Abstract
Due to the erratic nature of renewable sources and repeatedly varying load burdens, variations happening in the execution of AGC is a significant problem concerning deregulated power system (DPS) frequency stability. To solve this, issue demand response (DR) regulation and a hybrid energy storage system (HESS) with a new technique are required. Hence, this paper presents a novel quasi-opposition arithmetic optimization algorithm (QOAOA) optimized cascade interval type-II fuzzy proportional–integral–derivative (IT2FPID)-fractional order PI controller with DR and HESS of super-capacitor and redox flow battery (RFB) for suppressing the variations of frequency and tie-line power in a two-area restructure smart grid system, where the proficiency of the new optimization algorithm (QOAOA) is confirmed by relating its figure of demerit with other present algorithms. Additionally, the supremacy of the suggested IT2FPID-FOPI controller’s implementation is confirmed by competing it with other dominant control strategy. The impact of demand response, load fluctuations, wind speed variations, solar irradiation, and other nonlinearities like the governor dead band (GDB) and generation rate limitation is also evaluated on the analyzed power system with the anticipated controller. Additionally, hybrid energy storage devices containing super-capacitor and redox flow batteries are integrated to study the impact on system dynamics and report higher occurrence. Sensitivity analysis exposes that the QOAOA—improved proposed controller estimated at minimal circumstances is capable of handling significant changes in the system conditions and parameters. Conclusively, by utilizing OPAL-RT, a real-time hardware-in-the-loop (HIL) simulation is estimated to approve the practical feasibility of the suggested controller for the AGC challenge in the smart grid scenario.
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Abbreviations
- EVS :
-
Electric vehicles
- PEVS :
-
Plug-in electric vehicle
- GRC:
-
Generation-rate constraint
- PHEVs:
-
Plug-in hybrid electric vehicles
- GDB:
-
Governor-dead-band
- SOC:
-
State of charge
- P max :
-
Maximum power
- P min :
-
Minimum power Gc1 = Transfer function of system 1, Gc2 = Transfer function of system 2
- TLBO:
-
Teaching learning base optimization
- WHO:
-
Whale optimization
- ABC:
-
Artificial bee colony
- PSO:
-
Particle swarm optimization
- SLD:
-
Step load disturbance
- I :
-
Integral
- PI:
-
Proportion integral
- PD:
-
Proportional–derivative
- PID:
-
Proportional–integral–derivative
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Appendix
Appendix
1.1 Values of System Parameters
Thermal: N1i = 0.8, N2i = -0.064, Tg1i = 0.08, Tg2i = 0.08, Tr1i = 10, Kr1i = 0.5, Tt1i = 0.3; BD: K3 = 0.92, K1 = 0.095, K2 = 0.85, Kib = 0.03, Trb = 69, Td = 1, Tf = 10; Gas: Cgi = 1, bi=0.049 XGi=0.6, YGi=1.1, TCRi=0.01, TFi=0.239, TCDi=0.2; Power system parameter: Kps1 = 120, Rth = 2.4, Kps2 = 120, B1 = B2 = 0.545, capacity of area 1 Parea1 = 2000 MW, capacity of area 2 Parea2 = 2000 MW, loading on the system = 50%.
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Ranjan, M., Shankar, R. A Cascade Fractional Type-II Fuzzy Control Approach for Enhancing Frequency Stability in a Smart Grid System with Diverse Energy Resources. Iran J Sci Technol Trans Electr Eng 47, 1537–1560 (2023). https://doi.org/10.1007/s40998-023-00642-5
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DOI: https://doi.org/10.1007/s40998-023-00642-5