CN113935549B - Comprehensive intelligent energy optimization scheduling system - Google Patents
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Abstract
The invention discloses a comprehensive intelligent energy optimization scheduling system, which belongs to the technical field of intelligent energy and comprises a resource mining module, a database and a server; the server is respectively in communication connection with the resource mining module and the database; the resource mining module is used for mining the energy resources of the production area of the industrial production enterprise, and the specific energy mining method comprises the following steps: acquiring a plant area plan, dividing the establishable areas by production area managers, acquiring image data of the establishable areas, establishing an identification model, processing the image data of the establishable areas through the identification model, and acquiring sunshine time and sunshine area corresponding to the establishable areas; the time threshold value and the area threshold value are set, the area which can be built and has the sunshine duration lower than the time threshold value is deleted, the energy resources of the production area of the industrial production enterprise are excavated through the resource excavation module, the energy consumption of the industrial production is relieved, and meanwhile, the energy consumption cost of the production enterprise is reduced.
Description
Technical Field
The invention belongs to the technical field of intelligent energy, and particularly relates to a comprehensive intelligent energy optimization scheduling system.
Background
At present, the energy transformation faces the problems of slow demand, excessive traditional capacity, prominent environmental problem, low overall efficiency and the like; the industrial production is the big household of energy consumption, occupy the head greatly in the energy consumption proportion, bring very big burden for the energy supply in region, energy consumption cost also occupies very big part in industrial production cost simultaneously, because industrial production enterprise can possess very big production area basically, but the renewable energy resource in the production area does not obtain abundant utilization, especially solar energy resource, the installation demand of solar panel is all satisfied to the big factory building in the production area, consequently need excavate the solar energy resource in the factory building, alleviate industrial production's energy consumption, reduce manufacturing enterprise's energy consumption cost simultaneously.
Disclosure of Invention
In order to solve the problems existing in the scheme, the invention provides a comprehensive intelligent energy optimization scheduling system.
The purpose of the invention can be realized by the following technical scheme:
a comprehensive intelligent energy optimization scheduling system comprises a resource mining module, a database and a server; the server is respectively in communication connection with the resource mining module and the database;
the resource mining module is used for mining the energy resources of the production area of the industrial production enterprise, and the specific energy mining method comprises the following steps:
acquiring a plant area plan, dividing the constructable area by a production area manager, acquiring image data of the constructable area, establishing an identification model, processing the image data of the constructable area through the identification model, and acquiring the sunshine time and the sunshine area corresponding to the constructable area;
setting a time threshold and an area threshold, deleting the constructable region with the sunshine time lower than the time threshold, deleting the constructable region with the sunshine area lower than the area threshold, and marking the rest constructable regions as regions to be constructed; the method comprises the steps of obtaining a region to be built as a region of a factory building roof, marking the region as a roof region, obtaining design bearing capacity of the roof corresponding to the factory building and solar panel information, converting the weight of a solar panel into roof load according to the solar panel information, and determining the installation number of the solar panels corresponding to the roof region; and (4) deleting the roofing areas with the mounting number of the solar panels lower than X1 in the roofing area, and marking the remaining areas to be built as mounting areas.
Further, after the installation area is marked, building three-dimensional models of installation areas in a factory are built, the installation areas are marked on the corresponding three-dimensional models, a plurality of video monitoring points are arranged in the installation areas and used for monitoring the installation areas, the video monitoring points are arranged in the building three-dimensional models, monitoring information of each video monitoring point is obtained, an induction area is arranged in the building three-dimensional models according to the monitoring range of each video monitoring point, and a quick connection channel between the induction area and the corresponding video monitoring point is built;
when the area in the building three-dimensional model is clicked, the coordinates of the corresponding area are obtained, the corresponding induction area is matched according to the coordinates of the corresponding area, and the monitoring picture of the corresponding video monitoring point is connected.
Furthermore, the server is in communication connection with an energy recycling module and an optimizing module.
Further, the energy recycling module is used for recycling energy generated in industrial production, and the specific method comprises the following steps:
the method comprises the steps of obtaining equipment information with mechanical vibration recovery and equipment information with heat recovery from the Internet, respectively marking the equipment information as vibration equipment and heat equipment, obtaining production equipment information in a factory area, matching the production equipment information with the vibration equipment and the heat equipment, marking the successfully matched production equipment as primary screening equipment, obtaining the number, power, recovery rate of a recovery device, refitting cost, enterprise scale and production energy consumption cost ratio of the primary screening equipment, integrating and marking the equipment information as input data, establishing a screening model, inputting the input data into the screening model, obtaining the screening label, and sending the screening label and the corresponding input data to a production area manager.
Further, the screening label comprises 01 and 02, and when the screening label is 01, the primary screening equipment is shown to meet the modification requirement; when the screening label is 02, the primary screening equipment is not qualified for refitting.
Further, the optimization module is used for optimizing energy use in industrial production, and the specific method comprises the following steps:
establishing an energy use method library, wherein the energy use method library comprises a plurality of classification sub-libraries which are used for storing energy use schemes of corresponding industries;
acquiring the industry to which the enterprise belongs, production scale, energy use types and energy use prices, and matching corresponding classification sub-libraries in an energy use method library according to the industry to which the enterprise belongs;
construction of a cosine similarity function
Wherein i and j are the interestingness vector of enterprise i and enterprise j respectively, and the interestingness vector comprises: the method comprises the following steps of (1) determining an interestingness function of an enterprise according to production scale scores, energy use type scores and energy use price scores:
and when wij > X2, recommending the corresponding energy optimization scheme to the plant management personnel.
Further, α1、α2、α3To adjust the coefficient, α1、α2、α3Has a value range of [0, 1]]。
Further, the energy usage method library is used for storing the optimized energy usage plan.
Compared with the prior art, the invention has the beneficial effects that: by establishing the building three-dimensional model, the installation and management of the solar panel are more convenient, and more visual observation data are provided for workers; through installing solar panel in the factory, excavate the solar energy resource in the factory, improve the resource utilization in the factory, reduce the energy resource consumption cost of enterprise, can reduce the burden of local energy supply simultaneously.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described below clearly and completely in conjunction with the embodiments, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Industrial production is a household with large energy consumption, occupies a large energy consumption ratio, brings a large burden to regional energy supply, and meanwhile, the energy consumption cost also occupies a large part of the industrial production cost.
As shown in fig. 1, a comprehensive intelligent energy optimization scheduling system includes a resource mining module, an energy recycling module, an optimization module, a database, and a server; the server is respectively in communication connection with the resource mining module and the database; the server is also in communication connection with an energy recycling module and an optimization module;
the resource mining module is used for mining the energy resources of the production area of the industrial production enterprise, because the industrial production enterprise basically has a large production area, but the renewable energy resources in the production area are not fully utilized, especially the solar energy resources, and a large number of plants in the production area meet the installation requirements of the solar panel, the solar energy resources in the plant area need to be mined, the energy consumption of industrial production is relieved, and the energy consumption cost of the production enterprise is reduced;
the specific energy mining method comprises the following steps:
acquiring a plant area plan, wherein the plant area refers to a production plant area of an industrial production enterprise, and a production area manager divides an establishable area, wherein the establishable area is an area without production planning and use in the plant area, and areas such as roads, reserved plant area construction places, parking lots and the like are not establishable areas and have great uncertainty, so that system judgment cannot be performed, great errors can be caused by the system judgment, the manual division can be more accurate, and long time can not be occupied; acquiring image data of a constructable area, establishing an identification model, processing the image data of the constructable area through the identification model, and acquiring sunshine time and sunshine area corresponding to the constructable area, wherein the sunshine area is the area which can be irradiated by sunlight;
setting a time threshold and an area threshold, wherein the time threshold and the area threshold are both set by discussion of an expert group, deleting the reconstructable region with the sunshine time lower than the time threshold, deleting the reconstructable region with the sunshine area lower than the area threshold, and marking the rest reconstructable region as a region to be reconstructed; the method comprises the steps of obtaining a region to be built as a region of a factory building roof, marking the region as a roof region, obtaining the design bearing capacity of the roof corresponding to the factory building, obtaining solar panel information, converting the weight of a solar panel into a roof load according to the solar panel information, and determining the installation quantity of the solar panels corresponding to the roof region, wherein the solar panel information comprises information such as weight, area and model; deleting the roof areas with the number of the solar panels in the roof areas lower than X1, wherein X1 is a threshold value, and marking the remaining areas to be built as installation areas;
establishing a building three-dimensional model of an installation area in a plant, namely, a plant plane graph which is not the installation area is still a two-dimensional plane, establishing a three-dimensional model for the building of the installation area, marking the installation area on the corresponding three-dimensional model, arranging a plurality of video monitoring points in the installation area for monitoring the installation area, arranging the video monitoring points in the building three-dimensional model, acquiring monitoring information of each video monitoring point, wherein the monitoring information comprises information such as the model of a camera and the monitoring area, setting a sensing area in the building three-dimensional model according to the monitoring range of each video monitoring point, the sensing area is the same as the monitoring range of the video monitoring point, and establishing a quick connection channel between the sensing area and the corresponding video monitoring point;
when an area in the building three-dimensional model is clicked, coordinates of the corresponding area are obtained, the corresponding induction area is matched according to the coordinates of the corresponding area, and a monitoring picture of the corresponding video monitoring point is connected;
by establishing the building three-dimensional model, the installation and management of the solar panel are more convenient, and more visual observation data are provided for workers; the solar panel is arranged in the plant area, so that solar energy resources in the plant area are excavated, the resource utilization rate in the plant area is improved, the energy consumption cost of enterprises is reduced, and meanwhile, the burden of local energy supply can be reduced;
the method for establishing the recognition model comprises the following steps: acquiring historical image data, setting corresponding sunshine time and sunshine area for the historical image data, and constructing an artificial intelligent model; the artificial intelligence model is a neural network model, and historical image data and corresponding sunshine time and sunshine area are divided into a training set, a test set and a check set according to a set proportion; training, testing and verifying the artificial intelligent model through a training set, a testing set and a verifying set; and marking the trained artificial intelligence model as a recognition model.
The energy recycling module is used for recycling energy generated in industrial production, the provided energy is not fully and effectively utilized in the industrial production, and a large part of energy is converted into mechanical energy and thermal energy of mechanical vibration, so that the energy is wasted;
the specific method comprises the following steps:
acquiring equipment information with mechanical vibration recovery and equipment information with heat recovery from the Internet, wherein the equipment information comprises information such as model, volume, recovery rate and recovery device, the recovery device refers to a device for energy recovery, generally, refitted equipment is respectively marked as vibrating equipment and heat equipment, production equipment information in a factory area is acquired, the production equipment information comprises information such as model, volume and quantity, the production equipment information is matched with the vibrating equipment and the heat equipment, the specific matching mode is model and type matching, the successfully matched production equipment is marked as prescreened equipment, the number, power and recovery rate of the recovery device, refitted cost, enterprise scale and production energy consumption cost are acquired, the equipment information is integrated and marked as input data, a screening model is established, and the input data is input into the screening model, obtaining screening labels, wherein the screening labels comprise 01 and 02, and when the screening label is 01, the primary screening equipment is shown to meet the modification requirement; when the screening label is 02, the primary screening equipment is indicated to be not in accordance with the modification requirement; sending the screening labels and the corresponding input data to a production area manager;
the method for establishing the screening model comprises the following steps: acquiring historical screening data, wherein the historical screening data comprises the number and power of primary screening equipment, the recovery rate of a recovery device, refitting cost, enterprise scale and production energy consumption cost ratio, setting corresponding screening labels for the historical image data, and constructing an artificial intelligent model; the artificial intelligence model is a neural network model, and historical screening data and corresponding screening labels are divided into a training set, a test set and a check set according to a set proportion; training, testing and verifying the artificial intelligent model through a training set, a testing set and a verifying set; and marking the trained artificial intelligence model as a screening model.
The optimization module is used for optimizing energy use in industrial production, and the specific method comprises the following steps:
establishing an energy use method library, wherein the energy use method library is used for storing the optimized energy use scheme and also storing the energy use scheme which is discussed and set by an expert group, and the energy use method library comprises a plurality of classification sub-libraries which are used for storing the energy use scheme of the corresponding industry;
acquiring the industry to which the enterprise belongs, production scale, energy use types and energy use price, wherein the energy use types are the energy types used in the enterprise, and matching corresponding classification sub-libraries in an energy use method library according to the industry to which the enterprise belongs;
construction of cosine similarity function
Wherein i and j are the interest degree vectors of enterprise i and enterprise j respectively, the smaller the included angle between i and j is, the higher the similarity is, and the interest degree vectors include: production scale scoring, energy use type scoring and energy use price scoring; the production scale scoring, the energy use type scoring and the energy use price scoring are all scoring by comparing the enterprise i with the enterprise j, for example, the production scales of the enterprise i and the enterprise j are compared and the scoring is carried out;
illustratively, the format of the interestingness vector is a triple (x1, x2, x3), and the interestingness function of the enterprise is determined according to the production scale score, the energy usage category score and the energy usage price score:
wherein alpha is1、α2、α3To adjust the coefficient, α1、α2、α3Has a value range of [0, 1]]F, t and r are respectively the production scale, the energy use type and the energy use price of the enterprise; setting an initial value and a value read from a database respectively for the production scale, the energy use type and the energy use price;
fijrepresents the production scale score of business i to business j, fminFor the minimum production-size score recorded in the database, fmaxScoring the maximum production scale recorded in the database; t is tijScoring energy usage categories of Enterprise j for Enterprise i, tmaxScoring the maximum energy usage class recorded in the database, tminScoring the smallest energy usage category recorded in the database; r isijScoring energy use price of Enterprise j for Enterprise i, rmaxScore for maximum energy use price recorded in database, rminScoring the minimum energy use price recorded in the database;
adjustment factor alpha1、α2、α3Can be within a specified range, i.e., [0, 1]]Generating random numbers, and then optimizing coefficients through a genetic algorithm; f. t and r are data of recording enterprise, and the set initial value is substituted into the objective function wijThe iterative computation can be carried out by using a genetic algorithm toolbox carried in matlab software through the genetic algorithm optimization coefficient and the initial value;
and when wij > X2, recommending the corresponding energy optimization scheme to the factory floor management personnel, wherein X2 is a threshold value.
The above formulas are all calculated by removing dimensions and taking numerical values thereof, the formula is a formula which is obtained by acquiring a large amount of data and performing software simulation to obtain the closest real situation, and the preset parameters and the preset threshold value in the formula are set by the technical personnel in the field according to the actual situation or obtained by simulating a large amount of data.
Although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the spirit and scope of the present invention.
Claims (4)
1. A comprehensive intelligent energy optimization scheduling system is characterized by comprising a resource mining module, a database and a server; the server is respectively in communication connection with the resource mining module and the database;
the resource mining module is used for mining the energy resources of the production area of the industrial production enterprise, and the specific energy mining method comprises the following steps:
acquiring a plant area plan, dividing the constructable area by a production area manager, acquiring image data of the constructable area, establishing an identification model, processing the image data of the constructable area through the identification model, and acquiring the sunshine time and the sunshine area corresponding to the constructable area;
setting a time threshold and an area threshold, deleting the constructable region with the sunshine time lower than the time threshold, deleting the constructable region with the sunshine area lower than the area threshold, and marking the rest constructable regions as regions to be constructed; the method comprises the steps of obtaining a region to be built as a region of a factory building roof, marking the region as a roof region, obtaining design bearing capacity of the roof corresponding to the factory building and solar panel information, converting the weight of a solar panel into roof load according to the solar panel information, and determining the number of solar panels corresponding to the roof region; deleting the roof areas with the number of the solar panels in the roof area lower than X1, wherein X1 is a threshold value, and marking the remaining areas to be built as installation areas;
the server is in communication connection with an energy recycling module and an optimizing module;
the energy recycling module is used for recycling energy generated in industrial production, and the specific method comprises the following steps:
acquiring equipment information with mechanical vibration recovery and equipment information with heat recovery from the Internet, respectively marking the equipment information as vibration equipment and heat equipment, acquiring production equipment information in a plant area, matching the production equipment information with the vibration equipment and the heat equipment, marking the successfully matched production equipment as primary screening equipment, acquiring the number, power, recovery rate of a recovery device, refitting cost, enterprise scale and production energy consumption cost ratio of the primary screening equipment, integrating and marking the equipment information as input data, establishing a screening model, inputting the input data into the screening model, acquiring a screening label, and sending the screening label and the corresponding input data to a production area manager;
the optimization module is used for optimizing energy use in industrial production, and the specific method comprises the following steps:
establishing an energy use method library, wherein the energy use method library comprises a plurality of classification sub-libraries which are used for storing energy use schemes of corresponding industries;
acquiring the industry to which the enterprise belongs, production scale, energy use types and energy use prices, and matching corresponding classification sub-libraries in an energy use method library according to the industry to which the enterprise belongs;
construction of a cosine similarity function
Wherein, i and j are the interestingness vector of enterprise i and enterprise j respectively, and the interestingness vector includes: the method comprises the following steps of (1) determining an interestingness function of an enterprise according to production scale scores, energy use type scores and energy use price scores:
wherein, alpha 1, alpha 2 and alpha 3 are regulating coefficients, the value ranges of alpha 1, alpha 2 and alpha 3 are [0, 1], fij represents the production scale score of enterprise j by enterprise i, fmin is the minimum production scale score recorded in the database, and fmax is the maximum production scale score recorded in the database; tij is the energy use type score of enterprise i on enterprise j, tmax is the maximum energy use type score recorded in the database, and tmin is the minimum energy use type score recorded in the database; rij is the energy usage price score for business i to business j, rmax is the maximum energy usage price score recorded in the database, and rmin is the minimum energy usage price score recorded in the database.
2. The comprehensive intelligent energy optimization scheduling system of claim 1, wherein after marking the installation area, a building three-dimensional model of the installation area in the plant area is established, the installation area is marked on the corresponding three-dimensional model, a plurality of video monitoring points are arranged in the installation area for monitoring the installation area, the video monitoring points are arranged in the building three-dimensional model, monitoring information of each video monitoring point is obtained, a sensing area is arranged in the building three-dimensional model according to the monitoring range of each video monitoring point, and a fast connection channel between the sensing area and the corresponding video monitoring point is established;
when the area in the building three-dimensional model is clicked, the coordinates of the corresponding area are obtained, the corresponding induction area is matched according to the coordinates of the corresponding area, and the monitoring picture of the corresponding video monitoring point is connected.
3. The integrated intelligent energy-optimized dispatching system of claim 1, wherein the screening labels include 01 and 02, and when the screening label is 01, the prescreening device is indicated to meet the modification requirement; when the screening label is 02, the primary screening equipment does not meet the modification requirement.
4. The integrated intelligent energy-optimized dispatching system of claim 1, wherein the energy usage method library is used for storing optimized energy usage schemes.
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