CN115018311A - Method, system, equipment and medium for multi-dimensional potential depiction evaluation of power industry users - Google Patents

Method, system, equipment and medium for multi-dimensional potential depiction evaluation of power industry users Download PDF

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CN115018311A
CN115018311A CN202210609294.2A CN202210609294A CN115018311A CN 115018311 A CN115018311 A CN 115018311A CN 202210609294 A CN202210609294 A CN 202210609294A CN 115018311 A CN115018311 A CN 115018311A
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韩富佳
史梦洁
王晓辉
李家腾
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Abstract

The invention discloses a method, a system, equipment and a medium for evaluating multidimensional potential portrayal of users in the power industry, wherein the evaluation method comprises the following steps: acquiring power utilization information data of a plurality of power industry users to be subjected to potential description and evaluation within a preset area range; for each power industry user to be potential-portrayed and evaluated, calculating to obtain an evaluation index by utilizing a pre-constructed power industry user multi-dimensional potential-portrayal index system based on the corresponding power utilization information data; and performing scoring evaluation based on all evaluation indexes of all power industry users to be subjected to potential depiction evaluation to obtain an evaluation result. The technical scheme provided by the invention can comprehensively depict the potential of industrial users in a multidimensional way and reasonably and quantitatively evaluate the potential, and is beneficial to realizing the accurate marketing of individuation and differentiation of the electric power data value-added service products.

Description

Method, system, equipment and medium for multi-dimensional potential depiction evaluation of power industry users
Technical Field
The invention belongs to the technical field of electric power big data analysis, and particularly relates to a method, a system, equipment and a medium for evaluating multidimensional potential portrayal of users in the power industry.
Background
With the wide popularization and deployment of intelligent measuring devices and the construction and development of novel power systems, the high-frequency and accurate-acquisition power consumer data becomes a new production element of power grid companies through years of precipitation. Specifically, in recent years, the technology of electric power big data is rapidly developed, and technologies such as extraction and representation of electric power consumption behavior characteristics of mass electric power users, mining of user demands and value potentials and the like have a lot of research and demonstration; meanwhile, the power industry forms diversified data products such as energy efficiency optimization, electric charge optimization, electric power trade package optimization, electric power environmental protection, electric power credit investigation and the like through data value-added service exploration in recent years.
The prior art method is difficult to systematically and comprehensively depict the multidimensional potential of the power industry users, the deep potential depicting index based on the big data analysis technology is lacked, and an objective method is not adopted to reasonably and quantitatively evaluate the multidimensional potential of the power industry users.
Disclosure of Invention
The invention aims to provide a method, a system, equipment and a medium for evaluating multidimensional potential portrayal of users in the power industry so as to solve one or more technical problems. The technical scheme provided by the invention can comprehensively depict the potential of industrial users in a multi-dimensional manner and reasonably and quantitatively evaluate the potential, and is favorable for realizing the precise marketing of individuation and differentiation of the electric power data value-added service product.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention provides a multi-dimensional potential depiction evaluation method for power industry users, which comprises the following steps:
acquiring power utilization information data of a plurality of power industry users to be subjected to potential description and evaluation within a preset area range;
for each power industry user to be potential-portrayed and evaluated, calculating to obtain an evaluation index by utilizing a pre-constructed power industry user multi-dimensional potential-portrayal index system based on the corresponding power utilization information data; the evaluation indexes comprise a capacity-to-electricity-demand charge ratio, a power factor qualification rate, a peak-time electricity consumption ratio, an average daily maximum load, an average demand response potential, an average daily electricity quantity, an enterprise operation rate, an energy consumption development stage, an electricity consumption increase rate, an energy consumption level, an owing risk level, an electricity stealing suspicion level, a heavy overload time ratio, a voltage qualification rate, an average load rate, a load rate fluctuation level, an average power factor, an average three-phase unbalance degree, an electricity abnormal day ratio and an abnormal zero number ratio;
and performing grading evaluation on all evaluation indexes of all power industry users to be subjected to potential characterization evaluation to obtain an evaluation result.
The method of the invention is further improved in that the step of acquiring the power utilization information data of a plurality of power industry users to be potential portrayed and evaluated in the preset area range specifically comprises the following steps:
acquiring power consumption information data of a plurality of power industry users to be potential portrayed and evaluated after abnormal data preprocessing in a preset area range;
the power utilization information data comprise transformer installation capacity, power factors, active power, reactive power, power consumption, payment times, defaulting times, voltage and current.
The method is further improved in that the pre-constructed multi-dimensional potential depiction index system of the power industry users comprises three dimensions of electricity charge optimization potential, operation optimization potential and safe electricity utilization optimization potential;
the electric charge optimization potential includes:
(1) the electricity charge ratio is required to be high,
Figure BDA0003672573170000021
wherein r is the capacity-demand electricity rate, a is the capacity electricity rate, b is the demand electricity rate, C T-plan Reporting capacity, L, for a user transformer max-predict For the future maximum load demand of the user, p c To capacity price, p need The electricity price is the demand;
(2) the qualification rate of the power factor is high,
Figure BDA0003672573170000022
where eta is the power factor yield, n pass Counting the total quantity points of the user power factor within the standard qualified range within a month, n sum Counting the total quantity points of the power factors of the users in the month;
(3) the electricity consumption accounts for the ratio in the peak time,
Figure BDA0003672573170000023
in which beta is the ratio of the peak power consumption, Q peak Is the sum of the peak power consumption per month, Q sum The total monthly electricity consumption;
(4) the average daily maximum load is given to the load,
Figure BDA0003672573170000031
in the formula, L avgmax Is the average daily maximum load, L max I is the maximum load of the ith day in the statistical month, and n is the total days in the statistical month;
(5) the average demand response potential is given to the demand,
Figure BDA0003672573170000032
in the formula, E dr For average demand response potential, DP n Daily power consumption curve l for nth day of user n Total of power consumption in peak hours, TP k Is 1 of n Typical daily electricity consumption curve C of affiliated user k N is the set S ═ N | DP n -TP k More than 0,1 is not less than n and not more than 365;
the business optimization potentials include:
(1) the average daily electricity consumption is calculated,
Figure BDA0003672573170000033
in the formula, Q avg Is the average daily power, Q i Counting the electricity consumption of the ith day in the month, wherein n is the total number of days in the month;
(2) the operation rate of an enterprise is increased,
Figure BDA0003672573170000034
wherein, gamma is the enterprise operating rate, n work Total days of work of the user within one year, n year Total days in a year;
(3) the energy-use development stage is that,
Figure BDA0003672573170000035
wherein R is the increase rate of the ring ratio of the monthly power consumption of the user, Q is the monthly power consumption of the user, and Q avg The average value of the monthly power consumption of the industry;
(4) the rate of increase in the amount of electricity used,
Figure BDA0003672573170000036
wherein λ is the rate of increase of power consumption, W current For the current monthly power consumption, W last The electricity consumption is the electricity consumption in the previous month;
(5) the level of energy consumption is high,
Figure BDA0003672573170000037
wherein α is the energy consumption level, P pro For total energy of the user, Q con The total electricity consumption of the user is calculated;
(6) the level of the risk of an arrears,
Figure BDA0003672573170000041
where δ is the arrearage risk level, n de l ay Number of arrears, n pay The number of times of payment is;
(7) the suspected level of electricity stealing is high,
Figure BDA0003672573170000042
in the formula (I), the compound is shown in the specification,
Figure BDA0003672573170000043
in order to make the electricity stealing suspect level,n abnormal for the number of curves of abnormal daily electricity consumption of the user, n year The total number of curves of daily electricity consumption of a user in one year;
the safety power utilization optimization potential comprises:
(1) the heavy overload time period is a ratio of,
Figure BDA0003672573170000044
where μ is the ratio of the heavy overload duration, N h For counting the number of heavy load measurement points of the user in the month, N o Counting the number of overloaded user points in the month, N total Counting the total number of points in the month;
(2) the yield of the voltage is high,
Figure BDA0003672573170000045
wherein θ is the voltage yield, N pass Counting the number of measurement points of the user voltage in a standard qualified range in a month, wherein N is the total number of measurement points in the month;
(3) the average load rate is the average load rate,
Figure BDA0003672573170000046
in the formula, LR average Is the average load factor, LR i Counting the load rate corresponding to the ith metering point in the month, wherein N is the total quantity point in the month;
(4) the level of the fluctuation of the load factor,
Figure BDA0003672573170000047
where LF is the load factor fluctuation level, LR i To count the load rate, LR, corresponding to the ith metering point in the month average The average load rate in the statistical month is shown, and N is the total quantity point in the statistical month;
(5) the average power factor of the power-supply line,
Figure BDA0003672573170000051
in the formula, F avg Is the average power factor, N is the total number of points in the statistical month, F i The power factor corresponding to the ith metering point;
(6) the degree of unbalance of the three phases is averaged,
Figure BDA0003672573170000052
in the formula I im To average out of balance of three phases, I i,j Phase current of j phase for I-th metering point, I i,average The average phase current of the ith metering point is N, and the number of the total metering points in the statistical month is N;
(7) the number of the days of abnormal electricity consumption accounts for the ratio,
Figure BDA0003672573170000053
in the formula, R abn In terms of abnormal days of electricity consumption, N abn For the number of curves of abnormal daily electricity consumption of the user, N year The total number of curves of daily electricity consumption of a user in one year;
(8) the number of days of an abnormal zero is proportional,
Figure BDA0003672573170000054
in the formula, R zero Number of days of abnormal zero, N zero Number of exceptional zero-value days, N month To account for the total number of days in the month.
The method is further improved in that the evaluation is carried out based on all evaluation indexes of all power industry users to be subjected to potential characterization evaluation, and the step of obtaining the evaluation result specifically comprises the following steps:
for the power industry users to be subjected to potential depiction and evaluation, ranking the users based on each evaluation index to obtain the score of each evaluation index of each power industry user;
and on the basis of the scores of all the evaluation indexes, calculating the weights of different evaluation indexes by adopting an analytic hierarchy process aiming at the electricity charge optimization potential, the business optimization potential and the safety electricity utilization optimization potential, weighting to obtain the comprehensive score of each dimensionality potential, and obtaining an evaluation result.
The invention provides a system for evaluating the multidimensional potential portrayal of users in the power industry, which comprises:
the data acquisition module is used for acquiring power utilization information data of a plurality of power industry users to be potential portrayed and evaluated in a preset area range;
the evaluation index acquisition module is used for calculating and obtaining an evaluation index for each power industry user to be potential-delineated and evaluated by utilizing a pre-constructed power industry user multi-dimensional potential delineation index system based on the corresponding power utilization information data; the evaluation indexes comprise a capacity-to-electricity-demand charge ratio, a power factor qualification rate, a peak-time electricity consumption ratio, an average daily maximum load, an average demand response potential, an average daily electricity quantity, an enterprise operation rate, an energy consumption development stage, an electricity consumption increase rate, an energy consumption level, an owing risk level, an electricity stealing suspicion level, a heavy overload time ratio, a voltage qualification rate, an average load rate, a load rate fluctuation level, an average power factor, an average three-phase unbalance degree, an electricity abnormal day ratio and an abnormal zero number ratio;
and the evaluation result acquisition module is used for carrying out grading evaluation on all evaluation indexes of all power industry users to be subjected to potential description evaluation to obtain an evaluation result.
The system of the present invention is further improved in that the step of acquiring the power consumption information data of a plurality of power industry users to be potential-characterized and evaluated within the preset area specifically includes:
acquiring power consumption information data of a plurality of power industry users to be potential portrayed and evaluated after abnormal data preprocessing in a preset area range;
the power utilization information data comprise transformer installation capacity, power factors, active power, reactive power, power consumption, payment times, defaulting times, voltage and current.
The system is further improved in that the pre-constructed multi-dimensional potential depiction index system for the power industry users comprises three dimensions of electricity charge optimization potential, operation optimization potential and safe electricity utilization optimization potential;
the electric charge optimization potential includes:
(1) the electricity charge ratio is required to be high,
Figure BDA0003672573170000061
wherein r is the capacity-demand electricity rate, a is the capacity electricity rate, b is the demand electricity rate, C T-plan Reporting capacity, L, for a user transformer max-predict For the future maximum load demand of the user, p c To the capacity price, p need The electricity price is the demand;
(2) the qualification rate of the power factor is high,
Figure BDA0003672573170000071
where eta is the power factor yield, n pass Counting the total quantity points of the user power factor within the standard qualified range within a month, n sum Counting the total points of the power factors of the users in the month;
(3) the electricity consumption accounts for the ratio in the peak time,
Figure BDA0003672573170000072
in which beta is the ratio of the peak power consumption, Q peak Is the sum of the power consumption at peak per month, Q sum The total monthly electricity consumption;
(4) the average daily maximum load is given to the load,
Figure BDA0003672573170000073
in the formula, L avgmax Is the average daily maximum load, L max,i Counting the maximum load of the ith day in the month, wherein n is the total number of days in the month;
(5) the average demand response potential is given to the demand,
Figure BDA0003672573170000074
in the formula, E dr For average demand response potential, DP n For the nth day and day electricity consumption of usersQuantity curve l n Total of electricity consumption at peak hours, TP k Is 1 of n Typical daily electricity consumption curve C of affiliated user k N is the set S ═ N | DP n -TP k More than 0,1 is not less than n and not more than 365;
the business optimization potentials include:
(1) the average daily electricity consumption is calculated,
Figure BDA0003672573170000075
in the formula, Q avg Average daily power, Q i Counting the electricity consumption of the ith day in the month, wherein n is the total number of days in the month;
(2) the operation rate of an enterprise is increased,
Figure BDA0003672573170000076
wherein, gamma is the enterprise operating rate, n work Total days of work of the user within one year, n year Total days in a year;
(3) the energy-use stage is the development stage of the energy,
Figure BDA0003672573170000077
wherein R is the increase rate of the ring ratio of the monthly power consumption of the user, Q is the monthly power consumption of the user, and Q avg The average value of the monthly power consumption of the industry;
(4) the rate of increase in the amount of electricity used,
Figure BDA0003672573170000081
wherein λ is the rate of increase of power consumption, W current For the current monthly power consumption, W last The electricity consumption is the electricity consumption in the previous month;
(5) the level of energy consumption is high,
Figure BDA0003672573170000082
wherein α is the energy consumption level, P pro For total energy of the user, Q con Total power consumption for users;
(6) The level of risk of an arrear is,
Figure BDA0003672573170000083
where δ is the arrearage risk level, n delay Number of arrears, n pay The number of times of payment is;
(7) the suspected level of electricity stealing is high,
Figure BDA0003672573170000084
in the formula (I), the compound is shown in the specification,
Figure BDA0003672573170000085
to the suspected level of electricity theft, n abnormal Number of curves for abnormal daily electricity consumption of user, n year The total number of curves of daily electricity consumption of a user in one year;
the safety power utilization optimization potential comprises:
(1) the heavy overload time is a ratio of the time length,
Figure BDA0003672573170000086
where μ is the ratio of the heavy overload duration, N h For counting the number of heavy load measurement points of the user in the month, N o For counting the number of measurement points of overload of users in month, N total Counting the total number of points in the month;
(2) the yield of the voltage is high,
Figure BDA0003672573170000087
wherein θ is the voltage yield, N pass Counting the number of measurement points of the user voltage in a standard qualified range in a month, wherein N is the total number of measurement points in the month;
(3) the average load rate is the average load rate,
Figure BDA0003672573170000088
in the formula, LR average Is the average load factor, LR i Is a systemCalculating the load rate corresponding to the ith measuring point in the month, wherein N is the total number of points in the month;
(4) the level of the fluctuation of the load factor,
Figure BDA0003672573170000091
where LF is the level of load factor fluctuation, LR i To calculate the load rate, LR, corresponding to the ith metering point in the month average The average load rate in the statistical month is shown, and N is the total quantity point in the statistical month;
(5) the average power factor of the power-supply line,
Figure BDA0003672573170000092
in the formula, F avg Is the average power factor, N is the total number of points in the statistical month, F i The power factor corresponding to the ith metering point;
(6) the degree of unbalance of the three phases is averaged,
Figure BDA0003672573170000093
in the formula I im To average out of balance of three phases, I i,j Phase current of j phase for I-th metering point, I i,average The average phase current of the ith metering point is N, and the number of the total metering points in the statistical month is N;
(7) the number of days of abnormal electricity utilization is proportional to the number of days of abnormal electricity utilization,
Figure BDA0003672573170000094
in the formula, R abn In terms of abnormal days of electricity consumption, N abn For the number of curves of abnormal daily electricity consumption of the user, N year The total number of curves of daily electric quantity of a user in one year;
(8) the number of days of an abnormal zero is proportional,
Figure BDA0003672573170000095
in the formula, R zer o is the number of abnormal zero days, N zer o isNumber of exceptional zero-valued days, N month To account for the total number of days in the month.
The system of the invention is further improved in that the evaluation is performed based on all evaluation indexes of all power industry users to be potential-characterization-evaluated, and the step of obtaining the evaluation result specifically comprises:
for the power industry users to be subjected to potential depiction and evaluation, ranking the users based on each evaluation index to obtain the score of each evaluation index of each power industry user;
and on the basis of the scores of all the evaluation indexes, calculating the weights of different evaluation indexes by adopting an analytic hierarchy process aiming at the electricity charge optimization potential, the business optimization potential and the safety electricity utilization optimization potential, weighting to obtain the comprehensive score of each dimensionality potential, and obtaining an evaluation result.
A third aspect of the present invention provides an electronic device, comprising:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform any of the above described methods of evaluating a multi-dimensional potential depiction of a power industry user according to the present invention.
In a fourth aspect of the present invention, a computer-readable storage medium is provided, which stores a computer program, and when the computer program is executed by a processor, the method for evaluating the multidimensional potential characterization of the power industry user according to any one of the above aspects of the present invention is implemented.
Compared with the prior art, the invention has the following beneficial effects:
the technical scheme provided by the invention can systematically and comprehensively depict the multidimensional potential of industrial users and reasonably and quantitatively evaluate the multidimensional potential, and is beneficial to realizing the accurate marketing of individuation and differentiation of the electric power data value-added service products. Specifically, the method provided by the invention comprises the steps of constructing a power industry user multi-dimensional potential depiction index system to finely depict a user portrait, mining deep potential depiction indexes of an industrial user by adopting a big data analysis technology, and further quantitatively evaluating the multi-dimensional potential of the industrial user in a scoring mode, so that the comprehensive evaluation score of each dimension potential of the user is obtained.
The comprehensive score obtained by the method can be used for recommending corresponding data products to the user, guiding the user to rationalize power utilization and improving the power utilization management capability of the user; the method can assist a power grid company to mine the power utilization data value of industrial users, deeply know the power utilization behaviors and requirements of the users, identify high-value industrial users, formulate a differentiated marketing strategy, realize the matching and matching transaction of the data products and the power users, provide targeted data products for different industrial user groups, improve the service quality and marketing benefit, expand the revenue channel of the power grid company, and have great practical application value and popularization prospect for power marketing business.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the description of the prior art are briefly introduced below; it is obvious that the drawings in the following description are some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.
FIG. 1 is a schematic flow chart of a method for multi-dimensional potential characterization evaluation of users in the power industry according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a method for evaluating a multi-dimensional potential depiction of a power industry user according to another embodiment of the present invention;
FIG. 3 is a schematic diagram of an index system for multi-dimensional potential depiction for industrial users in an embodiment of the present invention;
fig. 4 is a schematic flow chart of a power consumer multidimensional potential characterization evaluation system according to still another embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only some embodiments, not all embodiments, of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It is noted that the terms "first," "second," and the like in the description and claims of the present invention and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example one
Referring to fig. 1, a method for evaluating a multi-dimensional potential depiction of a power industry user according to an embodiment of the present invention includes the following steps:
acquiring power utilization information data of a plurality of power industry users to be subjected to potential description and evaluation within a preset area range; the electricity consumption information data specifically includes: the transformer reporting capacity, power factor, active power, reactive power, power consumption, payment times, arrearage times, voltage, current and the like; by way of further explanation, the electricity consumption information data can be obtained from the existing utilization system and marketing system of the power grid company;
for each power industry user to be potential-portrayed and evaluated, calculating to obtain an evaluation index by utilizing a pre-constructed power industry user multi-dimensional potential-portrayal index system based on the corresponding power utilization information data; the evaluation indexes comprise a capacity-to-power-demand charge ratio, a power factor qualification rate, a peak-time power consumption ratio, an average daily maximum load, an average demand response potential, an average daily power, an enterprise operation rate, a power consumption development stage, a power consumption increase rate, an energy consumption level, an arrearage risk level, an electricity stealing suspicion level, a heavy overload duration ratio, a voltage qualification rate, an average load rate, a load rate fluctuation level, an average power factor, an average three-phase unbalance degree, an electricity abnormal day ratio and an abnormal zero-value day ratio;
and evaluating all evaluation indexes of all power industry users to be subjected to potential depiction evaluation to obtain an evaluation result.
Referring to fig. 2 and fig. 3, a method for evaluating a multidimensional potential characterization of a power industry user for accurate marketing of data products according to an embodiment of the present invention includes the following steps:
step 1, acquiring power utilization information data of power industry users, and performing data preprocessing by adopting methods such as interpolation, elimination and the like aiming at abnormal data;
step 2, constructing an index system for the multidimensional potential depiction of the industrial user from three dimensions of electricity charge optimization, operation optimization, safety electricity utilization optimization and the like, and designing a calculation model of each index;
and 3, calculating all index values of all industrial users in a given range based on the calculation model of each index to obtain all index values of each user, respectively carrying out user sequencing on each index, and dividing the users into four parts by utilizing a quartile method to obtain the scores of each index of each user.
And 4, calculating the weights of different indexes by adopting an analytic hierarchy process aiming at the electricity charge optimization potential, the business optimization potential and the safety electricity utilization optimization potential respectively based on the grading of each index, thereby obtaining the comprehensive score of each dimensionality potential by weighting.
And 5, evaluating the comprehensive score based on the user basic file information, the potential portrayal indexes and the potentials of all dimensions, generating an industrial user portrait by utilizing a visual display tool, reasonably evaluating the potential of the user, and recommending a corresponding data product.
In the step 1 of the embodiment of the invention, the power utilization information data of the power industry user is acquired, which mainly comprises energy utilization acquisition data and marketing archive data; and for abnormal data, methods such as interpolation, elimination and the like are adopted to carry out data preprocessing.
In step 2 of the above embodiment of the present invention, an index system for multi-dimensional potential depiction of industrial users is constructed from three dimensions, such as power rate optimization, business optimization, and safety power optimization, as shown in fig. 3, and a calculation model of each index is designed, which is specifically described as follows:
1. the electric charge optimization potential comprises:
(1) the electricity charge ratio is required to be high,
Figure BDA0003672573170000131
in the formula: r is the capacity-demand electricity rate, a is the capacity-demand electricity rate, b is the demand electricity rate, C T-plan Reporting capacity, L, for a user transformer max-predict For the future maximum load demand of the user, p c To the capacity price, p need The electricity price is the demand; wherein, higher the capacity-to-electricity-demand rate, the greater the potential of the user.
(2) The qualification rate of the power factor is high,
Figure BDA0003672573170000132
in the formula: eta is power factor qualification rate, n pass Counting the total quantity points of the user power factor within the standard qualified range within a month, n sum The total points of the power factor of the user in the month are counted. Wherein a lower power factor yield indicates a greater user potential.
(3) The electricity consumption accounts for the ratio in the peak time,
Figure BDA0003672573170000133
in the formula: beta is the ratio of the peak power consumption, Q peak Is the sum of the power consumption at peak per month, Q sum Is the sum of monthly power consumption. Wherein, the higher the peak power consumption ratio, the greater the potential of the user.
(4) The average daily maximum load is given to the load,
Figure BDA0003672573170000141
in the formula: l is avgmax Is the average daily maximum load, L max,i The maximum load of the ith day in the month is counted, and n is the total number of days in the month. Wherein a larger average daily maximum load indicates a larger potential for the user.
(5) Average demand response potential, including:
1) clustering all daily electricity consumption curves of the user all the year by using a K mean value clustering algorithm to obtain a typical daily electricity consumption curve C of the user k (k=1,2,3,…,K);
2) Respectively calculating daily electricity quantity curve l of the user aiming at the peak period of electricity consumption i (i ═ 1,2,3, …,365) and user typical daily electricity consumption curve C k And (K is the sum of the electricity consumption in the peak period of 1,2,3, … and K), and obtaining the demand response potential of the user, wherein the specific expression is as follows:
Figure BDA0003672573170000142
in the formula: e dr For average demand response potential, DP n Daily power consumption curve l for nth day of user n Total of electricity consumption at peak hours, TP k Is 1 of n Typical daily electricity consumption curve C of affiliated user k N is the set S ═ N | DP n -TP k More than 0,1 is not less than n and not more than 365. Wherein a higher average demand response potential indicates a greater potential for the user.
2. Business optimization potentials include:
(1) the average daily electricity consumption is calculated,
Figure BDA0003672573170000143
in the formula: q avg Is the average daily power, Q i The electricity consumption of the ith day in the month is counted, and n is the total number of days in the month. Wherein, the lower the average daily electricity consumption, the greater the potential of the user.
(2) The operation rate of an enterprise is increased,
Figure BDA0003672573170000144
in the formula: gamma is the operating rate of the enterprise, n work Total days of work of the user within one year, n year Is the total number of days in a year. Wherein, the lower the enterprise operation rate, the greater the potential of the user.
In the specific embodiment of the invention, whether the user stops working is judged according to the daily electric quantity of the user, and the specific judgment is as follows:
Figure BDA0003672573170000151
in the formula: q avg For the average daily power consumption of the user per year, Q day The actual daily electric quantity of the user is obtained.
(3) The energy-use stage is the development stage of the energy,
Figure BDA0003672573170000152
in the formula: r is the increase rate of the annual ratio of the monthly power consumption of the user, Q is the monthly power consumption of the user, and Q avg The average value of the monthly power consumption of the industry. Wherein, the starting stage shows that the user potential is the maximum, the development stage shows that the user potential is intermediate, and the maturity stage shows that the user potential is the minimum.
(4) The rate of increase in the amount of electricity used,
Figure BDA0003672573170000153
in the formula: λ is the rate of increase in power consumption, W current For the current monthly power consumption, W last The power consumption in the last month. Wherein, the lower the power consumption increase rate, the greater the potential of the user.
(5) The level of energy consumption is high,
Figure BDA0003672573170000154
in the formula: alpha is the energy consumption level, P pro For total energy of the user, Q con The total electricity consumption of the user. Wherein a higher energy consumption level indicates a userThe greater the potential.
(6) The level of risk of an arrear is,
Figure BDA0003672573170000155
in the formula: delta is the arrearage risk level, n delay Number of arrears, n pay The number of payment times. Wherein a higher risk level of arrears indicates a greater potential for the user.
(7) Suspected levels of electricity theft, including:
1) calculating the abnormal degree A of all daily electricity curves of the user all the year by applying a local outlier factor algorithm i (i is 1,2,3, …,365), and judging whether the electricity consumption of the user is abnormal according to the abnormal degree of the daily electricity consumption curve, wherein the specific judgment is as follows:
Figure BDA0003672573170000161
2) counting the quantity of the abnormal daily electricity consumption curves of the user to obtain the suspected electricity stealing level, wherein the specific expression is as follows:
Figure BDA0003672573170000162
in the formula:
Figure BDA0003672573170000163
to the suspected level of electricity theft, n abnormal For the number of curves of abnormal daily electricity consumption of the user, n year The total number of daily electricity consumption curves of the user in one year. Wherein a higher suspected level of electricity theft indicates a greater potential for the user.
3. The potential for safety power utilization optimization comprises the following steps:
(1) the heavy overload time period is a ratio of,
Figure BDA0003672573170000164
in the formula: mu is the ratio of the heavy overload duration, N h Counting the number of heavy load measurement points of user in month,N o Counting the number of overloaded user points in the month, N total The total number of points in the month is counted. Wherein, the higher the heavy overload time ratio, the greater the user potential.
(2) The yield of the voltage is high,
Figure BDA0003672573170000165
in the formula: theta is the voltage yield, N pass And counting the number of the measurement points of the user voltage in the standard qualified range in the month, wherein N is the total number of the measurement points in the month. Wherein a lower voltage yield indicates a greater user potential.
(3) The average load rate is the average load rate,
Figure BDA0003672573170000166
in the formula: LR average Is the average load factor, LR i The load rate corresponding to the ith metering point in the statistical month is shown, and N is the total quantity point in the statistical month. Wherein a lower average load rate indicates a greater potential for the user.
(4) The level of the fluctuation of the load factor,
Figure BDA0003672573170000167
in the formula: LF is the load factor fluctuation level, LR i To count the load rate, LR, corresponding to the ith metering point in the month average The average load rate in the statistical month is obtained, and N is the total quantity point in the statistical month. Wherein a higher level of load rate fluctuation indicates a greater potential for the user.
(5) The average power factor of the power-supply line,
Figure BDA0003672573170000171
in the formula: f avg Is the average power factor, N is the total number of points in the statistical month, F i And (4) corresponding to the power factor of the ith metering point. Wherein a lower average power factor indicates a greater potential for the user.
(6) Average three-phase unbalance,
Figure BDA0003672573170000172
In the formula: i is im To average out of balance of three phases, I i,j Phase current of j phase for I-th metering point, I i,average The average phase current of the ith metering point is N, and the total quantity point number in the statistical month is N. Wherein a higher average three-phase imbalance indicates a greater user potential.
(7) The electricity consumption abnormal days comprises:
1) and (3) applying a principal component analysis algorithm based on a kernel function to reduce the dimensions of all daily electric quantity curves of the user all the year round.
2) Based on the daily electricity curve after dimensionality reduction, an abnormal daily electricity curve is detected by using an isolated forest algorithm, and the proportion of abnormal electricity consumption days is calculated, and the specific expression is as follows:
Figure BDA0003672573170000173
in the formula: r abn In terms of abnormal days of electricity consumption, N abn For the number of curves of abnormal daily electricity consumption of the user, N year The total number of the daily electricity consumption curves of the user in one year. Wherein, the higher the proportion of abnormal days of electricity is, the greater the potential of the user is.
(8) The number of days of an abnormal zero is proportional,
Figure BDA0003672573170000174
in the formula: r zero Number of days of abnormal zero, N zero Number of exceptional zero-value days, N month To account for the total number of days in the month. Wherein a higher percentage of outlier zero days indicates a greater potential for the user.
In the embodiment of the invention, whether the day is an abnormal zero-value day is judged according to the number of zero values appearing in the daily electric quantity curve of the user, and the specific judgment is as follows:
Figure BDA0003672573170000181
in the formula: num is the number of zero values appearing in the daily electricity consumption curve of the user.
Example two
In step 3 of the above embodiment of the present invention, for all industrial users in a given range, all index values of each user are calculated based on the calculation model of each index, user sorting is performed for each index, and the user is divided into four parts (i.e., 1% -25%, 26% -50%, 51% -75%, 76% -100%) by using a quartile method. Wherein the larger the potential, the higher the score obtained. Therefore, each user will eventually obtain a score according to the respective index.
In the embodiment of the invention, the comparison relationship between the specific index and the scoring rule is shown in table 1.
TABLE 1 comparison table of each index and scoring rule
Figure BDA0003672573170000182
Figure BDA0003672573170000191
In step 4 of the above embodiment of the present invention, based on the scores of the indexes, the weight ω of different indexes is calculated by using an analytic hierarchy process for the electricity fee optimization potential, the business optimization potential, and the safety electricity utilization optimization potential respectively i E (0,1), i ═ 1,2,3, …, n, so that the weighting yields a composite score for each dimension potential. Specifically, for the electricity fee optimization potential, the business optimization potential and the safety electricity utilization optimization potential, the value of n is 5, 7 and 8 respectively.
Based on the calculation result of the embodiment of the invention, the comprehensive score is evaluated according to the basic archive information, the potential depiction index and the potential of each dimension of the user, an industrial user portrait is generated by utilizing a visual display tool, the potential of the user is reasonably evaluated, and a corresponding data product is recommended.
In the embodiment of the invention, the comparison relationship between the specific user potential and the data product is shown in table 2.
TABLE 2 comparison of user potentiality with data products
Figure BDA0003672573170000192
In summary, the embodiment of the invention adopts the power big data technology to mine the data value of the power consumer, establishes a system for comprehensively depicting the multidimensional potential of the power consumer and quantitatively evaluating the multidimensional potential, and serves the selection of the target user to realize the precise marketing of individuation and differentiation of the power data value-added service product. Because the potential of the industrial user is difficult to systematically and comprehensively depict and reasonably and quantitatively evaluate by the method in the prior art, the invention provides the power user multi-dimensional potential depicting system oriented to the accurate marketing of data products so as to effectively depict and evaluate the potential of the industrial user. Specifically, firstly, an industrial user multi-dimensional potential depiction index system is constructed from three dimensions of electricity charge optimization, operation optimization, safe electricity utilization optimization and the like, and each index calculation rule is designed; then, based on an index calculation rule, calculating each index value of the user, comprehensively depicting the multidimensional potential of the user by a system, and scoring each index of the user by adopting a quartile method; then, calculating potential evaluation comprehensive scores of all dimensions of the user by using an analytic hierarchy process; and finally, evaluating the comprehensive score based on the user basic file information, the potential portrayal index and the potentials of all dimensions, visually displaying the industrial user portrait, reasonably evaluating the potential of the user, and recommending a corresponding data product. The invention can powerfully support the profit mode and marketing strategy reform and innovation of a power grid company, accurately grasp the demand of power users, realize accurate marketing and have greater practical application value and popularization prospect for power marketing business.
EXAMPLE III
The following are embodiments of the apparatus of the present invention that may be used to perform embodiments of the method of the present invention. For details of non-careless mistakes in the embodiment of the apparatus, please refer to the embodiment of the method of the present invention.
In another embodiment of the present invention, a system for evaluating a multi-dimensional potential depiction of a power industry user is provided, which includes:
the data acquisition module is used for acquiring power utilization information data of a plurality of power industry users to be potential portrayed and evaluated in a preset area range;
the evaluation index acquisition module is used for calculating and acquiring an evaluation index for each power industry user to be potential-portrayed and evaluated by utilizing a pre-constructed multi-dimensional potential-portrayal index system of the power industry user based on the corresponding power utilization information data; the evaluation indexes comprise a capacity-to-electricity-demand charge ratio, a power factor qualification rate, a peak-time electricity consumption ratio, an average daily maximum load, an average demand response potential, an average daily electricity quantity, an enterprise operation rate, an energy consumption development stage, an electricity consumption increase rate, an energy consumption level, an owing risk level, an electricity stealing suspicion level, a heavy overload time ratio, a voltage qualification rate, an average load rate, a load rate fluctuation level, an average power factor, an average three-phase unbalance degree, an electricity abnormal day ratio and an abnormal zero number ratio;
and the evaluation result acquisition module is used for carrying out grading evaluation on all evaluation indexes of all power industry users to be subjected to potential description evaluation to obtain an evaluation result.
Example four
In yet another embodiment of the present invention, a computer device is provided that includes a processor and a memory for storing a computer program comprising program instructions, the processor for executing the program instructions stored by the computer storage medium. The Processor may be a Central Processing Unit (CPU), or may be other general-purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, a discrete hardware component, etc., which is a computing core and a control core of the terminal, and is specifically adapted to load and execute one or more instructions in a computer storage medium to implement a corresponding method flow or a corresponding function; the processor provided by the embodiment of the invention can be used for operating the multi-dimensional potential characterization and evaluation method for the power industry users.
In yet another embodiment of the present invention, the present invention further provides a storage medium, specifically a computer-readable storage medium (Memory), which is a Memory device in a computer device and is used for storing programs and data. It is understood that the computer readable storage medium herein can include both built-in storage media in the computer device and, of course, extended storage media supported by the computer device. The computer-readable storage medium provides a storage space storing an operating system of the terminal. Also, one or more instructions, which may be one or more computer programs (including program code), are stored in the memory space and are adapted to be loaded and executed by the processor. It should be noted that the computer-readable storage medium may be a high-speed RAM memory, or may be a non-volatile memory (non-volatile memory), such as at least one disk memory. One or more instructions stored in the computer-readable storage medium may be loaded and executed by a processor to implement the corresponding steps of the method for evaluating the multidimensional potential characterization of the power industry users in the above embodiments.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.

Claims (10)

1. A multi-dimensional potential depiction evaluation method for power industry users is characterized by comprising the following steps:
acquiring power utilization information data of a plurality of power industry users to be subjected to potential description and evaluation within a preset area range;
for each power industry user to be potential-portrayed and evaluated, calculating to obtain an evaluation index by utilizing a pre-constructed power industry user multi-dimensional potential-portrayal index system based on the corresponding power utilization information data; the evaluation indexes comprise a capacity-to-electricity-demand charge ratio, a power factor qualification rate, a peak-time electricity consumption ratio, an average daily maximum load, an average demand response potential, an average daily electricity quantity, an enterprise operation rate, an energy consumption development stage, an electricity consumption increase rate, an energy consumption level, an owing risk level, an electricity stealing suspicion level, a heavy overload time ratio, a voltage qualification rate, an average load rate, a load rate fluctuation level, an average power factor, an average three-phase unbalance degree, an electricity abnormal day ratio and an abnormal zero number ratio;
performing scoring evaluation on all evaluation indexes of all power industry users to be subjected to potential portrayal evaluation to obtain an evaluation result; and marketing a preset electric power data value-added service product based on the evaluation result.
2. The method according to claim 1, wherein the step of obtaining power consumption information data of a plurality of power industry users to be potential-portrayed and evaluated within a preset area specifically comprises:
acquiring power consumption information data of a plurality of power industry users to be potential portrayed and evaluated after abnormal data preprocessing in a preset area range;
the power utilization information data comprise transformer installation capacity, power factors, active power, reactive power, power consumption, payment times, defaulting times, voltage and current.
3. The method for evaluating the multi-dimensional potential depiction of the power industry users as claimed in claim 1, wherein the pre-constructed multi-dimensional potential depiction index system of the power industry users comprises three dimensions of electricity charge optimization potential, business optimization potential and safe electricity utilization optimization potential;
the electric charge optimization potential includes:
(1) the electricity charge ratio is required to be high,
Figure FDA0003672573160000011
wherein r is the capacity-demand electricity rate, a is the capacity electricity rate, b is the demand electricity rate, C T-plan Reporting capacity, L, for the user's transformer max-predict For the future maximum load demand of the user, p c To capacity price, p need The electricity price is the demand;
(2) the qualification rate of the power factor is high,
Figure FDA0003672573160000021
where eta is the power factor yield, n pass Counting the total quantity points of the user power factor within the standard qualified range within a month, n sum Counting the total quantity points of the power factors of the users in the month;
(3) the electricity consumption accounts for the ratio in the peak time,
Figure FDA0003672573160000022
in which beta is the ratio of the peak power consumption, Q peak Is the sum of the power consumption at peak per month, Q sum The total monthly electricity consumption;
(4) the average daily maximum load is given to the load,
Figure FDA0003672573160000023
in the formula, L avgmax Is the average daily maximum load, L max,i Counting the maximum load of the ith day in the month, wherein n is the total number of days in the month;
(5) the average demand response potential is given to the demand,
Figure FDA0003672573160000024
in the formula, E dr Is flatAverage demand response potential, DP n Daily power consumption curve l for nth day of user n Total of electricity consumption at peak hours, TP k Is 1 n Typical daily electricity consumption curve C of affiliated user k N is the set S ═ N | DP n -TP k More than 0,1 is not less than n and not more than 365;
the business optimization potentials include:
(1) the average daily electricity consumption is calculated,
Figure FDA0003672573160000025
in the formula, Q avg Is the average daily power, Q i Counting the electricity consumption of the ith day in the month, wherein n is the total days in the month;
(2) the operation rate of an enterprise is increased,
Figure FDA0003672573160000026
wherein, gamma is the enterprise operating rate, n work Total days of work of the user within one year, n year Total days in a year;
(3) the energy-use development stage is that,
Figure FDA0003672573160000031
wherein R is the increase rate of the ring ratio of the monthly power consumption of the user, Q is the monthly power consumption of the user, and Q avg The average value of the monthly power consumption of the industry;
(4) the rate of increase in the amount of electricity used,
Figure FDA0003672573160000032
wherein λ is the rate of increase of power consumption, W current For the current monthly electricity consumption, W last The electricity consumption is the electricity consumption in the previous month;
(5) the level of energy consumption is high,
Figure FDA0003672573160000033
in which α is the energy consumption level, P pro For total energy of the user, Q con The total electricity consumption of the user is calculated;
(6) the level of risk of an arrear is,
Figure FDA0003672573160000034
where δ is the arrearage risk level, n delay Number of arrears, n pay The number of times of payment is;
(7) the suspected level of electricity stealing,
Figure FDA0003672573160000035
in the formula (I), the compound is shown in the specification,
Figure FDA0003672573160000036
to the suspected level of electricity theft, n abnormal Number of curves for abnormal daily electricity consumption of user, n year The total number of curves of daily electricity consumption of a user in one year;
the safety power utilization optimization potential comprises:
(1) the heavy overload time is a ratio of the time length,
Figure FDA0003672573160000037
where μ is the ratio of the heavy overload duration, N h For counting the number of heavy load measurement points of the user in the month, N o Counting the number of overloaded user points in the month, N total Counting the total number of points in the month;
(2) the yield of the voltage is high,
Figure FDA0003672573160000038
wherein θ is the voltage yield, N pass Counting the number of measurement points of the user voltage in a standard qualified range in a month, wherein N is the total number of measurement points in the month;
(3) the average load rate is the average load rate,
Figure FDA0003672573160000041
in the formula, LR average Is the average load factor, LR i Counting the load rate corresponding to the ith metering point in the month, wherein N is the total quantity point in the month;
(4) the level of the fluctuation of the load factor,
Figure FDA0003672573160000042
where LF is the level of load factor fluctuation, LR i To count the load rate, LR, corresponding to the ith metering point in the month average The average load rate in the statistical month is shown, and N is the total quantity point in the statistical month;
(5) the average power factor of the power-supply line,
Figure FDA0003672573160000043
in the formula, F avg Is the average power factor, N is the total number of points in the statistical month, F i The power factor corresponding to the ith metering point;
(6) the degree of unbalance of the three phases is averaged,
Figure FDA0003672573160000044
in the formula I im To average out of balance of three phases, I i,j Phase current of j phase for I-th metering point, I i,average The average phase current of the ith metering point is N, and the number of the total metering points in the statistical month is N;
(7) the number of days of abnormal electricity utilization is proportional to the number of days of abnormal electricity utilization,
Figure FDA0003672573160000045
in the formula, R abn In terms of abnormal days of electricity consumption, N abn For the number of curves of abnormal daily electricity consumption of the user, N year The total number of curves of daily electricity consumption of a user in one year;
(8) the number of days of an abnormal zero is proportional,
Figure FDA0003672573160000046
in the formula, R zero Number of days of abnormal zero, N zero Number of exceptional zero-value days, N month To account for the total number of days in the month.
4. The method according to claim 3, wherein the step of performing scoring evaluation based on all evaluation indexes of all power industry users to be evaluated for potential characterization to obtain an evaluation result specifically comprises:
for the power industry users to be subjected to potential depiction and evaluation, ranking the users based on each evaluation index to obtain the score of each evaluation index of each power industry user;
and on the basis of the scores of all the evaluation indexes, calculating the weights of different evaluation indexes by adopting an analytic hierarchy process aiming at the electricity charge optimization potential, the business optimization potential and the safety electricity utilization optimization potential, weighting to obtain the comprehensive score of each dimensionality potential, and obtaining an evaluation result.
5. A power industry user multi-dimensional potential depiction evaluation system is characterized by comprising:
the data acquisition module is used for acquiring power utilization information data of a plurality of power industry users to be potential portrayed and evaluated in a preset area range;
the evaluation index acquisition module is used for calculating and obtaining an evaluation index for each power industry user to be potential-delineated and evaluated by utilizing a pre-constructed power industry user multi-dimensional potential delineation index system based on the corresponding power utilization information data; the evaluation indexes comprise a capacity-demand electricity charge ratio, a power factor qualification rate, a peak-time electricity consumption ratio, an average daily maximum load, an average demand response potential, an average daily electricity quantity, an enterprise operation rate, an energy consumption development stage, an electricity consumption increase rate, an energy consumption level, an owing risk level, an electricity stealing suspicion level, a heavy overload time ratio, a voltage qualification rate, an average load rate, a load rate fluctuation level, an average power factor, an average three-phase unbalance degree, an electricity consumption abnormal day ratio and an abnormal day zero value ratio;
and the evaluation result acquisition module is used for carrying out grading evaluation on all evaluation indexes of all power industry users to be subjected to potential description evaluation to obtain an evaluation result.
6. The power industry user multi-dimensional potential depiction evaluation system according to claim 5, wherein the step of obtaining power consumption information data of a plurality of power industry users to be potential depiction evaluated within a preset area specifically comprises:
acquiring power consumption information data of a plurality of power industry users to be potential portrayed and evaluated after abnormal data preprocessing in a preset area range;
the power utilization information data comprise transformer installation capacity, power factors, active power, reactive power, power consumption, payment times, defaulting times, voltage and current.
7. The power industry user multi-dimensional potential depiction evaluation system as claimed in claim 5, wherein the pre-constructed power industry user multi-dimensional potential depiction index system comprises three dimensions of electricity charge optimization potential, business optimization potential and safe electricity utilization optimization potential;
the electric charge optimization potential includes:
(1) the electricity charge ratio is required to be high,
Figure FDA0003672573160000061
wherein r is the capacity-demand electricity rate, a is the capacity electricity rate, b is the demand electricity rate, C T-plan Reporting capacity, L, for a user transformer max-predict For the user's future maximum load demand, p c To the capacity price, p need The electricity price is the demand;
(2) the qualification rate of the power factor is high,
Figure FDA0003672573160000062
where eta is the power factor yield, n pass Counting the total quantity points of the user power factor within the standard qualified range within a month, n sum Counting the total points of the power factors of the users in the month;
(3) the electricity consumption accounts for the ratio in the peak time,
Figure FDA0003672573160000063
in which beta is the ratio of the peak power consumption, Q peak Is the sum of the power consumption at peak per month, Q sum The total monthly electricity consumption;
(4) the average daily maximum load is given to the load,
Figure FDA0003672573160000064
in the formula, L avgmax Is the average daily maximum load, L max,i Counting the maximum load of the ith day in the month, wherein n is the total number of days in the month;
(5) the average demand response potential is given to the demand,
Figure FDA0003672573160000065
in the formula, E dr To average demand response potential, DP n Daily power consumption curve l for nth day of user n Total of electricity consumption at peak hours, TP k Is 1 n Typical daily electricity consumption curve C of affiliated user k N is the set S ═ N | DP n -TP k More than 0,1 is not less than n and not more than 365;
the business optimization potentials include:
(1) the average daily electricity consumption is calculated,
Figure FDA0003672573160000071
in the formula, Q avg Is the average daily power, Q i Counting the electricity consumption of the ith day in the month, wherein n is the total number of days in the month;
(2) the operation rate of an enterprise is increased,
Figure FDA0003672573160000072
wherein, gamma is the enterprise operating rate, n work Total days of work of the user within one year, n year Total days in a year;
(3) the energy-use stage is the development stage of the energy,
Figure FDA0003672573160000073
wherein R is the increase rate of the ring ratio of the monthly power consumption of the user, Q is the monthly power consumption of the user, and Q avg The average value of the monthly power consumption of the industry;
(4) the rate of increase in the amount of electricity used,
Figure FDA0003672573160000074
wherein λ is the rate of increase of power consumption, W current For the current monthly power consumption, W last The electricity consumption is the electricity consumption in the previous month;
(5) the level of energy consumption is high,
Figure FDA0003672573160000075
wherein α is the energy consumption level, P pro For total energy of the user, Q con The total electricity consumption of the user is calculated;
(6) the level of risk of an arrear is,
Figure FDA0003672573160000076
where δ is the arrearage risk level, n delay For the number of defaults, n pay The number of times of payment is;
(7) the suspected level of electricity stealing is high,
Figure FDA0003672573160000077
in the formula (I), the compound is shown in the specification,
Figure FDA0003672573160000078
to the suspected level of electricity theft, n abnormal For the number of curves of abnormal daily electricity consumption of the user, n year The total number of curves of daily electricity consumption of a user in one year;
the safety power utilization optimization potential comprises:
(1) the heavy overload time period is a ratio of,
Figure FDA0003672573160000081
where μ is the ratio of the heavy overload duration, N h For counting the number of heavy load measurement points of the user in the month, N o Counting the number of overloaded user points in the month, N total Counting the total number of points in the month;
(2) the yield of the voltage is high,
Figure FDA0003672573160000082
wherein θ is the voltage yield, N pass Counting the number of measurement points of the user voltage in a standard qualified range in a month, wherein N is the total number of measurement points in the month;
(3) the average load rate of the load is,
Figure FDA0003672573160000083
in the formula, LR average Is the average load factor, LR i Counting the load rate corresponding to the ith metering point in the month, wherein N is the total quantity point in the month;
(4) the level of the fluctuation in the load factor,
Figure FDA0003672573160000084
where LF is the level of load factor fluctuation, LR i To count the load rate, LR, corresponding to the ith metering point in the month average The average load rate in the statistical month is shown, and N is the total quantity point in the statistical month;
(5) the average power factor of the power-supply line,
Figure FDA0003672573160000085
in the formula, F avg Is the average power factor, N is the total number of points in the statistical month, F i The power factor corresponding to the ith metering point;
(6) the degree of unbalance of the three phases is averaged,
Figure FDA0003672573160000086
in the formula I im To average out of balance of three phases, I i,j Phase current of j phase for I-th metering point, I i,average The average phase current of the ith metering point is N, and the number of the total metering points in the statistical month is N;
(7) the number of days of abnormal electricity utilization is proportional to the number of days of abnormal electricity utilization,
Figure FDA0003672573160000091
in the formula, R abn In terms of abnormal days of electricity consumption, N abn For the number of curves of abnormal daily electricity consumption of the user, N year The total number of curves of daily electricity consumption of a user in one year;
(8) the number of days of an abnormal zero is proportional,
Figure FDA0003672573160000092
in the formula, R zero Number of days of abnormal zero, N zero Number of exceptional zero-value days, N month To account for the total number of days in the month.
8. The power industry user multi-dimensional potential depiction evaluation system as claimed in claim 7, wherein the step of performing scoring evaluation based on all evaluation indexes of all power industry users to be evaluated for potential depiction and obtaining evaluation results specifically comprises:
for the power industry users to be subjected to potential depiction and evaluation, ranking the users based on each evaluation index to obtain the score of each evaluation index of each power industry user;
and on the basis of the scores of all the evaluation indexes, calculating the weights of different evaluation indexes by adopting an analytic hierarchy process aiming at the electricity charge optimization potential, the business optimization potential and the safety electricity utilization optimization potential, weighting to obtain the comprehensive score of each dimensionality potential, and obtaining an evaluation result.
9. An electronic device, comprising:
at least one processor; and (c) a second step of,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the power industry user multi-dimensional potential characterization assessment method of any one of claims 1 to 4.
10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the method for multi-dimensional potential characterization assessment of power industry users according to any one of claims 1 to 4.
CN202210609294.2A 2022-05-31 2022-05-31 Method, system, equipment and medium for multi-dimensional potential depiction evaluation of power industry users Pending CN115018311A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115439165A (en) * 2022-10-25 2022-12-06 南方电网数字电网研究院有限公司 Method, device, equipment and medium for determining supply increase and marketing information of power consumer

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115439165A (en) * 2022-10-25 2022-12-06 南方电网数字电网研究院有限公司 Method, device, equipment and medium for determining supply increase and marketing information of power consumer

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