Regulation of Voltage and Frequency in Solid Oxide Fuel Cell-Based Autonomous Microgrids Using the Whales Optimisation Algorithm

Qazi, Sajid Hussain; Mustafa, Mohd Wazir; Sultana, Umbrin; Mirjat, Nayyar Hussain; Soomro, Suhail Ahmed; Rasheed, Nadia

doi:10.3390/en11051318

Cited by 23 publications

(26 citation statements)

References 27 publications

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“…In both case studies, the frequency declined to 59.7 Hz from its rated value (60 Hz) during DG insertion and load change conditions. Most recently, Qazi et al [13] used the whale optimization algorithm (WOA) for regulating frequency and voltage independently by formulating two different fitness functions in an islanded MG. However, it may be noted that the voltage and frequency are two interrelated parameters [12], and therefore, it is not practically possible to independently optimize these two inter-dependent parameters.…”

Section: Control Architecturesmentioning

confidence: 99%

Salp Swarm Optimization Algorithm-Based Controller for Dynamic Response and Power Quality Enhancement of an Islanded Microgrid

et al. 2019

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The islanded mode of the microgrid (MG) operation faces more power quality challenges as compared to grid-tied mode. Unlike the grid-tied MG operation, where the voltage magnitude and frequency of the power system are regulated by the utility grid, islanded mode does not share any connection with the utility grid. Hence, a proper control architecture of islanded MG is essential to control the voltage and frequency, including the power quality and optimal transient response during different operating conditions. Therefore, this study proposes an intelligent and robust controller for islanded MG, which can accomplish the above-mentioned tasks with the optimal transient response and power quality. The proposed controller utilizes the droop control in addition to the back to back proportional plus integral (PI) regulator-based voltage and current controllers in order to accomplish the mentioned control objectives efficiently. Furthermore, the intelligence of the one of the most modern soft computational optimization algorithms called salp swarm optimization algorithm (SSA) is utilized to select the best combination of the PI gains (kp and ki) and dc side capacitance (C), which in turn ensures optimal transient response during the distributed generator (DG) insertion and load change conditions. Finally, to evaluate the effectiveness of the proposed control approach, its outcomes are compared with that of the previous approaches used in recent literature on basis of transient response measures, quality of solution and power quality. The results prove the superiority of the proposed control scheme over that of the particle swarm optimization (PSO) and grasshopper optimization algorithm (GOA) based MG controllers for the same operating conditions and system configuration.

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Section: Control Architecturesmentioning

confidence: 99%

Salp Swarm Optimization Algorithm-Based Controller for Dynamic Response and Power Quality Enhancement of an Islanded Microgrid

et al. 2019

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“…However, after the DG insertion and load change, the frequency level was settled to a new value (59.7 Hz) after a decline of 0.5% from its rated value (60 Hz) in both case studies. Most recently in Reference [34], the Whales Optimization Algorithm (WOA) was utilized for the regulation of voltage and frequency separately by using two different cost functions in an autonomous MG. In the referred study [34], the voltage and current were converted from three-phase (abc) axis to direct-quadrature (d-q) axis reference frame before the control loops using Park's transformation.…”

Section: Related Work In Literaturementioning

confidence: 99%

“…Most recently in Reference [34], the Whales Optimization Algorithm (WOA) was utilized for the regulation of voltage and frequency separately by using two different cost functions in an autonomous MG. In the referred study [34], the voltage and current were converted from three-phase (abc) axis to direct-quadrature (d-q) axis reference frame before the control loops using Park's transformation. As such, the frequency (or its integral θ) is included inside the conversion.…”

Section: Related Work In Literaturementioning

confidence: 99%

“…In addition, the obtained results are better than those of previous research work in the mentioned area of research. Unlike the previous studies, such as References [3,34], our proposed control strategy has managed to keep the frequency value within its ±1% tolerance limits as seen in Figure 8b. Moreover, unlike the voltage control in Reference [34] where an over-voltage of 20% has been observed during steady state condition (from 0.5 s to 0.7 s of the simulation), the proposed control strategy is able to reach and maintain its rated voltage within 0.07 s. The voltage and frequency control of an islanded MG using the hybrid Big-Bang Big-Crunch (BB-BC) and the Pareto based BB-BC algorithm has been studied in References [14,25] respectively.…”

Section: Voltage and Frequency Regulation During Dg Insertion And Loamentioning

confidence: 99%

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Optimal Voltage and Frequency Control of an Islanded Microgrid Using Grasshopper Optimization Algorithm

et al. 2018

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Due to the lack of inertia and uncertainty in the selection of optimal Proportional Integral (PI) controller gains, the voltage and frequency variations are higher in the islanded mode of the operation of a Microgrid (MG) compared to the grid-connected mode. This study, as such, develops an optimal control strategy for the voltage and frequency regulation of Photovoltaic (PV) based MG systems operating in islanding mode using Grasshopper Optimization Algorithm (GOA). The intelligence of the GOA is utilized to optimize the PI controller parameters. This ensures an enhanced dynamic response and power quality of the studied MG system during Distributed Generators (DG) insertion and load change conditions. A droop control is also employed within the control architecture, alongside the voltage and current control loops, as a power-sharing controller. In order to validate the performance of the proposed control architecture, its effectiveness in regulating MG voltage, frequency, and power quality is compared with the precedent Artificial Intelligence (AI) based control architectures for the same control objectives. The effectiveness of the proposed GOA based parameter selection method is also validated by analyzing its performance with respect to the improved transient response and power quality of the studied MG system in comparison with that of the Particle Swarm Optimization (PSO) and Whales Optimization Algorithm (WOA) based parameter selection methods. The simulation results establish that the GOA provides a faster and better solution than PSO and WOA which resulted in a minimum voltage and frequency overshoot with minimum output current and Total Harmonic Distortion (THD).

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“…Discretization of voltage has a negative impact that is, an imperceptible amount of subharmonics is generated while synthesizing the periodic waveforms [113,114]. In order to obtain an indistinguishable output, DM-CC should be switched at a seven times higher frequency compared to PWM modulator [113,115]. Nevertheless, this controller is simple in design and is independent from the parameters of the load.…”

Section: 1 Discrete Modulation Current Controller (Dm-cc)mentioning

confidence: 99%

Review on Current Control Techniques of Grid Connected PWM-VSI Based Distributed Generation

2019

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Nowadays, new trends in the industry of electricity generation are to enhance the power generation by employing distributed generation (DG) system which is mostly based on renewable generation sources such as wind, solar, etc. However, many power quality problems could arise on existing grid when DG is connected or the operation of distributed energy resources (DER) is not controlled properly. That's why, while integrating DG with the power grid, a seamless attention should be given to power generation and safe running of system. Several methods, having a diverse concept, have been divided into two main sets: linear and nonlinear controllers. The first group comes with PI controller and parameter feedback controller, and control by means of constant frequency with predictive techniques. The second group includes hysteresis current control and on-line optimization for predictive controllers. Additionally, new current control techniques with neural networks and fuzzy based controllers are also discussed. Selected methods associate the arrangement for the sake to demonstrate the described groups of the controller.

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Regulation of Voltage and Frequency in Solid Oxide Fuel Cell-Based Autonomous Microgrids Using the Whales Optimisation Algorithm

Cited by 23 publications

References 27 publications

Salp Swarm Optimization Algorithm-Based Controller for Dynamic Response and Power Quality Enhancement of an Islanded Microgrid

Salp Swarm Optimization Algorithm-Based Controller for Dynamic Response and Power Quality Enhancement of an Islanded Microgrid

Optimal Voltage and Frequency Control of an Islanded Microgrid Using Grasshopper Optimization Algorithm

Review on Current Control Techniques of Grid Connected PWM-VSI Based Distributed Generation

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