TY - GEN
T1 - Estimation of Power system frequency response based on measured & simulated frequencies
AU - Nilsson, Martin
AU - Söder, Lennart
AU - Yuan, Zhao
N1 - Publisher Copyright: © 2016 IEEE.
PY - 2016/11/10
Y1 - 2016/11/10
N2 - Electrical Power systems are going through a transition of increasing penetration of Renewable Energy Sources (RES) and growing transmission capacity between Asynchronous Areas (TBAA). Maintaining a reliable power balance is essential but most new RES and TBAA are not delivering Primary Frequency Controlled Reserves (PFCR) and not enhancing power systems Frequency Response Characteristics β. The issue addressed within this paper is to estimate β in this context. Accurate estimation is important for power system modelling or Automatic Secondary Reserve (ASR) design. We propose a method to estimate Frequency Response Characteristics based on measured and simulated frequencies. In this paper, we propose an iterative optimization method to obtain high resolution data from low resolution measurement. Based on the high resolution data, β is estimated with a σ approach. Then, we use linear regression to estimate the normal Frequency Containment Reserves (FCR). The proposed methods are tested in a Nordic Synchronous Power System case. Results show that our methods can give accurate estimations of frequency response characteristics and FCR.
AB - Electrical Power systems are going through a transition of increasing penetration of Renewable Energy Sources (RES) and growing transmission capacity between Asynchronous Areas (TBAA). Maintaining a reliable power balance is essential but most new RES and TBAA are not delivering Primary Frequency Controlled Reserves (PFCR) and not enhancing power systems Frequency Response Characteristics β. The issue addressed within this paper is to estimate β in this context. Accurate estimation is important for power system modelling or Automatic Secondary Reserve (ASR) design. We propose a method to estimate Frequency Response Characteristics based on measured and simulated frequencies. In this paper, we propose an iterative optimization method to obtain high resolution data from low resolution measurement. Based on the high resolution data, β is estimated with a σ approach. Then, we use linear regression to estimate the normal Frequency Containment Reserves (FCR). The proposed methods are tested in a Nordic Synchronous Power System case. Results show that our methods can give accurate estimations of frequency response characteristics and FCR.
KW - Frequency Bias Factor
KW - Frequency Controlled Reserves
KW - Frequency Response Characteristic
KW - Nordic Power System
UR - https://www.scopus.com/pages/publications/85001764892
U2 - 10.1109/PESGM.2016.7741498
DO - 10.1109/PESGM.2016.7741498
M3 - Conference contribution
T3 - IEEE Power and Energy Society General Meeting
BT - 2016 IEEE Power and Energy Society General Meeting, PESGM 2016
PB - IEEE Computer Society
T2 - 2016 IEEE Power and Energy Society General Meeting, PESGM 2016
Y2 - 17 July 2016 through 21 July 2016
ER -