Maiden application of SSA‐optimised CC‐TID controller for load frequency control of power systems

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

“…where [24]. The slave controller acts promptly than a master controller to eliminate the disturbance erupting in the process swiftly to avoid its spread in other sections of the process.…”

“…Other advantages of CC structure over non-cascade structure include isolation of load disturbances, enhanced output, precise manipulation of mass or energy and compensation for nonlinearities. Additional details and benefits of CC are discussed in [24]. The assembly of the controller is displayed in Fig.…”

“…10. 1 Nominal system parameters (a) 2-ANTPS [16,[22][23][24][25]27]: P r = 2000 MW, P n = 50%, R i = 2.4 Hz/puMW, F 0 = 60 Hz, β i = 0.425 puMW/Hz, T Gi = 0.08 s, K PSi = 120 Hz/puMW, T PSi = 20 s, T Ti = 0.3 s, 2πT 12 = 0.545 puMW/Hz, ΔP D1 = 0.01 puMW, α 12 = −1, ΔF UL = 10 mHz, ΔF LL − 10 mHz, R AG = 2.4 Hz/puMW, [17-1λ, 26, 34]…”

“…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.…”

Credibility‐based secure distributed load frequency control for power systems under false data injection attacks

“…In a practical multi-area power system with a prescribed topology, each area cooperates with each other through interconnected tielines to maintain the balance between power generation and consumption [1][2][3][4][5]. However, with the unexpected load disturbances, the balance is easily broken and the load frequency appears with fluctuations [6][7][8][9].…”