一种求解交直流互联电网分布式最优潮流的同步ADMM方法

对于具有多个调度中心的大规模多区域交直流互联电网,对最优潮流计算进行分布式求解更符合信息的保密性和安全性需求。通过将联络线复制同时放到相邻分区中和引入边界变量一致性约束的方法建立交直流互联电网分布式最优潮流模型,并提出了一种完全分布式的不需要任何协调中心的同步交替方向乘子法(Synchronous Alternating Direction Method of Multipliers,SADMM)求解最优潮流模型。对于交直流系统直流部分的网络分区,提出将换流站保留在各自区域中只将中间直流线路复制的直流联络线处理方法。SADMM通过对高斯赛德尔型ADMM(GS-ADMM)进行改进,将当前迭代得到的相邻区域边界节点电压值的加权平均作为下一次迭代的固定参考值,实现不同区域间的并行同步计算。并根据优化问题的特点,确定算法中惩罚因子的合理取值,以加快算法的收敛性。以某一实际大规模交直流互联电网和两个修改的IEEE交直流系统为例,通过与集中式最优潮流计算比较,验证了所提算法的正确有效性。

A synchronous ADMM algorithm for solving distributed optimal power flow of AC/DC interconnected power grid

For a large-scale multi-region AC/DC interconnected power grid with multiple dispatching centers, the distributed solution to optimal power flow calculation is more in line with the information privacy and security requirements. An AC/DC interconnected power grid distributed OPF model is established by duplicating the tie-lines into adjacent regions and introducing boundary consistency constraints, and a fully distributed algorithm called Synchronous Alternating Direction Method of Multipliers (SADMM) with no form of central controllers is proposed. With regard to network partitioning for DC tie-lines, convertor stations are maintained in their own regions and only the DC transmission lines are duplicated. The proposed SADMM is improved based on the Gauss-Seidel ADMM (GS-ADMM), by using the weighted average value of boundary variables of adjacent regions obtained from current iteration as the reference values of both regions for the next iteration, which realizes the parallel computation among different regions. Moreover, the value of penalty factor is rationally determined based on the characteristics of the optimal problem, and the convergence speed is accelerated. The algorithm is tested with an actual AC/DC interconnected power grid and two modified IEEE AC/DC systems, and by comparing with the results obtained from centralized algorithm, its correctness and effectiveness can be validated. This work is supported by National Key Basic Research Program of China (973 Program) (No. 2013CB228205) and Natural Science Foundation of Guangdong Province (No. 2015A030313233).