A Fast-Algorithmic Probabilistic Evaluation on Regional Rate of Change of Frequency (RoCoF) for Operational Planning of High Renewable Penetrated Power Systems

Jiaxin Wen, Siqi Bu, Bowen Zhou, Qiyu Chen and Dongsheng Yang
Additional contact information
Jiaxin Wen: Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
Siqi Bu: Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
Bowen Zhou: College of Information Science and Engineering, Northeastern University, Shenyang 110819, China
Qiyu Chen: Power System Department, China Electric Power Research Institute, Haidian District, Beijing 100192, China
Dongsheng Yang: College of Information Science and Engineering, Northeastern University, Shenyang 110819, China

Energies, 2020, vol. 13, issue 11, 1-14

Abstract: The high rate of change of frequency (RoCoF) issue incurred by the integration of renewable energy sources (RESs) into a modern power system significantly threatens the grid security, and thus needs to be carefully examined in the operational planning. However, severe fluctuation of regional frequency responses concerned by system operators could be concealed by the conventional assessment based on aggregated system frequency response. Moreover, the occurrence probability of a high RoCoF issue is actually a very vital factor during the system planner’s decision-making. Therefore, a fast-algorithmic evaluation method is proposed to determine the probabilistic distribution of regional RoCoF for the operational planning of a RES penetrated power system. First, an analytical sensitivity (AS) that quantifies the relationship between the regional RoCoF and the stochastic output of the RES is derived based on the generator and network information. Then a linear sensitivity-based analytical method (LSM) is established to calculate the regional RoCoF and the corresponding probabilistic distribution, which takes much less computational time when comparing with the scenario-based simulation (SBS) and involves much less complicated calculation procedure when comparing with the cumulant-based method (CBM). The effectiveness and efficiency of the proposed method are verified in a modified 16-machine 5-area IEEE benchmark system by numerical SBS and analytical CBM.

Keywords: renewable energy sources (RESs); regional RoCoF; model-based operational planning; linear sensitivity-based method (LSM); cumulant-based method (CBM) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/1996-1073/13/11/2780/pdf (application/pdf)
https://www.mdpi.com/1996-1073/13/11/2780/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:13:y:2020:i:11:p:2780-:d:365738

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().