This paper proposes an optimal strategy for regulating active-power flows in electric power systems based on sparsity-promoting linear-quadratic-Gaussian (LQG) control. The proposed method relies on the mapping of nodal active- and reactive-power injections to line flows, which are obtained via a measurement-based approach. Building on this, we outline a combined sparsity-promoting linear-quadratic regulator and Kalman-filter design. The optimal controller sparsity is identified using the alternating direction method of multipliers, which strikes a balance between feedback controller sparsity and the closed-loop dynamic performance. With this, we optimally dispatch generators and controllable loads to achieve desired line flows while ensuring zero steady-state frequency offset. We demonstrate the utility of the proposed LQG controller via a representative congestion-management application deployed on the New England 10-machine 39-bus test system.
Bibliographical noteFunding Information:
Manuscript received September 20, 2017; revised January 15, 2018; accepted February 5, 2018. Date of publication February 21, 2018; date of current version August 22, 2018. This work was supported by the Natural Sciences and Engineering Research Council of Canada under Grant RGPIN-2016-04271 and Grant 514710-17. The work of S. V. Dhople was supported in part by the National Science Foundation under the CAREER Award 1453921. Paper no. TPWRS-01455-2017. (Corresponding author: Yu Christine Chen.) A. Al-Digs and Y. C. Chen are with the Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, BC V6T 1Z2, Canada (e-mail: firstname.lastname@example.org; email@example.com).
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- Alternating direction method of multipliers (ADMM)
- injection shift factors
- line-flow control
- linear-quadratic-Gaussian control
- sparsity-promoting control