Derivation of Monthly Operating Rules for Cascade Hydropower Stations Based on SVM

Abstract:

In order to promote the efficiency of actual hydropower system operation under limited inflow forecast, an Implicit Stochastic Optimization method using Support Vector Machine (SVM) theory is proposed in this paper to derive long-term optimal operating rules. By applying the model to the Jinsha-Yangtze river system which is the largest hydropower base in China, fitting performance of operating rules is explained and evaluated. System simulation results are given and compared to deterministic optimal operation. Power output processes comparison shows that the average annual system power generation in two scenarios are 395TWh and 392TWh, and the overall operation processes are in well accordance with explicable inconsistency, which proves the efficiency of SVM in operating rules derivation for hydropower stations.

• Periodical: Advanced Materials Research (Volumes 838-841)
• Pages: 1673-1676
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.838-841.1673
• Online since: November 2013
• Authors: Ting Zhou*, Chang Ming Ji, Bi Kui Zhao
• Keywords: Cascade Hydropower Stations, Operating Rule, Simulation, Support Vector Machine (SVM)

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