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Dynamic Reactive Power Optimization (DRPO) is a large-scale, multi-period, and strongly coupled nonlinear mixed-integer programming problem that is difficult to solve directly. First, to handle discrete variables and switching operation constraints, DRPO is formulated as a nonlinear constrained two-objective optimization problem in this paper. The first objective is to minimize the real power loss and the Total Voltage Deviations (TVDs), and the second objective is to minimize incremental system loss. Then a Filter Collaborative State Transition Algorithm (FCSTA) is presented for solving DRPO problems. Two populations corresponding to two different objectives are employed. Moreover, the filter technique is utilized to deal with constraints. Finally, the effectiveness of the proposed method is demonstrated through the results obtained for a 24-hour test on Ward & Hale 6 bus, IEEE 14 bus, and IEEE 30 bus test power systems. To substantiate the effectiveness of the proposed algorithms, the obtained results are compared with different approaches in the literature.


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A New Filter Collaborative State Transition Algorithm for Two-Objective Dynamic Reactive Power Optimization

Show Author's information Hongli ZhangCong Wang( )Wenhui Fan
School of Electrical Engineering, Xinjiang University, Urumqi 830047, China.
Department of Automation, Tsinghua University, Beijing 100084, China.

Abstract

Dynamic Reactive Power Optimization (DRPO) is a large-scale, multi-period, and strongly coupled nonlinear mixed-integer programming problem that is difficult to solve directly. First, to handle discrete variables and switching operation constraints, DRPO is formulated as a nonlinear constrained two-objective optimization problem in this paper. The first objective is to minimize the real power loss and the Total Voltage Deviations (TVDs), and the second objective is to minimize incremental system loss. Then a Filter Collaborative State Transition Algorithm (FCSTA) is presented for solving DRPO problems. Two populations corresponding to two different objectives are employed. Moreover, the filter technique is utilized to deal with constraints. Finally, the effectiveness of the proposed method is demonstrated through the results obtained for a 24-hour test on Ward & Hale 6 bus, IEEE 14 bus, and IEEE 30 bus test power systems. To substantiate the effectiveness of the proposed algorithms, the obtained results are compared with different approaches in the literature.

Keywords: dynamic reactive power optimization, filter collaborative state transition algorithm, Ward & Hale 6 bus, IEEE 14 bus, IEEE 30 bus

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Publication history

Received: 10 April 2017
Revised: 24 May 2017
Accepted: 25 May 2017
Published: 08 November 2018
Issue date: February 2019

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© The author(s) 2019

Acknowledgements

The work was supported by the National Natural Science Foundation of China (Nos. 51767022 and 51575469).

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