Published December 2014 | Version v1
Journal article

Short-term forecasting model for aggregated regional hydropower generation

  • 1. FEUP, Faculdade Engenharia Universidade do Porto, Porto (Portugal)
  • 2. Electrical Engineering Department, University of Zaragoza, Zaragoza (Spain)
  • 3. Electrical Engineering Department, University of La Rioja, Logroño (Spain)

Description

Highlights: • Original short-term forecasting model for the hourly hydropower generation. • The use of NWP forecasts allows horizons of several days. • New variable to represent the capacity level for generating hydroelectric energy. • The proposed model significantly outperforms the persistence model. - Abstract: This paper presents an original short-term forecasting model of the hourly electric power production for aggregated regional hydropower generation. The inputs of the model are previously recorded values of the aggregated hourly production of hydropower plants and hourly water precipitation forecasts using Numerical Weather Prediction tools, as well as other hourly data (load demand and wind generation). This model is composed of three modules: the first one gives the prediction of the "monthly" hourly power production of the hydropower plants; the second module gives the prediction of hourly power deviation values, which are added to that obtained by the first module to achieve the final forecast of the hourly hydropower generation; the third module allows a periodic adjustment of the prediction of the first module to improve its BIAS error. The model has been applied successfully to the real-life case study of the short-term forecasting of the aggregated hydropower generation in Spain and Portugal (Iberian Peninsula Power System), achieving satisfactory results for the next-day forecasts. The model can be valuable for agents involved in electricity markets and useful for power system operations

Availability note (English)

Available from http://dx.doi.org/10.1016/j.enconman.2014.08.017

Additional details

Identifiers

DOI
10.1016/j.enconman.2014.08.017;
PII
S0196-8904(14)00741-9;

Publishing Information

Journal Title
Energy Conversion and Management
Journal Volume
88
Journal Page Range
p. 231-238
ISSN
0196-8904
CODEN
ECMADL

Optional Information

Copyright
Copyright (c) 2014 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.