New Type Power System and the Integrated Energy

Robust Optimal Scheduling of Micro Energy Grid Considering Multi-Interval Uncertainty Set of Source-Load and Integrated Demand Response

  • MI Yang ,
  • FU Qixin ,
  • ZHAO Haihui ,
  • MA Siyuan ,
  • WANG Yufei
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  • College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China

Received date: 2023-01-19

  Revised date: 2023-03-11

  Accepted date: 2023-05-04

  Online published: 2023-05-24

Abstract

Aiming at the uncertainty of the source and load in micro energy grid, a robust optimal scheduling model considering multi-interval uncertainty set of source-load and integrated demand response is proposed. First, considering the uncertainty of wind power, photovoltaic output and electric, and thermal and cooling loads in the micro energy grid, a multi-interval uncertainty set of source-load is established. Then, in order to fully tap the potential of load side dispatching, an integrated demand response model is established, which includes reducible electric load, transferable electric load, flexible cooling, heating load, and replaceable load, based on which, the uncertainty of integrated demand response is considered. Afterwards, with the lowest dispatching cost of micro energy grid as the objective function, a two-stage robust optimal scheduling model of micro energy network is constructed, which considers the multi-interval uncertainty set of source load and the integrated demand response. The model is solved by the column and constraint generation algorithm, the strong duality theory, and the large M method. Finally, the rationality and effectiveness of the proposed model are verified through the analysis of numerical examples.

Cite this article

MI Yang , FU Qixin , ZHAO Haihui , MA Siyuan , WANG Yufei . Robust Optimal Scheduling of Micro Energy Grid Considering Multi-Interval Uncertainty Set of Source-Load and Integrated Demand Response[J]. Journal of Shanghai Jiaotong University, 2024 , 58(9) : 1323 -1333 . DOI: 10.16183/j.cnki.jsjtu.2023.022

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