Optimized 2DOF PID for AGC of Multi-area Power System Using Dragonfly Algorithm

Effect of electric vehicles on load frequency control in interconnected thermal and hydrothermal power systems utilising CF‐FOIDF controller

“…To inspect the efficacy of CF-FOIDF controller to handle the diverse systems, the work is protracted to a multi-unit 2-AHTPS whose TF model is displayed in Fig. 2a [15,[20][21][22]28]. Each area is furnished with one thermal and one hydro plants.…”

“…Via suitable control arrangements, LFC reinstate the system stability and preserve the frequency/power at anticipated values. Various optimal, robust and intelligent control methodologies as stated few above are utilised as potential solutions to get a robust performance and stability of real PSs [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26]. These include hybrid human brain emotional learning PI [12], sine-cosine algorithm based on wavelet mutation (SCAWM) based model-free non-linear sliding mode controller (MFNSMC) [13], hybrid SCA-HS algorithm based FO-SMC [14], firefly algorithm-pattern search (hFA-PS) tuned PI/PID [15], hybrid invasive weed optimisation-PS (hIWO-PS) tuned PI/2-DOF-PID [16], multi-objective genetic algorithm (MOGA)/GA tuned PI/PID [17,18], modified evolutionary particle swarm optimisation-time varying acceleration coefficient (MEPSO-TVAC) tuned PID [19], dragonfly algorithm (DA) tuned PID/2DOF-PID [20], blended biogeography based optimisation (BBBO) tuned PID [21], grey wolf optimisation (GWO)/ensemble of mutation and crossover strategies and parameters in differential evolution (EPSDE) tuned PI/PID [22], hybrid gravitational search algorithm-PS (hGSA-PS) tuned PI/PID with filter (PIDF) [23], salp swarm algorithm (SSA) tuned PIDF/ tilt IDF (TIDF)/cascade control-TIDF (CC-TIDF) [24], differential evolution (DE) tuned PID/TIDF [25] and lozi map-based chaotic optimisation algorithm (LCOA) tuned PID [26] controllers applied on different PS configurations.…”

Dragonfly Algorithm and Its Hybrids: A Survey on Performance, Objectives and Applications

“…In [37], DA has been applied to the economic load dispatch problem in power systems, which consists of minimizing the generation cost while satisfying constraints such as ramp rate, demand and generator operating limit; in [38], it has been applied to the static economic dispatch problem incorporating solar energy; in [39], it has been applied to the combined economic emission dispatch problem, and in [40], it has been applied to the dynamic economic dispatch problem. In [41,42], DA has been applied to the automatic generation control problem to optimize the gains of the controller. Furthermore, DA has been used in power transmission systems [43] for optimizing the size and cost of static var compensator, in PV panel [44] to maximize the tracking of solar power, in photovoltaic system [45] to track the global maximum power point (GMPP) and in Photovoltaic-biomass system [46] to find the optimal size and cost of grid-integrated renewable energy resources.…”

A Survey on Dragonfly Algorithm and its Applications in Engineering

“…The outcomes showed that the DA had better performance for the mentioned problem, and it was competitive with other methods for decreasing MSL. In reference [44], automatic generation control of an interconnected two-area multi-source hydrothermal power system considered. The performance of the scrutinized system was evaluated and planned with proportional-integral (PI), proportional integral derivative (PID), and 2 degrees of freedom PID or so-called 2DOF PID.…”