proposes a new combined controller, the proportional integral derivative-second derivative with a proportional derivative (PIDD2-PD), to improve the frequency response of a multi-area interconnected power system with multiple generating units linked to it. The optimum gains of the presented controller are well-tuned using a wild horse optimizer (WHO), a modern metaheuristic optimization approach. The main study is a two-area-linked power system with varied conventional and renewable generating units. The physical constraints of the speed turbines and governors are considered. The WHO optimization algorithm is proven to outperform various other optimization approaches, such as the whale optimization algorithms (WOA) and chimp optimization algorithms (ChOA). The efficacy of the proposed WHO-based PIDD2-PD controller is evaluated by comparing its performance to other controllers in the literature (cascaded proportional integral derivative-tilted integral derivative (PID-TID), integral derivative-tilted (ID-T) controller). Multiple and varied scenarios are applied in this work to test the proposed controller’s sturdiness to various load perturbations (step, random, and multi-step), renewable energy source penetration, and system parameter variations. The results are provided as time-domain simulations run using MATLAB/SIMULINK. The simulation results reveal that the suggested controller outperforms other structural controllers in the dynamic response of the system in terms of settling time, maximum overshoot, and undershoot values, with an improvement percentage of 70%, 73%, and 67%, respectively.

Improvement of Frequency Regulation of a Wind-Integrated Power System Based on a PD-PIDA Controlled STATCOM Tuned by the Artificial Rabbits Optimizer

“…Encouraged by their success, the authors continued along this path, proposing the PD-PIDA controller, which has better performance in the LFC problem [36] in order to improve STATCOM's ability to keep the frequency within acceptable ranges. The Artificial Rabbits Optimization (ARO) method, which is a novel bio-inspired meta-heuristic approach, is used to fine-tune the suggested PD-PIDA parameters.…”

“…The purpose of the control strategy is to boost the performance of frequency for the linked generators of the kundur system. The PD-PIDA regulator that has been developed has nine parameters that have to be their values optimized, and the transfer function of this regulator may be described as follows [36]:…”

Enhancement the Frequency Stability and Protection of Interconnected Microgrid Systems Using Advanced Hybrid Fractional Order Controller

“…several structures of power systems are considered with LFC, such as single area, multiple interconnected areas, nonlinear power system considerations, deregulated power grids, etc. [7]. In which, several control schemes from traditional to advanced ones have been proposed for LFC in the literature [8].…”

“…In which, several control schemes from traditional to advanced ones have been proposed for LFC in the literature [8]. The widely-presented LFC schemes are integer order (IO) controls [7], fractional order (FO) controls [2], model predictive controls (MPCs) [9], artificial intelligence (AI) controls [10], fuzzy logic (FL) controls [11], deep learning controls [3], etc. Several papers have been introduced for reviewing, comparing, and investigating the performance of various LFC schemes [12], [13].…”

“…However, tuning processes based on trial-and-error methods require long time for the parameters adjustments. Therefore, great efforts are made by researchers for properly adjusting the control parameters of IO based PI and PID control methods [7]. Among various widely-employed design methodologies for LFC applications, optimization algorithms based tuning schemes have shown improved performance and easier tuning processes [17].…”