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A Novel Reconstruction Approach to Elevator Energy Conservation Based on a DC Micro-Grid in High-Rise Buildings

Author

Listed:
  • Yongming Zhang

    (College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China)

  • Zhe Yan

    (College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China)

  • Feng Yuan

    (College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China)

  • Jiawei Yao

    (College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China)

  • Bao Ding

    (Harbin Institute of Technology, Harbin 150001, China)

Abstract

Elevators were reported to cause an important part of building energy consumption. In general, each elevator has two operation states: The load state and power regeneration state. During operation, it has the potential to save energy by using regeneration power efficiently. In existing research, a set of energy storage devices are installed for every elevator, which is highly costly. In this paper, an energy conservation approach for elevators based on a direct current (DC) micro-grid is proposed, which has better economy. Then, an innovative energy-efficient device for the elevator group is designed based on a supercapacitor with similar characteristics and lifetimes. In a high-rise building case study, the experimental test and field data collection show that the innovative approach could result in a high energy efficiency within 15.87–23.1% and 24.1–54.5%, respectively. It is expected that the proposed method and designed device could be employed practically, saving energy consumption for elevator reconstruction.

Suggested Citation

  • Yongming Zhang & Zhe Yan & Feng Yuan & Jiawei Yao & Bao Ding, 2018. "A Novel Reconstruction Approach to Elevator Energy Conservation Based on a DC Micro-Grid in High-Rise Buildings," Energies, MDPI, vol. 12(1), pages 1-17, December.
    • Handle: RePEc:gam:jeners:v:12:y:2018:i:1:p:33-:d:192704
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    References listed on IDEAS

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    1. Sergio Saponara, 2016. "Distributed Measuring System for Predictive Diagnosis of Uninterruptible Power Supplies in Safety-Critical Applications," Energies, MDPI, vol. 9(5), pages 1-18, April.
    2. Jiawei Yao & Yongming Zhang & Zhe Yan & Li Li, 2018. "A Group Approach of Smart Hybrid Poles with Renewable Energy, Street Lighting and EV Charging Based on DC Micro-Grid," Energies, MDPI, vol. 11(12), pages 1-17, December.
    3. Yongming Zhang & Zhe Yan & Li Li & Jiawei Yao, 2018. "A Hybrid Building Power Distribution System in Consideration of Supply and Demand-Side: A Short Overview and a Case Study," Energies, MDPI, vol. 11(11), pages 1-19, November.
    4. Otilia Elena Dragomir & Florin Dragomir & Veronica Stefan & Eugenia Minca, 2015. "Adaptive Neuro-Fuzzy Inference Systems as a Strategy for Predicting and Controling the Energy Produced from Renewable Sources," Energies, MDPI, vol. 8(11), pages 1-15, November.
    5. Hee-Jun Cha & Dong-Jun Won & Sang-Hyuk Kim & Il-Yop Chung & Byung-Moon Han, 2015. "Multi-Agent System-Based Microgrid Operation Strategy for Demand Response," Energies, MDPI, vol. 8(12), pages 1-15, December.
    6. Sundar Raj Thangavelu & Inam Ullah Nutkani & Chia Meng Hwee & Aung Myat & Ashwin Khambadkone, 2015. "Integrated Electrical and Thermal Grid Facility - Testing of Future Microgrid Technologies," Energies, MDPI, vol. 8(9), pages 1-24, September.
    7. Eleonora Riva Sanseverino & Maria Luisa Di Silvestre & Romina Badalamenti & Ninh Quang Nguyen & Josep Maria Guerrero & Lexuan Meng, 2015. "Optimal Power Flow in Islanded Microgrids Using a Simple Distributed Algorithm," Energies, MDPI, vol. 8(10), pages 1-22, October.
    8. Wei-Tzer Huang & Tsai-Hsiang Chen & Hong-Ting Chen & Jhih-Siang Yang & Kuo-Lung Lian & Yung-Ruei Chang & Yih-Der Lee & Yuan-Hsiang Ho, 2015. "A Two-stage Optimal Network Reconfiguration Approach for Minimizing Energy Loss of Distribution Networks Using Particle Swarm Optimization Algorithm," Energies, MDPI, vol. 8(12), pages 1-17, December.
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    Cited by:

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    2. Lemiao Qiu & Huifang Zhou & Zili Wang & Wenqian Lou & Shuyou Zhang & Lichun Zhang, 2020. "A Stepped-Segmentation Method for the High-Speed Theoretical Elevator Car Air Pressure Curve Adjustment," Energies, MDPI, vol. 13(10), pages 1-21, May.

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