Active Power Allocation of Virtual Synchronous Generator Using Particle Swarm Optimization Approach

Rahman, Fathin Saifur; Kerdphol, Thongchart; Watanabe, Masayuki; Mitani, Yasunori

doi:10.4236/epe.2017.94b047

Cited by 9 publications

(3 citation statements)

References 15 publications

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“…Furthermore, VAD of each VSG for centre of inertia is used to substitute the usage of rotor angle deviation in a real-time transient index. Another example of the usage of PSO in VSG application is to minimise the frequency deviation of the MG by optimising the reference value of active power [48]. From the simulation, as the number of iterations gets higher, the frequency deviation gets smaller.…”

Section: Coordination Of Vsg Using Intelligent Techniquesmentioning

confidence: 99%

Progress in control and coordination of energy storage system‐based VSG: a review

Othman

Mokhlis

Mubin

et al. 2019

IET Renewable Power Generation

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Virtual synchronous generator (VSG) is an important concept toward frequency stabilisation of the modern power system. The penetration of power electronic-based power generation in power grid reduces the total inertia, and thus increases the risk of frequency instability when disturbance occurs in the grid. VSG produces virtual inertia by injecting appropriate active power value to the grid when needed. This virtual inertia can stabilise the grid frequency in case of a power imbalance between generation and loads or any disturbances that affected frequency stability. Its intensive research can see the importance of VSG in inertia control and various intelligent controller techniques. Owing to the importance of VSG in the modern power grid, this study provides a comprehensive review on the control and coordination of VSG toward grid stabilisation in terms of frequency, voltage and oscillation damping during inertia response. A review on the type of energy storage system used for VSG and their benefits is also presented. Finally, perspective on the technical challenges and potential future research related to VSG is also discussed in this study. Nomenclature P g measured active power Q g measured reactive power P * active power reference Q* reactive power reference V g * output voltage reference V g output voltage ω o reference angular frequency ω g grid Frequency ω r rotor angular frequency J moment of inertia constant D damping coefficient constant δ VSG phase angle X output reactance of the VSG K w governor proportional control gain K q reactive power proportional control gain T Q reactive power first-order lag time constant

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Section: Coordination Of Vsg Using Intelligent Techniquesmentioning

confidence: 99%

Progress in control and coordination of energy storage system‐based VSG: a review

Othman

Mokhlis

Mubin

et al. 2019

IET Renewable Power Generation

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“…Wu et al [15], proposed the alternating current (AC) frequency represents the state of charge (SOC) of the battery, while the PV generation controls its output power depending on the frequency calculated to maintain its stability. Rahman et al [16] used particle swarm optimization (PSO) to determine the best location for the active power of VSG to maintain the frequency within the allowable limits in the microgrid.…”

Section: Introductionmentioning

confidence: 99%

Optimized proportional-integral controller for a photovoltaic-virtual synchronous generator system

Edan

Mahdi

Wahab

2022

IJPEDS

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Due to the lack of a physical rotating rotor, the photovoltaic generators (PVG) have no inertia. Therefore, replacing traditional synchronous generators (SG), (source of inertia), with PVG will reduce the inertia of overall power systems. A reduced inertia and damping feature will frequently cause instability issues due to high rate of change of frequency (RoCoF), and less stringent voltage at the nearby point of common coupling (PCC). In this paper, the concept of virtual synchronous generators (VSG) is adopted in to couple the source with the grid frequency in order to provide virtual inertia. This is created by using energy storage for short time, direct current (DC) to alternating current (AC) converter, and a suitable control mechanism. In implementing VSG, the important aspects to focus on are reducing the fluctuation of DC-link voltage, stabilize the frequency and voltage, and power flow. So, the particle swarm optimization (PSO) algorithm was used to adjust the parameters of proportional integral (PI) controller by reducing the error of the current controller and voltage regulator in the VSG controller. The simulation results illustrate the advantages of the PI tuning using PSO, where the overshoot is decreased by 68.9% and the settling time is decreased by 34% due to load fluctuations.

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“…In addition, SS stability issues are as well found in the HMG. The stability issue is labelled as the instability that relies on DG units intended for sufficient balancing of energy [13]. The control system adopted finds the solution for instability issues [14].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Microgrid based on PID Controller with the Modified Particle Swarm Optimization

Rojin¹,

Linda²

2022

Intelligent Automation &Amp; Soft Computing

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Microgrids (MG) are distribution networks encompassing distributed energy sources. As it obtains the power from these resources, few problems such as instability along with Steady-State (SS) issues are noticed. To address the stability issues, that arise due to disturbances of low magnitude. Small-Signals Stability (SSS) becomes mandatory in the network. Convergence at local optimum is one of the major issues noticed with the existing optimization algorithms. This paper proposes a detailed model of SSS in Direct Current (DC)-Alternate Current (AC) Hybrid MG (HMG) using Proportional Integral and Derivative Controller (PIDC) tuned with Modified Particle Swarm Optimization (MPSO) algorithm to alleviate such issues. The power is extracted from Renewable Energy Resources (RER), such as Photovoltaic (PV), Micro-Hydro (MH), and Wind Energy Conversation System (WECS). For tracking the power more efficiently, Maximum Power Point Tracking (MPPT) techniques are employed. Boost Converters (BC) are used and inverters are employed to convert DC to the AC. Here, the power flow is managed by the PIDC. If the Firing Angle (FA) is not properly determined, it results in instability and steady-state stability issues. To address this, the optimum tuning parameters are chosen for PIDC, by utilizing the MPSO. Finally, through experimentation analysis, the proposed system's performance is analyzed and compared with the existing algorithms and validated.

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Active Power Allocation of Virtual Synchronous Generator Using Particle Swarm Optimization Approach

Cited by 9 publications

References 15 publications

Progress in control and coordination of energy storage system‐based VSG: a review

Progress in control and coordination of energy storage system‐based VSG: a review

Optimized proportional-integral controller for a photovoltaic-virtual synchronous generator system

Hybrid Microgrid based on PID Controller with the Modified Particle Swarm Optimization

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