Title :
Estimating the system costs of wind power forecast uncertainty
Author :
Cardell, J.B. ; Anderson, C.L.
Author_Institution :
Picker Eng. Program & Dept. of Comput. Sci., Smith Coll., Northampton, MA, USA
Abstract :
Uncertainty in forecasts of wind power generation raises concerns of integrating wind power into power system operations and electricity markets at acceptable costs. The analysis presented in this paper uses an optimal power flow (OPF) model in a Monte Carlo Simulation (MCS) framework to estimate the additional cost of power system operation with uncertain output from a wind farm. A base case dispatch is established along with alternate dispatches based upon a probability distribution of real time wind power generation. The cost of the uncertainty in wind power forecasts is then quantified in terms of the difference in production cost between the base case and the cost for system dispatch under scenarios drawn from the distribution of real time wind power generation. Using various regional load levels and ramp capabilities of other generators, the results from the OPF and MCS show that wind power forecast uncertainty for the test system can increase production cost between 2.5% and 11%.
Keywords :
Monte Carlo methods; costing; power generation planning; power markets; power system economics; wind power; Monte Carlo simulation framework; electricity markets; optimal power flow; power system operations; probability distribution; wind power forecast uncertainty; wind power generation; Costs; Economic forecasting; Power system analysis computing; Power system modeling; Power system simulation; Production systems; Uncertainty; Wind energy; Wind forecasting; Wind power generation; Monte Carlo simulation; Wind power integration;
Conference_Titel :
Power & Energy Society General Meeting, 2009. PES '09. IEEE
Conference_Location :
Calgary, AB
Print_ISBN :
978-1-4244-4241-6
DOI :
10.1109/PES.2009.5275882