Title :
Generating capacity reliability assessment of the Itaipu hydroelectric plant via sequential Monte Carlo simulation
Author :
Gonzalez-Fernandez, Reinaldo A. ; Oviedo-Sanabria, Ricci E. ; Leite da Silva, Armando M.
Author_Institution :
Superintendency of Oper., Itaipu Binacional, Hernandarias, Paraguay
Abstract :
The Itaipu Dam is a well-known hydroelectric plant located at the Paraná River, in the border between Brazil and Paraguay. With an installed capacity of 14GW, Itaipu is currently the world´s largest electric energy generation plant and the second largest in terms of installed capacity, reaching in 2012 a total generation of 98.3TWh. This work proposes a probabilistic methodology based on sequential Monte Carlo simulation (MCS) to assess the generating capacity reliability of Itaipu. The main objective is to estimate reliability indices which can quantify the risks of not having sufficient available generation capacity to meet contractual and/or system demands. All deterministic and stochastic data regarding the Itaipu generating units are directly obtained from their operating history data base. Furthermore, many chronological aspects, such as scheduled maintenance and capacity fluctuation, can be easily included in the simulation model. Finally, by taking advantage of the sequential MCS framework, the proposed method can represent both Markovian and non-Markovian state transitions, obtain monthly indices, and also estimate the annualized reliability indices probability distributions. Case studies are presented and discussed in details.
Keywords :
Markov processes; Monte Carlo methods; hydroelectric power stations; power generation reliability; risk management; statistical distributions; Brazil; Itaipu dam; Itaipu generating units; Itaipu hydroelectric plant; Markovian state transitions; Paraguay; Paraná River; annualized reliability indices probability distribution estimation; capacity fluctuation; chronological aspects; contractual demands; deterministic data; electric energy generation plant; generating capacity reliability assessment; monthly indices; nonMarkovian state transitions; operating history data base; power 14 GW; probabilistic methodology; risk quantification; sequential MCS framework; sequential Monte Carlo simulation; stochastic data; system demands; Fluctuations; Indexes; Load modeling; Maintenance engineering; Power system reliability; Stochastic processes; Itaipu Binacional; generating capacity reliability; hydroelectric plants; renewable energy sources; risk analysis; sequential Monte Carlo simulation;
Conference_Titel :
Power Systems Computation Conference (PSCC), 2014
Conference_Location :
Wroclaw
DOI :
10.1109/PSCC.2014.7038436