CN108847674B - User load adjustable potential calculation method and device based on wavelet packet decomposition - Google Patents
User load adjustable potential calculation method and device based on wavelet packet decomposition Download PDFInfo
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- CN108847674B CN108847674B CN201810847579.3A CN201810847579A CN108847674B CN 108847674 B CN108847674 B CN 108847674B CN 201810847579 A CN201810847579 A CN 201810847579A CN 108847674 B CN108847674 B CN 108847674B
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
- H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
- Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
- Y02B70/3225—Demand response systems, e.g. load shedding, peak shaving
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
- Y04S20/20—End-user application control systems
- Y04S20/222—Demand response systems, e.g. load shedding, peak shaving
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Abstract
The invention discloses a user load adjustable potential calculation method and device based on wavelet packet decomposition. The method comprises the steps of extracting historical load data of a user in a first preset time length as original signals, windowing the original signals in a second preset time length, respectively performing wavelet packet decomposition on the original signals of each sub-segment through a preset wavelet base to obtain a fundamental frequency component waveform of the original signals of each sub-segment, overlapping the fundamental frequency component waveforms, averaging to obtain an average fundamental frequency waveform of the original signals of each sub-segment, calculating average fundamental frequency energy of the average fundamental frequency waveform, calculating an absolute difference between the energy of the original signals of each sub-segment and the average fundamental frequency energy by using the average fundamental frequency energy as a reference value, and calculating an average value of the absolute differences to obtain the load absolute adjustable potential of the user.
Description
Technical Field
The invention relates to the technical field of power management, in particular to a user load adjustable potential calculation method and device based on wavelet packet decomposition.
Background
In the current power system, along with the development of the demand side market, the application and development of demand side market items such as load management and the like gradually appear, and more refined classification and prediction on the power utilization behaviors of power consumers are required so as to analyze the load regulation potential of the consumers.
An advanced metering system (AMI) composed of an intelligent electric meter and the like can record and store the electricity utilization behaviors of users, and a large amount of electricity utilization data are accumulated.
How to perform data mining on historical electricity utilization data of a user and analyze load adjustment potential of the user becomes a technical problem which needs to be solved urgently by technical personnel in the field.
Disclosure of Invention
The invention provides a user load adjustable potential calculation method and device based on wavelet packet decomposition, and solves the technical problems of data mining of historical power consumption data of a user and analysis of the load adjustable potential of the user.
The invention provides a user load adjustable potential calculation method based on wavelet packet decomposition, which comprises the following steps of:
s1: acquiring historical load data of a user in a first preset time length as an original signal, windowing the original signal in a second preset time length, and calculating the energy of the original signal of each subsection;
s2: respectively carrying out wavelet packet decomposition on each sub-segment original signal by using a preset wavelet basis, extracting the fundamental frequency component waveform of each sub-segment original signal, superposing the fundamental frequency component waveforms of each sub-segment original signal to obtain an average fundamental frequency waveform, and calculating average fundamental frequency energy according to the average fundamental frequency waveform;
s3: and calculating the average value of the absolute difference between the energy of the original signal of each subsection and the average fundamental frequency energy to obtain the load absolute adjustable potential of the user.
Preferably, step S3 is followed by: step S4;
s4: and calculating the ratio of the load absolute adjustable potential to the average fundamental frequency energy to obtain the load relative adjustable potential of the user.
Preferably, step S1 specifically includes: acquiring historical load data of a user in a first preset time length as an original signal, windowing the original signal in a second preset time length, and calculating the energy of the original signal of each sub-section by a two-norm energy calculation method.
Preferably, the second preset time period is 24 hours.
Preferably, the preset wavelet bases are symlets wavelet bases.
The invention provides a user load adjustable potential calculation device based on wavelet packet decomposition, which comprises:
the signal windowing unit is used for acquiring historical load data of a first preset time length of a user as an original signal, windowing the original signal by a second preset time length and calculating the energy of the original signal of each subsection;
the wavelet decomposition unit is used for respectively carrying out wavelet packet decomposition on each sub-section original signal by using a preset wavelet basis, extracting the fundamental frequency component waveform of each sub-section original signal, superposing the fundamental frequency component waveforms of each sub-section original signal to obtain an average fundamental frequency waveform, and calculating the average fundamental frequency energy according to the average fundamental frequency waveform;
and the absolute calculation unit is used for calculating the average value of the absolute difference between the energy of the original signal of each sub-section and the average fundamental frequency energy to obtain the load absolute adjustable potential of the user.
Preferably, the method further comprises the following steps: a relative calculation unit;
and the relative calculation unit is used for calculating the ratio of the load absolute adjustable potential to the average fundamental frequency energy to obtain the load relative adjustable potential of the user.
Preferably, the signal windowing unit is specifically configured to acquire historical load data of a user in a first preset time length as an original signal, perform windowing on the original signal in a second preset time length, and calculate the energy of the original signal of each sub-segment by using a two-norm energy calculation method.
Preferably, the second preset time period is 24 hours.
Preferably, the preset wavelet bases are symlets wavelet bases.
According to the technical scheme, the invention has the following advantages:
the method comprises the steps of extracting historical load data of a user in a first preset time length as original signals, windowing the original signals in a second preset time length, respectively performing wavelet packet decomposition on the original signals of each sub-segment through a preset wavelet base to obtain a fundamental frequency component waveform of the original signals of each sub-segment, overlapping the fundamental frequency component waveforms, averaging to obtain an average fundamental frequency waveform of the original signals of each sub-segment, calculating average fundamental frequency energy of the average fundamental frequency waveform, calculating an absolute difference between the energy of the original signals of each sub-segment and the average fundamental frequency energy by using the average fundamental frequency energy as a reference value, and calculating an average value of the absolute differences to obtain the load absolute adjustable potential of the user.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
Fig. 1 is a schematic flowchart of an embodiment of a method for calculating user load adjustable potential based on wavelet packet decomposition according to the present invention;
fig. 2 is a schematic flowchart of a user load adjustable potential calculation method based on wavelet packet decomposition according to another embodiment of the present invention;
fig. 3 is a schematic structural diagram of an embodiment of a user load adjustable potential calculating apparatus based on wavelet packet decomposition according to the present invention;
FIG. 4 is a schematic diagram illustrating a wavelet packet decomposition according to an embodiment of the present invention;
fig. 5 is a schematic waveform diagram of a symlets wavelet provided by the embodiment of the present invention;
FIG. 6 is a topology diagram of wavelet packet decomposition provided by an embodiment of the present invention;
fig. 7 is a waveform diagram of a fundamental frequency component waveform of an original signal of a certain sub-segment according to an embodiment of the present invention;
fig. 8 is a waveform diagram of an average fundamental frequency waveform according to an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a user load adjustable potential calculation method and device based on wavelet packet decomposition, and solves the technical problems of data mining of historical power consumption data of a user and analysis of the load adjustable potential of the user.
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, an embodiment of the present invention provides a method for calculating a user load adjustable potential based on wavelet packet decomposition, including:
step 101: acquiring historical load data of a user in a first preset time length as an original signal, windowing the original signal in a second preset time length, and calculating the energy of the original signal of each subsection;
it should be noted that, before calculating the load tunable potential of the user, it needs to obtain: acquiring historical load data of a user in a first preset time length as an original signal, windowing the original signal in a second preset time length, and calculating the energy of the original signal of each subsection.
Step 102: respectively carrying out wavelet packet decomposition on each sub-segment original signal by using a preset wavelet basis, extracting the fundamental frequency component waveform of each sub-segment original signal, superposing the fundamental frequency component waveforms of each sub-segment original signal to obtain an average fundamental frequency waveform, and calculating average fundamental frequency energy according to the average fundamental frequency waveform;
it should be noted that, after the original signal is windowed, wavelet packet decomposition is performed on the original signal of each sub-segment by using a preset wavelet basis, and a fundamental frequency component waveform of the original signal of each sub-segment is extracted.
And superposing the fundamental frequency component waveforms of the original signals of all the subsections to obtain an average fundamental frequency waveform.
The average fundamental frequency energy can be calculated from the average fundamental frequency waveform
Step 103: and calculating the average value of the absolute difference between the energy of the original signal of each subsection and the average fundamental frequency energy to obtain the load absolute adjustable potential of the user.
It should be noted that after the average fundamental frequency energy is calculated, the average fundamental frequency energy is used as a reference value, the absolute difference between the energy of the original signal of each sub-segment and the average fundamental frequency energy is calculated, and the average value of the absolute differences is calculated, so that the load absolute adjustable potential of the user can be obtained.
In this embodiment, historical load data of a user in a first preset time length is extracted as an original signal, windowing is performed on the original signal in a second preset time length, wavelet packet decomposition is performed on each sub-segment original signal through a preset wavelet base, a fundamental frequency component waveform of each sub-segment original signal can be obtained, the fundamental frequency component waveforms are superposed and averaged, an average fundamental frequency waveform of each sub-segment original signal can be obtained, average fundamental frequency energy of the average fundamental frequency waveform can be calculated, the average fundamental frequency energy is used as a reference value, an absolute difference between the energy of each sub-segment original signal and the average fundamental frequency energy is calculated, and an average of the absolute differences is calculated, so that the load absolute adjustable potential of the user can be obtained.
The foregoing is an embodiment of a method for calculating a user load adjustable potential based on wavelet packet decomposition according to an embodiment of the present invention, and the following is another embodiment of a method for calculating a user load adjustable potential based on wavelet packet decomposition according to an embodiment of the present invention.
Referring to fig. 2 and fig. 4 to 8, another embodiment of a method for calculating a user load adjustable potential based on wavelet packet decomposition according to the present invention includes:
step 201: acquiring historical load data of a user in a first preset time length as an original signal, windowing the original signal in a second preset time length, and calculating the energy of the original signal of each sub-section by a two-norm energy calculation method;
it should be noted that before calculating the load adjustable potential of the user, it is necessary to obtain the historical load data of the user for a first preset time length as the original signal, for example, the historical load data of a month of a certain user is selected as the original signal, and a discrete time sequence X ═ X may be used1,x2,…,xN]Representing historical load data collected from the two-sided device, where N represents the total number of sample points.
After obtaining the original signal, windowing the original signal with a second preset time length, for example, the second preset time length may be selected as 24 hours, then segmenting the original signal by day to obtain a matrix representation of a discrete time sequence:
wherein m represents the number of sampling points in one day, and since the sampling interval of the electric quantity data is generally 15min, m is generally 96, d represents the number of days contained in the data in the original signal, and thus N is the product of m and d.
Each row vector of the Load corresponds to the power utilization sampling data of one day of the Load of the user, and each row represents the original signal of each subsection.
After windowing the original signal, the energy of the original signal of each sub-segment can be expressed as:
Energy＝(E1 E2…Ed)T (2)
the energy of the original signal of each sub-segment can be calculated by a two-norm energy calculation method, and E is1For example, it can be expressed as:
step 202: respectively carrying out wavelet packet decomposition on each sub-segment original signal by using a preset wavelet basis, extracting the fundamental frequency component waveform of each sub-segment original signal, superposing the fundamental frequency component waveforms of each sub-segment original signal to obtain an average fundamental frequency waveform, and calculating average fundamental frequency energy according to the average fundamental frequency waveform;
it should be noted that the expression of the wavelet transform is:
cjk＝[Wψf](2-j,k2-j) (5)
wherein a is a scale, b is a translation amount, cjkAre wavelet coefficients.
Wavelet packet decomposition, namely, respectively passing an original signal through a high-pass filter and a low-pass filter to obtain a high-frequency coefficient and a low-frequency coefficient of the original signal, and continuously further decomposing the high-frequency coefficient and the low-frequency coefficient to obtain an expected decomposition requirement, wherein the maximum decomposition level of the mode is log2N。
The schematic diagram of wavelet packet decomposition is shown in fig. 4, where g represents low frequency quantity and h represents high frequency quantity.
In this embodiment, the preset wavelet basis may be selected as a symlets wavelet basis, the form of the symlets wavelet is shown in fig. 5, specifically, the preset wavelet basis may be selected as sym2 in the symlets wavelet, a 3-layer decomposition is adopted with a data density of 96 sampling points per day, a topological structure of the decomposition is shown in fig. 6, and a fundamental frequency component obtained by the decomposition is shown in fig. 7.
In practical application, other wavelet bases can be selected according to practical requirements.
The fundamental frequency component waveforms of the original signals of each sub-segment are superposed and averaged to obtain an average fundamental frequency waveform (as shown in fig. 8), and the average fundamental frequency waveform is calculated by a two-norm energy calculation method to obtain an average fundamental frequency energy, which is denoted as Ebase。
Step 203: calculating the average value of the absolute difference between the energy of the original signal of each subsection and the average fundamental frequency energy to obtain the load absolute adjustable potential of the user;
it should be noted that, with the average fundamental frequency energy as a reference value, the absolute difference between the energy of the original signal of each sub-segment and the average fundamental frequency energy can be calculated, and the average value of each absolute value can be calculated to obtain the load absolute adjustable potential of the user, where the expression is:
wherein E isopFor the absolute adjustable potential of the load of the user, Delta EiIs the absolute difference of the original signal of the i-th subsection.
Step 204: and calculating the ratio of the load absolute adjustable potential to the average fundamental frequency energy to obtain the load relative adjustable potential of the user.
It should be noted that the load relative adjustable potential of the user can be obtained by calculating the ratio of the load absolute adjustable potential to the average fundamental frequency energy, and the expression of the load relative adjustable potential is as follows:
wherein alpha is the relatively adjustable potential of the load.
The historical load data for the first preset time duration of the user is extracted as the raw signal in this embodiment, windowing the original signal by a second preset time length, applying the wavelet decomposition technology to the field of load analysis, respectively carrying out wavelet packet decomposition on the original signals of each sub-segment time sequence by presetting a wavelet basis to obtain the fundamental frequency component waveform of each sub-segment original signal, overlapping all the fundamental frequency component waveforms and averaging to obtain the average fundamental frequency waveform of each sub-segment original signal, and calculating the average fundamental frequency energy of the average fundamental frequency waveform, taking the average fundamental frequency energy as a reference value, calculating the absolute difference between the energy of the original signal of each sub-section and the average fundamental frequency energy, and the average value of the absolute differences is calculated to obtain the absolute adjustable potential of the load of the user, so that the technical problems of data mining of the historical power consumption data of the user and analysis of the load adjustment potential of the user are solved.
The present invention provides another embodiment of a method for calculating a user load adjustable potential based on wavelet packet decomposition, and the following is an embodiment of a device for calculating a user load adjustable potential based on wavelet packet decomposition according to the present invention.
Referring to fig. 3, an embodiment of the present invention provides an embodiment of a user load adjustable potential calculating apparatus based on wavelet packet decomposition, including:
a signal windowing unit 301, configured to obtain historical load data of a first preset time duration of a user as an original signal, perform windowing on the original signal with a second preset time duration, and calculate energy of the original signal of each sub-segment;
the wavelet decomposition unit 302 is configured to perform wavelet packet decomposition on each sub-segment original signal respectively by using a preset wavelet basis, extract a fundamental frequency component waveform of each sub-segment original signal, superimpose the fundamental frequency component waveforms of each sub-segment original signal to obtain an average fundamental frequency waveform, and calculate average fundamental frequency energy according to the average fundamental frequency waveform;
and the absolute calculation unit 303 is configured to calculate an average value of absolute differences between the energy of the original signal of each sub-segment and the average fundamental frequency energy to obtain an absolutely adjustable potential of the load of the user.
Further, still include: a relative calculation unit 304;
and the relative calculation unit 304 is configured to calculate a ratio of the load absolute adjustable potential to the average fundamental frequency energy to obtain the load relative adjustable potential of the user.
Further, the signal windowing unit 301 is specifically configured to obtain historical load data of a first preset time length of the user as an original signal, perform windowing on the original signal with a second preset time length, and calculate energy of the original signal of each sub-segment by using a two-norm energy calculation method.
Further, the second preset time period is 24 hours.
Further, the preset wavelet bases are symlets wavelet bases.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A user load adjustable potential calculation method based on wavelet packet decomposition is characterized by comprising the following steps:
s1: acquiring historical load data of a user in a first preset time length as an original signal, windowing the original signal in a second preset time length, and calculating the energy of the original signal of each subsection;
s2: respectively carrying out wavelet packet decomposition on each sub-segment original signal by using a preset wavelet basis, extracting the fundamental frequency component waveform of each sub-segment original signal, superposing the fundamental frequency component waveforms of each sub-segment original signal to obtain an average fundamental frequency waveform, and calculating average fundamental frequency energy according to the average fundamental frequency waveform;
s3: and calculating the absolute difference between the energy of the original signal of each subsection and the average fundamental frequency energy, and calculating the average value of each absolute difference to obtain the load absolute adjustable potential of the user.
2. The method for calculating user load adjustable potential based on wavelet packet decomposition according to claim 1, wherein the step S3 is followed by further comprising: step S4;
s4: and calculating the ratio of the load absolute adjustable potential to the average fundamental frequency energy to obtain the load relative adjustable potential of the user.
3. The method for calculating user load adjustable potential based on wavelet packet decomposition according to claim 1, wherein the step S1 specifically comprises: acquiring historical load data of a user in a first preset time length as an original signal, windowing the original signal in a second preset time length, and calculating the energy of the original signal of each sub-section by a two-norm energy calculation method.
4. The method according to claim 1, wherein the second preset time period is 24 hours.
5. The method as claimed in claim 1, wherein the preset wavelet basis is a symlets wavelet basis.
6. A user load adjustable potential calculation device based on wavelet packet decomposition, comprising:
the signal windowing unit is used for acquiring historical load data of a first preset time length of a user as an original signal, windowing the original signal by a second preset time length and calculating the energy of the original signal of each subsection;
the wavelet decomposition unit is used for respectively carrying out wavelet packet decomposition on each sub-section original signal by using a preset wavelet basis, extracting the fundamental frequency component waveform of each sub-section original signal, superposing the fundamental frequency component waveforms of each sub-section original signal to obtain an average fundamental frequency waveform, and calculating the average fundamental frequency energy according to the average fundamental frequency waveform;
and the absolute calculation unit is used for calculating the absolute difference between the energy of the original signal of each sub-section and the average fundamental frequency energy, and calculating the average value of all the absolute differences to obtain the load absolute adjustable potential of the user.
7. The apparatus of claim 6, further comprising: a relative calculation unit;
and the relative calculation unit is used for calculating the ratio of the load absolute adjustable potential to the average fundamental frequency energy to obtain the load relative adjustable potential of the user.
8. The apparatus according to claim 6, wherein the signal windowing unit is specifically configured to obtain historical load data of a first preset time duration of the user as the original signal, perform windowing on the original signal with a second preset time duration, and calculate the energy of the original signal of each sub-segment by using a two-norm energy calculation method.
9. The apparatus according to claim 6, wherein the second preset time period is 24 hours.
10. The apparatus of claim 6, wherein the preset wavelet basis is a symlets wavelet basis.
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| CN107292462A (en) * | 2017-08-25 | 2017-10-24 | 广东工业大学 | A kind of short-term load forecasting method, apparatus and system |
| CN107590557A (en) * | 2017-08-31 | 2018-01-16 | 河海大学 | Load forecasting method based on wavelet transformation and harmony search updated gray correlation analysis |
| CN107729868A (en) * | 2017-11-01 | 2018-02-23 | 广西师范学院 | A kind of signal processing method based on wavelet analysis |
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| CN107292462A (en) * | 2017-08-25 | 2017-10-24 | 广东工业大学 | A kind of short-term load forecasting method, apparatus and system |
| CN107590557A (en) * | 2017-08-31 | 2018-01-16 | 河海大学 | Load forecasting method based on wavelet transformation and harmony search updated gray correlation analysis |
| CN107729868A (en) * | 2017-11-01 | 2018-02-23 | 广西师范学院 | A kind of signal processing method based on wavelet analysis |
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