Optimising the transformer substation topology in order to minimise annual energy losses
Journal article, 2018

The transformer losses can usually be classified into two basic categories: losses in the transformer core (voltage-dependent losses) and losses in the transformer winding copper (current-dependent losses). By increasing the number of active transformers in the transformer substation the authors reduce the total losses in the transformer copper but on the other hand increase the total losses in the transformer iron core. Considering this, it can be concluded that it is possible to determine the optimum number of active transformers in the substation for each operating condition together with the way they are connected. In this study, the authors propose a novel optimisation algorithm which can be used to determine the optimal operating conditions of the transformer substation to minimise annual energy losses while avoiding frequent transformer switching and assuring provision of sufficient transformation power in order to supply distribution load. The algorithms which are outlined are applicable for substations 110/xkV and 35/10(20)kV which have more than one transformer installed with different levels of substation topology complexity (flexibility).

transformer winding copper losses

current-dependent losses

substation topology complexity levels

voltage-dependent losses

transformer core losses

transformer substation topology

power transformers

transformer windings

novel optimisation algorithm

minimisation

distribution load

transformer substations

transformation power

annual energy losses minimisation

Author

Damir Jakus

University of Split

Josip Vasilj

Chalmers, Electrical Engineering, Systems and control

Rade Cadenovic

University of Split

Petar Sarajcev

University of Split

IET Generation, Transmission and Distribution

1751-8687 (ISSN) 1751-8695 (eISSN)

Vol. 12 6 1323-1330

Subject Categories

Other Mathematics

Marine Engineering

Other Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1049/iet-gtd.2017.0721

More information

Latest update

5/4/2018 1