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电–气互联系统的气电解耦分布式多目标优化调度
引用本文:郑宝敏,余涛,瞿凯平,李富盛.电–气互联系统的气电解耦分布式多目标优化调度[J].控制理论与应用,2019,36(3):492-503.
作者姓名:郑宝敏  余涛  瞿凯平  李富盛
作者单位:华南理工大学,华南理工大学,华南理工大学,华南理工大学
基金项目:国家自然科学基金(51477055, 51777078)
摘    要:本文基于能源互联网背景建立了一种计及供能成本、碳排放量和净负荷曲线平滑度的电–气互联系统多目标优化模型,并采用线性化方法将非线性优化模型转化为混合整数线性规划模型.同时,为了求解该模型,实现各能源的协同互补利用,提高能源的利用率,本文在保障各能源网络分散自治权的基础上提出一种基于气电解耦的分布式多目标优化算法,以气电解耦优化的方式实现电、气系统的分散自治.所提算法将原系统的多目标优化问题分解为电网和气网的子优化问题,并采用独立的优化器完成子问题的求解.电网和气网仅需交换少量边界变量以及虚拟目标因子分别进行全局调整即可获得多目标解.最后,本文根据修改的IEEE 39节点电力网络和比利时20节点天然气网络搭建模型并进行仿真分析,结果验证:所提算法能够完成电–气互联系统的气电解耦并实现多目标并行求解,从而提高系统信息私密性、实现各能源网络的分散自治.

关 键 词:气电解耦  分布式多目标  高私密性  电-气互联系统  分散自治
收稿时间:2018/9/7 0:00:00
修稿时间:2019/2/26 0:00:00

Distributed multi-objective optimization for scheduling of integrated electric and gas system based on electric and gas network decoupling
ZHENG Bao-min,YU Tao,KU Kai-ping and LI Fu-sheng.Distributed multi-objective optimization for scheduling of integrated electric and gas system based on electric and gas network decoupling[J].Control Theory & Applications,2019,36(3):492-503.
Authors:ZHENG Bao-min  YU Tao  KU Kai-ping and LI Fu-sheng
Affiliation:South China University of Technology,South China University of Technology,South China University of Technology,South China University of Technology
Abstract:With the background of energy internet, in this paper a multi-objective optimization model of integrated electric and gas system is established, 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.
Keywords:Decoupling of electric and gas network  distributed multi-objective  high privacy  integrated electric and gas system  distributed autonomy
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