Probabilistic power flow analysis based on arbitrary polynomial chaos expansion for networks with uncertain renewable sources

Abstract

© 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. Probabilistic power flow (PPF) analysis was applied to investigate the effects of uncertain renewable energy sources, that is, solar and wind power plants, on power system operations. The PPF analysis based on the general polynomial chaos (gPC) expansion technique requires that the probability density function (PDF) of each random parameter is known in order to select the appropriate basis polynomial set. Since information on the parameter's distribution may not be available, this paper presents an application of the arbitrary polynomial chaos (aPC) expansion technique to the PPF problem. In aPC, the basis polynomial sets can be constructed from the measured data of the uncertain parameters: the exact distribution is not necessary. To reduce the computation work for finding the aPC coefficients, the collocation technique is applied; a method for improving the computation burden has also been suggested. The proposed technique was implemented in MATLAB environment and tested with the modified IEEE 57-bus system. Numerical experimental results indicate that the proposed method can achieve good accuracy and uses less computation time compared with conventional PC-based methods. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.