CN110991043A - Energy consumption modeling and evaluating method of energy consumption system - Google Patents
Energy consumption modeling and evaluating method of energy consumption system Download PDFInfo
- Publication number
- CN110991043A CN110991043A CN201911221623.0A CN201911221623A CN110991043A CN 110991043 A CN110991043 A CN 110991043A CN 201911221623 A CN201911221623 A CN 201911221623A CN 110991043 A CN110991043 A CN 110991043A
- Authority
- CN
- China
- Prior art keywords
- energy consumption
- data
- product
- energy
- unit product
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/80—Management or planning
- Y02P90/82—Energy audits or management systems therefor
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Feedback Control In General (AREA)
Abstract
The invention provides an energy consumption modeling and evaluating method of an energy consumption system, which comprises the following steps: constructing an energy consumption model for an energy consumption system; analyzing the energy consumption model to obtain a unit product comprehensive energy consumption model; and evaluating the process and equipment energy consumption of the energy consumption system by utilizing the comprehensive energy consumption model of the unit product to obtain an evaluation result, and generating an improvement suggestion for the process and equipment of the energy consumption system according to the evaluation result. According to the energy consumption modeling and evaluating method, the energy consumption model is analyzed to obtain a unit product comprehensive energy consumption model, the unit product comprehensive energy consumption model is evaluated, the process and equipment of the energy consumption system are improved according to the evaluation result, the process optimization is guided, the energy-saving space is evaluated, and the process is optimized according to the result predicted by the energy consumption model and corresponding energy-saving measures are guided to be made, so that the energy consumption is reduced, and the energy-saving goal is realized.
Description
Technical Field
The invention relates to the technical field of energy conservation, in particular to an energy consumption modeling and evaluating method of an energy consumption system.
Background
At present, the main production process flow of beer is as follows: the malt and the grain auxiliary materials are crushed → saccharified → filtered → the wort boiled → cooled → fermented → filtered → the beer → packaged. According to the analysis of steam consumption data, the steam consumption in the traditional beer process is mainly generated in the following steps: the saccharifying and wort making process accounts for 60% of the total amount of steam, the beer fermentation and filtration process accounts for 5% of the total amount of steam, and the beer packaging process accounts for 35% of the total amount of steam.
Wherein, wort boiling accounts for 60% in the steam consumption of the manufacturing procedure of the saccharified wort, and the reduction of the wort boiling steam consumption is an important link for reducing the wort steam consumption. The traditional wort boiling process is that malt and other grain auxiliary materials are saccharified and filtered to obtain wort, the wort enters a boiling pot and is heated by steam, the evaporation rate of the boiling process is more than 8 percent, the opening of a steam valve is 100 percent, the wort is continuously and intensively boiled and rolled, and the boiling time is 80-90 minutes. The traditional process is characterized by large wort evaporation capacity, high energy consumption, high wort heat load and easy beer aging. In order to reduce the cost, an energy consumption modeling and evaluating method of an energy consumption system is needed to optimize the process and guide the formulation of corresponding energy-saving measures according to the result predicted by an energy consumption model.
Disclosure of Invention
The invention provides an energy consumption modeling and evaluating method of an energy consumption system, which is used for reducing energy consumption and realizing the aim of energy conservation.
The invention provides an energy consumption modeling and evaluating method of an energy consumption system, which comprises the following steps:
step 1: constructing an energy consumption model for the energy consumption system;
step 2: analyzing the energy consumption model to obtain a unit product comprehensive energy consumption model;
and step 3: and evaluating the process and equipment energy consumption of the energy consumption system by using the unit product comprehensive energy consumption model to obtain an evaluation result, and generating an improvement suggestion for the process and equipment of the energy consumption system according to the evaluation result.
Further, in the step 1, constructing an energy consumption model for the energy consumption system, the following steps are performed:
step S101: the real-time energy consumption data of each process of the energy consumption system are acquired and stored on line to form an energy source database;
step S102: collecting and storing production data of each process of the energy consumption system to form a production database;
step S103: extracting the energy consumption data in the energy source database and the production data in the production database to a middle layer for conditioning, converting and integrating, and importing the energy consumption data and the production data into a data warehouse;
step S104: and constructing an energy consumption model for the energy consumption system according to the data in the data warehouse.
Further, in the step S104, the building an energy consumption model for the energy consumption system according to the data in the data warehouse performs the following steps:
step S1041: organizing the data in the data warehouse according to a multi-dimensional form to form multi-dimensional data;
step S1042: analyzing the multi-dimensional data to obtain an analysis result, wherein the analysis comprises slicing, cutting, drilling and rotating;
step S1043: and constructing and verifying an energy consumption model of the energy consumption system according to the analysis result.
Further, in the step 2, analyzing the energy consumption model to obtain a comprehensive energy consumption model of a unit product, and executing the following steps:
step S201: converting the energy consumption of the energy consumption system into comprehensive energy consumption according to the energy consumption type and by using a standard conversion coefficient;
step S202: calculating the comprehensive energy consumption of the unit product according to the comprehensive energy consumption and the product yield;
step S203: dividing the comprehensive energy consumption into the sum of products of product ratio coefficients in all processes of the energy consumption system and process energy consumption of all processes by adopting an e-p analysis method;
step S204: calculating the energy consumption change quantity of the product caused by the process energy consumption change of the process and the energy consumption change quantity of the product caused by the product ratio coefficient change by adopting an e-p analysis method;
step S205: and introducing an energy consumption reference line value by adopting an energy consumption reference factor method, and comparing the unit actual energy consumption with the unit product comprehensive energy consumption so as to judge the condition of the energy consumption system in the effective energy consumption.
Further, in the step S202, the following formula is adopted to calculate the comprehensive energy consumption per unit product,
wherein E is0Is the comprehensive energy consumption per unit product, TceThe total amount of energy consumed for producing the product in the statistical period, and T is the product yield in the statistical period;
in step S203, the integrated energy consumption is divided into the sum of products of product ratio coefficients in the respective processes of the energy consumption system and process energy consumptions of the respective processes by using the following formula,
wherein e isiFor the energy consumption of the individual processes in the production of the products, piThe product ratio coefficient is the yield of the product in each process and the yield of the finished product, i is 1,2,3, …, and N is the total number of the production processes of the product;
in the step S204, the product energy consumption change amount caused by the process energy consumption change of the process and the product energy consumption change amount caused by the product ratio coefficient change are calculated by the following formulas,
wherein delta E is total product energy consumption change amount, E'iAnd e ″)iRespectively at the beginning of the statistical period,Process energy consumption of the last i Process, p'iAnd p' are the product ratio coefficients of the ith process at the beginning and the end of the statistical period respectively, and the first term on the right side of the equation is the factor eiThe change of energy consumption of the product caused by the change is called direct energy saving, and the second term on the right side of the equation is piThe change of the energy consumption of the product caused by the change is called indirect energy saving;
in step S205, the unit actual energy consumption and the unit product integrated energy consumption are compared by the following formula,
wherein Gc is the energy consumption baseline value of the product production equipment, eIFor the actual energy consumption per unit of the production plant, ecThe energy consumption is the unit effective energy consumption of the product production equipment, and if Gc is 100%, the effective energy consumption reaches the standard condition; if Gc is>100%, the energy consumption is wasted and needs to be improved; if Gc is<100%, the energy consumption is better than the standard condition.
Further, in the step 3, the unit product comprehensive energy consumption model is used to evaluate the process and equipment energy consumption of the energy consumption system, so as to obtain an evaluation result, and an improvement suggestion for the process and equipment of the energy consumption system is generated according to the evaluation result, and the following steps are performed:
step S301: evaluating the energy efficiency of each process and equipment of the energy consumption system by using the comprehensive energy consumption model of the unit product and adopting an energy consumption reference factor method to obtain the evaluation result;
step S302: and generating a prediction and suggestion for reducing the energy consumption according to the evaluation result and the theoretical model of the unit product comprehensive energy consumption model so as to realize a set energy-saving target.
Further, in the step S101, a data acquisition system is used to perform online acquisition on the real-time energy consumption data of each process of the energy consumption system, an energy consumption monitoring system is used to monitor the real-time energy consumption data of each process of the energy consumption system,
wherein designing the data acquisition system comprises: the system comprises a gas flow data acquisition module consisting of a gas vortex flowmeter and a flow calculation microprocessor, a water consumption data acquisition module consisting of a photoelectric direct-reading remote water meter, a condensed water metering module and an electric energy metering module consisting of a mutual inductor and a three-phase electric meter;
the energy consumption monitoring system comprises an energy consumption monitoring system management platform, a data center, an energy consumption data acquisition terminal and an intelligent instrument, wherein the data center is used for receiving data reported by the energy consumption data acquisition terminal equipment, classifying and storing the data, and regularly transmitting the acquired data to an information cloud storage platform big data storage server through a wireless transmission device;
the server or the computer acquires corresponding energy consumption information through the cloud storage platform big data storage server, energy consumption monitoring system management platform software is used for centrally managing real-time energy consumption data of each process of the energy consumption system in the region under jurisdiction, and the centralized management comprises instrument management, acquisition terminal management, energy consumption management, data analysis and display and data report forms;
the energy consumption monitoring system management platform uses a B/S architecture; the energy consumption data acquisition terminal is arranged in workshops of each process of the energy consumption system and is responsible for data acquisition of energy consumption in each workshop, a special low-power consumption embedded acquisition device is adopted, the intelligent metering instrument is connected through a field bus, various main flow communication protocols are supported, data acquisition is actively carried out on the instrument and the sensing device, the data are uploaded to a data center layer at regular time or according to needs, AO and DO ports are provided, and meanwhile, a control command can be issued to the intelligent instrument; the intelligent instrument comprises an electric energy metering instrument with a data remote transmission function, sensing equipment and an actuator, wherein the electric energy metering instrument comprises a single-phase electric energy meter, a three-phase electric energy meter and a multifunctional electric energy meter, is in charge of real-time consumption metering of electric energy and provides original energy consumption data for the energy consumption data acquisition terminal.
Further, in step S1041, organizing the data in the data warehouse in a multidimensional manner to form multidimensional data, and performing the following steps:
receiving data information from an external database from a first database interface, establishing an attribute data warehouse for the received data information, and storing attribute data of the data information in the attribute data warehouse, wherein the database connected with the first database interface comprises an energy source database and a production database;
receiving geographic data from an external database from a second database interface, establishing a spatial data warehouse for the received geographic data, and storing the geographic data in the spatial data warehouse, wherein the geographic data is related to the data information, and the database connected with the second database interface comprises: a map database, a process database and a workshop database;
analyzing the attribute data of the data information stored in the attribute data warehouse to generate analysis data of the attribute data;
and establishing a multi-dimensional relation table between the analysis data and the geographic data.
Further, the energy consuming system comprises an energy consuming system for beer production, the process of the energy consuming system comprising a boiling process comprising 3 stages:
the first stage 1 is wort preheating, wherein wort entering a boiling pot from a temporary storage tank is preheated by heat recovered in the boiling process;
stage 2, the wort is boiled, and the wort is heated to a boiling state;
stage 3 is low pressure boiling and waste heat recovery to increase the evaporation speed, and the heat of the evaporated water vapor is recovered to be used for preheating the wort.
In the step 3, a proposal for improving the process and equipment of the energy consumption system is generated according to the evaluation result, and the proposal comprises adopting a pressurized boiling process, adopting a steam recovery process, adopting a wort preheating process or adopting a high concentration dilution process.
Further, in the step 3, the unit product integrated energy consumption model is used to evaluate the process and equipment energy consumption of the energy consumption system, so as to obtain an evaluation result, and according to the evaluation result, an improvement suggestion for the process and equipment of the energy consumption system is generated, and the following steps are performed:
step A301, acquiring the process and equipment energy consumption of the unit product by using the comprehensive energy consumption model of the unit product, and determining the comprehensive energy intensity of the unit product;
wherein f isiThe integrated energy intensity, K, for the ith unit producti,jEnergy consumption of the jth process for the ith unit product, Ci,jThe yield of the jth process for the ith unit product, Ci,j2The yield of the j2 th process of the ith unit product, N is the total process amount of the ith unit product, i is 1,2 and 3 … … It, wherein It is the unit product quantity, j is 1,2 and 3 … … N, and j2 is 1,2,3 … j-1, j +2.. N;
step A302, using the unit product corresponding to the minimum value of the comprehensive energy intensity as a base product;
step A303, determining the factor intensity of the unit product according to the base product;
fRSi＝fi-fFi-fIi
wherein, fFiIs the efficiency intensity of the ith unit product, K0,jEnergy consumption of the jth process for the base product, C0,jThe yield of the jth process for the base product, C0,j2Yield of the base product from the j2 th process, fIiStructural Strength of the ith Unit product, fRSiIs the decomposition margin of the ith unit product；
Step A304, determining the process energy consumption investment of each unit product;
wherein, KCi,jEnergy input for the jth process of the ith unit product, f0Is the integrated energy intensity of the base product;
step A305, performing energy consumption adjustment on each process of the energy consumption system according to the result of the step A304.
The energy consumption modeling and evaluating method of the energy consumption system provided by the embodiment of the invention has the following beneficial effects: the energy consumption model is analyzed to obtain a comprehensive energy consumption model of a unit product, the comprehensive energy consumption model is evaluated, the process and equipment of the energy consumption system are improved according to the obtained evaluation result, so that the process optimization and the energy-saving space evaluation can be guided through the analysis and comparison of the equipment and process energy consumption, the process and the equipment energy consumption can be reasonably predicted, and the process is optimized and corresponding energy-saving measures are made according to the result of the energy consumption model prediction, so that the energy consumption is reduced, and the energy-saving goal is realized.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic flow chart of a method for modeling and evaluating energy consumption of an energy consumption system according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
The embodiment of the invention provides an energy consumption modeling and evaluating method of an energy consumption system, as shown in fig. 1, the method comprises the following steps:
step 1: constructing an energy consumption model for the energy consumption system;
step 2: analyzing the energy consumption model to obtain a unit product comprehensive energy consumption model;
and step 3: and evaluating the process and equipment energy consumption of the energy consumption system by using the unit product comprehensive energy consumption model to obtain an evaluation result, and generating an improvement suggestion for the process and equipment of the energy consumption system according to the evaluation result.
The working principle of the technical scheme is as follows: constructing an energy consumption model for an energy consumption system; analyzing the energy consumption model to obtain a comprehensive energy consumption model of a unit product; and evaluating the process and equipment energy consumption of the energy consumption system by utilizing the comprehensive energy consumption model of the unit product to obtain an evaluation result, and improving the process and equipment of the energy consumption system according to the evaluation result.
The beneficial effects of the above technical scheme are: the energy consumption model is analyzed to obtain a comprehensive energy consumption model of a unit product, the comprehensive energy consumption model is evaluated, the process and equipment of the energy consumption system are improved according to the obtained evaluation result, so that the process optimization and the energy-saving space evaluation can be guided through the analysis and comparison of the equipment and process energy consumption, the process and the equipment energy consumption can be reasonably predicted, and the process is optimized and corresponding energy-saving measures are made according to the result of the energy consumption model prediction, so that the energy consumption is reduced, and the energy-saving goal is realized.
In one embodiment, in the step 1, constructing the energy consumption model for the energy consumption system comprises the following steps:
step S101: the real-time energy consumption data of each process of the energy consumption system are acquired and stored on line to form an energy source database;
step S102: collecting and storing production data of each process of the energy consumption system to form a production database;
step S103: extracting the energy consumption data in the energy source database and the production data in the production database to a middle layer for conditioning, converting and integrating, and importing the energy consumption data and the production data into a data warehouse;
step S104: and constructing an energy consumption model for the energy consumption system according to the data in the data warehouse.
The working principle of the technical scheme is as follows: in step S101, a dynamic multi-parameter online energy metering method is used to collect and store real-time energy consumption data of each process of the energy consumption system online, so as to form an energy source database.
The energy source database stores energy consumption data in units of seconds, and provides powerful data support for energy analysis. Many energy models require energy consumption data and field production data, and can be manually logged in a webpage for entry or acquired and stored in an online transaction processing (OLTP) mode. Before analysis, energy consumption real-time data and production data of each workshop need to be extracted to an intermediate layer for conditioning, conversion and integration (namely an ETL process), and finally a data warehouse is led to become the basis of energy modeling analysis.
The beneficial effects of the above technical scheme are: the energy consumption model can be built for the energy consumption system according to the energy consumption data and the production data in the data warehouse, and the accuracy of the built energy consumption model is improved.
In one embodiment, in the step S104, the building an energy consumption model for the energy consumption system according to the data in the data warehouse performs the following steps:
step S1041: organizing the data in the data warehouse according to a multi-dimensional form to form multi-dimensional data;
step S1042: analyzing the multi-dimensional data to obtain an analysis result, wherein the analysis comprises slicing, cutting, drilling and rotating;
step S1043: and constructing and verifying an energy consumption model of the energy consumption system according to the analysis result.
The working principle of the technical scheme is as follows: data in the data warehouse are organized in a multi-dimensional form, and various analysis actions such as slicing (Slice), dicing (Dice), drilling (Drill-down and Roll-up), rotating (Pivot) and the like are adopted to obtain analysis data, so that a user can observe the data in the data warehouse from multiple angles and multiple sides, further understand information contained in the data and establish and verify an energy model. And then, generating a report form, a meter panel, a query data set and the like according to the analysis result, and distributing the report form, the meter panel, the query data set and the like to an enterprise intranet. And each browsing terminal in the enterprise can check the appropriate content according to the user permission level.
The drilling is a hierarchy with changed dimensions, and the analysis granularity is changed, including upward drilling and downward drilling; the slice and the block are the distribution of the relation measurement data on the remaining dimension after the value is partially selected, if the remaining dimension is only two, the slice is the slice, if the remaining dimension is three, the block is the block; the rotation is the direction in which the dimensions are transformed, i.e. the placement of the dimensions is rearranged in the table. The upward drilling is to summarize low-level detail data to high-level summarized data in a certain dimension or reduce the dimension; the drill-down takes observations from summary data deep into detail data or adds new dimensions.
The beneficial effects of the above technical scheme are: the data in the data warehouse is further processed and analyzed, so that the accuracy of the constructed energy consumption model can be further improved, and the aim of energy conservation is fulfilled.
In one embodiment, in the step 2, analyzing the energy consumption model to obtain a comprehensive energy consumption model per unit product performs the following steps:
step S201: converting the energy consumption of the energy consumption system into comprehensive energy consumption according to the energy consumption type and by using a standard conversion coefficient;
step S202: calculating the comprehensive energy consumption of the unit product according to the comprehensive energy consumption and the product yield;
step S203: dividing the comprehensive energy consumption into the sum of products of product ratio coefficients in all processes of the energy consumption system and process energy consumption of all processes by adopting an e-p analysis method;
step S204: calculating the energy consumption change quantity of the product caused by the process energy consumption change of the process and the energy consumption change quantity of the product caused by the product ratio coefficient change by adopting an e-p analysis method;
step S205: and introducing an energy consumption reference line value by adopting an energy consumption reference factor method, and comparing the unit actual energy consumption with the unit product comprehensive energy consumption so as to judge the condition of the energy consumption system in the effective energy consumption.
The working principle of the technical scheme is as follows: at present, energy modeling and energy efficiency evaluation methods developed at home and abroad are numerous, such as an energy consumption reference factor method, an input-output method and the like. The invention provides a unit product comprehensive energy consumption model suitable for most enterprises by combining the characteristics of the production process and adopting an energy consumption reference factor method and an e-p analysis method.
According to the general rule of GB/T2589-2008 comprehensive energy consumption calculation, the consumption of water, electricity, coal and the like in each process section in the production flow of an enterprise is converted into comprehensive energy consumption according to the energy consumption type and the standard conversion coefficient, and the definition of the comprehensive energy of a unit product is introduced into the energy consumption analysis of the product process.
In step S202, the comprehensive energy consumption per unit product is calculated by using the following formula,
wherein E is0Is the comprehensive energy consumption per unit product, TceThe total amount of energy consumed for producing the product in the statistical period, and T is the product yield in the statistical period;
in step S203, the integrated energy consumption is divided into the sum of products of product ratio coefficients in the respective processes of the energy consumption system and process energy consumptions of the respective processes by using the following formula,
wherein e isiFor the energy consumption of the individual processes in the production of the products, piThe product ratio coefficient is the yield of the product in each process and the yield of the finished product, i is 1,2,3, …, and N is the total number of the production processes of the product;
in the step S204, the product energy consumption change amount caused by the process energy consumption change of the process and the product energy consumption change amount caused by the product ratio coefficient change are calculated by the following formulas,
wherein delta E is total product energy consumption change amount, E'iAnd e ″)iThe process energy consumption p 'of the ith process from the beginning and the end of the statistical period respectively'iAnd p' are the product ratio coefficients of the ith process at the beginning and the end of the statistical period respectively, and the first term on the right side of the equation is the factor eiThe change of energy consumption of the product caused by the change is called direct energy saving, and the second term on the right side of the equation is piThe change of the energy consumption of the product caused by the change is called indirect energy saving;
in step S205, the unit actual energy consumption and the unit product integrated energy consumption are compared by the following formula,
wherein Gc is the energy consumption baseline value of the product production equipment, eIFor the actual energy consumption per unit of the production plant, ecThe energy consumption is the unit effective energy consumption of the product production equipment, and if Gc is 100%, the effective energy consumption reaches the standard condition; if Gc is>100%, the energy consumption is wasted and needs to be improved; if Gc is<100%, the energy consumption is better than the standard condition.
The beneficial effects of the above technical scheme are: the specific steps of analyzing the energy consumption model by adopting an energy consumption reference factor method and an e-p analysis method are provided, and the comprehensive energy consumption model of a unit product can be obtained.
In one embodiment, in the step 3, the integrated energy consumption model of the unit product is used to evaluate the energy consumption of the process and the equipment of the energy consumption system, so as to obtain an evaluation result, and the following steps are performed according to the evaluation result to generate a recommendation for improving the process and the equipment of the energy consumption system:
step S301: evaluating the energy efficiency of each process and equipment of the energy consumption system by using the comprehensive energy consumption model of the unit product and adopting an energy consumption reference factor method to obtain the evaluation result;
step S302: and generating a prediction and suggestion for reducing the energy consumption according to the evaluation result and the theoretical model of the unit product comprehensive energy consumption model so as to realize a set energy-saving target.
The working principle of the technical scheme is as follows: on the basis of statistics and calculation of historical process energy consumption data, the energy efficiency of each process in the energy consumption system is evaluated by an energy consumption reference factor method, and a reasonable process energy consumption reference value is worked out according to the requirements of an energy-saving target. Whether the key energy consumption process reaches the preset energy-saving target or not can be analyzed through a comparison graph of the comprehensive energy consumption and the energy consumption reference line of the unit product. And verifying and comparing the effects by using actual data to find an energy efficiency evaluation and energy consumption prediction model most suitable for a specific energy consumption system.
The beneficial effects of the above technical scheme are: the method is characterized in that the comprehensive energy consumption model of unit products is utilized to evaluate the energy consumption of the process and equipment, and the improvement is carried out according to the evaluation result.
In one embodiment, in step S101, a data acquisition system is used to acquire real-time energy consumption data of each process of the energy consumption system on line, an energy consumption monitoring system is used to monitor real-time energy consumption data of each process of the energy consumption system,
wherein designing the data acquisition system comprises: the system comprises a gas flow data acquisition module consisting of a gas vortex flowmeter and a flow calculation microprocessor, a water consumption data acquisition module consisting of a photoelectric direct-reading remote water meter, a condensed water metering module and an electric energy metering module consisting of a mutual inductor and a three-phase electric meter;
the energy consumption monitoring system comprises an energy consumption monitoring system management platform, a data center, an energy consumption data acquisition terminal and an intelligent instrument, wherein the data center is used for receiving data reported by the energy consumption data acquisition terminal equipment, classifying and storing the data, and regularly transmitting the acquired data to an information cloud storage platform big data storage server through a wireless transmission device;
the server or the computer acquires corresponding energy consumption information through the cloud storage platform big data storage server, energy consumption monitoring system management platform software is used for centrally managing real-time energy consumption data of each process of the energy consumption system in the region under jurisdiction, and the centralized management comprises instrument management, acquisition terminal management, energy consumption management, data analysis and display and data report forms;
the energy consumption monitoring system management platform uses a B/S architecture; the energy consumption data acquisition terminal is arranged in workshops of each process of the energy consumption system and is responsible for data acquisition of energy consumption in each workshop, a special low-power consumption embedded acquisition device is adopted, the intelligent metering instrument is connected through a field bus, various main flow communication protocols are supported, data acquisition is actively carried out on the instrument and the sensing device, the data are uploaded to a data center layer at regular time or according to needs, AO and DO ports are provided, and meanwhile, a control command can be issued to the intelligent instrument; the intelligent instrument comprises an electric energy metering instrument with a data remote transmission function, sensing equipment and an actuator, wherein the electric energy metering instrument comprises a single-phase electric energy meter, a three-phase electric energy meter and a multifunctional electric energy meter, is in charge of real-time consumption metering of electric energy and provides original energy consumption data for the energy consumption data acquisition terminal. The working principle of the technical scheme is as follows: the data acquisition system can acquire a plurality of steam and CO2Compressed air, N2Water consumption point, condensed water and energy consumption data of an electric meter. According to the analysis of medium and operating mode, design the data acquisition system into 4 modules, namely: gas flow data acquisition module and photoelectric direct-reading remote water meter consisting of gas vortex flowmeter and flow integrating microprocessorThe system comprises a generated water consumption data acquisition module, a condensed water metering module, a mutual inductor and an electric energy metering module consisting of a three-phase electric meter. The 4 kinds of energy consumption data are transmitted by an on-line measuring instrument which meets the requirements of media and working conditions when the media pass through, are converted into bus digital signals which can be identified by a computer after signal modulation is carried out by a corresponding microprocessor, are transmitted into the computer through the Ethernet, are decoded by the computer according to protocols and addresses appointed by the microprocessor and enter a real-time historical database to form a huge database for storage.
The on-line energy metering information platform and the data analysis technology based on the B/S structure and the real-time database technology furthest realize the opening and sharing of energy information, can quickly and accurately carry out continuous measurement on various energy consumption data, form the storage, analysis and summarization of massive data, establish a unified energy statistics and summarization method, process the complex and massive data into effective and accurate management information, and provide scientific and effective quantitative indexes for energy assessment and energy saving work.
The beneficial effects of the above technical scheme are: by means of the data acquisition system and the energy consumption monitoring system, the on-line acquisition and real-time monitoring of the real-time energy consumption data of each process in the energy consumption system can be completed.
In one embodiment, in step S1041, the data in the data warehouse is organized in a multidimensional form to form multidimensional data, and the following steps are performed:
receiving data information from an external database from a first database interface, establishing an attribute data warehouse for the received data information, and storing attribute data of the data information in the attribute data warehouse, wherein the database connected with the first database interface comprises an energy source database and a production database;
receiving geographic data from an external database from a second database interface, establishing a spatial data warehouse for the received geographic data, and storing the geographic data in the spatial data warehouse, wherein the geographic data is related to the data information, and the database connected with the second database interface comprises: a map database, a process database and a workshop database;
analyzing the attribute data of the data information stored in the attribute data warehouse to generate analysis data of the attribute data;
and establishing a multi-dimensional relation table between the analysis data and the geographic data.
The working principle of the technical scheme is as follows: the generating of the analysis data of the attribute data includes: and performing projection, connection and grouping pretreatment on the attribute data to obtain analysis data, and establishing a view set for the analysis data.
The beneficial effects of the above technical scheme are: the data in the data warehouse can be effectively collected and organized, and a multidimensional relation table is established between the analysis data of the attribute data and the geographic data.
In one embodiment, the energy consuming system comprises an energy consuming system for beer production, the process of the energy consuming system comprising a boiling process comprising 3 stages:
the first stage 1 is wort preheating, wherein wort entering a boiling pot from a temporary storage tank is preheated by heat recovered in the boiling process;
stage 2, the wort is boiled, and the wort is heated to a boiling state;
stage 3 is low pressure boiling and waste heat recovery to increase the evaporation speed, and the heat of the evaporated water vapor is recovered to be used for preheating the wort.
The working principle of the technical scheme is as follows: and calculating the comprehensive beer energy consumption in the boiling process of beer production by using an e-p analysis method, and analyzing the calculation result.
The equipment used in the boiling procedure comprises a boiling pot, a secondary steam heat exchanger, a heat energy storage tank, a wort preheating plate, and the like. The boiling process is divided into 3 stages: the first stage 1 is that wort is preheated, and the heat recovered in the boiling process is utilized to preheat the wort entering a boiling pot from a temporary storage tank to 94 ℃ from 78 ℃; stage 2, the wort is boiled, and the wort is heated to a boiling state; stage 3 is low pressure boiling and waste heat recovery to increase the evaporation speed, and the heat of the evaporated water vapor is recovered to be used for preheating the wort.
The beneficial effects of the above technical scheme are: the energy consumption modeling and evaluating method can be applied to the boiling process in an energy consumption system for beer production.
In one embodiment, in the step 3, a recommendation for improvement of the process and equipment of the energy consumption system is generated according to the evaluation result, including using a pressure boiling process, using a steam recovery process, using a wort preheating process, or using a high concentration dilution process.
The working principle of the technical scheme is as follows: the complete equipment is provided with a perfect metering and detecting instrument, and the collected actual data is transmitted to an Energy Metering System (EMS) database for analysis. Extracting parameters such as wort flow and temperature from the database, obtaining consumption data of steam, water, electricity and compressed air by referring to historical data statistics, and calculating a theoretical value of comprehensive energy consumption by using an e-p analysis method. The yield of the intermediate product (wort) in the boiling process is G2,E105.7 t; the (steam) evaporation capacity is G1,V＝L1,F-G2,ET ═ 16.7t (122.4-105.7), where L is1,FThe total amount of wort entering the boiling pot. The total consumption of steam, water, electricity and compressed air in the boiling process is multiplied by respective conversion coefficients to convert the standard coal mass, kg, corresponding to different energy consumptions. The specific conversion results are shown in Table l. The total energy consumption G of the boiling process can be obtainedI2116.10kg/t unit energy consumption (integrated energy consumption)
TABLE 1 signature coal results for different energy consumption in boiling process
Still taking the boiling process as an example, the energy efficiency of the boiling process is estimated by adopting an energy consumption reference factor method, and the energy consumption space of the equipment is given from a theoretical model as an energy consumption reference line of the process. Formula (II)
The actual energy consumption of the equipment can be regarded as the unit energy consumption of the boiling process. The effective energy consumption Ec of the boiling process equipment is composed of the heat of wort evaporation capacity and the sensible heat of wort:
EC＝G2,E(h″-h′)+L1,FCV·Δt
wherein h ═ 2679.36kJ/kg and h ═ 428.84kJ/kg are the saturated steam specific enthalpy and saturated water specific enthalpy at 100 ℃ respectively, and CV＝4.212kJ·kg-1The temperature of the product is the specific heat capacity of the wort; delta t is the temperature difference of the wort when it is heated in the boiler, where delta t is 22 ℃.
Bringing the data into the above formula, EC48925.45 MJ. The conversion coefficient of the heat signature coal is 0.03412kg/MJ, so that the unit effective energy consumption can be obtained
ec＝EC/G2,E15.8kg/t, (48925.45 × 0.03412)/105.70 kg/t. Calculating the reference factor G of the energy consumption of the boiling processc＝eI/ec＝127.8％。
According to the statistics of historical data, G is carried out before energy-saving processes such as pressurized boiling, steam recovery, wort preheating and the like are not adoptedcAbout 152%. When the above process is employed, GcThe reduction is 127.8 percent, and a large energy consumption reduction space still exists, so that the process can be optimized and a new energy-saving index can be established.
Still take the boiling process as an example to calculate the influence of reducing the beer ratio coefficient on the energy-saving effect. The comparison of the beer before and after the high-concentration dilution process can be seen in table 2, the 14P wine is diluted to 10P in the high-concentration dilution process, and the quality of the finished wine after the high-concentration dilution process is adopted can be increased from the original quality. Therefore, the beer ratio coefficients before and after the high concentration and dilution process are calculated to be respectively the sum.
TABLE 2 comparison of energy consumption before and after beer high concentration and dilution process
| Name (R) | Without using high-consistency diluent | Using high-consistency diluent |
| Intermediate yield G of boiling process2,E，t | 105.70 | 105.70 |
| Quality of finished wine CE，t | 98.86 | 138.40 |
| Beer ratio coefficient pI＝G2,E/CE | 1.07 | 0.76 |
| Boiling process energy consumption component E0I＝eI﹒pI，kg/t | 21.42 | 15.22 |
When beer ratio coefficient piWhen the energy consumption is reduced, the comprehensive energy consumption of the boiling process is reduced from 20.02kg/t to 15.22kg/t, and the energy saving rate reaches 24 percent. Therefore, the beer ratio coefficient (the ratio of the yield of the real objects of each process such as wort, fermentation liquor and the like to the yield of finished wine) is reduced, and the comprehensive energy consumption of all the previous processes can be reduced.
The beneficial effects of the above technical scheme are: the comprehensive beer energy consumption model obtained based on the energy consumption reference factor method and the e-p analysis method can reasonably predict the energy consumption of each process and equipment in beer production, reduce the process energy consumption and the beer ratio coefficient, and reduce the energy consumption of enterprises.
In one embodiment, in the step 3, the process and equipment energy consumption of the energy consumption system is evaluated by using the integrated energy consumption model of unit product, an evaluation result is obtained, and the following steps are performed according to the evaluation result to generate an improvement suggestion for the process and equipment of the energy consumption system:
step A301, acquiring the process and equipment energy consumption of the unit product by using the comprehensive energy consumption model of the unit product, and determining the comprehensive energy intensity of the unit product;
wherein f isiThe integrated energy intensity, K, for the ith unit producti,jEnergy consumption of the jth process for the ith unit product, Ci,jThe yield of the jth process for the ith unit product, Ci,j2The yield of the j2 th process of the ith unit product, N is the total process amount of the ith unit product, i is 1,2 and 3 … … It, It is the unit product quantity, j is 1,2 and 3 … … N, and j2 is 1,2,3 … j-1, j +1 and j +2 … N;
step A302, using the unit product corresponding to the minimum value of the comprehensive energy intensity as a base product;
step A303, determining the factor intensity of the unit product according to the base product;
fRSi＝fi-fFi-fIi
wherein, fFiIs the efficiency intensity of the ith unit product, K0,jEnergy consumption of the jth process for the base product, C0,jThe yield of the jth process for the base product, C0,j2Being said base productYield of procedure j2, fIiStructural Strength of the ith Unit product, fRSiThe decomposition allowance of the ith unit product;
step A304, determining the process energy consumption investment of each unit product;
wherein, KCi,jEnergy input for the jth process of the ith unit product, f0Is the integrated energy intensity of the base product;
step A305, performing energy consumption adjustment on each process of the energy consumption system according to the result of the step A304.
The beneficial effects of the above technical scheme are: the energy consumption of each process of the process and the equipment of the energy consumption system can be adjusted by utilizing the technology, so that the energy consumption of each process of each unit product is optimized, the energy saving effect is achieved, the efficiency strength of the unit product with the yield in each unit product and the structural strength of the unit product can be determined by utilizing the technology, and when the efficiency strength of the unit product is lower, namely lower than the average value of the efficiency strengths of all the unit products, the technology of the unit product is improved, so that the continuous optimization effect is achieved.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. An energy consumption modeling and evaluating method of an energy consumption system, characterized in that the method performs the following steps:
step 1: constructing an energy consumption model for the energy consumption system;
step 2: analyzing the energy consumption model to obtain a unit product comprehensive energy consumption model;
and step 3: and evaluating the process and equipment energy consumption of the energy consumption system by using the unit product comprehensive energy consumption model to obtain an evaluation result, and generating an improvement suggestion for the process and equipment of the energy consumption system according to the evaluation result.
2. The energy consumption modeling and evaluation method of claim 1, wherein in step 1, the following steps are performed for constructing the energy consumption model for the energy consumption system:
step S101: the real-time energy consumption data of each process of the energy consumption system are acquired and stored on line to form an energy source database;
step S102: collecting and storing production data of each process of the energy consumption system to form a production database;
step S103: extracting the energy consumption data in the energy source database and the production data in the production database to a middle layer for conditioning, converting and integrating, and importing the energy consumption data and the production data into a data warehouse;
step S104: and constructing an energy consumption model for the energy consumption system according to the data in the data warehouse.
3. The energy consumption modeling and evaluation method of claim 1, wherein in step S104, said constructing an energy consumption model for said energy consumption system from data in said data warehouse performs the following steps:
step S1041: organizing the data in the data warehouse according to a multi-dimensional form to form multi-dimensional data;
step S1042: analyzing the multi-dimensional data to obtain an analysis result, wherein the analysis comprises slicing, cutting, drilling and rotating;
step S1043: and constructing and verifying an energy consumption model of the energy consumption system according to the analysis result.
4. The energy consumption modeling and assessment method according to claim 1, wherein in said step 2, analyzing said energy consumption model to obtain a unit product integrated energy consumption model performs the following steps:
step S201: converting the energy consumption of the energy consumption system into comprehensive energy consumption according to the energy consumption type and by using a standard conversion coefficient;
step S202: calculating the comprehensive energy consumption of the unit product according to the comprehensive energy consumption and the product yield;
step S203: dividing the comprehensive energy consumption into the sum of products of product ratio coefficients in all processes of the energy consumption system and process energy consumption of all processes by adopting an e-p analysis method;
step S204: calculating the energy consumption change quantity of the product caused by the process energy consumption change of the process and the energy consumption change quantity of the product caused by the product ratio coefficient change by adopting an e-p analysis method;
step S205: and introducing an energy consumption reference line value by adopting an energy consumption reference factor method, and comparing the unit actual energy consumption with the unit product comprehensive energy consumption so as to judge the condition of the energy consumption system in the effective energy consumption.
5. The energy consumption modeling and evaluation method of claim 4, wherein in said step S202, the integrated energy consumption per unit product is calculated using the following formula,
wherein E is0Is the comprehensive energy consumption per unit product, TceThe total amount of energy consumed for producing the product in the statistical period, and T is the product yield in the statistical period;
in step S203, the integrated energy consumption is divided into the sum of products of product ratio coefficients in the respective processes of the energy consumption system and process energy consumptions of the respective processes by using the following formula,
wherein e isiFor the energy consumption of the individual processes in the production of the products, piThe product ratio coefficient is the yield of the product in each process and the yield of the finished product, i is 1,2,3, …, and N is the total number of the production processes of the product;
in the step S204, the product energy consumption change amount caused by the process energy consumption change of the process and the product energy consumption change amount caused by the product ratio coefficient change are calculated by the following formulas,
wherein delta E is total product energy consumption change amount, E'iAnd e ″)iThe process energy consumption p 'of the ith process from the beginning and the end of the statistical period respectively'iAnd p' are the product ratio coefficients of the ith process at the beginning and the end of the statistical period respectively, and the first term on the right side of the equation is the factor eiThe change of energy consumption of the product caused by the change is called direct energy saving, and the second term on the right side of the equation is piThe change of the energy consumption of the product caused by the change is called indirect energy saving;
in step S205, the unit actual energy consumption and the unit product integrated energy consumption are compared by the following formula,
wherein Gc is the energy consumption baseline value of the product production equipment, eIFor the actual energy consumption per unit of the production plant, ecThe energy consumption is the unit effective energy consumption of the product production equipment, and if Gc is 100%, the effective energy consumption reaches the standard condition; if Gc is>100%, the energy consumption is wasted and needs to be improved; if Gc is<100%, the energy consumption is better than the standard condition.
6. The energy consumption modeling and evaluation method according to claim 1, wherein in the step 3, the integrated energy consumption model of the unit product is used to evaluate the energy consumption of the process and equipment of the energy consumption system, so as to obtain an evaluation result, and a recommendation for improving the process and equipment of the energy consumption system is generated according to the evaluation result, and the following steps are performed:
step S301: evaluating the energy efficiency of each process and equipment of the energy consumption system by using the comprehensive energy consumption model of the unit product and adopting an energy consumption reference factor method to obtain the evaluation result;
step S302: and generating a prediction and suggestion for reducing the energy consumption according to the evaluation result and the theoretical model of the unit product comprehensive energy consumption model so as to realize a set energy-saving target.
7. The energy consumption modeling and evaluation method according to claim 2, wherein in step S101, the real-time energy consumption data of each process of the energy consumption system is collected on-line by using a data collection system, the real-time energy consumption data of each process of the energy consumption system is monitored by using an energy consumption monitoring system,
wherein designing the data acquisition system comprises: the system comprises a gas flow data acquisition module consisting of a gas vortex flowmeter and a flow calculation microprocessor, a water consumption data acquisition module consisting of a photoelectric direct-reading remote water meter, a condensed water metering module and an electric energy metering module consisting of a mutual inductor and a three-phase electric meter;
the energy consumption monitoring system comprises an energy consumption monitoring system management platform, a data center, an energy consumption data acquisition terminal and an intelligent instrument, wherein the data center is used for receiving data reported by the energy consumption data acquisition terminal equipment, classifying and storing the data, and regularly transmitting the acquired data to an information cloud storage platform big data storage server through a wireless transmission device;
the server or the computer acquires corresponding energy consumption information through the cloud storage platform big data storage server, energy consumption monitoring system management platform software is used for centrally managing real-time energy consumption data of each process of the energy consumption system in the region under jurisdiction, and the centralized management comprises instrument management, acquisition terminal management, energy consumption management, data analysis and display and data report forms;
the energy consumption monitoring system management platform uses a B/S architecture; the energy consumption data acquisition terminal is arranged in workshops of each process of the energy consumption system and is responsible for data acquisition of energy consumption in each workshop, a special low-power consumption embedded acquisition device is adopted, the intelligent metering instrument is connected through a field bus, various main flow communication protocols are supported, data acquisition is actively carried out on the instrument and the sensing device, the data are uploaded to a data center layer at regular time or according to needs, AO and DO ports are provided, and meanwhile, a control command can be issued to the intelligent instrument; the intelligent instrument comprises an electric energy metering instrument with a data remote transmission function, sensing equipment and an actuator, wherein the electric energy metering instrument comprises a single-phase electric energy meter, a three-phase electric energy meter and a multifunctional electric energy meter, is in charge of real-time consumption metering of electric energy and provides original energy consumption data for the energy consumption data acquisition terminal.
8. The energy consumption modeling and assessment method according to claim 3, wherein in said step S1041, said organizing the data in said data warehouse in a multidimensional form, forming multidimensional data, performing the following steps:
receiving data information from an external database from a first database interface, establishing an attribute data warehouse for the received data information, and storing attribute data of the data information in the attribute data warehouse, wherein the database connected with the first database interface comprises an energy source database and a production database;
receiving geographic data from an external database from a second database interface, establishing a spatial data warehouse for the received geographic data, and storing the geographic data in the spatial data warehouse, wherein the geographic data is related to the data information, and the database connected with the second database interface comprises: a map database, a process database and a workshop database;
analyzing the attribute data of the data information stored in the attribute data warehouse to generate analysis data of the attribute data;
and establishing a multi-dimensional relation table between the analysis data and the geographic data.
9. The energy consumption modeling and assessment method according to claim 1, wherein said energy consumption system comprises an energy consumption system for beer production, said energy consumption system process comprises a boiling process comprising 3 stages:
the first stage 1 is wort preheating, wherein wort entering a boiling pot from a temporary storage tank is preheated by heat recovered in the boiling process;
stage 2, the wort is boiled, and the wort is heated to a boiling state;
and 3, low-pressure boiling and waste heat recovery are carried out to increase the evaporation speed, the heat of the evaporated water vapor is recovered to be used for preheating the wort, and in the step 3, improvement suggestions for the process and equipment of the energy consumption system are generated according to the evaluation result, wherein the improvement suggestions comprise that a pressurized boiling process is adopted, a steam recovery process is adopted, a wort preheating process is adopted, or a high-concentration and thin process is adopted.
10. The energy consumption modeling and evaluation method according to claim 1, wherein in the step 3, the energy consumption of the process and the equipment of the energy consumption system is evaluated by using the integrated energy consumption model of the unit product, an evaluation result is obtained, and the following steps are performed according to the evaluation result to generate an improvement suggestion for the process and the equipment of the energy consumption system:
step A301, acquiring the process and equipment energy consumption of the unit product by using the comprehensive energy consumption model of the unit product, and determining the comprehensive energy intensity of the unit product;
wherein f isiThe integrated energy intensity, K, for the ith unit producti,jEnergy consumption of the jth process for the ith unit product, Ci,jThe yield of the jth process for the ith unit product, Ci,j2As the ith unit productThe yield of the j2 th process, wherein N is the total process amount of the i unit product, i is 1,2, 3.... It, which is the unit product quantity, j is 1,2, 3..... N, j2 is 1,2,3 … j-1, j +2.. N;
step A302, using the unit product corresponding to the minimum value of the comprehensive energy intensity as a base product;
step A303, determining the factor intensity of the unit product according to the base product;
fRSi＝fi-fFi-fIi
wherein, fFiIs the efficiency intensity of the ith unit product, K0,jEnergy consumption of the jth process for the base product, C0,jThe yield of the jth process for the base product, C0,j2Yield of the base product from the j2 th process, fIiStructural Strength of the ith Unit product, fRSiThe decomposition allowance of the ith unit product;
step A304, determining the process energy consumption investment of each unit product;
wherein, KCi,jEnergy input for the jth process of the ith unit product, f0Is the integrated energy intensity of the base product;
step A305, performing energy consumption adjustment on each process of the energy consumption system according to the result of the step A304.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911221623.0A CN110991043B (en) | 2019-12-03 | 2019-12-03 | Energy consumption modeling and evaluating method of energy consumption system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911221623.0A CN110991043B (en) | 2019-12-03 | 2019-12-03 | Energy consumption modeling and evaluating method of energy consumption system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110991043A true CN110991043A (en) | 2020-04-10 |
| CN110991043B CN110991043B (en) | 2023-05-16 |
Family
ID=70089612
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911221623.0A Active CN110991043B (en) | 2019-12-03 | 2019-12-03 | Energy consumption modeling and evaluating method of energy consumption system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110991043B (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111667186A (en) * | 2020-06-10 | 2020-09-15 | 西门子电力自动化有限公司 | Method and device for determining the energy consumption of a machine for production |
| CN111798103A (en) * | 2020-06-16 | 2020-10-20 | 厦门大学 | Real-time evaluation method and system for energy efficiency of anode furnace |
| CN112270458A (en) * | 2020-09-15 | 2021-01-26 | 广东韶钢松山股份有限公司 | Energy refined management and control method and device, computer equipment and storage medium |
| CN112448048A (en) * | 2020-11-23 | 2021-03-05 | 合肥阳光新能源科技有限公司 | Energy storage battery compartment layout method, temperature adjusting method and layout device |
| CN113128895A (en) * | 2021-04-29 | 2021-07-16 | 重庆城市管理职业学院 | Intelligent workshop management system based on big data |
| CN113269435A (en) * | 2021-05-21 | 2021-08-17 | 国网山东省电力公司电力科学研究院 | New energy station running state coupling monitoring and evaluating system |
| WO2023039729A1 (en) * | 2021-09-14 | 2023-03-23 | 西门子（中国）有限公司 | Production plan evaluation method and apparatus, and computer readable storage medium |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101887544A (en) * | 2010-06-10 | 2010-11-17 | 同济大学 | Optimization modeling method for coupling of production and energy of continuous enterprises |
| WO2011106917A1 (en) * | 2010-03-05 | 2011-09-09 | 朗德华信（北京）自控技术有限公司 | Energy management control system based on cloud computing and method thereof |
| US20140107851A1 (en) * | 2012-10-16 | 2014-04-17 | Electronics And Telecommunications Research Institute | Apparatus and method for evaluating energy consumption performance of building |
| CL2013003810A1 (en) * | 2013-12-31 | 2015-01-09 | Univ Talca | System and method of monitoring and management for energy efficiency in buildings where the system comprises means for measuring and acquiring data online from sensors, means of transmission, reception and transfer of data, processing means, storage and user interface, where it includes an alarm module, a monitoring module and an investment options module. |
| CN104992298A (en) * | 2015-07-16 | 2015-10-21 | 南京朗坤软件有限公司 | Energy management system |
| US20170277816A1 (en) * | 2016-03-22 | 2017-09-28 | Chu-Fu Chen | Method of verifying and analyzing energy efficiency ratio EER of a heating ventilation and air conditioning HVAC chiller unit |
| CN108388759A (en) * | 2018-05-29 | 2018-08-10 | 广东工业大学 | A kind of horse shoe flame glass furnace energy consumption modeling and local energy consumption benchmark method |
| CN109063255A (en) * | 2018-06-29 | 2018-12-21 | 广州能迪能源科技股份有限公司 | A kind of energy-saving control method, electronic equipment, storage medium, apparatus and system |
| CN109299199A (en) * | 2018-10-15 | 2019-02-01 | 河北师范大学 | Precursor chemicals dimensional analytic system and implementation method based on data warehouse |
| CN109610056A (en) * | 2018-12-10 | 2019-04-12 | 江南大学 | A kind of ring throstle Internet of Things production control and management system |
| CN109857800A (en) * | 2019-02-25 | 2019-06-07 | 南京世界村云数据产业集团有限公司 | A kind of data processing method of industry internet energy management and optimization system |
-
2019
- 2019-12-03 CN CN201911221623.0A patent/CN110991043B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2011106917A1 (en) * | 2010-03-05 | 2011-09-09 | 朗德华信（北京）自控技术有限公司 | Energy management control system based on cloud computing and method thereof |
| CN101887544A (en) * | 2010-06-10 | 2010-11-17 | 同济大学 | Optimization modeling method for coupling of production and energy of continuous enterprises |
| US20140107851A1 (en) * | 2012-10-16 | 2014-04-17 | Electronics And Telecommunications Research Institute | Apparatus and method for evaluating energy consumption performance of building |
| CL2013003810A1 (en) * | 2013-12-31 | 2015-01-09 | Univ Talca | System and method of monitoring and management for energy efficiency in buildings where the system comprises means for measuring and acquiring data online from sensors, means of transmission, reception and transfer of data, processing means, storage and user interface, where it includes an alarm module, a monitoring module and an investment options module. |
| CN104992298A (en) * | 2015-07-16 | 2015-10-21 | 南京朗坤软件有限公司 | Energy management system |
| US20170277816A1 (en) * | 2016-03-22 | 2017-09-28 | Chu-Fu Chen | Method of verifying and analyzing energy efficiency ratio EER of a heating ventilation and air conditioning HVAC chiller unit |
| CN108388759A (en) * | 2018-05-29 | 2018-08-10 | 广东工业大学 | A kind of horse shoe flame glass furnace energy consumption modeling and local energy consumption benchmark method |
| CN109063255A (en) * | 2018-06-29 | 2018-12-21 | 广州能迪能源科技股份有限公司 | A kind of energy-saving control method, electronic equipment, storage medium, apparatus and system |
| CN109299199A (en) * | 2018-10-15 | 2019-02-01 | 河北师范大学 | Precursor chemicals dimensional analytic system and implementation method based on data warehouse |
| CN109610056A (en) * | 2018-12-10 | 2019-04-12 | 江南大学 | A kind of ring throstle Internet of Things production control and management system |
| CN109857800A (en) * | 2019-02-25 | 2019-06-07 | 南京世界村云数据产业集团有限公司 | A kind of data processing method of industry internet energy management and optimization system |
Non-Patent Citations (1)
| Title |
|---|
| 胡小梅;朱文华;王宇颖;俞涛;: "高能耗企业能效综合评估***设计研究" * |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111667186A (en) * | 2020-06-10 | 2020-09-15 | 西门子电力自动化有限公司 | Method and device for determining the energy consumption of a machine for production |
| CN111667186B (en) * | 2020-06-10 | 2023-05-05 | 西门子电力自动化有限公司 | Method and device for determining the energy consumption of a machine for production |
| CN111798103A (en) * | 2020-06-16 | 2020-10-20 | 厦门大学 | Real-time evaluation method and system for energy efficiency of anode furnace |
| CN112270458A (en) * | 2020-09-15 | 2021-01-26 | 广东韶钢松山股份有限公司 | Energy refined management and control method and device, computer equipment and storage medium |
| CN112448048A (en) * | 2020-11-23 | 2021-03-05 | 合肥阳光新能源科技有限公司 | Energy storage battery compartment layout method, temperature adjusting method and layout device |
| CN112448048B (en) * | 2020-11-23 | 2021-12-14 | 合肥阳光新能源科技有限公司 | Energy storage battery compartment layout method, temperature adjusting method and layout device |
| CN113128895A (en) * | 2021-04-29 | 2021-07-16 | 重庆城市管理职业学院 | Intelligent workshop management system based on big data |
| CN113269435A (en) * | 2021-05-21 | 2021-08-17 | 国网山东省电力公司电力科学研究院 | New energy station running state coupling monitoring and evaluating system |
| WO2023039729A1 (en) * | 2021-09-14 | 2023-03-23 | 西门子（中国）有限公司 | Production plan evaluation method and apparatus, and computer readable storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110991043B (en) | 2023-05-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110991043B (en) | Energy consumption modeling and evaluating method of energy consumption system | |
| CN105260836A (en) | Automobile manufacture enterprise carbon emission acquisition checking system and method | |
| CN104318482A (en) | Comprehensive assessment system and method of smart distribution network | |
| CN103106333B (en) | The online theoretical energy consumption computing system of catalytic cracking unit based on process simulation software | |
| Gong et al. | Energy efficiency evaluation in ethylene production process with respect to operation classification | |
| CN104699050A (en) | Leaf-shred preparation segment on-line monitoring and fault diagnosing method for cigarette filament treatment driven by data | |
| Gong et al. | Energy efficiency evaluation based on DEA integrated factor analysis in ethylene production | |
| CN104091008A (en) | User electric equipment safety assessment method based on improvement section analytic hierarchy process | |
| CN103116814B (en) | A kind of area power grid main equipment medium term load forecasting system | |
| CN103439114A (en) | System and device for testing thermal performance of turboset | |
| CN105136510A (en) | Heat exchanger network energy efficiency evaluation method based on principal component analysis | |
| CN104865944B (en) | Gas separation unit control system performance estimating method based on PCA LSSVM | |
| CN115330130A (en) | Agricultural park comprehensive energy system evaluation method based on improved AHP-CRITIC | |
| CN113722656B (en) | Real-time health evaluation method and system for thermal generator set | |
| Gong et al. | Multi-level and multi-granularity energy efficiency diagnosis scheme for ethylene production process | |
| Fangfang | Research on the model and application progress based on grey relational analysis theory | |
| CN106649906A (en) | Energy consumption analyzing method and system used for oil field gathering and transportation system | |
| Zhang et al. | A framework of energy-consumption driven discrete manufacturing system | |
| CN107909477B (en) | Power transmission network planning project investment combination optimization method | |
| Han et al. | Linear optimization fusion model based on fuzzy C-means: Case study of energy efficiency evaluation in ethylene product plants | |
| CN107350295B (en) | A kind of rolling system production energy efficiency evaluating method | |
| CN111898976A (en) | Online monitoring and intelligent operation system of steam power system | |
| CN203909597U (en) | Real-time energy-consumption monitoring and energy-consumption abnormity detection system for aluminum section extruder | |
| Xiong et al. | Research on prediction method of finish rolling power consumption of multi-specific strip steel based on random forest optimization model | |
| CN113033864A (en) | Energy consumption prediction method for newly built enterprise based on energy big data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |