Maximizing energy production from hydropower dams using short-term weather forecasts

Shahryar Khalique Ahmad and Faisal Hossain

Renewable Energy, 2020, vol. 146, issue C, 1560-1577

Abstract: This study explores the maximization of hydropower generation by optimizing reservoir operations based on short-term inflow forecasts derived from publicly available numerical weather prediction (NWP) models. Forecast fields from the NWP model of Global Forecast System (GFS) were used to force the Variable Infiltration Capacity (VIC) hydrologic model to forecast reservoir inflow for 1–16 days lead time. The optimization of reservoir operations was performed based on the forecast of inflow. The concept was demonstrated for two dams in the United States. Results showed that a significantly greater amount additional hydroelectric energy benefit can be derived consistently than the traditional operations without optimization and weather forecasts. Goals of flood control and dam safety were also not compromised when exploring opportunities for hydropower maximization. An alternate data-based technique was also demonstrated to improve the forecasting skill and efficiency. The study clearly underscores the additional value of weather forecasts that are available publicly and globally from NWP models for any dam location for hydropower maximization. Given the on-going effort to coordinate strategies for sustainable energy production from renewable energy sources, it is timely that this concept be expanded further to current hydropower dam sites around the world.

Keywords: Hydropower; Maximization; Short-term weather forecasts; Reservoir operations optimization; Flood control (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:146:y:2020:i:c:p:1560-1577

DOI: 10.1016/j.renene.2019.07.126

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