Research On Optimal Configuration And Detection Of Voltage Sag Monitoring Points

With the rapid growth of socio-economic development and continuous deployment of sensitive equipment,there are increasingly higher demands for power quality.Among accidents caused by power quality issues,the most common and harmful is voltage sag.To effectively suppress voltage sag problems and reduce economic losses,it is crucial to establish a monitoring network that can monitor real-time voltage sags at each node in the power system.The most direct way to construct this monitoring network is to install voltage sag monitoring devices at every node in the power system.However,due to the large size of the power system and numerous nodes involved,considering investment and data transmission issues,it is not feasible to install monitoring devices at all nodes.Therefore,limited nodes need to be selected for installing monitoring devices so that they can reflect voltage sag situations when any node fails in the system.To achieve complete observability of voltage dips in all nodes of the system,a BPSO algorithm was used to optimize the configuration of voltage dip monitoring points in the system.First,four voltage dip matrices were constructed using power system fault analysis methods for four types of short circuit faults.Then,based on concave analysis,node concave domain matrices were constructed to determine the observable range of monitoring points.Finally,with the constraint that voltage dips during any node short circuit fault must be completely observable and minimizing the number of monitoring points as the objective function,a BPSO algorithm was used for optimization.Through simulation calculations on IEEE-39 node test systems,optimized configurations for different threshold values and different types of short circuit faults were determined.In addition to installing a real-time monitoring network in the system,effective detection of voltage sag characteristic quantities is also an important solution for implementing voltage sag prevention and compensation.By building an IEEE-39 node system model using Simulink for practical application analysis,commonly used dq transformation method and αβtransformation method were mainly studied,as well as improvements made to the αβtransformation method by adding a derivative calculation algorithm.After applying these several detection methods,the improved algorithm detected more ideal voltage sag waveforms and could meet the real-time and accuracy requirements of actual systems.Finally,to verify the feasibility of the optimized configuration scheme mentioned earlier,this 39-node system model will be used with the improved αβ algorithm for simulation verification.Through extensive simulation analysis,significant effects on voltage sag monitoring have been demonstrated by this optimized configuration scheme.