CN104950192A - Compressed-sensing power-utilization energy efficiency monitoring method - Google Patents
Compressed-sensing power-utilization energy efficiency monitoring method Download PDFInfo
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- CN104950192A CN104950192A CN201410123311.7A CN201410123311A CN104950192A CN 104950192 A CN104950192 A CN 104950192A CN 201410123311 A CN201410123311 A CN 201410123311A CN 104950192 A CN104950192 A CN 104950192A
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Abstract
The invention discloses a compressed-sensing wireless sensor network power-utilization energy efficiency monitoring method in the technical field of power-utilization energy efficiency monitoring. The method comprises the steps: carrying out the collection of power-utilization energy efficiency data through a concentrator; building a compressed-sensing power-utilization energy efficiency monitoring data aggregate model, wherein the concentrator and an energy efficiency monitoring main station are respectively used for data compressed-sensing sparse operation and reconstruction operation; and carrying out power-utilization energy efficiency monitoring analysis according to the compressed-sensing reconstruction data. The method provided by the invention can effectively reduce the network power-utilization energy efficiency monitoring uplink transmission data volume, and guarantees the stable and reliable operation of a system.
Description
Technical field
The present invention relates to electricity consumption energy efficiency monitoring technical field, especially pay close attention to the compressed sensing electricity consumption energy efficiency monitoring method being total to platform with power information collection.
Background technology
Electricity consumption energy efficiency monitoring refers to guarantees power grid operation by analyzing user side electricity consumption trend and power network fluctuation, and improving electrical network efficiency, is the powerful guarantee to customer power supply reliability, the good quality of power supply and operation of power networks economic validity.The construction requirements of intelligent grid realizes electrical network Intelligent Service by automatic demand response, meets power consumer multiple demand simultaneously, and builds the novel confession electricity consumption relation of flow of power between electrical network and client, information flow, Business Stream real-time interactive on this basis.Wherein, the electricity consumption efficiency information acquisition system based on intelligent electric meter is intelligent grid informationization, robotization, interactive provide real time data source and technical support.
The real-time interactive business demand of intelligent power brings the problem that the information communication support platform traffic is doubled and redoubled, for electricity consumption efficiency information acquisition system, if gather every day 96 times (namely periodically gathering once every 15 minutes), then will increase the weight of the load of communication network because amount of communication data suddenly increases.Communication network load increase may cause congested, when network congestion can not control in time, will affect telecommunication service quality (QoS:Quality of Service).
Compressed sensing is a kind of effective data compression method, can break through the bottleneck of system in the process of mass data, transmission and storage.Compressive sensing theory is a kind of brand-new mathematical theory, is used widely in a lot of field, and it by observation low volume data, at terminal operating restructing algorithm, can recover data, substantially reduce the number the data volume circulated in a network.
For the problem that data volume in electricity consumption energy effective information energy efficiency monitoring is huge, the present invention proposes a kind of electricity consumption energy efficiency monitoring method based on compressed sensing.The method first concentrator carries out the data acquisition of electricity consumption efficiency; Next sets up the electricity consumption efficiency data aggregate model of compressed sensing, and concentrator and energy efficiency monitoring main website carry out compressed sensing rarefaction operation and the compressed sensing reconstructed operation of data respectively; Last energy efficiency monitoring main website carries out energy efficiency monitoring analysis according to compressed sensing reconstruct data.The method, by the Type division to power information data, adopts compressed sensing structural model data aggregate to electricity consumption energy efficiency monitoring data division, effectively reduces network energy efficiency monitoring uplink transmission data amount, ensures the reliable and stable operation of system.
Summary of the invention
The present invention is intended to propose a kind of electricity consumption energy efficiency monitoring method based on compressed sensing, and its concrete steps are as follows.
Step 1: concentrator electricity consumption efficiency Source Data Acquisition
Its user power utilization efficiency data covering platform district ammeter terminal are collected as electricity consumption energy efficiency monitoring data sources by power concentrator.
Step 2: the electricity consumption efficiency data aggregate structural modeling of compressed sensing
The electricity consumption efficiency data aggregate structural model of compressed sensing is set up between concentrator and energy efficiency monitoring main website, concentrator realizes the Sparse of compressed sensing, energy efficiency monitoring main website realizes the data reconstruction of compressed sensing, realizes compressed sensing process parameter synchronization between concentrator and energy efficiency monitoring main website by message exchange.
Step 3: the compressed sensing Sparseization operation of concentrator
The data aggregate setting up compressed sensing between concentrator and energy efficiency monitoring main website implements framework, and electricity consumption efficiency information data is carried out compressive sensing theory data compression by the concentrator being configured in public distribution transformer platform area, specific as follows: concentrator is by signal
be expressed as public part and unique portion add and:
.The user got under same concentrator adopts the sparse base of identical FFT
, to common component
and endemic element
carry out rarefaction respectively, be expressed as
under Vector Groups
,
, as shown in the formula.
By random Gaussian matrix measuring system complete realize from high (
n) dimension space to low (
m) projection of dimension space, as shown in the formula.
。
Wherein,
for
m×
ncalculation matrix,
for
ndimension matrix,
xfor
mdimension matrix,
n>>M.Thus reduce the required data volume gathered, realize data compression object by Sparse.
Step 4: the compressed sensing data reconstruction operations of energy efficiency monitoring main website
The data aggregate setting up compressed sensing between concentrator and energy efficiency monitoring main website implements framework, the data reconstruction operations of compressed sensing is completed in energy efficiency monitoring main website, specific as follows: the data that energy efficiency monitoring main website uploads according to concentrator, carry out data reconstruction by iterative algorithm: first arrange and need to reconstruct initial value, iteration step length and maximum iteration time; Then estimate first time iterative data, and calculate the target function value of reconstruct data, and upgrade iterations; Recycle the numerical value of the reconstruct numerical value renewal next iteration of first twice, and calculate the target function value of reconstruct; Relatively twice target function value, until this time target function value is less than or equal to previous, and when iterations equals maximum iteration time at present, stops iteration, returns the data of reconstruct, otherwise continue the renewal of previous step.
Step 5: energy efficiency monitoring main website carries out the analysis of electricity consumption energy efficiency monitoring according to compressed sensing reconstruct data
Energy efficiency monitoring main website, by the Real-Time Monitoring to the electricity consumption efficiency information data of reconstruct data, completes the analysis of electrical network electricity consumption energetic efficiency characteristic, and then carries out effective management and running according to current power energy efficiency monitoring situation to electrical network.
In described step 1, concentrator carries out electricity consumption efficiency Source Data Acquisition.
The electricity consumption efficiency data aggregate structural model of compressed sensing is established in described step 2.
In described step 3, concentrator carries out the compressed sensing rarefaction operation of data.
In described step 4, energy efficiency monitoring main website carries out the compressed sensing reconstructed operation of data.
In described step 5, energy efficiency monitoring main website carries out the analysis of electricity consumption energy efficiency monitoring according to compressed sensing reconstruct data.
The electricity consumption energy efficiency monitoring method of the compressed sensing that the present invention proposes effectively can reduce network energy efficiency monitoring uplink transmission data amount, ensures the reliable and stable operation of system.
Accompanying drawing explanation
Fig. 1 is overall flow figure of the present invention.
Fig. 2 is the inventive method compressed sensing paradigmatic structure framework.
Fig. 3 is the inventive method compressed sensing reconstruct data and former Data Comparison curve.
Embodiment
Below in conjunction with accompanying drawing, preferred embodiment is elaborated.It is emphasized that following explanation is only exemplary, instead of in order to limit the scope of the invention and apply.
Example realizes in electric power electricity consumption efficiency data acquisition system (DAS) environment.Parameter sample data is commercial power, user's one day typical electricity consumption data.Compressed sensing ratio of compression is set to 70%.
Fig. 1 is the overall flow figure of the electricity consumption energy efficiency monitoring method that the present invention proposes.According to Fig. 1, method provided by the present invention comprises following implementation step:
Step 1: concentrator electricity consumption efficiency Source Data Acquisition
Its user power utilization efficiency data covering platform district ammeter terminal are collected as electricity consumption energy efficiency monitoring data sources by power concentrator.
Step 2: the electricity consumption efficiency data aggregate structural modeling of compressed sensing
Fig. 2 is the electricity consumption efficiency data aggregate structural model of compressed sensing, concentrator realizes the Sparse of compressed sensing, energy efficiency monitoring main website realizes the data reconstruction of compressed sensing, realizes compressed sensing process parameter synchronization between concentrator and energy efficiency monitoring main website by message exchange.
Step 3: the compressed sensing Sparseization operation of concentrator
The data aggregate setting up compressed sensing between concentrator and energy efficiency monitoring main website implements framework, and electricity consumption efficiency information data is carried out compressive sensing theory data compression by the concentrator being configured in public distribution transformer platform area, specific as follows: concentrator is by signal
be expressed as public part and unique portion add and:
.The user got under same concentrator adopts the sparse base of identical FFT
, to common component
and endemic element
carry out rarefaction respectively, be expressed as
under Vector Groups
,
, as shown in the formula.
By random Gaussian matrix measuring system complete realize from high (
n) dimension space to low (
m) projection of dimension space, as shown in the formula.
。
Wherein,
for
m×
ncalculation matrix,
for
ndimension matrix,
xfor
mdimension matrix,
n>>M.Thus reduce the required data volume gathered, realize data compression object by Sparse.
Step 4: the compressed sensing data reconstruction operations of energy efficiency monitoring main website
The data aggregate setting up compressed sensing between concentrator and energy efficiency monitoring main website implements framework, the data reconstruction operations of compressed sensing is completed in energy efficiency monitoring main website, specific as follows: the data that energy efficiency monitoring main website uploads according to concentrator, carry out data reconstruction by iterative algorithm: first arrange and need to reconstruct initial value, iteration step length and maximum iteration time; Then estimate first time iterative data, and calculate the target function value of reconstruct data, and upgrade iterations; Recycle the numerical value of the reconstruct numerical value renewal next iteration of first twice, and calculate the target function value of reconstruct; Relatively twice target function value, until this time target function value is less than or equal to previous, and when iterations equals maximum iteration time at present, stops iteration, returns the data of reconstruct, otherwise continue the renewal of previous step.
Step 5: energy efficiency monitoring main website carries out the analysis of electricity consumption energy efficiency monitoring according to compressed sensing reconstruct data
Energy efficiency monitoring main website, by the Real-Time Monitoring to the electricity consumption efficiency information data of reconstruct data, completes the analysis of electrical network electricity consumption energetic efficiency characteristic, and then carries out effective management and running according to current power energy efficiency monitoring situation to electrical network.
Step 2: the electricity consumption efficiency data aggregate structural modeling of compressed sensing
Below accompanying drawing of the present invention is described.Fig. 3 is the inventive method compressed sensing reconstruct data and former Data Comparison curve.The average error value compressing the existence compared with former data of sensing reconstructing data as seen from the figure under 70% ratio of compression condition is 4.05%, can meet the tendency observation requirement of electricity consumption energy efficiency monitoring.
In sum, method proposed by the invention, when meeting electricity consumption energy efficiency monitoring data accuracy demand, effectively reduces network energy efficiency monitoring uplink transmission data amount; Pass image data back energy efficiency monitoring main website real-time and efficiently simultaneously, realize electricity consumption energy efficiency monitoring, ensure the reliable and stable operation of system.
The above; be only the present invention's preferably embodiment, but protection scope of the present invention is not limited thereto, is anyly familiar with those skilled in the art in the technical scope that the present invention discloses; the change that can expect easily or replacement, all should be encompassed within protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection domain of claim.
Claims (4)
1. an electricity consumption energy efficiency monitoring method for compressed sensing, it is characterized in that, it comprises the following steps:
Step 1: concentrator electricity consumption efficiency Source Data Acquisition
Step 2: the electricity consumption efficiency data aggregate structural modeling of compressed sensing
Step 3: the compressed sensing Sparseization operation of concentrator
Step 4: the compressed sensing data reconstruction operations of energy efficiency monitoring main website
Step 5: energy efficiency monitoring main website carries out the analysis of electricity consumption energy efficiency monitoring according to compressed sensing reconstruct data
Electricity consumption efficiency data monitoring method according to claim 1, is characterized in that, described step 2 sets up the electricity consumption efficiency polymerization model of compressed sensing, and electricity consumption efficiency information data is carried out the operation of compressed sensing Sparseization by concentrator; Energy efficiency monitoring main website carries out the data reconstruction operations of compressed sensing.
2. electricity consumption efficiency data monitoring method according to claim 1, is characterized in that, described step 3 achieves the Sparseization operation of concentrator compressed sensing, and concentrator is by signal
be expressed as public part and unique portion add and:
, by common component
and endemic element
be expressed as sparse base
under Vector Groups
,
, as shown in the formula.
3. realize the projection from high (N) dimension space to low (M) dimension space by random Gaussian matrix measuring system, as shown in the formula.
4. electricity consumption efficiency data monitoring method according to claim 1, it is characterized in that, described step 4 has carried out the data reconstruction operations of energy efficiency monitoring main website compressed sensing, and the data that energy efficiency monitoring main website uploads according to concentrator carry out data reconstruction to recover data by iterative algorithm.
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Citations (4)
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|---|---|---|---|---|
| CN201378753Y (en) * | 2008-12-12 | 2010-01-06 | 长沙大家网络科技有限责任公司 | Electric power wireless network regional management concentrator |
| US20120203810A1 (en) * | 2011-02-04 | 2012-08-09 | Alexei Ashikhmin | Method And Apparatus For Compressive Sensing With Reduced Compression Complexity |
| CN103280084A (en) * | 2013-04-24 | 2013-09-04 | 中国农业大学 | Data acquisition method for multi-parameter real-time monitoring |
| CN103368578A (en) * | 2013-07-01 | 2013-10-23 | 中国农业大学 | Compressed-sensing-based signal sampling method for distributed wireless sensor network nodes |
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201378753Y (en) * | 2008-12-12 | 2010-01-06 | 长沙大家网络科技有限责任公司 | Electric power wireless network regional management concentrator |
| US20120203810A1 (en) * | 2011-02-04 | 2012-08-09 | Alexei Ashikhmin | Method And Apparatus For Compressive Sensing With Reduced Compression Complexity |
| CN103280084A (en) * | 2013-04-24 | 2013-09-04 | 中国农业大学 | Data acquisition method for multi-parameter real-time monitoring |
| CN103368578A (en) * | 2013-07-01 | 2013-10-23 | 中国农业大学 | Compressed-sensing-based signal sampling method for distributed wireless sensor network nodes |
Non-Patent Citations (3)
| Title |
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| DAVID L. DONOHO: "Compressed Sensing", 《IEEE TRANSACTIONS ON INFORMATION THEORY》 * |
| 李卓凡 等: "压缩感知及应用", 《微计算机应用》 * |
| 董奥: "基于能效监测平台的能源管理与优化", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 * |
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