TY - JOUR

T1 - Order reduction in electrical power systems using singular perturbation in different coordinate systems

AU - Huisinga, Hauke Hendrik

AU - Hofmann, Lutz

N1 - Funding information: The authors would like to thank the Volkswagen Foundation for the financial support of the project AMSES.

PY - 2018/10/16

Y1 - 2018/10/16

N2 - Purpose: Efficient calculations of the transient behaviour after disturbances of large-scale power systems are complex because of, among other things, the non-linearity and the stiffness of the overall state equation system (SES). Because of the rising amount of flexible transmission system elements, there is an increasing need for reduced order models with a negligible loss of accuracy. With the Extended Nodal Approach and the application of the singular perturbation method, it is possible to reduce the order of the SES adapted to the respective setting of the desired tasks and accuracy requirements. Design/methodology/approach: Based on a differential-algebraic equation for the electric power system which is formulated with the Extended Nodal Approach, the automatic decomposition into reduced order models is shown in this paper. The paper investigates the effects of different coordinate systems for an automatic order reduction with the singular perturbation method, as well as a comparison of results calculated with the full and reduced order models. Findings: The eigenvalues of the full system are approximated sufficiently by the three subsystems. A simulation example demonstrates the good agreement between the reduced order models and the full model independent of the choice of the coordinate system. The decomposed subsystems in rotating coordinates have benefits as compared to those in static coordinates. Originality/value: The paper presents a systematic decomposition based only on a differential-algebraic equation system of the electric power system into three subsystems.

AB - Purpose: Efficient calculations of the transient behaviour after disturbances of large-scale power systems are complex because of, among other things, the non-linearity and the stiffness of the overall state equation system (SES). Because of the rising amount of flexible transmission system elements, there is an increasing need for reduced order models with a negligible loss of accuracy. With the Extended Nodal Approach and the application of the singular perturbation method, it is possible to reduce the order of the SES adapted to the respective setting of the desired tasks and accuracy requirements. Design/methodology/approach: Based on a differential-algebraic equation for the electric power system which is formulated with the Extended Nodal Approach, the automatic decomposition into reduced order models is shown in this paper. The paper investigates the effects of different coordinate systems for an automatic order reduction with the singular perturbation method, as well as a comparison of results calculated with the full and reduced order models. Findings: The eigenvalues of the full system are approximated sufficiently by the three subsystems. A simulation example demonstrates the good agreement between the reduced order models and the full model independent of the choice of the coordinate system. The decomposed subsystems in rotating coordinates have benefits as compared to those in static coordinates. Originality/value: The paper presents a systematic decomposition based only on a differential-algebraic equation system of the electric power system into three subsystems.

KW - Efficient simulation

KW - Electric power systems

KW - Extended nodal approach

KW - Singular perturbation method

UR - http://www.scopus.com/inward/record.url?scp=85052607031&partnerID=8YFLogxK

U2 - 10.1108/COMPEL-08-2017-0360

DO - 10.1108/COMPEL-08-2017-0360

M3 - Article

VL - 37

SP - 1525

EP - 1534

JO - COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering

JF - COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering

SN - 0332-1649

IS - 4

ER -