Multiple Linear Regression Based Disturbance Magnitude Estimations for Bulk Power Systems

Conference · Wed Aug 01 00:00:00 EDT 2018 · IEEE Power & Energy Society General Meeting (Online)

DOI:https://doi.org/10.1109/PESGM.2018.8585894· OSTI ID:1564159

Wu, Ling ^[1]; You, Shutang ^[2]; Dong, Jiaojiao ^[2]; Liu, Yilu ^[2]; Bilke, Terry ^[3]

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1. University of Tennessee (UT)
2. ORNL
3. Midcontinent ISO

Sudden trips of generation or large system load threaten bulk power systems (BPSs) secure and reliable operations. With the increasing deployment of Phasor Measurements Units (PMUs), system operators are thrilled to receive instant notifications of sudden disturbances and be aware of where, when, and what type of disturbances the system is experiencing. The amount of power imbalance is one of the fundamental information of the interests of both system operators and academic researchers. The PMU-based applications estimate the magnitude by interpreting the dynamic frequency responses immediately after a disturbance occurrence. However, the accuracy of the traditional method is unsatisfying because it oversimplifies the relation between the imbalance magnitude and the frequency response. This paper proposes to estimate the magnitudes of power imbalances based on multiple linear regression. It considers several other system and environmental factors and identifies those factors strongly associated with the disturbance magnitude. The approach is applied to actual generation trip events happened in two of the main power grids in North America. Compared with the traditional method, the proposed approach demonstrates improved accuracy.

• Research Organization: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1564159
• Journal Information: IEEE Power & Energy Society General Meeting (Online), Vol. 2018; Conference: 2018 IEEE Power & Energy Society General Meeting (IEEE PESGM 2018), Portland, OR (United States), 5-10 Aug 2018; ISSN 1944-9933
• Publisher: IEEE
• Country of Publication: United States
• Language: English