Analysis and Control of Temporary Overvoltages for Automated Restoration Planning

Ketabi,; Ranjbar,; Feuillet,

doi:10.1109/mper.2002.4312325

Cited by 5 publications

(7 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…4 shows the harmonic overvoltages after the transformer energization for the best-case condition (i.e., 56°). For temporary overvoltages, the overvoltage duration has to be taken into account in addition to the amplitude [3]. Table I summarizes the results of overvoltages simulation for three different switching conditions that verify the effectiveness of W index.…”

Section: B Best Switching Condition Determinationmentioning

confidence: 98%

“…[1], [2]. A major process of power system restoration following a blackout would be energization of primary restorative transmission lines in most countries [3]. The energizing process begins by starting black-start generators such as hydro generators or gas turbines, and then charging some pre-defined transmission lines to supply cranking power for large generation plants [4], [6].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

New Approach to Harmonic Overvoltages Reduction during Transformer Energization via Controlled Switching

Sadeghkhani

Ketabi

Feuillet

2009

2009 15th International Conference on Intelligent System Applications to Power Systems

View full text Add to dashboard Cite

During early stage of primary restoration process, unexpected Overvoltages may happen due to nonlinear interaction between the unloaded transformer and the transmission system. The most effective method for the limitation of the switching Overvoltages is controlled switching since the magnitudes of the produced transients are strongly dependent on the closing instants of the switch. We introduce a harmonic index that it's minimum value is corresponding to the best case switching time. Also, this paper presents an Artificial Neural Network (ANN)-based approach to estimate the optimum switching instants for real time applications. In the proposed ANN, Levenberg-Marquardt second order method is used to train the multilayer perceptron. To verify the effectiveness of the proposed index and accuracy of the ANN-based approach, two case studies are presented and demonstrated.

show abstract

Section: B Best Switching Condition Determinationmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

New Approach to Harmonic Overvoltages Reduction during Transformer Energization via Controlled Switching

Sadeghkhani

Ketabi

Feuillet

2009

2009 15th International Conference on Intelligent System Applications to Power Systems

View full text Add to dashboard Cite

show abstract

“…The authors of [28] reported that WTGs are commonly modeled as a constant impedance in low frequency transients. Naturally, this replacement was also applied in the WTGs modeling for studying energization transients, and examples can be found in [29,30]. The constant impedance model is treated as parallel/series-connected resistive and inductive elements.…”

Section: Energization With Different Load Typesmentioning

confidence: 99%

Modeling and Mitigation for High Frequency Switching Transients Due to Energization in Offshore Wind Farms

2016

View full text Add to dashboard Cite

This paper presents a comprehensive investigation on high frequency (HF) switching transients due to energization of vacuum circuit breakers (VCBs) in offshore wind farms (OWFs). This research not only concerns the modeling of main components in collector grids of an OWF for transient analysis (including VCBs, wind turbine transformers (WTTs), submarine cables), but also compares the effectiveness between several mainstream switching overvoltage (SOV) protection methods and a new mitigation method called smart choke. In order to accurately reproduce such HF switching transients considering the current chopping, dielectric strength (DS) recovery capability and HF quenching capability of VCBs, three models are developed, i.e., a user-defined VCB model, a HF transformer terminal model and a three-core (TC) frequency dependent model of submarine cables, which are validated through simulations and compared with measurements. Based on the above models and a real OWF configuration, a simulation model is built and several typical switching transient cases are investigated to analyze the switching transient process and phenomena. Subsequently, according to the characteristics of overvoltages, appropriate parameters of SOV mitigation methods are determined to improve their effectiveness. Simulation results indicate that the user-defined VCB model can satisfactorily simulate prestrikes and the proposed component models display HF characteristics, which are consistent with onsite measurement behaviors. Moreover, the employed protection methods can suppress induced SOVs, which have a steep front, a high oscillation frequency and a high amplitude, among which the smart choke presents a preferable HF damping effect.

show abstract

“…They can be excited by harmonic sources such as saturated transformers, power electronics, and so forth. They may lead to long-lasting overvoltages resulting in arrester failures and system faults [2]. …”

Section: Study For Temporary Overvoltages During Restorationmentioning

confidence: 99%

“…Both factors increase the risk of major power outages. After a blackout, power needs to be restored as quickly and reliably as possible and, consequently, detailed restoration plans are necessary [1, 2]. If the frequency characteristic of the system shows resonance conditions around multiples of the fundamental frequency, very high and weakly damped temporary overvoltages (TOVs) of long duration may occur when the system is excited by a harmonic disturbance, such as the switching of lightly loaded transformers or transformer saturation [1, 3–5].…”

Section: Introductionmentioning

confidence: 99%

Radial Basis Function Neural Network Application to Power System Restoration Studies

Sadeghkhani

Ketabi

Feuillet

2012

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

One of the most important issues in power system restoration is overvoltages caused by transformer switching. These overvoltages might damage some equipment and delay power system restoration. This paper presents a radial basis function neural network (RBFNN) to study transformer switching overvoltages. To achieve good generalization capability for developed RBFNN, equivalent parameters of the network are added to RBFNN inputs. The developed RBFNN is trained with the worst-case scenario of switching angle and remanent flux and tested for typical cases. The simulated results for a partial of 39-bus New England test system show that the proposed technique can estimate the peak values and duration of switching overvoltages with good accuracy.

show abstract

Analysis and Control of Temporary Overvoltages for Automated Restoration Planning

Cited by 5 publications

References 0 publications

New Approach to Harmonic Overvoltages Reduction during Transformer Energization via Controlled Switching

New Approach to Harmonic Overvoltages Reduction during Transformer Energization via Controlled Switching

Modeling and Mitigation for High Frequency Switching Transients Due to Energization in Offshore Wind Farms

Radial Basis Function Neural Network Application to Power System Restoration Studies

Contact Info

Product

Resources

About