TY  - JOUR
T1  - Solar energy potential assessment and investment profitability analysis: The case of North Macedonia
AU  - Kaya, Hakan
PY  - 2026
DA  - March
Y2  - 2026
DO  - 10.58559/ijes.1787421
JF  - International Journal of Energy Studies
JO  - Int J Energy Studies
PB  - Türkiye Enerji Stratejileri ve Politikaları Araştırma Merkezi (TESPAM)
WT  - DergiPark
SN  - 2717-7513
SP  - 43
EP  - 83
VL  - 11
IS  - 1
LA  - en
AB  - This study presents a novel integrated framework that combines meteorological data analysis, machine learning forecasting models, clustering techniques, and economic modeling to offer the first data-driven investment roadmap for solar energy in North Macedonia. High-accuracy solar radiation forecasts for 2025 were generated using the Gradient Boosting Regression model (R² = 0.953) using NASA POWER data for the period 2020–2024. Cities were grouped into clusters based on their climatological characteristics; cities such as Štip, Veles, and Kavadarci demonstrated the highest solar potential and economic efficiency. Economic analyses identified payback periods of 3–5 years and average ROI (Return on Investment) values ​​exceeding 24%. It was determined that increasing electricity prices linearly affected the ROI, reaching 33% with an increase in price to $0.12/kWh. The findings highlight the importance of a new integrated decision-support framework merging ML-based solar forecasting, spatial clustering, and dynamic economic modeling tailored for data-limited emerging markets such as North Macedonia
KW  - Economic feasibility
KW  - Investment analysis
KW  - Machine learning
KW  - North Macedonia
KW  - Solar energy
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UR  - https://doi.org/10.58559/ijes.1787421
L1  - https://dergipark.org.tr/tr/download/article-file/5257231
ER  -