CN104091042B - Operating data-based method for energy conservation diagnosis and energy conservation potential analysis on central air-conditioning system - Google Patents
Operating data-based method for energy conservation diagnosis and energy conservation potential analysis on central air-conditioning system Download PDFInfo
- Publication number
- CN104091042B CN104091042B CN201410264063.8A CN201410264063A CN104091042B CN 104091042 B CN104091042 B CN 104091042B CN 201410264063 A CN201410264063 A CN 201410264063A CN 104091042 B CN104091042 B CN 104091042B
- Authority
- CN
- China
- Prior art keywords
- data
- analysis
- energy
- equipment
- energy conservation
- 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.)
- Active
Links
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
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Landscapes
- Air Conditioning Control Device (AREA)
Abstract
The invention discloses an operating data-based method for energy conservation diagnosis and energy conservation potential analysis on a central air-conditioning system. The method comprises the following steps: based on practical operation data of the central air-conditioning system, performing data preprocessing on input data, further performing data analysis on preprocessed data so as to recognize system working condition mode, analyze system equipment power and energy consumption characteristics and analyze system and equipment operation constraint conditions, and based on such analysis, performing energy conservation potential calculation so as to calculate the minimum operation energy consumption (or expense), thereby obtaining system energy conservation diagnosis result and energy conservation potential condition. By adopting the method, due to analysis on the practical operation data of the system, more comprehensive energy conservation diagnosis and energy conservation potential result which better meets the practical situation is provided for users, and significant decision basis is provided for optimized system energy conservation operation and energy conservation transformation.
Description
Technical field
The present invention relates to a kind of diagnose and calculate obtain energy-conservation potentiality based on service data to Energy Saving of Central Air-conditioning
Method.Belong to data analysis diagnosis of energy saving and Refrigeration ＆ Air-Conditioning technical field.
Background technology
At present, it is energy-saving to seem particularly urgent in the case of global energy anxiety.Central air conditioner system energy consumption is
Account for 1/10th of global energy consumption.Therefore the energy saving research of air-conditioning system is to reduction building energy consumption, or even to economy and society
Can the promotion of sustainable development all have and be of great significance.
The method of the existing air conditioner system energy saving diagnosis being widely used is summarized as " observing/exchanging → test/calculate → sentence
It is disconnected/to solve " method.But in " test/calculate " link of this method, it is often necessary to according to real system situation, artificial selection
Diagnosis index, is then tested and is assessed.And during actual " judge/solve ", in addition it is also necessary to change, be adapted to often
The different demands of individual project.In other words, this method is only limited the use of in the concrete analysis to particular problem.
Air-conditioning system service data is that running state most directly, most really reflects that this is caused by automatic
Monitoring service data simultaneously takes corresponding control device reduction system operation energy consumption to become an important way for realizing air conditioner energy saving
Footpath.At present, many air conditioning systems have realized the collection of service data, and the mass data accumulated in running is from number
Provide the foundation according to upper analysis system energy consumption and ruuning situation.But, substantial amounts of data also bring " data disaster ", make
Obtain operation maintenance personnel to be difficult to fast and effeciently find energy waste and energy consumption abnormal problem, and effectively diagnosis of energy saving is more had no way of
Talk.
In other words, up to the present also for air-conditioning system service data quickly do not analyzed, diagnosed, and drawn
A set of ripe achievement in research of energy saving of system potentiality and method of operating.This causes lot of research and application more experience
Property, and its versatility need to be improved.
The content of the invention
In view of prior art is not enough above, it is an object of the invention to provide a kind of service data that is based on is to central air-conditioning system
System diagnosis of energy saving and the method for energy-saving potential analysis, make it suitable for utilizing actual motion number for all types of central air conditioner systems
Calculate according to effective diagnosis of energy saving and energy-saving potential is carried out, there is provided more comprehensively, more meet actual diagnosis of energy saving and energy-saving potential
As a result, cost and human cost the time required to reducing.
Method used in the present invention is：
A kind of Energy Saving of Central Air-conditioning diagnosis and energy-saving potential are analyzed method based on service data, based on central hollow
Adjusting system actual operating data, Jing after carrying out data prediction to input data, then Jing data analysis steps to carrying out pre- place
The data of reason carry out system condition pattern-recognition, system equipment operation duration and impartial operation reserve analysis, system equipment operation
Order analysis, the analysis of system equipment frequency property, system equipment are exerted oneself and energy consumption characteristics analysis, system and equipment operation constraint bar
Part analyze, based on this again warp knuckle energy potentiality calculation procedure to system minimum operation energy consumption (or expense) calculate, obtain system
Diagnosis of energy saving result and energy-saving potential result；Including the steps：
Step S401：Start；
Step S402, from data input device 101 central air conditioner system of pending diagnosis of energy saving and Potentials is input into
Actual operating data；Then, pre-processed by 102 pairs of data of data prediction device；
The data of input are carried out step S403, data scrubbing device 201 cleaning of missing data, using it is existing in column
Delete, paired delet method is cleared up missing data；
Step S404, data scrubbing device 201 will with using peel off point analysis or using decision tree to interference prune
Mode will be identified as disturbing the object data of data to filter out and then mask；
Step S405, data scrubbing device 201 will can be plotted meeting interference observation of the curve map for analysis and research and be regarded later
Line and the equipment outage data that data are carried out with numerical characteristic calculating is needed to clear up；
Step S406, data integration device 202 will be that reference items will derive from same air-conditioning system typically with common item
Different monitoring system data are merged, if there is the inconsistent situation of different monitoring system data acquisition time step-lengths, will be compared with
Large time step place system data regards the data with deficient phenomena as, and high priority data after merging is proceeded to into data scrubbing
Device 201 carries out missing data cleaning；
Step S407, data integration device 202 will not meet the duplicate data of data acquisition time step-length rule in data
Deleted；
Step S408, data integration device 202 will not meet the colliding data of Refrigeration ＆ Air-Conditioning technical field physics law
Deleted；
Step S409, data converting apparatus 203 will be transformed to more one to the unification of the measurement unit of same physical type data
As measurement unit；
Step S410, data converting apparatus 203 will start the continuous type of the equipment energy consumption of order analysis for system equipment
Data are transformed to the discrete data as started shooting or shut down；
Step S411, data amplification device 204 will be derived cold using such as chilled water supply water temperature and chilled water return water temperature
Freeze water supply backwater temperature difference, so as to expand to available data；
Step S412, system condition pattern recognition device 301 is poly- using energy consumption data based on the data for completing to pre-process
Alanysis and the method for decision tree classification, are identified to system condition pattern；
Step S413, system equipment operation duration will be to owning with Time-Series analysis device 302 under the various regime modes of system
Equipment operation duration carries out statistical analysis, draws the result for whether meeting equal equal travel time strategy；
Step S414, system equipment operation duration will be using association analysis method to various works with Time-Series analysis device 302
The condition pattern operation order that similarly hereinafter type equipment shows in actual moving process is analyzed, and draws the various operating modes of system
Pattern divides into received shipment row order result；
Step S415, system and equipment analysis on Operating device 303 are by using the numerical characteristic pair of equipment energy consumption data
System equipment converting operation characteristic is analyzed, and whether identification equipment is frequency conversion equipment or whether converting operation；
Step S416, system and equipment analysis on Operating device 303 use regression analysis, to system energy equipment
The relation property that energy consumption is exerted oneself with it is fitted；
Step S417, system and equipment analysis on Operating device 303 will be using service data, all kinds of operations to system
Constraints carries out reductive analysis；
Step S418, energy-saving potential computing device 104 is directed to each moment system load demand, based on by data analysis
The system equipment that the analysis of device 103 is obtained is exerted oneself and energy consumption characteristics and system and equipment operation constraints, using optimized algorithm
Optimizing is carried out, and draws system minimum operation energy consumption result, actual motion energy consumption data and its difference are energy-saving potential
As a result；
Step S419, as a result output device 105 is by the diagnosis of energy saving result and energy-saving potential of output data analytical equipment 103
The energy-saving potential result of computing device 104；
Step S420 terminates the method for the present invention.
The diagnostic process is as shown in Figure 2.
The invention has the beneficial effects as follows：One kind is diagnosed and energy-saving potential point based on service data to Energy Saving of Central Air-conditioning
Analysis method, can more comprehensively, more be met actual energy-conservation and is examined by the analysis to running data to user's offer
Disconnected and energy-saving potential result, is that energy saving of system optimization operation and reducing energy consumption etc. provide important decision foundation.
Fig. 1 is that one kind of the present invention is diagnosed and energy-saving potential analysis system based on service data to Energy Saving of Central Air-conditioning
The general frame；
Fig. 2 is that one kind of the present invention is diagnosed and energy-saving potential analysis system based on service data to Energy Saving of Central Air-conditioning
Data prediction device block diagram；
Fig. 3 is that one kind of the present invention is diagnosed and energy-saving potential analysis system based on service data to Energy Saving of Central Air-conditioning
Data analysis set-up block diagram；
Fig. 4 is that one kind of the present invention is diagnosed and energy-saving potential analysis method based on service data to Energy Saving of Central Air-conditioning
Flow chart.
Specific embodiment：
With reference to accompanying drawing 1～4, the specific embodiment of the present invention is described in detail.
Fig. 1 shows that a kind of service data that is based on of the invention is diagnosed and energy-saving potential to Energy Saving of Central Air-conditioning
The general frame of analysis system 100.It is described Energy Saving of Central Air-conditioning to be diagnosed based on service data and energy-saving potential analysis system
The air-conditioning system actual operating data to being input into of uniting is processed, analyzed, and finally gives diagnosis of energy saving and energy-saving potential result.
As shown in figure 1, a kind of include data based on service data to Energy Saving of Central Air-conditioning diagnosis and energy-saving potential analysis system 100
The output of input unit 101, data prediction device 102, data analysis set-up 103, energy-saving potential computing device 104 and result
Device 105.
Data input device 101 is used for the central air conditioner system actual operating data that input will be analyzed, the data
Can be that equipment energy consumption data, state parameter or other air-conditioning systems for including various data types run relevant data, example
Such as whether equipment is frequency conversion equipment.
Data prediction device 102, is connected with data input device 101, for coming from data input device 101
Input data carries out data prediction.
In the present embodiment, as shown in Fig. 2 data prediction device 102 is further included：Data scrubbing device 201,
It is connected with data input device 101, for carrying out data scrubbing to the input data for coming from data input device 101；Data
Integrating device 202, is connected with data scrubbing device 201, for completing liquidation procedures to come from data scrubbing device 201
Data carry out data integration；Data converting apparatus 203, are connected, for coming from data integration with data integration device 202
The data for completing integrated program of device 202 carry out data conversion；And, data amplification device 204, with data converting apparatus
203 connections, for carrying out data amplification to the data for completing conversion program for coming from data converting apparatus 203.
Data analysis set-up 103, is connected with the data amplification device 204 in data prediction device 102, for from
Data analysis is carried out in the data for completing to pre-process of data amplification device 204.
In the present embodiment, as shown in figure 3, data analysis set-up 103 is further included：System condition pattern-recognition is filled
301 are put, is connected to coming from data amplification device 204 with the data amplification device 204 in data prediction device 102
The data for completing to pre-process carry out system condition pattern-recognition；System equipment operation duration and Time-Series analysis device 302, and be
System regime mode identifying device 301 connects, for completing regime mode to come from system condition pattern recognition device 301
The data of identification carry out system equipment operation duration and Time-Series analysis；And, system and equipment analysis on Operating device 303,
It is connected with system equipment operation duration with Time-Series analysis device 302, for coming from system equipment operation duration with sequential point
The equipment of the completion system operation duration of analysis apparatus 302 carries out system and equipment analysis on Operating with the data of Time-Series analysis.
System and equipment analysis on Operating device in energy-saving potential computing device 104, with data analysis set-up 103
303 connections, dive for carrying out energy-conservation to the data for completing to analyze for coming from system and equipment analysis on Operating device 303
Power is calculated.
As a result output device 105, are connected with energy-saving potential computing device 104, for the section of output data analytical equipment 103
The energy-saving potential result of energy diagnostic result and energy-saving potential computing device 104.
Fig. 4 shows that a kind of service data that is based on of the invention is diagnosed and energy-saving potential to Energy Saving of Central Air-conditioning
The flow chart of analysis method.Method shown in Fig. 4 starts from step S401.Then, in step S402, from data input device
The central air conditioner system actual operating data of the pending diagnosis of energy saving of 101 inputs and Potentials.
Then, pre-processed by 102 pairs of data of data prediction device：
In step S403, the data of input are carried out data scrubbing device 201 cleaning of missing data, using it is existing into
Row are deleted, paired delet method is cleared up missing data.In step S404, point analysis or to utilize decision tree using peeling off
The mode pruned to interference will be identified as disturbing the object data of data to filter out and then mask.In step
S405, will can be plotted curve map for the meeting interference observation sight line of analysis and research and need to carry out numerical characteristic to data later
(such as：Mean value, intermediate value, median, the coefficient of skewness, coefficient of kurtosis of energy consumption etc.) calculate equipment outage data cleared up.
202 pairs, data integration device has completed the data of the liquidation procedures of data scrubbing device 201 and has carried out data integration.Due to
Air-conditioning system service data is probably derived from two sets of even more how different monitoring systems (or platform), such as equipment energy consumption monitoring
System and running state parameter monitoring system, in step S406, typically with common item (such as：Time term) be by two sets for reference items
The data of system are merged, if there is the inconsistent situation of two sets of system data acquisition time steps, will be compared with large time step institute
Regarding the data with deficient phenomena as in system data, and high priority data after merging is proceeded to into data cleaning plant 201 is carried out
Missing data is cleared up.In step S407, the duplicate data that data acquisition time step-length rule is not met in data is deleted,
Such as, time step to occur in that 17 simultaneously in the data of 1 hour (integral point):59:00 moment and 18:00:The data at 00 moment,
Should be by 17:59:00 time data is considered as the neighbouring integral point moment (18:00:00) repetition of data, and be deleted.In step
S408, the colliding data for not meeting Refrigeration ＆ Air-Conditioning technical field physics law is deleted, such as, certain moment is operating
Main frame chilled water supply water temperature is higher than this kind of data of chilled water return water temperature, runs counter to Refrigeration Technique principle, is considered as colliding data simultaneously
By its paired deletion.
Data converting apparatus 203 pairs have completed the data of the integrated program of data integration device 202 and have carried out data conversion.In step
Rapid S409, data converting apparatus 203 will be transformed to more generally measure list to the unification of the measurement unit of same physical type data
Position, such as be transformed to relative more generally measurement unit kilowatt (kW) by standard ton made in U.S.A (USRT) with kilowatt (kW) unification.To sky
Adjusting system equipment starts the concrete energy consumption size that equipment is indifferent in the analysis of order, more pays close attention to whether equipment runs, so in step
Rapid S410, can by for the continuous data of the equipment energy consumption of the analysis be transformed to such as start shooting (ON) or shut down (OFF) from
Scattered type data.
Data amplification device 204 pairs has completed the data of the conversion program of data converting apparatus 203 and has carried out data amplification.In order to
Data analysis efficiency is improved, particularly in the case where data relationship less understands, in step S411, it is possible to use as chilled water
Supply water temperature and chilled water return water temperature derive chilled water supply backwater temperature difference, so as to expand to available data.
After completing and being pre-processed by 102 pairs of data of data prediction device, will be by data analysis set-up
103 pairs of data are analyzed：
In step S412, system condition pattern recognition device 301 is based on the data for completing to pre-process, using energy consumption data
Cluster analysis and the method for decision tree classification, are identified to system condition pattern.For example, to ice-chilling air conditioning system energy consumption
Data carry out cluster analysis, it can be seen that there is the data cases that a class compares concentration to be its refrigeration host computer, cooling water pump and its outdoor
The energy consumption of heat transmission equipment is 0 or near 0, can will possess ejusdem generis data using Decision tree classification and be classified as one
Class, and define the system condition pattern that this kind of data represent the independent cooling of cold accumulating device by ice.
In step S413, system equipment operation duration will be to institute under the various regime modes of system with Time-Series analysis device 302
There is equipment operation duration to carry out statistical analysis, draw the result for whether meeting equal equal travel time strategy.Then, in step
S414, system equipment operation duration will be using association analysis method to similar under various regime modes with Time-Series analysis device 302
(startup) operation order that type equipment shows in actual moving process is analyzed, and draws under the various regime modes of system
Equipment (startup) runs order result.
In step S415, system and equipment analysis on Operating device 303 are by using the numerical characteristic of equipment energy consumption data
(such as：The coefficient of skew, the coefficient of variation, coefficient of kurtosis etc.) system equipment converting operation characteristic is analyzed, whether identification equipment
For frequency conversion equipment or whether converting operation.In step S416, system and equipment analysis on Operating device 303 will be using returning point
Analysis method, to system can the relation property exerted oneself with it of equipment energy consumption be fitted, such as, and to determine frequency centrifugal water pump energy consumption and
Discharge relation characteristic can typically carry out linear fit, and for should typically carry out the Nonlinear Quasi of cubic curve during frequency conversion
Close.Afterwards, in step S417, system and equipment analysis on Operating device 303 will be using service datas, to system operation
In all kinds of constraintss carry out reductive analysis, such as, the maximum cooling capacity of refrigeration host computer under certain regime mode is returned
Receive, and such as, recurrence point is carried out with the restriction relation of remaining cold storage capacity to cold of releasing maximum per hour in ice-chilling air conditioning system
Analysis.
Completing the data analysis that carried out by 103 pairs of data of data analysis set-up for the purpose of System Energy Save Diagnosis
Afterwards, energy-saving potential computing device 104 will be analyzed calculating to energy saving of system potentiality：In step S418, energy-saving potential meter
Calculate device 104 and be directed to each moment system load demand, gone out based on the system equipment that acquisition is analyzed by data analysis set-up 103
Power and energy consumption characteristics and system and equipment operation constraints, using intelligent optimization algorithm (such as：Particle swarm optimization algorithm) to fortune
Row energy consumption (or expense) minimum carries out optimizing, and draws system minimum operation energy consumption (or expense) result, actual motion energy
Consumption (or expense) data and its difference are energy-saving potential result.
Step S419, as a result output device 105 is by the diagnosis of energy saving result and energy-saving potential of output data analytical equipment 103
The energy-saving potential result of computing device 104.
Finally terminate the method for the present invention in step S420.
The description of the specification of disclosure provided above is exemplary, rather than restricted.According to above-mentioned teaching,
Many modifications and changes of the present invention are all possible.Therefore, it is to preferably explain this to select and describe embodiment
Bright principle and its application, and understand those of ordinary skill in the art, on the premise of without departing from essence of the present invention, Suo Youxiu
Change and change is each fallen within protection scope of the present invention defined by the claims.
Claims (1)
1. it is a kind of based on service data to Energy Saving of Central Air-conditioning diagnose and energy-saving potential analysis method, based on central air-conditioning
Running data, Jing after carrying out data prediction to input data, then Jing data analysis steps to pre-processing
Data carry out system condition pattern-recognition, system equipment operation duration and impartial operation reserve analysis, system equipment operation time
Sequence analysis, the analysis of system equipment frequency property, system equipment are exerted oneself and energy consumption characteristics analysis, system and equipment operation constraints
Analysis, based on this again warp knuckle energy potentiality calculation procedure to system minimum operation energy consumption calculate, obtain System Energy Save Diagnosis knot
Fruit and energy-saving potential result；Including the steps：
Step S401, starts；
Step S402, from data input device (101) the central air conditioner system reality of pending diagnosis of energy saving and Potentials is input into
Border service data；Then, the data are pre-processed by data prediction device (102)；
The data of input are carried out step S403, data scrubbing device (201) cleaning of missing data, are deleted in column using existing
Except, paired delet method is cleared up missing data；
Step S404, data scrubbing device (201) to interference using peeling off by point analysis or being pruned using decision tree
Mode is identified as disturbing the object data of data to filter out and then mask；
Step S405, data scrubbing device (201) will can be plotted meeting interference observation sight line of the curve map for analysis and research later
Clear up with the equipment outage data for needing to carry out data numerical characteristic calculating；
Step S406, data integration device (202) is that reference items will be monitored from the different of same air-conditioning system with common item
System data is merged, if there is the inconsistent situation of different monitoring system data acquisition time step-lengths, by larger time step
Long place system data regards the data with deficient phenomena as, and high priority data after merging is proceeded to into data cleaning plant
(201) missing data cleaning is carried out；
Step S407, data integration device (202) enters the duplicate data that data acquisition time step-length rule is not met in data
Row is deleted；
Step S408, data integration device (202) enters the colliding data for not meeting Refrigeration ＆ Air-Conditioning technical field physics law
Row is deleted；
Step S409, data converting apparatus (203) will be transformed to unified metering to the measurement unit of same physical type data
Unit；
Step S410, data converting apparatus (203) will start the continuous type number of the equipment energy consumption of order analysis for system equipment
According to the discrete data for being transformed to start shooting or shut down；
Step S411, data amplification device (204) is derived chilled water and is supplied using chilled water supply water temperature and chilled water return water temperature
Backwater temperature difference, so as to expand to available data；
Step S412, system condition pattern recognition device (301) is clustered based on the data for completing to pre-process using energy consumption data
The method of analysis and decision tree classification, is identified to system condition pattern；
Step S413, system equipment operation duration is with Time-Series analysis device (302) to all devices under the various regime modes of system
Operation duration carries out statistical analysis, draws the result for whether meeting equal equal travel time strategy；
Step S414, system equipment operation duration is with Time-Series analysis device (302) using association analysis method to various operating mode moulds
The formula operation order that similarly hereinafter type equipment shows in actual moving process is analyzed, and draws the various regime modes of system
Divide into received shipment row order result；
Step S415, system and equipment analysis on Operating device (303) are using the numerical characteristic of equipment energy consumption data to system
Equipment converting operation characteristic is analyzed, and whether identification equipment is frequency conversion equipment or whether converting operation；
Step S416, system and equipment analysis on Operating device (303) use regression analysis, to system energy equipment energy
The relation property that consumption is exerted oneself with it is fitted；
Step S417, system and equipment analysis on Operating device (303) utilize service data, and all kinds of operations to system are constrained
Condition carries out reductive analysis；
Step S418, energy-saving potential computing device (104) for each moment system load demand, based on being filled by data analysis
The system equipment for putting (103) analysis acquisition is exerted oneself and energy consumption characteristics and system and equipment operation constraints, using optimized algorithm
Optimizing is carried out, and draws system minimum operation energy consumption result, actual motion energy consumption data and its difference are energy-saving potential
As a result；
Step S419, as a result the diagnosis of energy saving result and energy-saving potential meter of output device (105) output data analytical equipment (103)
Calculate the energy-saving potential result of device (104)；
Step S420, terminates.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410264063.8A CN104091042B (en) | 2014-06-15 | 2014-06-15 | Operating data-based method for energy conservation diagnosis and energy conservation potential analysis on central air-conditioning system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410264063.8A CN104091042B (en) | 2014-06-15 | 2014-06-15 | Operating data-based method for energy conservation diagnosis and energy conservation potential analysis on central air-conditioning system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104091042A CN104091042A (en) | 2014-10-08 |
| CN104091042B true CN104091042B (en) | 2017-04-12 |
Family
ID=51638758
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410264063.8A Active CN104091042B (en) | 2014-06-15 | 2014-06-15 | Operating data-based method for energy conservation diagnosis and energy conservation potential analysis on central air-conditioning system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104091042B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105759608B (en) * | 2016-02-26 | 2018-12-28 | 北京邮电大学 | A kind of power-economizing method and system |
| CN108224681A (en) * | 2017-12-16 | 2018-06-29 | 广西电网有限责任公司电力科学研究院 | Non-intrusion type starting of air conditioner detection method based on decision tree classifier |
| CN109084403B (en) * | 2018-06-29 | 2021-02-26 | 广州能迪能源科技股份有限公司 | Method for obtaining static control strategy of water chilling unit based on air conditioner load time sequence distribution |
| CN109460873A (en) * | 2018-11-14 | 2019-03-12 | 北京未来科学城科技发展有限公司 | Air-conditioning system running optimizatin method and apparatus |
| CN116520709A (en) * | 2023-06-16 | 2023-08-01 | 上海能誉科技股份有限公司 | Operation optimization device and operation optimization method for energy power system |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101782258A (en) * | 2009-01-19 | 2010-07-21 | 中华电信股份有限公司 | Energy-saving method for air conditioner |
| CN202734154U (en) * | 2012-06-30 | 2013-02-13 | 李钢 | Central air conditioning self-optimization intelligent fuzzy control device |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7840383B2 (en) * | 2009-04-01 | 2010-11-23 | Eugene Wang | Operationalizing a power usage monitoring system |
| US20100318235A1 (en) * | 2009-06-15 | 2010-12-16 | David Moss | System for monitoring energy consumption of an electrical appliance |
-
2014
- 2014-06-15 CN CN201410264063.8A patent/CN104091042B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101782258A (en) * | 2009-01-19 | 2010-07-21 | 中华电信股份有限公司 | Energy-saving method for air conditioner |
| CN202734154U (en) * | 2012-06-30 | 2013-02-13 | 李钢 | Central air conditioning self-optimization intelligent fuzzy control device |
Non-Patent Citations (2)
| Title |
|---|
| 典型绿色建筑运行能耗与节能潜力分析;杨石等;《建筑科学》;20140531;第30卷(第增刊-1期);第27-32页 * |
| 基于运行数据的建筑能耗评价方法研究-以5星级酒店建筑为例;刘益民等;《建筑科学》;20121231;第28卷(第12期);第57-60页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104091042A (en) | 2014-10-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104091042B (en) | Operating data-based method for energy conservation diagnosis and energy conservation potential analysis on central air-conditioning system | |
| Xue et al. | Fault detection and operation optimization in district heating substations based on data mining techniques | |
| CN107146004B (en) | A kind of slag milling system health status identifying system and method based on data mining | |
| CN103853106B (en) | A kind of energy consumption Prediction Parameters optimization method of building energy supplied equipment | |
| Jianzhong et al. | Aircraft air conditioning system health state estimation and prediction for predictive maintenance | |
| CN111486552B (en) | Method for identifying water supply temperature strategy of chilled water of air conditioner based on subentry metering data | |
| JP2003242212A (en) | Apparatus and method for determining day of the week with similar utility consumption profile | |
| Sun et al. | Optimization of support vector regression model based on outlier detection methods for predicting electricity consumption of a public building WSHP system | |
| CN104697107A (en) | Intelligent learning energy-saving regulation and control system and method | |
| CN104456852A (en) | System and method for monitoring and evaluating operation of concentrated air conditioner refrigerating station | |
| CN107291830A (en) | A kind of creation method of equipment knowledge base | |
| CN103335537A (en) | Method for on-line monitoring real-time operation cleanness factor of condenser | |
| JP5787831B2 (en) | Equipment inspection plan support device and program | |
| CN105465946A (en) | Method and system for energy consumption analysis of central air conditioner refrigeration station | |
| CN103487644A (en) | Electric energy subentry energy consumption metering method and device | |
| CN107121943A (en) | A kind of method and apparatus for being used to obtain the health forecast information of intelligence instrument | |
| CN107607342A (en) | The healthy efficiency detection method of Air Conditioning Facilities device cluster | |
| CN103487250A (en) | Coal mining equipment predictive maintenance method based on two-dimensional projection | |
| CN202546235U (en) | Automatic monitoring system of steam trap | |
| CN101539137A (en) | Residual life gray prediction method of aerospace hydraulic pump based on delta filter | |
| CN102495305A (en) | Grey theory-based fault trend analysis method of track traffic operation electromechanical equipment | |
| CN104295373A (en) | Three-point model based diesel engine fault prediction method | |
| CN103914630A (en) | Supervising system for building energy consumption | |
| CN107461881B (en) | Refrigeration host energy efficiency diagnosis method and system for hospital air conditioner room | |
| KR20130065844A (en) | System and method for managing energy equipments efficiency in intelligent building |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |