Data processing system and method based on comprehensive energy intelligent management platform

Abstract

The invention discloses a data processing system and method based on a comprehensive energy intelligent management platform, and relates to the technical field of energy data processing, and the method comprises the steps: outputting total energy index data through the comprehensive energy intelligent management platform, obtaining the total product demand of a target project, calculating the energy consumption based on the total product demand of the target project, and meanwhile, calculating the energy consumption. Acquiring real-time energy consumption under unit product production; on the basis of invalid additional product data in the product production process of the target project, forming a prediction model, and outputting invalid additional product prediction data under different total production amounts of the product; and obtaining storage loss and destruction loss under the invalid appendages of the unit, forming a processing work order of the target project based on the invalid appendage prediction data, and feeding back the processing work order to the administrator port. According to the invention, the precision degree of energy management can be improved, the energy structure is optimized, carbon emission is reduced, and green and low-carbon development is promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of energy data processing, and specifically to a data processing system and method based on an integrated energy intelligent management platform. Background Art

[0002] The integrated energy intelligent management platform is an intelligent energy management system built based on new generation information technologies such as the Internet of Things, big data, and artificial intelligence, aiming to achieve collaborative optimization and efficient utilization of multiple energies such as electricity, heat, cold, and gas. The platform is widely applied in fields such as industrial parks, smart cities, commercial buildings, and microgrids. Based on the multi-energy collaboration method, it realizes joint dispatching and complementary operation to improve energy utilization efficiency. However, in the current integrated energy intelligent management platform, almost all are for energy monitoring and processing during the production process, using algorithm models to achieve the best energy utilization rate during the production process, so as to achieve reasonable control of energy. However, it ignores that in the actual production process, there are many consumption factors in energy consumption. Taking the production of energy-added products as an example, during the product production process using production raw materials, there will inevitably be useless added products. For useless added products, the integrated energy intelligent management platforms on the market often define them as product losses during the production process and directly deduct them at the production end in the form of a ratio, resulting in blurred energy consumption data for the storage and destruction processes of useless added products, and further affecting the accuracy of the entire energy management and adding a large amount of losses to the energy consumption cost. Summary of the Invention

[0003] The purpose of the present invention is to provide a data processing system and method based on an integrated energy intelligent management platform to solve the problems proposed in the prior art.

[0004] To achieve the above purpose, the present invention provides the following technical solution: A data processing method based on an integrated energy intelligent management platform, the method includes:

[0005] S1. The integrated energy intelligent management platform outputs total energy index data, and the total energy index data refers to the real-time total energy consumption index of the integrated energy intelligent management platform applied to a target project;

[0006] S2. Obtain the total product demand of the target project, calculate the energy consumption based on the total product demand of the target project, and at the same time, obtain the real-time energy consumption per unit product production;

[0007] S3. Based on the data of ineffective additional products during the product production process of the target project, form a prediction model and output the predicted data of ineffective additional products under different total amounts of product production;

[0008] S4. Obtain the storage loss and destruction loss under the unit of invalid accessories, form a processing work order for the target project based on the predicted data of invalid accessories, and feedback it to the administrator port.

[0009] According to the above technical solution, the S1 includes:

[0010] Step S1-1: The integrated energy intelligent management platform reads the target project data input by the administrator, sorts out the time data required for the target project, determines the time cut-off node of the target project in the integrated energy intelligent management platform based on the time data required for the target project, and outputs the energy supply duration of the target project at the time cut-off node.

[0011] Step S1-2: The administrator manually assigns an energy weight to the target project on the integrated energy intelligent management platform, outputs the total energy index data, and marks the permission cut-off time of the total energy index data on the energy supply duration.

[0012] According to the above technical solution, the S2 includes:

[0013] Step S2-1: Based on the product requirements of the target project, call the energy consumption under the production of unit products of the target project in the historical database, including: marking the energy consumption of unit products of the target project in the historical database, and taking the average value as the energy consumption under the production of unit products of the target project called.

[0014] Step S2-2: Based on the energy consumption under the production of unit products of the target project and the total product demand of the target project, calculate and generate the total energy consumption of the target project. Based on the total energy consumption divided by the real-time total energy consumption index applied to the target project by the integrated energy intelligent management platform, if the formed data is less than the data difference between the time cut-off node and the current time node, feedback it to the administrator port for alarm.

[0015] According to the above technical solution, the step S3 includes:

[0016] Step S3-1: Obtain the data of invalid accessories in the production process of the target project in the historical database, and the data of invalid accessories includes the quantity of invalid accessories and the quantity of products produced by the target project.

[0017] Step S3-2: Write each group of invalid accessory data into a data set (x0, y0), where x0 refers to the quantity of products produced by the target project, and y0 refers to the quantity of invalid accessories, build a prediction model, and form the logical relationship between the quantity of products produced by the target project and the quantity of invalid accessories, specifically including:

[0018] Form a linear relationship equation for all data sets, and calculate the regression coefficient k1 using the least squares method to form a logical relationship of y0 = k1x0 + m, where m represents the constant term.

[0019] According to the above technical solution, the step S4 includes:

[0020] Step S4-1: Obtain the storage loss and destruction loss under the unit invalid addendum based on the experimental data. The storage consumption refers to the energy consumption during the storage of the unit invalid addendum, and the destruction loss refers to the energy consumption when the unit invalid addendum is destroyed;

[0021] Step S4-2: Take the unit time period as the processing work order time period of the target project. In the first time period of the processing work order time period of the target project, only products are produced, and the product production quantity of the formed target project is where T0 represents the real-time total energy consumption index of the integrated energy intelligent management platform applied to the target project; v0 represents the energy consumption under the production of a unit product of the target project; represents taking the integer of ;

[0022] Step S4-3: Starting from the second time period in the processing work order time period of the target project, there are three work order operations in each processing work order time period of the target project, including production operation, storage operation, and destruction operation. Construct an analysis model, specifically including:

[0023] Record the i-th time period as [a i , b i , n i-1 - b i , where a i refers to the newly produced quantity of the target project's products in the i-th time period; b i refers to the destruction quantity of the invalid addendum in the i-th time period; n i-1 refers to the quantity of the invalid addendum in the (i - 1)-th time period;

[0024] Then the energy consumption in the i-th time period is recorded as: T i = a i * v0 + b i * t0 + (n i-1 - b i ) * h0, where T i represents the energy consumption in the i-th time period; t0 represents the destruction loss under the unit invalid addendum; h0 represents the storage loss under the unit invalid addendum; for any time period, the energy consumption T i is less than T0. After the total production quantity of the target project's products is completed and all the invalid addenda are destroyed, the target project ends.

[0025] The system automatically forms several groups of processing work orders, obtains the total energy of each group of processing work orders in all time periods within the target project, and takes the maximum value of the total energy as the output work order to be fed back to the administrator port.

[0026] A data processing system based on an integrated energy intelligent management platform, the system includes:

[0027] The total energy index data module is used to output the real-time total energy consumption index of the integrated energy intelligent management platform applied to the target project;

[0028] The real-time energy consumption statistics module is used to obtain the total product demand of the target project, calculate the energy consumption based on the total product demand of the target project, and at the same time, obtain the real-time energy consumption under the production of a unit product;

[0029] The invalid accessory prediction module forms a prediction model based on the invalid accessory data in the product production process of the target project, and outputs the invalid accessory prediction data under different total amounts of product production;

[0030] The work order management module is used to obtain the storage loss and destruction loss under a unit of invalid accessories, form the processing work order of the target project based on the invalid accessory prediction data, and feed it back to the administrator port.

[0031] According to the above technical solution, the total energy index data module further includes: the integrated energy intelligent management platform reads the target project data input by the administrator, sorts out the time data required for the target project, determines the time cut-off node of the target project on the integrated energy intelligent management platform based on the time data required for the target project, and outputs the energy supply duration of the target project at the time cut-off node; the administrator manually assigns an energy weight to the target project on the integrated energy intelligent management platform, outputs the total energy index data, and marks the permission cut-off time of the total energy index data on the energy supply duration.

[0032] According to the above technical solution, the real-time energy consumption statistics module further includes: based on the product demand of the target project, calling the energy consumption under the production of a unit product of the target project in the historical database, including: marking the energy consumption of a unit product of the target project in the historical database, and taking the average value as the energy consumption under the production of a unit product of the target project to be called; based on the energy consumption under the production of a unit product of the target project and the total product demand of the target project, calculating and generating the total energy consumption of the target project, and based on the total energy consumption divided by the real-time total energy consumption index of the integrated energy intelligent management platform applied to the target project, if the formed data is less than the data difference between the time cut-off node and the current time node, it is fed back to the administrator port for alarm.

[0033] According to the above technical solution, the storage consumption refers to the energy consumption during the storage of unit ineffective accessories, and the destruction loss refers to the energy consumption when unit ineffective accessories are destroyed.

[0034] Compared with the prior art, the beneficial effects of the present invention are as follows: During the production process of this application, the energy additional products can be fully considered. For the useless additional products, the storage loss and destruction loss brought by them are analyzed in detail. The product loss in the production process can be newly defined, the accuracy of energy management can be improved, the energy structure can be optimized, carbon emissions can be reduced, and green and low-carbon development can be promoted. Description of the Drawings

[0035] Figure 1 It is a schematic diagram of the steps of the data processing method based on the integrated energy intelligent management platform of the present invention. Specific Embodiments

[0036] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0037] Embodiment: As Figure 1 shown, the present invention provides a data processing method based on an integrated energy intelligent management platform, and the method includes:

[0038] The integrated energy intelligent management platform outputs total energy index data, and the total energy index data refers to the real-time total energy consumption index of the integrated energy intelligent management platform applied to the target project;

[0039] The integrated energy intelligent management platform reads the target project data input by the administrator, sorts out the time data required for the target project, determines the time cut-off node of the target project on the integrated energy intelligent management platform based on the time data required for the target project, and outputs the energy supply duration of the target project at the time cut-off node;

[0040] The administrator manually assigns an energy weight to the target project on the integrated energy intelligent management platform, outputs the total energy index data, and marks the permission cut-off time of the total energy index data on the energy supply duration.

[0041] Obtain the total product demand of the target project, calculate the energy consumption based on the total product demand of the target project, and at the same time, obtain the real-time energy consumption under the production of unit products;

[0042] Based on the product requirements of the target project, call the energy consumption per unit product production of the target project in the historical database, including: mark the energy consumption per unit product of the target project in the historical database, and take the average value as the energy consumption per unit product production of the target project to be called;

[0043] Based on the energy consumption per unit product production of the target project and the total product demand of the target project, calculate and generate the total energy consumption of the target project. Based on the total energy consumption divided by the real-time total energy consumption index of the integrated energy intelligent management platform applied to the target project, if the formed data is less than the data difference between the time cut-off node and the current time node, feedback to the administrator port for alarm.

[0044] Based on the invalid add-on data in the product production process of the target project, form a prediction model and output the predicted invalid add-on data under different total product productions;

[0045] Obtain the invalid add-on data in the product production process of the target project during the production process in the historical database. The invalid add-on data includes the quantity of invalid add-ons and the quantity of product production of the target project;

[0046] Write each group of invalid add-on data as a data set (x0, y0), where x0 refers to the quantity of product production of the target project, and y0 refers to the quantity of invalid add-ons. Build a prediction model to form the logical relationship between the quantity of product production and the quantity of invalid add-ons of the target project, specifically including:

[0047] Form a linear relationship equation for all data sets, calculate the regression coefficient k1 using the least squares method, and form a logical relationship of y0 = k1x0 + m, where m represents the constant term.

[0048] Obtain the storage loss and destruction loss per unit invalid add-on, form a processing work order for the target project based on the predicted invalid add-on data, and feedback to the administrator port.

[0049] Obtain the storage loss and destruction loss per unit invalid add-on based on experimental data. The storage consumption refers to the energy consumption during the storage of per unit invalid add-on, and the destruction loss refers to the energy consumption when per unit invalid add-on is destroyed;

[0050] Take the unit time period as the processing work order time period of the target project. In the first time period of the processing work order time period of the target project, only products are produced, then the quantity of product production of the target project formed is where, T0 represents the real-time total energy consumption index of the integrated energy intelligent management platform applied to the target project; v0 represents the energy consumption per unit product production of the target project; represents taking the integer of ;

[0051] Starting from the second time period in the processing work order time period of the target project, there are three work order operations in the processing work order time period of each target project, including production operation, storage operation, and destruction operation. An analysis model is constructed, specifically including:

[0052] For the i-th time period, it is denoted as [a i , b i , n i-1 -b i , where a i refers to the newly produced quantity of the products of the target project within the i-th time period; b i refers to the destruction quantity of the invalid accessories within the i-th time period; n i-1 refers to the quantity of the invalid accessories within the (i - 1)-th time period;

[0053] Then the energy consumption in the i-th time period is denoted as: T i = a i * v0 + b i * t0 + (n i-1 - b i ) * h0, where T i represents the energy consumption in the i-th time period; t0 represents the destruction loss per unit of invalid accessories; h0 represents the storage loss per unit of invalid accessories; for any time period, the energy consumption T i is less than T0. After the total production demand of the products of the target project is completed and all the invalid accessories are destroyed, the target project ends;

[0054] The system automatically forms several groups of processing work orders, obtains the total energy of each group of processing work orders in all time periods of the target project, and takes the maximum value of the total energy as the output work order and feedbacks it to the administrator port.

[0055] In this embodiment, a data processing system based on an integrated energy intelligent management platform is further provided. The system includes:

[0056] The total energy index data module is used to output the real-time total energy consumption index of the integrated energy intelligent management platform applied to the target project;

[0057] The real-time energy consumption statistics module is used to obtain the total product demand of the target project, calculate the energy consumption based on the total product demand of the target project, and at the same time, obtain the real-time energy consumption per unit of product production;

[0058] The invalid accessory prediction module forms a prediction model based on the invalid accessory data in the product production process of the target project, and outputs the invalid accessory prediction data under different total product productions;

[0059] The work order management module is used to obtain the storage loss and destruction loss of unit invalid accessories, form a processing work order for the target project based on the predicted data of invalid accessories, and feedback it to the administrator port.

[0060] The total energy index data module further includes: the integrated energy intelligent management platform reads the target project data input by the administrator, sorts out the time data required for the target project, determines the time cut-off node of the target project on the integrated energy intelligent management platform based on the time data required for the target project, and outputs the energy supply duration of the target project at the time cut-off node; the administrator manually assigns an energy weight to the target project on the integrated energy intelligent management platform, outputs the total energy index data, and marks the permission cut-off time of the total energy index data on the energy supply duration.

[0061] The real-time energy consumption statistics module further includes: based on the product demand of the target project, calling the energy consumption under the production of unit products of the target project in the historical database, including: marking the energy consumption of unit products of the target project in the historical database, and taking the average value as the energy consumption under the production of unit products of the target project called; calculating and generating the total energy consumption of the target project based on the energy consumption under the production of unit products of the target project and the total product demand of the target project, and dividing the total energy consumption by the real-time total energy consumption index applied to the target project by the integrated energy intelligent management platform. If the formed data is less than the data difference between the time cut-off node and the current time node, it is feedback to the administrator port for alarm.

[0062] The storage consumption refers to the energy consumption during the storage of unit invalid accessories, and the destruction loss refers to the energy consumption when unit invalid accessories are destroyed.

[0063] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and without departing from the spirit or basic characteristics of the present invention, the present invention can be implemented in other specific forms. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, it is intended to embrace all changes falling within the meaning and scope of the equivalent elements of the claims in the present invention. Any reference signs in the claims should not be regarded as limiting the claimed rights.

Claims

1. A data processing method based on an integrated energy intelligent management platform, characterized in that: The method includes: S1. The integrated energy intelligent management platform outputs total energy index data, where the total energy index data refers to the real-time total energy consumption index of the integrated energy intelligent management platform applied to the target project; S2. Obtain the total product demand of the target project, calculate the energy consumption based on the total product demand of the target project. At the same time, obtain the real-time energy consumption per unit product production; S3. Based on the invalid add-on data in the product production process of the target project, form a prediction model and output the predicted data of invalid add-ons under different total product productions; S4. Obtain the storage loss and destruction loss per unit of invalid add-on, form a processing work order for the target project based on the predicted data of invalid add-ons, and feedback it to the administrator port.

2. The data processing method based on the integrated energy intelligent management platform according to claim 1, wherein: The S1 includes: Step S1-1: The integrated energy intelligent management platform reads the target project data input by the administrator, sorts out the time data required for the target project, determines the time cut-off node of the target project on the integrated energy intelligent management platform based on the required time data of the target project, and outputs the energy supply duration of the target project at the time cut-off node; Step S1-2: The administrator manually assigns an energy weight to the target project on the integrated energy intelligent management platform, outputs the total energy index data, and marks the permission cut-off time of the total energy index data on the energy supply duration.

3. The data processing method based on the integrated energy intelligent management platform according to claim 2, wherein: The S2 includes: Step S2-1: Based on the product demand of the target project, call the energy consumption per unit product production of the target project in the historical database, including: mark the energy consumption per unit product of the target project in the historical database, and take the average value as the energy consumption per unit product production of the called target project; Step S2-2: Calculate and generate the total energy consumption of the target project based on the energy consumption per unit product production of the target project and the total product demand of the target project. Divide the total energy consumption by the real-time total energy consumption index of the integrated energy intelligent management platform applied to the target project. If the formed data is less than the data difference between the time cut-off node and the current time node, feedback it to the administrator port for alarm.

4. The data processing method based on the integrated energy intelligent management platform according to claim 3, wherein: The step S3 includes: Step S3-1: Obtain the invalid add-on data in the product production process of the target project during the production process in the historical database. The invalid add-on data includes the quantity of invalid add-ons and the quantity of product production of the target project; Step S3-2: Write each group of invalid add-on data as a data set (x0, y0), where x0 refers to the quantity of product production of the target project, and y0 refers to the quantity of invalid add-ons. Build a prediction model to form the logical relationship between the quantity of product production and the quantity of invalid add-ons of the target project, specifically including: Form a linear relationship equation for all data sets, calculate the regression coefficient k1 using the least squares method, and form a logical relationship of y0 = k1x0 + m, where m represents the constant term.

5. The data processing method based on the integrated energy intelligent management platform according to claim 4, characterized in that: The step S4 includes: Step S4-1: Obtain the storage loss and destruction loss per unit of invalid add-on based on experimental data. The storage consumption refers to the energy consumption during the storage of per unit of invalid add-on, and the destruction loss refers to the energy consumption when per unit of invalid add-on is destroyed; Step S4-2: Take the unit time period as the processing work order time period of the target project. If only products are produced in the first time period within the processing work order time period of the target project, the product production quantity of the target project formed is wherein, T0 represents the real-time total energy consumption index of the integrated energy intelligent management platform applied to the target project; v0 represents the energy consumption per unit product production of the target project; represents taking the integer of ; Step S4-3: Starting from the second time period in the processing work order time period of the target project, there are three work order operations in the processing work order time period of each target project, including production operations, storage operations, and destruction operations. Construct an analysis model, specifically including: For the i-th time period, it is denoted as [a i , b i , n i-1 - b i , where a i refers to the newly produced quantity of the target item's products within the i-th time period; b i refers to the quantity of invalid accessories destroyed within the i-th time period; n i-1 refers to the quantity of invalid accessories in the (i - 1)-th time period; Then the energy consumption in the i-th time period is denoted as: T i = a i * v0 + b i * t0 + (n i-1 - b i ) * h0, where T i represents the energy consumption in the i-th time period; t0 represents the destruction loss under unit ineffective accessories; h0 represents the storage loss under unit ineffective accessories; for any time period, the energy consumption T i is less than T0. After the total production demand of the target project's products is completed and all the ineffective accessories are completely destroyed, the target project ends; The system automatically forms several groups of processing work orders, obtains the total energy of each group of processing work orders in all time periods within the target project, and takes the maximum value of the total energy as the output work order and feeds it back to the administrator port.

6. A data processing system based on an integrated energy intelligent management platform, using the data processing method based on the integrated energy intelligent management platform as described in claim 1, characterized in that: The system includes: The total energy index data module is used to output the real-time total energy consumption index of the integrated energy intelligent management platform applied to the target project; The real-time energy consumption statistics module is used to obtain the total product demand of the target project, calculate the energy consumption based on the total product demand of the target project, and at the same time, obtain the real-time energy consumption under the production of a unit product; The invalid accessory prediction module forms a prediction model based on the invalid accessory data in the product production process of the target project, and outputs the invalid accessory prediction data under different total amounts of product production; The work order management module is used to obtain the storage loss and destruction loss under a unit of invalid accessories, form the processing work order of the target project based on the invalid accessory prediction data, and feed it back to the administrator port.

7. The data processing system based on the integrated energy intelligent management platform according to claim 6, wherein: The total energy index data module further includes: The integrated energy intelligent management platform reads the target project data input by the administrator, sorts out the time data required for the target project, determines the time cut-off node of the target project on the integrated energy intelligent management platform based on the time data required for the target project, and outputs the energy supply duration of the target project at the time cut-off node; The administrator manually assigns an energy weight to the target project on the integrated energy intelligent management platform, outputs the total energy index data, and marks the permission cut-off time of the total energy index data on the energy supply duration.

8. The data processing system based on the integrated energy intelligent management platform according to claim 6, wherein: The real-time energy consumption statistics module further includes: Based on the product demand of the target project, call the energy consumption under the production of a unit product of the target project in the historical database, including: Mark the energy consumption of a unit product of the target project in the historical database, and take the average value as the energy consumption under the production of a unit product of the target project called; Calculate and generate the total energy consumption of the target project based on the energy consumption under the production of a unit product of the target project and the total product demand of the target project. Based on the total energy consumption divided by the real-time total energy consumption index of the integrated energy intelligent management platform applied to the target project, if the formed data is less than the data difference between the time cut-off node and the current time node, feed it back to the administrator port for alarm.

9. The data processing system based on the integrated energy intelligent management platform according to claim 6, characterized in that: The storage consumption refers to the energy consumption when storing a unit of invalid accessories, and the destruction loss refers to the energy consumption when a unit of invalid accessories is destroyed.

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