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Low-Voltage Distribution Network Loss-Reduction Method Based on Load-Timing Characteristics and Adjustment Capabilities

Author

Listed:
  • Cheng Huangfu

    (State Grid Jibei Electric Power Company Limited, Beijing 100054, China)

  • Erwei Wang

    (Hubei Key Laboratory of Power Equipment & System Security for Integrated Energy, Wuhan 430072, China
    School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China)

  • Ting Yi

    (School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China)

  • Liang Qin

    (Hubei Key Laboratory of Power Equipment & System Security for Integrated Energy, Wuhan 430072, China
    School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China)

Abstract

The primary contributors to elevated line losses in low-voltage distribution networks are three-phase load imbalances and variations in load peak–valley differentials. The conventional manual phase sequence adjustment fails to capitalize on the temporal characteristics of the load, and the proliferation of smart homes has opened up new scheduling possibilities for managing the load. Consequently, this paper introduces a loss-reduction method for low-voltage distribution networks that leverages load-timing characteristics and adjustment capabilities. This method combines dynamic and static methods to reduce energy consumption from different time scales. To commence, this paper introduced a hierarchical fuzzy C-means algorithm (H-FCM), taking into account the distance and similarity of load curves. Subsequently, a phase sequence adjustment method, grounded in load-timing characteristics, was developed. The typical user load curve, derived from the classification of user loads, serves as the foundation for constructing a long-term commutation model, therefore mitigating the impact of load fluctuations on artificial commutation. Following this, this paper addressed the interruptible and transferable characteristics of various smart homes. This paper proposed a multi-objective transferable load (TL) optimal timing task adjustment model and a peak-shaving control strategy specifically designed for maximum sustainable power reduction of temperature-controlled loads (TCL). These strategies aim to achieve real-time load adjustment, correct static commutation errors, and reduce peak-to-valley differences. Finally, a simulation verification model was established in MATLAB (R2022a). The results show that the proposed method mainly solves the problems of three-phase imbalance and large load peak–valley difference in low-voltage distribution networks and reduces the line loss of low-voltage distribution networks through manual commutation and load adjustment.

Suggested Citation

  • Cheng Huangfu & Erwei Wang & Ting Yi & Liang Qin, 2024. "Low-Voltage Distribution Network Loss-Reduction Method Based on Load-Timing Characteristics and Adjustment Capabilities," Energies, MDPI, vol. 17(5), pages 1-19, February.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:5:p:1115-:d:1346347
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    References listed on IDEAS

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    1. Youssef, Heba & Kamel, Salah & Hassan, Mohamed H. & Nasrat, Loai, 2023. "Optimizing energy consumption patterns of smart home using a developed elite evolutionary strategy artificial ecosystem optimization algorithm," Energy, Elsevier, vol. 278(C).
    Full references (including those not matched with items on IDEAS)

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