Emission reduction pathways for satisfying Türkiye's future electricity demand: A cross-country dynamic panel analysis with linear programming scenarios

Abstract

This paper studies whether feasible and plausible pathways exist for Türkiye to meet its growing electricity demand while reducing its emissions, 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 determine the future electricity demand of Türkiye from 2020 to 2040 with the use of a dynamic panel data model. A 41-country balanced panel data set that comprises of five-year interval data, between 1990 and 2015. In the second stage, we develop linear programming models to generate realistic and reasonable scenarios representing three probable future pathways to meet the econometrically estimated electricity demand. The scenarios we have designed are business-as-usual (BAU), which includes the nuclear power plant, minimize GHGs (minGHG), and maximize local resources (MaxLocal). The latter scenarios omit the possible completion of the nuclear power plant in the next ten to twelve years. The generated scenarios are compared in terms of investment requirements and CO₂e emissions. The model results of minGHG and MaxLocal both show that the share of renewable generation should reach around 65% to satisfy the projected demand by 2040. However, the difference in CO₂e emissions (Mton/TWh) between the two cases is enormous: 0.408 for MaxLocal vs. 0.180 for minGHG! Moreover, required annual investment under minGHG is USD 0.19 billion cheaper on average (per year), which corresponds to a 21-year cumulative difference of USD 3.99 billion in current dollars. Therefore, a secure low-carbon pathway with a lower investment requirement is possible for Türkiye without nuclear power or new coal plants, while also phasing-out the existing coal plants under a moderate transition plan with a minimum amount of stranded assets.