Akademik Veri Yönetim Sistemi
Energy Reports, cilt.15, 2026 (SCI-Expanded, Scopus)
This study proposes a multi-objective mixed-integer optimization model aimed at integrating renewable energy sources into long-term production planning. The model presents a decision support framework that simultaneously addresses the objectives of reducing total system costs, lowering CO2 emissions, and supporting social acceptability by locating power plants further away from city centers. During the solution process, a Pareto-optimal solution set was generated using the ɛ constraint method, and seven portfolio alternatives were comparatively evaluated for the Turkish electricity system for the period 2024–2050. The findings show that different trade-off profiles exist between cost, emissions, and spatial targets depending on the portfolio composition. In the Pareto solution set, total cost ranges from 1.3766×1012 to 2.9234×1012 $, while the total distance indicator to city centers ranges from 1.3925×108 to 6.5674×109 km. In terms of relative performance, the geothermal+biomass combination provides the highest cost reduction (1.31%) and CO2 reduction (0.008%) compared to the reference solution; the solution with the most significant spatial target improvement is the geothermal+wind combination, with a total distance increase of 3.08%. The geothermal+wind+biomass combination increases distance (by approximately 2.28%) but shows more limited gains in terms of cost reduction. The Pareto solutions obtained provide a quantitative basis for a comparative discussion of the relative performance of hybrid portfolios, under the assumptions considered and depending on policy priorities.