Optimal capacity planning of substation transformers by demand response combined with network automation

Muhammad Humayun*, Amir Safdarian, Mubbashir Ali, Merkebu Z. Degefa, Matti Lehtonen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

7 Citations (Scopus)


The inclusion of smart grid features such as demand response (DR) and network automation for capacity planning of substation transformers may provide substantial monetary savings. This paper proposes an optimization model for quantification of the savings in capacity management of substation transformers over long-run. The proposed model incorporates the DR as a resource to decrease the outage cost during contingencies while considering existing switching types for load transfer between substations. The model provides optimal selection and scheduling of multistage transformer installations and their refurbishments by considering all the costs associated with them including investment, losses, maintenance, reliability, and the salvage value. For a realistic study, numerical value of the savings in transformers' cost is calculated for a typical Finnish two-transformer primary distribution substation planning over a period of forty years. Case studies are performed based on situations encountered by utilities and type of load transfer switching (manual and remote) between substations. A sensitivity analysis based on DR penetration and load curtailment (LC) cost is also performed. The results indicate that substantial monetary benefits can be obtained in substation transformers' cost by utilities through employing DR. The benefit of DR is superior for cases where it is used in combination with remote switching of load transfer between neighbouring substations (NSS).

Original languageEnglish
Pages (from-to)176-185
Number of pages10
JournalElectric Power Systems Research
Publication statusPublished - 1 May 2016
MoE publication typeA1 Journal article-refereed


  • Automation
  • Demand response
  • Planning
  • Substation
  • Transformer


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