ArticleiScience2026
A scenario-based framework for measuring time-varying generation costs in medium- and long-term electricity markets.
Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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3 authors.
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Abstract
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.
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