An integrated energy management method based on data governance

Abstract

The application discloses a kind of based on data management comprehensive energy management method, the present application relates to data management technical field, the present application is analyzed to the energy parameter of different data source in several call demands by platform analysis unit to the call time, for any one data source, the frequency of call and quantity of different energy parameters under different call demands are analyzed, and the one-way call degree of different energy parameters is determined, the frequency of call and quantity of different energy parameters under different call demands are analyzed, and the set of different energy parameters is determined, and the call degree of synchronization is called, the monitoring value of different energy parameters is combined and encrypted by security archiving unit, by this way, the relationship of different energy parameters call can be established, so that better encryption grouping is carried out, excessive redundancy in decryption process is reduced, further shorten the time required for data call, improve the efficiency of energy management.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data governance, and particularly relates to a comprehensive energy management method based on data governance. BACKGROUND

[0002] Under the background of rapid development of the energy field, comprehensive energy management has become a key means to realize efficient use of energy and optimize resource allocation, with the increasing number of various power stations and the increasing intelligent degree, the energy data generated presents an explosive growth trend; these energy data cover the running state of the power station, energy production and consumption, equipment performance parameters and other aspects, their accuracy, integrity and security are of great significance to the efficient operation of the power station, the optimization scheduling of the energy system and the sustainable development of the entire energy industry;

[0003] In order to ensure the security of energy data in the storage process, prevent data from being illegally stolen, tampered or leaked, encrypting the energy data is an important measure commonly used; in the prior art, when storing and managing the energy data of several power stations, in order to improve the speed of encrypted storage, a grouped encryption method is often used; the core idea of this method is to divide the huge energy data set into several groups, and then encrypt each group in parallel, thereby speeding up the encryption process to a certain extent;

[0004] However, there is no fixed and scientific grouping basis when grouping; the grouping method is often arbitrary, and the division is only for the purpose of simply improving the encryption speed, without fully considering the actual needs of subsequent data retrieval; in the actual energy management process, these encrypted data will be frequently retrieved based on various retrieval needs, such as energy consumption analysis, equipment fault diagnosis, running state evaluation, etc.

[0005] Due to the unfixing and randomness of the grouping method, when extracting target data, there will be too much unnecessary extraction and decryption data in the encrypted data relative to the target data, and decryption of such data will cause more decryption redundancy in the decryption process, which will reduce the data extraction efficiency, prolong the time to obtain the required data, and affect the real-time and accuracy of energy management;

[0006] In order to solve the above problems, the present application provides a solution. SUMMARY

[0007] The present application aims to provide a comprehensive energy management method based on data governance, in order to solve the problems raised in the background art.

[0008] The application provides a comprehensive energy management method based on data governance, comprising the following steps:

[0009] Step one: the security archiving unit receives the energy standard data of the current time data source, and determines whether the storage semaphore stored in the security archiving unit is 1. If the storage semaphore stored in the security archiving unit is 1, the security archiving unit stores a plurality of homomorphic extraction sets and independent energy parameters of the data source generated by analyzing the retrieval log information of a plurality of energy parameters stored in the platform analysis unit, and the storage semaphore is selected from the numbers 1 and 0.

[0010] All homomorphic extraction sets and independent energy parameters stored in the security archiving unit are extracted.

[0011] Step two: for any one homomorphic extraction set extracted, the monitoring values of all energy parameters contained in the homomorphic extraction set are extracted from the energy standard data, the monitoring values of all energy parameters extracted are taken as an energy standard block, the energy standard block is encrypted by using a symmetric encryption algorithm to obtain an energy encryption block of the data source relative to the homomorphic extraction set at the current time, and the energy encryption block is stored.

[0012] Step three: for any one independent energy parameter extracted, the monitoring value of the independent energy parameter is extracted from the energy standard data, the monitoring value of the independent energy parameter extracted is taken as an energy standard block, the energy standard block is encrypted by using a symmetric encryption algorithm to obtain an energy encryption block of the data source relative to the independent energy parameter at the current time, and the energy encryption block is stored.

[0013] Further, the following steps need to be completed before step one is completed:

[0014] SS1: the data acquisition unit acquires the energy data of the current time data source and transmits the energy data to the encryption interaction unit;

[0015] SS2: the encryption interaction unit receives the energy data of the current time data source transmitted, encrypts the energy data of the current time data source by using a stack encryption algorithm to obtain energy interaction data of the current time data source, and transmits the energy interaction data to the multi-source data interaction unit;

[0016] SS3: the multi-source data interaction unit receives the energy interaction data of the current time data source transmitted, first decrypts and restores the energy interaction data to obtain the energy data of the current time data source, then performs a data cleaning operation on the energy data to obtain energy standard data of the current time data source, and transmits the energy standard data to the security archiving unit.

[0017] Further, in step one, if the storage signal quantity stored in the security archiving unit at the current time is 0, the split encryption index P1 stored in the security archiving unit at this time is obtained, the energy standard data is cut into P1 energy standard blocks according to the split encryption index P1, the P1 energy standard blocks are synchronously encrypted by using a symmetric encryption algorithm to obtain corresponding P1 energy encrypted blocks, and the P1 energy encrypted blocks are taken as the energy archiving data of the data source at the time for archiving storage.

[0018] Further, the calling log information includes a calling time, a calling data source and a monitoring value.

[0019] Further, after the security archiving unit receives all the homomorphic extraction sets of the data source transmitted, the security archiving unit stores the homomorphic extraction sets, synchronously modifies the value of the storage signal quantity stored in the security archiving unit from 0 to 1, and stores the several independent energy parameters of the data source received by the security archiving unit.

[0020] Further, the initial storage signal quantity stored in the security archiving unit is 0.

[0021] Compared with the prior art, the method has the following beneficial effects:

[0022] The platform analysis unit analyzes the calling time of the energy parameters of different data sources in several calling demands, determines the one-way calling degree of different energy parameters by analyzing the calling frequency and quantity of different energy parameters under different calling demands for any data source, determines the set calling degree of different energy parameters by analyzing the frequency and quantity of synchronous calling of different energy parameters under different calling demands, and further determines the several homomorphic extraction sets and independent energy parameters of different data sources. BRIEF DESCRIPTION OF DRAWINGS

[0023] Figure 1 The method flowchart of the application. DETAILED DESCRIPTION

[0024] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments of the present application, all the other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of the present application.

[0025] Please refer to Figure 1 The present application provides a comprehensive energy management method based on data governance, and the method is realized by a comprehensive energy management system based on data governance. The system comprises a data source terminal and an energy management platform.

[0026] The data source terminal is configured to transmit the real-time collected energy data of a plurality of trusted data sources to the energy management platform after encryption, wherein the data sources include but are not limited to various types of power stations, and trusted refers to identity authentication by the energy management platform, which can be any one of password authentication, smart card / token authentication, biometric authentication, multi-factor authentication, one-time password (OTP), digital certificate, and behavior characteristic authentication.

[0027] The data source terminal comprises a plurality of data source sub-modules, one data source sub-module corresponding to one trusted data source, and the data source sub-module comprises a data collection unit and an encryption interaction unit.

[0028] The data collection unit collects the energy data of the corresponding data source in real time and transmits it to the encryption interaction unit. The energy data refers to various types of data in the whole life cycle of energy (production, transmission, conversion, consumption, storage, etc.), and the energy data includes the monitoring values of a plurality of energy parameters. In the present application, the energy parameters include the load of a generator set, the main steam pressure, the temperature, the fuel consumption, the turbine speed / vibration amplitude, the generator stator voltage, the current, the photovoltaic component temperature, the inverter input / output parameter, the wind turbine gearbox oil temperature, the blade angle, the power transmission line topology, the conductor temperature / icing thickness, the cable insulation resistance / local discharge capacity, the transformer oil temperature / oil chromatogram, the circuit breaker opening / closing times, the arrester leakage current, etc., the conversion equipment operating efficiency, the power factor, the transformer ratio error / no-load loss, the frequency converter output harmonic, the switching device temperature, etc., the electricity load, the peak-valley electricity consumption, the unit product energy consumption, the motor efficiency, the air conditioning system COP value, the lighting power density, etc., the energy storage system SOC / SOH, the charge / discharge power, the single battery voltage / inner resistance, the battery pack temperature field distribution, the pumped storage water level difference, the hydrogen storage tank pressure / purity, etc., the meteorological temperature / humidity, the carbon emission intensity, the real-time electricity price, the medium and long-term contract electricity, the data sampling frequency / transmission delay, etc.

[0029] The encryption interaction unit uses a symmetric encryption algorithm to encrypt the real-time energy data of the data source to obtain energy interaction data of the data source, and transmits the energy interaction data to an energy management platform. The symmetric encryption algorithm can be any one of DES, 3DES, Blowfish, IDEA, RC4, RC5, RC6 and AES. In this application, the symmetric encryption algorithm is AES.

[0030] The energy management platform is used for managing energy interaction data transmitted by a plurality of trusted data sources. The energy management platform includes a multi-source data interaction unit, a secure archiving unit and a platform analysis unit.

[0031] For any trusted data source, the energy management platform receives the real-time energy interaction data transmitted by the data source, and transmits the data to the multi-source data interaction unit. The multi-source data interaction unit receives the real-time energy interaction data transmitted by the data source, first decrypts and restores the data to obtain real-time energy data of the data source, then performs data cleaning on the energy data to obtain energy standard data of the data source, and transmits the energy standard data to the secure archiving unit. The energy standard data includes a plurality of energy parameters and their monitoring values after data cleaning.

[0032] In this application, the data cleaning operation includes removing duplicate data, processing missing values, correcting erroneous data, processing abnormal values, data conversion, uniform data format, data type conversion and processing inconsistent data.

[0033] The secure archiving unit stores a plurality of storage semaphores. The storage semaphores are selected from the numbers 0 and 1. When the storage semaphore is 0, the secure archiving unit also stores a plurality of preset split encryption indicators for the data sources. One storage semaphore corresponds to one trusted data source, and one storage semaphore corresponds to one split encryption indicator.

[0034] The secure archiving unit first determines whether the storage semaphore of the data source stored in the secure archiving unit is 0 or 1 when receiving the energy standard data of the data source at a time point.

[0035] If the storage semaphore stored in the security archiving unit at the time is 0, the partition encryption index P1 corresponding to the storage semaphore stored in the security archiving unit at this time is obtained, the energy standard data is cut according to the partition encryption index P1 to obtain a plurality of energy standard blocks, the data capacity of each energy standard block is P1, all the obtained energy standard blocks are synchronously encrypted by using a symmetric encryption algorithm to obtain a corresponding number of energy encrypted blocks, and all the obtained energy encrypted blocks are archived and stored as the energy archiving data of the data source at the time. It should be noted that each energy encrypted block has a corresponding relationship with all the energy parameters contained therein.

[0036] If the storage semaphore of the data source stored in the security archiving unit is 1, all the homomorphic extraction sets and independent energy parameters stored in the security archiving unit are extracted at this time.

[0037] For any one homomorphic extraction set extracted, the monitoring values of all the energy parameters contained in the homomorphic extraction set are extracted from the energy standard data, the monitoring values of all the energy parameters extracted are taken as an energy standard block, the energy standard block is encrypted by using a symmetric encryption algorithm to obtain an energy encrypted block of the data source at the time relative to the homomorphic extraction set, and the energy encrypted block is stored.

[0038] For any one independent energy parameter extracted, the monitoring value of the independent energy parameter is extracted from the energy standard data, the monitoring value of the independent energy parameter extracted is taken as an energy standard block, the energy standard block is encrypted by using a symmetric encryption algorithm to obtain an energy encrypted block of the data source at the time relative to the independent energy parameter, and the energy encrypted block is stored.

[0039] It should be noted that the symmetric encryption algorithm used by the security archiving unit can be any one of DES, 3DES, Blowfish, IDEA, RC4, RC5, RC6 and AES. In this application, the symmetric encryption algorithm is AES.

[0040] The platform analysis unit stores a plurality of energy parameter call log information, the call log information contains a call time, a call data source and a monitoring value.

[0041] In the present application, for any one data source, the energy management platform manager extracts a number of energy parameter monitoring values from all energy archival data of the data source stored in the secure archival unit based on periodic access requirements, and for each extracted monitoring value, generates an access log information of the monitoring parameter according to the data source transmitting the monitoring value, the access time, and the energy parameter corresponding to the monitoring value, and the access time refers to the time when the monitoring value is accessed.

[0042] It should be noted that when the energy management platform accesses a number of energy parameter monitoring values from the secure archival unit, it first needs to decrypt the corresponding energy encryption block. The decryption here is the inverse process of the encryption process.

[0043] The access requirements include, but are not limited to, power grid stability analysis, equipment state monitoring, weather prediction, historical output curve, and maintenance plan.

[0044] The platform analysis unit is used to analyze the access log information of a number of energy parameters stored therein, and the analysis steps are as follows:

[0045] S11: Randomly select one data source from all trusted data sources as a data source to be analyzed, and mark all energy parameters contained in the energy data of the data source to be analyzed as A1, A2,..., Aa, a≥1;

[0046] S12: Obtain all access log information containing energy parameter A1 of the data source to be analyzed from the platform analysis unit, and mark the obtained all access log information in order from far to near according to the access time contained from the current time as B1, B2,..., Bb, b≥1;

[0047] S13: Extract access times Z1, Z2,..., Zb from access log information B1, B2,..., Bb in order, calculate the access time difference C1 of access times Z1 and Z2 using the formula C1=B2-B1, and similarly calculate the access time differences C2, C3,..., Cb-1 of access times Z2 and Z3, Z3 and Z4,..., Zb-1 and Zb in order;

[0048] S14: According to the first rejection rule, reject a number of access time differences from access time differences C1, C2,..., Cb-1, and calculate the mean of the remaining all access time differences using the sum average formula, and mark the mean as the standard access frequency F1 of the data source to be analyzed relative to energy parameter A1. The rejection rule is as follows:

[0049] Using the formula 1≤e≤b-1Calculate the dispersion E1 of the call time difference C1, C2,..., Cb-1, compare E1 and E, where Ce represents each of the call time differences C1, C2,..., Cb-1, C is the average of Ce at this time, and E is the standard dispersion threshold of the preset call time difference;

[0050] If E1>E, delete the corresponding Ce in order of |Ce-C| from large to small, and calculate the dispersion E1 of the remaining Ce, and compare E1 and E again, until E1<E, obtain the average of all call time differences participating in the calculation of E1 at this time, and mark the average as the standard call frequency F1 of the energy parameter A1 of the data source to be analyzed;

[0051] S15: Calculate the one-way call degree D1 of the energy parameter A1 of the data source to be analyzed using the formula D1=F1×ɑ1+b / P2×ɑ2, where P2 is a preset frequency constant used to define the degree of call frequency of each energy parameter, and ɑ1 and ɑ2 are preset first and second proportion weights used to adjust the weight proportion of the corresponding dimension in the calculation process;

[0052] S16: Calculate the one-way call degree D2, D3,..., Da of the energy parameter A2, A3,..., Aa of the data source to be analyzed in turn according to S11 to S15;

[0053] S17: Set the grouping index as g, and take 1, 2,..., a-1 in turn to combine the energy parameter A1 with a corresponding number of energy parameters A2, A3,..., Aa to obtain the grouping set H1, H2,..., Hh, h=C 2 a-1 +...+C m a-1 +1, where g represents the number of energy parameters selected from A2, A3,..., Aa in addition to A1 in each group;

[0054] When g=1, A1 is combined with A2, A3,..., Aa respectively to form a-1 groups of grouping sets, each of which contains 2 energy parameters;

[0055] When g=2, any 2 energy parameters from A2, A3,..., Aa are combined with A1 to form C 2 a-1 grouping sets, each of which contains 3 energy parameters;

[0056] By analogy, when g=m, 1≤m≤a-1, m energy parameters from A2, A3,..., Aa are combined with A1 to form Cm a-1 a sets of components, each set containing m+1 energy parameters;

[0057] For example, take a=5 as an example:

[0058] g=1: the set of groups is {A1,A2}, {A1,A3}, {A1,A4}, {A1,A5}, a total of 5−1=4 groups;

[0059] g=2: select 2 from A2−A5 and combine with A1, such as {A1,A2,A3}, {A1,A2,A4}, …, {A1,A4,A5}, a total of C4 2 =6 groups;

[0060] g=3: select 3 from A2−A5 and combine with A1, a total of C4 3 =4 groups;

[0061] g=4: only {A1,A2,A3,A4,A5} one group, a total of C4 4 =1 group;

[0062] S18: calculate the set of energy parameters A1 relative to the set of groups H1 according to the preset first calculation rule to obtain the set of groups H1, at this time the set of groups H1 corresponds to the energy parameter A1, and the first calculation rule is as follows:

[0063] S181: extract all energy parameters in the set of groups H1 except the energy parameter A1, and re-label them as I1, I2, …, Ii, 1≤i≤a−1;

[0064] S182: obtain all access log information J1, J2, …, Jj containing the energy parameter I1 of the data source to be analyzed from the platform analysis unit, j≥1;

[0065] S183: create a count variable K1 of the energy parameter I1 in the set of groups H1 relative to the access time C1, the initial value of the count variable K1 is 0, and the count variable K1 is assigned according to the preset assignment rule, and the assignment rule is as follows:

[0066] Iterate through the access time contained in the access log information J1, J2, …, Jj, and count the total number of access times whose difference with the access time C1 is less than or equal to P3, and assign the total number to the count variable K1, P3 being a preset extraction time difference threshold value;

[0067] S184: create count variables K2, K3,..., Ki for energy parameters I2, I3,..., Ii in group set H1 in sequence, and assign values to count variables K2, K3,..., Ki in sequence according to S183;

[0068] S185: remove some count variables from count variables K1, K2,..., Ki according to a preset second removal rule, and calculate the mean value of the remaining count variables by using the sum and average formula to obtain the mean value, and mark the mean value as the call count average N1 of energy parameter A1 relative to group set H1, the second removal rule is as follows;

[0069] The formula is used to calculate the deviation L1 of count variables K1, K2,..., Ki, and L1 and L are compared in size, where Kl represents each of count variables K1, K2,..., Ki, K is the average value of Kl at this time, and L is a preset count variable deviation screening threshold of energy parameter A1 relative to g=2 group set;

[0070] If L1>L, then delete the corresponding Kl in the order from large to small according to |Kl-K| and calculate the deviation L1 of the remaining Kl, and then compare L1 and L in size again, until L1<L, obtain the average value of all count variables participating in the calculation of L1 at this time, and mark the average value as the call count average N1 of energy parameter A1 relative to group set H1, and simultaneously obtain the total number N2 of all Kl deleted at this time;

[0071] S186: Calculate the set-oriented call degree Q1 of energy parameter A1 relative to group set H1 by using the formula Q1=N1×β1+(1-N2 / j)×β2, where β1 and β2 are respectively preset third and fourth proportion weights, used to adjust the weight proportion of the corresponding dimension in the calculation process;

[0072] S19: Calculate the set-oriented call degree of energy parameter A1 relative to group set H2, H3,..., Hh in sequence according to S18, and extract all group sets corresponding to the set-oriented call degree greater than or equal to P4 from them, and take the extracted all group sets as the homomorphic extraction set of energy parameter A1, P4 is a preset critical set screening threshold;

[0073] S110: Obtain all homomorphic extraction sets of energy parameters A2, A3,..., Aa in sequence according to S17 to S19, and remove duplicates from all homomorphic extraction sets of energy parameters A1, A2,..., Aa, and only one copy is retained for several homomorphic extraction sets containing the same energy parameters in the de-duplication process;

[0074] ​transmit all homomorphic extraction sets of the remaining data sources after deduplication to the secure archiving unit, it is to be noted that if there are some energy parameters in the energy parameters A1, A2,..., Aa whose one-way call degree is greater than or equal to P5 and no homomorphic extraction set, the energy parameters are also marked as independent energy parameters of the data sources to be analyzed, and all independent energy parameters of the data sources to be analyzed are transmitted to the secure archiving unit, P5 is a preset independent determination degree threshold value;

[0075] S111: sequentially select all trusted data sources as data sources to be analyzed, and sequentially generate all homomorphic extraction sets and independent energy parameters of all data sources according to S11 to S110;

[0076] The secure archiving unit stores all homomorphic extraction sets of a data source transmitted by it, and synchronously modifies the value of the storage semaphore stored in it to 1, and if the secure archiving unit synchronously receives some independent energy parameters of the data source, it also stores the independent energy parameters.

[0077] Some data in the above formula are dimensionless for numerical calculation, and the contents not described in detail in the specification all belong to the prior art known to those skilled in the art.

[0078] The above embodiments are only used to illustrate the technical method of the present application and are not limiting, and although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present application can be modified or replaced equivalently without departing from the spirit and scope of the technical method of the present application.

Claims

1. A comprehensive energy management method based on data governance, characterized in that, Includes the following steps: Step 1: After receiving the energy standard data of the data source at the current moment, the secure archiving unit determines whether the stored semaphore of the data source stored in the secure archiving unit is 1. If the stored semaphore stored in the secure archiving unit is 1, then the secure archiving unit stores several homomorphic extraction sets and independent energy parameters of the data source generated by the platform analysis unit through the analysis of the retrieval log information of several energy parameters stored in it. The stored semaphore is selected from the numbers 1 and 0. Extract all homomorphic extraction sets and independent energy parameters stored within the secure archiving unit; Step 2: For any homomorphic extraction set, based on all energy parameters contained in the homomorphic extraction set, extract the monitoring values ​​of all energy parameters from the energy standard data, take the extracted monitoring values ​​of all energy parameters as an energy standard block, encrypt the energy standard block using a symmetric encryption algorithm to obtain the energy encrypted block of the data source relative to the homomorphic extraction set at the current time, and store it. Step 3: For any extracted independent energy parameter, extract the monitoring value of the independent energy parameter from the energy standard data, take the extracted monitoring value of the independent energy parameter as an energy standard block, encrypt the energy standard block using a symmetric encryption algorithm to obtain the energy encryption block of the data source relative to the independent energy parameter at the current time, and store it. Before completing step one, the following steps also need to be completed: SS1: The data acquisition unit collects energy data from the data source at the current moment and transmits it to the encrypted interaction unit; SS2: After receiving the energy data from the current data source, the encrypted interaction unit uses a stacking encryption algorithm to encrypt the energy data from the current data source to obtain the energy interaction data from the current data source, and then transmits the energy interaction data to the multi-source data interaction unit. SS3: After receiving the energy interaction data of the data source at the current moment, the multi-source data interaction unit first decrypts and restores it to obtain the energy data of the data source at the current moment, then performs data cleaning operation on the energy data to obtain the energy standard data of the data source at the current moment, and transmits the energy standard data to the secure archiving unit. The analysis steps are as follows: S11: Label all energy parameters contained in the energy data of the data source as A1, A2, ..., Aa, where a≥1; S12: Obtain all retrieval log information containing the energy parameter A1 from the platform analysis unit, and sequentially label all the retrieved retrieval log information as B1, B2, ..., Bb, where b≥1, according to the order of the retrieval time from the current time to the earliest. S13: Extract the retrieval times Z1, Z2, ..., Zb from the retrieved log information B1, B2, ..., Bb in sequence. Calculate the retrieval time difference C1 between retrieval times Z1 and Z2 using the formula C1=B2-B1. Similarly, calculate the retrieval time differences C2, C3, ..., Cb-1 between retrieval times Z2 and Z3, Z3 and Z4, ..., Zb-1 and Zb in sequence. S14: According to the preset first elimination rule, a number of extraction time differences are eliminated from extraction time differences C1, C2, ..., Cb-1, and the average value of all remaining extraction time differences is calculated using the summation and averaging formula. The average value is calibrated as the standard extraction frequency F1 of the data source relative to the energy parameter A1. S15: Calculate the degree of one-way access to the data source relative to the energy parameter A1 using the formula D1=F1×ɑ1+b / P2×ɑ2. In the formula, P2 is a preset frequency verification constant used to define the degree of access frequency of each energy parameter, and ɑ1 and ɑ2 are preset first and second proportion weights, respectively, used to adjust the weight proportion of the corresponding dimensions in the calculation process. S16: Calculate and obtain the unidirectional access degree D2, D3, ..., Da of the relative energy parameters A2, A3, ..., Aa of the data source in sequence according to S11 to S15; S17: Set the grouping index as g, and sequentially take 1, 2, ..., a-1 to combine the energy parameter A1 with the corresponding number of energy parameters A2, A3, ..., Aa to obtain the grouping sets H1, H2, ..., Hh, where h=C 2 a-1 +...+C m a-1 +1, where g represents the number of energy parameters selected from A2, A3, ..., Aa in each group, excluding energy parameter A1; When g=1, A1 is combined with A2, A3, ..., Aa in sequence to form a-1 groups. At this time, each group contains 2 energy parameters. When g=2, any two energy parameters can be randomly selected from A2, A3, ..., Aa and combined with A1 to form C. 2 a-1 Group the data into sets, where each group contains 3 energy parameters; Similarly, when g = m, 1 ≤ m ≤ a - 1, select m energy parameters from A2, A3, ..., Aa and combine them with A1 to form C. m a-1 Groups are sets of m+1 energy parameters. S18: Calculate and obtain the set-direction retrieval degree Q1 of energy parameter A1 relative to group set H1 according to the preset first calculation rule; S19: Calculate the set retrieval degree of energy parameter A1 relative to the group sets H2, H3, ..., Hh in sequence according to S18, and extract all group sets corresponding to the set retrieval degree with values ​​greater than or equal to P4. Use the extracted group sets as the homomorphic extraction set of energy parameter A1, and P4 is the preset critical set screening threshold. S110: Obtain all homomorphic extraction sets of energy parameters A2, A3, ..., Aa in sequence according to S17 to S19. Remove duplicates from all homomorphic extraction sets of energy parameters A1, A2, ..., Aa. During the deduplication process, for several homomorphic extraction sets that contain the same energy parameters, only one copy is retained. After deduplication, all remaining homomorphic extraction sets are transmitted to the secure archiving unit. If there are several energy parameters among energy parameters A1, A2, ..., Aa whose unidirectional retrieval degree is greater than or equal to P5 and have no homomorphic extraction sets, then these energy parameters are also marked as independent energy parameters, and all independent energy parameters are transmitted to the secure archiving unit. P5 is a preset threshold for the degree of independence.

2. The integrated energy management method based on data governance according to claim 1, characterized in that, In step one, if the storage semaphore of the data source stored in the secure archiving unit at the current time is 0, then the segmentation encryption index P1 corresponding to the storage semaphore stored in the secure archiving unit at this time is obtained. The energy standard data is segmented into several energy standard blocks according to the segmentation encryption index P1. The data capacity of each energy standard block is P1. All the obtained energy standard blocks are synchronously encrypted using a symmetric encryption algorithm to obtain a corresponding number of energy encryption blocks. All the obtained energy encryption blocks are archived and stored as the energy archiving data of the data source at the current time.

3. The integrated energy management method based on data governance according to claim 1, characterized in that, The retrieved log information includes the retrieval time, the data source, and the monitored values.

4. The integrated energy management method based on data governance according to claim 1, characterized in that, In S18, the first calculation rule for calculating the set-to-set retrieval degree Q1 of energy parameter A1 relative to group set H1 is as follows: S181: Extract all energy parameters from the group set H1 except for energy parameter A1, and relabel them as I1, I2, ..., Ii, where 1≤i≤a-1; S182: Obtain all retrieval log information J1, J2, ..., Jj, where j≥1, from the platform analysis unit, containing energy parameter I1 from the data source; S183; Create a count variable K1 for energy parameter I1 relative to the retrieval time C1 in group set H1. The initial value of the count variable K1 is 0. Assign values ​​to the count variable K1 according to the preset assignment rules, as follows: The retrieval times contained in the retrieved log information J1, J2, ..., Jj are traversed, and the total number of retrieval times whose difference from the retrieval time C1 is less than or equal to P3 is counted. The total number is assigned to the count variable K1, and P3 is a preset retrieval time difference filtering threshold. S184: Sequentially create the count variables K2, K3, ..., Ki of the energy parameters I2, I3, ..., Ii in the group set H1 relative to the retrieval time C1, and assign values ​​to the count variables K2, K3, ..., Ki in sequence according to S183; S185: According to the preset second elimination rule, remove a number of counting variables from the counting variables K1, K2, ..., Ki, and use the summation and averaging formula to calculate the mean of all remaining counting variables. The mean is calibrated as the average count N1 of energy parameter A1 relative to group set H1, and the total number N2 of the counting variables deleted at this time is obtained simultaneously. S186: The set-direction retrieval degree Q1 of energy parameter A1 relative to group set H1 is calculated using the formula Q1=N1×β1+(1-N2 / j)×β2. In the formula, β1 and β2 are the preset third and fourth proportion weights, which are used to adjust the weight proportion of the corresponding dimensions during the calculation process.

5. The integrated energy management method based on data governance according to claim 4, characterized in that, After receiving all homomorphic extraction sets of the transmitted data source, the secure archiving unit stores them and synchronously modifies the value of the stored semaphore stored within them from 0 to 1. The secure archiving unit also stores several independent energy parameters received from the data source.

6. The integrated energy management method based on data governance according to claim 1, characterized in that, The initial storage semaphore stored in the secure archiving unit is 0.

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