학술논문
Estimation of Regulation Reserve Requirement Based on Control Performance Standard
Document Type
Periodical
Author
Source
IEEE Transactions on Power Systems IEEE Trans. Power Syst. Power Systems, IEEE Transactions on. 33(2):1173-1183 Mar, 2018
Subject
Language
ISSN
0885-8950
1558-0679
1558-0679
Abstract
This paper proposes a method to estimate the real-time regulation reserve requirement based on the NERC Control Performance Standard (CPS). This method is constructed via three steps: first, a Multiple Linear Regression (MLR) model is applied to abstract the relationship between CPS and regulation reserve and other system conditions using training observations generated from a load frequency control model; second, a stepwise method with cross validation is used to select the most relevant features of MLR; and third, the regulation reserve requirement is computed by the MLR model as a function of the predicted system conditions and target CPS score. The recursive least square (RLS) method is used to update the model parameters in an online environment. Testing on a single area automatic generation control model with load and wind data from CAISO 33% Renewable Portfolio Standard scenario indicates the method outperforms methods used in the industry today.