Determination of zonal power demand S-curves with GA based on top-to-bottom and end-use approaches

Tursun F., Cebeci M. E., Tör O. B., Şahin A., Taşkin H. G., GÜVEN A. N.

4th International Istanbul Smart Grid Congress and Fair, ICSG 2016, İstanbul, Turkey, 20 - 21 April 2016 identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/sgcf.2016.7492423
  • City: İstanbul
  • Country: Turkey
  • Keywords: demand forecast, DigSilent PowerFactory, genetic algorithm, power distribution, S-curve
  • TED University Affiliated: No

Abstract

Long-term zonal demand forecasting is a complex problem for electric distribution systems, particularly when the planner has limited data, and therefore, needs smart approaches along with proper estimations. This paper presents a novel methodology to determine saturation curves (S-curves) of demand zones which are classified based on municipality development plans. The methodology which is based on combination of top-to-bottom and bottom-to-top (also called end-use) approaches, is applied to the network of Akdeniz Distribution Company (DISCO) of Turkey. Genetic algorithm (GA) technique is utilized to determine zonal S-curves by utilizing top-to-bottom projections and expected saturation demands of the zones. Sensitivity analysis shows that the proposed method gives reliable results as long as top-to-bottom results represent the total demand of the zones satisfactorily and the planner defines the constraints reasonably.