Abstract
This paper presents an optimization-based method to detect the occurrence, estimate the magnitude, and identify the location of load changes in the power system. The proposed method relies on measurements of only frequency at the output of synchronous generators along with a reduced-order power system dynamical model that captures locational effects of load disturbances on generator frequency dynamics. These locational aspects are retained in the estimation model by incorporating linearized power-flow balance into differential equations that describe synchronous-generator dynamics. The sparsity structure of load-change disturbances is leveraged so that only a limited number of measurements are needed to estimate load changes. Furthermore, a convex relaxation of the problem ensures that it can be solved online in a computationally efficient manner. Time-domain simulations involving the Western Electricity Coordinating Council 9-bus test system demonstrate the accuracy of the proposed method.
Original language | English (US) |
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Title of host publication | GlobalSIP 2019 - 7th IEEE Global Conference on Signal and Information Processing, Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781728127231 |
DOIs | |
State | Published - Nov 2019 |
Externally published | Yes |
Event | 7th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2019 - Ottawa, Canada Duration: Nov 11 2019 → Nov 14 2019 |
Publication series
Name | GlobalSIP 2019 - 7th IEEE Global Conference on Signal and Information Processing, Proceedings |
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Conference
Conference | 7th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2019 |
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Country/Territory | Canada |
City | Ottawa |
Period | 11/11/19 → 11/14/19 |
Bibliographical note
Publisher Copyright:© 2019 IEEE.
Keywords
- Convex optimization
- Event detection
- Load change estimation