TY - GEN
T1 - Reliability constrained optimal design of distributed generators in power system under load and wind turbine generation uncertainty
AU - Chen, Zhetao
AU - Xi, Zhimin
N1 - Publisher Copyright:
Copyright © 2021 by ASME.
PY - 2021
Y1 - 2021
N2 - Power systems are designed to meet power demands of the communities with high reliability. Distributed generators (DGs) could play an essential role in improving the power system reliability and resilience. To date, influence of the uncertainty of the DGs to power system reliability has not been well addressed. Consequently, placement of the DGs considering reliability constraints may not be optimally conducted. This paper proposes reliability analysis and design of power systems under time-dependent load uncertainty and wind power generation uncertainty using an efficient uncertainty quantification (UQ) method, i.e., the eigenvector dimension reduction (EDR) method. Furthermore, binary particle swarm optimization (B-PSO) is proposed to address the optimal placement of DGs considering the reliability constraint. Two case studies, including an IEEE 14-bus power system and an IEEE 57-bus power system, are used to demonstrate the effectiveness of the proposed methodology.
AB - Power systems are designed to meet power demands of the communities with high reliability. Distributed generators (DGs) could play an essential role in improving the power system reliability and resilience. To date, influence of the uncertainty of the DGs to power system reliability has not been well addressed. Consequently, placement of the DGs considering reliability constraints may not be optimally conducted. This paper proposes reliability analysis and design of power systems under time-dependent load uncertainty and wind power generation uncertainty using an efficient uncertainty quantification (UQ) method, i.e., the eigenvector dimension reduction (EDR) method. Furthermore, binary particle swarm optimization (B-PSO) is proposed to address the optimal placement of DGs considering the reliability constraint. Two case studies, including an IEEE 14-bus power system and an IEEE 57-bus power system, are used to demonstrate the effectiveness of the proposed methodology.
KW - Binary particle swarm optimization
KW - Distributed generators
KW - Eigenvector dimension reduction
KW - Power generation uncertainty
KW - Power system
KW - Reliability analysis
UR - http://www.scopus.com/inward/record.url?scp=85119991909&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85119991909&partnerID=8YFLogxK
U2 - 10.1115/DETC2021-68199
DO - 10.1115/DETC2021-68199
M3 - Conference contribution
AN - SCOPUS:85119991909
T3 - Proceedings of the ASME Design Engineering Technical Conference
BT - 47th Design Automation Conference (DAC)
PB - American Society of Mechanical Engineers (ASME)
T2 - 47th Design Automation Conference, DAC 2021, Held as Part of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2021
Y2 - 17 August 2021 through 19 August 2021
ER -