基于交替方向乘子法的输-配-天然气系统分布式优化调度

随着电力网络与天然气网络耦合程度的加深以及传统配电网向主动配电网的转变,传统输配电气分离下的优化调度无法充分利用各种资源的灵活控制能力,不能获得整体最优解.因此,考虑电气耦合下的输配气协同优化,提出一种输-配-天然气系统优化调度模型.此外,考虑到未来输电系统运营中心、配电系统运营中心与天然气系统运营中心之间的独立性,为了保护各运营中心的信息隐私,提出了一个基于交替方向乘子法的分布式求解框架求解所提模型.为了确保分布式求解算法的收敛性,利用二阶锥松弛方法将气网优化问题转化为凸优化问题.算例结果表明,考虑电气耦合的输配气协同优化能够充分利用主动配电网中的多能耦合资源和储能资源,促进可再生能源消纳,提升系统总体运行经济性.此外,所提分布式求解算法的精确性和收敛性也得到了验证.

Distributed Optimal Scheduling for Transmission-Distribution-Natural-Gas System Based on Alternating Direction Method of Multipliers

With the deepening of the coupling between the power grid and the natural-gas network, and the transformation from the traditional distribution network to the active distribution network, the optimal scheduling with the traditional separated transmission and distribution of electricity and natural-gas can not make full use of the flexible control ability of various resources, and can not obtain the overall optimal solution. Therefore, considering the coordinated optimization of transmission, distribution and natural-gas networks under the coupling of electricity and natural-gas, an optimal scheduling model of transmission-distribution-natural-gas system is proposed. In addition, considering the independence between the transmission system operator (TSO), distribution system operator (DSO) and natural-gas system operator (NGSO) in the future, a distributed solution framework based on the alternating direction method of multipliers is proposed to solve the proposed model, so as to protect the privacy of each operator. In order to ensure the convergence of the distributed solving algorithm, the second-order cone relaxation method is utilized to transform the optimization problem of gas network into a convex optimization problem. The case results show that the coordinated optimization of transmission, distribution and natural-gas networks under the coupling of electricity and natural-gas can make full use of the multi-energy coupling resources and energy storage resources in the active distribution network, promote the accommodation of the renewable energy, and improve the overall operation economy of the system. Besides, the accuracy and convergence of the proposed distributed solving algorithm are also verified.