Distributed multi-objective optimization for scheduling of integrated electric and gas system based on electric and gas network decoupling

With the background of energy internet, this paper establishes a multi-objective optimization model of integrated electric and gas system, where three objectives, e.g., the cost of energy supply, carbon emission and the smoothness of load curve, are taken into account and then an incremental piecewise linearization method is adopted to transform the nonlinear optimization model into a mixed integer linear programming model. To promote coordinated, complementary and effective use of various energy sources on the basis of disparate autonomy of each energy network, a decentralized multi-objective optimization method with decoupling between electricity and gas network is proposed, where the original multi-objective optimization problem is decomposed into two sub-problems of power grid and gas network, following by two independent optimizers to solve the sub-problems. Within each sub region, an independent optimizer is used to optimize its own sub problem using only boundary variables and virtual objective coefficients from the other interconnected region, which can be utilized for the global regulation. Finally, connecting the modified IEEE 39-node electric network and the Belgian 20-node gas network to construct a model for simulation analysis, and compare results of the proposed algorithm with that of the centralized algorithm. The simulation results verify that the proposed algorithm can accurately handle the decoupling and multi-objective parallelizing optimization of the integrated electric and gas system and achieve decentralized autonomy of energy networks, which is quite useful and valuable for improvement of system information privacy. © 2019, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.