Title :
Small Hydro Power Plants Energy Availability Modeling for Generation Reliability Evaluation
Author :
Borges, Carmen L T ; Pinto, Roberto J.
Author_Institution :
Fed. Univ. of Rio de Janeiro-Poli/COPPE, Rio de Janeiro
Abstract :
This paper presents a model for evaluating small hydro power plants (SHPP) generation availability that can be applied to generation systems reliability and to generation planning studies. The model considers the uncertainties of rivers inflows and generation units operation. The river inflow is modeled as a stationary stochastic process by a multiple states Markov chain and the generator unit by a two states Markov model. The large number of different inflow values is reduced by the application of the statistical clustering techniques K-means in two different approaches: inflow clustering and power clustering. The steady state probabilities of each power generation value of the SHPP are calculated by the solution of the stochastic system. The expected value of the annual power generation of the SHPP, the duration curve, and several reliability indices are then calculated in a more accurate way than conventional approaches, since the model considers both the river inflow variation and the generation unit operation. Results obtained with actual Brazilian rivers inflows used for SHPP generation are reported in the paper and demonstrate the accuracy and applicability of the presented method for reliability evaluation.
Keywords :
hydroelectric power stations; pattern clustering; power generation planning; power generation reliability; stochastic processes; Brazilian rivers; generation reliability evaluation; hydropower plants energy availability; multiple states Markov chain; power clustering; rivers inflow uncertainties; stationary stochastic process; statistical clustering techniques; Availability; Power generation; Power system modeling; Power system planning; Power system reliability; Probability; Rivers; Steady-state; Stochastic processes; Uncertainty; Energy availability; generation systems; inflow time series; reliability evaluation; small hydro power plants; statistical clustering technique;
Journal_Title :
Power Systems, IEEE Transactions on
DOI :
10.1109/TPWRS.2008.926713