摘要
分布式电源引入农村配电网后,网络结构发生改变,传统潮流算法将不再适用。基于农村配电网络拓扑结构特点,提出一种适用于含分布式电源的农村弱环配电网改进前推回代算法,算法建立了支路电流-节点电流关联矩阵;同时,将分布式电源以PQ、PV型节点引入农村配电网,对于P、V恒定型分布式电源,提出一种新的模型,利用新增虚拟节点和带有电抗的虚拟支路与该PV型节点相连,通过注入无功来维持电压为恒定值。通过33节点配电系统验证所提算法的正确性和有效性,并将分布式电源和环网对系统电压和有功损耗的影响进行了计算和比较分析。结果表明,该文提出的方法计算简单,具有良好的收敛性,而且分布式电源及环网对节点电压改善效果明显,其中PV型DG对电压提升效果最为突出。
The traditional power flow method is no longer applicable for rural power distribution systems since the distributed generation(DG)is introduced.According to the analysis of the network topological structure,an improved backward/forward sweep algorithm is proposed for weakly meshed(or radial)rural power distribution systems with DG.The method develops an incidence matrix?branch current-bus injection matrix,by using this matrix the solution to branch current,branch voltage and node voltage becomes very simple.Meanwhile,the mathematical models of DG connected to distribution systems are regarded as PQ and PV nodes.For PV type DG,this paper uses a virtual node and virtual branch with reactance which injects reactive power to the specified node to maintain the specified voltage value.The correctness and validity of the proposed algorithm is tested by using 33-bus systems.In addition,the impact of both weakly meshed and DG on voltage profile and system power losses is also investigated.The results show that the proposed algorithm can be adapted to deal with weakly meshed distribution systems.Simulation results also show that the increase in iterations is not significant with the increase in DG,while the number of iterations decreases with the increase in the loop in the proposed method,and the voltage profile of distribution networks is improved with DG or loops.For PV type DG,the voltage profile is better than the DG modeled as PQ node.However,the power loss is becoming bigger.
出处
《中国农村水利水电》
北大核心
2014年第12期152-156,共5页
China Rural Water and Hydropower
基金
国家科技支撑计划(2012BAJ26B01)
辽宁省自然科学基金(201202191)
辽宁省教育厅科研项目(L2013260)
关键词
分布式电源
弱环配电网
PV节点
关联矩阵
distributed generation
weakly meshed distribution systems
PV nodes
incidence matrix