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Optimizing Allocation of Distributed Electric Heating for Large-Scale Access Distribution Considering the Influence of Power Quality

Author

Listed:
  • Wei Li

    (School of Electrical Engineering and Automation, Tianjin University of Technology, Tianjin 300384, China)

  • Mengjun Li

    (School of Electrical Engineering and Automation, Tianjin University of Technology, Tianjin 300384, China)

  • Ning Zhang

    (National Research Center for Rehabilitation AIDS, Beijing 100176, China)

  • Xuesong Zhou

    (School of Electrical Engineering and Automation, Tianjin University of Technology, Tianjin 300384, China)

  • Jiegui Zhou

    (China Railway Design Group Co. Ltd., Tianjin 300010, China)

  • Guanyu Song

    (Key Laboratory of Smart Grid of Education Ministry, Tianjin University, Tianjin 300072, China)

Abstract

In this paper, a dual-layer grid comprehensive resource optimizing allocation model is proposed, which considers power quality controlling and load optimization scheduling under large-scale application of distributed electric heating. The upper-layer planning aims to minimize the active power loss of the distribution network, the minimum voltage deviation, and the minimum investment cost of the power quality control device. The capacity configuration of the management device and the number and location of the commutation switch configuration were determined. The lower layer is load optimization scheduling, with the minimum number of action switches and the minimum three-phase imbalance as the planning goals, and the decision variable is the state of the commutation switch. By co-simulation through Matlab and OpenDSS, the improved particle swarm algorithm and genetic algorithm are used for multi-objective optimization and the solution. In this way, the capacity configuration of reactive power compensation and active filter, as well as the installation position and switch state of the commutation switch are optimized and managed. Finally, taking the rural low-voltage distribution network in the Tongzhou District as an example, simulations considering the variation in the distributed electric heating penetration rate in the range of 20–80% are carried out. The calculation example results show that the proposed algorithm is effective, can effectively improve the power factor, reduces the harmonic content of the distribution network and the three-phase unbalance, and significantly improves the distribution network voltage.

Suggested Citation

  • Wei Li & Mengjun Li & Ning Zhang & Xuesong Zhou & Jiegui Zhou & Guanyu Song, 2022. "Optimizing Allocation of Distributed Electric Heating for Large-Scale Access Distribution Considering the Influence of Power Quality," Energies, MDPI, vol. 15(10), pages 1-18, May.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:10:p:3587-:d:815180
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    References listed on IDEAS

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    1. Valeriya Tuzikova & Josef Tlusty & Zdenek Muller, 2018. "A Novel Power Losses Reduction Method Based on a Particle Swarm Optimization Algorithm Using STATCOM," Energies, MDPI, vol. 11(10), pages 1-15, October.
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    3. Luo, Lizi & Gu, Wei & Zhang, Xiao-Ping & Cao, Ge & Wang, Weijun & Zhu, Gang & You, Dingjun & Wu, Zhi, 2018. "Optimal siting and sizing of distributed generation in distribution systems with PV solar farm utilized as STATCOM (PV-STATCOM)," Applied Energy, Elsevier, vol. 210(C), pages 1092-1100.
    4. Samer Takriti & Benedikt Krasenbrink & Lilian S.-Y. Wu, 2000. "Incorporating Fuel Constraints and Electricity Spot Prices into the Stochastic Unit Commitment Problem," Operations Research, INFORMS, vol. 48(2), pages 268-280, April.
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