| The advent of micro-synchronous phasor measurement devices(D-PMUs)has made it possible to deploy state estimation systems in distribution networks.Compared with the traditional SCADA system,the state estimatio n system based on D-PMU measurement can quickly and accurately grasp the dynamic operating conditions of the power grid,support more efficient multi-party interaction,and effectively improve the measurable,observable and controllable level of the power grid.The new measurement equipment brings new estimation methods,but also brings many challenges that did not exist,such as multi-source data fusion,and the security of data during transmission.This paper,funded by the national key research and development plan “Research and Application of Wide-area Measurement and Control Technology for Distribution Network”(2017YFB0902900),studies a safe and stable state estimation system for distribution network,including five aspectes,i.e.multi-source data integration in the distribution network,D-PMU data attack and its countermeasure,false data injection attacks and its countermeasure,state estimation algorithm stability analysis and state estimation system development.Through the research of this subject,a relatively complete basic theory and key technologies have been formed,which laid the foundation for the follow-up research.The main innovations of the thesis are as follows:(1)The method of multi-source information fusion is studied,and a unified information model is proposed.The differences and solutions of IEC 61850 standard and CIM(IEC 61968-301)standard are analyzed regarding the system model and data format.The unified information model proposed is verified by the actual system in the demonstration area.The ASE 61850 Suite modeling management tool was used to model the network and equipment of a substation feeder.The power distribution SCADA system originally built on the CIM standard was integrated with the new system based on the IEC 61850 model.The merged XML file can make different system information interact,thus verifying the correctness of the proposed method.(2)The attacking theory of D-PMU network and data is studied.A wireless transmission network architecture based on cognitive radio technology(CR)and data encryption confusion algorithm is proposed.The proposed CR based network can flexibly utilize each spectrum gap for data transmission,increase the difficulty of data interception,and adopt random undefined Splepian window,making it difficult for attackers to utilize independent component analysis.(ICA)technology separates the D-PMU mixed data volume.At the same time,the security of the CR technology itself has been improved,thereby further improving the reliabi lity of the data.The simulation results prove the correctness of the method proposed in this chapter.(3)The theory and mode of false data injection attack are studied.A robust state estimation algorithm against false data injection attacks is proposed and mathematically verified.The method "dilutes" the bad data by generating "pseudo D-PMU measurement" to achieve the purpose of anti-FDIA,and the standard deviation of "pseudo-measurement" can be obtained by the error uncertainty propagation theory to determine the calculation radius.At the same time,in order to improve the speed of the algorithm,a sequence state estimation method based on variable measurement(CMBSSE)is proposed.The robustness and rapidity of the proposed method are verified by IEEE standard testbeds.(4)A condition number calculation and estimation method based on machine learning method is proposed.This method expands the limited sample data and improves the accuracy of the training result through iterative training of precisio n cirtical data.The output reveals the implicit relationship between the condition number with various types of measurements and measurement points.At the same time,two matrix decomposition methods for state estimation stability optimization are proposed,and the proposed methods are compared.The correctness of the method is verified by simulation.(5)Developed a state estimation system for the distribution network,focusing on the safety and stability of the system.The security and stability of the system are verified by tools such as the Information Model Manager(Kalki Software),D-PMU Data Simulator(PMU Simulator),and Data Simulator(Dynamic Simulator).Through the observation of the field operation results,it is found that the state estimation algorithm has very good estimation accuracy.In the absence of data attacks,the state estimation accuracy is 95% and the convergence is 97%.In the case of data attacks,the system state estimation accuracy can still reach more than 90%,and the convergence is higher than 95%.The state estimation result s can be displayed by means of one-line diagram or geographical wiring diagram.Based on the research of wide-area measurement and control technology of distribution network in the construction of "smart d istribution network",this paper proposes a unified information model suitable for distribution network data.At the same time,according to the characteristics of D-PMU data,the principle of network attack against D-PMU data is revealed,and the security of data transmission is enhanced by establishing a new cognitive wireless network.On this basis,a robust state estimation algorithm using "pseudo D-PMU" and a fast state estimation algorithm based on variable measurement are proposed.In this paper,the stability of the state estimation algorithm of distribution network is also studied.The influencing factors of the condition number of the gain matrix are analyzed.The optimization method of algorithm stability is proposed.Finally,according to the req uirements of the demonstration project,a safe and stable state estimation system suitable for distribution network was developed.The theoretical methods and system design proposed in this paper have certain reference value and significance for promoting the development of smart distribution network. |
PDF Full Text Request