A Cross-Country Dynamic Panel Data Analysis For Turkey's Future Electricity Demand And Linear Programming Models For Generating Pathways Under Various Objectives

Ercan H., Önenli Ö.

41. Yöneylem Arastirmasive Endüstri Mühendisligi Ulusal Kongresi, Denizli, Turkey, 26 October - 28 November 2022, pp.1

  • Publication Type: Conference Paper / Summary Text
  • City: Denizli
  • Country: Turkey
  • Page Numbers: pp.1
  • Middle East Technical University Affiliated: Yes


This paper studies whether Turkey can meet its growing electricity demand by relying more on renewables, instead of increasing the use of its local coal resources. Our quantitative analysis proceeds in two stages. In the first stage, we provide projections for the future electricity demand of Turkey through 2040 by using a dynamic balanced panel data model of 41 countries. In the second stage, we develop linear programming models to study realistic and reasonable scenarios representing three probable future pathways to meet the econometrically estimated electricity demand.  The scenarios we run in this study are business-as-usual (BAU), minimize GHGs (minGHG), and maximize local resources (MaxLocal) simulations. A nuclear power program is included in BAU while the latter scenarios omit the possible completion of the nuclear power plant in the next ten to twelve years. The scenarios are compared in terms of investment requirements. The model results of minGHG and MaxLocal both show that the share of renewable generation should reach around two thirds of total generation to satisfy the projected demand by 2040. Moreover, annual investment requirement under minGHG is cheaper than of BAU, which corresponds to a 21-year cumulative difference of around 4 billion in current US dollars. Therefore, a secure low-carbon pathway with a lower investment requirement is possible for Turkey without nuclear power or new coal plants, while also retiring most of the existing coal plants.