基于局域重加权的智能配电网多源分布式协调优化算法

为了实现大量间歇式新能源的充分消纳,提出了一种含高密度分布式电源的智能配电网有功和无功资源的区域分布式协调优化算法。该方法首先建立多时间段线性锥最优潮流模型,其次利用辅助变量增广Lagrangian乘子法分裂节点以实现各区域子系统潮流的空间解耦,最后提出了基于局域重加权Lagrangian的分布式优化算法,实施全网有功和无功资源的协调优化。算法上,各区域子系统无需全局协调可独立并行迭代优化,通过邻域子系统间少量的部分信息交互达到全网优化。该算法降低了通信复杂度,最大限度地保留了各子系统的独立性。算例验证结果表明,所提算法计算效率较高且收敛特性良好。

Multi-source Distributed Optimization Strategy for Smart Distribution Systems Based on Local Reweighted Method

In order to maximize the utilization of large-scale intermittent renewable energy, this paper proposes an area-distributed strategy for active and reactive power optimization in the smart distribution system with a large number of distributed generators. Firstly, the linear conic programming of the multi-period optimal power flow is developed. Then, some ancillary variables at the junction bus are introduced to decompose the distribution system into several separate subsystems. Moreover, the distributed optimization algorithm based on the local reweighted augmented Lagrangian method is proposed to realize the active and reactive power optimization in the whole network. Each subsystem only exchanges partial messages with its neighbors and solves the individual sub-optimization problem by itself in fully distributed manner without global coordinators. Communication complexity is reduced by the algorithm, and the independence of each subsystem is retained as much as possible. The simulation results show that the proposed strategy is of high calculating efficiency and good performance on convergence. This work is supported by National Natural Science Foundation of China(No. 51377142)and Zhejiang Provincial Natural Science Foundation of China(No. LQ15F030001).