An Optimization Method for Reducing Losses in Distribution Networks Based on Tabu Search Algorithm
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Keywords

Distribution network
Loss reduction measures
Economy
Optimization model
Tabu search algorithm

DOI

10.26689/jera.v9i2.10004

Submitted : 2025-03-25
Accepted : 2025-04-09
Published : 2025-04-24

Abstract

With the continuous growth of power demand and the diversification of power consumption structure, the loss of distribution network has gradually become the focus of attention. Given the problems of single loss reduction measure, lack of economy, and practicality in existing research, this paper proposes an optimization method of distribution network loss reduction based on tabu search algorithm and optimizes the combination and parameter configuration of loss reduction measure. The optimization model is developed with the goal of maximizing comprehensive benefits, incorporating both economic and environmental factors, and accounting for investment costs, including the loss of power reduction. Additionally, the model ensures that constraint conditions such as power flow equations, voltage deviations, and line transmission capacities are satisfied. The solution is obtained through a tabu search algorithm, which is well-suited for solving nonlinear problems with multiple constraints. Combined with the example of 10kV25 node construction, the simulation results show that the method can significantly reduce the network loss on the basis of ensuring the economy and environmental protection of the system, which provides a theoretical basis for distribution network planning.

References

Yang Y, 2018, Comprehensive Analysis and Research on Power Loss in Urban Medium and Low Voltage Distribution Network. Electric Times, 2018(9): 72–73.

Yan L U, Co H P, Ltd, 2015, Measures of Reducing Line Loss through the Optimization of Chengmai Power Grid Structure. China Electric Power (Technology Edition), 2015(1): 41–43.

Zhou R, Wang J, Hou X, Wang M, Qiu X, 2015, Phase Optimization Adjustment Method for Three-phase Feeder Loss Model. Journal of Electric Power Systems and Automation, 27(4): 1–6.

Wang X, 2018, Research on Economic Operation and Loss Reduction Measures of Distribution Network, thesis, Heilongjiang: Northeast Agricultural University, DOI:10.7666/d.Y3516823.

Li T, 2010, Research on Energy Saving and Loss Reduction of 10kV Distribution Network, thesis, South China University of Technology.

Wang Y, Zheng T, Shi Y, 2019, A Combined Optimization Model for Distribution Network Loss Reduction Considering Low-Carbon Benefits. Distributed Energy Resources, 4(1): 13–16.

Rouhi F, Effatnejad R, 2015, Unit Commitment in Power System by Combination of Dynamic Programming (DP), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Indian Journal of Science and Technology, 8(2): 134.

Wang H, Xiong X-G, Wu Y-W, 2002, Reactive Power Optimization of Power System Based on Improved Tabu Search Algorithm. Power Grid Technology, 26(1): 15–18.

Zhang P, Liu Y, 1999, Simplified Dynamic Programming Method for Voltage Control and Reactive Power Optimization of Distribution Systems. Journal of Electric Power Systems and Automation, 11(4): 49–54.

Ying L, Liu M, Deng L, Sun J, 2017, Review on Loss Reduction of Distribution Network. Power System Protection and Control, 45(19): 162–169.

Tang H, Wang X, Xie G, Feng M, 2019, Combinatorial Optimization Model of Distribution Network Loss Reduction Scheme Considering Low Carbon Benefit. Journal of Electric Power Systems and Automation, 32(2): 113–118.

]Golberg D E, 1989, Genetic Algorithms in Search, Optimization, and Machine Learning. Addison Wesley, 1989(102): 36.

Tungadio D H, Numbi B P, Siti M W, et al, 2015, Particle Swarm Optimization for Power System State Estimation. Neurocomputing, 148: 175–180.

Sun Y, Shen T, Liu C, Sun Z, Zhang Z, 2017, Loss Reduction Decision of Distribution Network Based on Grey Relational Degree Algorithm. Sichuan Electric Power Technology, 40(4): 24–2847.

HHe W, 2008, Reactive Power Optimization of Regional Power Network Based on Tabu Search Algorithm, thesis, Shaanxi: Xi’an University of Science and Technology, DOI:10.7666/d.y1322167.

Ren G, 2021, Research on Reactive Power Compensation Method of Distribution Network with Distributed Power Source. Electronic Technology and Software Engineering, 2021(19): 212–213.