Probabilistic microgrid energy management with interval predictions

Jiayu Cheng, Dongliang Duan, Xiang Cheng, Liuqing Yang, Shuguang Cui

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In this paper, we consider a probabilistic microgrid dispatch problem where the predictions of the load and the Renewable Energy Source (RES) generation are given in the form of intervals. A hybrid method combining scenario-selected optimization and reserve strategy using the Model Predictive Control (MPC) framework is proposed. Specifically, first of all, an appropriate scenario is selected by the optimizer at each optimization stage, and then the optimal scheduling and reservation of system capacity are determined based on the selected scenario and possible variations in the future as provided by the predictors. In addition, a new reserve strategy is introduced to adaptively maintain system reliability and respond to variations in the hierarchical microgrid control. Simulations are conducted to compare our proposed method with the existing robust method and the deterministic dispatch with perfect information. Results show that our proposed method significantly improves the system efficiency while maintaining system reliability.

Original languageEnglish (US)
Article number3116
JournalEnergies
Volume13
Issue number12
DOIs
StatePublished - Jun 2020
Externally publishedYes

Bibliographical note

Funding Information:
Acknowledgments: This work was supported in part by Key-Area Research and Development Program of Guangdong Province Project under Grant No. 2018B030338001, Natural Science Foundation of China under Grant NSFC-61629101, Shenzhen Fundamental Research Fund under Grant No. JCYJ20170411102217994, the National Science Foundation under Grant DMS-1923142, the Open Research Fund from Shenzhen Research Institute of Big Data under Grant 2019ORF01006, the National Key R&D Program of China under Grant No. 2018YFB1800800, and Guangdong Zhujiang Project under Grant No. 2017ZT07X152.

Funding Information:
This work was supported in part by Key-Area Research and Development Program of Guangdong Province Project under Grant No. 2018B030338001, Natural Science Foundation of China under Grant NSFC-61629101, Shenzhen Fundamental Research Fund under Grant No. JCYJ20170411102217994, the National Science Foundation under Grant DMS-1923142, the Open Research Fund from Shenzhen Research Institute of Big Data under Grant 2019ORF01006, the National Key R&D Program of China under Grant No. 2018YFB1800800, and Guangdong Zhujiang Project under Grant No. 2017ZT07X152.

Publisher Copyright:
© 2020 by the author.

Keywords

  • Interval predictions
  • Isolated microgrid system
  • Microgrid energy management
  • Model predictive control (MPC)
  • Probabilistic dispatch

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