CN106570783A - Customer electricity utilization behavior analysis model based on big data thinking - Google Patents
Customer electricity utilization behavior analysis model based on big data thinking Download PDFInfo
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- CN106570783A CN106570783A CN201610954108.3A CN201610954108A CN106570783A CN 106570783 A CN106570783 A CN 106570783A CN 201610954108 A CN201610954108 A CN 201610954108A CN 106570783 A CN106570783 A CN 106570783A
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Abstract
The invention discloses a customer electricity utilization behavior analysis model based on big data thinking. The association relation of electricity consumption and load change caused by electricity utilization composition, the peak-valley energy utilization rationality, the power factor, the rate of capacity utilization, super-capacity electricity utilization and the environment change of users is analyzed through combination of the industries and the regional background of the users; the electricity utilization analysis result and the reasonable electricity utilization suggestions are pushed to the enterprise users to guide the users to reasonably sign the electricity purchasing and selling contract, select the electricity price policy and arrange the production activities so that the production and energy consumption cost of the users can be reduced and the benefit of the users is enabled to be maximized; meanwhile, the companies can guide and promote the users to perform structural adjustment through price and policy and other measures so as to change the mode of growth; and the users can be guided to sign the electricity purchasing and selling contract, select the electricity price policy, arrange the production activities and perform off-peak electricity consumption so that the production and energy consumption cost of the users can be reduced, the benefit of the users can be maximized and energy saving and consumption reduction can be facilitated.
Description
Technical field
The present invention relates to a kind of customer electricity Analysis model of network behaviors based on big data thinking, belongs to power marketing and intelligently should
Use technical field.
Background technology
China's Eleventh Five-Year Plan outline is proposed, built a resource-conserving and environment-friendly society；Propulsion economic structure is adjusted
It is whole, growth pattern transformation.Base oneself upon enterprise practical, it is ensured that comprehensive development of efficiency services, analysis user's condition of production, load
Situation, A clear guidance client optimization power mode assists to formulate ordered electric scheme, and actively helping, assistance Electricity customers are big
Push into energy-saving and emission-reduction.
Residential electricity consumption data not only have the features such as magnanimity, high frequency, dispersion, and there is relatedness and similar between data
Property.User is excavated and studied to these electricity consumption datas by under cover electricity consumption behavioural habits of user in the electricity consumption data of user
Type, can help electrical network to understand personalization, the differentiated service demand of user, so that the further extended theorem of grid company
Depth and range, provide data supporting for following electric power demand side response policy making.
Power consumption, the electricity charge, electrovalence policy and payment promptness, pay charge way, the time of payment according to resident
Deng the foundation characteristic and electricity consumption behavior analysiss of information analysiss user（Living habit, consumption habit, the electricity charge, electrovalence policy etc.）；Point
Analysis each department city net, the electricity consumption radix of the resident of rural power grids；The electrical equipment rate of resident and electrical equipment service condition are analyzed.
Enterprise customer has a major impact to the marketing achievement and economic benefit of power supply enterprise, and development supplies electricity consumption to enterprise customer
Situation, the investigation of electricity consumption situation, analysis, carry out enterprise customer's marketing service strategy study, carry out the innovation of marketing service, formulate
Measure, takes active action, and with high-quality, comprehensive service, meets the electricity consumption needs of enterprise customer.
According to the affiliated industry of enterprise customer, part throttle characteristics, electricity, electricity charge information, pay charge way, payment frequency, whether purchase
The electricity consumption behavior of the information analysiss enterprises such as electricity, power purchase frequency, and classified；Production capacity, the output value and the production capacity for analyzing enterprise is utilized
Efficiency（With can be with the relation of contract capacity）.
The content of the invention
The technical problem to be solved is, with advanced big data thought, to set up customer electricity behavior analysiss
Model, generates client's rational utilization of electricity recommendation, and guiding client's adjustment electricity consumption behavioural habits reduce electric cost.
To solve above-mentioned technical problem, the present invention provides a kind of customer electricity behavior analysiss mould based on big data thinking
Type, including residential electricity consumption habit analysis model, business electrical habit analysis model and public change electricity consumption habit analysis model；
The residential electricity consumption habit analysis model includes electricity consumption of resident analysis module, resident load specificity analysises module and resident
Electricity consumption behavioural habits analysis module；
The business electrical habit analysis model includes business electrical amount analysis module, business electrical specificity analysises module, enterprise
Electricity consumption model analysiss module and enterprise's rate of capacity utilization analysis module；
The public electricity consumption habit analysis model that becomes includes that Analysis of Electrical Characteristics module is used in public change analysis of electric power consumption module and public change.
Aforesaid electricity consumption of resident analysis module is used for：
Electricity consumption trend analysis：By to regional city net, rural power grids residential customers electricity consumption statistics of variables, analysis different geographical urban and rural residents
Electricity consumption difference, analyzes resident living rule, daily schedule；
Electricity using at the peak time trend analysis：According to resident's peak-trough electricity service condition, the electricity consumption peak valley custom of residential customers is analyzed, with reference to residence
People's time-of-use tariffs policy and resident monthly electricity charge, formulate electricity consumption suggestion；
Season electrical energy consumption analysis：By the analysis to resident's four seasons power consumption, impact of the season to electricity consumption of resident is understood；
Ladder electrical energy consumption analysis：By counting resident's ladder power consumption, with reference to step price policy and the monthly electricity charge, electricity consumption is formulated
Suggestion；
Daily electrical energy consumption analysis：By the accounting for calculating refrigeration electricity consumption, heating electricity consumption and the household electricity of residential customers over the years, analysis
The refrigeration of residential customers, the accounting change of heating electricity consumption, analysis temperature changes the impact relation to refrigeration, heating electricity consumption.
Aforesaid resident load specificity analysises module is used for：Residential electricity consumption load Analysis：According to daily 96 point load of resident
Variation tendency, studies residential electricity consumption behavior, and analysis resident living rule, daily schedule, kinsfolk are constituted and air-conditioning, refrigerator
The service condition of electrical equipment, finds in time customer electricity exception；
The four seasons all electrical energy consumption analyses：According to the daily load data of residential customers, calculate 1 year and press spring, summer, autumn, winter, four seasons
Monday to Sunday average load variation tendency, by average load variation tendency, analysis resident living power utility rule, work and rest
Temporal regularity, house person composition.
Aforesaid residential electricity consumption behavioural habits analysis module is used for social group's electrical energy consumption analysis：By distribution transformer monitoring arrive it is white
My god, night, working day, the electricity statistics on day off, analyze the Regional Distribution and electricity consumption rule of different society colony；
Urban and rural residents' electrical energy consumption analysis：Analysis urban and rural residents festivals or holidays electrical feature, power consumption contrast；Analysis and statistics different regions
The daily schedule rule of urban and rural residents, kinsfolk constitute situation；
The household electricity rule of residential customers, daily schedule rule and kinsfolk's structural analyses：By by the every of residential customers
It per hour power consumption and daily 96 point load tendency clustered, by cluster result analyze residential customers household electricity rule
Rule, daily schedule rule and kinsfolk's structure.
Aforesaid business electrical amount analysis module is used for：Electricity consumption trend analysis：By to corporate client power consumption and use
The analysis of electric amount of increase, understands corporate client in regional trade power consumption proportion and enterprise operation state；
The flat coulometric analyses of peak valley：By the peak to enterprise, paddy, ordinary telegram amount statistics, the electricity consumption peak valley custom of corporate client, knot are analyzed
Close to enterprise's time-of-use tariffs preferential policy and enterprise's monthly electricity charge, formulate electricity consumption suggestion.
Aforesaid business electrical specificity analysises module is used for：
Business electrical load Analysis：The daily 96 point load variation tendency of analysis enterprise, finds in time customer electricity exception；
The four seasons all electrical energy consumption analyses：According to the daily load data of corporate client, calculate 1 year and press spring, summer, autumn, winter, four seasons
Monday to Sunday average load variation tendency, by average load variation tendency, analyze the rule that goes into operation in enterprise's four seasons；
Annual distribution is analyzed：Counted the time that daily maximum, minimum load occurs by enterprise, reflection business electrical load peak
The rule that value, valley occur；
Rate of load condensate is analyzed：Rate of load condensate is the ratio of average load and peak load, and rate of load condensate reflects corporate client power load
Stability, rate of load condensate is more big more stable, and rate of load condensate is low to illustrate that this business electrical load peak valley differs greatly, and needs peak clipping to fill out
Paddy, reduces day part load variations；
Load peak-valley difference is analyzed：By the peak load and the difference of minimum load of corporate client, load peak-valley difference is determined；
Load factor is analyzed：By the actual load and working capacity computational load rate of corporate client, the load factor of corporate client is analyzed,
The corporate client high for permanent load, it is proposed that its increase-volume, while also can in time find that enterprise is super holds phenomenon.
Aforesaid business electrical model analysiss module is used for：Load meteorological effect model analysiss：Analyze each corporate client to use
Electric load is in different time points, the relation affected by different temperatures, setup time, temperature, load threedimensional model, by model point
It is responsive to temperature type or non-responsive to temperature type to separate out current enterprise client；
Festivals or holidays model analysiss：Each corporate client is studied in different year, power consumption and the impact relation of festivals or holidays, electricity consumption is set up
Amount, the two dimensional model of festivals or holidays, by festivals or holidays model analysiss business electrical amount the influence degree of each big festivals or holidays is received.
Aforesaid enterprise's rate of capacity utilization module is referred to, with the current power amount of corporate client and the charge capacity ratio of capacity
With enterprise history maximum charge capacity ratio, the rate of capacity utilization of enterprise is calculated, reflection enterprise practical goes into operation situation and prosperity degree.
The aforesaid public analysis of electric power consumption module that becomes is used for：Electricity consumption trend analysis：By rising to public change power consumption and electricity consumption
The analysis of width, understands and current public become in regional electricity consumption proportion, public become running status and public become all and have electricity consumption visitor under its command
The overall electricity consumption situation at family；
Peak-valley electric energy is analyzed：By the way that to public peak, the paddy electricity statistics of variables for becoming, the public change of research has all Electricity customers and cell under its command
The electricity using at the peak time custom of domain Electricity customers.
Aforesaid public change Analysis of Electrical Characteristics module is used for：Public affairs become analysis of power consumption load：Analysis is public to become daily 96 point load
Variation tendency, finds in time public change multiplexing electric abnormality；
The four seasons all electrical energy consumption analyses：Become daily load data according to public, calculate 1 year and press spring, summer, autumn, winter, the week in four seasons
The average load variation tendency on one to Sunday, by average load variation tendency, the public change of analysis has the four of all Electricity customers under its command
The impact relation of season electricity consumption rule and seasonal variations to power load；
Time power load distributing is analyzed：Counted by the public change time that daily maximum, minimum load occurs, reflection public affairs become electricity consumption and bear
The rule that lotus peak value, valley occur；
Rate of load condensate is analyzed：Rate of load condensate is the ratio of average load and peak load, and rate of load condensate reflects the steady of public change power load
Qualitative, rate of load condensate is more big more stable；
Load peak-valley difference is analyzed：By the public peak load for becoming and the difference of minimum load, load peak-valley difference is determined；
Load factor is analyzed：By the public actual load for becoming and working capacity computational load rate, load factor reflects the capacity profit of public change
With degree, the public rate of load condensate for becoming of analysis, the public change high for permanent load rate, it is proposed that to its increase-volume.
The beneficial effect that the present invention is reached：
The present invention is according to electricity consumptions such as the flat power consumption of enterprise customer's peak valley, contract capacity, part throttle characteristics, payment information, energy consumption levels
Information, sets up user power utilization analysis model；Industry, regional background with reference to belonging to user, analyzes electricity consumption composition, the peak valley of user
Pass is associated with energy reasonability, power factor (PF), the rate of capacity utilization, super electricity consumption, the power consumption that environmental change causes and the load variations held
System, studies a set of enterprise customer's electricity consumption method of assessment, determines the energy-saving potential of user, and the assessment of energy-saving effect；By electricity consumption
Analysis result and rational utilization of electricity suggestion be pushed to enterprise customer, instruct user rationally sign purchase sale of electricity contract, select electrovalence policy,
Production activity schedule, reduces the production of user, uses energy cost, promotes user benefit to maximize；Simultaneously company can pass through price, political affairs
The measures such as plan guiding, propulsion user carry out structural adjustment, and growth pattern transformation, promotion are energy-saving.
Description of the drawings
Fig. 1 is resident's electricity consumption trend analysis curve of the present invention；
Fig. 2 is the residential electricity consumption analysis curve of the present invention；
Fig. 3 is resident's season electrical energy consumption analysis curve of the present invention；
Fig. 4 is resident's ladder electrical energy consumption analysis curve of the present invention；
Fig. 5 is the daily electrical energy consumption analysis curve of resident of the present invention；
Fig. 6 is the residential electricity consumption load Analysis curve of the present invention；
Fig. 7 is the week resident's four seasons electrical energy consumption analysis curve of the present invention；
Fig. 8 is the business electrical trend analysis curve of the present invention；
Fig. 9 is the flat coulometric analyses curve of peak valley of the present invention；
Figure 10 is the business electrical load Analysis curve of the present invention；
Figure 11 is the week enterprise's four seasons electrical energy consumption analysis curve of the present invention；
Figure 12 is enterprise's rate of load condensate analysis curve of the present invention；
Figure 13 is enterprise's load peak-valley difference analysis curve of the present invention；
Figure 14 is enterprise's load factor analysis curve of the present invention；
Figure 15 is enterprise's load meteorological effect model analysiss curve of the present invention；
Figure 16 is enterprise's festivals or holidays model analysiss curve of the present invention；
Figure 17 is the rate of capacity utilization analysis analysis curve of the present invention.
Specific embodiment
Below in conjunction with the accompanying drawings the invention will be further described.Following examples are only used for clearly illustrating the present invention
Technical scheme, and can not be limited the scope of the invention with this.
The present invention is no longer analyzed by traditional classification, using full sample analyses, with big data thinking, based on the whole province
The electricity consumption data of more than 3600 ten thousand Electricity customers, archive information and related electricity price electricity charges policy, by Electricity customers by residential customers,
Corporate client and public change, carry out respectively the analysis of electricity consumption habit.
The customer electricity Analysis model of network behaviors of the present invention, including residential electricity consumption habit analysis model, business electrical habit point
Analysis model and public change electricity consumption habit analysis model, specifically,
Residential electricity consumption habit analysis model is included with lower module：
1-1）Electricity consumption of resident analysis module, function is as follows：
1-1-1）Electricity consumption trend analysis：By to regional city net, rural power grids residential customers electricity consumption statistics of variables, analysis different geographical city
Township's residential electricity consumption difference, analyzes resident living rule, daily schedule etc..Fig. 1 is residential electricity consumption trend analysis result, is suitable for enterprise
And domestic consumer, show the electric quantity curve and equal line of the user in the time period, changeable day curve, all curves, moon curve, figure
Mark switching curve or K lines show.
1-1-2）Electricity using at the peak time trend analysis：According to resident's peak-trough electricity service condition, the electricity consumption peak valley of residential customers is analyzed
Custom, with reference to the resident's time-of-use tariffs policy and resident monthly electricity charge, formulates rational utilization of electricity suggestion, reduces electric cost.Fig. 2 is
Resident's electricity using at the peak time analysis result, shows peak electricity, paddy electricity amount, ordinary telegram amount and the temperature data information in the time period, can be with
The peak-valley electric energy of switching day month year.
1-1-3）Season electrical energy consumption analysis：By the analysis to resident's four seasons power consumption, season is understood to electricity consumption of resident
Affect.Fig. 3 is resident's season electrical energy consumption analysis result, is suitable for domestic consumer, shows the spring, summer, autumn and winter four seasons of the user within the time period
Power consumption data, show two curves of the data of spring, summer, autumn and winter four and summer accounting and winter accounting, it is also possible to post with block diagram
Shape figure and accumulation graph show.
1-1-4）Ladder electrical energy consumption analysis：It is with reference to step price policy and monthly electric by counting resident's ladder power consumption
Take, formulate rational utilization of electricity suggestion, to reach the purpose for saving public resource and rational utilization of electricity.Fig. 4 is resident's ladder electrical energy consumption analysis
As a result, domestic consumer is suitable for, shows that user, in the ladder charge condition of each moon in selected time, can show moon data and annual data,
It is illustrated as showing the ladder power consumption situation in every year in selected time interval during annual data.
1-1-5）Daily electrical energy consumption analysis：By the refrigeration electricity consumption, heating electricity consumption and the household electricity that calculate residential customers over the years
Accounting, analyze residential customers refrigeration, heating electricity consumption accounting change, analysis temperature change to refrigeration, heating electricity consumption shadow
The relation of sound.Fig. 5 is the daily electrical energy consumption analysis result of resident, is suitable for domestic consumer, shows that daily within the time period of user uses telecommunications
Breath, comprising the summary data that electricity consumption is constituted, the day that daily electricity consumption, refrigeration electricity consumption, the data of heating electricity consumption three and curve show
Chang Jun electricity consumption datas.
1-2）Resident load specificity analysises module, function is as follows：
1-2-1）Residential electricity consumption load Analysis：According to the daily 96 point load variation tendency of resident, residential electricity consumption behavior, analysis are studied
Resident living rule, daily schedule, kinsfolk constitute and the electrical equipment such as air-conditioning, refrigerator service condition, client is found in time
Multiplexing electric abnormality.Fig. 6 is residential electricity consumption load Analysis result, is suitable for enterprise customer, shows the load tendency data and curves of user, is added
Plus curve is used to add the curve on selected date to picture, load is called together and surveys the survey of calling together for carrying out current and historical data, temperature tune
Section can carry out single point movement and move integrally to be adjusted to temperature curve, and the prediction load curve refreshed at new temperature,
The changeable display curve of superposition stretching radio box combination is superposition or stretching mode, changes 96 forms for being defaulted as stretching and shows,
Show in 96 forms when being less than or equal to 5 days on the selected date, the then loading curve in the form of daily point during more than 5 days,
Can control whether to show actual load and prediction load by check box.
1-2-2）The four seasons all electrical energy consumption analyses：According to the daily load data of residential customers, calculate 1 year by the spring, the summer, the autumn,
Winter, the average load variation tendency on Monday to the Sunday in four seasons.By week in four seasons power load trend, resident living is analyzed
Electricity consumption rule, daily schedule rule, house person composition etc..Fig. 7 is week resident's four seasons electrical energy consumption analysis result, is suitable for enterprise and uses
Family, shows user in selected spring, summer, autumn and winter in time and the power consumption data and curves of whole year.
1-3）Residential electricity consumption behavioural habits analysis module, function is as follows：
1-3-1）Social group's electrical energy consumption analysis：Daytime, night, working day, the electricity statistics on day off arrived by distribution transformer monitoring,
The Regional Distribution and electricity consumption rule of analysis different society colony.
1-3-2）Urban and rural residents' electrical energy consumption analysis：Analysis urban and rural residents festivals or holidays electrical feature, power consumption contrast；Analysis and system
The daily schedule rule of the urban and rural residents of meter different regions, kinsfolk constitute situation.
1-3-3）The household electricity rule of residential customers, daily schedule rule and kinsfolk's structural analyses：By occupying
Daily power consumption and the daily 96 point load tendency per hour of people client is clustered, and by cluster result the life of residential customers is analyzed
Apply flexibly electric rule, daily schedule rule and kinsfolk's structure.
Business electrical habit analysis model, including with lower module：
2-1）Business electrical amount analysis module, function is as follows：
2-1-1）Electricity consumption trend analysis：By the analysis to corporate client power consumption and electricity consumption amount of increase, understand corporate client and exist
Regional trade power consumption proportion and enterprise operation state.Fig. 8 is business electrical trend analysis result, and showing should in the time period
The electric quantity curve of user and equal line, changeable day curve, all curves, moon curve, right side switches curve with icon or K lines are aobvious
Show, acquiescence shows moon curve.
2-1-2）The flat coulometric analyses of peak valley：By the peak to enterprise, paddy, ordinary telegram amount statistics, the electricity consumption of corporate client is analyzed
Peak valley is accustomed to, and with reference to rational utilization of electricity suggestion to enterprise's time-of-use tariffs preferential policy and enterprise's monthly electricity charge, is formulated, optimizes enterprise
Electricity consumption is arranged.Fig. 9 is peak valley ordinary telegram amount analysis result, is suitable for enterprise and domestic consumer, shows peak electricity, paddy electricity in the time period
Amount, ordinary telegram amount and temperature data information, the peak-valley electric energy of changeable day month year is shown with block diagram, accumulation graph, graphical format
Show.
2-2）Business electrical specificity analysises module, function is as follows：
2-2-1）Business electrical load Analysis：The daily 96 point load variation tendency of analysis enterprise, finds in time customer electricity exception.
Can carry out Real-time Load and call survey together by the negative control relevant interface with extraction system, current power load condition is grasped in time.Figure 10 is
Enterprise's load curve, load curve shows the actual load of user's following period of time and prediction load tendency.
2-2-2）The four seasons all electrical energy consumption analyses：According to the daily load data of corporate client, calculate 1 year by the spring, the summer, the autumn,
Winter, the average load variation tendency on Monday to the Sunday in four seasons, by week in four seasons power load trend, analyzes enterprise's four seasons
The rule that goes into operation：
Work hours：The week, Monday to Sunday etc.,
Class's system：Single shift system, three-shift system etc.,
Figure 11 is week enterprise's four seasons electrical energy consumption analysis result, is suitable for enterprise customer, and display user is in selected spring, summer, autumn and winter in time and entirely
The power consumption data and curves in year.
2-2-3）Annual distribution is analyzed：Counted the time that daily maximum, minimum load occurs by enterprise, reflected enterprise
The rule that power load peak value, valley occur.
2-2-4）Rate of load condensate is analyzed：Rate of load condensate is the ratio of average load and peak load, and rate of load condensate reflects enterprise visitor
The stability of family power load, rate of load condensate is more big more stable, and rate of load condensate is low to illustrate that this business electrical load peak valley differs greatly, and needs
Peak load shifting is wanted, reduces day part load variations.Rate of load condensate is improved, the electricity consumption of enterprise can be caused to reach economical rationality.
Daily load rate：Per day load/Daily treatment cost,
Day ratio of minimum load to maximum load：Day minimum load/Daily treatment cost,
Figure 12 is enterprise's rate of load condensate analysis result, is suitable for enterprise customer, shows rate of load condensate information of the user in a period of time.Can open up
Show day, the moon, season, annual data, whether controlling curve shows.Day：Daily load rate, day ratio of minimum load to maximum load, daily load utilization rate, day are born
Lotus stability bandwidth；Month：Monthly load factor, moon ratio of minimum load to maximum load, monthly average daily load rate, moon load utilization rate；Season：Season rate of load condensate, season
Ratio of minimum load to maximum load, season average daily load rate, season load utilization rate；Year：Yearly load factor, year ratio of minimum load to maximum load, annual daily load
Rate, annual monthly load factor, year load utilization rate.
2-2-5）Load peak-valley difference is analyzed：By the peak load and the difference of minimum load of corporate client, load peak is determined
Paddy is poor.Can be enterprise's adjustment power load, peak load shifting, using electricity wisely, there is provided data supporting by analysis load peak-valley difference.
Figure 13 is enterprise's load peak-valley difference analysis result, is suitable for enterprise customer, shows peak-valley difference information of the user within a period of time.Can
Show day, the moon, annual data, whether controllable curve shows.Day：Day peak-valley difference, day peak-valley ratio；Month：Month maximum peak-valley difference, the moon
Average peak-valley difference, moon maximum peak-valley ratio, monthly average day peak-valley ratio；Year：Year maximum peak-valley difference, annual day peak-valley difference, year
Maximum peak-valley ratio, annual day peak-valley ratio.
2-2-6）Load factor is analyzed：By the actual load and working capacity computational load rate of corporate client, load factor reflection
The capacity producing level of enterprise.The load factor of analysis corporate client, the corporate client high for permanent load, electric company can
Advise its increase-volume, while also can in time find that enterprise is super holds phenomenon.Figure 14 is enterprise's load factor analysis result, is suitable for enterprise and uses
Family, shows load factor information of the user within a period of time, shows rate of load condensate, peak load and super appearance data, may control whether
Show working capacity data.
2-3）Business electrical model analysiss module, function is as follows：
2-3-1）Load meteorological effect model analysiss：Each corporate client power load is analyzed in different time points, by different temperatures
The relation of impact, setup time, temperature, load threedimensional model.It is that temperature is sensitive that can analyze current enterprise client by model
Type or non-responsive to temperature type.Figure 15 is enterprise's load meteorological effect modal analysis results, is suitable for enterprise and domestic consumer, shows institute
Selecting the temperature in time and area affects relation.
2-3-2）Festivals or holidays model analysiss：Each corporate client is studied in different year, power consumption is closed with the impact of festivals or holidays
System, sets up the two dimensional model of power consumption, festivals or holidays.Shadow of the business electrical amount by each big festivals or holidays can be analyzed by festivals or holidays model
The degree of sound.Figure 16 is enterprise's festivals or holidays model, is suitable for enterprise and domestic consumer, shows each festivals or holidays in selected time and area
Electricity consumption contributive rate.
2-4）Enterprise's rate of capacity utilization module, with the charge capacity ratio and enterprise of the current power amount of corporate client and capacity
History maximum charge capacity ratio, calculates the rate of capacity utilization of enterprise.Enterprise's rate of capacity utilization is that enterprise's production goes into operation the one of situation
Kind of index, can reflect that enterprise practical goes into operation situation and prosperity degree.Figure 17 is rate of capacity utilization analysis, is suitable for enterprise customer,
Rate of capacity utilization information of the user within a period of time is shown, the rate of capacity utilization information in day, the moon, season, year can be shown.Capacity school
To showing original working capacity, user's rate of capacity utilization and adjustment three curves of capacity.Capacity curve is wherein adjusted to enter
The redjustment and modification of row curve point.
Enterprise's rate of capacity utilization=charge capacity ratio/history maximum charge capacity ratio.
Public affairs become electricity consumption habit analysis model, including with lower module：
3-1）Public affairs become analysis of electric power consumption module, and function is as follows：
3-1-1）Electricity consumption trend analysis：Become in area by the public analysis for becoming power consumption and electricity consumption amount of increase, understanding current public affairs
Proportion, public change running status and all overall electricity consumption situations for having Electricity customers under its command of public change in electricity consumption.
3-1-2）Peak-valley electric energy is analyzed：By the way that to public peak, the paddy electricity statistics of variables for becoming, the public change of research has all electricity consumption visitors under its command
The electricity using at the peak time custom of family and zonule Electricity customers.
3-2）Public affairs become uses Analysis of Electrical Characteristics module, and function is as follows：
3-2-1）Public affairs become analysis of power consumption load：Analysis is public to become daily 96 point load variation tendency, and discovery in time is public to become multiplexing electric abnormality.
By the negative control relevant interface with extraction system, carry out Real-time Load and call survey together, current power load condition is grasped in time.
3-2-2）The four seasons all electrical energy consumption analyses：Become daily load data according to public, calculate 1 year and press spring, summer, autumn, winter, four
The average load variation tendency on the Monday in individual season to Sunday, by week in four seasons power load trend, can analyze public change and have institute under its command
There is the impact relation of the four seasons electricity consumption rule and seasonal variations of Electricity customers to power load.
3-2-3）Time power load distributing is analyzed：Counted by the public change time that daily maximum, minimum load occurs, reflected
Public affairs become the rule that power load peak value, valley occur.
3-2-4）Rate of load condensate is analyzed：Rate of load condensate is the ratio of average load and peak load, and rate of load condensate reflects that public change is used
The stability of electric load, rate of load condensate is more big more stable.
Daily load rate：Per day load/Daily treatment cost,
Day ratio of minimum load to maximum load：Day minimum load/Daily treatment cost.
3-2-5）Load peak-valley difference is analyzed：By the public peak load for becoming and the difference of minimum load, load peak-valley difference is determined.
3-2-6）Load factor is analyzed：By the public actual load for becoming and working capacity computational load rate, load factor reflects public affairs
The capacity producing level of change.The public rate of load condensate for becoming of analysis, the public change high for permanent load rate, can advise to its increase-volume.
The above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, on the premise of without departing from the technology of the present invention principle, some improvement and deformation can also be made, these improve and deform
Also should be regarded as protection scope of the present invention.
Claims (10)
1. a kind of customer electricity Analysis model of network behaviors based on big data thinking, it is characterised in that including residential electricity consumption habit point
Analysis model, business electrical habit analysis model and public change electricity consumption habit analysis model；
The residential electricity consumption habit analysis model includes electricity consumption of resident analysis module, resident load specificity analysises module and resident
Electricity consumption behavioural habits analysis module；
The business electrical habit analysis model includes business electrical amount analysis module, business electrical specificity analysises module, enterprise
Electricity consumption model analysiss module and enterprise's rate of capacity utilization analysis module；
The public electricity consumption habit analysis model that becomes includes that Analysis of Electrical Characteristics module is used in public change analysis of electric power consumption module and public change.
2. a kind of customer electricity Analysis model of network behaviors based on big data thinking according to claim 1, it is characterised in that
The electricity consumption of resident analysis module is used for：
Electricity consumption trend analysis：By to regional city net, rural power grids residential customers electricity consumption statistics of variables, analysis different geographical urban and rural residents
Electricity consumption difference, analyzes resident living rule, daily schedule；
Electricity using at the peak time trend analysis：According to resident's peak-trough electricity service condition, the electricity consumption peak valley custom of residential customers is analyzed, with reference to residence
People's time-of-use tariffs policy and resident monthly electricity charge, formulate electricity consumption suggestion；
Season electrical energy consumption analysis：By the analysis to resident's four seasons power consumption, impact of the season to electricity consumption of resident is understood；
Ladder electrical energy consumption analysis：By counting resident's ladder power consumption, with reference to step price policy and the monthly electricity charge, electricity consumption is formulated
Suggestion；
Daily electrical energy consumption analysis：By the accounting for calculating refrigeration electricity consumption, heating electricity consumption and the household electricity of residential customers over the years, analysis
The refrigeration of residential customers, the accounting change of heating electricity consumption, analysis temperature changes the impact relation to refrigeration, heating electricity consumption.
3. a kind of customer electricity Analysis model of network behaviors based on big data thinking according to claim 1, it is characterised in that
The resident load specificity analysises module is used for：Residential electricity consumption load Analysis：According to the daily 96 point load variation tendency of resident, grind
Study carefully residential electricity consumption behavior, analysis resident living rule, daily schedule, kinsfolk are constituted and air-conditioning, the use of refrigerator electrical equipment
Situation, finds in time customer electricity exception；
The four seasons all electrical energy consumption analyses：According to the daily load data of residential customers, calculate 1 year and press spring, summer, autumn, winter, four seasons
Monday to Sunday average load variation tendency, by average load variation tendency, analysis resident living power utility rule, work and rest
Temporal regularity, house person composition.
4. a kind of customer electricity Analysis model of network behaviors based on big data thinking according to claim 1, it is characterised in that
The residential electricity consumption behavioural habits analysis module is used for social group's electrical energy consumption analysis：Daytime, night, the work arrived by distribution transformer monitoring
Make the electricity statistics on day, day off, analyze the Regional Distribution and electricity consumption rule of different society colony；
Urban and rural residents' electrical energy consumption analysis：Analysis urban and rural residents festivals or holidays electrical feature, power consumption contrast；Analysis and statistics different regions
The daily schedule rule of urban and rural residents, kinsfolk constitute situation；
The household electricity rule of residential customers, daily schedule rule and kinsfolk's structural analyses：By by the every of residential customers
It per hour power consumption and daily 96 point load tendency clustered, by cluster result analyze residential customers household electricity rule
Rule, daily schedule rule and kinsfolk's structure.
5. a kind of customer electricity Analysis model of network behaviors based on big data thinking according to claim 1, it is characterised in that
The business electrical amount analysis module is used for：Electricity consumption trend analysis：By dividing corporate client power consumption and electricity consumption amount of increase
Analysis, understands corporate client in regional trade power consumption proportion and enterprise operation state；
The flat coulometric analyses of peak valley：By the peak to enterprise, paddy, ordinary telegram amount statistics, the electricity consumption peak valley custom of corporate client, knot are analyzed
Close to enterprise's time-of-use tariffs preferential policy and enterprise's monthly electricity charge, formulate electricity consumption suggestion.
6. a kind of customer electricity Analysis model of network behaviors based on big data thinking according to claim 1, it is characterised in that
The business electrical specificity analysises module is used for：
Business electrical load Analysis：The daily 96 point load variation tendency of analysis enterprise, finds in time customer electricity exception；
The four seasons all electrical energy consumption analyses：According to the daily load data of corporate client, calculate 1 year and press spring, summer, autumn, winter, four seasons
Monday to Sunday average load variation tendency, by average load variation tendency, analyze the rule that goes into operation in enterprise's four seasons；
Annual distribution is analyzed：Counted the time that daily maximum, minimum load occurs by enterprise, reflection business electrical load peak
The rule that value, valley occur；
Rate of load condensate is analyzed：Rate of load condensate is the ratio of average load and peak load, and rate of load condensate reflects corporate client power load
Stability, rate of load condensate is more big more stable, and rate of load condensate is low to illustrate that this business electrical load peak valley differs greatly, and needs peak clipping to fill out
Paddy, reduces day part load variations；
Load peak-valley difference is analyzed：By the peak load and the difference of minimum load of corporate client, load peak-valley difference is determined；
Load factor is analyzed：By the actual load and working capacity computational load rate of corporate client, the load factor of corporate client is analyzed,
The corporate client high for permanent load, it is proposed that its increase-volume, while also can in time find that enterprise is super holds phenomenon.
7. a kind of customer electricity Analysis model of network behaviors based on big data thinking according to claim 1, it is characterised in that
The business electrical model analysiss module is used for：Load meteorological effect model analysiss：Each corporate client power load is analyzed not
Same time point, the relation affected by different temperatures, setup time, temperature, load threedimensional model go out current enterprise by model analysiss
Industry client is responsive to temperature type or non-responsive to temperature type；
Festivals or holidays model analysiss：Each corporate client is studied in different year, power consumption and the impact relation of festivals or holidays, electricity consumption is set up
Amount, the two dimensional model of festivals or holidays, by festivals or holidays model analysiss business electrical amount the influence degree of each big festivals or holidays is received.
8. a kind of customer electricity Analysis model of network behaviors based on big data thinking according to claim 1, it is characterised in that
Enterprise's rate of capacity utilization module is referred to, with the current power amount of corporate client and the charge capacity ratio and enterprise's history of capacity
Maximum charge capacity ratio, calculates the rate of capacity utilization of enterprise, and reflection enterprise practical goes into operation situation and prosperity degree.
9. a kind of customer electricity Analysis model of network behaviors based on big data thinking according to claim 1, it is characterised in that
The public analysis of electric power consumption module that becomes is used for：Electricity consumption trend analysis：By the analysis to public change power consumption and electricity consumption amount of increase,
The current public affairs of solution become proportion, public affairs in regional electricity consumption and become running status and all overall electricity consumptions for having Electricity customers under its command of public change
Situation；
Peak-valley electric energy is analyzed：By the way that to public peak, the paddy electricity statistics of variables for becoming, the public change of research has all Electricity customers and cell under its command
The electricity using at the peak time custom of domain Electricity customers.
10. a kind of customer electricity Analysis model of network behaviors based on big data thinking according to claim 1, its feature exists
In the public change Analysis of Electrical Characteristics module is used for：Public affairs become analysis of power consumption load：The daily 96 point load change of the public change of analysis becomes
Gesture, finds in time public change multiplexing electric abnormality；
The four seasons all electrical energy consumption analyses：Become daily load data according to public, calculate 1 year and press spring, summer, autumn, winter, the week in four seasons
The average load variation tendency on one to Sunday, by average load variation tendency, the public change of analysis has the four of all Electricity customers under its command
The impact relation of season electricity consumption rule and seasonal variations to power load；
Time power load distributing is analyzed：Counted by the public change time that daily maximum, minimum load occurs, reflection public affairs become electricity consumption and bear
The rule that lotus peak value, valley occur；
Rate of load condensate is analyzed：Rate of load condensate is the ratio of average load and peak load, and rate of load condensate reflects the steady of public change power load
Qualitative, rate of load condensate is more big more stable；
Load peak-valley difference is analyzed：By the public peak load for becoming and the difference of minimum load, load peak-valley difference is determined；
Load factor is analyzed：By the public actual load for becoming and working capacity computational load rate, load factor reflects the capacity profit of public change
With degree, the public rate of load condensate for becoming of analysis, the public change high for permanent load rate, it is proposed that to its increase-volume.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107292513A (en) * | 2017-06-21 | 2017-10-24 | 国网辽宁省电力有限公司 | A kind of method that power customer management is realized based on svm classifier algorithm |
| CN107622340A (en) * | 2017-08-18 | 2018-01-23 | 广东电网有限责任公司电力调度控制中心 | A kind of motivational techniques and device based on user power utilization data analysis |
| CN108051674A (en) * | 2017-11-27 | 2018-05-18 | 江阴长仪集团有限公司 | Intelligent power quantity monitoring method and intelligent electric meter |
| CN108493946A (en) * | 2018-04-12 | 2018-09-04 | 辽宁石油化工大学 | Electric energy control method, device and equipment based on user power utilization analysis |
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| CN109685552A (en) * | 2018-12-06 | 2019-04-26 | 国网山东省电力公司青岛供电公司 | The analysis of non-intrusion type residential electricity consumption efficiency and method of servicing |
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| CN109064079A (en) * | 2018-10-30 | 2018-12-21 | 国网河南省电力公司经济技术研究院 | The choosing method of electricity needs response baseline calculation method based on load classification |
| CN109685552A (en) * | 2018-12-06 | 2019-04-26 | 国网山东省电力公司青岛供电公司 | The analysis of non-intrusion type residential electricity consumption efficiency and method of servicing |
| CN109636465A (en) * | 2018-12-12 | 2019-04-16 | 国网内蒙古东部电力有限公司通辽供电公司 | A kind of micro-capacitance sensor sale of electricity set meal design method based on the fluctuation of electricity equivalent value |
| CN109816145A (en) * | 2018-12-21 | 2019-05-28 | 国网上海市电力公司 | A kind of supply load management data platform |
| CN110112828A (en) * | 2019-05-20 | 2019-08-09 | 北京恒信铭达科技有限公司 | A kind of green power utilization index number system generates and representation method and publication application system |
| CN110163527A (en) * | 2019-05-31 | 2019-08-23 | 国网上海市电力公司 | A kind of enterprise's energy intellectual analysis management method |
| CN111027741A (en) * | 2019-10-28 | 2020-04-17 | 国网天津市电力公司电力科学研究院 | Method for constructing space-time dimension-oriented generalized load model analysis library |
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