The impact of hydroclimate-driven periodic runoff on hydropower production and management

Abstract

Abstract This study evaluates the impact of hydroclimate-driven periodic runoff on hydropower operations and production, with a focus on how the forecasted biennial periodicity of runoff time series could affect the efficiency of hydropower generation. Hydrologic stochastic processes are utilized to forecast long-term runoff, and seven hydroclimate scenarios are developed to be input into a production management model, allowing for an analysis of how periodic hydroclimate variations influence hydropower management and output. The results reveal that the biennial alternation between wet and dry years is a key factor affecting hydropower operations in the Dalälven River Basin. Notable differences between wet- and dry-year scenarios were observed in terms of power efficiency, production output, and forecasting accuracy. Operating hydropower systems based on dry-year runoff forecasts in wet years results in a 1.63% decrease in production efficiency and a reduction of 9,104 MWh in power generation. Conversely, applying wet-year forecasts in dry years slightly boosts production efficiency by 0.31% and increases power generation by 7,832 MWh. Scenarios that adhere to biennial periodicity offer the highest forecasting accuracy, particularly when applying dry-year forecasts in dry years in winter and spring, which produce the most precise predictions. In contrast, using dry-year forecasts in wet years results in the lowest forecasting accuracy.

Keywords

• Biennial periodicity
• Stochastic forecasting
• Scenarios
• Optimisation of hydropower
• Wet-year
• Dry-year