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Multidispatch for microgrid including renewable energy and electric vehicles with robust optimization algorithm

  • Ruifeng Shi
  • , Penghui Zhang
  • , Jie Zhang
  • , Li Niu*
  • , Xiaoting Han
  • *Corresponding author for this work
  • North China Electric Power University
  • China Institute of Energy and Transportation Integrated Development
  • School of Information Resource Management

Research output: Contribution to journalArticlepeer-review

Abstract

With the deterioration of the environment and the depletion of fossil fuel energy, renewable energy has attracted worldwide attention because of its continuous availability from nature. Despite this continuous availability, the uncertainty of intermittent power is a problem for grid dispatching. This paper reports on a study of the scheduling and optimization of microgrid systems for photovoltaic (PV) power and electric vehicles (EVs). We propose a mathematical model to address the uncertainty of PV output and EV charging behavior, and model scheduling optimization that minimizes the economic and environmental cost of a microgrid system. A semi-infinite dual optimization model is then used to deal with the uncertain variables, which can be solved with a robust optimization algorithm. A numerical case study shows that the security and stability of the solution obtained by robust optimization outperformed that of stochastic optimization.

Original languageEnglish
Article number2813
JournalEnergies
Volume13
Issue number11
DOIs
StatePublished - Jun 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Electric vehicle
  • Microgrid
  • Photovoltaic
  • Robust optimization
  • Stochastic optimization

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