A scenario-based framework for measuring time-varying generation costs in medium- and long-term electricity markets

Accurately measuring time-varying generation costs is essential for effective pricing and resource allocation in electricity markets. Conventional cost measures capture either long-term averages or short-run operating conditions, but fail to jointly reflect temporal variability and capacity cost recovery. This study proposes a scenario-based framework for measuring time-varying generation costs under China's time-division trading mechanism, integrating accounting-based capacity costs with market-driven operational and opportunity costs across different supply-demand conditions. Using 8,760 h of data from Province H, the model reveals substantial hourly and seasonal cost variation, with cost spikes concentrated in short-lived peak and shortage periods and persistently low costs during renewable-rich hours. A comparative case study in Province J confirms that the framework robustly captures cost dynamics under different load profiles, providing practical cost signals for time-differentiated pricing and contract design in medium- and long-term electricity markets.