A Novel Approach to Predict Transformer Temperature Rise under Harmonic Load Current Conditions
Bonginkosi A. Thango and
Pitshou N. Bokoro
Additional contact information
Bonginkosi A. Thango: Department of Electrical and Electronic Engineering Technology, University of Johannesburg, Johannesburg 2028, South Africa
Pitshou N. Bokoro: Department of Electrical and Electronic Engineering Technology, University of Johannesburg, Johannesburg 2028, South Africa
Energies, 2022, vol. 15, issue 8, 1-18
Abstract:
In South Africa, distribution transformers (DTs) facilitating solar photovoltaic applications represent the highest percentage of total ownership cost investment for independent power producers (IPPs). One of the most indispensable variables that regulate DTs’ operational life span is the hotspot temperature. The prevailing analytical approaches designated to guesstimate the transformer thermal necessities were fathered in accordance with the conservative foundation that an electrical transformer is prone to uniform mean daily and monthly peak loads. In order to appropriately puzzle out the transformer thermal necessities, the formation of a more detailed thermal model that operates with real-time contorted cyclic loading, ambient air temperature, and the intrinsic characteristics of the transformer in-service losses is required. In the current work, various regression models are proposed for the modification of the top-oil formula and the hotspot temperature formula in the IEEE loading guide standard to replicate the real harmonic load currents (HLCs) and the fluctuating ambient air temperature (AT) on an hourly and daily basis. The proposed thermal model is examined in various transformers case studies, in which the computed outcomes produce an error margin of no more than 3% throughout all test cases when compared to the measured data.
Keywords: distribution transformers; solar photovoltaic; hotspot temperature (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://www.mdpi.com/1996-1073/15/8/2769/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/8/2769/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:8:p:2769-:d:790420
Access Statistics for this article
Energies is currently edited by Ms. Agatha Cao
More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().