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

Abstract

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.

Keywords

• Transmission–distribution integrated electricity–gas​ systems
• Day-ahead scheduling
• Renewable energy
• Convex relaxation