Parameters used for dynamic optimization of Turkey's energy supply system costs under carbon emission constraints

Published: 8 September 2020| Version 2 | DOI: 10.17632/5bfcggr9ty.2
Görkem Güngör


These parameters are used for exploring the development of Turkey's energy supply system under carbon emission constraints. The data represent coefficients of the objective function and dynamic constraints in IIASA's MESSAGE dynamic linear optimization model. Energy system costs include activity and capacity costs of energy conversion technologies. The externalities included in the optimization function include costs for filtering air pollutant SO2 and NOx emissions and increasing carbon tax starting from 2020. The time steps of the model starts from 2014 as base year and increases to 2050 with five year intervals in order to assess the climate mitigation strategies in the first and second commitment periods of the Paris Agreement. The energy scenarios are based on SSPs with "SSP3 - Regional Rivalry" selected as baseline scenario with "SSP2 - Middle of the Road" and "SSP1 - Taking the green road" as climate mitigation scenarios. Turkey's historical data for population and GDP with future projections for SSPs are taken from IIASA database. Uranium costs are taken from Optimistic Uranium Crustal models for SSPS and front-end costs from IAEA database with per kg uranium costs for extraction and conversion, per kg SWU for enrichment and per kg enriched uranium for fuel fabrication. Snow cover change for Eastern Turkey is taken as proxy for annual rate of change in hydropower potential from CCSM4 General Circulation Model results for Turkey. Monthly load data for solar, wind and hydropower are elaborated for most suitable locations in Turkey from NASA Langley Research Center POWER project database using RStudio statistical software. The costs of electricity generation technologies are taken from IIASA scenario database for GEA study. Average costs are used for SSP3 (GEA-Supply), SSP2 (GEA-Mixed) and SSP1 (GEA-Efficiency) with carbon prices for RCP scenarios taken from SSP database hosted by IIASA. Capital costs, fixed costs and conversion efficiencies of electricity conversion technologies are taken from IIASA scenario database for GEA study for Western European region. Process heat is supplied from CHP plant with back-pressure units using natural gas as fuel and heat extracted from coke production. Other technologies with defined capacities are oil refinery, electricity T&D and biodiesel generation. Electricity grid stability is represented by flexibility coefficients of technologies capable to provide ancillary services. Final energy demand is calculated using Kaya Identity based on energy sector assumptions for SSPs. Carbon emission factors from fossil fuels are based on Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. Revenues from atmospheric emissions are used for cumulative constraint with FITs for subsidizing solar, biomass and geothermal power plants as backstop technologies for carbon emission reduction.



Metu University


Energy Optimization Model