| Autor: |
Fleten, Kristine Klock, Aasgård, Ellen Krohn, Xing, Liyuan, Grøttum, Hanne Høie, Fleten, Stein-Erik, Gundersen, Odd Erik |
| Předmět: |
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| Zdroj: |
Computational Management Science; 11/16/2024, Vol. 21 Issue 2, p1-24, 24p |
| Abstrakt: |
Aneo is one of the first Nordic power companies to apply stochastic programming for day-ahead bidding of hydropower. This paper describes our experiences in implementing, testing, and operating a stochastic programming-based bidding method aimed at setting up an automated process for day-ahead bidding. The implementation process has faced challenges such as generating price scenarios for the optimization model, post-processing optimization results to create feasible and understandable bids, and technically integrating these into operational systems. Additionally, comparing the bids from the new stochastic-based method to the existing operator-determined bids has been challenging, which is crucial for building trust in new procedures. Our solution is a rolling horizon comparison, benchmarking the performance of the bidding methods over consecutive two-week periods. Our benchmarking results show that the stochastic method can replicate the current operator-determined bidding strategy. However, additional work is needed before we can fully automate the stochastic bidding setup, particularly in addressing inflow uncertainty and managing special constraints on our watercourses. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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