CN105260792A - Air conditioner electricity reference value prediction system and method - Google Patents
Air conditioner electricity reference value prediction system and method Download PDFInfo
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- 230000005611 electricity Effects 0.000 title claims abstract description 123
- 238000000034 method Methods 0.000 title claims abstract description 30
- 238000004378 air conditioning Methods 0.000 claims description 63
- 238000013075 data extraction Methods 0.000 claims description 9
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Abstract
The invention relates to an air conditioner electricity reference value prediction system and a method. The system comprises an intelligent air conditioner, a cloud database server, a meteorological data extractor and an algorithm server which are respectively used for acquiring electricity data, electricity data interaction and storage, extracting meteorological data and predicting a future air conditioner electricity reference value. The invention further relates to the air conditioner electricity reference value prediction method. The air conditioner electricity reference value prediction method is used for acquiring the electricity data and predicting the future air conditioner electricity reference value for the intelligent air conditioner according to historical electricity data and the meteorological information. Through the method, self periodicity of electrical equipment is fully considered as well as relationship between electricity and the weather; optimum prediction can be adjusted in a rolling window in real time, and an electricity prediction blank of electrical appliances is filled.
Description
Technical field
The present invention relates to the system and method for a kind of air conditioning electricity reference value prediction, belong to computing machine power domain.
Background technology
For increasing new forms of energy supply in the future, the configuration of electric power energy seems abnormal important, and how distributing different electric power energy distribution is a problem always perplexing electrical supplier.
Traditional load forecast generally concentrates on grid side, according to the height of voltage, be followed successively by: transmission system load prediction (69 kilovolts of its above load buses), transformer station's load prediction (11 kilovolts to 69 kilovolts), power distribution system load prediction (220 volts to 11 kilovolts).Load forecast is generally maximum is accurate to bus endpiece (feederlevel), and can not arrive certain concrete consumer.Following along with more and more Smart Home introducing electrical network, the above-mentioned load prediction being accurate to bus end no longer enough will be used for the double regulation control (namely simultaneously controlling generating and electricity consumption side) of intelligent grid.This invention is exactly filled up the vacancy of precision of prediction at facility level.Based on the reference value of prediction, electrical power services business (such as grid company, the such as following professional sale of electricity business that may occur) accurately can provide Subsequent activations mechanism, thus quantize the benefit of incentive mechanism.
Summary of the invention
For the technical deficiency of prior art power prediction, current electric power is detected and analyzes, invented a kind of air conditioning electricity reference value prognoses system and method, make up electric power and detect the vacancy on equipment.
One aspect of the present invention provides a kind of air conditioning electricity reference value prognoses system, comprise: intelligent air condition, for gathering intelligent air condition electricity consumption numerical value, and send collection current power data, described current power data comprise the acquisition time of intelligent air condition electricity consumption numerical value and correspondence; Weather data extraction apparatus, for extracting local history weather data, and can receive the instruction transferring history weather data, described weather data comprises temperature, humidity; Cloud database server, for storing the electricity consumption data that intelligent air condition sends, receive the current power data that described intelligent air condition sends, the instruction transferring history weather data is sent to described data message extraction apparatus, and transfer and the history electricity consumption data self stored, described current power data, history weather data, history electricity consumption data become combination electricity consumption data, and send described combination electricity consumption data; Arithmetic server, for receiving the combination power information that described cloud database server sends, using autoregression algorithm to combination electricity consumption data analysis, doping air conditioning electricity reference value in the future, and send the air conditioning electricity reference value of prediction.
Further, the intelligent air condition of described air conditioning electricity reference value prognoses system comprises: electricity consumption data acquisition module, gathers the time data of air-conditioning current power numerical value and correspondence at set intervals; The electricity consumption data of collection are sent to described cloud database server by data transmission module, also for receiving the air-conditioning prediction reference value that described arithmetic server sends; Reference value display module, for showing the air-conditioning prediction of described data link, the change of the air conditioning electricity reference value predicted data that can send according to arithmetic server, dynamic conditioning display numerical value.
Further, the weather data extraction apparatus of described air conditioning electricity reference value prognoses system comprises: the history weather data extracted is the weather data of the corresponding time interval (such as: No. 1, the moon) of current power data.
Further, the cloud database server of described air conditioning electricity reference value prognoses system comprises: memory module, receive and store described intelligent air condition send electricity consumption data; Data transfer module, send the instruction transferring history weather data to described weather data extraction apparatus; Combination electricity consumption data are sent to described arithmetic server by data transmission blocks.
Further, the arithmetic server of described air conditioning electricity reference value prognoses system comprises: Algorithm Analysis module, average based on weather data proportion weighted to the current power data in described data splitting and history electricity consumption data, draw air conditioning electricity prediction reference value, and send air conditioning electricity prediction;
The present invention provides the method for a kind of air conditioning electricity reference value prediction on the other hand, the method comprises the following steps: gather intelligent air condition electricity consumption numerical value, and sending collection current power data, described current power data comprise the acquisition time of intelligent air condition electricity consumption numerical value and correspondence; Extract local history weather data, and can receive the instruction transferring history weather data, described weather data comprises temperature, humidity; Store the electricity consumption data that intelligent air condition sends, receive the current power data that described intelligent air condition sends, the instruction transferring history weather data is sent to described data message extraction apparatus, and transfer and the history electricity consumption data self stored, described current power data, history weather data, history electricity consumption data become combination electricity consumption data, and send described combination electricity consumption data; Receive the combination power information that described cloud database server sends, use autoregression algorithm to combination electricity consumption data analysis, dope air conditioning electricity reference value in the future, and send the air conditioning electricity reference value of prediction.
Further, described air conditioning electricity reference value Forecasting Methodology also comprises: the time data gathering air-conditioning current power numerical value and correspondence at set intervals; The electricity consumption data of collection are sent to described cloud database server, also for receiving the air-conditioning prediction reference value that described arithmetic server sends; Show the air-conditioning prediction of described data link, the change of the air conditioning electricity reference value predicted data that can send according to arithmetic server, dynamic conditioning display numerical value.
Further, in described air conditioning electricity reference value Forecasting Methodology, the history weather data extracted is the weather data of the corresponding time interval (such as: No. 1, the moon) of current power data.
Further, described air conditioning electricity reference value Forecasting Methodology also comprises: receive and store described intelligent air condition send electricity consumption data; The instruction transferring history weather data is sent to described weather data extraction apparatus; Combination electricity consumption data are sent to described arithmetic server.
Further, described air conditioning electricity reference value Forecasting Methodology also comprises: average based on weather data proportion weighted to the current power data in described data splitting and history electricity consumption data, draws air conditioning electricity prediction reference value, and sends air conditioning electricity prediction.
Beneficial effect of the present invention is: utilize autoregression algorithm, average based on weather proportion weighted with phase electricity consumption data in the same time to the date of same period in history.Such algorithm fully takes into account the periodicity that consumer self has, and the strong correlation between electricity consumption with weather is coupled.Based on the reference value prediction that this algorithm draws, can also adjust in real-time rolling window and reach optimum prediction.
Accompanying drawing explanation
Figure 1 shows that according to embodiment of the present invention general structure block diagram;
Figure 2 shows that the process flow diagram according to embodiment of the present invention;
Figure 3 shows that the data flow diagram according to embodiment of the present invention.
Embodiment
In order to make the object, technical solutions and advantages of the present invention clearly, describe the present invention below in conjunction with the drawings and specific embodiments.Air-conditioning reference value Forecasting Methodology of the present invention.
Figure 1 shows that the general structure block diagram according to embodiment of the present invention.Described air-conditioning reference value prognoses system in comprising intelligent air condition 1, cloud database server 2, weather information extraction apparatus 3, and in the system that forms of arithmetic server 4 of prediction reference prediction.Described intelligent air condition 1, for gathering the actual power consumption of each air-conditioning, is designed by developer.Described cloud server 2, for the data needed for Storage Estimation, comprises the electricity consumption of air-conditioning history, history weather information.Weather information extraction apparatus 3 is connected with cloud server, to extract local temperature and humidity information at any time.Described prediction reference value algorithm 4 is core algorithm server.Detailed, intelligent air condition, for gathering intelligent air condition electricity consumption numerical value, and send collection current power data, described current power data comprise the acquisition time of intelligent air condition electricity consumption numerical value and correspondence; Weather data extraction apparatus, for extracting local history weather data, and can receive the instruction transferring history weather data, described weather data comprises temperature, humidity; Cloud database server, for storing the electricity consumption data that intelligent air condition sends, receive the current power data that described intelligent air condition sends, the instruction transferring history weather data is sent to described data message extraction apparatus, and transfer and the history electricity consumption data self stored, described current power data, history weather data, history electricity consumption data become combination electricity consumption data, and send described combination electricity consumption data; Arithmetic server, for receiving the combination power information that described cloud database server sends, using autoregression algorithm to combination electricity consumption data analysis, doping air conditioning electricity reference value in the future, and send the air conditioning electricity reference value of prediction.
Figure 2 shows that the process flow diagram according to embodiment of the present invention.It comprises following detailed step:
1. intelligent air condition end 1 was sent to cloud server 2 by every 15 minutes power information;
2. cloud server 2 extracts three months in the past temperature informations in the same time on the same day weekly from weather information 3;
3. cloud server 2 extracts past three months corresponding to this air-conditioning ID power information in the same time, altogether 90/7=13 data point on the same day weekly from historical data;
4. these 13 (temperature, electricity consumption) combined informations are sent to prediction reference value arithmetic server 4 by cloud server 2;
5. reference value arithmetic server 4 is weighted on average according to these 13 (temperature, electricity consumption) combined informations, obtains the prediction reference value of following 15 minutes these intelligent air conditions;
6. reference value arithmetic server is after the actual value arrival of lower 15 minutes, does dynamic conditioning to prediction reference value before, using the AME of 10 windows that roll as value of making up the difference, calibrates next one prediction;
7. carry out next one prediction in 15 minutes, get back to step 1.
Figure 3 shows that the data flow diagram according to embodiment of the present invention, based on the flow process that Fig. 2 provides, its detailed data flow has set forth air conditioning electricity data from collection to prediction detailed process.
The above, just preferred embodiment of the present invention, the present invention is not limited to above-mentioned embodiment, as long as it reaches technique effect of the present invention with identical means, all should belong to protection scope of the present invention.In protection scope of the present invention, its technical scheme and/or embodiment can have various different modifications and variations.
Claims (10)
1. a system for air conditioning electricity reference value prediction, it is characterized in that, this system comprises:
Intelligent air condition, for gathering the time of intelligent air condition electricity consumption numerical value and correspondence, and send collection current power data, described current power data comprise the acquisition time of intelligent air condition electricity consumption numerical value and correspondence;
Weather data extraction apparatus, for extracting local history weather data, and can receive the instruction transferring history weather data;
Cloud database server, for storing the electricity consumption data that intelligent air condition sends, receive the current power data that described intelligent air condition sends, the instruction transferring history weather data is sent to described data message extraction apparatus, and transfer and the history electricity consumption data self stored, described current power data, history weather data, history electricity consumption data become combination electricity consumption data, and send described combination electricity consumption data;
Arithmetic server, for receiving the combination power information that described cloud database server sends, using respective algorithms to combination electricity consumption data analysis, doping air conditioning electricity reference value in the future, and send the air conditioning electricity reference value of prediction.
2. the system of air conditioning electricity reference value prediction according to claim 1, it is characterized in that, described intelligent air condition comprises:
Electricity consumption data acquisition module, gathers the time data of air-conditioning current power numerical value and correspondence at set intervals;
The electricity consumption data of collection are sent to described cloud database server by data transmission module, also for receiving the air-conditioning prediction reference value that described arithmetic server sends;
Reference value display module, for showing the air-conditioning prediction of described data link, the change of the air conditioning electricity reference value predicted data that can send according to arithmetic server, dynamic conditioning display numerical value.
3. the system of air conditioning electricity reference value prediction according to claim 1, it is characterized in that, described weather data extraction apparatus comprises:
The history weather data extracted is the weather data in the current power data corresponding time interval.
4. the system of air conditioning electricity reference value prediction according to claim 1, it is characterized in that, described cloud database server comprises:
Memory module, receive and store described intelligent air condition send electricity consumption data;
Data transfer module, send the instruction transferring history weather data to described weather data extraction apparatus;
Combination electricity consumption data are sent to described arithmetic server by data transmission blocks.
5. the system of air conditioning electricity reference value prediction according to claim 1, it is characterized in that, described arithmetic server comprises:
Algorithm Analysis module, average based on weather data proportion weighted to the current power data in described data splitting and history electricity consumption data, draw air conditioning electricity prediction reference value, and send described air conditioning electricity prediction reference value.
6. a method for air conditioning electricity reference value prediction, it is characterized in that, the method comprises:
Gather intelligent air condition electricity consumption numerical value, and send collection current power data, described current power data comprise the acquisition time of intelligent air condition electricity consumption numerical value and correspondence;
Extract local history weather data, and can receive the instruction transferring history weather data, described weather data comprises temperature, humidity;
Store the electricity consumption data that intelligent air condition sends, receive the current power data that described intelligent air condition sends, the instruction transferring history weather data is sent to described data message extraction apparatus, and transfer and the history electricity consumption data self stored, described current power data, history weather data, history electricity consumption data become combination electricity consumption data, and send described combination electricity consumption data;
Receive the combination power information that described cloud database server sends, use autoregression algorithm to combination electricity consumption data analysis, dope air conditioning electricity reference value in the future, and send the air conditioning electricity reference value of prediction.
7. the method for air conditioning electricity reference value prediction according to claim 6, it is characterized in that, the method also comprises:
Gather the time data of air-conditioning current power numerical value and correspondence at set intervals;
The electricity consumption data of collection are sent to described cloud database server, also for receiving the air-conditioning prediction reference value that described arithmetic server sends;
Show the air-conditioning prediction of described data link, the change of the air conditioning electricity reference value predicted data that can send according to arithmetic server, dynamic conditioning display numerical value.
8. the method for air conditioning electricity reference value prediction according to claim 6, it is characterized in that, the method also comprises:
The history weather data extracted is the weather data in the current power data corresponding time interval.
9. the method for air conditioning electricity reference value prediction according to claim 6, it is characterized in that, the method also comprises:
Receive and store described intelligent air condition send electricity consumption data;
The instruction transferring history weather data is sent to described weather data extraction apparatus;
Combination electricity consumption data are sent to described arithmetic server.
10. the method for air conditioning electricity reference value prediction according to claim 6, it is characterized in that, the method also comprises:
Average based on weather data proportion weighted to the current power data in described data splitting and history electricity consumption data, draw air conditioning electricity prediction reference value, and send described air conditioning electricity prediction reference value.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106773763A (en) * | 2016-12-28 | 2017-05-31 | 重庆金鑫科技产业发展有限公司 | A kind of information linkage processing method and device |
| CN107480811A (en) * | 2017-07-26 | 2017-12-15 | 珠海格力电器股份有限公司 | Equipment energy consumption data processing method, device, system and equipment |
| CN107958307A (en) * | 2017-11-28 | 2018-04-24 | 珠海格力电器股份有限公司 | Electricity charge prediction method and device |
| CN109764449A (en) * | 2019-03-06 | 2019-05-17 | 杭州享福多智能科技有限公司 | A kind of intelligence energy accumulation air conditioner |
| CN111600393A (en) * | 2020-06-18 | 2020-08-28 | 国网四川省电力公司电力科学研究院 | Voltage measurement data reduction method and identification method for different voltage levels in substations |
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| CN106773763A (en) * | 2016-12-28 | 2017-05-31 | 重庆金鑫科技产业发展有限公司 | A kind of information linkage processing method and device |
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| CN111600393A (en) * | 2020-06-18 | 2020-08-28 | 国网四川省电力公司电力科学研究院 | Voltage measurement data reduction method and identification method for different voltage levels in substations |
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