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Backwards square completion MPC solution for real‐time economic dispatch in power networks
Author(s) -
Zhang HaiTao,
Sun Weigao,
Chen Zhiyong,
Meng Haofei,
Chen Guanrong
Publication year - 2019
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2018.6304
Subject(s) - economic dispatch , control theory (sociology) , square (algebra) , power (physics) , computer science , mathematical optimization , electric power system , mathematics , control (management) , artificial intelligence , physics , geometry , quantum mechanics
The existing economic dispatch (ED) control structures in power systems are based on solving a quadratic optimisation problem, which can only guarantee the optimal steady‐state performance. In this study, the authors formulate the real‐time ED problem for the transient operation of power systems as a dynamic model predictive control (MPC) optimisation problem. A novel MPC solving method, named backwards square completion (BSC) is thereby proposed to solve it with guaranteed transient economic performance. Meanwhile, it satisfies the input and state security constraints. Conventional linear MPC algorithms routinely involve with inverse matrix calculation, which is computationally expensive and may result in singularity. By contrast, BSC algorithm replaces the inverse matrix calculation by recursive receding horizon optimisation problem solving, which significantly reduces the computational complexity in terms of the control horizon. The proposed BSC‐MPC solution for real‐time ED is applied to an IEEE 39‐bus benchmark power network system to show its effectiveness and efficiency.

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