Influence of Ambient Temperature on Transformer Overloading During Cold Load Pickup

Edstrom, F.; Rosenlind, Johanna; Alvehag, Karin; Hilber, Patrik; Söder, Lennart

doi:10.1109/tpwrd.2012.2219079

Cited by 12 publications

(7 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance, in 2007, Savaghebi [70] among others determined the loading capability as a function of voltage variation (including over-excitation) and in 2008 [61] for non-linear currents (harmonics). Other factors, affecting transformer limits, can be grouped as follows: economical [42,[71][72][73][74]; probabilistic [62,[75][76][77][78][79][80][81][82]; statistical [38,77,[83][84][85][86][87][88][89][90]. 4 OLTC stands for an On-Load Tap Changer…”

Section: Literature Review On Transformer Limitsmentioning

confidence: 99%

Energy limit of oil‐immersed transformers: A concept and its application in different climate conditions

Daminov

Prokhorov

Caire

et al. 2020

IET Generation Trans & Dist

View full text Add to dashboard Cite

The reality of modern power grids requires the use of flexibilities from generation, load and storage. These flexibilities allow system operators to modify a transformer loading in a smart way. Therefore, power constraints of transformers can be overcome by using the appropriate flexibility. However, transformers have a physical limit of energy transfer which cannot be overpassed. This energy limit represents the unique transformer's loading profile, ensuring the highest energy transfer under a given ambient temperature profile. The paper explains how the energy limit can be calculated. Typical characteristics of an energy limit are estimated in cold continental climate of Russia and warm temperate climate in France. Maximal, minimal and mean loadings are identified for each month. Loading durations of energy limit are determined for each cooling system. It is found that winding temperatures of transformers, operating at energy limits, remain in the vicinity of design winding temperature. Therefore, transformer operation at energy limit avoids a high temperature stress and simultaneously maximizes the energy transfer. The application of energy limits for power system problems is briefly explained along the paper. Energy limit application can reduce an energy cost, maximize a renewable generation and increase a hosting capacity of distribution network. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

show abstract

Section: Literature Review On Transformer Limitsmentioning

confidence: 99%

Energy limit of oil‐immersed transformers: A concept and its application in different climate conditions

Daminov

Prokhorov

Caire

et al. 2020

IET Generation Trans & Dist

View full text Add to dashboard Cite

show abstract

“…Since the effects of CLPU and the delayed reconnection of distributed generators occur at the same time and lead to an increased gradient of the residual load [14], the consideration of CLPU is especially relevant for investigations in mixed grids that contain generation as well as load. Furthermore, the CLPU curves can be considered in protection systems, in particular for slow-acting overload protection [22], and to assess the probability of thermal overload of equipment in such a situation [23].…”

Section: Motivationmentioning

confidence: 99%

Cold load pickup model parameters based on measurements in distribution systems

Hachmann

Lammert

Hamann³

et al. 2019

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

“…In addition, parameter σ has been nearly kept constant as the contamination coefficient increases. However, parameter γ decreases as the contamination coefficient increases, which can be justified using equation (10). As can be seen, in equation ( 10), γ is basically the regularization trade-off factor which determines the weight of the training set's inherent noise level during the training process.…”

Section: A Feeder Clpu Demand Ratio Estimation 1) Clpu Ratio Estimati...mentioning

confidence: 99%

“…For feeders with high penetration of TCLs, CLPU can have serious consequences, such as restoration failure [4]- [8], transformers aging [9], [10], transformer overloading [11], and unacceptable voltage drops [12]. CLPU demand can continue several minutes to even several hours after extreme weather conditions [2].…”

Section: Introductionmentioning

confidence: 99%

A Data-Driven Framework for Assessing Cold Load Pick-Up Demand in Service Restoration

Dehghanpour

Wang

et al. 2019

IEEE Trans. Power Syst.

View full text Add to dashboard Cite

Cold load pick-up (CLPU) has been a critical concern to utilities. Researchers and industry practitioners have underlined the impact of CLPU on distribution system design and service restoration. The recent large-scale deployment of smart meters has provided the industry with a huge amount of data that is highly granular, both temporally and spatially. In this paper, a data-driven framework is proposed for assessing CLPU demand of residential customers using smart meter data. The proposed framework consists of two interconnected layers: 1) At the feeder level, a nonlinear auto-regression model is applied to estimate the diversified demand during the system restoration and calculate the CLPU demand ratio. 2) At the customer level, Gaussian Mixture Models (GMM) and probabilistic reasoning are used to quantify the CLPU demand increase. The proposed methodology has been verified using real smart meter data and outage cases.Index Terms-Cold load pick-up, distribution systems, service restoration, least squares support vector machine, Gaussian Mixture Model.

show abstract

Influence of Ambient Temperature on Transformer Overloading During Cold Load Pickup

Cited by 12 publications

References 21 publications

Energy limit of oil‐immersed transformers: A concept and its application in different climate conditions

Energy limit of oil‐immersed transformers: A concept and its application in different climate conditions

Cold load pickup model parameters based on measurements in distribution systems

A Data-Driven Framework for Assessing Cold Load Pick-Up Demand in Service Restoration

Contact Info

Product

Resources

About