CN105759608A - Energy-saving method and system - Google Patents
Energy-saving method and system Download PDFInfo
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- CN105759608A CN105759608A CN201610109373.1A CN201610109373A CN105759608A CN 105759608 A CN105759608 A CN 105759608A CN 201610109373 A CN201610109373 A CN 201610109373A CN 105759608 A CN105759608 A CN 105759608A
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
Abstract
An embodiment of the invention provides an energy-saving method and system. The method comprises the steps of acquiring a current working condition type of a power system, and acquiring power consumption data of a power consumption device in the current working condition type within a preset period of time; matching the current working condition type with historical working condition types in a pre-built energy-saving measure model, determining whether a successfully matched historical working condition type exists, and if so, determining a size relation between the power consumption data and historical power consumption data of the power consumption device corresponding to the successfully matched historical working condition type within the preset period of time; and when the absolute value of a difference between the power consumption data and the historical power consumption data is greater than a preset threshold, determining that the power consumption device is in an abnormal working mode, and performing an energy-saving operation for the power consumption device by taking energy-saving measures corresponding to the power consumption device corresponding to the successfully matched historical working condition type. The embodiment of the invention can be used for reducing the threshold for the user to taking better energy-saving measures, thus reducing the energy-saving cost.
Description
Technical field
The present invention relates to power control techniques field, particularly relate to a kind of power-economizing method and system.
Background technology
At present, in the Energy Saving Control to power system, conservation measures is selected to realize each current consuming apparatus energy-conservation in power system usually by manual mode.And the technical merit of operator is had higher requirement by the method that this kind implements conservation measures, that is, veteran management personnel are needed to select suitable conservation measures according to the energy consumption data of machine room, and for those of ordinary skill, it is difficult to select suitable conservation measures, namely select preferably conservation measures that common operating personnel has higher threshold, thus result in this kind of power save mode relatively costly.
Therefore, a kind of new energy-saving scheme of offer is provided badly, implements the threshold of preferably conservation measures reducing user, and then reduce energy-conservation cost.
Summary of the invention
The purpose of the embodiment of the present invention is in that to provide a kind of power-economizing method and system, implements the threshold of preferably conservation measures reducing user, and then reduces energy-conservation cost.Concrete technical scheme is as follows:
First aspect, embodiments provides a kind of power-economizing method, is applied to power system, and described power system includes current consuming apparatus, and described method may include that
Obtaining the current working type of described power system, and obtain the power consumption data in preset time period of the current consuming apparatus under described current working type, wherein, described current working type includes at least one condition affecting current consuming apparatus power consumption data；
Described current working type is mated with the history operating mode type in the conservation measures model built in advance, judge whether the history operating mode type that the match is successful, if existing, then judge the magnitude relationship of described power consumption data and the described current consuming apparatus corresponding to history operating mode type that the match is successful the history power consumption data in preset time period, wherein, described history operating mode type includes the condition of at least one history power consumption data affecting current consuming apparatus；
When judging the absolute value of difference of described power consumption data and the described current consuming apparatus corresponding to the history operating mode type that the match is successful the history power consumption data in preset time period more than predetermined threshold value, it is determined that described current consuming apparatus is in anomalous operating mode；
When determining that described current consuming apparatus is in anomalous operating mode, utilize the corresponding conservation measures corresponding to described current consuming apparatus in the described history operating mode type that the match is successful that described current consuming apparatus is carried out power-save operation.
Preferably, the history power consumption data of described current consuming apparatus, including the correction power consumption data that: described current consuming apparatus is performed manually after conservation measures in preset time period, or, the normal power consumption data in preset time period when described current consuming apparatus is not performed manually conservation measures.
Preferably, utilizing sorting algorithm to build conservation measures model in advance, wherein, described sorting algorithm includes one or more in decision tree C45 algorithm, NB Algorithm and algorithm of support vector machine.
Preferably, described sorting algorithm is utilized to build conservation measures model in advance, including:
Utilizing sorting algorithm to build the disaggregated model of the conservation measures corresponding to the disaggregated model of current consuming apparatus in the disaggregated model of history operating mode type, history operating mode type and current consuming apparatus, wherein, described power system includes at least two current consuming apparatus；
Create the first mapping relations table of the disaggregated model of the disaggregated model current consuming apparatus corresponding with it of history operating mode type, and the second mapping relations table of the disaggregated model of the disaggregated model of current consuming apparatus and conservation measures, wherein, the disaggregated model of described current consuming apparatus includes the history power consumption data corresponding to current consuming apparatus；
According to default pretreatment mode, described history power consumption data is carried out pretreatment, to obtain pretreated history power consumption data；
Based on the disaggregated model of the disaggregated model of history operating mode type, the disaggregated model of current consuming apparatus and conservation measures, and the first mapping relations table, the second mapping relations table and pretreated history power consumption data build conservation measures and use model.
Preferably, described pretreatment mode includes: vacancy value facture and at least one calculated in new determinant method.
Preferably, in the embodiment of the present invention, also include:
If judging to be absent from the history operating mode type that the match is successful, then recommend conservation measures based on the history power consumption data in preset time period of the current consuming apparatus in described current consuming apparatus power consumption data in preset time period and the conservation measures model that builds in advance to user.
Second aspect, embodiments provides a kind of energy conserving system, is applied to power system, and described power system includes current consuming apparatus, and described system may include that acquiring unit, matching unit, conservation measures model construction unit, determines unit and judging unit；
Described acquiring unit, for obtaining the current working type of described power system, and obtain the power consumption data in preset time period of the current consuming apparatus under described current working type, wherein, described current working type includes at least one condition affecting current consuming apparatus power consumption data；
Described matching unit, mate for the history operating mode type in conservation measures model that described current working type is built in advance with described conservation measures model construction unit, judge whether the history operating mode type that the match is successful, if existing, then judge the magnitude relationship of described power consumption data and the described current consuming apparatus corresponding to history operating mode type that the match is successful the history power consumption data in preset time period, wherein, described history operating mode type includes the condition of at least one history power consumption data affecting current consuming apparatus；
Described determine unit, for when judging the absolute value of difference of described power consumption data and the described current consuming apparatus corresponding to the history operating mode type that the match is successful the history power consumption data in preset time period more than predetermined threshold value, it is determined that described current consuming apparatus is in anomalous operating mode；
Described judging unit, for when determining that described current consuming apparatus is in anomalous operating mode, utilizing the corresponding conservation measures corresponding to described current consuming apparatus in the described history operating mode type that the match is successful that described current consuming apparatus is carried out power-save operation.
Preferably, the history power consumption data of described current consuming apparatus, including the correction power consumption data that: described current consuming apparatus is performed manually after conservation measures in preset time period, or, the normal power consumption data in preset time period when described current consuming apparatus is not performed manually conservation measures.
Preferably, described conservation measures model construction unit is used for utilizing sorting algorithm to build conservation measures model in advance, and wherein, described sorting algorithm includes one or more in decision tree C45 algorithm, NB Algorithm and algorithm of support vector machine.
Preferably, described conservation measures model construction unit includes: disaggregated model builds subelement, mapping relations table creates subelement, pretreatment subelement and conservation measures and uses model construction subelement；
Described disaggregated model builds subelement, for utilizing sorting algorithm to build the disaggregated model of the conservation measures corresponding to the disaggregated model of current consuming apparatus in the disaggregated model of history operating mode type, history operating mode type and current consuming apparatus, wherein, described power system includes at least two current consuming apparatus；
Described mapping relations table creates subelement, first mapping relations table of the disaggregated model of the current consuming apparatus that disaggregated model for creating history operating mode type is corresponding with it, and the second mapping relations table of the disaggregated model of the disaggregated model of current consuming apparatus and conservation measures, wherein, the disaggregated model of described current consuming apparatus includes the history power consumption data corresponding to current consuming apparatus；
Described pretreatment subelement, for carrying out pretreatment according to default pretreatment mode to described history power consumption data, to obtain pretreated history power consumption data；
Described conservation measures uses model construction subelement, for the disaggregated model based on the disaggregated model of history operating mode type, the disaggregated model of current consuming apparatus and conservation measures, and the first mapping relations table, the second mapping relations table and pretreated history power consumption data build conservation measures and use model.
Preferably, described pretreatment mode includes: vacancy value facture and at least one calculated in new determinant method.
Preferably, in embodiments of the present invention, described matching unit is additionally operable to: if judging to be absent from the history operating mode type that the match is successful, then recommend conservation measures based on the history power consumption data in preset time period of the current consuming apparatus in described current consuming apparatus power consumption data in preset time period and the conservation measures model that builds in advance to user.
nullThe power-economizing method of embodiment of the present invention offer and system，Conservation measures model can be built in advance，Namely according to history operating mode type、The conservation measures that history power consumption data and skilled engineer adopt takes out conservation measures recommended models，Realize the conservation measures that under different history operating mode types, current consuming apparatus power consumption data in the normal mode of operation and conservation measures and experienced staff adopted at reply anomalous operating mode and power consumption data is analyzed and learns，And then only need to obtain the power consumption data corresponding to the current working type of power system and current consuming apparatus and can judge under current working type, whether current consuming apparatus is in anomalous operating mode by the conservation measures model built in advance，If judging to be in anomalous operating mode，Then according to conservation measures corresponding to current consuming apparatus under this operating mode type in the conservation measures model that builds in advance, current consuming apparatus is carried out energy-conservation，Skilled engineer can be obtained in history in the conservation measures adopted in this kind of situation and take preferably power-save operation，Provide the Forecasting Methodology of conservation measures，Reduce user and implement the threshold of preferably conservation measures，Improve Consumer's Experience，Thus reducing energy-conservation cost.Certainly, arbitrary product or the method for implementing the present invention it is not absolutely required to reach all the above advantage simultaneously.
Accompanying drawing explanation
In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, the accompanying drawing used required in embodiment or description of the prior art will be briefly described below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the premise not paying creative work, it is also possible to obtain other accompanying drawing according to these accompanying drawings.
The schematic flow sheet of a kind of power-economizing method that Fig. 1 provides for the embodiment of the present invention；
The structural representation of a kind of energy conserving system that Fig. 2 provides for the embodiment of the present invention；
The schematic diagram of a kind of conservation measures model built in advance that Fig. 3 provides for the embodiment of the present invention；
The schematic diagram of the conservation measures model that the another kind that Fig. 4 provides for the embodiment of the present invention builds in advance.
Detailed description of the invention
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is only a part of embodiment of the present invention, rather than whole embodiments.Based on the embodiment in the present invention, the every other embodiment that those of ordinary skill in the art obtain under not making creative work premise, broadly fall into the scope of protection of the invention.
In order to solve prior art problem, embodiments provide a kind of power-economizing method and system.
First aspect, embodiments provides a kind of power-economizing method, is applied to power system, and this power system includes current consuming apparatus, as it is shown in figure 1, this power-economizing method may include steps of:
S101: obtain the current working type of this power system, and obtain the power consumption data in preset time period of the current consuming apparatus under operating mode type in this prior, wherein, this current working type includes at least one condition affecting current consuming apparatus power consumption data；
Wherein, first the current working type of this power system is obtained, and obtain current consuming apparatus power consumption data in preset time period, it is understandable that, this power system can include multiple current consuming apparatus, and when including multiple current consuming apparatus, obtain the power consumption data that the plurality of current consuming apparatus is corresponding in preset time period.
It is emphasized that, technical staff can set the size of preset time period as the case may be, and, the factors such as temperature, humidity and operating time can be set as affecting the factor of operating mode type, and acquiescence operating mode type differs when the value of the factors such as temperature, humidity and operating time exceedes preset range.
S102: this current working type is mated with the history operating mode type in the conservation measures model built in advance, judge whether the history operating mode type that the match is successful, if existing, then judge the magnitude relationship of this power consumption data and this current consuming apparatus corresponding to history operating mode type that the match is successful history power consumption data in preset time period, wherein, this history operating mode type includes the condition of at least one history power consumption data affecting current consuming apparatus；
Wherein, the conservation measures model that this builds in advance is a kind of supervised learning model based on classification.History operating mode type can belong to a classification in the conservation measures built in advance, and would be likely to occur history operating mode Class1, history operating mode type 2 and history operating mode type 3 etc. in history operating mode type；The history power consumption data of current consuming apparatus in this history operating mode Class1-3 and history operating mode Class1-3 can be carried out classification supervised learning by the conservation measures model built in advance；Now have only in the conservation measures model that the power consumption data input of current consuming apparatus under current working type and current working type is built in advance, this conservation measures built in advance can provide the conservation measures of prediction, and the conservation measures of this prediction is that the history conservation measures adopted in the corresponding situation of reply according to skilled engineer in history obtains.
S103: when judging the absolute value of difference of this power consumption data and this current consuming apparatus corresponding to the history operating mode type that the match is successful history power consumption data in preset time period more than predetermined threshold value, it is determined that this current consuming apparatus is in anomalous operating mode；
Wherein, when determining that this current consuming apparatus is in anomalous operating mode, it is possible to send warning, current consuming apparatus under prompting user's current working type is in anomalous operating mode, causes the attention of user, it is to avoid the generation of accident, it is understood that it is also feasible that this kind sends the mode of alarm.
S104: when determining that this current consuming apparatus is in anomalous operating mode, utilizes the conservation measures corresponding to this current consuming apparatus corresponding in this history operating mode type that the match is successful that this current consuming apparatus is carried out power-save operation.
Wherein, there is the conservation measures of at least one correspondence in the current consuming apparatus being determined to be in anomalous operating mode.
It should be noted that the step of an embodiment of the conservation measures model prediction conservation measures utilizing this to build in advance concretely: the power consumption data of current consuming apparatus under current working type and current working type is inputted the conservation measures model built in advance；Carry out current working type in a model to mate with history operating mode type；When current working type exists the history operating mode type that the match is successful, the power consumption data of current consuming apparatus under current working is compared with the history power consumption data of current consuming apparatus of the same race under this kind of history operating mode；And can pass through to do difference and compare, and the absolute value of difference more than predetermined threshold value time, determine that now current consuming apparatus is in anomalous operating mode, then adopt the conservation measures corresponding to this current consuming apparatus corresponding in the history operating mode type that the match is successful that this current consuming apparatus is carried out power-save operation；Or compare by doing difference, and the absolute value of difference less than predetermined threshold value time, the energy consumption data of another current consuming apparatus under current working type is compared with the power consumption data of current consuming apparatus of the same race under this kind of history operating mode type, until conservation measures can be matched in this conservation measures model built in advance and adopts this conservation measures that this current consuming apparatus is carried out power-save operation.
Certainly, in another embodiment, after conservation measures can being matched in the conservation measures model that this builds in advance, the conservation measures of this coupling can be prompted to user rather than directly adopt this conservation measures that this current consuming apparatus is carried out power-save operation, allow and the user decide whether to adopt this conservation measures, it is understood that this kind of power save mode is also feasible.
nullIn the embodiment of the present invention，Conservation measures model can be built in advance，Namely according to history operating mode type、The conservation measures that history power consumption data and skilled engineer adopt takes out conservation measures recommended models，Realize the conservation measures that under different history operating mode types, current consuming apparatus power consumption data in the normal mode of operation and conservation measures and experienced staff adopted at reply anomalous operating mode and power consumption data is analyzed and learns，And then only need to obtain the power consumption data corresponding to the current working type of power system and current consuming apparatus and can judge under current working type, whether current consuming apparatus is in anomalous operating mode by the conservation measures model built in advance，If judging to be in anomalous operating mode，Then according to conservation measures corresponding to current consuming apparatus under this operating mode type in the conservation measures model that builds in advance, current consuming apparatus is carried out energy-conservation，Skilled engineer can be obtained in history in the conservation measures adopted in this kind of situation and take preferably power-save operation，Provide the Forecasting Methodology of conservation measures，Reduce user and implement the threshold of preferably conservation measures，Improve Consumer's Experience，Thus reducing energy-conservation cost.
Further, the history power consumption data of this current consuming apparatus, including the correction power consumption data that: this current consuming apparatus is performed manually after conservation measures in preset time period, or, the normal power consumption data in preset time period when this current consuming apparatus is not performed manually conservation measures.
It is understandable that, when building conservation measures model in advance, the correction power consumption data that current consuming apparatus is performed manually after conservation measures in preset time period can be recorded, or, when this current consuming apparatus is not performed manually conservation measures, the normal power consumption data in preset time period is as the history power consumption data corresponding to current consuming apparatus, the then data that now the history power consumption data of current consuming apparatus is corresponding when being all normal operation.When the conservation measures model prediction preferably conservation measures utilizing this to build in advance, find the history operating mode type corresponding to current working type, search after successfully, may determine that whether power consumption data that the current consuming apparatus under current working type the is corresponding absolute value with the difference of the history power consumption data of this kind of current consuming apparatus is more than predetermined threshold value, when more than threshold value, can determine that this current consuming apparatus is in anomalous operating mode, and utilize the conservation measures corresponding to this current consuming apparatus corresponding in this history operating mode type that the match is successful that this current consuming apparatus is carried out power-save operation.
It is emphasized that technical staff can arrange this predetermined threshold value according to specific needs.
Further, utilizing sorting algorithm to build conservation measures model in advance, wherein, this sorting algorithm includes one or more in decision tree C45 algorithm, NB Algorithm and algorithm of support vector machine.
It is understandable that, utilize one or more sorting algorithms in decision tree C45 algorithm, NB Algorithm and algorithm of support vector machine to build conservation measures model in advance the power consumption data of the conservation measures that skilled engineer in history manually performs in power system and the current consuming apparatus of the power system of correspondence to be analyzed and learn, thus the power consumption data of the current consuming apparatus in current power system and current working type can be inputted in this conservation measures model built in advance, obtain the preferably conservation measures obtained by this model prediction.
It is emphasized that the algorithm itself of decision tree C45 algorithm, NB Algorithm and algorithm of support vector machine is prior art, do not repeat at this.
Further, this utilizes sorting algorithm to build conservation measures model in advance, including:
Utilizing sorting algorithm to build the disaggregated model of the conservation measures corresponding to the disaggregated model of current consuming apparatus in the disaggregated model of history operating mode type, history operating mode type and current consuming apparatus, wherein, this power system includes at least two current consuming apparatus；
Create the first mapping relations table of the disaggregated model of the disaggregated model current consuming apparatus corresponding with it of history operating mode type, and the second mapping relations table of the disaggregated model of the disaggregated model of current consuming apparatus and conservation measures, wherein, the disaggregated model of this current consuming apparatus includes the history power consumption data corresponding to current consuming apparatus；
According to default pretreatment mode, this history power consumption data is carried out pretreatment, to obtain pretreated history power consumption data；
Based on the disaggregated model of the disaggregated model of history operating mode type, the disaggregated model of current consuming apparatus and conservation measures, and the first mapping relations table, the second mapping relations table and pretreated history power consumption data build conservation measures and use model.
It is understandable that, in this kind of implementation, can set up according to the mapping relations table between disaggregated model and disaggregated model and build conservation measures model in advance, the corresponding classification of history operating mode type, the corresponding classification of each current consuming apparatus in history operating mode type, the corresponding classification of conservation measures corresponding to each current consuming apparatus, finally can corresponding at least one conservation measures according to the mapping relations between classification with classification.
Below by Fig. 3, a kind of conservation measures model utilizing decision tree C45 algorithm to build in advance is illustrated.
nullAs shown in Figure 3，This power system includes server、Luminaire and three kinds of current consuming apparatus of pressure fan，According to decision tree C45 sorting algorithm by history operating mode type，Current consuming apparatus type and conservation measures are as classification，By history operating mode type，Current consuming apparatus type and conservation measures are arranged at node location，And conservation measures can only be arranged on leaf node position，Diverging paths represents mapping relations，This guarantees by time in power consumption data input corresponding with current consuming apparatus for current working type to this decision tree，Can predict and obtain at least one conservation measures，Thus reducing user to adopt the threshold of preferably conservation measures，Wherein，In Fig. 3 judge magnitude relationship be more than or equal to or in-less-than symbol before all difference of asking as current consuming apparatus history power consumption data and current power consumption data take absolute value corresponding numerical value，This inequality constitutes the mapping relations in diverging paths.
Specifically, current working type is mated with history operating mode type, learn that current working type belongs to operating mode Class1, now the absolute value of the server power consumption data under current working type with the difference of the history power consumption data of the server under operating mode Class1 is compared with a °, when this absolute value is be more than or equal to a °, learn that current server is in anomalous operating mode, then now prediction obtains conservation measures 1；When difference is less than a °, judge the power consumption data of luminaire under current working type and the absolute value of the difference of the history power consumption data of the luminaire under the operating mode Class1 magnitude relationship with b °, when this absolute value is be more than or equal to b °, learn that current luminaire is in anomalous operating mode, then now prediction obtains conservation measures 2；When difference is less than b °, judge the power consumption data of pressure fan under current working type and the absolute value of the difference of the history power consumption data of the pressure fan under the operating mode Class1 magnitude relationship with c °, when this absolute value is be more than or equal to c °, learn when pressure fan is in anomalous operating mode, then now prediction obtains conservation measures 3；When difference is less than c °, due to now without other current consuming apparatus, then now with reference to the conservation measures 4 that experienced staff manually performs in that case in history, wherein, this history power consumption data is the correction power consumption data that this current consuming apparatus is performed manually after conservation measures in preset time period, or, the normal power consumption data in preset time period when this current consuming apparatus is not performed manually conservation measures.
Require emphasis, when belonging to operating mode type 2 or operating mode type 3 in current working type, it was predicted that obtain the method for conservation measures with the method for operating mode Class1, do not repeat them here；It addition, power system can include but be not limited to that server, luminaire and three kinds of current consuming apparatus of pressure fan；Additionally, the conservation measures model built in advance includes but are not limited to: conservation measures model as shown in Figure 3.
Wherein, a ° as shown in Figure 3, b ° and c ° can be set according to specific requirement by those skilled in the art, and conservation measures 1 to conservation measures 12 can belong to identical conservation measures, may belong to different conservation measures, and depend on the training data for building this conservation measures model.
Further, this pretreatment mode includes: vacancy value facture and at least one calculated in new determinant method.
It is understandable that, in this kind of implementation, in the training stage of model, vacancy value facture can delete the sample data that there is vacancy value in the history power consumption data corresponding to current consuming apparatus, make the model set up more accurate, it is thus achieved that the conservation measures of prediction more preferably；Training stage at model, can also according to the business of the history power consumption data calculated corresponding to new determinant method two kinds of current consuming apparatus of calculating, and this business can weigh the efficiency level of power system, in certain span, the conservation measures that different efficiency levels is corresponding different, then in the operational phase of model, the judgement to efficiency level can be passed through, it is achieved the prediction to conservation measures.
Further, in embodiments of the present invention, also include:
If judging to be absent from the history operating mode type that the match is successful, then recommend conservation measures based on the history power consumption data in preset time period of the current consuming apparatus in this current consuming apparatus power consumption data in preset time period and the conservation measures model that builds in advance to user.
It is understandable that, in this kind of implementation, if judge to be absent from the history operating mode type that the match is successful, then skip the coupling to history operating mode type, be directly based upon the history power consumption data in preset time period of the current consuming apparatus in this current consuming apparatus power consumption data in preset time period and the conservation measures model that builds in advance and recommend conservation measures to user.
Below by Fig. 4, the another kind of conservation measures model utilizing decision tree C45 algorithm to build in advance is illustrated.
As shown in Figure 4, this power system includes the part classifying in classification as shown in Figure 3, namely all can not the match is successful in current working type and history operating mode type, then mate with the history power consumption data corresponding to current consuming apparatus of the same race either directly through the power consumption data of current consuming apparatus, wherein, when this history power consumption data can be anomalous operating mode the current consuming apparatus of unmodified do not revise history power consumption data, then now as shown in Figure 4 30 ° be in for server and not revise history power consumption data under anomalous operating mode；5 ° are in for luminaire and not to revise history power consumption data under anomalous operating mode；20 ° are in for pressure fan and not to revise history power consumption data under anomalous operating mode.When the power consumption data of the server power consumption in current power system is be more than or equal to 30 °, it was predicted that obtain conservation measures 13；During less than 30 °, the power consumption data of luminaire is judged；When judging that the power consumption data of luminaire is be more than or equal to 5 °, it was predicted that obtain conservation measures 14；During less than 5 °, the power consumption data of pressure fan is judged；When judging that the power consumption data of pressure fan is be more than or equal to 20 °, it was predicted that obtain conservation measures 15；During less than 20 °, it was predicted that obtain conservation measures 16.
It is emphasized that, when building conservation measures model in advance, in order to improve the speed of prediction conservation measures, the history power consumption data to current consuming apparatus of only setting up as shown in Figure 4 is classified and conservation measures classification, and the method simplifying mapping relations is also feasible, wherein, history power consumption data mentioned herein and power consumption data should be understood as data corresponding in preset time period.
Second aspect, corresponding to said method embodiment, the embodiment of the present invention additionally provides a kind of energy conserving system, it is applied to power system, this power system includes current consuming apparatus, as in figure 2 it is shown, this system may include that acquiring unit 201, matching unit 202, conservation measures model construction unit 203, determines unit 204 and judging unit 205；
This acquiring unit 201, for obtaining the current working type of this power system, and obtain the power consumption data in preset time period of the current consuming apparatus under operating mode type in this prior, wherein, this current working type includes at least one condition affecting current consuming apparatus power consumption data；
This matching unit 202, mate for the history operating mode type in conservation measures model that this current working type is built in advance with this conservation measures model construction unit 203, judge whether the history operating mode type that the match is successful, if existing, then judge the magnitude relationship of this power consumption data and this current consuming apparatus corresponding to history operating mode type that the match is successful history power consumption data in preset time period, wherein, this history operating mode type includes the condition of at least one history power consumption data affecting current consuming apparatus；
This determines unit 204, for when judging the absolute value of difference of this power consumption data and this current consuming apparatus corresponding to the history operating mode type that the match is successful history power consumption data in preset time period more than predetermined threshold value, it is determined that this current consuming apparatus is in anomalous operating mode；
This judging unit 205, for when determining that this current consuming apparatus is in anomalous operating mode, utilizing the conservation measures corresponding to this current consuming apparatus corresponding in this history operating mode type that the match is successful that this current consuming apparatus is carried out power-save operation.
nullIn the embodiment of the present invention，Conservation measures model can be built in advance，Namely according to history operating mode type、The conservation measures that history power consumption data and skilled engineer adopt takes out conservation measures recommended models，Realize the conservation measures that under different history operating mode types, current consuming apparatus power consumption data in the normal mode of operation and conservation measures and experienced staff adopted at reply anomalous operating mode and power consumption data is analyzed and learns，And then only need to obtain the power consumption data corresponding to the current working type of power system and current consuming apparatus and can judge under current working type, whether current consuming apparatus is in anomalous operating mode by the conservation measures model built in advance，If judging to be in anomalous operating mode，Then according to conservation measures corresponding to current consuming apparatus under this operating mode type in the conservation measures model that builds in advance, current consuming apparatus is carried out energy-conservation，Skilled engineer can be obtained in history in the conservation measures adopted in this kind of situation and take preferably power-save operation，Provide the Forecasting Methodology of conservation measures，Reduce user and implement the threshold of preferably conservation measures，Improve Consumer's Experience，Thus reducing energy-conservation cost.
Further, the history power consumption data of this current consuming apparatus, including the correction power consumption data that: this current consuming apparatus is performed manually after conservation measures in preset time period, or, the normal power consumption data in preset time period when this current consuming apparatus is not performed manually conservation measures.
Further, this conservation measures model construction unit 203 is used for utilizing sorting algorithm to build conservation measures model in advance, and wherein, this sorting algorithm includes one or more in decision tree C45 algorithm, NB Algorithm and algorithm of support vector machine.
Further, this conservation measures model construction unit 203 includes: disaggregated model builds subelement, mapping relations table creates subelement, pretreatment subelement and conservation measures and uses model construction subelement；
This disaggregated model builds subelement, for utilizing sorting algorithm to build the disaggregated model of the conservation measures corresponding to the disaggregated model of current consuming apparatus in the disaggregated model of history operating mode type, history operating mode type and current consuming apparatus, wherein, this power system includes at least two current consuming apparatus；
This mapping relations table creates subelement, first mapping relations table of the disaggregated model of the current consuming apparatus that disaggregated model for creating history operating mode type is corresponding with it, and the second mapping relations table of the disaggregated model of the disaggregated model of current consuming apparatus and conservation measures, wherein, the disaggregated model of this current consuming apparatus includes the history power consumption data corresponding to current consuming apparatus；
This pretreatment subelement, for carrying out pretreatment according to default pretreatment mode to this history power consumption data, to obtain pretreated history power consumption data；
This conservation measures uses model construction subelement, for the disaggregated model based on the disaggregated model of history operating mode type, the disaggregated model of current consuming apparatus and conservation measures, and the first mapping relations table, the second mapping relations table and pretreated history power consumption data build conservation measures and use model.
Further, described pretreatment mode includes: vacancy value facture and at least one calculated in new determinant method.
Further, in embodiments of the present invention, this matching unit 202 is additionally operable to:
If judging to be absent from the history operating mode type that the match is successful, then recommend conservation measures based on the history power consumption data in preset time period of the current consuming apparatus in described current consuming apparatus power consumption data in preset time period and the conservation measures model that builds in advance to user.
It should be noted that, in this article, the relational terms of such as first and second or the like is used merely to separate an entity or operation with another entity or operating space, and not necessarily requires or imply the relation that there is any this reality between these entities or operation or sequentially.And, term " includes ", " comprising " or its any other variant are intended to comprising of nonexcludability, so that include the process of a series of key element, method, article or equipment not only include those key elements, but also include other key elements being not expressly set out, or also include the key element intrinsic for this process, method, article or equipment.When there is no more restriction, statement " including ... " key element limited, it is not excluded that there is also other identical element in including the process of described key element, method, article or equipment.
Each embodiment in this specification all adopts relevant mode to describe, between each embodiment identical similar part mutually referring to, what each embodiment stressed is the difference with other embodiments.Especially for system embodiment, owing to it is substantially similar to embodiment of the method, so what describe is fairly simple, relevant part illustrates referring to the part of embodiment of the method.
The foregoing is only presently preferred embodiments of the present invention, be not intended to limit protection scope of the present invention.All make within the spirit and principles in the present invention any amendment, equivalent replacement, improvement etc., be all contained in protection scope of the present invention.
Claims (10)
1. a power-economizing method, it is characterised in that be applied to power system, described power system includes current consuming apparatus, and described method includes:
Obtaining the current working type of described power system, and obtain the power consumption data in preset time period of the current consuming apparatus under described current working type, wherein, described current working type includes at least one condition affecting current consuming apparatus power consumption data；
Described current working type is mated with the history operating mode type in the conservation measures model built in advance, judge whether the history operating mode type that the match is successful, if existing, then judge the magnitude relationship of described power consumption data and the described current consuming apparatus corresponding to history operating mode type that the match is successful the history power consumption data in preset time period, wherein, described history operating mode type includes the condition of at least one history power consumption data affecting current consuming apparatus；
When judging the absolute value of difference of described power consumption data and the described current consuming apparatus corresponding to the history operating mode type that the match is successful the history power consumption data in preset time period more than predetermined threshold value, it is determined that described current consuming apparatus is in anomalous operating mode；
When determining that described current consuming apparatus is in anomalous operating mode, utilize the corresponding conservation measures corresponding to described current consuming apparatus in the described history operating mode type that the match is successful that described current consuming apparatus is carried out power-save operation.
2. method according to claim 1, it is characterised in that the history power consumption data of described current consuming apparatus, including:
Described current consuming apparatus is performed manually the correction power consumption data after conservation measures in preset time period, or,
Normal power consumption data in preset time period when described current consuming apparatus is not performed manually conservation measures.
3. the method according to any one of claim 1 or 2, it is characterized in that, utilizing sorting algorithm to build conservation measures model in advance, wherein, described sorting algorithm includes one or more in decision tree C45 algorithm, NB Algorithm and algorithm of support vector machine.
4. method according to claim 3, it is characterised in that described utilize sorting algorithm to build conservation measures model in advance, including:
Utilizing sorting algorithm to build the disaggregated model of the conservation measures corresponding to the disaggregated model of current consuming apparatus in the disaggregated model of history operating mode type, history operating mode type and current consuming apparatus, wherein, described power system includes at least two current consuming apparatus；
Create the first mapping relations table of the disaggregated model of the disaggregated model current consuming apparatus corresponding with it of history operating mode type, and the second mapping relations table of the disaggregated model of the disaggregated model of current consuming apparatus and conservation measures, wherein, the disaggregated model of described current consuming apparatus includes the history power consumption data corresponding to current consuming apparatus；
According to default pretreatment mode, described history power consumption data is carried out pretreatment, to obtain pretreated history power consumption data；
Based on the disaggregated model of the disaggregated model of history operating mode type, the disaggregated model of current consuming apparatus and conservation measures, and the first mapping relations table, the second mapping relations table and pretreated history power consumption data build conservation measures and use model.
5. method according to claim 4, it is characterised in that described pretreatment mode includes: vacancy value facture and at least one calculated in new determinant method.
6. the method according to any one of claim 1 or 2, it is characterised in that also include:
If judging to be absent from the history operating mode type that the match is successful, then recommend conservation measures based on the history power consumption data in preset time period of the current consuming apparatus in described current consuming apparatus power consumption data in preset time period and the conservation measures model that builds in advance to user.
7. an energy conserving system, it is characterised in that be applied to power system, described power system includes current consuming apparatus, and described system includes:
Acquiring unit, for obtaining the current working type of described power system, and obtain the power consumption data in preset time period of the current consuming apparatus under described current working type, wherein, described current working type includes at least one condition affecting current consuming apparatus power consumption data；
Matching unit, mate for the history operating mode type in conservation measures model that described current working type is built in advance with conservation measures model construction unit, judge whether the history operating mode type that the match is successful, if existing, then judge the magnitude relationship of described power consumption data and the described current consuming apparatus corresponding to history operating mode type that the match is successful the history power consumption data in preset time period, wherein, described history operating mode type includes the condition of at least one history power consumption data affecting current consuming apparatus；
Determine unit, for when judging the absolute value of difference of described power consumption data and the described current consuming apparatus corresponding to the history operating mode type that the match is successful the history power consumption data in preset time period more than predetermined threshold value, it is determined that described current consuming apparatus is in anomalous operating mode；
Judging unit, for when determining that described current consuming apparatus is in anomalous operating mode, utilizing the corresponding conservation measures corresponding to described current consuming apparatus in the described history operating mode type that the match is successful that described current consuming apparatus is carried out power-save operation.
8. system according to claim 7, it is characterised in that the history power consumption data of described current consuming apparatus, including:
Described current consuming apparatus is performed manually the correction power consumption data after conservation measures in preset time period, or,
Normal power consumption data in preset time period when described current consuming apparatus is not performed manually conservation measures.
9. the system according to any one of claim 7 or 8, it is characterized in that, described conservation measures model construction unit is used for utilizing sorting algorithm to build conservation measures model in advance, wherein, described sorting algorithm includes one or more in decision tree C45 algorithm, NB Algorithm and algorithm of support vector machine.
10. system according to claim 9, it is characterised in that described conservation measures model construction unit includes:
Disaggregated model builds subelement, for utilizing sorting algorithm to build the disaggregated model of the conservation measures corresponding to the disaggregated model of current consuming apparatus in the disaggregated model of history operating mode type, history operating mode type and current consuming apparatus, wherein, described power system includes at least two current consuming apparatus；
Mapping relations table creates subelement, first mapping relations table of the disaggregated model of the current consuming apparatus that disaggregated model for creating history operating mode type is corresponding with it, and the second mapping relations table of the disaggregated model of the disaggregated model of current consuming apparatus and conservation measures, wherein, the disaggregated model of described current consuming apparatus includes the history power consumption data corresponding to current consuming apparatus；
Pretreatment subelement, for carrying out pretreatment according to default pretreatment mode to described history power consumption data, to obtain pretreated history power consumption data；
Conservation measures uses model construction subelement, for the disaggregated model based on the disaggregated model of history operating mode type, the disaggregated model of current consuming apparatus and conservation measures, and the first mapping relations table, the second mapping relations table and pretreated history power consumption data build conservation measures and use model.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107357673A (en) * | 2017-06-28 | 2017-11-17 | 深圳市金立通信设备有限公司 | A kind of method, terminal and computer-readable recording medium for detecting abnormal power consumption |
| CN109272059A (en) * | 2018-12-04 | 2019-01-25 | 合肥泰禾光电科技股份有限公司 | A kind of dynamic data classification method and device |
| CN112560973A (en) * | 2020-12-22 | 2021-03-26 | 浙江浙大中控信息技术有限公司 | Automatic judgment method for energy-saving equipment applied to energy management system |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101872437A (en) * | 2009-04-27 | 2010-10-27 | 深圳市中电电力技术有限公司 | Energy-saving processing method and system thereof |
| CN102289585A (en) * | 2011-08-15 | 2011-12-21 | 重庆大学 | Real-time monitoring method for energy consumption of public building based on data mining |
| CN103853106A (en) * | 2012-11-28 | 2014-06-11 | 同济大学 | Energy consumption prediction parameter optimization method of building energy supply device |
| CN104091042A (en) * | 2014-06-15 | 2014-10-08 | 西南交通大学 | Operating data-based method for energy conservation diagnosis and energy conservation potential analysis on central air-conditioning system |
| CN104199961A (en) * | 2014-09-19 | 2014-12-10 | 北京建筑技术发展有限责任公司 | Data mining based public building energy consumption monitoring platform data processing method |
| CN104915562A (en) * | 2015-06-11 | 2015-09-16 | 上海新长宁低碳投资管理有限公司 | Building energy efficiency diagnosis method and system |
-
2016
- 2016-02-26 CN CN201610109373.1A patent/CN105759608B/en not_active Expired - Fee Related
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101872437A (en) * | 2009-04-27 | 2010-10-27 | 深圳市中电电力技术有限公司 | Energy-saving processing method and system thereof |
| CN102289585A (en) * | 2011-08-15 | 2011-12-21 | 重庆大学 | Real-time monitoring method for energy consumption of public building based on data mining |
| CN103853106A (en) * | 2012-11-28 | 2014-06-11 | 同济大学 | Energy consumption prediction parameter optimization method of building energy supply device |
| CN104091042A (en) * | 2014-06-15 | 2014-10-08 | 西南交通大学 | Operating data-based method for energy conservation diagnosis and energy conservation potential analysis on central air-conditioning system |
| CN104199961A (en) * | 2014-09-19 | 2014-12-10 | 北京建筑技术发展有限责任公司 | Data mining based public building energy consumption monitoring platform data processing method |
| CN104915562A (en) * | 2015-06-11 | 2015-09-16 | 上海新长宁低碳投资管理有限公司 | Building energy efficiency diagnosis method and system |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107357673A (en) * | 2017-06-28 | 2017-11-17 | 深圳市金立通信设备有限公司 | A kind of method, terminal and computer-readable recording medium for detecting abnormal power consumption |
| CN109272059A (en) * | 2018-12-04 | 2019-01-25 | 合肥泰禾光电科技股份有限公司 | A kind of dynamic data classification method and device |
| CN109272059B (en) * | 2018-12-04 | 2021-05-04 | 合肥泰禾光电科技股份有限公司 | Dynamic data classification method and device |
| CN112560973A (en) * | 2020-12-22 | 2021-03-26 | 浙江浙大中控信息技术有限公司 | Automatic judgment method for energy-saving equipment applied to energy management system |
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