4.8 Article

Optimal operation for integrated electricity and natural gas systems considering demand response uncertainties

期刊

APPLIED ENERGY
卷 323, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2022.119455

关键词

Integrated electricity and natural gas systems; Integrated demand response; Demand response uncertainties; Distributed coordinated optimization; Analytical target cascading (ATC)

资金

  1. National Key R&D Program of China [2016YFB0901900]
  2. National Natural Science Foundation of China [51877174]

向作者/读者索取更多资源

An optimal operation model for integrated electricity and natural gas systems considering demand response uncertainty is proposed in this study. The uncertainty of wind power is dealt with using chance-constrained, and the models of three demand response loads are established. A distributed optimization model is used, and the effectiveness and convergence of the method are verified through a case study.
The volatility of wind power and the uncertainty of demand response have brought greater challenges to the operation of integrated electricity and natural gas systems. Therefore, an optimal operation model considering comprehensive demand response uncertainty is proposed. First, chance-constrained is used to deal with the uncertainty of wind power. The uncertainty of three demand response loads that can be transferred, reduced, and replaced are modeled respectively. Secondly, considering that the two systems are different stakeholders, a distributed optimization model is established, the mixed-integer nonlinear model established by incremental linearization and second-order cone relaxation processing is further used, and the distributed optimization model is realized through target cascade (ATC). Finally, a case study of the integrated electricity and natural gas system composed of an IEEE 33-bus power system and 24-node natural gas system verifies that: 1) considering the demand response will reduce the system cost by 3.57%; 2) the necessity of considering the uncertainty of demand response; 3) the convergence of this method is better than ADMM method.

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