Real-time reservoir operation using data mining techniques

Environmental Monitoring and Assessment
Omid Bozorg-HaddadHugo A Loáiciga

Abstract

The optimal operation of hydropower reservoirs is essential for the planning and efficient management of water resources and the production of hydroelectric energy. Various techniques such as the genetic algorithm (GA), artificial neural networks (ANN), support vector machine (SVM), and dynamic programming (DP) have been employed to calculate reservoir operation rules. This paper implements the data mining techniques SVM and ANN to calculate the optimal release rule of hydropower reservoirs under "forecasting" and "non-forecasting" scenarios. The employment of data mining techniques accounting for data uncertainty to calculate optimal hydropower reservoir operation is novel in the field of water resource systems analysis. The optimal operation of the Karoon 3 reservoir, Iran, serves as a test of the proposed methodology. The upstream streamflow, storage records, and several lagged variables are model inputs. Data obtained from solving the reservoir optimization problem with nonlinear programming (NLP) are applied to train (calibrate) the SVM, and ANN, SVM, and ANN are executed in the "non-forecasting" scenario based on all inputs along with their time-lagged variables. In contrast, current parameters are removed from the set of...Continue Reading

References

May 11, 2005·Ground Water·Tirusew AsefaMac McKee
Sep 6, 2011·Analytica Chimica Acta·Kunwar P SinghShikha Gupta

❮ Previous
Next ❯

Citations


❮ Previous
Next ❯

Related Concepts

Related Feeds

Bioinformatics in Biomedicine

Bioinformatics in biomedicine incorporates computer science, biology, chemistry, medicine, mathematics and statistics. Discover the latest research on bioinformatics in biomedicine here.