HDMR在电网潮流概率评估与调控中的应用

Application of High Dimensional Model Representation in Probability Assessment and Regulation of Power Flow

高维模型表达(high dimensional model representation,HDMR)在描述系统输出量关于多输入量之间关系方面具有独特的性能,而电网潮流状态量与网络多个节点源流注入量间正好符合HDMR的相关属性。基于此,将HDMR应用于电网潮流概率评估与调控问题:通过典型代表性的样本构建关键支路上传输的功率与电源和负荷间的HDMR关系,并替换传统潮流计算方式承担潮流概率评估过程中大规模的潮流计算任务,以极大地提高关键支路潮流累积概率分布生成及其相关特征求取的效率;对关键支路潮流阻塞问题,设计了一种利用HDMR提供的全局灵敏度信息并兼顾节能减排性能指标的概率调控策略。算例表明,HDMR的应用可显著提高电网潮流概率评估的计算效率和关键支路潮流阻塞概率调控的性能。

High dimensional model representation （HDMR） possesses unique performance in describing the relationship between the output and the multiple inputs of a nonlinear system,and the relation between power state variables and multiple bus inputs of the power system just accords with the related property of HDMR.Based on this,HDMR is applied in probabilistic assessment and regulation of power flow,that is,the HDMR relation among the power transmitted in the key branch and power sources and loads is constructed by typical representative samples to replace large-scale power flow computation carried out by traditional power flow calculation modes undertaking the task of power flow probabilistic assessment,thus the generation of cumulative probability distribution of power flow in key branch and the efficiency to obtain its related property can be greatly improved.To solve the congestion of power flow in key branch,a probabilistic regulation strategy,which utilizes the global sensitivity information provided by HDMR and takes performance indices of energy conservation and emission reduction into account,is designed.Simulation results of IEEE New England 10-machine 39-bus system show that applying HDMR can evidently speed up the calculation of probabilistic assessment of power flow power system and enhance the regulation performance of power flow congestion.