A Coordinated Frequency Control in Microgrid Based on Asymmetric Synthetic Inertia Considering Rotational Speed of Wind Turbine

Qi, Jingting; Tsuji, Takeshi

doi:10.1002/tee.23763

Cited by 2 publications

(2 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, it is impossible to eliminate the imbalance completely and frequency fluctuation occurs accordingly. Figure 2 shows the block diagram of DE model consisting of governor, engine, generator as well as time delay [45]. Here, the isochronous operation is modeled with an integrator.…”

Section: Ac Microgrid Model and Fundamental Equationsmentioning

confidence: 99%

See 1 more Smart Citation

Coordinated Q‐V/P‐f Control Strategy Using Virtual Power Factor for Autonomous AC Microgrid with PV Smart Inverters

Arou,

Tsuji

2024

IEEJ Transactions Elec Engng

Self Cite

View full text Add to dashboard Cite

Given the increasing interests in carbon neutrality due to climate change, photovoltaic (PV)‐based microgrid has become an important research topic worldwide. Typically, high PV penetration without proper control schemes causes power quality issues such as voltage or frequency violation, resulting in the limited PV hosting capacity. Reactive and active power support from the PV is effective to solve the issues, however, it is a critical challenge to efficiently contribute to the stabilizing controls under the inverter capacity constraint. Recent studies have applied smart inverters, equipped with fixed active and reactive power control reserves, for dynamic voltage and frequency support. In this paper, we proposed a control strategy in which the control reserves for voltage and frequency support are flexibly adjusted using virtual power factor (VPF) to improve the power quality with reducing active power curtailment. The effectiveness of the proposed Q‐V/P‐f control is verified through numerical simulations using a microgrid model developed in MATLAB/Simulink platform. It was observed through the simulation that the proposed method contributed to mitigating voltage and frequency fluctuation with satisfying the inverter capacity constraint. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

show abstract

Section: Ac Microgrid Model and Fundamental Equationsmentioning

confidence: 99%

“…Parameters for PV smart inverter controlTableIVshows the control parameters for smart inverters. The time constant for low-pass filter in Figs 6 and 7 are set to 30 s because the cut-off frequency of DE output control is around 30 s according to[45].…”

mentioning

confidence: 99%

Coordinated Q‐V/P‐f Control Strategy Using Virtual Power Factor for Autonomous AC Microgrid with PV Smart Inverters

Arou,

Tsuji

2024

IEEJ Transactions Elec Engng

Self Cite

View full text Add to dashboard Cite

show abstract

The energy management strategy of a loop microgrid with wind energy prediction and energy storage system day-ahead optimization

Xu,

Zhang,

Bai

et al. 2024

Front. Energy Res.

View full text Add to dashboard Cite

Microgrid has been extensively applied in the modern power system as a supplementary mode for the distributed energy resources. The microgrid with wind energy is usually vulnerable to the intermittence and uncertainty of the wind energy. To increase the robustness of the microgrid, the energy storage system (ESS) is necessary to compensate the power imbalance between the power supply and the load. To further maximize the economic efficiency of the system, the system level control for the microgrid is desired to be optimized when it is integrated with the utility grid. Aiming at the aforementioned problem, this paper comprehensively analyzes the power flow of a typical loop microgrid. A transformer-based wind power prediction (WPP) algorithm is proposed and compared with recurrent neural networks algorithm. With the historical weather data, it can accurately predict the 24 h average wind energy. Based on the predicted wind energy and the time-of-use (TOU) electricity price, a day-ahead daily cycling profile of the ESS with particle swarm optimization algorithm is introduced. It comprehensively considers the system capacity constraints and the battery degree of health. The functionality of the proposed energy management strategy is validated from three levels. First, WPP is conducted with the proposed algorithm and the true historical weather data. It has validated the accuracy of the transformer algorithm in prediction of the hourly level wind energy. Second, with the predicted wind energy, a case study is given to validate the day-ahead daily cycling profile. A typical 1 MVA microgrid is utilized as the simulation model to validate performance of the daily cycling optimization algorithm. The case study results show that the ESS daily cycling can effectively reduce the daily energy expense and help to shave the peak power demand in the grid.

show abstract

A Coordinated Frequency Control in Microgrid Based on Asymmetric Synthetic Inertia Considering Rotational Speed of Wind Turbine

Cited by 2 publications

References 25 publications

Coordinated Q‐V/P‐f Control Strategy Using Virtual Power Factor for Autonomous AC Microgrid with PV Smart Inverters

Coordinated Q‐V/P‐f Control Strategy Using Virtual Power Factor for Autonomous AC Microgrid with PV Smart Inverters

The energy management strategy of a loop microgrid with wind energy prediction and energy storage system day-ahead optimization

Contact Info

Product

Resources

About