4.6 Article Proceedings Paper

Day-ahead optimal scheduling model of transmission-distribution integrated electricity-gas systems based on convex optimization

Journal

ENERGY REPORTS
Volume 8, Issue -, Pages 759-767

Publisher

ELSEVIER
DOI: 10.1016/j.egyr.2022.05.163

Keywords

Transmission-distribution integrated electricity-gas systems; Day-ahead scheduling; Renewable energy; Convex relaxation

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This paper proposes a cooperative optimization scheduling model to enhance the operation flexibility and economy of transmission-distribution integrated electricity-gas systems (TD-IEGS). By considering the coordinated operation of multi-energy coupling devices and utilizing the second order cone relaxation method, the model can reduce total operation cost and promote wind power utilization.
With the deepening of the coupling degree between power network and natural gas network, the traditional independent optimal scheduling of transmission and distribution integrated electricity-gas systems cannot make full use of the flexible control ability of various resources and the complementary support capabilities between different energy systems. Therefore, this paper puts forward a cooperative optimization scheduling model of transmission-distribution integrated electricity-gas systems (TD-IEGS). The coordinated operation of multi-energy coupling devices including gas-fired units, combined heat and power (CHP) units and electric boilers (EB) are considered in this paper to enhance system operation flexibility and economy. The second order cone relaxation (SOCR) method is utilized to tackle the non-linear power and gas flow constraints, and the proposed mixed-integer non-linear programming co-optimization scheduling model is transformed into a mixed integer second order cone programming model (MISOCP). Case studies demonstrate that compared with the independent operation mode, the proposed co-optimization scheduling model of TD-IEGS can reduce total operation cost by about 6.7% under 50% wind power penetration level. Moreover, the co-optimization of TD-IEGS can promote wind power utilization especially in a high share of wind energy. (C) 2022 The Author(s). Published by Elsevier Ltd.

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