CN112785033A - Wind power disorder index and prediction effect evaluation method based on information entropy theory - Google Patents
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Abstract
The invention belongs to the technical field of power systems, and particularly relates to a wind power disorder index and prediction effect evaluation method based on an information entropy theory. The invention comprises the following steps: step 1, acquiring a random component of wind power output; step 2, calculating the probability corresponding to the second random component; step 3, respectively calculating the entropy value of the wind power output prediction and the entropy value of the actual wind power output, and calculating the absolute value of the difference between the two values; and 4, judging the disordering simulation effect of the prediction method. The stability and the disorder of the wind power prediction method are evaluated by using an informatics entropy theory aiming at the stability and the disorder of the wind power prediction result, so that the scientificity and the comprehensiveness of the prediction evaluation method can be obviously improved, and the accuracy and the stability of the wind power prediction can be improved. Meanwhile, the average value and the distribution standard of the wind power prediction error are comprehensive and accurate, and the method plays an important role in stable frequency modulation of a power grid.
Description
Technical Field
The invention belongs to the technical field of power systems, and particularly relates to a wind power disorder index and prediction effect evaluation method based on an information entropy theory.
Background
Wind power prediction mainly refers to prediction of wind power plant output, and a wind power prediction result can be used for short-term prediction and ultra-short-term prediction of power generation output of a power grid dispatching department and is an important basis for making a day-ahead plan by power grid dispatching. The accuracy of wind power prediction is improved, the safety and stability level of a power grid can be improved, and the development and utilization of renewable energy sources are promoted.
Because the wind power generation output has strong randomness and volatility, the wind power prediction is very important for predicting the randomness and the disorder of the output. The disorder reflects the difference degree of error values of all sample points, and the accurate simulation of disorder performance is an important aspect of the capability of the prediction method. The disorder of the wind power output is directly related to the fluctuation range of the wind power, and is important for realizing stable frequency modulation on a power grid.
The evaluation of the current prediction method mainly comprises the steps of calculating relative errors and root mean square errors and estimating the probability density of wind power errors. The two methods are mature at present, are based on probability theory, and describe the average value and the standard deviation of distribution of wind power prediction errors by adopting a Gaussian-parameter equal probability distribution model.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a wind power disorder index and prediction effect evaluation method based on an information entropy theory. The method aims to realize the purpose of evaluating the stability and the disorder of the wind power prediction result by using an informatics entropy theory so as to obviously improve the scientificity and the comprehensiveness of the prediction evaluation method.
The technical scheme adopted by the invention for realizing the purpose is as follows:
the wind power disorder index and prediction effect evaluation method based on the information entropy theory comprises the following steps:
step 1, acquiring a random component of wind power output;
step 2, calculating the probability corresponding to the second random component;
step 3, respectively calculating the entropy value of the wind power output prediction and the entropy value of the actual wind power output, and calculating the absolute value of the difference between the two values;
and 4, judging the disordering simulation effect of the prediction method.
Further, the acquiring the random component of the wind power output includes:
the calculation formula of the wind power output random component is represented as follows:
S(i)＝C(i)+ε(i)
wherein: s (i) represents an original sequence of wind power output, C (i) represents components after different fundamental wave transformations, and epsilon (i) represents an error random component after signal decomposition.
Furthermore, the curve of the wind power output is obtained by adopting a signal decomposition method to decompose, and the entropy value is obtained after the obtained random component is normalized.
Further, the random component is obtained in other manners, so that the entropy value of the wind power is calculated.
Further, the calculating the probability corresponding to the second random component means calculating the probability p (Δ x) corresponding to the ith random component ∈ (i)i)。
Further, the entropy value of the predicted wind power output and the entropy value of the actual wind power output are respectively calculated, and the absolute value of the difference between the two values is obtained, wherein the calculation formula is as follows:
wherein: hpridictRepresenting an entropy value of wind power output prediction; hrealRepresenting the entropy value of the actual wind power output, and delta H representing the wind power output.
Further, the determining the chaotic simulation effect of the prediction method comprises:
the judgment standard is that the closer the entropy of the wind power output predicted value is to the entropy of the wind power actual value, the better the randomness and disorder effect of the simulated original sequence in the prediction method is.
Furthermore, the disorder simulation effect of the judgment and prediction method has 3 prediction methods
ΔH1＞ΔH2＞ΔH3The disorder simulation effect of the method 3 is optimal;
the expected effect is as follows:
and (3) introducing an information entropy theory, and obtaining a prediction result disorder index according to analysis of the prediction result information entropy, thereby selecting a prediction method with a good simulation original sequence effect.
A computer storage medium is stored with a computer program, and when the computer program is executed by a processor, the steps of the wind power disorder index and prediction effect evaluation method based on the information entropy theory are realized.
The invention has the following beneficial effects and advantages:
the method can evaluate the stability and the disorder of the prediction method by using an informatics entropy theory aiming at the stability and the disorder of the wind power prediction result, so that the scientificity and the comprehensiveness of the prediction evaluation method can be obviously improved.
The invention proves that by introducing the information entropy theory, the randomness index of the prediction result can be obtained according to the analysis of the information entropy of the prediction result, so that the prediction method with better simulation original sequence effect is selected, and the accuracy and the stability of wind power prediction are improved.
The average value and the distribution standard of the wind power prediction error are comprehensive and accurate, and the method can play an important role in stabilizing frequency modulation for a power grid.
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The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments of the present invention and features of the embodiments may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
The solution of some embodiments of the invention is described below with reference to fig. 1.
Example 1
The invention discloses a wind power disorder index and prediction effect evaluation method based on an information entropy theory, which is shown in figure 1, and figure 1 is a flow chart of the method.
According to the theory of information theory, information is a measure of the order of a system and entropy is a measure of the disorder of a system. To solve the quantitative measurement problem of information, shannon (c.e. shannon) in 1948 proposed the concept of information entropy and defined it as the probability of discrete random events occurring.
The calculation formula of the information entropy is as follows:
in the formula: p (x)i) Representing the probability of occurrence of the variable x, xiIs a random variable.
The entropy method is a classical method for evaluating the disorder of information: for a certain item of information, the smaller the entropy value of the information is, the larger the variation degree of the information is, and the worse the stability of the sample sequence is; conversely, the larger the entropy value, the better the stability.
In the effect evaluation of wind power prediction, the wind power output disorder degree is evaluated by introducing the idea of information entropy, namely the entropy value of wind power. And after the result of the wind power prediction appears, evaluating the stability of the wind power prediction method by adopting the entropy calculation result of the random component.
The method comprises the following specific operation steps:
step 1, acquiring a random component of wind power output.
The calculation formula of the wind power output random component can be expressed as follows:
S(i)＝C(i)+ε(i)
wherein: s (i) represents an original sequence of wind power output, C (i) represents components after different fundamental wave transformations, and epsilon (i) represents an error random component after signal decomposition.
For example, a signal decomposition method may be used to decompose the wind power output curve, and the entropy value may be obtained after normalizing the obtained random component, or other methods may be used to obtain the random component so as to calculate the entropy value of the wind power.
Step 2, calculating the probability p (delta x) corresponding to the ith random component epsilon (i)i)。
Step 3, respectively calculating the entropy value of the wind power output prediction and the entropy value of the actual wind power output, and calculating the absolute value of the difference between the two values, wherein the calculation formula is as follows:
wherein: hpridictRepresenting an entropy value of wind power output prediction; hrealRepresenting the entropy of the actual wind output, Δ H representing the wind output, p (Δ x)i)＝Δxix is the random variable in the system.
And 4, judging the disordering simulation effect of the prediction method.
The judgment standard is that the closer the entropy of the wind power output predicted value is to the entropy of the wind power actual value, the better the randomness and disorder effect of the simulated original sequence in the prediction method is.
For example, if there are 3 prediction methods Δ H1＞ΔH2＞ΔH3The best effect of the disorder simulation of method 3 is shown.
The expected effect is as follows:
by introducing the information entropy theory, the randomness index of the prediction result can be obtained according to the analysis of the information entropy of the prediction result, so that the prediction method with better simulation original sequence effect is selected, and the accuracy and the stability of wind power prediction are improved.
Example 2
Based on the same inventive concept, the embodiment of the present invention further provides a computer storage medium, where a computer program is stored on the computer storage medium, and when the computer program is executed by a processor, the method for evaluating the wind power disorder index and the prediction effect based on the entropy theory described in embodiment 1 is implemented.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (9)
1. The wind power disorder index and prediction effect evaluation method based on the information entropy theory is characterized by comprising the following steps: the method comprises the following steps:
step 1, acquiring a random component of wind power output;
step 2, calculating the probability corresponding to the second random component;
step 3, respectively calculating the entropy value of the wind power output prediction and the entropy value of the actual wind power output, and calculating the absolute value of the difference between the two values;
and 4, judging the disordering simulation effect of the prediction method.
2. The wind power disorder index and prediction effect evaluation method based on the information entropy theory as claimed in claim 1, wherein the method comprises the following steps: the acquiring of the random component of the wind power output comprises the following steps:
the calculation formula of the wind power output random component is represented as follows:
S(i)＝C(i)+ε(i)
wherein: s (i) represents an original sequence of wind power output, C (i) represents components after different fundamental wave transformations, and epsilon (i) represents an error random component after signal decomposition.
3. The wind power disorder index and prediction effect evaluation method based on the information entropy theory as claimed in claim 1, wherein the method comprises the following steps: and decomposing the curve of the obtained wind power output by adopting a signal decomposition method, and normalizing the obtained random component to obtain an entropy value.
4. The wind power disorder index and prediction effect evaluation method based on the information entropy theory as claimed in claim 2, wherein the method comprises the following steps: and acquiring the random component by adopting other modes, thereby calculating the entropy value of the wind power.
5. The wind power disorder index and prediction effect evaluation method based on the information entropy theory as claimed in claim 1, wherein the method comprises the following steps: the step of calculating the probability corresponding to the second random component is to calculate the probability p (Δ x) corresponding to the ith random component ε (i)i)。
6. The wind power disorder index and prediction effect evaluation method based on the information entropy theory as claimed in claim 1, wherein the method comprises the following steps: the entropy value of the wind power output prediction and the entropy value of the actual wind power output are respectively calculated, and the absolute value of the difference between the two is obtained, wherein the calculation formula is as follows:
wherein: hpridictRepresenting an entropy value of wind power output prediction; hrealEntropy representing actual wind power outputAnd Δ H represents wind power output.
7. The wind power disorder index and prediction effect evaluation method based on the information entropy theory as claimed in claim 1, wherein the method comprises the following steps: the method for judging the chaotic simulation effect of the prediction method comprises the following steps:
the judgment standard is that the closer the entropy of the wind power output predicted value is to the entropy of the wind power actual value, the better the randomness and disorder effect of the simulated original sequence in the prediction method is.
8. The wind power disorder index and prediction effect evaluation method based on the information entropy theory as claimed in claim 1, wherein the method comprises the following steps: the disorder simulation effect of the judgment prediction method has 3 prediction methods
ΔH1＞ΔH2＞ΔH3The disorder simulation effect of the method 3 is optimal;
the expected effect is as follows:
and (3) introducing an information entropy theory, and obtaining a prediction result disorder index according to analysis of the prediction result information entropy, thereby selecting a prediction method with a good simulation original sequence effect.
9. A computer storage medium, characterized by: the computer storage medium stores a computer program, and the computer program when executed by a processor implements the steps of the wind power disorder index and prediction effect evaluation method based on the information entropy theory according to claims 1 to 8.
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