Title :
Modeling and simulation of the electricity generation system of Uruguay in 2015 with high penetration of wind power
Author :
Cornalino, E. ; Coppes, E. ; Chaer, R.
Author_Institution :
UTE, Montevideo, Uruguay
Abstract :
The system of electric power generation of Uruguay will verify significant changes in the near future. The main one will be the incorporation of a large amount of wind power. The stated goal is to reach 1200 MW of installed capacity by 2015. The expected demand for that year is about 1495 MW on average, with a peak of 2000 MW. The wind penetration then will be of 60% in capacity and 33% in energy. Uruguay will be among the countries with the largest share of renewables in its energy matrix. Wind farms will be distributed nationwide so part of the inherent variability of the wind power will be filtered by the non-simultaneity involving geographic dispersion. The rest of the variations must be absorbed by the regulating system resources. The purpose of this paper is to simulate how the system will be operated in 2015 with such a high share of wind power and evaluate if the resources available to compensate the variations in wind power are enough. For this purpose a stochastic model with Gaussian Space Correlations with Histogram was identified. This model identification was carried out using series of two year hourly measures of the wind speed in seven sites distributed over the country. This stochastic model was used to perform a simulation of operation of the system in 2015 using an integration time-step of one hour with the simulator SimSEE. In this simulation all power stations in Uruguay are represented. This includes: hydroelectric plants with their storage capacity and gas-oil, fuel-oil, bio-fuel and natural gas fired thermal units. The detail level used is similar to that used by the National Load Dispatch agency of Uruguay for conducting the weekly generation schedule plan. The results show that the resources available for filtering the wind power variations in the country are sufficient to allow operation of the system without problems. As expected, it is verified that most of the filtering work is done by the hydraulic system and rarely has to be handled b- the thermal system.
Keywords :
Gaussian processes; biofuel; electric power generation; hydroelectric generators; power engineering computing; power generation planning; thermal power stations; wind power plants; Gaussian space correlation; National Load Dispatch agency; SimSEE; Uruguay; biofuel thermal units; electricity generation system; filtering work; fuel-oil thermal units; gas-oil thermal units; hydraulic system; hydroelectric plants; natural gas fired thermal units; power 1200 MW; stochastic model; storage capacity; wind farms; wind power; Biological system modeling; Electronic mail; Hydroelectric power generation; PROM; Planning; Wind power generation;
Conference_Titel :
Transmission and Distribution: Latin America Conference and Exposition (T&D-LA), 2012 Sixth IEEE/PES
Conference_Location :
Montevideo
Print_ISBN :
978-1-4673-2672-8
DOI :
10.1109/TDC-LA.2012.6319143