Transmission Grid Secondary Voltage Control Method Using PMU Data

Su, Heng-Yi; Kang, Feng-Ming; Liu, Chih-Wen

doi:10.1109/tsg.2016.2623302

Cited by 43 publications

(22 citation statements)

References 31 publications

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“…The nonlinear equality constraint can be linearized using linearized model of decoupled power flow equations where real power changes are assumed to be less sensitive to changes in the voltage magnitude. Thus, the approximate model of the small disturbance voltage-VAR control can be represented by a linear relation between the reactive power and the voltages of the generator, capacitor and load buses as given in (15) [9,10]. ΔΔ…”

Section: Load Busmentioning

confidence: 99%

“…Once the predefined value of tolerance is achieved, the proposed algorithm will stop and produce the optimal u*. (27) where l is the total number of load buses.…”

Section: Load Busmentioning

confidence: 99%

“…Flowchart for the SVC algorithmThe performance of the SVC algorithm can be expressed as the root mean square value of voltage deviations at all load buses given by(27) …”

mentioning

confidence: 99%

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Compressive Sensing and Morphology Singular Entropy-Based Real-Time Secondary Voltage Control of Multiarea Power Systems

Khan

Kar

et al. 2019

IEEE Trans. Ind. Inf.

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This paper presents an improved secondary voltage control (SVC) methodology incorporating compressive sensing (CS) for a multi-area power system. SVC minimizes the voltage deviation of the load buses while CS deals with the problem of the limited bandwidth capacity of the communication channel by reducing the size of massive data output from phasor measurement unit (PMU) based monitoring system. The proposed strategy further incorporates the application of a Morphological Median Filter (MMF) to reduce noise from the output of the PMUs. To keep the control area secure and protected locally, Mathematical Singular Entropy (MSE) based fault identification approach is utilized for fast discovery of faults in the control area. Simulation results with 27-bus and 486-bus power systems show that CS can reduce the data size up to 1/10 th while the MSE based fault identification technique can accurately distinguish between fault and steady state conditions. N communication channel, and communication channel cost.CS is regarded as a promising joint data acquisition and reconstruction method to deal with the problem of limited bandwidth and data congestion. The data retrieved from the PMUs can be compressed before sending through the communication channel and can be recovered at the end of communication channel. Plenty of research has been performed to recover the signal at the end of communication channel [13], [14]. A CS based control strategy is developed for load frequency control in a multi-area power system network [15]. This strategy helps reduce the transmission data loss and increase the reliability of the communication network.Performance of CS may be affected by the noise in the signal, which may induce error in the signal processing and degrade the system's dynamic performance [16]. In order to deal with such problems, several noise filtering techniques have been developed in the recent literature [17], [18]. Based on the theory of Mathematical Morphology (MM), a mathematical morphological filter (MMF) is proposed in [21],

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Section: Load Busmentioning

confidence: 99%

“…Once the predefined value of tolerance is achieved, the proposed algorithm will stop and produce the optimal u*. (27) where l is the total number of load buses.…”

Section: Load Busmentioning

confidence: 99%

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Compressive Sensing and Morphology Singular Entropy-Based Real-Time Secondary Voltage Control of Multiarea Power Systems

Khan

Kar

et al. 2019

IEEE Trans. Ind. Inf.

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“…Outro controle secundário de tensãoé elaborado por Su et al (2018) utilizando um método adaptativo baseado em "Phasor Measurement Unit" (PMU), unidade de medição fasorial. As perturbações de carga são estimadas online e o objetivoé melhorar os perfis de tensão por meio da diminuição do desvio de tensão da carga.…”

Section: Introductionunclassified

Controle Secundário de Tensão aplicado à microrredes

Reis

Filho

2020

Anais Do Congresso Brasileiro De Automática 2020

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A busca por um sistema que seja capaz de atender a demanda com segurança e confiabilidade requer o desenvolvimento de ferramentas computacionais que modelem tais equipamentos na prática. Desta forma, realizar um controle de tensão eficaz é cada vez mais essencial para que haja um bom planejamento e operação do sistema. Este artigo realiza uma implementação do controle secundário de tensão no fluxo de potência tradicional em microrredes, considerando unidades de geração distribuída com inversores em droop. A contribuição deste trabalho está baseada na modificação/expansão da matriz jacobiana do fluxo de potência, por meio da inserção do fator de participação dos geradores integrantes de tal controle. A metodologia será aplicada no sistema teste de 38 barras do IEEE e validada por meio do software ANAREDE.

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“…An inter-plant voltage control was introduced for improving the voltage stability margin by coordinating reactive power reserves [12]. However, such solutions often lay on on-line (i.e., at each control sampling time) optimization of multi-variable quadratic function which is difficult to implement in real-time, especially when a lot of distant (PMU) measures have to be used [13]. Moreover, voltage and reactive power tracking objectives are mixed into a quadratic index to be minimized and this leads to uncertain reactive power alignment.…”

Section: Introductionmentioning

confidence: 99%

Structural Analysis and Improved Reactive Power Alignment for Secondary Voltage Control

Bouzid

Marinescu

Denis³

2019

2019 IEEE Milan PowerTech

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This paper proposes a new strategy for secondary voltage control which is easier to implement and improves the alignment of reactive power of generators The control objectives are revisited from both static and dynamic points of view using the internal model principle. A new alignment strategy for the reactive power generations is proposed along with robust dynamic control. The methodology is applied to interconnected power networks based on real data on EUROSTAG. The simulation results show the performance of the proposed methods to regulate the voltage on the pilot buses at the desired values.

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Transmission Grid Secondary Voltage Control Method Using PMU Data

Cited by 43 publications

References 31 publications

Compressive Sensing and Morphology Singular Entropy-Based Real-Time Secondary Voltage Control of Multiarea Power Systems

Compressive Sensing and Morphology Singular Entropy-Based Real-Time Secondary Voltage Control of Multiarea Power Systems

Controle Secundário de Tensão aplicado à microrredes

Structural Analysis and Improved Reactive Power Alignment for Secondary Voltage Control

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