Abstract

Abstract In medium/long-term reservoir operation, the hydropower output is calculated from k × q × h, where q is the power discharge, h is the water head, and k is the comprehensive hydropower coefficient. k indicates the conversion efficiency from water power to electricity, however, it is standard practice to use a constant k. We developed a novel method to derive the varying k based on observed big data. The operational frequencies of different units for time (multiple periods) and space (multiple units) were accounted based on the observed big data from each unit, and then weights were obtained. Finally, k was derived by integrating the efficiency curves (hill charts) of the different units with their weights. The Three Gorges Project, China, was selected for a case study. Results indicated that: (1) the varying k value can improve hydropower simulation accuracy, (2) simulations using 10-day intervals have a higher accuracy for hydropower calculation than daily and monthly scales, (3) the evaluation of hydropower plant benefits is sensitive to k, and there is potential for producing more hydropower. These findings are highly relevant to the operation of hydropower plants and to the evaluation of medium/long-term hydropower generation for a hydropower plant.

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