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Development of a prediction-based scheduling control strategy with V2B mode for PV-building-EV integrated systems

Author

Listed:
  • Luo, Jianing
  • Yuan, Yanping
  • Joybari, Mahmood Mastani
  • Cao, Xiaoling

Abstract

Extending the energy boundary from the building-integrated photovoltaic to E-mobility is an effective alternative to further improve the integrated energy system performance. In this study, a new prediction-based scheduling control (PSC) strategy was developed considering vehicle-to-building mode for PV-building-EV integrated systems. The control strategies consisted of three components, model predictive control (MPC), simple operation mode, and schedule control. First, the MPC was based on the weather forecast, while the calculated daily renewable power generation and building energy consumption were used for mode selections. Second, the simple operation mode was based on system operation using conventional methods. Third, the developed scheduling control strategy was activated based on the periods of the day, involving different operating modes (e.g., V2B mode, renewable-to-building mode, etc.). Overall, the developed PSC can effectively improve energy performance and achieve cost savings. Validation tests were conducted for an office building, whose results showed higher renewable energy penetration and renewable power use efficiency at 9.56% and 30.48%, respectively. The levelized cost of energy (LCOE) values for building energy consumption and EV charging decreased to 0.4561 CNY/kWh and 0.6304 CNY/kWh, respectively. It indicated that the annual cost savings of building energy consumption and EV charging decreased by 16.5% and 42.7%, respectively.

Suggested Citation

  • Luo, Jianing & Yuan, Yanping & Joybari, Mahmood Mastani & Cao, Xiaoling, 2024. "Development of a prediction-based scheduling control strategy with V2B mode for PV-building-EV integrated systems," Renewable Energy, Elsevier, vol. 224(C).
  • Handle: RePEc:eee:renene:v:224:y:2024:i:c:s0960148124003021
    DOI: 10.1016/j.renene.2024.120237
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