A Novel Hybrid Fuzzy PD-TID Controller for Load Frequency Control of a Standalone Microgrid

Khokhar, Bhuvnesh; Dahiya, Surender; Parmar, K. P. Singh

doi:10.1007/s13369-020-04761-7

Cited by 39 publications

(19 citation statements)

References 26 publications

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“…A modified moth swarm algorithm (mMSA) with a hybrid fuzzy PD-PI controller to achieve the frequency stability of a distributed HGS is described in [7]. In addition, a feedforward fractional-order PID strategy based on a harmony search algorithm is applied in [8] to regulate system frequency considering the integral of time multiplied squared error (ITSE), while the chaotic crow search algorithm is used to optimize the hybrid fuzzy proportional derivative-tilt integral derivative controller parameters to control the frequency of a standalone microgrid [9].…”

Section: Introductionmentioning

confidence: 99%

Adaptive coordination control strategy of renewable energy sources, hydrogen production unit, and fuel cell for frequency regulation of a hybrid distributed power system

Salama

Magdy

Bakeer

et al. 2022

Prot Control Mod Power Syst

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Owing to the significant number of hybrid generation systems (HGSs) containing various energy sources, coordination between these sources plays a vital role in preserving frequency stability. In this paper, an adaptive coordination control strategy for renewable energy sources (RESs), an aqua electrolyzer (AE) for hydrogen production, and a fuel cell (FC)-based energy storage system (ESS) is proposed to enhance the frequency stability of an HGS. In the proposed system, the excess energy from RESs is used to power electrolysis via an AE for hydrogen energy storage in FCs. The proposed method is based on a proportional-integral (PI) controller, which is optimally designed using a grey wolf optimization (GWO) algorithm to estimate the surplus energy from RESs (i.e., a proportion of total power generation of RESs: Kn). The studied HGS contains various types of generation systems including a diesel generator, wind turbines, photovoltaic (PV) systems, AE with FCs, and ESSs (e.g., battery and flywheel). The proposed method varies Kn with varying frequency deviation values to obtain the best benefits from RESs, while damping the frequency fluctuations. The proposed method is validated by considering different loading conditions and comparing with other existing studies that consider Kn as a constant value. The simulation results demonstrate that the proposed method, which changes Kn value and subsequently stores the power extracted from the RESs in hydrogen energy storage according to frequency deviation changes, performs better than those that use constant Kn. The statistical analysis for frequency deviation of HGS with the proposed method has the best values and achieves large improvements for minimum, maximum, difference between maximum and minimum, mean, and standard deviation compared to the existing method.

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Section: Introductionmentioning

confidence: 99%

Adaptive coordination control strategy of renewable energy sources, hydrogen production unit, and fuel cell for frequency regulation of a hybrid distributed power system

Salama

Magdy

Bakeer

et al. 2022

Prot Control Mod Power Syst

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“…However, the performance efficacy of classical controllers is more likely to be dependent upon the optimization algorithms that have been deployed to optimize the controller gains. Several population-and stochastic-based searching algorithms reported in domain of LFC in optimizing classical controllers are chaotic atom search optimization (CASO) (Irudayaraj et al, 2022), many-objective optimization approach (MOOA) (Hajiakbari Fini et al, 2016), chaotic crow search (CCS) algorithm (Khokhar et al, 2021), gray wolf optimizer (GWO) (Sharma and Saikia, 2015), quadratic approach with pole compensator (QAWPC) (Hanwate and Hote, 2018), marine predator algorithm (MPA) (Yakout et al, 2021), Hooke-Jeeve's optimizer (HJO) (Chatterjee, 2010), quasioppositional harmony search algorithm (QOHSA) (Shankar and Mukherjee, 2016), chemical reaction optimizer (CRO) (Mohanty and Hota, 2018), hybrid artificial electric field algorithm (HAEFA) (Sai Kalyan et al, 2020), bacteria foraging optimization (BFOA) (Ali and Elazim, 2015), mine blast optimizer (MBO) (Alattar et al, 2019), particle swarm optimizer (PSO) (Magid and Abido, 2003), differential evolution (DE) (Kalyan and Suresh, 2021), combination of DE with pattern search (Sahu et al, 2015a) and AEFA (DE-AEFA) (Kalyan and Rao, 2021a), grasshopper optimizer (GHO), and cuckoo search approach (CSA) (Latif et al, 2018). Moreover, the conventional controllers exhibit efficacy in linearized models and could not maintain the stability of nonlinear interconnected power systems (IPS).…”

Section: Introductionmentioning

confidence: 99%

Seagull Optimization Algorithm–Based Fractional-Order Fuzzy Controller for LFC of Multi-Area Diverse Source System With Realistic Constraints

Kalyan¹,

Goud

Reddy

et al. 2022

Front. Energy Res.

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This study initiates the implementation of fractional-order (FO) fuzzy (F) PID (FOFPID) controller fine-tuned using a seagull optimization algorithm (SOA) for the study of load frequency control (LFC). Initially, the SOA-tuned FOFPID regulator is implemented on the widely utilized model of dual-area reheat-thermal system (DARTS), named test system-1 in this work for a perturbation of 10% step load (10% SLP) on area-1. Dynamical analysis of the DARTS system reveals the viability of the SOA-tuned FOFPID control scheme in regulating frequency deviations effectively compared to other control schemes covered in the literature. Later, the presented regulator is implemented on the multi-area diverse sources (MADS) system possessing realistic constraints in this study, termed test system-2. The sovereignty of the presented FOFPID controller is once again evidenced with controllers of PID/FOPID/FPID fine-tuned with the SOA approach. Moreover, the effect of considering practical realistic nonlinearity constraints such as communication time delays (CTDs) on MADS system performance is visualized and the necessity of its consideration is demonstrated. Furthermore, AC-DC lines are incorporated with the MADS system to enhance the performance under heavy-load disturbances and the robustness of the proposed regulatory mechanism is deliberated.

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“…A nonlinear load frequency controller is developed in [8], also with sliding mode controller in [24], [25], however, they have more mathematical intricacies. More new optimization methods are implemented for this problem in [20]− [23].…”

Section: Introductionmentioning

confidence: 99%

Implementation of Harris Hawks optimization for load frequency control of hydropower plant

Potnuru¹,

Kumar²,

Sonia³

et al. 2022

IJPEDS

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Hydropower has been used for many years and is essential to meet the renewable energy ambition of the world at present. In a hydroelectric power plant, voltage and frequency control are required, but, the voltage control could be done on the load side. In the present paper, frequency control using Harris Hawks optimization (HHO) for improved performance has been presented. Simulations are performed on the dynamic model of the hydropower plant and results are compared with the conventional PID that is designed using the Ziegler-Nichols method. The efficacy of the proposed algorithm is also tested at dynamic conditions of the hydropower plant.

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A Novel Hybrid Fuzzy PD-TID Controller for Load Frequency Control of a Standalone Microgrid

Cited by 39 publications

References 26 publications

Adaptive coordination control strategy of renewable energy sources, hydrogen production unit, and fuel cell for frequency regulation of a hybrid distributed power system

Adaptive coordination control strategy of renewable energy sources, hydrogen production unit, and fuel cell for frequency regulation of a hybrid distributed power system

Seagull Optimization Algorithm–Based Fractional-Order Fuzzy Controller for LFC of Multi-Area Diverse Source System With Realistic Constraints

Implementation of Harris Hawks optimization for load frequency control of hydropower plant

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