CN115456346B - Electric quantity monitoring and early warning method and device, electronic equipment and medium - Google Patents
Electric quantity monitoring and early warning method and device, electronic equipment and medium Download PDFInfo
- Publication number
- CN115456346B CN115456346B CN202210971792.1A CN202210971792A CN115456346B CN 115456346 B CN115456346 B CN 115456346B CN 202210971792 A CN202210971792 A CN 202210971792A CN 115456346 B CN115456346 B CN 115456346B
- Authority
- CN
- China
- Prior art keywords
- demand
- cost
- reporting
- determining
- electricity consumption
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 62
- 238000012544 monitoring process Methods 0.000 title claims description 29
- 230000005611 electricity Effects 0.000 claims abstract description 195
- 238000004519 manufacturing process Methods 0.000 claims description 52
- 238000003860 storage Methods 0.000 claims description 10
- 238000004590 computer program Methods 0.000 claims description 3
- 230000007274 generation of a signal involved in cell-cell signaling Effects 0.000 claims description 2
- 238000012163 sequencing technique Methods 0.000 claims description 2
- 238000009825 accumulation Methods 0.000 claims 2
- 238000004364 calculation method Methods 0.000 claims 2
- 238000012545 processing Methods 0.000 abstract description 3
- 230000000694 effects Effects 0.000 abstract description 2
- 238000004458 analytical method Methods 0.000 description 5
- 230000002349 favourable effect Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 230000006978 adaptation Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000005587 bubbling Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000002093 peripheral effect Effects 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 238000004891 communication Methods 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06315—Needs-based resource requirements planning or analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0283—Price estimation or determination
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Development Economics (AREA)
- Theoretical Computer Science (AREA)
- Entrepreneurship & Innovation (AREA)
- General Physics & Mathematics (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Game Theory and Decision Science (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Health & Medical Sciences (AREA)
- Educational Administration (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application relates to the field of data processing, in particular to a method, a device, electronic equipment and a medium for determining an electric charge pricing mode, which comprise the steps of acquiring user data; determining an alternative reporting demand group based on the user data; determining contract demand cost corresponding to each alternative demand based on the alternative declaration demand group; determining a minimum contract demand charge based on the plurality of contract demand charges; acquiring declaration transformer data, and acquiring capacity cost according to the declaration transformer data; acquiring actual electricity consumption, and determining actual demand cost according to the actual electricity consumption; comparing the minimum contract demand cost, the capacity cost and the actual demand cost to determine the optimal cost; and determining the electric charge pricing mode corresponding to the optimal charge as the optimal electric charge pricing mode. The application has the effect of optimizing and selecting the electric charge pricing mode so as to reduce the electric charge expense of enterprises.
Description
Technical Field
The present application relates to the field of data processing, and in particular, to a method and apparatus for monitoring and early warning of electric quantity, an electronic device, and a medium.
Background
Because the residential electricity is needed in daily life, the value is not generated by the electricity, and the large industrial electricity can be used for generating the value, the large industrial electricity is different from the residential electricity in payment mode. The large industrial electricity fee includes four kinds: basic electric charge, electricity degree electric charge, power adjustment electric charge and water conservancy basic adjustment electric charge, wherein the basic electric charge is the electric charge which is fixed to a power grid company for large industrial electric enterprises every month, and the electric charge is paid to a national power grid even if the enterprises do not consume any electric power in the current month.
The basic electric charge payment modes are divided into three types, including the payment according to the capacity, namely the declared transformer capacity charge; paying according to the declaration demand; and paying according to the actual demand, namely charging according to the demand in the actual use process. Although the unit price of paying according to the transformer capacity is low, the basic number of transformers is generally larger, so that basic electricity fee cannot be saved only by paying through the transformer capacity, and the payment mode needs to be reasonably selected by combining the electricity demand of enterprises in order to save the expenditure of the electricity expenses of the enterprises. Because the enterprise scale is different, so the corresponding power consumption demand of every enterprise is also different, so not every enterprise is applicable to pay according to the volume or pay according to the demand, therefore how rationally select the payment mode of basic electric charge is very critical to reducing enterprise's electric charge expense and reducing the manufacturing cost of enterprise.
Disclosure of Invention
In order to optimally select an electric charge pricing mode and further reduce electric charge expenditure of enterprises, the application provides an electric quantity monitoring and early warning method, an electric quantity monitoring and early warning device, electronic equipment and a medium.
In a first aspect, the present application provides an electric quantity monitoring and early warning method, which adopts the following technical scheme:
an electric quantity monitoring and early warning method comprises the following steps:
acquiring user data;
determining an alternative reporting demand group based on the user data;
determining contract demand cost corresponding to each alternative demand based on the alternative declaration demand group;
determining a minimum contract demand charge based on the plurality of contract demand charges;
analyzing the user data to obtain declaration transformer data, and obtaining capacity cost according to the declaration transformer data;
analyzing the user data to obtain actual electricity consumption, and determining actual demand cost according to the actual electricity consumption;
comparing the minimum contract demand cost, the capacity cost and the actual demand cost to determine an optimal cost;
and the electric quantity monitoring and early warning corresponding to the optimal cost is used as an optimal electric charge pricing mode.
By adopting the technical scheme, the alternative reporting demand group is determined according to the acquired electricity consumption data, wherein the alternative reporting demand group comprises a plurality of reporting demands, the contract demand cost corresponding to each reporting demand is determined according to the corresponding contract demand price calculating formula, the lowest contract demand cost is determined from the plurality of contract demand costs, the reporting transformer data and the actual electricity consumption are obtained through analysis from the user data, the corresponding capacity cost is obtained based on the transformer data, the corresponding actual demand cost is obtained based on the actual electricity consumption, the optimal cost in the lowest contract demand cost, the capacity cost and the actual demand cost is finally determined, and the electric quantity corresponding to the optimal cost is monitored and early warned as the optimal electricity fee price calculating mode, so that the optimal electricity fee price calculating mode is selected, and the enterprise electricity fee price calculating mode is favorable for reducing the enterprise electricity fee price.
In one possible implementation, the determining an alternative reporting requirement group based on the user data includes:
acquiring initial user demand in a plurality of preset time periods;
sequencing the plurality of initial user demands to form a demand sequence;
and determining an alternative reporting demand group according to the demand sequence.
By adopting the technical scheme, the initial user demands in a plurality of preset time periods are acquired, the initial user demands are sequenced to form the demand sequence, the alternative reporting demand group is determined from the demand sequence, and the accuracy of determining the reporting demand is improved by determining the reporting demand from the alternative reporting demand group.
In one possible implementation, the determining the alternative reporting requirement group according to the requirement sequence includes:
calculating a demand mode of the demand sequence according to the demand sequence;
calculating a demand average of the demand sequences according to the demand sequences;
calculating a demand maximum value of the demand sequence according to the demand sequence;
the demand mode, the demand average, and the demand maximum form an alternative reporting demand group.
By adopting the technical scheme, the demand mode, the demand average number and the demand maximum value corresponding to the demand sequence are respectively calculated through the demand sequence, the alternative reporting demand group is formed, and the accuracy in determining the reporting demand is improved through a plurality of alternative reporting demands.
In one possible implementation, the method further includes:
if the optimal electricity charge pricing method is a contract demand pricing method, determining an alternative reporting demand corresponding to the lowest contract charge as a target reporting demand;
and sending the target reporting demand to a terminal device so that the enterprise reports the target reporting demand to the power grid.
By adopting the technical scheme, when the optimal electric charge pricing mode is contract demand pricing sending, the corresponding alternative reporting demand is determined according to the lowest contract cost, and the alternative reporting demand is sent to the terminal equipment, so that related staff can record the alternative reporting demand conveniently, and report to the power grid according to the reporting demand.
In one possible implementation, the method further includes:
extracting historical production order information from a historical database;
predicting production order information of the next period according to the previous production order information;
comparing the next period production order information with the current year production order information to obtain a production order difference value;
and determining a difference working time according to the difference value of the production order and the historical working efficiency, and determining a difference requirement of the difference working time.
By adopting the technical scheme, the historical production order information is extracted from the historical database, the next-period production order information is predicted according to the historical production order information, the predicted next-period production order information is compared with the current-period production order information to obtain a production order difference value, the difference working time is determined according to the production order difference value and the historical working efficiency, the difference required amount corresponding to the difference working time is obtained, and the accuracy of determining the electric charge pricing mode is improved based on the difference required amount.
In one possible implementation manner, after the extracting the historical production order information from the historical database, the method further includes:
according to the historical production order information, predicting the electricity consumption of each month in the next period;
comparing the electricity consumption of the preset month with the electricity consumption of each month of the next period to determine a light month, wherein the light month is the month of which the electricity consumption of each month of the next period is lower than the electricity consumption of the preset month;
and according to the power consumption requirement corresponding to the light month, reporting and stopping adjustment is carried out on the capacity of the transformer.
Through adopting above-mentioned technical scheme, through the order information of production of past time confirm each month electricity consumption of past time, and according to each month electricity consumption of past time each month electricity consumption forecast, again according to predetermine electricity consumption and each month electricity consumption of next cycle, confirm the light month, through the electricity consumption that the light month corresponds, report and stop the adjustment to the transformer capacity, be convenient for reduce the consumption of electricity consumption, and then reduce the expenditure of charges of electricity.
In one possible implementation, the method further includes:
acquiring the electricity consumption requirement of the next period corresponding to the optimal electricity charge pricing mode;
according to the electricity demand of the next period, a monthly electricity limit value is formulated;
when the month practical electricity consumption exceeds the month electricity consumption limit value, generating a warning signal, pushing the warning signal to user related equipment, and facilitating the user to adjust the electricity consumption in time.
Through adopting above-mentioned technical scheme, after the electricity demand of next cycle is monitored and early-warned through best electric quantity, according to next cycle electricity demand, the month electricity limit value of working out is behind month actual electricity demand exceeded month electricity limit value to the warning information is generated to the terminal equipment of relevant user is sent to the warning information that generates, and the relevant user of being convenient for in time adjusts the electric quantity service condition, reduces the probability that electricity demand exceeded month limit value, and then reduces the expenditure of charges of electricity.
In a second aspect, the application provides an electric quantity monitoring and early warning device, which adopts the following technical scheme:
an electrical quantity monitoring and early warning device, comprising:
the acquisition module is used for acquiring user data;
an alternative determining module, configured to determine an alternative reporting requirement group based on the user data;
The contract cost determining module is used for determining contract demand cost corresponding to each alternative demand based on the alternative declaration demand group;
the minimum contract cost determining module is used for determining minimum contract demand cost according to the contract costs;
the capacity charge determining module is used for analyzing the user data to obtain declaration transformer data and obtaining capacity charge according to the declaration transformer data;
the actual demand cost determining module is used for analyzing the user data to obtain actual electricity demand, and determining actual demand cost according to the actual electricity demand;
a determining optimal cost module for comparing the minimum contract demand cost, the capacity cost and the actual demand cost to determine an optimal cost;
and the pricing mode determining module is used for taking the electric quantity monitoring and early warning corresponding to the optimal expense as the optimal electric expense pricing mode.
By adopting the technical scheme, the alternative reporting demand group is determined according to the acquired electricity consumption data, wherein the alternative reporting demand group comprises a plurality of reporting demands, the contract demand cost corresponding to each reporting demand is determined according to the corresponding contract demand price calculating formula, the lowest contract demand cost is determined from the plurality of contract demand costs, the reporting transformer data and the actual electricity consumption are obtained through analysis from the user data, the corresponding capacity cost is obtained based on the transformer data, the corresponding actual demand cost is obtained based on the actual electricity consumption, the optimal cost in the lowest contract demand cost, the capacity cost and the actual demand cost is finally determined, and the electric quantity corresponding to the optimal cost is monitored and early warned as the optimal electricity fee price calculating mode, so that the optimal electricity fee price calculating mode is selected, and the enterprise electricity fee price calculating mode is favorable for reducing the enterprise electricity fee price.
In a third aspect, the present application provides an electronic device, which adopts the following technical scheme:
an electronic device, the electronic device comprising:
at least one processor;
a memory;
at least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application configured to: executing the method for monitoring and early warning the electric quantity.
In a fourth aspect, the present application provides a computer readable storage medium, which adopts the following technical scheme:
a computer-readable storage medium, comprising: a computer program capable of being loaded by a processor and executing the electric quantity monitoring and early warning method is stored.
In summary, the present application includes at least one of the following beneficial technical effects:
the method comprises the steps of determining an alternative reporting demand group according to acquired electricity consumption data, wherein the alternative reporting demand group comprises a plurality of reporting demands, determining contract demand fees corresponding to each reporting demand according to corresponding contract demand price formulas, determining the lowest contract demand fees from the plurality of contract demand fees, analyzing from user data to obtain reporting transformer data and actual electricity consumption, obtaining corresponding capacity fees based on the transformer data and obtaining corresponding actual demand fees based on the actual electricity consumption, finally determining the optimal fees among the lowest contract demand fees, the capacity fees and the actual demand fees, monitoring and early warning electric quantity corresponding to the optimal fees as an optimal electricity fee pricing mode, and selecting the optimal electricity fee pricing mode to be helpful for reducing electricity fees of enterprises in an optimal electricity fee selecting mode.
Drawings
FIG. 1 is a schematic flow chart of an electric quantity monitoring and early warning method in an embodiment of the application;
fig. 2 is a schematic structural diagram of an electric quantity monitoring and early warning device according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Description of the embodiments
The application is described in further detail below with reference to fig. 1-3.
Modifications of the embodiments which do not creatively contribute to the application may be made by those skilled in the art after reading the present specification, but are protected by patent laws within the scope of the claims of the present application.
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The charging mode of the large industrial electricity is different from the charging mode of the resident electricity, and particularly, the charging mode of the large industrial electricity comprises four parts: the power grid system comprises a basic electric charge, an electricity degree electric charge, a power adjustment electric charge and a water conservancy basic adjustment electric charge, wherein the basic electric charge is the electric charge which is fixedly paid to a power grid company by an enterprise every month, and even if the enterprise does not consume any electric power in the current month, the electric charge is paid to a national power grid, and the basic electric charge can be understood as a fixed capacity occupation charge. When basic electric charge payment is carried out, three modes exist:
In the first mode, the price is calculated according to the capacity, namely, the basic electricity charge capacity unit price is calculated according to the declared transformer capacity;
in a second mode, the price is calculated according to contract demand, namely, a user provides a declaration demand value for the power grid, when the actual demand of the user exceeds 105% of the declaration demand value, the exceeding part charges according to one time of the demand unit price, and the part 105% of the non-exceeding declaration value charges according to the demand unit price;
in the third mode, the price is calculated according to the actual demand, that is, the price unit price is calculated according to the actual demand actually generated.
Generally, the unit price of the capacity is far lower than the unit price of the demand, but the method of charging the capacity electric charge is not meant to be suitable for all enterprises, for example, in Beijing area, the unit price of the capacity is 32 yuan/kilovolt ampere, the unit price of the demand is 48 yuan/kilowatt, and according to the unit price of the capacity demand, it can be calculated that when the load of the enterprise is below 32/48=66%, the basic electric charge is properly declared according to the demand, otherwise, if the load is above 66%, the basic electric charge is properly paid according to the capacity. If the basic electric charge is paid according to the contract demand and the monthly demand is reported to the power grid, the excessive electric charge paying risk is easily caused when the actual demand is higher than the reporting demand. Examples: the transformer capacity of a Beijing company is 1000 kilovolts, the unit price of the transformer is 32 yuan/kilovolts, the unit price of the transformer is 48 yuan/kilovolts, the enterprise pays 32000 yuan of basic electricity fee per month according to the unit price of the transformer, if the requirement is 400KW and the actual electricity consumption is 600KW, the basic electricity fee is 400.105.48+ (600-400.105.48.48.48.37440 yuan) and 37440-32000.5440 yuan more than the basic electricity fee according to the unit price.
Therefore, in order to optimally select the electric charge pricing mode and further reduce the electric charge expense of an enterprise, in the implementation of the application, an alternative declaration demand set is determined according to the acquired electric power consumption data, wherein the alternative declaration demand set comprises a plurality of declaration demands, the contract demand expense corresponding to each declaration demand is determined according to the corresponding contract demand pricing formula, the lowest contract demand expense is determined from the contract demand fees, the declaration transformer data and the actual electric power consumption are obtained through analysis from the user data, the corresponding capacity expense is obtained based on the transformer data, the corresponding actual demand expense is obtained based on the actual electric power consumption, the optimal expense in the lowest contract demand expense, the capacity expense and the actual demand expense is finally determined, the electric quantity corresponding to the optimal expense is monitored and early-warned as the optimal electric charge pricing mode, and the optimal electric charge pricing mode is selected to help reduce the electric charge expense of the enterprise.
Specifically, the embodiment of the application provides a method for selecting an electricity price payment mode, which is executed by electronic equipment, wherein the electronic equipment can be a server or terminal equipment, and the server can be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server for providing cloud computing service. The terminal device may be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc., but is not limited thereto, and the terminal device and the server may be directly or indirectly connected through a wired or wireless communication manner, which is not limited herein.
Referring to fig. 1, fig. 1 is a method for monitoring and early warning of electric quantity according to an embodiment of the present application, the method includes steps S110, S120, S130, S140, S150, S160, S170, and S180, wherein:
step S110: user data is acquired.
The user data comprises three-phase voltage and current of a user, and the three-phase voltage and current of the transformer in the operation process can be collected by the data collection equipment and sent to the electronic equipment.
Step S120: based on the user data, an alternative reporting demand group is determined.
Step S130: and determining contract demand cost corresponding to each alternative demand based on the alternative declaration demand group.
Specifically, the demand is the average power of the enterprise transformer in the use process, and the demand value can be calculated and known according to the three-phase voltage and current in the user data. The reporting demand group comprises a plurality of reporting demand values, wherein the reporting demand is the reporting demand provided by a user to the power grid when the contract demand value price payment mode is selected. The method has the advantages that the reporting requirement is determined through a plurality of requirement values, so that the method is beneficial to optimizing the selection mode of the reporting requirement, and further, the expenditure of the enterprise electric charge is reduced through the reporting requirement.
Step S140: the minimum contract demand charge is determined based on the plurality of contract demand charges.
Specifically, comparing the calculated multiple contract demand fees to obtain the minimum contract demand fee, when determining the minimum contract demand fee from the multiple contract demand fees, the minimum contract demand fee can be determined according to the contract demand fee sequence by sorting the multiple contract demand fees according to the order from high to low or according to the order from high to low, generating a contract demand fee sequence.
Step S150: and analyzing the user data to obtain declaration transformer data, and obtaining capacity cost according to the declaration transformer data.
Specifically, the declaration transformer data includes the number of enterprise declaration transformers, and the capacity of each transformer. Importing declaration transformer data into a pricing formula according to capacity to obtain capacity cost, wherein the pricing formula is as follows: the declared transformer capacity is the unit price of the basic electric charge capacity, the declared transformer capacity=the number of declared transformers is the capacity of each transformer.
Step S160: and analyzing the user data to obtain the actual electricity consumption, and determining the actual electricity consumption cost according to the actual electricity consumption.
Specifically, the actual electricity demand is the integrated monthly actual electricity demand. The actual demand price calculating formula is: the actual demand value per month is the unit price of the demand.
Step S170: the minimum contract demand cost, the capacity cost and the actual demand cost are compared to determine the optimum cost.
Step S180: and the electric quantity monitoring and early warning corresponding to the optimal cost is used as an optimal electric charge pricing mode.
Specifically, the electric charge pricing mode corresponding to the lowest contract demand charge is to meter according to the contract demand; the electric charge price-calculating mode corresponding to the capacity charge is according to the capacity price-calculating mode; the electric charge price-calculating mode corresponding to the actual demand charge is to price according to the actual demand. The optimal cost is the lowest cost among the minimum contract demand cost, the capacity cost and the actual demand cost, and the optimal electric charge pricing mode is selected by adopting the optimal cost, so that the optimal user can select the electric charge pricing mode, and the electric charge expense of enterprises is reduced.
The electricity consumption of the next year is predicted through the user data, and then the electricity fee charging mode of the next year is determined, wherein the user data can be the electricity consumption of the current year.
In the embodiment of the application, an alternative reporting demand group is determined according to the acquired electricity consumption data, wherein the alternative reporting demand group comprises a plurality of reporting demands, the contract demand cost corresponding to each reporting demand is determined according to a corresponding contract demand price calculating formula, the lowest contract demand cost is determined from the plurality of contract demand costs, reporting transformer data and actual electricity consumption are obtained through analysis from user data, the corresponding capacity cost is obtained based on the transformer data, the corresponding actual demand cost is obtained based on the actual electricity consumption, the optimal cost in the lowest contract demand cost, the capacity cost and the actual demand cost is finally determined, and the electric quantity corresponding to the optimal cost is monitored and early warned as an optimal electricity cost calculating mode.
Further, in step S120, based on the user data, the determining the alternative reporting requirement group may specifically include: step S1201 (not shown in the drawings), step S1202 (not shown in the drawings), step S1203 (not shown in the drawings), wherein:
step S1201: and acquiring initial user demand in a plurality of preset time periods.
Specifically, the preset duration may be modified according to the user requirement, and the preset duration may be one week, one month, or one quarter, which is not specifically limited in the embodiment of the present application. When the preset duration is one month, the acquired multiple initial user demands are used for representing the user demands of each month, and then the user demands of the whole year are analyzed through the multiple initial user demands.
Step S1202: the plurality of initial user demands are ordered to form a demand sequence.
Specifically, when sorting according to the multiple initial user demands, a bubbling sorting method, a selection sorting method and a Hill sorting method can be utilized, wherein the bubbling sorting method is that firstly, from the first element in the array comprising the multiple initial user demands to the last element in the array, two adjacent elements in the array are compared, if the element at the left end of the array is larger than the element at the right end of the array, the positions of the two elements in the array are exchanged, so that the element at the rightmost end of the array is the maximum value of all elements in the array element after the operation, and then, the same operation is carried out on all the remaining elements except the rightmost element of the array until the whole array is orderly arranged. In the embodiment of the present application, the specific sorting manner is not specifically limited, as long as the demand sequence can be formed according to a plurality of initial user demands.
Step S1203: and determining an alternative reporting demand group according to the demand sequence.
Specifically, the alternative reporting demand group includes a plurality of reporting demands, and the plurality of reporting demands include a demand mode, a demand average, and a demand maximum, and each reporting demand can characterize a demand sequence condition.
In the embodiment of the application, the initial user demand in a plurality of preset time periods is obtained, the plurality of initial user demand is sequenced to form the demand sequence, the alternative reporting demand group is determined from the demand sequence, and the accuracy of determining the reporting demand is improved by determining the reporting demand from the alternative reporting demand group.
Further, in step S1203, determining the alternative reporting requirement group according to the requirement sequence may specifically include: step S1203a (not shown in the drawings), step S1203b (not shown in the drawings), step S1203c (not shown in the drawings), step S1203d (not shown in the drawings), wherein:
step S1203a: from the demand sequence, a demand mode of the demand sequence is calculated.
Specifically, the demand mode is a statistical term, and the statistical distribution has a numerical value of a significant concentration trend point, which is used for the general level of the demand sequence, and when determining the demand mode in the demand sequence, the number of occurrences of each element in the demand sequence needs to be counted, and the element with the largest number of occurrences is determined as the demand mode.
Step S1203b: from the demand sequence, a demand average of the demand sequence is calculated.
Specifically, the demand average is used to reflect more concentrated central positions in the demand sequence, and is similar to the demand mode, and is used to represent the general level in the demand sequence, unlike the demand mode, which is an element in the demand sequence, but the demand average is not necessarily an element in the demand sequence.
Step S1203c: and calculating the demand maximum value of the demand sequence according to the demand sequence.
Step S1203d: the demand mode, demand average, and demand maximum constitute an alternative reporting demand group.
In particular, the demand maxima are used to characterize the limits of the demand sequence. Alternatively declared demand groups include demand modes, demand averages, and demand maxima.
In the embodiment of the application, the demand mode, the demand average number and the demand maximum value corresponding to the demand sequence are respectively calculated through the demand sequence, the alternative reporting demand group is formed, and the accuracy in determining the reporting demand is improved through a plurality of alternative reporting demands.
Further, the embodiment of the application further comprises:
and if the optimal electricity charge pricing method is a contract demand pricing method, determining the alternative reporting demand corresponding to the lowest contract charge as the target reporting demand.
And sending the target reporting demand to the terminal equipment so that the enterprise reports the target reporting demand to the power grid.
Specifically, when the contract demand metering method is adopted to meter the electric charge, the target declaration demand is required to be provided for the power grid, the power grid draws up the contract after receiving the target declaration demand provided by the enterprise, and when the electric charge is counted, the electric charge is charged according to the contract.
In the embodiment of the application, when the optimal electric charge pricing mode is contract demand pricing sending, the corresponding alternative reporting demand is determined according to the lowest contract cost, and the alternative reporting demand is sent to the terminal equipment, so that related staff can record the alternative reporting demand conveniently, and report to the power grid according to the reporting demand.
Further, in order to optimize the method for selecting the electricity fee charging, the embodiment of the present application further includes a step Sa (not shown in the accompanying drawings), a step Sb (not shown in the accompanying drawings), a step Sc (not shown in the accompanying drawings), and a step Sd (not shown in the accompanying drawings), wherein:
step Sa: historical production order information is extracted from the historical database.
Specifically, the historical database stores production orders for a plurality of times, and the information of the production orders for the past time can be extracted from the historical database according to the date.
Step Sb: and determining the next period production order information according to the past production order information.
Specifically, a plurality of historical production order information is extracted from a historical database to obtain a plurality of months and production order information corresponding to each month, the plurality of months and the corresponding production order information are imported into a preset coordinate system to obtain a line diagram of the months and the production order information, and the production order information of the next period is predicted according to the line diagram.
The method comprises the steps of determining the electric charge pricing mode according to the historical data, and determining the electric charge pricing mode according to the historical data.
Step Sc: and comparing the next period production order information with the current period production order information to obtain a production order difference value.
Step Sd: and determining the difference working time according to the difference value of the production order and the historical working efficiency, and determining the difference value requirement of the difference working time.
Specifically, the difference value of the production order is the difference value between the production order information of the next period and the production order information of the current period, the production difference value can be a positive value or a negative value, and when the production difference value is a positive value, the production order information of the next period is higher than the production order information of the current period, and the production order information is in an ascending trend; when the production difference is negative, the production order information of the next period is lower than that of the current period, and the production order information is in a descending trend.
The difference working time can be obtained through historical working efficiency and production order difference calculation.
The difference value demand is the electricity consumption demand required for producing the difference value, when the production difference value is a positive value, the corresponding electricity consumption demand is a positive value, and when the production difference value is a negative value, the corresponding electricity consumption demand is a negative value.
In the embodiment of the application, the historical production order information is extracted from the historical database, the next-period production order information is predicted according to the historical production order information, the predicted next-period production order information is compared with the current-period production order information to obtain the production order difference value, the difference working time is determined according to the production order difference value and the historical working efficiency, the difference required amount corresponding to the difference working time is obtained, and the accuracy of determining the electric charge pricing mode is improved based on the difference required amount.
Further, step Sa of the embodiment of the present application further includes, after extracting the past production order information from the history database:
according to the production order information of the past times, predicting the electricity consumption of each month in the next period;
comparing the electricity consumption of the preset month with the electricity consumption of each month in the next period to determine a light month, wherein the light month is the month of which the electricity consumption of each month in the next period is lower than the electricity consumption of the preset month;
And according to the power consumption requirement corresponding to the light month, reporting and stopping adjustment is carried out on the capacity of the transformer.
Specifically, the light month is a month with a month electricity consumption amount lower than a preset month electricity consumption amount, wherein the preset month electricity consumption amount can be adjusted according to requirements, and the light month screening method is not particularly limited in the embodiment of the application, so long as the light month can be screened. The reasons for the light month are related to the enterprise production order information.
For example, when the light month is 3 months and 4 months according to the preset month electricity consumption amount, the light month of the next period is 3 months and 4 months, and when the light month of the next period is 3 months and 4 months, the adjustment information is submitted to report and stop adjustment on the capacity of the transformer, so that the electricity consumption amount is reduced.
In the embodiment of the application, the electricity consumption of each month of the past time is determined through the information of the production order of the past time, the electricity consumption of each month of the next past time is predicted according to the electricity consumption of each month of the past time, the light month is determined according to the comparison between the preset electricity consumption and the electricity consumption of each month of the next period, and the power consumption corresponding to the light month is used for reporting and stopping the adjustment of the capacity of the transformer, so that the consumption of the electricity consumption is reduced, and the expenditure of electricity charge is further reduced.
Further, step S180 further includes step S1 (not shown in the drawing), step S2 (not shown in the drawing), and step S3 (not shown in the drawing) after the electric quantity monitoring and early warning corresponding to the best fee is performed as the best fee charging mode, wherein:
step S1: and obtaining the electricity consumption requirement of the next period corresponding to the optimal electricity fee pricing mode.
Step S2: and (5) according to the electricity demand of the next period, establishing a monthly electricity utilization limit value.
Step S3: when the month practical electricity consumption exceeds the month electricity consumption limit value, generating a warning signal, pushing the warning signal to user related equipment, and facilitating the user to adjust the electricity consumption in time.
Specifically, after the optimal electricity fee pricing mode is determined, the periodic electricity consumption needs are conveniently determined according to an electricity fee pricing formula. For example, when the optimal electricity fee pricing mode is to be rated according to contract demand, the electricity demand of the next period can be determined according to the declared demand of the user to the power grid, and the monthly electricity consumption limit value is formulated according to the electricity demand of the next period, and the electricity consumption limit value is formulated according to the part of the contract demand pricing formula, which is 105% of the actual demand of the user, and the price is doubled according to the price of the demand, so that the monthly electricity consumption limit value is formulated in the production process, and when the actual electricity consumption of the month exceeds the monthly electricity consumption limit value, a warning signal is generated, so that the probability that the electricity consumption demand exceeds the monthly limit value is reduced.
In the embodiment of the application, after the electricity consumption of the next period is early warned through the optimal electricity quantity monitoring, the monthly electricity consumption limit value is made according to the electricity consumption of the next period, when the monthly actual electricity consumption exceeds the monthly electricity consumption limit value, the warning information is generated, and the generated warning information is sent to the terminal equipment of the relevant user, so that the relevant user can conveniently adjust the electricity consumption in time, the probability that the electricity consumption exceeds the monthly limit value is reduced, and the expenditure of electricity charge is further reduced.
The foregoing embodiment describes an electric quantity monitoring and early warning method from the aspect of a method flow, and the following embodiment describes an electric quantity monitoring and early warning device from the aspect of a virtual module or a virtual unit, which is specifically described in the following embodiment.
An embodiment of the present application provides a device for monitoring and early warning of electric quantity, as shown in fig. 2, which may specifically include: the acquisition module 210, the alternative determination module 220, the contract cost determination module 230, the minimum contract cost determination module 240, the capacity cost determination module 250, the actual demand cost determination module 260, the optimal cost determination module 270, and the pricing model determination module 280, wherein:
an acquisition module 210, configured to acquire user data;
An alternative determining module 220, configured to determine an alternative reporting requirement group based on the user data;
a contract fee determination module 230, configured to determine a contract demand fee corresponding to each alternative demand based on the alternative reporting demand group;
a determine minimum contract cost module 240 for determining a minimum contract demand cost based on the plurality of contract costs;
the capacity fee determining module 250 is configured to parse the user data to obtain declared transformer data, and obtain capacity fee according to the declared transformer data;
the actual demand cost determination module 260 is configured to parse the user data to obtain an actual electricity demand, and determine an actual demand cost according to the actual electricity demand;
a determine optimal cost module 270 for comparing the minimum contract demand cost, the capacity cost, and the actual demand cost to determine an optimal cost;
the pricing method determining module 280 is configured to pre-warn the electric quantity corresponding to the optimal cost as the optimal electric charge pricing method.
In one possible implementation, the alternative determining module 220 includes:
the initial user demand obtaining unit is used for obtaining initial user demands in a plurality of preset time periods;
the ordering unit is used for ordering the plurality of initial user demands to form a demand sequence;
And the alternative group determining unit is used for determining an alternative reporting demand group according to the demand sequence.
In one possible implementation, determining the alternative set of cells includes:
a mode subunit is determined and used for calculating the demand mode of the demand sequence according to the demand sequence;
determining an average subunit for calculating a demand average of the demand sequence according to the demand sequence;
determining a maximum subunit, configured to calculate a demand maximum value of the demand sequence according to the demand sequence;
and determining an alternative group subunit, wherein the alternative group subunit is used for forming an alternative reporting demand group by the demand mode, the demand average and the demand maximum.
In one possible implementation, the method further includes:
the target reporting demand determining module is used for determining the alternative reporting demand corresponding to the lowest contract cost as the target reporting demand if the optimal electric charge pricing mode is the contract demand pricing mode;
and the sending module is used for sending the target reporting demand to the terminal equipment so that the enterprise reports the target reporting demand to the power grid.
In one possible implementation, the method further includes:
the order information extracting module is used for extracting the production order information of the past times from the historical database;
the prediction module is used for predicting the next period production order information according to the previous production order information;
The comparison module is used for comparing the next period production order information with the current year production order information to obtain a production order difference value;
and the difference determining module is used for determining the difference working time according to the difference of the production order and the historical working efficiency and determining the difference requirement of the difference working time.
In one possible implementation, the method further includes:
the month electricity consumption prediction module is used for predicting the electricity consumption of each month in the next period according to the production order information of the past times;
the light month determining module is used for comparing the electricity consumption required by the preset month with the electricity consumption required by each month in the next period to determine light months, wherein the light months are months in which the electricity consumption required by each month in the next period is lower than the electricity consumption required by the preset month;
and the capacity reduction adjustment module is used for reporting and stopping adjustment of the capacity of the transformer according to the power consumption requirement corresponding to the light month.
In one possible implementation, the method further includes:
the annual electricity consumption acquisition module is used for acquiring the electricity consumption of the next period corresponding to the optimal electricity fee pricing mode;
the limit setting module is used for setting a monthly electricity consumption limit according to the electricity consumption requirement of the next period;
the warning signal generation module is used for generating a warning signal when the monthly actual electricity consumption exceeds the monthly electricity consumption limit value, pushing the warning signal to user related equipment, and facilitating the user to adjust the electricity consumption in time.
In an embodiment of the present application, as shown in fig. 3, an electronic device 300 shown in fig. 3 includes: a processor 301 and a memory 303. Wherein the processor 301 is coupled to the memory 303, such as via a bus 302. Optionally, the electronic device 300 may also include a transceiver 304. It should be noted that, in practical applications, the transceiver 304 is not limited to one, and the structure of the electronic device 300 is not limited to the embodiment of the present application.
The processor 301 may be a CPU (Central Processing Unit ), general purpose processor, DSP (Digital Signal Processor, data signal processor), ASIC (Application Specific Integrated Circuit ), FPGA (Field Programmable Gate Array, field programmable gate array) or other programmable logic device, transistor logic device, hardware components, or any combination thereof. Which may implement or perform the various exemplary logic blocks, modules and circuits described in connection with this disclosure. Processor 301 may also be a combination that implements computing functionality, e.g., comprising one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.
Bus 302 may include a path to transfer information between the components. Bus 302 may be a PCI (Peripheral Component Interconnect, peripheral component interconnect Standard) bus or an EISA (Extended Industry Standard Architecture ) bus, or the like. Bus 302 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in fig. 3, but not only one bus or one type of bus.
The Memory 303 may be, but is not limited to, a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory ) or other type of dynamic storage device that can store information and instructions, an EEPROM (Electrically Erasable Programmable Read Only Memory ), a CD-ROM (Compact Disc Read Only Memory, compact disc Read Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
The memory 303 is used for storing application program codes for executing the inventive arrangements and is controlled to be executed by the processor 301. The processor 301 is configured to execute the application code stored in the memory 303 to implement what is shown in the foregoing method embodiments.
Among them, electronic devices include, but are not limited to: mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and stationary terminals such as digital TVs, desktop computers, and the like. But may also be a server or the like. The electronic device shown in fig. 3 is merely an example and should not be construed to limit the functionality and scope of use of the disclosed embodiments.
Embodiments of the present application provide a computer-readable storage medium having a computer program stored thereon, which when run on a computer, causes the computer to perform the corresponding method embodiments described above. Compared with the related art, in the embodiment of the application, the alternative reporting demand group is determined according to the acquired electricity consumption data, wherein the alternative reporting demand group comprises a plurality of reporting demands, the contract demand cost corresponding to each reporting demand is determined according to the corresponding contract demand price calculating formula, the minimum contract demand cost is determined from the contract demand costs, the reporting transformer data and the actual electricity consumption are obtained through analysis from the user data, the corresponding capacity cost is obtained based on the transformer data, the corresponding actual demand cost is obtained based on the actual electricity consumption, the optimal cost in the minimum contract demand cost, the capacity cost and the actual demand cost is finally determined, and the electric quantity corresponding to the optimal cost is monitored and early-warned as the optimal electricity fee price calculating mode, so that the optimal electricity fee price calculating mode is selected, and the enterprise electricity fee price calculating mode is favorable for reducing the electricity fee expense of an enterprise.
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited in order and may be performed in other orders, unless explicitly stated herein. Moreover, at least some of the steps in the flowcharts of the figures may include a plurality of sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, the order of their execution not necessarily being sequential, but may be performed in turn or alternately with other steps or at least a portion of the other steps or stages.
The foregoing is only a partial embodiment of the present application, and it should be noted that it will be apparent to those skilled in the art that modifications and adaptations can be made without departing from the principles of the present application, and such modifications and adaptations are intended to be comprehended within the scope of the present application.
Claims (9)
1. The electric quantity monitoring and early warning method is characterized by comprising the following steps of:
acquiring user data, wherein the user data comprises three-phase voltage and current of a user, and the user data can be used for acquiring the three-phase voltage and current of the transformer in the process by data acquisition equipment;
Based on the user data, determining an alternative reporting requirement group, wherein the reporting requirement group comprises a plurality of reporting requirement values, the reporting requirement is the average power of the enterprise transformer in the using process, and the reporting requirement values can be obtained according to the three-phase voltage and current calculation in the user data;
determining contract demand cost corresponding to each alternative demand based on the alternative declaration demand group;
determining a minimum contract demand charge based on the plurality of contract demand charges;
acquiring declaration transformer data, and obtaining capacity cost according to the declaration transformer data, wherein the declaration transformer data comprises the number of enterprise declaration transformers and the capacity of each transformer;
acquiring actual electricity consumption, and determining actual demand cost according to the actual electricity consumption, wherein the actual electricity consumption is the accumulation of actual electricity consumption per month;
comparing the minimum contract demand cost, the capacity cost and the actual demand cost to determine an optimal cost;
determining the electric charge pricing method corresponding to the optimal charge as the optimal electric charge pricing method;
acquiring the electricity consumption requirement of the next period corresponding to the optimal electricity charge pricing mode;
According to the electricity demand of the next period, a monthly electricity limit value is formulated;
when the month practical electricity consumption exceeds the month electricity consumption limit value, generating a warning signal, and pushing the warning signal to user related equipment;
wherein, the obtaining the capacity cost according to the declared transformer data comprises: obtaining the number of enterprise reporting transformers and the capacity of each transformer according to the reporting transformer data, and importing the number of the reporting transformers and the capacity of each transformer into a capacity pricing formula to obtain capacity cost, wherein the capacity pricing formula is a capacity cost= (the number of the reporting transformers is equal to the capacity of the transformers) and a basic electricity cost capacity unit price;
the determining the actual demand cost according to the actual electricity demand comprises the following steps: the actual electricity consumption is imported into an actual demand price calculating formula to obtain actual demand cost, wherein the actual demand price calculating formula is as follows: actual demand cost = actual demand value generated per month.
2. The method of claim 1, wherein determining the alternative reporting demand group based on the user data comprises:
acquiring initial user demand in a plurality of preset time periods;
Sequencing the plurality of initial user demands to form a demand sequence;
and determining an alternative reporting demand group according to the demand sequence.
3. The method of claim 2, wherein determining the alternative reporting requirement group according to the requirement sequence comprises:
calculating a demand mode of the demand sequence according to the demand sequence;
calculating a demand average of the demand sequences according to the demand sequences;
calculating a demand maximum value of the demand sequence according to the demand sequence;
the demand mode, the demand average, and the demand maximum form an alternative reporting demand group.
4. The method for monitoring and early warning of electric quantity according to claim 1, further comprising:
if the optimal electricity charge pricing method is a contract demand pricing method, determining an alternative reporting demand corresponding to the lowest contract charge as a target reporting demand;
and sending the target reporting demand to a terminal device so that the enterprise reports the target reporting demand to the power grid.
5. The method for monitoring and early warning of electric quantity according to claim 1, further comprising:
Extracting historical production order information from a historical database;
determining production order information of the next period according to the previous production order information;
comparing the next period production order information with the current year production order information to obtain a production order difference value;
and determining a difference working time according to the difference value of the production order and the historical working efficiency, and determining a difference requirement of the difference working time.
6. The method for monitoring and pre-warning electric quantity according to claim 5, wherein after the step of extracting the historical production order information from the historical database, the method further comprises:
according to the historical production order information, determining the electricity consumption prediction demand of each month in the next period;
comparing the preset monthly electricity consumption requirement with the electricity consumption prediction requirement of each month in the next period to determine a light month, wherein the light month is the month of which the electricity consumption prediction requirement of each month in the next period is lower than the preset monthly electricity consumption requirement;
and according to the power consumption requirement corresponding to the light month, reporting and stopping adjustment is carried out on the capacity of the transformer.
7. An electric quantity monitoring and early warning device is characterized by comprising:
the acquisition module is used for acquiring user data, wherein the user data comprises three-phase voltage and current of a user, and the user data can be acquired by the data acquisition equipment in the process of the transformer;
The alternative determining module is used for determining an alternative reporting demand group based on the user data, wherein the reporting demand group comprises a plurality of reporting demand values, the reporting demand is the average power of the enterprise transformer in the using process, and the reporting demand values can be obtained according to the three-phase voltage and current calculation in the user data;
the contract cost determining module is used for determining contract demand cost corresponding to each alternative demand based on the alternative declaration demand group;
the minimum contract cost determining module is used for determining minimum contract demand cost according to the contract costs;
the capacity charge determining module is used for acquiring declaration transformer data and obtaining capacity charge according to the declaration transformer data, wherein the declaration transformer data comprises the number of enterprise declaration transformers and the capacity of each transformer;
the actual electricity consumption determining module is used for obtaining actual electricity consumption and determining actual electricity consumption cost according to the actual electricity consumption, wherein the actual electricity consumption is the accumulation of the actual electricity consumption per month;
a determining optimal cost module for comparing the minimum contract demand cost, the capacity cost and the actual demand cost to determine an optimal cost;
The charging mode determining module is used for determining the charging mode of the electric charge corresponding to the optimal charge as the optimal charging mode of the electric charge;
the annual electricity consumption acquisition module is used for acquiring the electricity consumption of the next period corresponding to the optimal electricity fee pricing mode;
the limit setting module is used for setting a monthly electricity consumption limit according to the electricity consumption requirement of the next period;
the warning signal generation module is used for generating a warning signal when the monthly actual electricity consumption exceeds the monthly electricity consumption limit value and pushing the warning signal to user related equipment;
the capacity fee determining module is specifically used for obtaining the capacity fee according to the declared transformer data: obtaining the number of enterprise reporting transformers and the capacity of each transformer according to the reporting transformer data, and importing the number of the reporting transformers and the capacity of each transformer into a capacity pricing formula to obtain capacity cost, wherein the capacity pricing formula is a capacity cost= (the number of the reporting transformers is equal to the capacity of the transformers) and a basic electricity cost capacity unit price;
the actual demand cost determining module is specifically used for determining the actual demand cost according to the actual electricity demand: the actual electricity consumption is imported into an actual demand price calculating formula to obtain actual demand cost, wherein the actual demand price calculating formula is as follows: actual demand cost = actual demand value generated per month.
8. An electronic device, comprising:
at least one processor;
a memory;
at least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application configured to: the electrical quantity monitoring and early warning method of any one of claims 1-6 is performed.
9. A computer-readable storage medium, comprising: a computer program stored which can be loaded by a processor and which performs the method according to any of claims 1-6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210971792.1A CN115456346B (en) | 2022-08-12 | 2022-08-12 | Electric quantity monitoring and early warning method and device, electronic equipment and medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210971792.1A CN115456346B (en) | 2022-08-12 | 2022-08-12 | Electric quantity monitoring and early warning method and device, electronic equipment and medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115456346A CN115456346A (en) | 2022-12-09 |
| CN115456346B true CN115456346B (en) | 2023-09-26 |
Family
ID=84297719
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210971792.1A Active CN115456346B (en) | 2022-08-12 | 2022-08-12 | Electric quantity monitoring and early warning method and device, electronic equipment and medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115456346B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116562507A (en) * | 2023-07-05 | 2023-08-08 | 广东鹰视能效科技有限公司 | Electric bill analysis method and system |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109447449A (en) * | 2018-10-19 | 2019-03-08 | 云南电网有限责任公司玉溪供电局 | Big industrial user's basic charge as per installed capacity optimization method |
-
2022
- 2022-08-12 CN CN202210971792.1A patent/CN115456346B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109447449A (en) * | 2018-10-19 | 2019-03-08 | 云南电网有限责任公司玉溪供电局 | Big industrial user's basic charge as per installed capacity optimization method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115456346A (en) | 2022-12-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110418022B (en) | Method and device for adjusting flow package for multiple user identifications | |
| CN115456346B (en) | Electric quantity monitoring and early warning method and device, electronic equipment and medium | |
| Haas et al. | On the economics of storage for electricity: Current state and future market design prospects | |
| CN111126703A (en) | Method and device for predicting maximum power consumption demand of enterprise | |
| CN113125851A (en) | Power consumption statistical method, device, equipment and storage medium | |
| CN109389437B (en) | Pricing method and device of electricity price and terminal | |
| Vonsien et al. | Economic modeling of the economic efficiency of Li-ion battery storage with a special focus on residential PV systems | |
| CN113780625B (en) | User electricity charge prediction method, system, terminal and storage medium | |
| CN108830663B (en) | Electric power customer value evaluation method and system and terminal equipment | |
| CN115187061A (en) | User side green electricity configuration method, device, equipment and storage medium | |
| CN115395621A (en) | Emergency energy storage battery electric energy management method, device, equipment and medium | |
| CN112561150B (en) | Photovoltaic power station generated energy prediction method and device | |
| CN115526455A (en) | Water use analysis method and device, electronic equipment and storage medium | |
| CN115456668A (en) | Data processing method and device based on tiered pricing, equipment and storage medium | |
| CN114462676A (en) | User side energy storage optimization method and system | |
| JP5159686B2 (en) | Electricity use leveling promotion system and promotion method | |
| CN117196543B (en) | Multi-purpose ammeter recharging management method and system based on fund pool | |
| US11734779B2 (en) | Methods of allocating energy generated by a community solar energy system | |
| CN113780630B (en) | Method for realizing form code prediction based on historical electricity consumption data of electricity consumption customer | |
| US11138532B1 (en) | Statistical facility event monitor | |
| EP4120430A1 (en) | Processing device, processing method, and program | |
| CN117649071A (en) | Electric power control method, device, equipment and medium based on carbon emission | |
| CN110912117B (en) | Power balance calculation method and device | |
| CN118071036A (en) | Method and device for determining installation capacity of energy storage equipment and electronic equipment | |
| Niu et al. | The Evaluation Method of Integrated Energy Service Utility for User Demand |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |