2019•Unpublished venueRequires access

Static Stability Margin Index Construction Method for Large Grid

Xiaojing Li, Lina Fu, Jing Li, Xin Chen, Lixin Cui

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Abstract

Making full use of wide-area measurement information to perform static quantitative assessment of large power grids is critical for intelligent monitoring of power grids. In this paper, based on the generalized "source-grid-load" equivalent model, a method for constructing the static stability margin index of large power grid is proposed. First, based on the generalized "source-grid-load" equivalent model, the power generation node and the load node of power grid are respectively equivalent to the "source" point and the "load" point. Then the equivalent " source-grid-load " branch-related electrical parameters are obtained through computation and derivation, and the entire "source-grid-load" system is given. Then based parameters of the above equivalent system, the static voltage stability margin and the power angle stability margin index were deduced, and the static stability margin index of the large power grid was established, and the rapid quantitative assessment of the static stability of the large power grid was realized. The power flow simulation results of the IEEE 39-bus system verify the correctness and rationality of the proposed method. Compared with the traditional method (potential energy integration method), the validity of the proposed method is also verified.

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What this paper is about

Making full use of wide-area measurement information to perform static quantitative assessment of large power grids is critical for intelligent monitoring of power grids. In this paper, based on the generalized "source-grid-load" equivalent model, a method for constructing the static stability margin index of large power grid is proposed. First, based on the generalized "source-grid-load" equivalent model, the power generation node and the load node of power grid are respectively equivalent to the "source" point and the "load" point. Then the equivalent " source-grid-load " branch-related electrical parameters are obtained through computation and derivation, and the entire "source-grid-load" system is given. Then based parameters of the above equivalent system, the static voltage stability margin and the power angle stability margin index were deduced, and the static stability margin index of the large power grid was established, and the rapid quantitative assessment of the static stability of the large power grid was realized. The power flow simulation results of the IEEE 39-bus system verify the correctness and rationality of the proposed method. Compared with the traditional method (potential energy integration method), the validity of the proposed method is also verified.

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Available abstract

Making full use of wide-area measurement information to perform static quantitative assessment of large power grids is critical for intelligent monitoring of power grids. In this paper, based on the generalized "source-grid-load" equivalent model, a method for constructing the static stability margin index of large power grid is proposed. First, based on the generalized "source-grid-load" equivalent model, the power generation node and the load node of power grid are respectively equivalent to the "source" point and the "load" point. Then the equivalent " source-grid-load " branch-related electrical parameters are obtained through computation and derivation, and the entire "source-grid-load" system is given. Then based parameters of the above equivalent system, the static voltage stability margin and the power angle stability margin index were deduced, and the static stability margin index of the large power grid was established, and the rapid quantitative assessment of the static stability of the large power grid was realized. The power flow simulation results of the IEEE 39-bus system verify the correctness and rationality of the proposed method. Compared with the traditional method (potential energy integration method), the validity of the proposed method is also verified.

Key concepts: Electric power system, Margin (machine learning), Grid, Correctness, Control theory (sociology), Computer science, Stability (learning theory), Power (physics)

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