research-article

A genetic algorithm for AC optimal transmission switching

Author:

Masood JabarnejadAuthors Info & Claims

GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference

Pages 973 - 981

https://doi.org/10.1145/3449639.3459269

Published: 26 June 2021 Publication History

Abstract

Optimal transmission switching (OTS) is a new practice in power systems and can improve the economics of electric power systems integrated with renewable resources such as wind. In OTS modeling binary decision variables are added to the optimal power flow (OPF) problem to represent on and off switching status of lines. This extension to alternative current optimal power flow (ACOPF) problem results in a mixed integer nonlinear program (MINLP) which is not guaranteed to be solved optimally by existing solution methods and also requires excessive computation times for large real systems. In this paper we develop a genetic algorithm (GA) for ACOPF based OTS problem. In our GA approach we benefit from the structure of power transmission network and develop a line scoring method and a graphical distance based local improvement technique to better search the solution space. We compare our proposed genetic algorithm with two greedy heuristics on test power systems with renewable resources of energy. The results show that our proposed approach finds more economic solutions especially in larger power systems.

References

[1]

Y. Bai, H. Zhong, Q. Xia, and C. Kang. 2017. A Two-Level Approach to AC Optimal Transmission Switching With an Accelerating Technique. IEEE Transactions on Power Systems 32, 2 (2017), 1616--1625.

[2]

Y. Bai, H. Zhong, Q. Xia, and Y. Wang. 2015. A conic programming approach to optimal transmission switching considering reactive power and voltage security. In 2015 IEEE Power Energy Society General Meeting. 1--5.

[3]

C. Barrows, S. Blumsack, and P. Hines. 2014. Correcting Optimal Transmission Switching for AC Power Flows. In 2014 47th Hawaii International Conference on System Sciences. 2374--2379.

[4]

D. Bienstock and G. MuÃśoz. 2015. Approximate method for AC transmission switching based on a simple relaxation for ACOPF problems. In 2015 IEEE Power Energy Society General Meeting. 1--5.

[5]

F. Capitanescu and L. Wehenkel. 2014. An AC OPF-based heuristic algorithm for optimal transmission switching. In 2014 Power Systems Computation Conference. 1--6.

[6]

C. Coffrin, H. L. Hijazi, K. Lehmann, and P. Van Hentenryck. 2014. Primal and dual bounds for Optimal Transmission Switching. In 2014 Power Systems Computation Conference. 1--8.

[7]

E.B. Fisher, R.P. O'Neill, and M.C. Ferris. 2008. Optimal Transmission Switching. Power Systems, IEEE Transactions on 23, 3 (aug. 2008), 1346--1355.

[8]

J.D. Fuller, R. Ramasra, and A. Cha. 2012. Fast Heuristics for Transmission-Line Switching. Power Systems, IEEE Transactions on 27, 3 (aug. 2012), 1377--1386.

[9]

K.W. Hedman, M.C. Ferris, R.P. O'Neill, E.B. Fisher, and S.S. Oren. 2010. Co-Optimization of Generation Unit Commitment and Transmission Switching With N-1 Reliability. Power Systems, IEEE Transactions on 25, 2 (may 2010), 1052--1063.

[10]

K.W. Hedman, R.P. O'Neill, E.B. Fisher, and S.S. Oren. 2008. Optimal Transmission Switching - Sensitivity Analysis and Extensions. Power Systems, IEEE Transactions on 23, 3 (aug. 2008), 1469--1479.

[11]

K.W. Hedman, R.P. O'Neill, E.B. Fisher, and S.S. Oren. 2011. Smart Flexible Justin-Time Transmission and Flowgate Bidding. Power Systems, IEEE Transactions on 26, 1 (feb. 2011), 93--102.

[12]

K.W. Hedman, S.S. Oren, and R.P. O'Neill. 2011. A review of transmission switching and network topology optimization. In Power and Energy Society General Meeting, 2011 IEEE. 1--7.

[13]

Masood Jabarnejad and Jorge Valenzuela. 2016. Optimal investment plan for dynamic thermal rating using benders decomposition. European Journal of Operational Research 248, 3 (2016), 917 -- 929.

[14]

R. A. Jabr. 2013. Optimization of AC Transmission System Planning. IEEE Transactions on Power Systems 28, 3 (2013), 2779--2787.

[15]

M. Khanabadi, H. Ghasemi, and M. Doostizadeh. 2013. Optimal Transmission Switching Considering Voltage Security and N-1 Contingency Analysis. IEEE Transactions on Power Systems 28, 1 (2013), 542--550.

[16]

A. Khodaei and M. Shahidehpour. 2010. Transmission Switching in Security-Constrained Unit Commitment. Power Systems, IEEE Transactions on 25, 4 (nov. 2010), 1937--1945.

[17]

A. Khodaei and M. Shahidehpour. 2012. Security-constrained transmission switching with voltage constraints. International Journal of Electrical Power & Energy Systems 35, 1 (2012), 74--82.

[18]

A. Khodaei, M. Shahidehpour, and S. Kamalinia. 2010. Transmission Switching in Expansion Planning. Power Systems, IEEE Transactions on 25, 3 (aug. 2010), 1722--1733.

[19]

B. Kocuk, S. S. Dey, and X. A. Sun. 2017. New Formulation and Strong MISOCP Relaxations for AC Optimal Transmission Switching Problem. IEEE Transactions on Power Systems 32, 6 (2017), 4161--4170.

[20]

L.L. Lai, J.T. Ma, R. Yokoyama, and M. Zhao. 1997. Improved genetic algorithms for optimal power flow under both normal and contingent operation states. International Journal of Electrical Power & Energy Systems 19, 5 (1997), 287--292.

[21]

Cong Liu, Jianhui Wang, and J. Ostrowski. 2012. Heuristic Prescreening Switchable Branches in Optimal Transmission Switching. Power Systems, IEEE Transactions on 27, 4 (nov. 2012), 2289--2290.

[22]

Cong Liu, Jianhui Wang, and J. Ostrowski. 2012. Static Switching Security in Multi-Period Transmission Switching. Power Systems, IEEE Transactions on 27, 4 (nov. 2012), 1850--1858.

[23]

Muhammad Numan, Donghan Feng, Farukh Abbas, Salman Habib, and Aazim Rasool. 2020. Mobilizing grid flexibility through optimal transmission switching for power systems with large-scale renewable integration. International Transactions on Electrical Energy Systems 30, 3 (2020), e12211.

[24]

Muhammad Numan, Donghan Feng, Farukh Abbas, Usama Rahman, and Waqas Ahmad Wattoo. 2020. Impact assessment of a co-optimized dynamic line rating and transmission switching topology on network expansion planning. International Transactions on Electrical Energy Systems 30, 8 (2020), e12457.

[25]

P. E. Onate Yumbla, J. M. Ramirez, and C. A. Coello Coello. 2008. Optimal Power Flow Subject to Security Constraints Solved With a Particle Swarm Optimizer. IEEE Transactions on Power Systems 23, 1 (2008), 33--40.

[26]

J. Ostrowski, Jianhui Wang, and Cong Liu. 2012. Exploiting Symmetry in Transmission Lines for Transmission Switching. Power Systems, IEEE Transactions on 27, 3 (2012), 1708--1709.

[27]

T. Potluri and K. W. Hedman. 2012. Impacts of topology control on the ACOPF. In 2012 IEEE Power and Energy Society General Meeting. 1--7.

[28]

G. Poyrazoglu and H. Oh. 2015. Optimal topology control with physical power flow constraints and N-1 contingency criterion. In 2015 IEEE Power Energy Society General Meeting. 1--1.

[29]

P.A. Ruiz, J.M. Foster, A. Rudkevich, and M.C. Caramanis. 2012. Tractable Transmission Topology Control Using Sensitivity Analysis. Power Systems, IEEE Transactions on 27, 3 (2012), 1550--1559.

[30]

M. Soroush and J. D. Fuller. 2014. Accuracies of Optimal Transmission Switching Heuristics Based on DCOPF and ACOPF. IEEE Transactions on Power Systems 29, 2 (2014), 924--932.

[31]

Yaser Tohidi, Mohammad Reza Hesamzadeh, Ross Baldick, and Darryl R. Biggar. 2017. Transmission network switching for reducing market power cost in generation sector: A Nash-equilibrium approach. Electric Power Systems Research 146 (2017), 71--79.

[32]

B. E. Turkay and R. I. Cabadag. 2013. Optimal power flow solution using particle swarm optimization algorithm. In Eurocon 2013. 1418--1424.

[33]

J.C. Villumsen and A.B. Philpott. 2012. Investment in electricity networks with transmission switching. European Journal of Operational Research 222, 2 (2012), 377--385.

[34]

J. Yuryevich and Kit Po Wong. 1999. Evolutionary programming based optimal power flow algorithm. IEEE Transactions on Power Systems 14, 4 (1999), 1245--1250.

[35]

R. D. Zimmerman and C. Murillo-Sanchez. [n. d.]. MATPOWER User's Manual [Online]. Available: https://matpower.org/. ([n. d.]).

Cited By

Zhang MWang LLiu JDeng XWu K(2024)Multi-Period Optimal Transmission Switching with Voltage Stability and Security Constraints by the Minimum Number of ActionsSustainability10.3390/su1618827216:18(8272)Online publication date: 23-Sep-2024
https://doi.org/10.3390/su16188272
Han THill D(2023)Learning-Based Topology Optimization of Power NetworksIEEE Transactions on Power Systems10.1109/TPWRS.2022.317008338:2(1366-1378)Online publication date: Mar-2023
https://doi.org/10.1109/TPWRS.2022.3170083

Index Terms

A genetic algorithm for AC optimal transmission switching
1. Applied computing
  1. Operations research
2. Hardware
  1. Power and energy
    1. Energy distribution
      1. Power networks

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cover image ACM Conferences

GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference

June 2021

1219 pages

ISBN:9781450383509

DOI:10.1145/3449639

Editor:
Francisco Chicano
University of Malaga
,
General Chair:
Krzysztof Krawiec
Poznan University of Technology

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SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation

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Published: 26 June 2021

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GECCO '21: Genetic and Evolutionary Computation Conference

July 10 - 14, 2021

Lille, France

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Cited By

Zhang MWang LLiu JDeng XWu K(2024)Multi-Period Optimal Transmission Switching with Voltage Stability and Security Constraints by the Minimum Number of ActionsSustainability10.3390/su1618827216:18(8272)Online publication date: 23-Sep-2024
https://doi.org/10.3390/su16188272
Han THill D(2023)Learning-Based Topology Optimization of Power NetworksIEEE Transactions on Power Systems10.1109/TPWRS.2022.317008338:2(1366-1378)Online publication date: Mar-2023
https://doi.org/10.1109/TPWRS.2022.3170083

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