Power system chaos model monitoring method based on Lyapunov exponent

A power system and index technology, applied in forecasting, data processing applications, instruments, etc., can solve problems such as uncertainty, complexity of power load time series, nonlinearity, etc., to ensure safe and economic operation, and the forecast effect is impressive. The effect of high prediction accuracy

Inactive Publication Date: 2016-04-13
GUANGDONG UNIV OF TECH
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Problems solved by technology

The power load time series obtained in practice presents the characteristics of complexity, uncertainty and nonlinearity

Method used

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  • Power system chaos model monitoring method based on Lyapunov exponent
  • Power system chaos model monitoring method based on Lyapunov exponent
  • Power system chaos model monitoring method based on Lyapunov exponent

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Embodiment 1

[0040] 1. The hourly loads of a power system on the hour every day for 24 hours in a certain power system form a time series, and the sequence length is n=8760.

[0041] 2. Calculate the autocorrelation function of the sequence, and select the optimal delay time τ as 10h (see figure 1 ).

[0042] 3. Obtain the saturation correlation dimension m=8 of the hourly load. At this time, the corresponding spatial dimension is the optimal embedding dimension of the reconstructed phase space (see figure 2 ).

[0043] 4. Based on the theory of reconstructed phase space, establish the multi-dimensional phase space of hourly load, take the optimal embedding dimension of phase space m=8, delay time τ=10, constitute more than 8000 phase points, all phase points are expressed as:

[0044] Y(t i ) = [x(t i ), x(t i +10),···,x(t i +(8-1)*10)].

[0045] 5. Calculate the maximum Lyapunov exponent of the hourly load of electricity. In order to verify the stability of the algorithm, the s...

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Abstract

The invention provides a power system chaos model monitoring method based on a Lyapunov exponent. The method is a prediction method which carries out modeling on the basis of a maximum Lyapunov exponent [Lambda]1. The model favorably keeps the statistical property of a power hour load phase space attractor, is high in prediction accuracy, has a satisfactory prediction effect, and can effectively monitor the change rule of the power hour load so as to guarantee the safe and economic operation of the power system.

Description

technical field [0001] The invention relates to the field of power system detection methods, and more specifically, to a power system chaos model monitoring method based on Lyapunov exponents. Background technique [0002] Power load data is an important basis for water resources development, optimal allocation, and reservoir scheduling. Power load forecasting plays a very important role in the safe and economical operation of the power system. Power generation planning, system safety assessment and energy exchange planning require short-term load forecasting data as a basis for decision-making. The power load time series obtained in practice presents the characteristics of complexity, uncertainty and nonlinearity. Based on the chaos analysis method, it is very meaningful to reconstruct the electric load phase space, fully excavate the dynamic information characteristics of the electric load, study the nonlinear prediction scheme in the load phase space, and then apply it ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06
Inventor 李岱霖杨俊华陈集思林卓胜
Owner GUANGDONG UNIV OF TECH
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