基于配电网重构的固态变压器双层选址方法

A bi-level optimized location selection method for solid-state transformers based on distribution network reconfiguration

为了更好地发挥固态变压器(Solid-State Transformer,SST)减少网络损耗、提升电压质量的作用,提出了一种基于配电网重构的固态变压双层优化选址方法.首先,分析固态变压器的潮流调控原理和方式建立了固态变压器潮流计算模型.其次,将固态变压器选址与配电网重构相结合,综合考虑配网重构约束和固态变压器新增约束,以网损最小为目标实现固态变压器优化选址.针对含固态变压器的多维度非线性配电网重构问题,提出了一种步长自动调整的改进细菌觅食算法(Improved Bacterial Foraging Algorithm,IBFA)进行求解,以提高求解速度和寻优精度.最后,以西安10 kV真实配电网为例进行分析.结果表明:SST双层优化选址模型可以减少4.5%~30%网损,提高2%节点最小电压,改进算法提高10%寻优精度.

In order to better play the role of Solid-State Transformer(SST)in reducing network losses and improving voltage quality,a bi-level optimized location selection method of SST based on distribution network reconfiguration is proposed.First,the principles and methods of SST power flow control are analyzed,and an SST power flow calculation model is established.Secondly,with the goal of minimizing network loss,the SST location selection and distribution network reconstruction are combined to achieve SST optimized location selection,considering the reconfiguration constraints of distribution network and new constraints of SST.To solve the problem of multi-dimensional nonlinear distribution network reconstruction with SST,an Improved Bacterial Foraging Algorithm(IBFA)with automatic step length adjustment is proposed to improve the solution speed and optimal foraging accuracy.Finally,the 10 kV actual distribution network in Xi’an is used as an example to analyze.The results show that the SST bi-level optimized location selection model can reduce the network losses by 4.5%~30%,increase the minimum voltage of the node by 2%,and improve the optimal foraging accuracy of the algorithm by 10%.