CN113743756B - Synchronous measurement system and synchronous measurement algorithm of comprehensive energy system - Google Patents
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Abstract
The invention belongs to the technical field of energy internet measurement, and discloses a synchronous measurement system of a comprehensive energy system, which comprises the following components: the system comprises a basic data acquisition unit, a synchronous measurement unit and an energy comprehensive dispatching center; the basic data acquisition unit is used for acquiring sampling data of each energy subsystem; the synchronous measurement unit is internally provided with a synchronous measurement algorithm, the synchronous measurement algorithm obtains a fitting function of the slow-change system according to actual sampling data of the slow-change system and the synchronous moment, and the sampling data of the slow-change system at the synchronous moment is calculated according to the fitting function; and the output signal of the synchronous measurement unit is transmitted to an energy comprehensive dispatching center. The embodiment of the invention can synchronously measure the diversified data of all subsystems in the comprehensive energy system, and the data have the same sampling interval and precision, so that the basic sampling data of the power network, the cooling/heating network and the natural gas network are effectively fused, and the high sharing of the comprehensive energy system is realized.
Description
Technical Field
The invention relates to the technical field of energy internet measurement, in particular to a synchronous measurement system of a comprehensive energy system and a synchronous measurement algorithm.
Background
The contradiction between the continuous increase of energy demand and the shortage of energy is increasingly serious, and the gradual formation of a comprehensive energy system with multiple energy complementary optimization is promoted. The method has the advantages that diversified data of the comprehensive energy system are collected uniformly and accurately, and the method has important significance for effectively grasping the operation situation of the comprehensive energy system and realizing the joint scheduling of all the energy subsystems. Because of the difference of the development of each energy subsystem forming the comprehensive energy system, the energy supply of each energy subsystem is independently planned and operated, and each measurement system only has single energy data acquisition and analysis processing capability. The sensing data of the quick-change system represented by electricity has high precision and high sampling rate, and has good synchronism and real-time performance; the slow-change system represented by cold, hot and gas has lower requirements on data precision and synchronism, measurement data of all systems cannot be effectively fused, and the integrated energy system of interconnected operation presents the characteristics of large quantity, multiple types, multiple time scales and the like, so that bidirectional flow of energy flow and information flow is difficult to realize.
Therefore, how to realize synchronous measurement of the diversified data in the integrated energy system is a problem to be solved at present.
Disclosure of Invention
In order to solve the above problems, the present invention provides a synchronous measurement system for an integrated energy system, which can realize synchronous measurement of multiple data in the integrated energy system.
According to a first aspect of an embodiment of the present invention, a synchronization measurement algorithm is provided.
In one embodiment, the synchronization measurement algorithm includes the steps of:
Acquiring a fitting function of the slow-change system according to actual sampling data and synchronous time of the slow-change system;
And calculating sampling data of the slow-change system at the synchronous moment according to the fitting function.
Optionally, the calculation basis of the fitting function coefficients is: so that the error of the fitting value of the fitting function is minimized.
Optionally, the step of obtaining the fitting function of the slowly varying system according to the actual sampling data and the synchronization time of the slowly varying system includes:
Step (1), defining at the synchronous time Fitting function in neighborhood/>The method comprises the following steps:
wherein, For synchronizing time/>Sampling points in the neighborhood,/>Representing an estimated value of the fitting function, b i (t) being the base elements of the fitting function, i=1, 2,..m, m being the number of base elements, k i (t) being the coefficients of the base elements,
Step (2), determining a basal element expression;
step (3), defining an error function of the fitting function;
Step (4), solving the error function pair Obtaining a base element coefficient corresponding to a minimum value point of the fitting function error by making the deviation of the fitting function error be 0, and calculating a coefficient which enables the fitting function fitting value error to be minimum;
and (5) acquiring a fitting function according to the obtained coefficient, substituting the synchronous moment into the fitting function, and calculating sampling data of the synchronous moment.
Optionally, the base element b (t) is a single term, a polynomial, or a trigonometric function.
Optionally, the error function of the fitting function defined in the step (3) is:
Wherein f (t j) is the sampled data at time t j in the slowly varying system, j=1, 2,3, …, N sampling points are Discrete points in the immediate neighborhood,/>A weighted function of the square error of the fitting value of the fitting function and the sampled data at time t j.
Optionally, the error function is expressed in a matrix form:
Δ＝(Bk-f)TW(Bk-f) (7)
wherein,
f＝(f1,f2,...,fN)T＝(f(t1),f(t2),...,f(tN))T (8)
Optionally, the weighting function satisfies:
Δt is the support domain radius of the weighting function.
Optionally, the weighting function uses a normal distribution function:
wherein, Sigma E [1,9] is a shape parameter for the relative radius.
Optionally, the weighting function uses a gaussian weighting function:
wherein, Sigma E [1,9] is a shape parameter for the relative radius.
Optionally, the weighting function uses a spline function:
wherein, Is the relative radius.
Optionally, the base element coefficients corresponding to the minimum value points of the fitting function error obtained in the step (4) are:
Namely:
wherein,
The coefficient that minimizes the error of the fitting value of the fitting function is:
optionally, the synchronous measurement algorithm calculates sampling data of the slow-change system at the synchronous moment according to the sampling interval of the fast-change system or according to the uniform sampling interval set by the energy comprehensive scheduling center.
According to a second aspect of the embodiment of the invention, a synchronous measurement system of an integrated energy system is provided.
In one embodiment, the integrated energy system synchronization measurement system includes: the system comprises a basic data acquisition unit, a synchronous measurement unit and an energy comprehensive dispatching center;
the basic data acquisition unit is used for acquiring sampling data of each energy subsystem;
The synchronous measurement unit is internally provided with the synchronous measurement algorithm of the embodiment, the synchronous measurement algorithm obtains a fitting function of the slow-change system according to the actual sampling data of the slow-change system and the synchronous moment, and the sampling data of the slow-change system at the synchronous moment is calculated according to the fitting function;
And the output signal of the synchronous measurement unit is transmitted to an energy comprehensive dispatching center.
Optionally, the synchronization measurement unit calculates the energy data of the slow-change system according to the calculated sampling data of the slow-change system at the synchronization time.
Optionally, the synchronous measurement unit transmits the sampling data of the slow-change system at the synchronous moment to the energy comprehensive dispatching center, and the energy comprehensive dispatching center calculates and obtains the energy data of the slow-change system according to the sampling data of the slow-change system at the synchronous moment.
According to a third aspect of embodiments of the present invention, a computer device is provided.
In some embodiments, the computer device includes a memory storing a computer program and a processor implementing the steps of the synchronous metrology algorithm described above when the computer program is executed by the processor.
The technical scheme provided by the embodiment of the invention can have the following beneficial effects:
According to the sampling data of the slow-change system at the synchronous moment obtained by calculation, the energy data of the slow-change system can be calculated, the diversified data of all subsystems in the comprehensive energy system are synchronously measured, the data have the same sampling interval and precision, so that the basic sampling data of an electric power network, a cooling/heating network and a natural gas network are effectively fused, the high sharing of the comprehensive energy system is realized, and a reliable basis is provided for the efficient and accurate regulation and control of the comprehensive energy system.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
FIG. 1 is a schematic diagram of an integrated energy system synchronous measurement system, according to an exemplary embodiment;
FIG. 2 is a flowchart illustrating a synchronization measurement algorithm according to an exemplary embodiment;
FIG. 3 is a schematic diagram of a weighting function shown according to an exemplary embodiment;
FIG. 4 is a schematic diagram illustrating a given sampling instant and synchronization instant in accordance with an exemplary embodiment;
Fig. 5 is a schematic diagram of a computer device, according to an example embodiment.
Detailed Description
The following description and the drawings sufficiently illustrate specific embodiments herein to enable those skilled in the art to practice them. Portions and features of some embodiments may be included in, or substituted for, those of others. The scope of the embodiments herein includes the full scope of the claims, as well as all available equivalents of the claims. The terms "first," "second," and the like herein are used merely to distinguish one element from another element and do not require or imply any actual relationship or order between the elements. Indeed the first element could also be termed a second element and vice versa. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a structure, apparatus, or device that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such structure, apparatus, or device. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a structure, apparatus or device that comprises the element. Various embodiments are described herein in a progressive manner, each embodiment focusing on differences from other embodiments, and identical and similar parts between the various embodiments are sufficient to be seen with each other.
The terms "longitudinal," "transverse," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like herein refer to an orientation or positional relationship based on that shown in the drawings, merely for ease of description herein and to simplify the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operate in a particular orientation, and thus are not to be construed as limiting the invention. In the description herein, unless otherwise specified and limited, the terms "mounted," "connected," and "coupled" are to be construed broadly, and may be, for example, mechanically or electrically coupled, may be in communication with each other within two elements, may be directly coupled, or may be indirectly coupled through an intermediary, as would be apparent to one of ordinary skill in the art.
Herein, unless otherwise indicated, the term "plurality" means two or more.
Herein, the character "/" indicates that the front and rear objects are an or relationship. For example, A/B represents: a or B.
Herein, the term "and/or" is an association relation describing an object, meaning that three relations may exist. For example, a and/or B, represent: a or B, or, A and B.
FIG. 1 illustrates one embodiment of the integrated energy system synchronization measurement system of the present invention.
In this embodiment, the integrated energy system synchronization measurement system includes: the system comprises a basic data acquisition unit, a synchronous measurement unit and an energy comprehensive dispatching center.
The basic data acquisition unit is used for acquiring sampling data of each energy subsystem, and comprises sensors, such as a voltage transformer, a current transformer, a temperature transmitter, a pressure transmitter, a volume flowmeter and the like, which are respectively arranged in the energy subsystems such as a power network, a cooling/heating network, a natural gas network and the like.
And a synchronous measurement unit (Synchronous Measurement Unit, SMU) is internally provided with a synchronous measurement algorithm, and the synchronous measurement algorithm calculates sampling data of the slow-change system at the synchronous moment according to the sampling data of the slow-change system acquired by the basic data acquisition unit. According to the sampling data of the slow-change system at the synchronous moment obtained by the calculation of the synchronous measuring unit, the energy data of the slow-change system, such as the thermal power of a natural gas network and the thermal power of a cooling/heating network, can be calculated. The energy data of the slow-change system can be obtained by calculation of the synchronous measurement unit, and the synchronous measurement unit transmits the energy data to the energy comprehensive dispatching center. The energy data of the slow-change system can also be obtained by calculation of an energy comprehensive dispatching center, the synchronous measuring unit transmits the sampling data of the slow-change system at the synchronous moment to the energy comprehensive dispatching center, and the energy comprehensive dispatching center obtains the energy data of the slow-change system according to the sampling data of the slow-change system at the synchronous moment.
Optionally, the sampling data obtained by the basic data acquisition unit, or the sampling data of the slow-change system obtained by the synchronous measurement unit at the synchronous moment, or the energy data of the slow-change system obtained by the synchronous measurement unit can be used as the output signal of the synchronous measurement unit to be transmitted to the energy comprehensive dispatching center. For example, the sampled values of voltage, current, temperature, pressure and flow rate or the calculated values of electric power and thermal power can be selected as the output signals of the synchronous measuring unit.
Optionally, the synchronous measurement units of the energy subsystems are in communication with the energy comprehensive dispatching center through a regional communication network. Optionally, the regional communication network is a dual-layer ring network formed by optical fibers.
Optionally, the synchronous measurement algorithm performs synchronous measurement calculation on actual sampling data of the slow-change system according to a sampling interval of the fast-change system, and calculates sampling data of the slow-change system at a synchronous moment.
Optionally, the synchronous measurement algorithm performs synchronous measurement calculation on actual sampling data of the slow-change system according to a uniform sampling interval set by the energy comprehensive dispatching center, and calculates sampling data of the slow-change system at a synchronous moment.
The sensing data of the quick-change system has high precision and high sampling rate, and has good synchronism and real-time performance, and the synchronous measurement unit can directly obtain the sampling data of the quick-change system at the synchronous moment through the basic data acquisition unit, or the synchronous measurement unit can also obtain the sampling data of the quick-change system at the synchronous moment through the calculation of the synchronous measurement algorithm.
The embodiment of the invention constructs the synchronous measurement system suitable for the comprehensive energy system, the system can synchronously measure diversified data of all subsystems in the comprehensive energy system, and the data have the same sampling interval and precision, so that basic sampling data of an electric power network, a cooling/heating network and a natural gas network are effectively fused, the high sharing of the comprehensive energy system is realized, and a reliable basis is provided for the efficient and accurate regulation and control of the comprehensive energy system.
In one embodiment, as shown in fig. 2, the synchronization measurement algorithm includes the following steps:
According to actual sampling data and synchronous time of the slow-varying system, obtaining a fitting function of the slow-varying system, wherein the setting basis of the fitting function coefficients is that the fitting value error of the fitting function is minimum;
And calculating sampling data of the slow-change system at the synchronous moment according to the fitting function.
Optionally, the step of obtaining the fitting function of the slow-varying system according to the actual sampling data and the synchronization time of the slow-varying system includes:
Step (1), defining at the synchronous time Fitting function in neighborhood/>The method comprises the following steps:
wherein, For synchronizing time/>Sampling points in the neighborhood, which are given sampling points,/>Representing an estimated value of the fitting function, b i (t) being the base element of the fitting function, i=1, 2,..m, m being the number of base elements, k i (t) being the coefficient of the base element,/>
And (2) determining a basal element expression.
Optionally, when the base element b (t) is a single expression, the base element expression is:
bT＝(1,t) m＝2 (2)
bT＝(1,t,t2) m＝3 (3)
bT＝(1,t,t2,t3) m＝4 (4)
similarly, the base element expression can be obtained when m is other numerical value.
Step (3), defining an error function of the fitting function as:
Wherein f (t j) is the sampling data at time t j in the slowly varying system, the sampling data at time t j is the known sampling data, j=1, 2,3, …, N sampling points are Discrete points in the immediate neighborhood,/>A weighting function for fitting the square error of the function fitting value and the sampled data at time t j, centered at time t j, has a strong supporting effect on the sampled points at the synchronous time, and is schematically shown in fig. 3.
Optionally, to ensure strong support of the weighting function, positive in the support domain, otherwise 0, the weighting function satisfies:
where Δt is the support domain radius of the weighting function.
In the support domain of the weighting function, the fitting function fitting value decreases as the distance between the fitting point and the known point increases. Because the weighting function is automatically segmented, the sampling data can be locally fitted without dividing the synchronous time interval.
Alternatively, the error function is expressed in matrix form:
Δ＝(Bk-f)TW(Bk-f) (7)
wherein,
f＝(f1,f2,...,fN)T＝(f(t1),f(t2),...,f(tN))T (8)
Alternatively, the weighting function may use a normal distribution function:
Alternatively, the weighting function may use a gaussian weight function:
Alternatively, the weighting function may use a spline function:
In the above-described alternative embodiments of the present invention, For the relative radius, Δt is the radius of the supporting domain, σ e [1,9] is the shape parameter, and adjusting the size of the shape parameter can change the rate of change of the weighting function over the supporting domain.
Step (4), solving the error function pairAnd let it be 0, the base element coefficient corresponding to the minimum value point of the fitting function error can be obtained:
Namely:
wherein,
The coefficient which minimizes the error of the fitting value of the fitting function is calculated as follows:
And (5) obtaining a fitting function according to the obtained coefficient, substituting the needed synchronous moment, and calculating sampling data of the synchronous moment.
The synchronous measurement algorithm of the present invention is further described below by taking thermodynamic system temperature data as an example.
Given a sampling interval of Δt 1, a corresponding temperature of θ＝(θ1,θ2,...,θN)T＝(θ(t1),θ(t2),...,θ(tN))T, and a corresponding given sampling time of t= (t 1,t2,...,tN)T), a required sampling interval of Δt 1/2, and a required synchronization time of t' = (t 1′,t2′,...,tN′)T), the given sampling time and synchronization time being schematically shown in fig. 4.
Step (1), defining a fitting function of global approximation as theta (t), then at the synchronous momentLocal approximation function in the neighborhood/>The method comprises the following steps:
wherein, This fitting function is represented as an estimate of temperature, b i (t) (i=1, 2.,; m) is the base elements of the fitting function, m is the number of the base elements, and k i (t) is the coefficient of the base elements.
And (2) determining a basal element expression. The quadratic monomer is used as the base element of the temperature fitting function, m=3, i.e. b T＝(1,t,t2).
Step (3), defining an error function of the temperature fitting function as:
wherein θ (t j)∈θ,j＝1,2,3,…,N,tj ε t, In order to fit a weighted function of the square error of the temperature value and the known temperature value, the weighted function has a strong supporting effect on the sampling points at the synchronous moment, and the center of the weighted function is positioned at the moment t j.
The error function is expressed in matrix form:
Δ＝(Bk-θ)TW(Bk-θ) (25)
The selected weighting function is a gaussian weighting function:
wherein, Let σ=3, where Δt is the support domain radius and σ is the shape parameter.
Step (4), solving an error function pair of the temperature fitting functionAnd let it be 0, the base element coefficient corresponding to the minimum point of the error function can be obtained:
Namely:
wherein,
The coefficient that minimizes the error in the fitting value of the fitting function is:
step 5, according to Calculation/>And utilize/>And calculating sampling data of the required synchronization time.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 5. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used to store static information and dynamic information data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by the processor to implement the steps of the synchronous measurement algorithm described above.
It will be appreciated by those skilled in the art that the structure shown in FIG. 5 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer device is also provided, comprising a memory having a computer program stored therein and a processor that implements the steps of the synchronous metrology algorithm described above when the computer program is executed.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon which, when executed by a processor, implements the steps in the synchronous metrology algorithm described above.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, or the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory. By way of illustration, and not limitation, RAM can be in various forms such as static random access memory (Static RandomAccess Memory, SRAM) or dynamic random access memory (Dynamic RandomAccess Memory, DRAM), etc.
The present invention is not limited to the structure that has been described above and shown in the drawings, and various modifications and changes can be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.
Claims (22)
1. A synchronous measurement algorithm, comprising the steps of:
According to the actual sampling data and the synchronous time of the slow-changing system, obtaining a fitting function of the slow-changing system comprises the following steps:
Step (1), defining at the synchronous time Fitting function in neighborhood/>The method comprises the following steps:
wherein, For synchronizing time/>Sampling points in the neighborhood,/>Representing an estimated value of the fitting function, b i (t) being the base elements of the fitting function, i=1, 2,..m, m being the number of base elements, k i (t) being the coefficients of the base elements,
Step (2), determining a basal element expression;
Step (3), defining an error function of the fitting function as:
Wherein f (t j) is the sampled data at time t j in the slowly varying system, j=1, 2,3, …, N sampling points are Discrete points in the immediate neighborhood,/>A weighting function for fitting the function fitting value to the square error of the sampled data at time t j;
Step (4), solving the error function pair Obtaining a base element coefficient corresponding to a minimum value point of the fitting function error by making the deviation of the fitting function error be 0, and calculating a coefficient which enables the fitting function fitting value error to be minimum;
Step (5), obtaining a fitting function according to the obtained coefficient, substituting the synchronous moment into the fitting function, and calculating sampling data of the synchronous moment;
And calculating sampling data of the slow-change system at the synchronous moment according to the fitting function.
2. The synchronization measurement algorithm of claim 1, wherein,
The calculation basis of the fitting function coefficients is as follows: so that the error of the fitting value of the fitting function is minimized.
3. The synchronization measurement algorithm according to claim 1, wherein the base element b (t) is a single term.
4. The synchronization measurement algorithm of claim 1, wherein,
Representing the error function as a matrix form:
Δ= (Bk-f) T W (Bk-f) (7) wherein,
f＝(f1,f2,...,fN)T＝(f(t1),f(t2),...,f(tN))T(8)
5. The synchronization measurement algorithm of claim 1, wherein,
The weighting function satisfies:
Δt is the support domain radius of the weighting function.
6. The synchronization measurement algorithm of claim 5, wherein,
The weighting function uses a normal distribution function:
wherein, Sigma E [1,9] is a shape parameter for the relative radius.
7. The synchronization measurement algorithm of claim 5, wherein,
The weighting function uses a gaussian weight function:
wherein, Sigma E [1,9] is a shape parameter for the relative radius.
8. The synchronization measurement algorithm of claim 5, wherein,
The weighting function uses spline functions:
wherein, Is the relative radius.
9. The synchronization measurement algorithm of claim 4, wherein,
The base element coefficients corresponding to the minimum value points of the fitting function errors obtained in the step (4) are as follows:
Namely:
wherein,
The coefficient that minimizes the error of the fitting value of the fitting function is:
10. The synchronization measurement algorithm of claim 1, wherein,
The synchronous measurement algorithm calculates sampling data of the slow-change system at the synchronous moment according to the sampling interval of the fast-change system or according to the uniform sampling interval set by the energy comprehensive scheduling center.
11. A synchronous measurement system for an integrated energy system, comprising: the system comprises a basic data acquisition unit, a synchronous measurement unit and an energy comprehensive dispatching center;
the basic data acquisition unit is used for acquiring sampling data of each energy subsystem;
The synchronous measurement unit is internally provided with a1 synchronous measurement algorithm, and the synchronous measurement algorithm obtains a fitting function of the slow-change system according to actual sampling data and synchronous time of the slow-change system, and the method comprises the following steps: step (1), defining at the synchronous time Fitting function in neighborhoodThe method comprises the following steps:
wherein, For synchronizing time/>Sampling points in the neighborhood,/>Representing an estimated value of the fitting function, b i (t) being the base elements of the fitting function, i=1, 2,..m, m being the number of base elements, k i (t) being the coefficients of the base elements,
Step (2), determining a basal element expression;
Step (3), defining an error function of the fitting function as:
Wherein f (t j) is the sampled data at time t j in the slowly varying system, j=1, 2,3, …, N sampling points are Discrete points in the immediate neighborhood,/>A weighting function for fitting the function fitting value to the square error of the sampled data at time t j;
Step (4), solving the error function pair Obtaining a base element coefficient corresponding to a minimum value point of the fitting function error by making the deviation of the fitting function error be 0, and calculating a coefficient which enables the fitting function fitting value error to be minimum;
Step (5), obtaining a fitting function according to the obtained coefficient, substituting the synchronous moment into the fitting function, and calculating sampling data of the synchronous moment;
According to the fitting function, calculating sampling data of the slow-change system at the synchronous moment;
And the output signal of the synchronous measurement unit is transmitted to an energy comprehensive dispatching center.
12. The system for simultaneous measurement of integrated energy systems of claim 11, wherein,
The calculation basis of the fitting function coefficients is as follows: so that the error of the fitting value of the fitting function is minimized.
13. The system for simultaneous measurement of integrated energy systems of claim 11, wherein,
The base element b (t) is a single formula.
14. The system for simultaneous measurement of integrated energy systems of claim 11, wherein,
Representing the error function as a matrix form:
Δ= (Bk-f) T W (Bk-f) (7) wherein,
f＝(f1,f2,...,fN)T＝(f(t1),f(t2),...,f(tN))T(8)
15. The system for simultaneous measurement of integrated energy systems of claim 11, wherein,
The weighting function satisfies:
Δt is the support domain radius of the weighting function.
16. The system for simultaneous measurement of integrated energy systems of claim 15, wherein,
The weighting function uses a normal distribution function:
wherein, Sigma E [1,9] is a shape parameter for the relative radius.
17. The system for simultaneous measurement of integrated energy systems of claim 15, wherein,
The weighting function uses a gaussian weight function:
wherein, Sigma E [1,9] is a shape parameter for the relative radius.
18. The system for simultaneous measurement of integrated energy systems of claim 15, wherein,
The weighting function uses spline functions:
wherein, Is the relative radius.
19. The system for simultaneous measurement of integrated energy systems of claim 14, wherein,
The base element coefficients corresponding to the minimum value points of the fitting function errors obtained in the step (4) are as follows:
Namely:
wherein,
The coefficient that minimizes the error of the fitting value of the fitting function is:
20. the system for simultaneous measurement of integrated energy systems of claim 11, wherein,
And the synchronous measurement unit calculates the energy data of the slow-change system according to the sampling data of the slow-change system at the synchronous moment obtained by calculation.
21. The system for simultaneous measurement of integrated energy systems of claim 11, wherein,
And the synchronous measurement unit transmits the sampling data of the slow-change system at the synchronous moment to the energy comprehensive dispatching center, and the energy comprehensive dispatching center calculates and obtains the energy data of the slow-change system according to the sampling data of the slow-change system at the synchronous moment.
22. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the synchronization measurement algorithm of any one of claims 1 to 10 when the computer program is executed.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109190789A (en) * | 2018-07-19 | 2019-01-11 | 清华大学 | Long-term wind power power forecasting method, device, computer equipment and storage medium |
| CN111811398A (en) * | 2020-06-28 | 2020-10-23 | 上海大学 | Multi-surface measurement method based on phase shift characteristic polynomial high-precision fitting |
| CN112073460A (en) * | 2020-08-03 | 2020-12-11 | 国网山东省电力公司电力科学研究院 | Data acquisition unit, data transmission method and comprehensive energy monitoring system |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109190789A (en) * | 2018-07-19 | 2019-01-11 | 清华大学 | Long-term wind power power forecasting method, device, computer equipment and storage medium |
| CN111811398A (en) * | 2020-06-28 | 2020-10-23 | 上海大学 | Multi-surface measurement method based on phase shift characteristic polynomial high-precision fitting |
| CN112073460A (en) * | 2020-08-03 | 2020-12-11 | 国网山东省电力公司电力科学研究院 | Data acquisition unit, data transmission method and comprehensive energy monitoring system |
Non-Patent Citations (2)
| Title |
|---|
| 交流电电气参量高精度测量的加权算法;张介秋, 陈砚圃, 梁昌洪, 韩峰岩;仪器仪表学报;20050415(02);全文 * |
| 门电路延时查找表的凸平滑算法;刘学欣;陆伟成;;计算机工程与应用;20080901(25);全文 * |
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