Study of Scenario Analysis of the Electricity Market of Kazakhstan Using Renewable Energy Sources on the PyPSA Tool

Omirgaliyev R. Shauyenova A. Merlenkyzy N. Maulen A. Zhakiyev N.
November 2025 Multidisciplinary Digital Publishing Institute (MDPI)

Applied Sciences (Switzerland)
2025 #15 Issue 21

This study presents a scenario analysis of Kazakhstan’s electricity market using the PyPSA-KZ model, with a focus on the integration of renewable energy sources (RES). As Kazakhstan transitions towards a low-carbon economy, this study evaluates the technical and economic implications of increasing RES penetration under various scenarios, ranging from 10% to 60% RES shares, with projections targeted for the year 2030. The study simulates system behavior across scenarios and analyzes key indicators, including total system cost, electricity tariff, generation mix, thermal ramping, and CO₂ emissions. Results indicate that up to 30% RES integration is feasible without significant structural changes, delivering reduced system costs and emissions. However, scenarios beyond 30% reveal growing flexibility challenges, necessitating investment in grid modernization, energy storage, and flexible backup capacity. The model outcomes are benchmarked against the International Energy Agency’s 2030 carbon neutrality scenarios and show strong alignment, particularly at 45% RES share. Comparative insights are also drawn from international experiences in Denmark and China. This research demonstrates that the PyPSA-KZ model is a powerful tool for planning Kazakhstan’s energy transition and offers data-driven recommendations to support national energy security and climate goals.

energy system modeling , low-carbon transition , power system optimization , PyPSA-KZ , renewable integration , scenario-based planning

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School of Computer Engineering, Astana IT University, Astana, 010000, Kazakhstan
School of Artificial Intelligence and Data Science, Astana IT University, Astana, 010000, Kazakhstan
Davis Center for Russian and Eurasian Studies, Harvard University, Cambridge, 02138, MA, United States
School of Intelligent Systems, Astana IT University, Astana, 010000, Kazakhstan

School of Computer Engineering
School of Artificial Intelligence and Data Science
Davis Center for Russian and Eurasian Studies
School of Intelligent Systems

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