CN115796061B - Single-core cable dynamic current-carrying capacity prediction method and system considering load fluctuation characteristics - Google Patents
Single-core cable dynamic current-carrying capacity prediction method and system considering load fluctuation characteristics Download PDFInfo
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- CN115796061B CN115796061B CN202310077029.9A CN202310077029A CN115796061B CN 115796061 B CN115796061 B CN 115796061B CN 202310077029 A CN202310077029 A CN 202310077029A CN 115796061 B CN115796061 B CN 115796061B
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Abstract
The invention provides a single-core cable dynamic current-carrying capacity prediction method and system considering load fluctuation characteristics, which are characterized in that firstly, the temperature rise and the current-carrying capacity of a power cable are calculated according to IEC60287 standard, secondly, the load fluctuation is subjected to parting treatment by adopting a rain flow counting method, the fluctuation type is identified, the sudden fluctuation and trend fluctuation in the load fluctuation are divided, the power load capacity of environmental interference is subjected to denoising treatment, and finally, the power cable current-carrying capacity after denoising is predicted by adopting a differential integration moving average autoregressive (ARIMA) model. According to the method, the rain flow counting method is adopted to conduct parting treatment on load fluctuation, the influence of load fluctuation characteristics on the overall operation trend of the load in the power cable current-carrying capacity prediction is reduced, then the ARIMA model is adopted to predict dynamic current-carrying capacity, the past value of the random time sequence is utilized to infer a future value, the time sequence of power load data is concerned, the calculated amount is small, and meanwhile, the accuracy of short-term load prediction can be remarkably improved.
Description
Technical Field
The invention belongs to the technical field of cable current-carrying capacity prediction, and particularly relates to a single-core cable dynamic current-carrying capacity prediction method and system considering load fluctuation characteristics.
Background
The high-speed development of national economy in China requires stable and reliable electric energy supply, with the continuous development of national economy, urban electricity consumption is increased year by year, and a single-core cable is used as important power transmission equipment in a power system and plays an indispensable role in transmitting electric energy and transmitting signals. As the power load increases year by year, the power transmission corridor is increasingly tense, and the problem of load peak-valley difference increase can be effectively relieved by reasonably excavating the current carrying capacity of the existing power cable. The laying conditions of the single-core cable are as follows: the cable duct can bear certain mechanical external force and tension in the indoor, tunnel and cable duct, can be directly buried and laid with armors, and can also be laid in various pipes comprising magnetic pipelines. The direct-buried laying of the single-core cable has the advantages that: the laying is convenient, and the materials and the labor are saved. However, as the soil influences the heat dissipation of the cable, the insulation aging of the power cable can be accelerated in a soil environment with higher temperature after long-term operation, so that the maximum current-carrying capacity of the cable is reduced. Therefore, the temperature rise of the single-core cable under direct burial is accurately calculated, the relation between the temperature rise of the single-core cable and the current-carrying capacity is explored, a scientific and reasonable cable current-carrying capacity prediction method is provided, the operation reliability of the power system is improved, and a reference is provided for the power dispatching department.
The existing calculation methods of cable temperature rise and current-carrying capacity include an analysis method, a hot-path model method (IEC 60287 standard), a numerical calculation method and the like. The prior art mainly researches a single cable steady-state and transient temperature rise acquisition method and a power cable intermediate joint temperature calculation method, but rarely considers a cable current-carrying capacity calculation method under power load fluctuation. In actual operation, the power load is continuously changed and is accompanied by interference factors, and the prior art is difficult to adapt to the power load.
Disclosure of Invention
In view of the above, the invention aims to solve the problem that the existing calculation method of cable temperature rise and current-carrying capacity is difficult to be applied to calculation of cable current-carrying capacity under power load fluctuation.
In order to solve the technical problems, the invention provides the following technical scheme:
in a first aspect, the present invention provides a method for predicting the dynamic current-carrying capacity of a single-core cable in consideration of load fluctuation characteristics, which is suitable for predicting the current-carrying capacity of the single-core cable under direct-buried installation, and includes the following steps:
calculating the steady-state temperature rise and the current-carrying capacity of the power cable in a first period of time according to IEC60287 standard, and obtaining a series of time sequence data calculated values about the current-carrying capacity;
collecting current waveforms of the power cable in a second period, adopting a rain flow counting method to perform parting treatment on load fluctuation in the current waveforms, identifying fluctuation types and dividing the load fluctuation into normal fluctuation or abnormal fluctuation;
screening out abnormal fluctuation in the current waveform, and obtaining a series of time sequence data actual measurement values related to current carrying capacity according to the processed current waveform;
carrying out current-carrying capacity prediction of the power cable by adopting a differential integration moving average autoregressive model, and verifying the effectiveness of current-carrying capacity calculation of the power cable on the basis of a time sequence data calculated value and an actual measured value of the current-carrying capacity;
and calculating the current-carrying capacity of the power cable according to IEC60287 standard based on the historical data of the power cable, taking the calculated current-carrying capacity of the power cable as a training sample, learning sample data according to a differential integration moving average autoregressive model, and predicting the dynamic current-carrying capacity of the power cable in a future period.
Further, verifying the validity of the power cable current-carrying capacity calculation specifically includes:
taking the time sequence data calculated value of the current-carrying capacity in the first period as sample data;
and taking the actual measurement value of the time sequence data of the current-carrying capacity in the second period as a comparison group, and carrying out current-carrying capacity prediction of the power cable by utilizing a differential integration moving average autoregressive model to obtain a current-carrying capacity predicted value in the first period, and verifying the effectiveness of current-carrying capacity calculation of the power cable based on the current-carrying capacity predicted value and the calculated value.
Further, for a direct-buried single-core cable, the heat conduction between the soil and the cable is calculated using the following formula:
in the method, in the process of the invention,
temperature in K;Tis thermal resistance, and has the unit of K ∙ m/W;Wthe unit is J/m for heat source power;Qthe heat capacity is J/K; />
Is a thermal time constant, and has the unit of s.
Further, for a single loop consisting of isolated laid single cables or three single cables, the current carrying capacity at the time of external thermal resistance change caused by drying of the surrounding soil area is calculated according to the following formula:
wherein I represents a current flowing through one conductor, and the unit is A;
a conductor temperature rise above ambient temperature in K;Rindicating the highest operating temperature down-conductionAlternating current resistance of unit length of body, the unit is omega/m; />
Represents the dielectric loss around the conductor per unit length in W/m; />
The thermal resistance of a conductor and a metal sleeve in unit length is expressed as K.m/W; />
The unit length thermal resistance of the lining layer between the metal sleeve and the armor is expressed as K.m/W; />
The thermal resistance of the outer protective layer of the cable per unit length is expressed, and the unit is K.m/W; />
The thermal resistance of unit length between the surface of the cable and the surrounding medium is expressed as K.m/W; />
The number of conductors carrying a load in the cable; />
Representing the ratio of the cable metal sheath loss to the total loss of all conductors; />
Representing the ratio of cable armor loss to total loss of all conductors; />
Represents the ratio of the thermal resistivity of the dry and wet soil domains; />
The critical temperature rise of the soil, namely the temperature rise of the boundary between the dry soil and the wet soil which is higher than the ambient temperature, is expressed as K; />
The critical temperature of the soil, i.e. the temperature at the boundary of dry and wet soil, is expressed in c.
Further, in the process of classifying the load fluctuation in the current waveform by adopting the rain flow counting method, the evaluation indexes of the load fluctuation specifically comprise:
the trend fluctuation starting and stopping time, the starting and stopping power of a load trend fluctuation sequence, the duration relative time of trend fluctuation, the duration relative amplitude of trend fluctuation, the trend fluctuation inclination rate, the occurrence frequency of burst fluctuation in trend fluctuation, the trend fluctuation average value and the trend fluctuation standard deviation.
In a second aspect, the present invention provides a single-core cable dynamic current-carrying capacity prediction system considering load fluctuation characteristics, which is suitable for single-core cable current-carrying capacity prediction under direct-buried application, and includes:
the verification unit is used for calculating the steady-state temperature rise and the current-carrying capacity of the power cable in the first period of time according to IEC60287 standard to obtain a series of time sequence data calculated values related to the current-carrying capacity;
the method comprises the steps of collecting a current waveform of a power cable in a second period, classifying load fluctuation in the current waveform by adopting a rain flow counting method, identifying a fluctuation type and dividing the load fluctuation into normal fluctuation or abnormal fluctuation;
the method is also used for screening out abnormal fluctuation in the current waveform, and obtaining a series of time sequence data actual measurement values related to the current carrying capacity according to the processed current waveform;
the method is also used for predicting the current-carrying capacity of the power cable by adopting a differential integration moving average autoregressive model, and verifying the effectiveness of the current-carrying capacity calculation of the power cable based on a time sequence data calculated value and an actual measured value of the current-carrying capacity;
the prediction unit is used for calculating the current-carrying capacity of the power cable according to IEC60287 standard based on the historical data of the power cable, taking the calculated current-carrying capacity of the power cable as a training sample, learning sample data according to a differential integration moving average autoregressive model and predicting the dynamic current-carrying capacity of the power cable in a period in the future.
Further, in the verification unit, verifying the validity of the power cable current-carrying capacity calculation specifically includes:
taking the time sequence data calculated value of the current-carrying capacity in the first period as sample data;
and taking the actual measurement value of the time sequence data of the current-carrying capacity in the second period as a comparison group, and carrying out current-carrying capacity prediction of the power cable by utilizing a differential integration moving average autoregressive model to obtain a current-carrying capacity predicted value in the first period, and verifying the effectiveness of current-carrying capacity calculation of the power cable based on the current-carrying capacity predicted value and the calculated value.
Further, in the verification unit, for the direct-buried single-core cable, the heat conduction between the soil and the cable is calculated using the following formula:
in the method, in the process of the invention,
temperature in K;Tis thermal resistance, and has the unit of K ∙ m/W;Wthe unit is J/m for heat source power;Qthe heat capacity is J/K; />
Is a thermal time constant, and has the unit of s.
Further, in the verification unit, for a single loop consisting of a single cable or three single cables laid in isolation, the current-carrying capacity at the time of external thermal resistance change caused by drying of the surrounding soil area is calculated according to the following formula:
wherein I represents a current flowing through one conductor, and the unit is A;
a conductor temperature rise above ambient temperature in K;Rthe alternating current resistance of the conductor unit length at the highest working temperature is shown in omega/m; />
Represents the dielectric loss around the conductor per unit length in W/m; />
The thermal resistance of a conductor and a metal sleeve in unit length is expressed as K.m/W; />
The unit length thermal resistance of the lining layer between the metal sleeve and the armor is expressed as K.m/W; />
The thermal resistance of the outer protective layer of the cable per unit length is expressed, and the unit is K.m/W; />
The thermal resistance of unit length between the surface of the cable and the surrounding medium is expressed as K.m/W; />
The number of conductors carrying a load in the cable; />
Representing the ratio of the cable metal sheath loss to the total loss of all conductors; />
Representing the ratio of cable armor loss to total loss of all conductors; />
Represents the ratio of the thermal resistivity of the dry and wet soil domains; />
The critical temperature rise of the soil, namely the temperature rise of the boundary between the dry soil and the wet soil which is higher than the ambient temperature, is expressed as K; />
Indicating the critical temperature of the soil, i.e. the temperature at the boundary of dry and wet soilThe unit is in degrees Celsius.
Further, in the verification unit, in the step of classifying the load fluctuation in the current waveform by adopting the rain flow counting method, the evaluation indexes of the load fluctuation specifically include:
the trend fluctuation starting and stopping time, the starting and stopping power of a load trend fluctuation sequence, the duration relative time of trend fluctuation, the duration relative amplitude of trend fluctuation, the trend fluctuation inclination rate, the occurrence frequency of burst fluctuation in trend fluctuation, the trend fluctuation average value and the trend fluctuation standard deviation.
In summary, the invention provides a single-core cable dynamic current-carrying capacity prediction method and a system considering load fluctuation characteristics, which are characterized in that firstly, the temperature rise and the current-carrying capacity of a power cable are calculated according to IEC60287 standard, secondly, the load fluctuation is subjected to parting treatment by adopting a rain flow counting method, the fluctuation type is identified, the sudden fluctuation and trend fluctuation in the load fluctuation are divided, the noise removal treatment is carried out on the power load capacity of environmental interference, and finally, the power cable current-carrying capacity after noise removal is predicted by adopting a differential integration moving average autoregressive (ARIMA) model. According to the method, the rain flow counting method is adopted to conduct parting treatment on load fluctuation, the influence of load fluctuation characteristics on the overall operation trend of the load in the power cable current-carrying capacity prediction is reduced, then the ARIMA model is adopted to predict dynamic current-carrying capacity, the past value of the random time sequence is utilized to infer a future value, the time sequence of power load data is concerned, the calculated amount is small, and meanwhile, the accuracy of short-term load prediction can be remarkably improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a single-core cable dynamic current-carrying capacity prediction method considering load fluctuation characteristics according to an embodiment of the present invention;
fig. 2 is a graph comparing a predicted value and an actual value of current capacity obtained by using the method provided by the present invention in an example provided by the present invention.
Detailed Description
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is apparent that the embodiments described below are only some embodiments of the present invention, not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The existing calculation methods of cable temperature rise and current-carrying capacity include an analysis method, a hot-path model method (IEC 60287 standard), a numerical calculation method and the like. The prior art mainly researches a single cable steady-state and transient temperature rise acquisition method and a power cable intermediate joint temperature calculation method, but rarely considers a cable current-carrying capacity calculation method under power load fluctuation. In actual operation, the power load is continuously changed and is accompanied by interference factors, and the prior art is difficult to adapt to the power load.
Based on the method, the single-core cable dynamic current-carrying capacity prediction method and the system taking the load fluctuation characteristic into consideration are provided.
An embodiment of a single-core cable dynamic current-carrying capacity prediction method taking load fluctuation characteristics into consideration according to the present invention is described in detail below.
Referring to fig. 1, the present embodiment provides a single-core cable dynamic current-carrying capacity prediction method considering load fluctuation characteristics, which includes the following steps:
s100: and calculating the steady-state temperature rise and the current-carrying capacity of the power cable in the first period of time according to IEC60287 standard, and obtaining a series of time sequence data calculated values about the current-carrying capacity.
The heat transfer mode includes heat conduction, heat convection and heat radiation. For a direct-buried single-core cable, the heat transfer mode between the cable and soil is mainly heat conduction, and the heat balance process is established between the cable and the soil, and can be represented by the following Fourier heat transfer law:
in the method, in the process of the invention,
temperature in K;Tis thermal resistance, and has the unit of K ∙ m/W;Wthe unit is J/m for heat source power;Qthe heat capacity is J/K; />
Is a thermal time constant, and has the unit of s.
For an isolated laid single cable (multi-core) or three single-core cable single loop, the current-carrying capacity calculation when the surrounding soil area becomes dry and the external thermal resistance changes is given by the following formula:
wherein I represents a current flowing through one conductor, and the unit is A;
a conductor temperature rise above ambient temperature in K;Rthe alternating current resistance of the conductor unit length at the highest working temperature is shown in omega/m; />
Represents the dielectric loss around the conductor per unit length in W/m; />
The thermal resistance of a conductor and a metal sleeve in unit length is expressed as K.m/W; />
The unit length thermal resistance of the lining layer between the metal sleeve and the armor is expressed as K.m/W; />
The thermal resistance of the outer protective layer of the cable per unit length is expressed, and the unit is K.m/W; />
The thermal resistance of unit length between the surface of the cable and the surrounding medium is expressed as K.m/W; />
The number of conductors carrying a load in the cable; />
Representing the ratio of the cable metal sheath loss to the total loss of all conductors; />
Representing the ratio of cable armor loss to total loss of all conductors; />
Represents the ratio of the thermal resistivity of the dry and wet soil domains; />
The critical temperature rise of the soil, namely the temperature rise of the boundary between the dry soil and the wet soil which is higher than the ambient temperature, is expressed as K; />
The critical temperature of the soil, i.e. the temperature at the boundary of dry and wet soil, is expressed in c.
The IEC60287 standard gives reference values for environmental temperature and soil thermal resistance in different countries. Based on IEC60287 standard, the steady-state temperature rise and the current-carrying capacity of the power cable in the current environment can be calculated by combining the calculation formula of the steady-state temperature rise and the current-carrying capacity.
S200: and collecting current waveforms of the power cable in a second period, performing parting treatment on load fluctuation in the current waveforms by adopting a rain flow counting method, identifying the fluctuation type and dividing the load fluctuation into normal fluctuation or abnormal fluctuation.
The concentration degree and the position amount of the power load fluctuation sequence are used for the power load fluctuation sequenceThe four angles of the dispersion degree and the shape characteristic are used for classifying and sorting the power load waveform, so that the operation efficiency is improved, and all the characteristics of the power load waveform are reflected in multiple angles. For the waveform of the load fluctuation, the embodiment extracts 8 evaluation indexes describing the waveform based on the characteristics of the fluctuation trend, namely the start-stop time of the fluctuation trend
、/>
The method comprises the steps of carrying out a first treatment on the surface of the Load trend fluctuation sequence start-stop power +.>
、/>
The method comprises the steps of carrying out a first treatment on the surface of the Trend fluctuation duration relative duration +.>
The method comprises the steps of carrying out a first treatment on the surface of the Trend fluctuation continuous relative amplitude +.>
The method comprises the steps of carrying out a first treatment on the surface of the Trend fluctuation Tilt Rate->
The method comprises the steps of carrying out a first treatment on the surface of the Frequency of occurrence of sudden fluctuations in trend fluctuations +.>
The method comprises the steps of carrying out a first treatment on the surface of the And a two-dimensional statistical characteristic parameter, namely trend fluctuation average +.>
Standard deviation from trend fluctuation->
。/>
The expression is as follows:
for one load fluctuation, the above 8 index values are calculated, and when at least one of the index values exceeds a threshold value, the current fluctuation is determined to be an abnormal fluctuation. The threshold value of each index for abnormal fluctuation judgment is determined according to the actual situation.
S300: and screening out abnormal fluctuation in the current waveform, and obtaining a series of time sequence data actual measurement values related to the current carrying capacity according to the processed current waveform.
S400: and carrying out current-carrying capacity prediction of the power cable by adopting a differential integration moving average autoregressive model, and verifying the effectiveness of current-carrying capacity calculation of the power cable based on time sequence data calculated values and actual measured values of the current-carrying capacity.
It should be noted that, the differential integrated moving average autoregressive (ARIMA) model is one of time series analysis methods, and is commonly used for power load prediction, and the basic steps are as follows:
(1) And (5) checking stability, and if the stability passes, differential processing is not needed. When the ARIMA model is used for prediction, the time sequence must be stationary, and if it is a non-stationary sequence, it needs to be converted into a stationary sequence by difference.
(2) First order differential processing, if still not smooth, further differential processing is required. For non-stationary sequences, stationary sequences are obtained by one or several differential processes.
(3) And calculating a sample autocorrelation function and a partial autocorrelation function, and determining the order of the ARIMA model. The autocorrelation function reflects the correlation between values of the same sequence at different timings. The partial autocorrelation coefficient PACF is the correlation between the two variables (the present value and the lag value) strictly, and the interference of the intermediate random variable is eliminated.
Three parameters of ARIMA model can be determined from the sample data
Wherein, the method comprises the steps of, wherein,pis a partial autocorrelation coefficient, and is determined by a partial autocorrelation function;qis an autocorrelation coefficient, determined by an autocorrelation function;dthen the order.
(4) The single step predicts the electrical load. The ARIMA model is used to predict the electrical load.
(5) And (5) residual error checking.
And predicting the dynamic current-carrying capacity of the future cable by adopting an ARIMA model. The steady-state temperature rise calculated according to IEC60287 standard in step S100 is then used as sample data, the denoised load data in step S300 is used as a comparison group, prediction is performed through ARIMA model, the current-carrying capacity predicted value of the power cable is compared with the calculated value calculated according to IEC60287 standard, and the effectiveness of the calculation method is verified. Namely, the validity of the direct-buried single-core cable current-carrying capacity calculated based on IEC60287 standard is verified in the current environment.
S500: and calculating the current-carrying capacity of the power cable according to IEC60287 standard based on the historical data of the power cable, taking the calculated current-carrying capacity of the power cable as a training sample, learning sample data according to a differential integration moving average autoregressive model, and predicting the dynamic current-carrying capacity of the power cable in a future period.
On the premise of verifying the effectiveness of the calculation method, the current-carrying capacity of the power cable is calculated according to IEC60287 standard by combining cable history data to obtain a large number of calculation results, the calculation is recorded as a training sample of the ARIMA model, and the sample data is learned by the ARIMA model, so that the prediction of the dynamic current-carrying capacity of the power cable in a future period by the ARIMA model is realized. It can be understood that the sample data adopted in the ARIMA model is also required to be subjected to rain flow counting method to remove abnormal fluctuation, namely, the ARIMA model adopts the power load after denoising to carry out current-carrying capacity prediction.
For the prediction method provided by the embodiment, a single-core cable dynamic current-carrying capacity test is further developed, and the prediction accuracy of the ARIMA model is verified.
In one example, by applying different currents to the single-core cable, the first 90% of the test is used as a sample set, the experimental data of the last 10% is used as a verification set, and the prediction result pair obtained by performing prediction by using the prediction method of the embodiment is shown in fig. 2. As can be seen from fig. 2, the prediction method proposed in the present embodiment has higher prediction accuracy and faster calculation speed.
The embodiment provides a single-core cable dynamic current-carrying capacity prediction method considering load fluctuation characteristics, which comprises the steps of firstly calculating temperature rise and current-carrying capacity of a power cable according to IEC60287 standard, secondly adopting a rain flow counting method to conduct parting treatment on load fluctuation, identifying fluctuation types, dividing sudden fluctuation and trend fluctuation in the load fluctuation, conducting denoising treatment on power load capacity of environmental interference, and finally adopting a differential integration moving average autoregressive (ARIMA) model to predict the denoised current-carrying capacity of the power cable. According to the method, the rain flow counting method is adopted to conduct parting treatment on load fluctuation, the influence of load fluctuation characteristics on the overall operation trend of the load in the power cable current-carrying capacity prediction is reduced, then the ARIMA model is adopted to predict dynamic current-carrying capacity, the past value of the random time sequence is utilized to infer a future value, the time sequence of power load data is concerned, the calculated amount is small, and meanwhile, the accuracy of short-term load prediction can be remarkably improved.
The foregoing is a detailed description of an embodiment of a single-core cable dynamic current-carrying capacity prediction method taking into consideration load fluctuation characteristics of the present invention, and the following is a detailed description of an embodiment of a single-core cable dynamic current-carrying capacity prediction system taking into consideration load fluctuation characteristics of the present invention.
The embodiment provides a single-core cable dynamic current-carrying capacity prediction system considering load fluctuation characteristics, which is suitable for single-core cable current-carrying capacity prediction under direct-buried application, and comprises the following steps:
the verification unit is used for calculating the steady-state temperature rise and the current-carrying capacity of the power cable in the first period of time according to IEC60287 standard to obtain a series of time sequence data calculated values related to the current-carrying capacity;
the method comprises the steps of collecting a current waveform of a power cable in a second period, classifying load fluctuation in the current waveform by adopting a rain flow counting method, identifying a fluctuation type and dividing the load fluctuation into normal fluctuation or abnormal fluctuation;
the method is also used for screening out abnormal fluctuation in the current waveform, and obtaining a series of time sequence data actual measurement values related to the current carrying capacity according to the processed current waveform;
the method is also used for predicting the current-carrying capacity of the power cable by adopting a differential integration moving average autoregressive model, and verifying the effectiveness of the current-carrying capacity calculation of the power cable based on time sequence data calculated values and actual measured values of the current-carrying capacity.
In the verification unit, the verification of the validity of the power cable current-carrying capacity calculation specifically includes:
taking the time sequence data calculated value of the current-carrying capacity in the first period as sample data;
and taking the actual measurement value of the time sequence data of the current-carrying capacity in the second period as a comparison group, and carrying out current-carrying capacity prediction of the power cable by utilizing a differential integration moving average autoregressive model to obtain a current-carrying capacity predicted value in the first period, and verifying the effectiveness of current-carrying capacity calculation of the power cable based on the current-carrying capacity predicted value and the calculated value.
Further, in the verification unit, for the direct-buried single-core cable, the heat conduction between the soil and the cable is calculated using the following formula:
in the method, in the process of the invention,
temperature in K;Tis thermal resistance, and has the unit of K ∙ m/W;Wthe unit is J/m for heat source power;Qthe heat capacity is J/K; />
Is a thermal time constant, and has the unit of s.
Further, in the verification unit, for a single loop consisting of a single cable or three single cables laid in isolation, the current-carrying capacity at the time of external thermal resistance change caused by drying of the surrounding soil area is calculated according to the following formula:
wherein I represents a current flowing through one conductor, and the unit is A;
a conductor temperature rise above ambient temperature in K;Rthe alternating current resistance of the conductor unit length at the highest working temperature is shown in omega/m; />
Represents the dielectric loss around the conductor per unit length in W/m; />
The thermal resistance of a conductor and a metal sleeve in unit length is expressed as K.m/W; />
The unit length thermal resistance of the lining layer between the metal sleeve and the armor is expressed as K.m/W; />
The thermal resistance of the outer protective layer of the cable per unit length is expressed, and the unit is K.m/W; />
The thermal resistance of unit length between the surface of the cable and the surrounding medium is expressed as K.m/W; />
The number of conductors carrying a load in the cable; />
Representing the ratio of the cable metal sheath loss to the total loss of all conductors; />
Representing the ratio of cable armor loss to total loss of all conductors; />
Represents the ratio of the thermal resistivity of the dry and wet soil domains; />
The critical temperature rise of the soil, namely the temperature rise of the boundary between the dry soil and the wet soil which is higher than the ambient temperature, is expressed as K; />
The critical temperature of the soil, i.e. the temperature at the boundary of dry and wet soil, is expressed in c.
Further, in the verification unit, in the step of classifying the load fluctuation in the current waveform by adopting the rain flow counting method, the evaluation indexes of the load fluctuation specifically include:
the trend fluctuation starting and stopping time, the starting and stopping power of a load trend fluctuation sequence, the duration relative time of trend fluctuation, the duration relative amplitude of trend fluctuation, the trend fluctuation inclination rate, the occurrence frequency of burst fluctuation in trend fluctuation, the trend fluctuation average value and the trend fluctuation standard deviation.
The prediction unit is used for calculating the current-carrying capacity of the power cable according to IEC60287 standard based on the historical data of the power cable, taking the calculated current-carrying capacity of the power cable as a training sample, learning sample data according to a differential integration moving average autoregressive model and predicting the dynamic current-carrying capacity of the power cable in a period in the future.
It should be noted that, the prediction system provided in this embodiment is used to implement the prediction method provided in the foregoing embodiment, and specific settings of each unit are based on the complete implementation of the method, which is not described herein again.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the 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 scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. The single-core cable dynamic current-carrying capacity prediction method considering the load fluctuation characteristic is characterized by being suitable for single-core cable current-carrying capacity prediction under direct-buried arrangement and comprising the following steps of:
calculating the steady-state temperature rise and the current-carrying capacity of the power cable in a first period of time according to IEC60287 standard, and obtaining a series of time sequence data calculated values about the current-carrying capacity;
collecting a current waveform of a power cable in a second period, and adopting a rain flow counting method to perform parting treatment on load fluctuation in the current waveform, identifying a fluctuation type and dividing the load fluctuation into normal fluctuation or abnormal fluctuation, wherein the parting treatment is specifically to classify and sort the power load waveform through four angles of concentration degree, position quantity, dispersion degree and shape characteristic of a power load fluctuation sequence;
screening out abnormal fluctuation in the current waveform, and obtaining a series of time sequence data actual measurement values about current carrying capacity according to the processed current waveform;
carrying out current-carrying capacity prediction of the power cable by adopting a differential integration moving average autoregressive model, and verifying the effectiveness of current-carrying capacity calculation of the power cable based on the time sequence data calculated value and the actual measured value of the current-carrying capacity;
and calculating the current-carrying capacity of the power cable according to IEC60287 standard based on the historical data of the power cable, taking the calculated current-carrying capacity of the power cable as a training sample, learning sample data according to the differential integration moving average autoregressive model, and predicting the dynamic current-carrying capacity of the power cable in a future period.
2. The method for predicting dynamic current-carrying capacity of a single-core cable taking into consideration load fluctuation characteristics according to claim 1, wherein verifying the validity of the current-carrying capacity calculation of the power cable comprises:
taking the time sequence data calculated value of the current-carrying capacity in the first period as sample data;
and taking the actual measurement value of the current-carrying capacity of the time sequence data in the second period as a comparison group, and carrying out current-carrying capacity prediction of the power cable by utilizing a differential integration moving average autoregressive model to obtain a current-carrying capacity prediction value in the first period, and verifying the effectiveness of current-carrying capacity calculation of the power cable based on the current-carrying capacity prediction value and a calculation value.
3. The method for predicting dynamic current-carrying capacity of a single-core cable taking into consideration load fluctuation characteristics according to claim 1, wherein for a direct-buried single-core cable, the heat conduction between soil and cable is calculated by the following formula:
in the method, in the process of the invention,
temperature in K; />
Is thermal resistance, and has the unit of K ∙ m/W; />
The unit is J/m for heat source power; />
The heat capacity is J/K; />
Is a thermal time constant, and has the unit of s.
4. A method for predicting dynamic current-carrying capacity of a single-core cable in consideration of load fluctuation characteristics according to claim 3, wherein for a single loop consisting of a single cable or three single-core cables laid in isolation, the current-carrying capacity upon external thermal resistance change caused by drying in the surrounding soil area is calculated according to the following formula:
wherein I represents a current flowing through one conductor, and the unit is A;
a conductor temperature rise above ambient temperature in K; />
The alternating current resistance of the conductor unit length at the highest working temperature is shown in omega/m; />
Represents the dielectric loss around the conductor per unit length in W/m; />
The thermal resistance of a conductor and a metal sleeve in unit length is expressed as K.m/W; />
The unit length thermal resistance of the lining layer between the metal sleeve and the armor is expressed as K.m/W; />
The thermal resistance of the outer protective layer of the cable per unit length is expressed, and the unit is K.m/W; />
The thermal resistance of unit length between the surface of the cable and the surrounding medium is expressed as K.m/W; />
The number of conductors carrying a load in the cable; />
Representing the ratio of the cable metal sheath loss to the total loss of all conductors; />
Representing the ratio of cable armor loss to total loss of all conductors; />
Represents the ratio of the thermal resistivity of the dry and wet soil domains; />
The critical temperature rise of the soil, namely the temperature rise of the boundary between the dry soil and the wet soil which is higher than the ambient temperature, is expressed as K; />
The critical temperature of the soil, i.e. the temperature at the boundary of dry and wet soil, is expressed in c.
5. The method for predicting dynamic current-carrying capacity of a single-core cable taking load fluctuation characteristics into consideration according to claim 1, wherein in the step of classifying the load fluctuation in the current waveform by using a rain flow counting method, the evaluation index of the load fluctuation specifically comprises:
the trend fluctuation starting and stopping time, the starting and stopping power of a load trend fluctuation sequence, the duration relative time of trend fluctuation, the duration relative amplitude of trend fluctuation, the trend fluctuation inclination rate, the occurrence frequency of burst fluctuation in trend fluctuation, the trend fluctuation average value and the trend fluctuation standard deviation.
6. The single-core cable dynamic current-carrying capacity prediction system considering load fluctuation characteristics is characterized by being suitable for single-core cable current-carrying capacity prediction under direct-buried application and comprising:
the verification unit is used for calculating the steady-state temperature rise and the current-carrying capacity of the power cable in the first period of time according to IEC60287 standard to obtain a series of time sequence data calculated values related to the current-carrying capacity;
the method comprises the steps of collecting a current waveform of a power cable in a second period, classifying load fluctuation in the current waveform by adopting a rain flow counting method, identifying a fluctuation type, dividing the load fluctuation into normal fluctuation or abnormal fluctuation, and classifying the power load waveform by using four angles of concentration degree, position quantity, dispersion degree and shape characteristic of a power load fluctuation sequence;
the method is also used for screening out abnormal fluctuation in the current waveform, and obtaining a series of time sequence data actual measurement values related to current carrying capacity according to the processed current waveform;
the power cable current-carrying capacity prediction method is also used for predicting the current-carrying capacity of the power cable by adopting a differential integration moving average autoregressive model, and verifying the effectiveness of the power cable current-carrying capacity calculation based on the time sequence data calculated value and the actual measured value of the current-carrying capacity;
and the prediction unit is used for calculating the current-carrying capacity of the power cable according to IEC60287 standard based on the historical data of the power cable, taking the calculated current-carrying capacity of the power cable as a training sample, learning sample data according to the differential integration moving average autoregressive model and predicting the dynamic current-carrying capacity of the power cable in a period in the future.
7. The single-core cable dynamic current-carrying capacity prediction system taking into account load fluctuation characteristics according to claim 6, wherein in the verification unit, the validity of the power cable current-carrying capacity calculation is verified, specifically comprising:
taking the time sequence data calculated value of the current-carrying capacity in the first period as sample data;
and taking the actual measurement value of the current-carrying capacity of the time sequence data in the second period as a comparison group, and carrying out current-carrying capacity prediction of the power cable by utilizing a differential integration moving average autoregressive model to obtain a current-carrying capacity prediction value in the first period, and verifying the effectiveness of current-carrying capacity calculation of the power cable based on the current-carrying capacity prediction value and a calculation value.
8. The single-core cable dynamic current-carrying capacity prediction system considering load fluctuation characteristics according to claim 6, wherein in the verification unit, for a direct-buried single-core cable, heat conduction between soil and cable is calculated using the following formula:
in the method, in the process of the invention,
temperature in K; />
Is thermal resistance, and has the unit of K ∙ m/W; />
The unit is J/m for heat source power; />
The heat capacity is J/K; />
Is a thermal time constant, and has the unit of s.
9. The single-core cable dynamic current-carrying capacity prediction system considering load fluctuation characteristics according to claim 8, wherein in the verification unit, for a single loop consisting of a single cable or three single-core cables laid in isolation, the current-carrying capacity upon external thermal resistance change caused by drying of surrounding soil area is calculated according to the following formula:
wherein I represents a current flowing through one conductor, and the unit is A;
a conductor temperature rise above ambient temperature in K; />
The alternating current resistance of the conductor unit length at the highest working temperature is shown in omega/m; />
Represents the dielectric loss around the conductor per unit length in W/m; />
The thermal resistance of a conductor and a metal sleeve in unit length is expressed as K.m/W; />
The unit length thermal resistance of the lining layer between the metal sleeve and the armor is expressed as K.m/W; />
The thermal resistance of the outer protective layer of the cable per unit length is expressed, and the unit is K.m/W; />
The thermal resistance of unit length between the surface of the cable and the surrounding medium is expressed as K.m/W; />
The number of conductors carrying a load in the cable; />
Representing the ratio of the cable metal sheath loss to the total loss of all conductors; />
Representing the ratio of cable armor loss to total loss of all conductors; />
Represents the ratio of the thermal resistivity of the dry and wet soil domains; />
The critical temperature rise of the soil, namely the temperature rise of the boundary between the dry soil and the wet soil which is higher than the ambient temperature, is expressed as K; />
The critical temperature of the soil, i.e. the temperature at the boundary of dry and wet soil, is expressed in c.
10. The single-core cable dynamic current-carrying capacity prediction system considering load fluctuation characteristics according to claim 6, wherein in the verification unit, in the classifying process of the load fluctuation in the current waveform by adopting a rain flow counting method, the evaluation index of the load fluctuation specifically comprises:
the trend fluctuation starting and stopping time, the starting and stopping power of a load trend fluctuation sequence, the duration relative time of trend fluctuation, the duration relative amplitude of trend fluctuation, the trend fluctuation inclination rate, the occurrence frequency of burst fluctuation in trend fluctuation, the trend fluctuation average value and the trend fluctuation standard deviation.
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