Industrial chain operation monitoring method and system based on electric power big data

Abstract

The invention discloses an industrial chain operation monitoring method and system based on electric power big data, and the method comprises the steps: obtaining the contract capacity information of each enterprise in a target industrial chain and an electric power company, the monthly actual power consumption data, and the annual actual power consumption data of the last year; and respectively calculating an annual operation index, a quarterly operation index and a monthly operation index of each enterprise, and carrying out weighted summation according to a preset weight to obtain a comprehensive operation health index of the enterprise. According to the scheme, the electricity consumption condition of the industry chain user is directly acquired from the electricity consumption acquisition system of the electric power company, and the data acquisition mode is more direct, accurate and targeted; in addition, various power utilization related factors are comprehensively considered, and the development trend, stability and potential problems of an industrial chain can be caught more finely. In addition, according to the scheme, a more scientific monitoring system is established by utilizing correlation analysis of power consumption data, so that a more reliable basis is provided for decisions such as an orderly power consumption scheme and the like.

Description

Technical Field

[0001] The present invention relates to the field of electric power technology, and in particular to an industrial chain operation monitoring method and system based on electric power big data. Background Art

[0002] In today's economic development pattern, the government attaches great importance to the construction of an independent, controllable, safe and reliable industrial chain system. The stable operation of the industrial chain is crucial to regional economic development, and the effective monitoring of the operation of the industrial chain has become a key link in ensuring its stable development.

[0003] At present, there are many technologies and methods in the field of industrial chain monitoring. Traditional industrial chain operation monitoring mainly relies on data reported by enterprises, macroeconomic data from statistical departments, and some special survey data. These data sources can reflect the operation status of the industrial chain to a certain extent, such as the production scale, sales, profits and other information of the enterprise. However, these existing technologies for monitoring the operation of the industrial chain have the following problems: First, the data is not timely enough. There is often a certain time lag in the data reported by enterprises. From data collection, collation to summary analysis, it may take a long period of time, resulting in the inability to timely reflect sudden problems and real-time changes in the operation of the industrial chain. For example, when the chain leader enterprise suddenly faces a shortage of raw materials, through traditional data collection methods, the government and relevant departments may not be able to obtain information in the first time, making it difficult to make timely response decisions.

[0004] Second, the data lacks comprehensiveness. The data formats and standards from different sources are not unified, making it difficult to integrate and analyze. The data from statistical departments are mostly at the macro level, and it is difficult to go deep into the specific links and enterprise levels within the industrial chain. The data reported by enterprises may be biased or incomplete due to factors such as their own interests, and cannot fully and comprehensively reflect the operation of the industrial chain. For example, when analyzing the synergy of the entire industrial chain from raw material supply to finished product sales, the existing data cannot achieve effective correlation and comprehensive analysis.

[0005] Third, the insight is not deep enough. Most existing monitoring technologies can only analyze from the macro-industry level or a single enterprise dimension, and lack the ability to penetrate from the industrial chain to the industry and then to the enterprise. For example, for a complex industrial system like the synthetic leather industry chain, it is difficult to accurately measure the health of the overall operation of the industrial chain. The inability to accurately understand the specific impact of policies such as energy dual control on each link of the industrial chain makes it lack of scientific basis when formulating orderly electricity consumption plans, which is easy to cause unnecessary impact on the industrial economy.

[0006] Fourth, the data value density is low. There is a lot of redundant information in traditional data sources, which is inefficient in mining key information of industrial chain operation. When faced with factors that have a key impact on the industrial chain, such as orderly power consumption and shortage of raw materials, it is difficult to quickly extract effective information from massive low-value density data to guide decision-making and ensure the safe and stable development of the industrial chain. Summary of the invention

[0007] The present invention aims to at least solve the technical problems existing in the prior art. To this end, the first aspect of the present invention proposes an industrial chain operation monitoring method based on power big data, the method comprising: Obtain the monthly contract capacity information of each enterprise in the target industrial chain and the power company in each month of the current year, the actual monthly electricity consumption data of the enterprise in each month of the current year, and the actual annual electricity consumption data of the enterprise in the previous year; Determine the annual operation index of the enterprise according to the monthly contract capacity information, the monthly actual electricity consumption data and the annual actual electricity consumption data of the previous year; Obtaining the quarterly actual electricity consumption data of the enterprise in the current quarter and the historical average electricity consumption data of the same quarter in historical years, and determining the seasonal fluctuation coefficient of the enterprise based on the ratio of the quarterly actual electricity consumption data to the historical average electricity consumption data of the same quarter; Obtain the number of new enterprises in the target industrial chain connected to the power company in the current quarter, obtain the number of enterprises in the target industrial chain that have terminated cooperation with the power company, and determine the quarterly rate of change of the number of enterprises based on the number of new enterprises and the number of exiting enterprises; Determine the quarterly operation index of the enterprise according to the seasonal fluctuation coefficient and the quarterly enterprise quantity change rate; Determine the month-on-month change rate of the enterprise's electricity consumption in the current month based on the actual electricity consumption data of the month; Obtain the first average electricity consumption data of each enterprise in the target industry in which the enterprise in the target industrial chain is located in the current month, and the second average electricity consumption data of other industries in the target industrial chain in the current month, and determine the industry synergy change coefficient of the enterprise in the current month according to the ratio of the first average electricity consumption data to the second average electricity consumption data; Determine the monthly operation index of the enterprise according to the month-on-month change rate of electricity consumption and the industry coordinated change coefficient; According to the preset weights of the annual operation index, the quarterly operation index and the monthly operation index, the annual operation index, the quarterly operation index and the monthly operation index are weighted and summed to obtain the comprehensive operation health index of the enterprise.

[0008] Optionally, determining the annual operation index of the enterprise according to the contract capacity information, the monthly actual electricity consumption data and the annual actual electricity consumption data of the previous year includes: Determine the annual actual electricity consumption data of the enterprise in the current year based on the monthly actual electricity consumption data; and determine the annual contract capacity information of the enterprise in the current year based on the monthly contract capacity information; Determine the quotient of the annual actual electricity consumption and the annual contract capacity information to obtain the contract capacity utilization rate of the enterprise; Determine the year-on-year change rate of the enterprise's annual electricity consumption based on the annual actual electricity consumption data of the current year and the annual actual electricity consumption data of the previous year; According to the preset weights of the contract capacity utilization rate and the annual electricity consumption year-on-year change rate, the contract capacity utilization rate and the annual electricity consumption year-on-year change rate are weighted and summed to obtain the annual operation index of the enterprise.

[0009] Optionally, determining the quarterly rate of change in the number of enterprises according to the number of new enterprises and the number of exiting enterprises includes: Calculating a first difference between the number of new enterprises and the number of exited enterprises; Obtain the total number of enterprises in the target industrial chain in the previous quarter; The ratio of the first difference and the total number of enterprises is calculated to obtain the quarterly rate of change of the number of enterprises.

[0010] Optionally, determining the quarterly operation index of the enterprise according to the seasonal fluctuation coefficient and the quarterly enterprise quantity change rate includes: According to the preset weights of the seasonal fluctuation coefficient and the quarterly enterprise quantity change rate, the seasonal fluctuation coefficient and the quarterly enterprise quantity change rate are weighted and summed to obtain the quarterly operation index of the enterprise.

[0011] Optionally, determining the month-on-month change rate of the enterprise's electricity consumption in the current month according to the monthly actual electricity consumption data includes: Acquire first actual power consumption data of the current month, and acquire second actual power consumption data of the month before the current month; Calculating a second difference between the first actual power consumption data and the second actual power consumption data; The quotient between the second difference and the second actual electricity consumption data is calculated to obtain the month-on-month change rate of electricity consumption of the enterprise in the current month.

[0012] Optionally, determining the monthly operation index of the enterprise according to the month-on-month change rate of electricity consumption and the industry coordinated change coefficient includes: According to the preset weights of the month-on-month change rate of electricity consumption and the industry coordinated change coefficient, the month-on-month change rate of electricity consumption and the industry coordinated change coefficient are weighted and summed to obtain the monthly operation index of the enterprise.

[0013] Optionally, after obtaining the comprehensive operation health index of the enterprise, the method further includes: According to the pre-set evaluation interval, the comprehensive operation health index of each of the enterprises is evaluated, and the operation status of the target industrial chain is determined.

[0014] The second aspect of the present invention provides an industrial chain operation monitoring system based on power big data, the system comprising: An acquisition module, used to acquire the contract capacity information between the enterprise and the power company in the current year, the actual monthly electricity consumption data of the enterprise in each month of the current year, and the actual annual electricity consumption data of the enterprise in the previous year; An annual operation index determination module, used to determine the annual operation index of the enterprise according to the contract capacity information, the monthly actual electricity consumption data and the annual actual electricity consumption data of the previous year; A fluctuation coefficient determination module is used to obtain the quarterly actual electricity consumption data of the enterprise in the current quarter and the historical average electricity consumption data of the same quarter in historical years, and determine the seasonal fluctuation coefficient of the enterprise according to the ratio of the quarterly actual electricity consumption data to the historical average electricity consumption data of the same quarter; A quantity change rate determination module is used to obtain the number of new enterprises in the target industrial chain connected to the power company in the current quarter, obtain the number of exiting enterprises in the target industrial chain that terminated cooperation with the power company, and determine the quarterly enterprise quantity change rate based on the number of new enterprises and the number of exiting enterprises; A quarterly operation index determination module, used to determine the quarterly operation index of the enterprise according to the seasonal fluctuation coefficient and the quarterly enterprise quantity change rate; A month-on-month change rate determination module is used to determine the month-on-month change rate of the enterprise's electricity consumption in the current month based on the actual electricity consumption data of the month; A synergistic variation coefficient determination module is used to obtain the first average electricity consumption data of each enterprise in the target industry in which the enterprise in the target industrial chain is located in the current month, and the second average electricity consumption data of other industries in the target industrial chain in the current month, and determine the industry synergistic variation coefficient of the enterprise in the current month according to the ratio of the first average electricity consumption data to the second average electricity consumption data; A monthly operation index determination module, used to determine the monthly operation index of the enterprise according to the month-on-month change rate of electricity consumption and the industry synergy change coefficient; The operation health index determination module is used to perform weighted summation of the annual operation index, the quarterly operation index, and the monthly operation index according to the preset weights of the annual operation index, the quarterly operation index, and the monthly operation index to obtain the comprehensive operation health index of the enterprise.

[0015] Optionally, the annual operation index determination module is specifically used to: Determine the annual actual electricity consumption data of the enterprise in the current year based on the monthly actual electricity consumption data; and determine the annual contract capacity information of the enterprise in the current year based on the monthly contract capacity information; Determine the quotient of the annual actual electricity consumption and the annual contract capacity information to obtain the contract capacity utilization rate of the enterprise; Determine the year-on-year change rate of the enterprise's annual electricity consumption based on the annual actual electricity consumption data of the current year and the annual actual electricity consumption data of the previous year; According to the preset weights of the contract capacity utilization rate and the annual electricity consumption year-on-year change rate, the contract capacity utilization rate and the annual electricity consumption year-on-year change rate are weighted and summed to obtain the annual operation index of the enterprise.

[0016] Optionally, the quantity change rate determination module is specifically used to: Calculating a first difference between the number of new enterprises and the number of exited enterprises; Obtain the total number of enterprises in the target industrial chain in the previous quarter; The ratio of the first difference and the total number of enterprises is calculated to obtain the quarterly rate of change of the number of enterprises.

[0017] The embodiments of the present invention have the following beneficial effects: In an embodiment of the present invention, the contract capacity information between each enterprise in the target industrial chain and the power company in the current year, the actual monthly electricity consumption data of the enterprise in each month in the current year, and the actual annual electricity consumption data of the enterprise in the previous year are obtained, and the annual operation index, quarterly operation index, and monthly operation index of each enterprise are calculated respectively. According to the preset weights of the annual operation index, the quarterly operation index, and the monthly operation index, the weighted sum of the annual operation index, the quarterly operation index, and the monthly operation index is obtained to obtain the comprehensive operation health index of the enterprise. In this scheme, the electricity consumption of users in the industrial chain is directly obtained from the power company's electricity consumption collection system. This data acquisition method is more direct, accurate and targeted; and, according to the constructed industrial chain operation power index, the operation health of the industrial chain is measured from three dimensions of annual, quarterly, and monthly, and a variety of electricity-related factors are comprehensively considered. It can more finely capture the development trend, stability and potential problems of the industrial chain, and greatly improve the accuracy of industrial chain operation monitoring. In addition, this plan uses the correlation analysis of electricity consumption data to establish a more scientific monitoring system. In-depth analysis based on electricity data can more accurately judge the impact of problems such as shortages of raw materials and sales obstructions on the industrial chain, thereby providing a more reliable basis for decisions such as orderly electricity consumption plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flowchart of the steps of an industrial chain operation monitoring method based on power big data provided by an embodiment of the present invention; Figure 2 It is a structural block diagram of an industrial chain operation monitoring system based on power big data provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present disclosure, unless otherwise specified, "multiple" means two or more. In addition, the use of "based on" or "according to" means openness and inclusiveness, because the process, steps, calculations or other actions "based on" or "according to" one or more of the conditions or values ​​may be based on additional conditions or values ​​beyond the described values ​​in practice.

[0021] Figure 1 It is a step flow chart of an industrial chain operation monitoring method based on power big data provided by an embodiment of the present invention.

[0022] like Figure 1 As shown, the method comprises the following steps: Step 101: Obtain the contract capacity information between the enterprise and the power company in the current year, the actual monthly electricity consumption data of the enterprise in each month of the current year, and the actual annual electricity consumption data of the enterprise in the previous year.

[0023] In order to monitor the operating status of enterprises in the industrial chain, the power company's electricity consumption collection system can be used to comprehensively collect electricity consumption data of each enterprise in the industrial chain. These data include two parts: the enterprise's customer file data and the enterprise's electricity consumption details.

[0024] Compared with the prior art, the present invention directly obtains the electricity consumption of users in the industrial chain from the power company's electricity consumption collection system, including detailed customer profile data and electricity consumption information. This data acquisition method is more direct, accurate and targeted. The prior art relies on data reported by enterprises and integrated from multiple sources, and there are problems of inaccurate, untimely and incomplete data. The data we obtain through the power system, key information such as account number, etc., ensures the uniqueness and traceability of the data source, and the industry category can accurately classify the enterprises in the industrial chain. The data such as contract capacity and electricity consumption can be verified with each other to accurately analyze the production status of the enterprise, avoiding the defects of data integration difficulties and information bias in the prior art.

[0025] Specifically, the contract capacity information of the enterprise in the current year is obtained from the customer file data. The contract capacity information refers to the total planned electricity consumption information for the current year signed in the contract.

[0026] The actual monthly electricity consumption data of the enterprise in each month of the current year and the actual annual electricity consumption data of the enterprise in the previous year are obtained from the customer file data at the same time.

[0027] Step 102: Determine the annual operation index of the enterprise according to the contract capacity information, the monthly actual electricity consumption data and the annual actual electricity consumption data of the previous year.

[0028] Based on the contract capacity information, monthly actual electricity consumption data and the annual actual electricity consumption data of the previous year, the annual operation index of each enterprise is calculated, and then based on the annual operation index of each enterprise, the annual operation health status of the industrial chain is comprehensively evaluated.

[0029] Step 103: Obtain the quarterly actual electricity consumption data of the enterprise in the current quarter and the historical average electricity consumption data of the same quarter in historical years, and determine the seasonal fluctuation coefficient of the enterprise based on the ratio of the quarterly actual electricity consumption data to the historical average electricity consumption data of the same quarter.

[0030] The electricity consumption data is divided into quarters to obtain the actual electricity consumption data of each enterprise in the current quarter and the historical average electricity consumption data of the same quarter in historical years. The historical year specifically refers to the n years before the current year, where n is a natural number and the value of n can be preset according to demand.

[0031] Assume that the actual quarterly electricity consumption data of the enterprise is E ik , the historical average electricity consumption data for the same quarter is , then the seasonal fluctuation coefficient The calculation formula is as follows: (1) Step 104: obtain the number of new enterprises in the target industrial chain connected to the power company in the current quarter, obtain the number of exiting enterprises in the target industrial chain that have terminated cooperation with the power company, and determine the quarterly rate of change of the number of enterprises based on the number of new enterprises and the number of exiting enterprises.

[0032] Count the number of new enterprises connected to the power company in the target industry chain in the current quarter , and the number of exiting enterprises in the target industry chain that terminated cooperation with power companies , according to the number of new enterprises and the number of exiting enterprises, determine the quarterly change rate of the number of enterprises in the target industry chain .

[0033] Step 105: Determine the quarterly operation index of the enterprise according to the seasonal fluctuation coefficient and the quarterly rate of change of the number of enterprises.

[0034] According to the seasonal fluctuation coefficient and quarterly rate of change in the number of companies , determine the quarterly operating index of the enterprise .

[0035] Step 106: Determine the month-on-month change rate of the enterprise's electricity consumption in the current month based on the actual monthly electricity consumption data.

[0036] The month-on-month change rate of electricity consumption is obtained by comparing the electricity consumption in the current month with the electricity consumption in the previous month.

[0037] Step 107: Obtain the first average electricity consumption data of each enterprise in the target industry in which the enterprise in the target industrial chain is located in the current month, as well as the second average electricity consumption data of other industries in the target industrial chain in the current month, and determine the industry synergy variation coefficient of the enterprise in the current month based on the ratio of the first average electricity consumption data to the second average electricity consumption data.

[0038] Assume the first average power consumption data is , the second average power consumption data is , then the industry synergy change coefficient of the current month The calculation formula is as follows: (2) Step 108: Determine the monthly operation index of the enterprise according to the month-on-month change rate of electricity consumption and the industry coordinated change coefficient.

[0039] The month-on-month change rate of electricity consumption and the industry coordinated change coefficient in the current month can reflect the monthly operation status of the enterprise in the current month and obtain the monthly operation index of the enterprise.

[0040] Step 109: according to the preset weights of the annual operation index, the quarterly operation index and the monthly operation index, weighted sum of the annual operation index, the quarterly operation index and the monthly operation index is performed to obtain the comprehensive operation health index of the enterprise.

[0041] First, a data model is constructed to correlate the annual operation index, quarterly operation index and monthly operation index, and the weighted sum model is determined as the data model for calculating the comprehensive operation health index. The weighted sum model can take into account the comprehensive impact of changes in the index at different time scales on the overall operation of the enterprise.

[0042] Secondly, according to the industrial characteristics and external environmental factors of the target industrial chain, the weights of the annual operation index, quarterly operation index and monthly operation index are set in advance.

[0043] Specifically, for capital-intensive industries with long production cycles, such as large-scale equipment manufacturing and steel industries, the long-term development trend of these industries has a greater impact on their overall health. Long-term production planning and equipment updates are evaluated on an annual basis. Therefore, the weight of the annual operation index of capital-intensive industries with long production cycles is set at 0.5-0.6. For these industries, the weight of the quarterly operation index can be set at 0.3-0.4, and the weight of the monthly operation index can be set at 0.1-0.2. For industries with fast-changing market demand and frequent technological updates, such as electronic information and fashion apparel, these industries need to respond more promptly to the impact of short-term market fluctuations and technological innovation. Therefore, the weight of the monthly operating index can be increased to 0.3-0.4, the quarterly operating index weight is set to 0.3-0.4, and the annual operating index weight is adjusted to 0.2-0.4.

[0044] In addition, the weights need to be adjusted based on external environmental factors. During periods of stable economic growth, companies pay more attention to the implementation of long-term development strategies, so the weight of the annual operation index can be appropriately increased. When economic fluctuations are large or industry competition intensifies, in order to more keenly capture short-term changes, the weights of the monthly and quarterly operation indexes should be increased accordingly. For example, during economic downturns, the weight of the monthly operation index can be increased by 0.05-0.1 to strengthen the assessment of the company's short-term risk resistance. After determining the weights of the company's annual operation index, quarterly operation index, and monthly operation index, the annual operation index, quarterly operation index, and monthly operation index are weighted and summed to obtain the company's comprehensive operation health index.

[0045] Specifically, the calculation formula of the comprehensive operation health index OHI is as follows: (3) Among them, A, Q, and M are the weights of the annual operation index, quarterly operation index, and monthly operation index, respectively; Ia, Iq, and Im are the values ​​of the annual operation index, quarterly operation index, and monthly operation index, respectively. In a possible implementation manner, after step 109, the method further includes: According to the pre-set evaluation interval, the comprehensive operation health index of each of the enterprises is evaluated, and the operation status of the target industrial chain is determined.

[0046] In step 201-step 202, the evaluation interval of the enterprise comprehensive operation health index OHI is preset. OHI ≥ 80 is set as the healthy zone, 60 <= OHI < 80 is set as the concern zone, and OHI < 60 is set as the warning zone.

[0047] When OHI>= 80, the overall operation of the enterprise is in good health. In this range, the annual operation index is stable and at a high level (Ia>= 80), the quarterly operation index fluctuates slightly (within ±10), and the monthly operation index remains relatively stable (within ±5). This shows that the enterprise has a good development trend from the long term to the short term, the various links of the industrial chain are coordinated smoothly, the market competitiveness is strong, and it has strong resistance to external shocks.

[0048] When 60<= OHI<80, the enterprise is in a state that requires attention. The following situations may exist: 1) The annual operation index is stable, but the quarterly or monthly operation index fluctuates to a certain extent (the quarterly index fluctuates within ±15, and the monthly index fluctuates within ±10). This may mean that the enterprise is affected by short-term market demand changes, seasonal factors, or local supply chain adjustments. 2) The annual operation index has a slight downward trend (the decline is within 5%), and the quarterly and monthly operation indexes also fluctuate accordingly. This situation suggests that there may be potential problems in long-term development, and further analysis is needed on the upstream and downstream of the industrial chain, such as the stability of raw material supply, changes in market share, etc. When OHI < 60, the overall health status of the enterprise sends out an early warning signal. It may be that the annual operation index has declined significantly (the decline exceeds 5%), the quarterly operation index fluctuates violently (the fluctuation exceeds ± 20), and the monthly operation index fluctuates greatly (the fluctuation exceeds ± 15). This situation indicates that the enterprise may face serious problems, such as the deterioration of the macroeconomic environment, core technology bottlenecks, significant market share loss, long-term shortage of key raw materials, etc., and timely response measures need to be taken, such as adjusting production strategies, seeking strategic cooperation, optimizing supply chains, etc. The weights and index values ​​of the annual, quarterly and monthly operation indexes can be re-evaluated regularly (e.g. quarterly or semi-annually) to adapt to changes in industrial development and the external environment. If an enterprise makes major strategic adjustments, new market opportunities emerge or major changes occur in macroeconomic policies, it is necessary to adjust the weights and recalculate the comprehensive operation health index in a timely manner to ensure the accuracy and effectiveness of the evaluation results.

[0049] By evaluating the comprehensive operation health index of each enterprise, the operation health index of the entire target industrial chain can be obtained, thereby providing timely and accurate industrial chain operation monitoring information to enterprises and relevant departments, and providing strong support for decision-making.

[0050] The industrial chain operation power index constructed by the present invention measures the health of the industrial chain operation from three dimensions: annual, quarterly, and monthly, which is not available in the prior art. Most of the prior art is macro or single-dimensional analysis, which cannot provide in-depth insight into the dynamic changes within the industrial chain. Our index calculation takes into account a variety of electricity-related factors and can capture the development trend, stability, and potential problems of the industrial chain more finely. For example, by comparing the changes in the index in different time dimensions, short-term fluctuations and long-term trends can be discovered in a timely manner, rather than only being able to understand the general situation with a lag as in the prior art, which greatly improves the accuracy of industrial chain operation monitoring.

[0051] In addition, in terms of analyzing the relationship between chain leader enterprises and upstream and downstream enterprises, the present invention uses the correlation analysis of electricity consumption data to establish a more scientific monitoring system. The driving effect of chain leader enterprises on upstream and downstream enterprises is analyzed through the trend of electricity consumption changes, and the smooth flow of links such as raw material procurement and product sales is clarified. Compared with the existing technology that only analyzes the relationship between enterprises from a macro level, our in-depth analysis based on electricity data can more accurately judge the impact of problems such as shortage of raw materials and sales obstruction on the industrial chain, thereby providing a more reliable basis for decisions such as orderly electricity consumption plans, and effectively reducing the negative impact on the industrial chain and industrial economy.

[0052] In summary, in an embodiment of the present invention, the contract capacity information between each enterprise in the target industrial chain and the power company in the current year, the actual monthly electricity consumption data of the enterprise in each month in the current year, and the actual annual electricity consumption data of the enterprise in the previous year are obtained, and the annual operation index, quarterly operation index, and monthly operation index of each enterprise are calculated respectively. According to the preset weights of the annual operation index, the quarterly operation index, and the monthly operation index, the weighted sum of the annual operation index, the quarterly operation index, and the monthly operation index is obtained to obtain the comprehensive operation health index of the enterprise. In this scheme, the electricity consumption of users in the industrial chain is directly obtained from the power company's electricity consumption collection system. This data acquisition method is more direct, accurate and targeted; and, according to the constructed industrial chain operation power index, the operation health of the industrial chain is measured from three dimensions of annual, quarterly, and monthly, and a variety of electricity-related factors are comprehensively considered. It can more finely capture the development trend, stability and potential problems of the industrial chain, and greatly improve the accuracy of industrial chain operation monitoring. In addition, this plan uses the correlation analysis of electricity consumption data to establish a more scientific monitoring system. In-depth analysis based on electricity data can more accurately judge the impact of problems such as shortages of raw materials and sales obstructions on the industrial chain, thereby providing a more reliable basis for decisions such as orderly electricity consumption plans.

[0053] In a possible implementation, step 102 includes: Step 1021: Determine the annual actual electricity consumption data of the enterprise in the current year based on the monthly actual electricity consumption data; and determine the annual contract capacity information of the enterprise in the current year based on the monthly contract capacity information; Step 1022: determine the quotient of the annual actual power consumption and the annual contract capacity information to obtain the contract capacity utilization rate of the enterprise; Step 1023: Determine the year-on-year change rate of the enterprise's annual electricity consumption according to the annual actual electricity consumption data of the current year and the annual actual electricity consumption data of the previous year; Step 1024: according to the preset weights of the contract capacity utilization rate and the annual year-on-year change rate of electricity consumption, weighted summation is performed on the contract capacity utilization rate and the annual year-on-year change rate of electricity consumption to obtain the annual operation index of the enterprise.

[0054] In step 1021-step 1024, the actual power consumption data of each month is Add them up to get the actual annual electricity consumption data for the current year .

[0055] The monthly contract capacity information for each month Add them together to get the annual contract capacity information 12 .

[0056] In this way, the company's contract capacity utilization rate The calculation formula is: (4) Assume that the actual annual electricity consumption data for the current year is , the actual annual electricity consumption data for the previous year was , then the year-on-year change rate of annual electricity consumption is The calculation formula is: (5) Based on industry analysis and experience, the contract capacity utilization rate Setting weights , annual electricity consumption year-on-year change rate Setting weights For example, to set the contract capacity utilization weight =0.6, weight of year-on-year change rate of electricity consumption =0.4.

[0057] Thus, the calculation formula of the annual operation index is: (6) The annual operation index of each enterprise in the target industrial chain can comprehensively evaluate the annual operation health of the industrial chain.

[0058] In a possible implementation, step 104 includes: Step 1041: Calculate a first difference between the number of new enterprises and the number of exited enterprises; Step 1042, obtaining the total number of enterprises in the target industrial chain in the previous quarter; Step 1043: Calculate the ratio of the first difference to the total number of enterprises to obtain the quarterly rate of change of the number of enterprises.

[0059] In steps 1041 to 1043, the number of new enterprises is set to The number of exiting enterprises is , the total number of enterprises in the target industry chain in the previous quarter was , then the quarterly rate of change in the number of enterprises The calculation formula is: (7) In a possible implementation, step 105 includes: According to the preset weights of the seasonal fluctuation coefficient and the quarterly enterprise quantity change rate, the seasonal fluctuation coefficient and the quarterly enterprise quantity change rate are weighted and summed to obtain the quarterly operation index of the enterprise.

[0060] Specifically, according to industry characteristics and data analysis, the seasonal fluctuation coefficient S is determined. ik Weight and the rate of change of the number of enterprises R ik Weight For example, setting =0.7, =0.3.

[0061] The quarterly operating index The calculation formula is: (8) In a possible implementation, step 106 includes: Step 1061, obtaining first actual power consumption data of the current month, and obtaining second actual power consumption data of the previous month of the current month; Step 1062: Calculate a second difference between the first actual power consumption data and the second actual power consumption data; Step 1063: Calculate the quotient between the second difference and the second actual electricity consumption data to obtain the month-on-month change rate of electricity consumption of the enterprise in the current month.

[0062] In step 1061-step 1063, the first actual power consumption data is assumed to be , the second actual power consumption data is , then the month-on-month change rate of electricity consumption in the current month is The calculation formula is: (9) In a possible implementation, step 108 includes: According to the preset weights of the month-on-month change rate of electricity consumption and the industry coordinated change coefficient, the month-on-month change rate of electricity consumption and the industry coordinated change coefficient are weighted and summed to obtain the monthly operation index of the enterprise.

[0063] Specifically, according to the structure of the industrial chain and the data correlation, the month-on-month change rate of electricity consumption H is set. im Weight and the rate of change of the number of enterprises C jm Weight For example, setting =0.6, =0.4.

[0064] Monthly Operation Index The calculation formula is: (10) Figure 2 is a structural block diagram of an industrial chain operation monitoring system based on power big data provided by an embodiment of the present invention. Figure 2 As shown, the system 200 includes: The acquisition module 201 is used to acquire the contract capacity information between the enterprise and the power company in the current year, the actual monthly electricity consumption data of the enterprise in each month in the current year, and the actual annual electricity consumption data of the enterprise in the previous year; The annual operation index determination module 202 is used to determine the annual operation index of the enterprise according to the contract capacity information, the monthly actual power consumption data and the annual actual power consumption data of the previous year; The fluctuation coefficient determination module 203 is used to obtain the quarterly actual electricity consumption data of the enterprise in the current quarter and the historical average electricity consumption data of the same quarter in historical years, and determine the seasonal fluctuation coefficient of the enterprise according to the ratio of the quarterly actual electricity consumption data to the historical average electricity consumption data of the same quarter; The quantity change rate determination module 204 is used to obtain the number of new enterprises in the target industrial chain connected to the power company in the current quarter, obtain the number of enterprises in the target industrial chain that have terminated cooperation with the power company, and determine the quarterly enterprise quantity change rate based on the number of new enterprises and the number of exiting enterprises; A quarterly operation index determination module 205, for determining the quarterly operation index of the enterprise according to the seasonal fluctuation coefficient and the quarterly enterprise quantity change rate; The month-on-month change rate determination module 206 is used to determine the month-on-month change rate of the enterprise's electricity consumption in the current month based on the actual monthly electricity consumption data; The synergistic variation coefficient determination module 207 is used to obtain the first average power consumption data of each enterprise in the target industry in which the enterprise in the target industrial chain is located in the current month, and the second average power consumption data of other industries in the target industrial chain in the current month, and determine the industry synergistic variation coefficient of the enterprise in the current month according to the ratio of the first average power consumption data to the second average power consumption data; A monthly operation index determination module 208, configured to determine the monthly operation index of the enterprise according to the month-on-month change rate of electricity consumption and the industry synergy change coefficient; The operation health index determination module 209 is used to weighted sum the annual operation index, the quarterly operation index, and the monthly operation index according to the preset weights of the annual operation index, the quarterly operation index, and the monthly operation index to obtain the comprehensive operation health index of the enterprise.

[0065] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0066] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0067] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that comply with the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are to be considered exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0068] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for monitoring the operation of an industrial chain based on power big data, characterized in that: The method comprises: Obtain the monthly contract capacity information of each enterprise in the target industrial chain and the power company in each month of the current year, the actual monthly electricity consumption data of the enterprise in each month of the current year, and the actual annual electricity consumption data of the enterprise in the previous year; Determine the annual operation index of the enterprise according to the monthly contract capacity information, the monthly actual electricity consumption data and the annual actual electricity consumption data of the previous year; Obtaining the quarterly actual electricity consumption data of the enterprise in the current quarter and the historical average electricity consumption data of the same quarter in historical years, and determining the seasonal fluctuation coefficient of the enterprise based on the ratio of the quarterly actual electricity consumption data to the historical average electricity consumption data of the same quarter; Obtain the number of new enterprises in the target industrial chain connected to the power company in the current quarter, obtain the number of enterprises in the target industrial chain that have terminated cooperation with the power company, and determine the quarterly rate of change of the number of enterprises based on the number of new enterprises and the number of exiting enterprises; Determine the quarterly operation index of the enterprise according to the seasonal fluctuation coefficient and the quarterly enterprise quantity change rate; Determine the month-on-month change rate of the enterprise's electricity consumption in the current month based on the actual electricity consumption data of the month; Obtain the first average electricity consumption data of each enterprise in the target industry in which the enterprise in the target industrial chain is located in the current month, and the second average electricity consumption data of other industries in the target industrial chain in the current month, and determine the industry synergy change coefficient of the enterprise in the current month according to the ratio of the first average electricity consumption data to the second average electricity consumption data; Determine the monthly operation index of the enterprise according to the month-on-month change rate of electricity consumption and the industry coordinated change coefficient; According to the preset weights of the annual operation index, the quarterly operation index and the monthly operation index, the annual operation index, the quarterly operation index and the monthly operation index are weighted and summed to obtain the comprehensive operation health index of the enterprise.

2. The method according to claim 1, characterized in that Determining the annual operation index of the enterprise according to the contract capacity information, the monthly actual electricity consumption data and the annual actual electricity consumption data of the previous year includes: Determine the annual actual electricity consumption data of the enterprise in the current year based on the monthly actual electricity consumption data; and determine the annual contract capacity information of the enterprise in the current year based on the monthly contract capacity information; Determine the quotient of the annual actual electricity consumption and the annual contract capacity information to obtain the contract capacity utilization rate of the enterprise; Determine the year-on-year change rate of the enterprise's annual electricity consumption based on the annual actual electricity consumption data of the current year and the annual actual electricity consumption data of the previous year; According to the preset weights of the contract capacity utilization rate and the annual electricity consumption year-on-year change rate, the contract capacity utilization rate and the annual electricity consumption year-on-year change rate are weighted and summed to obtain the annual operation index of the enterprise.

3. The method according to claim 1, characterized in that Determining the quarterly rate of change in the number of enterprises based on the number of new enterprises and the number of exiting enterprises includes: Calculating a first difference between the number of new enterprises and the number of exited enterprises; Obtain the total number of enterprises in the target industrial chain in the previous quarter; The ratio of the first difference and the total number of enterprises is calculated to obtain the quarterly rate of change of the number of enterprises.

4. The method according to claim 1, characterized in that: Determining the quarterly operation index of the enterprise according to the seasonal fluctuation coefficient and the quarterly enterprise quantity change rate includes: According to the preset weights of the seasonal fluctuation coefficient and the quarterly enterprise quantity change rate, the seasonal fluctuation coefficient and the quarterly enterprise quantity change rate are weighted and summed to obtain the quarterly operation index of the enterprise.

5. The method according to claim 1, characterized in that Determining the month-on-month change rate of the enterprise's electricity consumption in the current month based on the actual monthly electricity consumption data includes: Acquire first actual power consumption data of the current month, and acquire second actual power consumption data of the month before the current month; Calculating a second difference between the first actual power consumption data and the second actual power consumption data; The quotient between the second difference and the second actual electricity consumption data is calculated to obtain the month-on-month change rate of electricity consumption of the enterprise in the current month.

6. The method according to claim 1, characterized in that Determining the monthly operation index of the enterprise according to the month-on-month change rate of electricity consumption and the industry coordinated change coefficient includes: According to the preset weights of the month-on-month change rate of electricity consumption and the industry coordinated change coefficient, the month-on-month change rate of electricity consumption and the industry coordinated change coefficient are weighted and summed to obtain the monthly operation index of the enterprise.

7. The method according to claim 1, characterized in that After obtaining the comprehensive operational health index of the enterprise, it also includes: According to the pre-set evaluation interval, the comprehensive operation health index of each of the enterprises is evaluated, and the operation status of the target industrial chain is determined.

8. An industrial chain operation monitoring system based on power big data, characterized in that: The system comprises: An acquisition module is used to acquire the monthly contract capacity information of each enterprise in the target industrial chain and the power company in each month of the current year, the monthly actual electricity consumption data of the enterprise in each month of the current year, and the annual actual electricity consumption data of the enterprise in the previous year; An annual operation index determination module, used to determine the annual operation index of the enterprise according to the monthly contract capacity information, the monthly actual electricity consumption data and the annual actual electricity consumption data of the previous year; A fluctuation coefficient determination module is used to obtain the quarterly actual electricity consumption data of the enterprise in the current quarter and the historical average electricity consumption data of the same quarter in historical years, and determine the seasonal fluctuation coefficient of the enterprise according to the ratio of the quarterly actual electricity consumption data to the historical average electricity consumption data of the same quarter; A quantity change rate determination module is used to obtain the number of new enterprises in the target industrial chain connected to the power company in the current quarter, obtain the number of exiting enterprises in the target industrial chain that terminated cooperation with the power company, and determine the quarterly enterprise quantity change rate based on the number of new enterprises and the number of exiting enterprises; A quarterly operation index determination module, used to determine the quarterly operation index of the enterprise according to the seasonal fluctuation coefficient and the quarterly enterprise quantity change rate; A month-on-month change rate determination module is used to determine the month-on-month change rate of the enterprise's electricity consumption in the current month based on the actual electricity consumption data of the month; A synergistic variation coefficient determination module is used to obtain the first average electricity consumption data of each enterprise in the target industry in which the enterprise in the target industrial chain is located in the current month, and the second average electricity consumption data of other industries in the target industrial chain in the current month, and determine the industry synergistic variation coefficient of the enterprise in the current month according to the ratio of the first average electricity consumption data to the second average electricity consumption data; A monthly operation index determination module, used to determine the monthly operation index of the enterprise according to the month-on-month change rate of electricity consumption and the industry synergy change coefficient; The operation health index determination module is used to perform weighted summation of the annual operation index, the quarterly operation index, and the monthly operation index according to the preset weights of the annual operation index, the quarterly operation index, and the monthly operation index to obtain the comprehensive operation health index of the enterprise.

9. The system according to claim 8, characterized in that The annual operation index determination module is specifically used for: Determine the annual actual electricity consumption data of the enterprise in the current year based on the monthly actual electricity consumption data; and determine the annual contract capacity information of the enterprise in the current year based on the monthly contract capacity information; Determine the quotient of the annual actual electricity consumption and the annual contract capacity information to obtain the contract capacity utilization rate of the enterprise; Determine the year-on-year change rate of the enterprise's annual electricity consumption based on the annual actual electricity consumption data of the current year and the annual actual electricity consumption data of the previous year; According to the preset weights of the contract capacity utilization rate and the annual electricity consumption year-on-year change rate, the contract capacity utilization rate and the annual electricity consumption year-on-year change rate are weighted and summed to obtain the annual operation index of the enterprise.

10. The system according to claim 8, characterized in that The quantity change rate determination module is specifically used for: Calculating a first difference between the number of new enterprises and the number of exited enterprises; Obtain the total number of enterprises in the target industrial chain in the previous quarter; The ratio of the first difference and the total number of enterprises is calculated to obtain the quarterly rate of change of the number of enterprises.

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