Transient Response Improvement of Microgrids Exploiting the Inertia of a Doubly-Fed Induction Generator (DFIG)

Papadimitriou, Christina; Vovos, N.A.

doi:10.3390/en30601049

Cited by 16 publications

(12 citation statements)

References 8 publications

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“…The references for a rotor-side convertor (RSC) and grid-side convertor (GSC) are determined by a DFIG-based WTG control system. The RSC controls the active and reactive powers supplied into an electric power grid; whereas the GSC maintains the DC-link voltage [18,19].…”

Section: Modeling and Control Of A Dfig-based Wtgmentioning

confidence: 99%

Short-Term Frequency Response of a DFIG-Based Wind Turbine Generator for Rapid Frequency Stabilization

et al. 2017

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This paper proposes a short-term frequency-response scheme of a doubly-fed induction generator (DFIG)-based wind turbine generator (WTG) for improving rotor speed recovery and frequency nadir. In the energy-releasing period, to improve the frequency nadir and rotor speed convergence by releasing a large amount of kinetic energy stored in the rotating masses in a DFIG-based WTG, the power reference is increased up to the torque limit referred to the power and reduces along with it for a predefined period which is determined based on the occurrence time of the frequency nadir in a power grid. Then, the reference decreases so that the rotor speed is forced to be converged to the preset value in the stable operating region of the rotor speed. In the energy-absorbing period, to quickly recover the rotor speed, the reference smoothly decreases with the rotor speed and time during a predefined period until it intersects with the maximum power point tracking curve. The simulation results demonstrate that the proposed scheme successfully achieves rapid frequency stabilization with the improved frequency nadir under various wind conditions based on the IEEE 14-bus system.

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Section: Modeling and Control Of A Dfig-based Wtgmentioning

confidence: 99%

Short-Term Frequency Response of a DFIG-Based Wind Turbine Generator for Rapid Frequency Stabilization

et al. 2017

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“…A microgrid can be a part of the distribution system, e.g., industry park, community, factory, or school [13][14][15]. The microgrid studied in this paper is operated by a single customer, a factory containing distributed generations.…”

Section: Microgridmentioning

confidence: 99%

Nonintrusive Energy Monitoring for Microgrids Using Hybrid Self-Organizing Feature-Mapping Networks

Hong

Chou

2012

Energies

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Microgrids can increase power penetration from distributed generation (DG) in the power system. The interface (i.e., the point of common coupling, PCC) between the microgrid and the power utility must satisfy certain standards, such as IEEE Sd. 1547. Energy monitoring of the microgrid at the PCC by the power utility is crucial if the utility cannot install advanced meters at different locations in the microgrid (e.g., a factory). This paper presents a new nonintrusive energy monitoring method using a hybrid self-organizing feature-mapping neural network (SOFMNN). The components of the FFT spectra for voltage, current, kW and kVAR, measured at the PCC, serve as the signatures for the hybrid SOFMNN inputs. The nonintrusive energy monitoring at the PCC identifies different load levels for individual linear/nonlinear loads and output levels for wind power generators in the microgrid. Using this energy monitoring result, the power utility can establish an energy management policy. The simulation results from a microgrid, consisting of a diesel generator, a wind-turbine-generator, a rectifier and a cyclo-converter, show the practicability of the proposed method.

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“…Subsequently, power managements of DGs (including MT, DFIG, etc.) also play an important role in maintaining frequency stability and regulating the microgrid to a new balanced state [12]. It has to be noted that DFIG can effectively support system frequency by auxiliary frequency control.…”

Section: Introductionmentioning

confidence: 99%

Cooperative Control to Enhance the Frequency Stability of Islanded Microgrids with DFIG-SMES

Liu

et al. 2013

Energies

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Abstract:The issue of frequency stability of microgrids under islanded operation mode and mode transfer has attracted particular attention recently. In this paper, a cooperative frequency control method, which consists of a microgrid central control (MGCC) and microgrid local control (MGLC), is proposed to achieve a seamless transfer from grid-connected to islanded mode, and hence increase the frequency stability of islanded microgrids during both primary and secondary frequency control. A power deficiency prediction and distribution method is proposed in MGCC to effectively distribute and utilize the power and loads, and accomplish the cooperative control of all microgrid units. With regards to MGLC, a Hopfield fuzzy neural network control (HFNNC) is applied to make the corresponding frequency control of DFIG-SMES more adaptive. Meanwhile a state of capacity (SOC) control is utilized in battery energy storage (BES) to extend battery life. Simulation results indicate that the proposed frequency control approach can maintain the frequency stability of islanded microgrids even in emergency conditions.

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Transient Response Improvement of Microgrids Exploiting the Inertia of a Doubly-Fed Induction Generator (DFIG)

Cited by 16 publications

References 8 publications

Short-Term Frequency Response of a DFIG-Based Wind Turbine Generator for Rapid Frequency Stabilization

Short-Term Frequency Response of a DFIG-Based Wind Turbine Generator for Rapid Frequency Stabilization

Nonintrusive Energy Monitoring for Microgrids Using Hybrid Self-Organizing Feature-Mapping Networks

Cooperative Control to Enhance the Frequency Stability of Islanded Microgrids with DFIG-SMES

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