CN104299167A - Energy consumption analysis method for user power data of intelligent energy consumption system - Google Patents
Energy consumption analysis method for user power data of intelligent energy consumption system Download PDFInfo
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- CN104299167A CN104299167A CN201410460859.0A CN201410460859A CN104299167A CN 104299167 A CN104299167 A CN 104299167A CN 201410460859 A CN201410460859 A CN 201410460859A CN 104299167 A CN104299167 A CN 104299167A
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P80/00—Climate change mitigation technologies for sector-wide applications
- Y02P80/10—Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
An energy consumption analysis method for user power data of an intelligent energy consumption system includes the steps of data integration, energy consumption data analysis, electricity statistical calculation, electric energy quality evaluation and the like. The energy consumption analysis method has the advantages that efficient and effective interactive service is provided for users, interaction between a power grid and the users is enhanced, service content is enriched, and the service quality is improved; systematic and integrated energy consumption analysis service is provided, and is of a great guiding significance on improving the level of operation and management on the power grid; an evaluation system and method for reliability of a power distribution network are provided, and a whole set of technical scheme is provided for developing reliability evaluation analysis and planning on a large scale; energy efficiency abnormities can be found in time, and the shortcomings in the operating process of the power grid are found conveniently, and are regulated conveniently in time; the satisfaction rate of the users is increased comprehensively, and the enterprise image and social brand value of power enterprises are improved; the specific subentry energy efficiency condition can be predicted for certain areas, and energy conservation measures are adopted, so that energy conservation and environment protection benefits and direct economic benefits are obtained.
Description
Technical field
The invention belongs to and belong to electric power system data analysis technical field, particularly relate to a kind of energy analysis method of intelligent energy consumption system custom power data.
Background technology
Interactive service portal technology is a new and developing branch in intelligent power grid technology, and object is to explore China intelligent power interaction technique, and setting up one can for the multi-faceted data analysis of dissimilar user, displaying and mutual platform; Wherein the research of the energy analysis method of electric power data is one of key of wherein exploratory development, although also there was the energy analysis of many be correlated with to energy analysis scrappy discussion and analysis, inadequate structure holonomic system in the past.
Summary of the invention
In order to solve the problem, the object of the present invention is to provide a kind of energy analysis method of intelligent energy consumption system custom power data;
In order to achieve the above object, the energy analysis method of intelligent energy consumption system custom power data provided by the invention comprises the following step performed in order:
Step one, Data Integration: Data Integration refers to and utilizes existing cluster now, under the prerequisite ensureing the safe and efficient characteristic of electric power data, each source data is carried out extraction and gathers, in extraction process, also comprise a small amount of statistical computation;
Step 2, with can data analysis: with can data analysis focus on can the analysis and designation of data, comprise the content systematically determining to analyze: determine with energy energy consumption statistic analysis and diagnosis, energy efficiency indexes, follow the tracks of and data intelligence processing;
Step 3, electricity statistical computation: electricity statistical computation comprise electric quantity data by quarter, time, sky, Month And Year calculate, the circuit electric quantity data corresponding to wherein time granularity is divided into again subitem calculating, one-level subitem calculates and secondary subitem calculates, in addition, corresponding time granularity is also had to carry out abnormal coulometric analysis, current/voltage quality analysis;
Step 4, quality of power supply evaluation: the evaluation of the quality of power supply carries out comprehensive evaluation from voltage deviation, voltage fluctuation, voltage flicker, frequency departure, asymmetrical three-phase degree, harmonic wave, power factor, transient overvoltage aspect; After each factor weight of preliminary acquisition, in order to overcome subjectivity, entropy power is adopted to carry out the correction of each factor weight.
In step 2, described data intelligence processing comprises following two aspects:
2.1, missing values process aspect:
The missing values computation model be mainly concerned with comprises: mean value interpolation, similar mean value interpolation, Maximum-likelihood estimation, multiple interpolation;
2.2, data analysis and prediction aspect:
The algoritic module related to has: the correlation rule of the intelligent diagnostics of electricity abnormal data, time-of-use tariffs and electric quantity consumption extracts, the load of electric power.
The effect of the energy analysis method of intelligent energy consumption system custom power data provided by the invention:
1, for user provides efficient effective interaction service, strengthen electrical network and user interaction, enriched service content, improve service quality;
2, the integrated energy analysis service that the system that proposes is complete, provides important directive significance for improving electrical network management level;
3, the assessment system and methodology of distribution network reliability is proposed, for carrying out reliability assessment analysis on a large scale and planning provides a whole set of technical scheme;
4, can Timeliness coverage efficiency abnormal, be convenient to the weak point finding to exist in network operation, be convenient to be adjusted in time;
5, run real time status in conjunction with current modern computer basis, data mining technology, mass data processing technology and power system computation and analytical technology to the whole network to have carried out comparatively systematically analyzing, accelerating power grid construction and transformation provides effective technical support, is once significant exploration to the interactive technology of intelligent grid;
6, the General Promotion satisfaction rate of user, promotes the corporate image of electric power enterprise and social brand value;
7, specifically can to itemize efficiency situation for certain region of prediction, take conservation measures to obtain energy conservation and environmental protection benefit and direct economic benefit, thus carry out relevant decision-making or provide theories integration for formulating correlation principle.
Accompanying drawing explanation
The electric power data statistical framework figure adopted in the energy analysis method of Fig. 1 for intelligent energy consumption system custom power data provided by the invention.
Fig. 2 is that overall power data statistic analysis flow process is always schemed.
Embodiment
Be described in detail below in conjunction with the energy analysis method of the drawings and specific embodiments to intelligent energy consumption system custom power data provided by the invention.
The energy analysis method of intelligent energy consumption system custom power data provided by the invention comprises the following step performed in order:
Step one, Data Integration: Data Integration refers to and utilizes existing cluster now, in the safe and efficient characteristic of guarantee electric power data, each source data is carried out extraction and gathers, in extraction process, also comprise a small amount of statistical computation;
Step 2, with can data analysis: with can data analysis focus on can the analysis and designation of data, comprise the content systematically determining to analyze: determine with energy energy consumption statistic analysis and diagnosis, energy efficiency indexes, follow the tracks of and data intelligence processing etc.;
Step 3, electricity statistical computation: electricity statistical computation comprise electric quantity data by quarter, time, sky, Month And Year calculate, the circuit electric quantity data corresponding to wherein time granularity is divided into again subitem calculating, one-level subitem calculates and secondary subitem calculates, in addition, corresponding time granularity is also had to carry out the quality analyses etc. such as abnormal coulometric analysis, current/voltage; Calculated amount is huge, in order to improve mass data statistical efficiency, has used existing Clustering to improve load balancing, by design execution script, Grade data calculation, timing extraction and calculating etc. is reduced to the amount of repetition of calculating, reaches and raise the efficiency;
Step 4, quality of power supply evaluation: the evaluation of the quality of power supply carries out comprehensive evaluation from voltage deviation, voltage fluctuation, voltage flicker, frequency departure, asymmetrical three-phase degree, harmonic wave, power factor, transient overvoltage aspect; After each factor weight of preliminary acquisition, in order to overcome subjectivity, entropy power is adopted to carry out the correction of each factor weight.
In step 2, described data intelligence processing comprises following two aspects:
2.1, missing values process aspect:
In order to make up the disappearance of electric quantity data acquisition, many algorithms model can be adopted to process, calculate according to the J curve effectJ selecting to produce and eigenwert, can be assessed by the effect of professional to algorithm thus choose the specific missing values computation model being applicable to current time section; The missing values computation model be mainly concerned with comprises: mean value interpolation, similar mean value interpolation, Maximum-likelihood estimation, multiple interpolation;
2.2, data analysis and prediction aspect:
Under the condition ensureing electric power data completeness, data analysis algorithm uses in a kind of occasion, may when replacing construction data, and significant data analysis algorithm changes to some extent; In order to greatly utilize current data to carry out the trial of several data analysis, to play the dirigibility of data mining; Data analysis module designs multiple back-up algorithm storehouse, can carry out exploratory data mining by artificial triggering; In exploration pattern, choose data analysis algorithm process selected data, produce data results; According to artificial experience, mining model is selected, through multiple professional and the selection of a period of time marking, marking statistics can be carried out to data analysis algorithm, produce form, for reference; Can choose the high algorithm of marking moves on in conventional algorithm storehouse, can be used for carrying out routine data excavation at normal mode; The algoritic module related to has: the correlation rule of the intelligent diagnostics of electricity abnormal data, time-of-use tariffs and electric quantity consumption extracts, the load of electric power.
Fig. 1 shows the electric power data statistical framework figure of this method, and Fig. 2 shows overall power data statistic analysis flow process always to scheme.
In step 2, the enforcement object of described energy analysis:
In the development of intelligent grid, the energy analysis for the comprehensive system of electric power data is one and currently there is no the actual work carrying out experience, is also the one exploration of interactive service to attempt intelligence; Energy analysis design effort can from multi-angle, the current urgent degree to the interactive demand of electrical network and power grid maintenance Energy-saving reformation demand of many scenes reflection, energy data can be used by analyzing user, diagnostic analysis user efficiency level, for user provide with can strategy, with can the diversified technology such as aid decision making, finally realize the popularization of power-saving technology in terminal user and use;
The implementation method of energy analysis:
1) Data acquisition, arranges
The energy analysis method relate to current power system and content are investigated and collect, and arrange out current energy analysis method present situation;
2) current intelligent grid demand is studied
According to development condition and the interactive Service and Construction target of national intelligent grid construction situation, determine energy analysis integration objective;
3) correlation technique is investigated
Relate to relevant technology to energy analysis method to investigate, by determining the feasibility of the current integrated technology that will realize to the research of the state of the art;
4) binding analysis
In conjunction with Current hardware, software, the state of the art, estimate the economic and social benefits brought, systematization research energy analysis, realizes target;
Energy analysis implementation result
1) clear and definite energy analysis target and content, for next step intelligent energy analysis provides support;
2) according to present situation and the new technology Integrated research of current techniques, for intelligent grid construction from now on provides technological guidance;
3) according to current energy-saving analysis and Economic and Efficiency Analysis, corresponding rationally effective conservation measures and long-range energy conservation program is formulated.
In step 3, described mass data statistical calculation, has used existing Clustering; The implementation goal of electric power data mass data processing:
The data analysis of any system designs the support energetically of all requirement technology and base layer data, therefore need to analyze according to existing mass data technology and Data Integration present situation, support energy analysis, this energy analysis is made to have good performance and efficiency, to be supplied to the service quality of user's quickness and high efficiency;
The implementation method of electric power data mass data processing:
1) Data Integration present studies
According to actual electric power data acquisition distribution situation, trade-off analysis is carried out with reference to the research of current data integrated scheme to the source of data source, access frequency and data volume size, understand planning current data integrated scheme;
2) data-base cluster technical research
Current database Clustering is studied, according to available data process and analytical technology determination data-base cluster framework, improves Data Analysis Services performance;
3) mass data analysis and processing method is determined
Data analysis subitem is divided, data-analysis time granularity is divided, according to treatment scheme optimization data treatment effeciency, improve Data Analysis Services speed;
4) design program
According to above technology and Data Analysis Services optimal design, timer is set in a database, and compile script completes magnanimity electric power data analyzing and processing;
The implementation result of electric power data mass data processing:
1) characteristic of clear and definite electric power data data analysis granularity, for lifting and optimization data process provide guidance further from now on;
2) in Data Integration and Clustering research, the effectively power grid data integration of economy and arrangement is selected;
3) raising in electric power data energy analysis is incorporated into further to the present computer technology, data mining technology and can provides technology place mat by service interaction;
4) specify that the conditions such as software and hardware configuration, and in conjunction with future plan, can calculate systematization power analysis cost of serving and benefit.
Claims (2)
1. an energy analysis method for intelligent energy consumption system custom power data, is characterized in that: the energy analysis method of described intelligent energy consumption system custom power data comprises the following step performed in order:
Step one, Data Integration: Data Integration refers to and utilizes existing cluster now, under the prerequisite ensureing the safe and efficient characteristic of electric power data, each source data is carried out extraction and gathers, in extraction process, also comprise a small amount of statistical computation;
Step 2, with can data analysis: with can data analysis focus on can the analysis and designation of data, comprise the content systematically determining to analyze: determine with energy energy consumption statistic analysis and diagnosis, energy efficiency indexes, follow the tracks of and data intelligence processing;
Step 3, electricity statistical computation: electricity statistical computation comprise electric quantity data by quarter, time, sky, Month And Year calculate, the circuit electric quantity data corresponding to wherein time granularity is divided into again subitem calculating, one-level subitem calculates and secondary subitem calculates, in addition, corresponding time granularity is also had to carry out abnormal coulometric analysis, current/voltage quality analysis;
Step 4, quality of power supply evaluation: the evaluation of the quality of power supply carries out comprehensive evaluation from voltage deviation, voltage fluctuation, voltage flicker, frequency departure, asymmetrical three-phase degree, harmonic wave, power factor, transient overvoltage aspect; After each factor weight of preliminary acquisition, in order to overcome subjectivity, entropy power is adopted to carry out the correction of each factor weight.
2. the energy analysis method of intelligent energy consumption system custom power data according to claim 1, is characterized in that: in step 2, and described data intelligence processing comprises following two aspects:
2.1, missing values process aspect:
The missing values computation model be mainly concerned with comprises: mean value interpolation, similar mean value interpolation, Maximum-likelihood estimation, multiple interpolation;
2.2, data analysis and prediction aspect:
The algoritic module related to has: the correlation rule of the intelligent diagnostics of electricity abnormal data, time-of-use tariffs and electric quantity consumption extracts, the load of electric power.
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| CN104865549A (en) * | 2015-04-23 | 2015-08-26 | 国网上海市电力公司 | Reliability evaluation method and system of electric energy metering device |
| CN104867059A (en) * | 2015-05-27 | 2015-08-26 | 南京国云电力有限公司 | Power load distribution analysis method |
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| CN107122549A (en) * | 2017-04-28 | 2017-09-01 | 重庆长安汽车股份有限公司 | A kind of analysis method of Automobile Welding workshop energy consumption |
| CN108537407A (en) * | 2018-03-12 | 2018-09-14 | 广东电网有限责任公司中山供电局 | A kind of multisystem data integration processing system |
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