CN115471003B - Flexible control-based intelligent energy consumption adjusting method and system - Google Patents
Flexible control-based intelligent energy consumption adjusting method and system Download PDFInfo
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Abstract
The invention discloses an intelligent energy consumption adjusting method and system based on flexible control, and relates to the technical field of computers, wherein the method comprises the following steps: the enterprise energy consumption data item acquisition of the target park is carried out through an energy consumption item metering platform, and energy consumption item metering data is generated; obtaining enterprise energy consumption identification data and constructing a data tag; constructing sub-item energy consumption constraint parameters through enterprise information and energy supply information; generating an energy consumption optimization evaluation result; obtaining enterprise feedback information; and adjusting the enterprise energy consumption based on the enterprise feedback information. The method solves the problems that in the prior art, multidimensional and multi-aspect exploration and analysis cannot be carried out on actual energy data of a park, energy regulation and control are not specific, so that flexible energy consumption management and control are inaccurate and unreasonable, energy utilization rate cannot be effectively improved, energy consumption regulation effect is affected, and enterprise energy consumption is even affected. The effects of improving the energy utilization rate, reducing the energy consumption cost and further promoting sustainable energy utilization and green low-carbon development are achieved.
Description
Technical Field
The invention relates to the technical field of computers, in particular to an intelligent energy consumption adjusting method and system based on flexible control.
Background
Along with the rapid development of economy, the problems of energy shortage, environmental deterioration, low energy conversion efficiency and the like are increasingly highlighted, more and more countries start to adjust energy structures, search new energy development modes and improve energy utilization rate, wherein an economic growth mode for changing high-speed growth into high-quality growth indicates a direction for the high-quality development of new era. In the prior art, when regional energy is regulated and controlled, multi-angle and multi-aspect exploration of energy consumption cannot be carried out, and the problems that energy regulation and control are inaccurate, unreasonable and non-pertinence and do not meet the actual energy use condition exist. Therefore, the research utilizes the computer technology to flexibly control the energy consumption of each enterprise in the energy consumption park, improves the utilization rate of energy sources on the basis of meeting the energy consumption requirements of the enterprises, and has important significance for promoting sustainable utilization of the energy sources and developing a green low-carbon society.
However, in the prior art, multidimensional and multi-aspect exploration and analysis cannot be carried out on the actual energy data of the park, and then the problems that energy regulation and control are not specific, so that flexible energy consumption management and control are inaccurate and unreasonable, the energy utilization rate cannot be effectively improved, the energy consumption regulation effect is finally influenced, and even the energy consumption of enterprises in the park is influenced are solved.
Disclosure of Invention
The invention aims to provide an intelligent energy consumption adjusting method and system based on flexible control, which are used for solving the problems that in the prior art, multidimensional and multi-aspect exploration and analysis cannot be carried out on actual energy data of a park, and further, the energy regulation and control are not targeted, so that the flexible control of the energy consumption is inaccurate and unreasonable, the energy utilization rate cannot be effectively improved, the energy consumption adjusting effect is finally influenced, and even the energy consumption of enterprises in the park is influenced.
In view of the above problems, the invention provides an intelligent energy consumption adjusting method and system based on flexible control.
In a first aspect, the invention provides an intelligent energy consumption adjusting method based on flexible control, which is realized by an intelligent energy consumption adjusting system based on flexible control, wherein the method comprises the following steps: the energy consumption sub-metering platform is used for carrying out enterprise energy consumption data sub-collection of the target park, so as to generate enterprise energy consumption sub-metering data; obtaining energy consumption identification data of enterprises, and constructing a data tag of the energy consumption sub-item metering data based on the energy consumption identification data; constructing sub-item energy consumption constraint parameters of the target park according to the enterprise information and the energy supply information of the target park; performing energy consumption optimization evaluation based on the data tag and the sub-term energy consumption constraint parameters to generate an energy consumption optimization evaluation result; the energy consumption optimization evaluation result is sent to enterprises of the target park, and enterprise feedback information is obtained; and adjusting the enterprise energy consumption of the target park based on the enterprise feedback information.
In a second aspect, the present invention further provides an intelligent energy consumption adjustment system based on flexible control, for performing an intelligent energy consumption adjustment method based on flexible control as described in the first aspect, where the system includes: the data acquisition module is used for carrying out enterprise energy consumption data item acquisition of the target park through the energy consumption item metering platform to generate enterprise energy consumption item metering data; the label construction module is used for obtaining energy consumption identification data of enterprises and constructing a data label of the energy consumption sub-metering data based on the energy consumption identification data; the constraint obtaining module is used for constructing sub-term energy consumption constraint parameters of the target park according to the enterprise information and the energy supply information of the target park; the optimizing evaluation module is used for carrying out energy consumption optimizing evaluation based on the data tag and the sub-item energy consumption constraint parameter to generate an energy consumption optimizing evaluation result; the feedback obtaining module is used for sending the energy consumption optimization evaluation result to an enterprise of the target park and obtaining enterprise feedback information; and the adjustment execution module is used for adjusting the enterprise energy consumption of the target park based on the enterprise feedback information.
One or more technical schemes provided by the invention have at least the following technical effects or advantages:
the energy consumption sub-metering platform is used for carrying out enterprise energy consumption data sub-collection of the target park, so as to generate enterprise energy consumption sub-metering data; obtaining energy consumption identification data of enterprises, and constructing a data tag of the energy consumption sub-item metering data based on the energy consumption identification data; constructing sub-item energy consumption constraint parameters of the target park according to the enterprise information and the energy supply information of the target park; performing energy consumption optimization evaluation based on the data tag and the sub-term energy consumption constraint parameters to generate an energy consumption optimization evaluation result; the energy consumption optimization evaluation result is sent to enterprises of the target park, and enterprise feedback information is obtained; and adjusting the enterprise energy consumption of the target park based on the enterprise feedback information. Through carrying out flexible management and control to the energy consumption of each enterprise in garden, on satisfying the basis of enterprise energy consumption demand, reached and improved energy utilization, reduced energy consumption cost, and then promoted the technical effect of energy sustainable utilization and green low carbon development.
The foregoing description is only an overview of the present invention, and is intended to be implemented in accordance with the teachings of the present invention in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present invention more readily apparent.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described below, it being obvious that the drawings in the description below are only exemplary and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of an intelligent energy consumption adjusting method based on flexible control;
FIG. 2 is a schematic flow chart of constructing sub-term energy consumption constraint parameters based on optimized energy consumption reference constraint data and energy supply information in the intelligent energy consumption adjustment method based on flexible control;
FIG. 3 is a schematic flow chart of constructing sub-term energy consumption constraint parameters by the sub-term energy consumption time period constraint parameters and the sub-term energy consumption total constraint parameters in the flexible control-based energy consumption intelligent regulation method;
FIG. 4 is a schematic flow chart of an energy consumption optimization evaluation result obtained in the intelligent energy consumption adjusting method based on flexible control;
fig. 5 is a schematic structural diagram of an intelligent energy consumption regulating system based on flexible control.
Reference numerals illustrate:
the system comprises a data acquisition module M100, a label construction module M200, a constraint acquisition module M300, an optimization evaluation module M400, a feedback acquisition module M500 and an adjustment execution module M600.
Detailed Description
The invention provides an intelligent energy consumption adjusting method and system based on flexible control, which solve the problems that in the prior art, multidimensional and multi-aspect exploration and analysis cannot be carried out on actual energy data of a park, and further, the energy regulation and control are not targeted, so that the flexible control of the energy consumption is inaccurate and unreasonable, the energy utilization rate cannot be effectively improved, the energy consumption adjusting effect is finally influenced, and even the energy consumption of enterprises in the park is influenced. Through carrying out flexible management and control to the energy consumption of each enterprise in garden, on satisfying the basis of enterprise energy consumption demand, reached and improved energy utilization, reduced energy consumption cost, and then promoted the technical effect of energy sustainable utilization and green low carbon development.
The technical scheme of the invention obtains, stores, uses, processes and the like the data, which all meet the relevant regulations of national laws and regulations.
In the following, the technical solutions of the present invention will be clearly and completely described with reference to the accompanying drawings, and it should be understood that the described embodiments are only some embodiments of the present invention, but not all embodiments of the present invention, and that the present invention is not limited by the exemplary embodiments described herein. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention. It should be further noted that, for convenience of description, only some, but not all of the drawings related to the present invention are shown.
Example 1
Referring to fig. 1, the invention provides an intelligent energy consumption adjusting method based on flexible control, wherein the method is applied to an intelligent energy consumption adjusting system, the intelligent energy consumption adjusting system is in communication connection with an energy consumption sub-metering platform, and the method specifically comprises the following steps:
step S100: the energy consumption sub-item metering platform is used for carrying out enterprise energy consumption data sub-item collection of the target park, so as to generate enterprise energy consumption sub-item metering data;
specifically, the intelligent energy consumption adjusting method based on flexible control is applied to the intelligent energy consumption adjusting system based on flexible control, and can improve the energy utilization rate on the basis of meeting the energy consumption requirements of enterprises by carrying out flexible control on the energy consumption of each enterprise in a target park. The target park is any industrial park for flexible control of energy consumption by using the intelligent energy consumption adjusting system. An exemplary textile industry park, such as a market, includes a plurality of textile manufacturing enterprises. And carrying out energy consumption data of each enterprise in the target park through an energy consumption sub-metering platform for sub-item collection, wherein the energy consumption sub-metering platform is in communication connection with a plurality of energy consumption metering devices, and the plurality of energy consumption metering devices are assembled after comprehensive analysis according to actual production energy consumption conditions of the enterprise and the like. In an exemplary textile industry park, various energy consumption data acquisition is performed on a cashmere fabric production enterprise, and cashmere fiber washing energy consumption, cashmere fiber drying energy consumption, cashmere fiber spinning energy consumption, cashmere yarn weaving energy consumption, cashmere woven fabric dyeing energy consumption, cashmere woven fabric rinsing energy consumption and the like of the cashmere fabric production enterprise are sequentially acquired.
By sequentially collecting various energy consumption data of enterprises in the target park, the energy consumption sub-metering data of the enterprises are obtained, and the technical effects of providing a data basis and a regulating and controlling basis for the follow-up flexible regulation and control of the energy consumption of the enterprises in the park are achieved.
Step S200: obtaining energy consumption identification data of enterprises, and constructing a data tag of the energy consumption sub-item metering data based on the energy consumption identification data;
specifically, the enterprises in the target park are sequentially subjected to energy consumption identification data acquisition, and further, data tags of energy consumption item metering data of the corresponding enterprises are constructed based on the energy consumption identification data. Exemplary, if a textile enterprise performs cashmere woven fabric dyeing in a certain period, the total energy consumption is 14.3KW, and the energy consumption label of the corresponding cashmere woven fabric dyeing is 15KW, it indicates that the actual energy consumption of the enterprise is lower than the label, and the cashmere woven fabric dyeing of the enterprise is cut down and labeled. The technical aim of providing an intuitive label foundation for the follow-up energy consumption flexible regulation and control of energy consumption projects of enterprises in a park is achieved by establishing the data labels.
Step S300: constructing sub-item energy consumption constraint parameters of the target park according to the enterprise information and the energy supply information of the target park;
further, as shown in fig. 2, step S300 of the present invention further includes:
step S310: obtaining enterprise scale information according to the enterprise information, and taking the enterprise scale information as energy consumption constraint reference data;
step S320: obtaining enterprise demand information according to the enterprise information, carrying out energy consumption sub-term occupation ratio weight distribution of an enterprise based on the enterprise demand information, and carrying out energy consumption constraint reference data optimization based on the energy consumption sub-term occupation ratio weight distribution to obtain optimized energy consumption reference constraint data;
step S330: and constructing the sub-term energy consumption constraint parameters based on the optimized energy consumption reference constraint data and the energy supply information.
Further, as shown in fig. 3, step S330 of the present invention further includes:
step S331: obtaining constraint parameters of total energy consumption of enterprise sub-items according to the optimized energy consumption reference constraint data and the energy supply information;
step S332: obtaining historical energy consumption sub-metering data, wherein the historical energy consumption sub-metering data has a consumption time identifier;
step S333: performing time period consumption analysis of the sub-term energy sources through the historical energy consumption sub-term metering data, and generating sub-term energy consumption time period constraint parameters according to a time period consumption analysis result;
step S334: and constructing the sub-item energy consumption constraint parameters according to the sub-item energy consumption period constraint parameters and the sub-item energy consumption total constraint parameters.
Specifically, the actual data of each enterprise in the target park is acquired sequentially, and the specific energy supply data in the target park is acquired. And firstly, sequentially acquiring enterprise scale information of each enterprise in the target park, and taking the acquired enterprise scale information as energy consumption constraint reference data. For example, if the occupied area of the enterprise A is 5000 km, the occupied area of the enterprise B is 1000 km, and the occupied area of the enterprise B is 450 km, the energy consumption of the enterprise A is integrally larger than that of the enterprise B. And then, sequentially collecting enterprise demand information of each enterprise in the target park, and distributing energy consumption sub-item duty ratio weights of the enterprises according to the collected enterprise demand information. Exemplary production activities such as cashmere fiber washing energy consumption, cashmere fiber drying energy consumption, cashmere fiber spinning energy consumption, cashmere yarn weaving energy consumption, cashmere woven fabric dyeing energy consumption, cashmere woven fabric rinsing energy consumption and the like are carried out by a cashmere fabric production enterprise, the enterprise carries out energy consumption estimation on each production activity according to comprehensive analysis of historical production conditions and the like, so that each energy consumption data of the cashmere fabric production enterprise is obtained, and then each energy consumption data is calculated, so that energy consumption fractional duty weight distribution is obtained. And optimizing the energy consumption constraint reference data based on the energy consumption fractional duty ratio weight distribution to obtain optimized energy consumption reference constraint data.
Further, the total energy consumption constraint parameters of the enterprise sub-items are obtained according to the optimized energy consumption reference constraint data and the energy supply information, and meanwhile, historical energy consumption sub-item metering data of the enterprise in the target park are collected. Wherein the historical energy consumption itemized data has a consumption time identification. Exemplary is 3 kilowatts in the first quarter, 4 kilowatts in the second quarter, and 5.5 kilowatts in the third quarter of an enterprise 2020, wherein the data is specific to a single day of energy consumption of the enterprise. And then, carrying out time period consumption analysis of the sub-item energy sources through the historical energy consumption sub-item metering data, and generating sub-item energy consumption time period constraint parameters according to the time period consumption analysis result. Exemplary, if the first quarter energy consumption of an enterprise is much lower than the other quarter energy consumption, the first quarter energy consumption supply of the enterprise is limited. And finally, constructing the sub-item energy consumption constraint parameters through the sub-item energy consumption period constraint parameters and the sub-item energy consumption total amount constraint parameters.
The sub-item energy consumption constraint parameters of each enterprise in the target park are constructed through the sub-item energy consumption time period constraint parameters and the sub-item energy consumption total amount constraint parameters, the dual constraint target based on the total energy consumption and the energy time period consumption is achieved, and the technical effects of improving the rationality and the effectiveness of regulation are achieved through energy consumption regulation based on the refined constraint parameters.
Step S400: performing energy consumption optimization evaluation based on the data tag and the sub-term energy consumption constraint parameters to generate an energy consumption optimization evaluation result;
further, as shown in fig. 4, step S400 of the present invention further includes:
step S410: performing energy consumption period translation analysis of the enterprise based on the data tag and the sub-term energy consumption constraint parameters to obtain an energy consumption translation period optimization result;
step S420: carrying out energy consumption transfer analysis of enterprises through the data labels and the sub-item energy consumption constraint parameters to obtain an energy consumption transfer optimization result;
step S430: carrying out energy consumption reduction analysis on enterprises through the data tag to obtain an energy consumption reduction analysis result;
step S440: and obtaining the energy consumption optimization evaluation result according to the energy consumption translation period optimization result, the energy consumption transfer optimization result and the energy consumption reduction analysis result.
Further, the invention also comprises the following steps:
step S451: constructing processing priorities of energy consumption translation time period, energy consumption transfer and energy consumption reduction;
step S452: processing and marking the energy consumption optimization evaluation result through the processing priority;
step S453: and carrying out enterprise energy consumption adjustment of the target park by processing the identification result.
Specifically, before energy consumption optimization evaluation is performed based on the data tag and the sub-term energy consumption constraint parameter, a processing priority of energy consumption adjustment is firstly constructed, and then energy consumption adjustment analysis is sequentially performed according to the priority.
Firstly, by comprehensively analyzing the means characteristics of each energy consumption adjustment process, constructing the process priorities of energy consumption translation period, energy consumption transfer and energy consumption reduction according to analysis results, then, carrying out process identification on the energy consumption optimization evaluation results according to the process priorities, and carrying out enterprise energy consumption adjustment of the target park according to identification results. Further, performing translation analysis of the energy consumption time period of the corresponding enterprise according to the data tag and the sub-item energy consumption constraint parameter, and obtaining an energy consumption translation time period optimization result. And then, according to the processing priority, carrying out energy consumption transfer analysis of the enterprise through the data tag and the sub-item energy consumption constraint parameter, obtaining an energy consumption transfer optimization result, and finally, carrying out energy consumption reduction analysis of the enterprise through the data tag, and obtaining an energy consumption reduction analysis result. Wherein, translation, transfer and reduction all belong to flexible regulation means. And finally, obtaining the energy consumption optimization evaluation result according to the energy consumption translation period optimization result, the energy consumption transfer optimization result and the energy consumption reduction analysis result.
The energy consumption evaluation data of the corresponding enterprises in the target park are obtained based on various flexible regulation and control analysis, so that the technical aim of providing a comprehensive, objective and effective evaluation data basis for the follow-up energy consumption regulation of the enterprises is achieved.
Step S500: the energy consumption optimization evaluation result is sent to enterprises of the target park, and enterprise feedback information is obtained;
step S600: and adjusting the enterprise energy consumption of the target park based on the enterprise feedback information.
Further, the invention also comprises the following steps:
step S610: obtaining the information matching degree parameters of the energy consumption optimization evaluation result and the enterprise feedback information;
step S620: constructing an enterprise optimization tag according to the information matching degree parameter;
step S630: obtaining optimized actual energy consumption data of an enterprise, and analyzing response uncertainty of the enterprise according to the optimized actual energy consumption data and the enterprise feedback information to generate an enterprise response uncertainty evaluation parameter;
step S640: and carrying out subsequent energy consumption adjustment management on the enterprise according to the enterprise optimization label and the enterprise response uncertainty evaluation parameter.
Further, the invention also comprises the following steps:
step S641: setting an optimized label initial value set;
step S642: obtaining an enterprise evaluation value through the enterprise optimization tag and the initial value set of the optimization tag;
step S643: the enterprise evaluation value is adjusted through the enterprise response uncertainty evaluation parameter, and an enterprise evaluation adjustment value is obtained;
step S644: matching an energy consumption rewarding policy according to the enterprise evaluation adjustment value;
step S645: and carrying out subsequent energy consumption adjustment management of the enterprise based on the energy consumption rewarding policy.
Specifically, after the energy consumption optimization evaluation result is sent to the enterprise of the target park, enterprise feedback information of the corresponding enterprise is obtained, and enterprise energy consumption adjustment of the target park is performed based on the enterprise feedback information. The enterprise feedback information refers to comparison analysis information of various energy consumption data determined by the corresponding enterprise according to actual production activity conditions and the energy consumption optimization evaluation result.
And firstly, matching the energy consumption optimization evaluation result with the enterprise feedback information, correspondingly calculating to obtain an information matching degree parameter, and taking the information matching degree parameter as an enterprise optimization label of the enterprise. And then, acquiring the actual energy consumption data of the enterprise in real time to obtain optimized actual energy consumption data, and analyzing response uncertainty of the enterprise according to the optimized actual energy consumption data and the enterprise feedback information to generate an enterprise response uncertainty evaluation parameter. The actual energy consumption of the enterprise is larger than the energy consumption in the feedback information of the enterprise, so that the actual energy consumption of the enterprise is uncertainty and is influenced by environmental factors, human factors and other factors. Further, an optimizing label initial value set is set, and enterprise evaluation values are obtained through the enterprise optimizing labels and the optimizing label initial value set. And then, adjusting the enterprise evaluation value through the enterprise response uncertainty evaluation parameter to obtain an enterprise evaluation adjustment value. And matching the energy consumption rewarding policy according to the enterprise evaluation adjustment value, and carrying out subsequent energy consumption adjustment management of the enterprise based on the energy consumption rewarding policy. And finally, carrying out subsequent energy consumption adjustment management on the enterprise according to the enterprise optimization label and the enterprise response uncertainty evaluation parameter.
Through carrying out flexible management and control to the energy consumption of each enterprise in garden, on satisfying the basis of enterprise energy consumption demand, reached and improved energy utilization, reduced energy consumption cost, and then promoted the technical effect of energy sustainable utilization and green low carbon development.
In summary, the intelligent energy consumption adjusting method based on flexible control provided by the invention has the following technical effects:
the energy consumption sub-metering platform is used for carrying out enterprise energy consumption data sub-collection of the target park, so as to generate enterprise energy consumption sub-metering data; obtaining energy consumption identification data of enterprises, and constructing a data tag of the energy consumption sub-item metering data based on the energy consumption identification data; constructing sub-item energy consumption constraint parameters of the target park according to the enterprise information and the energy supply information of the target park; performing energy consumption optimization evaluation based on the data tag and the sub-term energy consumption constraint parameters to generate an energy consumption optimization evaluation result; the energy consumption optimization evaluation result is sent to enterprises of the target park, and enterprise feedback information is obtained; and adjusting the enterprise energy consumption of the target park based on the enterprise feedback information. Through carrying out flexible management and control to the energy consumption of each enterprise in garden, on satisfying the basis of enterprise energy consumption demand, reached and improved energy utilization, reduced energy consumption cost, and then promoted the technical effect of energy sustainable utilization and green low carbon development.
Example two
Based on the same inventive concept as the energy consumption intelligent regulation method based on flexible control in the foregoing embodiment, the present invention further provides an energy consumption intelligent regulation system based on flexible control, referring to fig. 5, the system includes:
the data acquisition module M100 is used for carrying out enterprise energy consumption data item acquisition of the target park through the energy consumption item metering platform to generate energy consumption item metering data of an enterprise;
the label construction module M200 is used for obtaining energy consumption identification data of enterprises, and constructing a data label of the energy consumption sub-item metering data based on the energy consumption identification data;
the constraint obtaining module M300 is used for constructing sub-item energy consumption constraint parameters of the target park according to the enterprise information and the energy supply information of the target park, wherein the constraint obtaining module M300 is used for obtaining the sub-item energy consumption constraint parameters of the target park according to the enterprise information and the energy supply information of the target park;
the optimization evaluation module M400 is used for carrying out energy consumption optimization evaluation based on the data tag and the sub-term energy consumption constraint parameter, and generating an energy consumption optimization evaluation result;
the feedback obtaining module M500 is used for sending the energy consumption optimization evaluation result to an enterprise of the target park and obtaining enterprise feedback information;
and the adjustment execution module M600 is used for adjusting the enterprise energy consumption of the target park based on the enterprise feedback information.
Further, the constraint obtaining module M300 in the system is further configured to:
obtaining enterprise scale information according to the enterprise information, and taking the enterprise scale information as energy consumption constraint reference data;
obtaining enterprise demand information according to the enterprise information, carrying out energy consumption sub-term occupation ratio weight distribution of an enterprise based on the enterprise demand information, and carrying out energy consumption constraint reference data optimization based on the energy consumption sub-term occupation ratio weight distribution to obtain optimized energy consumption reference constraint data;
and constructing the sub-term energy consumption constraint parameters based on the optimized energy consumption reference constraint data and the energy supply information.
Further, the constraint obtaining module M300 in the system is further configured to:
obtaining constraint parameters of total energy consumption of enterprise sub-items according to the optimized energy consumption reference constraint data and the energy supply information;
obtaining historical energy consumption sub-metering data, wherein the historical energy consumption sub-metering data has a consumption time identifier;
performing time period consumption analysis of the sub-term energy sources through the historical energy consumption sub-term metering data, and generating sub-term energy consumption time period constraint parameters according to a time period consumption analysis result;
and constructing the sub-item energy consumption constraint parameters according to the sub-item energy consumption period constraint parameters and the sub-item energy consumption total constraint parameters.
Further, the optimization evaluation module M400 in the system is further configured to:
performing energy consumption period translation analysis of the enterprise based on the data tag and the sub-term energy consumption constraint parameters to obtain an energy consumption translation period optimization result;
carrying out energy consumption transfer analysis of enterprises through the data labels and the sub-item energy consumption constraint parameters to obtain an energy consumption transfer optimization result;
carrying out energy consumption reduction analysis on enterprises through the data tag to obtain an energy consumption reduction analysis result;
and obtaining the energy consumption optimization evaluation result according to the energy consumption translation period optimization result, the energy consumption transfer optimization result and the energy consumption reduction analysis result.
Further, the adjustment execution module M600 in the system is further configured to:
obtaining the information matching degree parameters of the energy consumption optimization evaluation result and the enterprise feedback information;
constructing an enterprise optimization tag according to the information matching degree parameter;
obtaining optimized actual energy consumption data of an enterprise, and analyzing response uncertainty of the enterprise according to the optimized actual energy consumption data and the enterprise feedback information to generate an enterprise response uncertainty evaluation parameter;
and carrying out subsequent energy consumption adjustment management on the enterprise according to the enterprise optimization label and the enterprise response uncertainty evaluation parameter.
Further, the adjustment execution module M600 in the system is further configured to:
setting an optimized label initial value set;
obtaining an enterprise evaluation value through the enterprise optimization tag and the initial value set of the optimization tag;
the enterprise evaluation value is adjusted through the enterprise response uncertainty evaluation parameter, and an enterprise evaluation adjustment value is obtained;
matching an energy consumption rewarding policy according to the enterprise evaluation adjustment value;
and carrying out subsequent energy consumption adjustment management of the enterprise based on the energy consumption rewarding policy.
Further, the optimization evaluation module M400 in the system is further configured to:
constructing processing priorities of energy consumption translation time period, energy consumption transfer and energy consumption reduction;
processing and marking the energy consumption optimization evaluation result through the processing priority;
and carrying out enterprise energy consumption adjustment of the target park by processing the identification result.
Various embodiments in the present disclosure are described in a progressive manner, and each embodiment focuses on the difference from other embodiments, and the foregoing method and specific example for intelligently adjusting energy consumption based on flexible control in the first embodiment of fig. 1 are also applicable to an intelligent energy consumption adjusting system based on flexible control in the present embodiment, and by the foregoing detailed description of an intelligent energy consumption adjusting method based on flexible control, those skilled in the art can clearly know that an intelligent energy consumption adjusting system based on flexible control in the present embodiment, so that the detailed description is omitted herein for brevity of the present disclosure. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the present invention and the equivalent techniques thereof, the present invention is also intended to include such modifications and variations.
Claims (7)
1. The utility model provides an energy consumption intelligent regulation method based on flexible management and control, its characterized in that, the method is applied to energy consumption intelligent regulation system, energy consumption intelligent regulation system and energy consumption minute metering platform communication connection, the method includes:
the energy consumption sub-item metering platform is used for carrying out enterprise energy consumption data sub-item collection of the target park, so as to generate enterprise energy consumption sub-item metering data;
obtaining energy consumption identification data of enterprises, and constructing a data tag of the energy consumption sub-item metering data based on the energy consumption identification data;
constructing sub-item energy consumption constraint parameters of the target park according to the enterprise information and the energy supply information of the target park;
performing energy consumption optimization evaluation based on the data tag and the sub-term energy consumption constraint parameters to generate an energy consumption optimization evaluation result;
the energy consumption optimization evaluation result is sent to enterprises of the target park, and enterprise feedback information is obtained;
adjusting the enterprise energy consumption of the target park based on the enterprise feedback information;
the method for constructing the sub-item energy consumption constraint parameters of the target park through the enterprise information and the energy supply information of the target park further comprises the following steps:
obtaining enterprise scale information according to the enterprise information, and taking the enterprise scale information as energy consumption constraint reference data;
obtaining enterprise demand information according to the enterprise information, carrying out energy consumption sub-term occupation ratio weight distribution of an enterprise based on the enterprise demand information, and carrying out energy consumption constraint reference data optimization based on the energy consumption sub-term occupation ratio weight distribution to obtain optimized energy consumption reference constraint data;
and constructing the sub-term energy consumption constraint parameters based on the optimized energy consumption reference constraint data and the energy supply information.
2. The method of claim 1, wherein the method further comprises:
obtaining constraint parameters of total energy consumption of enterprise sub-items according to the optimized energy consumption reference constraint data and the energy supply information;
obtaining historical energy consumption sub-metering data, wherein the historical energy consumption sub-metering data has a consumption time identifier;
performing time period consumption analysis of the sub-term energy sources through the historical energy consumption sub-term metering data, and generating sub-term energy consumption time period constraint parameters according to a time period consumption analysis result;
and constructing the sub-item energy consumption constraint parameters according to the sub-item energy consumption period constraint parameters and the sub-item energy consumption total constraint parameters.
3. The method of claim 1, wherein the method further comprises:
performing energy consumption period translation analysis of the enterprise based on the data tag and the sub-term energy consumption constraint parameters to obtain an energy consumption translation period optimization result;
carrying out energy consumption transfer analysis of enterprises through the data labels and the sub-item energy consumption constraint parameters to obtain an energy consumption transfer optimization result;
carrying out energy consumption reduction analysis on enterprises through the data tag to obtain an energy consumption reduction analysis result;
and obtaining the energy consumption optimization evaluation result according to the energy consumption translation period optimization result, the energy consumption transfer optimization result and the energy consumption reduction analysis result.
4. The method of claim 1, wherein the method further comprises:
obtaining the information matching degree parameters of the energy consumption optimization evaluation result and the enterprise feedback information;
constructing an enterprise optimization tag according to the information matching degree parameter;
obtaining optimized actual energy consumption data of an enterprise, and analyzing response uncertainty of the enterprise according to the optimized actual energy consumption data and the enterprise feedback information to generate an enterprise response uncertainty evaluation parameter;
and carrying out subsequent energy consumption adjustment management on the enterprise according to the enterprise optimization label and the enterprise response uncertainty evaluation parameter.
5. The method of claim 4, wherein the method further comprises:
setting an optimized label initial value set;
obtaining an enterprise evaluation value through the enterprise optimization tag and the initial value set of the optimization tag;
the enterprise evaluation value is adjusted through the enterprise response uncertainty evaluation parameter, and an enterprise evaluation adjustment value is obtained;
matching an energy consumption rewarding policy according to the enterprise evaluation adjustment value;
and carrying out subsequent energy consumption adjustment management of the enterprise based on the energy consumption rewarding policy.
6. A method as claimed in claim 3, wherein the method further comprises:
constructing processing priorities of energy consumption translation time period, energy consumption transfer and energy consumption reduction;
processing and marking the energy consumption optimization evaluation result through the processing priority;
and carrying out enterprise energy consumption adjustment of the target park by processing the identification result.
7. An intelligent energy consumption regulation system based on flexible management, characterized in that it is applied to the steps of the method according to any one of claims 1 to 6, said system comprising:
the data acquisition module is used for carrying out enterprise energy consumption data item acquisition of the target park through the energy consumption item metering platform to generate enterprise energy consumption item metering data;
the label construction module is used for obtaining energy consumption identification data of enterprises and constructing a data label of the energy consumption sub-metering data based on the energy consumption identification data;
the constraint obtaining module is used for constructing sub-term energy consumption constraint parameters of the target park according to the enterprise information and the energy supply information of the target park;
the optimizing evaluation module is used for carrying out energy consumption optimizing evaluation based on the data tag and the sub-item energy consumption constraint parameter to generate an energy consumption optimizing evaluation result;
the feedback obtaining module is used for sending the energy consumption optimization evaluation result to an enterprise of the target park and obtaining enterprise feedback information;
the adjustment execution module is used for adjusting the enterprise energy consumption of the target park based on the enterprise feedback information;
the constraint obtaining module is further configured to:
obtaining enterprise scale information according to the enterprise information, and taking the enterprise scale information as energy consumption constraint reference data;
obtaining enterprise demand information according to the enterprise information, carrying out energy consumption sub-term occupation ratio weight distribution of an enterprise based on the enterprise demand information, and carrying out energy consumption constraint reference data optimization based on the energy consumption sub-term occupation ratio weight distribution to obtain optimized energy consumption reference constraint data;
and constructing the sub-term energy consumption constraint parameters based on the optimized energy consumption reference constraint data and the energy supply information.
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