📄 Abstract
This manuscript presents a rigorous comparative evaluation of three methodological paradigms for autonomous generation dispatch in liberalized power markets. We investigate deterministic optimization under anticipated price trajectories, scenario-based stochastic programming, and a coherent risk measure framework employing Conditional Value-at-Risk (CVaR). The proposed formulation integrates price uncertainty via discrete scenario representation to optimize thermal unit dispatch while quantifying and constraining downside financial exposure. The analysis evaluates a 660 MW coal-fired unit across a 24-hour operational window, examining economic performance, dispatch trajectories, and risk-return profiles. Computational evidence indicates that the CVaR-embedded approach yields dispatch schedules that optimally reconcile expected profit maximization with tail-risk mitigation. The model is calibrated against the SIPAT-I thermal generating station within the Indian national grid, implemented in the General Algebraic Modeling System (GAMS) and resolved via the CPLEX mixed-integer solver, utilizing four price scenarios derived from historical market clearing prices of the Indian Energy Exchange (IEX).
🏷️ Keywords
📚 How to Cite:
K.Naresh, Dr. G.N.Srinivas , THERMAL POWER PLANT SELF-SCHEDULING: A COMPARATIVE ANALYSIS OF DETERMINISTIC, STOCHASTIC, AND CVaR MODELS , Volume 14 , Issue 6, June 2026, EPRA International Journal of Economic and Business Review(JEBR) , Pages: 58 - 62 , DOI: https://doi.org/10.36713/epra30607