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Distributed energy management of large-scale microgrids using predictive control

Ghazvini, H. R. B ; Sharif University of Technology | 2022

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  1. Type of Document: Article
  2. DOI: 10.1109/ICEE55646.2022.9827192
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2022
  4. Abstract:
  5. This paper studies the real-time energy management of large-scale residential households and standalone electric vehicles charging stations using a non-cooperative game based on consensus protocol. We consider a set of aggregators, each equipped with a processor, to minimize its own cost function by having access to the local estimation terms of neighboring aggregators. Since the cost function of each aggregator is affected by strategy of other aggregators through total generation cost, such interaction among competitive agents is modeled as a non-cooperative game. An idea based on model predictive control is utilized to deal with highly random behavior of users. In this paper, a time-of-use pricing tariff with less value for loyal users is proposed such that the convergence time remains unchanged. Finally, the effectiveness of the proposed iterative algorithm is assessed by a set of simulations. © 2022 IEEE
  6. Keywords:
  7. Aggregator ; Consensus Protocol ; Model predictive control ; Residential households ; Costs ; Energy management ; Game theory ; Housing ; Iterative methods ; Model predictive control ; Aggregator ; Consensus protocols ; Cost-function ; Distributed energies ; Large-scales ; Microgrid ; Model-predictive control ; Noncooperative game ; Predictive control ; Residential household ; Cost functions
  8. Source: 30th International Conference on Electrical Engineering, ICEE 2022, 17 May 2022 through 19 May 2022 ; 2022 , Pages 528-532 ; 9781665480871 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/9827192