Title :
A Novel Affine Arithmetic Method to Solve Optimal Power Flow Problems With Uncertainties
Author :
Pirnia, Mehrdad ; Canizares, Claudio A. ; Bhattacharya, Kankar ; Vaccaro, Alfredo
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Waterloo, Waterloo, ON, Canada
Abstract :
An affine arithmetic (AA) method is proposed in this paper to solve the optimal power flow (OPF) problem with uncertain generation sources. In the AA-based OPF problem, all the state and control variables are treated in affine form, comprising a center value and the corresponding noise magnitudes, to represent forecast, model error, and other sources of uncertainty without the need to assume a probability density function (pdf). The proposed AA-based OPF problem is used to determine the operating margins of the thermal generators in systems with uncertain wind and solar generation dispatch. The AA-based approach is benchmarked against Monte Carlo simulation (MCS) intervals in order to determine its effectiveness. The proposed technique is tested and demonstrated on the IEEE 30-bus system and also a real 1211-bus European system.
Keywords :
IEEE standards; Monte Carlo methods; affine transforms; busbars; load flow; power generation dispatch; solar power; wind power; 1211-bus European system; AA-based OPF problem; IEEE 30-bus system; MCS; Monte Carlo simulation; affine arithmetic method; control variable; model error; optimal power flow; pdf; probability density function; solar generation dispatch; thermal generator operating margin determination; uncertain generation source; wind generation dispatch; Chebyshev approximation; Load flow; Mathematical model; Power generation dispatch; Reactive power; Uncertainty; Affine arithmetic; generation uncertainty; interval analysis; optimal power flow;
Journal_Title :
Power Systems, IEEE Transactions on
DOI :
10.1109/TPWRS.2014.2316114
