A multi-area distributed state estimation method of power system based on pmu measurement

Abstract

The invention discloses an electric system multi-domain distributed state estimation method based on PMU measurement. Firstly, a linear measurement model is assumed to expand partitions in a subdomain method, expanded subdomains contain boundary buses of adjacent domains, the fact that the quantity of state of the boundary buses is identical serves as an equality constraint, a WLS serves as an optimization object, an ADMM is adopted for solving, the subdomains simply need to exchange information of the quantity of state of the boundary buses without a central coordination side, and independence of all the subdomains is reserved; secondly, a bilinear theory is expanded to PMU measurement, traditional nolinear WLS estimation is converted into a three-phase problem, the first phase and the third phase carry out linear WLS estimation (all the subdomains are solved through the ADMM in a distributed mode), and the second phase conducts one-step nonlinear transformation (all the subdomains can be transformed independently); at last, it is verified that the method has high estimated accuracy and computational efficiency through the test result of IEEE118.

Description

technical field [0001] The invention relates to a multi-area distributed state estimation method of a power system based on PMU measurement, belonging to the field of power system analysis and control. Background technique [0002] Power system state estimation estimates the optimal operating state of the system based on real-time measurements provided by SCADA. In modern energy management systems (energy management system, EMS), a series of subsequent analysis calculations (to ensure safe and economical operation of the power grid) rely on state estimation The real-time operating status of the system provided, so status estimation has become an indispensable basic function of modern EMS. [0003] With the interconnection of domestic regional power grids, the ever-increasing system scale has increased the computational burden of traditional integral state estimation. In addition, my country's power grid adopts a hierarchical control and distributed processing model, and the ...

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Problems solved by technology

[0005] Traditional distributed state estimation methods can be roughly divided into two categories: 1) Hierarchical distributed state estimation methods based on decomposition and coordination. The convergence performance and fault identification of this type of method are comparable to the overall method, but the partition side and the coordination side are iterated separately. Generally, only suboptimal solutions can be obtained, and the information transmitted from the partition side to the coordination side is of various types, and the communication complexity is large; 2) There is no need for a distributed method on the coordination side. This type of method has high estimation accuracy and does not require a central coordination side. The communication mechanism is simple, but the convergence performance is weak, and it is difficult to detect and identify bad data

Therefore, the traditional two types of distributed methods have certain shortcomings, and it is difficult to meet the development needs of modern smart grids.

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