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A linear programming based heuristic algorithm for charge and discharge scheduling of electric vehicles in a building energy management system

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  • Umetani, Shunji
  • Fukushima, Yuta
  • Morita, Hiroshi

Abstract

Electric vehicles (EVs) are becoming an attractive alternative to gasoline vehicles owing to the increase of greenhouse gas emissions and gasoline prices. EVs are also expected to function as battery storages for stabilizing large fluctuations in the power grid through the vehicle-to-grid power system, which requires smart charge and discharge scheduling algorithms. In this paper, we develop a linear programming based heuristic algorithm on a time–space network model for charge and discharge scheduling of EVs. We also develop an improved two-stage heuristic algorithm to cope with uncertain demands and departure times of EVs, and evaluate the effect of the smart charge and discharge scheduling of EVs on a peak load reduction in a building energy management system.

Suggested Citation

  • Umetani, Shunji & Fukushima, Yuta & Morita, Hiroshi, 2017. "A linear programming based heuristic algorithm for charge and discharge scheduling of electric vehicles in a building energy management system," Omega, Elsevier, vol. 67(C), pages 115-122.
    • Handle: RePEc:eee:jomega:v:67:y:2017:i:c:p:115-122
    DOI: 10.1016/j.omega.2016.04.005
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    Cited by:

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    8. Vinicius Braga Ferreira da Costa & Gabriel Nasser Doyle de Doile & Gustavo Troiano & Bruno Henriques Dias & Benedito Donizeti Bonatto & Tiago Soares & Walmir de Freitas Filho, 2022. "Electricity Markets in the Context of Distributed Energy Resources and Demand Response Programs: Main Developments and Challenges Based on a Systematic Literature Review," Energies, MDPI, vol. 15(20), pages 1-43, October.
    9. Wang, Tian & Deng, Shiming, 2019. "Multi-Period energy procurement policies for smart-grid communities with deferrable demand and supplementary uncertain power supplies," Omega, Elsevier, vol. 89(C), pages 212-226.
    10. Zhou, Yuekuan & Cao, Sunliang & Hensen, Jan L.M. & Lund, Peter D., 2019. "Energy integration and interaction between buildings and vehicles: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    11. Fahad R. Albogamy & Ghulam Hafeez & Imran Khan & Sheraz Khan & Hend I. Alkhammash & Faheem Ali & Gul Rukh, 2021. "Efficient Energy Optimization Day-Ahead Energy Forecasting in Smart Grid Considering Demand Response and Microgrids," Sustainability, MDPI, vol. 13(20), pages 1-29, October.
    12. Jiao, Zihao & Ran, Lun & Zhang, Yanzi & Ren, Yaping, 2021. "Robust vehicle-to-grid power dispatching operations amid sociotechnical complexities," Applied Energy, Elsevier, vol. 281(C).
    13. Xia Cao & Xin Zhang & ZeYu Xing, 2024. "Exploring the formation mechanism of new energy vehicle industry-university-research innovation network: the role of structural, cognitive and relational social capital," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(6), pages 3045-3065, June.
    14. Subrata Mitra & Balram Avittathur, 2018. "Application of linear programming in optimizing the procurement and movement of coal for an Indian coal-fired power-generating company," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 45(3), pages 207-224, September.
    15. Han, Jing & Guo, Ju-E & Cai, Xun & Lv, Cheng & Lev, Benjamin, 2022. "An analysis on strategy evolution of research & development in cooperative innovation network of new energy vehicle within policy transition period," Omega, Elsevier, vol. 112(C).
    16. Jorge García Álvarez & Miguel Ángel González & Camino Rodríguez Vela & Ramiro Varela, 2018. "Electric Vehicle Charging Scheduling by an Enhanced Artificial Bee Colony Algorithm," Energies, MDPI, vol. 11(10), pages 1-19, October.
    17. Bargos, Fabiano Fernandes & Lamas, Wendell de Queiróz & Bilato, Gabriel Adam, 2018. "Computational tools and operational research for optimal design of co-generation systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 507-516.

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