CN113285524A - Holographic sensing power dispatching system and method for power line carrier communication - Google Patents

Holographic sensing power dispatching system and method for power line carrier communication Download PDF

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Publication number
CN113285524A
CN113285524A CN202110500472.3A CN202110500472A CN113285524A CN 113285524 A CN113285524 A CN 113285524A CN 202110500472 A CN202110500472 A CN 202110500472A CN 113285524 A CN113285524 A CN 113285524A
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China
Prior art keywords
user
load
power
peak
power grid
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CN202110500472.3A
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CN113285524B (en
Inventor
吴晓政
姚诚
庄方军
马伟阳
刘惺惺
楼建伟
单卡迪
毛子春
周立
陈超
王睿
马青
周蔚
沈嘉平
孙雯
商丽君
吴佳
潘建乔
江锡忠
金烨
朱赟
陈胤彤
畅伟
项思雨
沈建强
沈昆皆
郭松
赵华芳
蒋燕
屠悦斐
沈孝贤
方洁
林弘
沈前
方景辉
沈红峰
张炜
张健
吕一凡
吴伟健
刘晶
陈建华
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Zhejiang Bada Electronic Instruments Co ltd
Jiaxing Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
Pinghu Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
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Zhejiang Bada Electronic Instruments Co ltd
Jiaxing Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
Pinghu Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
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Priority to CN202110500472.3A priority Critical patent/CN113285524B/en
Publication of CN113285524A publication Critical patent/CN113285524A/en
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
    • H02J13/00007—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment using the power network as support for the transmission
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00001—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
    • H02J13/00022—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment using wireless data transmission
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00032—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for
    • H02J13/00036—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for the elements or equipment being or involving switches, relays or circuit breakers
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
    • H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
    • H02J3/144—Demand-response operation of the power transmission or distribution network
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
    • H02J2310/50—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads
    • H02J2310/56—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads characterised by the condition upon which the selective controlling is based
    • H02J2310/58—The condition being electrical
    • H02J2310/60—Limiting power consumption in the network or in one section of the network, e.g. load shedding or peak shaving
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
    • Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
    • Y02B70/3225—Demand response systems, e.g. load shedding, peak shaving
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
    • Y04S20/20—End-user application control systems
    • Y04S20/222—Demand response systems, e.g. load shedding, peak shaving
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
    • Y04S40/12—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment
    • Y04S40/121—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment using the power network as support for the transmission

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Human Computer Interaction (AREA)
  • Supply And Distribution Of Alternating Current (AREA)
  • Cable Transmission Systems, Equalization Of Radio And Reduction Of Echo (AREA)
  • Remote Monitoring And Control Of Power-Distribution Networks (AREA)

Abstract

The invention discloses a holographic sensing electric energy scheduling system and method for power line carrier communication. The problem of lack among the prior art to the accurate real-time load management of low pressure demand side is solved. The intelligent electric energy control system comprises a user side, an electric power operation side and an electric energy control side which are connected through a wireless network, wherein the electric energy control side comprises a concentrator, a plurality of user electric energy collectors and a plurality of intelligent circuit breakers which are used for controlling the on-off of electric appliances in a user room, the concentrator is in communication connection with the electric power operation side and is respectively connected with the collectors, and the collectors are respectively connected with the intelligent circuit breakers in the user room. The power operation terminal analyzes the power consumption conditions of the power grid and the user in the peak power consumption period according to the daily load curve of the power grid and the daily load curve of the user, obtains the user with high matching degree of the power grid and the user in the peak power consumption period, selects the selected time period with the most power consumption in the peak power consumption period matched with the user, and conducts power scheduling in the power scheduling time period of the user. Accurate real-time low pressure demand side's accord with management has been realized.

Description

Holographic sensing power dispatching system and method for power line carrier communication
Technical Field
The invention relates to the technical field of electric power, in particular to a holographic sensing electric energy scheduling system and method for power carrier communication.
Background
With continuous breakthrough recording of the peak value of the electrical load in the whole society, the peak load regulation pressure of the power grid is increasing day by day, and a wider demand response means is urgently needed to be developed in order to liberate the construction and development of multiple high-elasticity power grids. The low-voltage user load curve is highly matched with the power grid load curve, the peak load time periods are coincident, and the time characteristic and the interruptible characteristic meet the construction requirements of multiple high-elasticity power grids.
At present, high-voltage demand side response surrounding a large user is developed, and low-voltage demand side response cannot make timely and effective response in a response time period because precise load remote automatic control cannot be realized, so that large-scale implementation cannot be realized all the time. Although the single-phase cost control electric energy meter has the response control capability, the control function only supports the on-off of the whole household, and the concept of high-quality service is not satisfied.
Disclosure of Invention
The invention mainly solves the problem that accurate real-time load management on a low-voltage demand side is lacked in the prior art, and provides a holographic sensing electric energy scheduling system and method for power line carrier communication.
The technical problem of the invention is mainly solved by the following technical scheme: a holographic sensing power dispatching system for power carrier communication comprises a user terminal, a power operation terminal and a power control terminal which are connected through a wireless network,
the concentrator is in communication connection with the power operation end, the concentrator is respectively connected with the collectors, the collectors are respectively connected with the intelligent circuit breakers in the user room, the concentrator receives a scheduling instruction of the power operation end, sends the scheduling instruction to the corresponding user electric energy collectors through a power line, and sends the scheduling instruction to the corresponding intelligent circuit breakers through the electric energy collectors;
the system comprises a power operation end, a user end and an electric energy control end, wherein the power operation end is used for receiving scheduling information or offer information of the power operation end, and returning offer feedback information to the electric energy control end according to user operation after receiving the offer information;
the power operation terminal distributes users needing power dispatching, analyzes power consumption peak period power consumption conditions of the power grid and the users according to the power grid daily load curve and the user daily load curve, obtains the users with high power consumption peak period curve matching degree of the power grid and the users, selects the selected time period with the most power consumption in the power consumption peak period matched with the users as the power dispatching time period of the users, and converts the dispatching time period into an instruction to be issued to the intelligent circuit breaker of the corresponding user for power dispatching.
The power operation end sends an instruction to control the user intelligent circuit breaker to be disconnected in response time during power consumption peak, transfers idle load of users, releases flexible power consumption load, enhances power grid peak capacity, greatly relieves load pressure during power consumption peak period, achieves the effects of peak clipping and valley filling, energy saving and emission reduction, improves equipment utilization rate and reduces power transmission and distribution infrastructure investment. The invention is based on the power line carrier communication technology, realizes the management of the intelligent circuit breaker of the tail end circuit by receiving the instruction through the power line broadband carrier channel, only needs to change the original circuit breaker of the user electric appliance into the intelligent circuit breaker, does not need to greatly transform equipment, and realizes the accurate remote automatic control of the load for the user. Because the matching degree of the daily load curves of most users and the daily load curves of the power grid is high, and the peak load time periods are overlapped more, the users with high matching degree of the daily load curves of the users and the daily load curves of the power grid are found out by comparing the daily load curves of the users and the daily load curves of the power grid, the power consumption peak loads of the users are overlapped more with the peak loads of the power grid, the users are screened out to carry out switching-off control in the power consumption peak time period, and the power consumption peak time loads of the power grid can be relieved more accurately and better. The users participating in the power dispatching are users who have entered into an agreement with the national network or who have received an offer.
A holographic sensing electric energy scheduling method for power line carrier communication comprises the following steps:
s1, a power operation end sets a load to be dispatched, wherein the load comprises a signed user load and an invitation user load, and candidate invitation users are determined through invitation; calculating the dynamic scheduling time period of the invited user;
s2, acquiring historical daily load data of the power grid and the candidate invited users, normalizing, and fitting a power grid daily load curve and a user daily load curve on the same coordinate system;
s3, setting a peak time period, selecting a power grid peak area on a power grid daily load curve section in the peak time period by adopting a square frame, and selecting a user peak area on a user daily load curve by adopting the square frame;
s4, acquiring a power grid peak area and a user peak area which are coincident, calculating the coincidence degree, and screening out a peak area with the coincidence degree greater than N1 to be recorded as a candidate peak area;
s5, finding out an overlapping part of a candidate peak area and a curve in the power grid peak area, calculating the area ratio of the overlapping part, recording the area ratio as the matching degree of the load of the user power consumption peak and the power grid peak area, screening out the candidate peak area with the load matching degree larger than N2, recording as an invitation peak area, and recording a user corresponding to the invitation peak area as an invitation user;
s6, selecting a set time interval with the most power consumption in an invitation peak area as a scheduling time interval of the invitation user, and generating a user dynamic scheduling instruction;
and S7, generating a fixed scheduling instruction according to a fixed time interval, sending the fixed scheduling instruction to the intelligent circuit breaker of the subscriber, and sending a dynamic scheduling instruction to the intelligent circuit breaker of the subscriber. The fixed time period is a time period preset in the peak time period of the power grid, for example, 18 to 20 points, and subscribers are scheduled at fixed time each day.
According to the invention, users with higher matching degree of the power utilization peak period curve are found by comparing the user daily load curve with the power grid daily load curve, the power utilization peak load of the part of users is overlapped with the power grid peak load more, and the part of users are screened out to carry out brake opening control in the power utilization peak period, so that the power grid power utilization peak period load can be relieved more accurately and better.
Preferably, step S1 includes:
s11, the power operation terminal sets loads to be scheduled, calculates the loads of the signed users according to the number of the signed users, and calculates the loads of the invited users by subtracting the loads of the signed users; the load to be scheduled can be adjusted regularly according to the situation through direct setting. And the next day load value can be predicted in advance through load prediction, and then the set power grid load threshold value is subtracted according to the power grid operation condition to calculate the load to be scheduled. The users who have installed the intelligent circuit breakers are regarded as schedulable users, the users participate in electric energy scheduling in two modes of signing and inviting, the signing mode is used for signing an agreement with a power supply enterprise, and the power supply enterprise can cut off and transmit power in a set scheduling period. The invitation mode is that the power supply enterprise sends invitation information to a user terminal of a user, the invitation information comprises a time period required to be switched off, the user operates on the user terminal to confirm receiving of the invitation and feed back the confirmation information to the power utilization enterprise, and the power supply enterprise cuts off and transmits power in the calculated scheduling time period.
S12, the power operation end sends invitation information to a user end of a non-signed user;
and S13, the user side returns offer feedback information to the power operation side according to user operation, whether the offer feedback information is an agreement or not is judged, and the user with the feedback information as the agreement is determined as a candidate offer user.
As a preferable scheme, the specific process of step S2 includes:
s21, acquiring load historical data of a power grid and a user in the past n days, acquiring the load historical data at set time points to obtain sampling data, wherein the time points are separated by delta t minutes, and averaging the sampling data at the same time point every day of the history to respectively obtain daily average sampling data Ai of the power grid and daily average sampling data Bi of the user, i =1, 2 … …, k = 1440/[ delta ] t; the sample data record form includes time points and corresponding load values.
S23, obtaining the maximum value A of the daily average sampling data set Ai of the power gridmaxAnd a minimum value AminSelecting the load more than and closest to A with 500 ten thousand kw as unit loadmaxThe load value is determined as the upper limit value of the daily load of the power grid, and the load value is selected to be less than and closest to AminThe load value is determined as the lower limit value of the daily load of the power grid, and the maximum value B of the daily average data set Bi adopted by the user is obtainedmaxAnd minimum value BminSelecting the load of 1kw as the unit load, which is greater than and closest to BmaxDetermining the upper limit value of the daily load of the user, and selecting the value which is less than and closest to BminThe load value of the user is determined as the lower limit value of the daily load of the user;
and S24, respectively carrying out normalization processing on the daily average sampling data set Ai of the power grid and the daily average sampling data Bi of the user, and respectively fitting a daily load curve of the power grid and a daily load curve of the user in the same coordinate system according to the processed data.
As a preferable scheme, the selecting of the power grid peak area in step S3 includes:
s311, setting a peak period according to historical daily load data of the power grid;
s312, obtaining a maximum value HA on a daily load curve section of a power grid in a peak period, setting an end value DA, DA = HA-C, wherein C is a peak difference value, the peak difference value is 20% of an upper limit value of a coordinate X axis, searching points equal to the end value DA along the load curve on two sides of the maximum value H, and marking the points as a left end value DALAnd a right end value DAR；
S313, drawing a square frame by taking the left end point and the right end point as two bottom angles and the maximum value HA as the top, wherein the area surrounded by the square frame is a power grid peak area.
As a preferred scheme, the process of selecting the user peak area comprises the following steps:
s321, searching a maximum HB on a daily load curve, and judging whether the maximum HB is greater than a peak threshold M1, wherein M1 is 60% of an upper limit value of a coordinate X axis, if not, ending the process of selecting a user peak area, and if so, entering the next step;
s322, setting an end value DB, DB = HB-C, wherein C is a peak difference value which is 20% of an upper limit value of a coordinate X axis, searching points which are equal to the end value DB along a load curve at two sides of the maximum value HB, and marking as a left end value DBLAnd a right end value DBR；
S323, judging left end value DBLAnd a right end value DBRWhether the time t between the first and second steps is greater than a time threshold M2, if yes, the process proceeds to step S324, and if no, the process proceeds to step S325; the time threshold M2 is set to 2 hours and the scheduling period is set to 2 hours, and scheduling is not facilitated when the peak area time width is less than 2 hours.
S324, drawing a square frame by taking the left end point and the right end point as two bottom angles and the maximum HB as the top, wherein the area surrounded by the square frame is a user peak area;
and S325, removing the selected user peak area, and repeating the steps S31-S33 on the rest daily load curves until all user peak areas are found.
As a preferable scheme, the process of determining the left end value and the right end value in step S322 further includes:
when one end is located in or crosses over another peak area, the abscissa of the end is set as the abscissa of the end of the adjacent other peak area, and the ordinate of the end is set as the ordinate of the other end.
As a preferable scheme, the specific process of step S4 includes:
s41, screening out the coincident power grid peak area and user peak area pair, and detecting the coincident area of the power grid peak area and the user peak area;
and S42, calculating the contact ratio of the overlapping area, wherein the contact ratio = (the area of the overlapping area/the area of the power grid peak area) × 100%, judging whether the contact ratio is greater than N1, and if so, marking the peak area as a candidate peak area. N1 is preferably set to 50%, when the coincidence degree of the peak area of the user and the peak area of the power grid is less than 50%, the curve coincidence part in the coincidence area is less, the matching degree is not high, and some users which obviously do not meet the conditions are eliminated through the coincidence degree.
As a preferable scheme, the specific process of step S5 includes:
s51, acquiring the overlapping part of the daily load curve of the power grid and the daily load curve of the user in the overlapping area, and calculating the volume of the overlapping part;
s52, calculating the area ratio of the overlapped part, wherein the area ratio of the overlapped part = (the area of the overlapped part/the area of a power grid peak area) × 100%, and recording as the matching degree Q of the load of the user power consumption peak and the power grid peak area; the matching degree reflects whether the power load condition of a user is close to the power load condition of the power grid or not in the peak time period of the power grid, the higher the matching degree is, the higher the power load of the user is in the peak time period of the power grid, and the user is also in the peak time period of the load, so that the power utilization scheduling is carried out on the user, the load can be effectively reduced, and the load pressure in the peak time period of the power grid is relieved; and when the matching degree is low, the power load of the user is low in the peak time of the power grid, the load for scheduling and reducing the user is small, and the effect of relieving the load pressure in the peak time of the power grid is small. The matching degree is used for selecting users whose peak time electricity load conditions are close to the electricity load conditions of the power grid, so that the effect of relieving the load pressure of the power grid in the peak time is more obvious.
And S53, judging whether the matching degree is greater than N2, and if so, recording the user corresponding to the user peak area as an invited user.
In addition, all the inviting users are obtained, calculation is carried out according to the regulation and control of each inviting user by 1kW, the actual inviting electric load is obtained, the actual inviting electric load is compared with the set inviting electric load, if the actual inviting electric load is larger than the set inviting electric load, the inviting users are sorted according to the matching degree Q, the inviting users are selected from high to low according to the matching degree Q, and electric energy scheduling control is carried out on the selected inviting users.
As a preferable scheme, the specific process of step S6 includes:
s61, setting a detection frame, wherein the width of the detection frame is the length of a set time interval; preferably, the set period of time is 2 hours in duration.
S62, moving a detection frame in an invitation peak area by taking a unit time point as a step length, and recording the part of the overlapped part in the detected frame as a scheduling part;
and S63, calculating the area of each scheduling part, selecting the scheduling part with the largest area, and recording the time period corresponding to the selected scheduling part as the scheduling time period of the invited user. And selecting the part with the maximum electric load within 2 hours in the overlapping part as a scheduling part, and acquiring two endpoint time points of a scheduling part time period and recording the two endpoint time points as a scheduling time period.
Therefore, the invention has the advantages that:
accurate real-time low pressure demand side's accord with management has been realized.
The intelligent circuit breaker of the user is controlled to be disconnected in response time by sending an instruction in the power utilization peak, the idle load of the user is transferred, the flexible power utilization load is released, the power grid peak capacity is enhanced, the load pressure in the power utilization peak period is greatly relieved, peak clipping and valley filling are achieved, energy is saved, emission is reduced, the equipment utilization rate is improved, and the power transmission and distribution infrastructure investment is reduced.
By comparing the daily load curve of the user with the daily load curve of the power grid, the users with higher curve matching degree in the power utilization peak period are found, the power utilization peak loads of the users are overlapped with the peak loads of the power grid more, the users are screened out to carry out brake opening control in the power utilization peak period, and the load of the power grid in the power utilization peak period can be relieved more accurately and better.
The intelligent circuit breaker management system has the advantages that the carrier communication technology is utilized to receive instructions to achieve management of the intelligent circuit breaker of the tail end circuit, only the original circuit breaker of the user electrical appliance needs to be replaced by the intelligent circuit breaker, large transformation of equipment is not needed, and accurate remote automatic load control is achieved for users.
Drawings
FIG. 1 is a block diagram of one configuration of the present invention;
FIG. 2 is a graph of the daily load of the grid;
FIG. 3 is a graph of user daily load;
fig. 4 is a graph of the combination of the daily load curve of the power grid and the daily load curve of the user in the present invention.
1-user side 2-electric power operation end 3-electric energy control end 4-concentrator 5-electric energy collector 6-intelligent short-circuiting device.
Detailed Description
The technical scheme of the invention is further specifically described by the following embodiments and the accompanying drawings.
Example (b):
in this embodiment, a holographic sensing power scheduling system for power carrier communication is shown in fig. 1, and includes a user side 1, a power operation side 2, and a power control side 3 connected via a wireless network, where the power control side includes a concentrator 5, a plurality of user power collectors 5, and an intelligent circuit breaker 6 for controlling on/off of an electrical appliance in a plurality of users. The concentrator is connected with the electric power operation end through a wireless network, the concentrator is respectively connected with each collector through an electric power transmission line, the collectors are respectively connected with each indoor intelligent circuit breaker through the electric power transmission line, and the intelligent circuit breakers are connected with electrical sockets or electrical circuits needing to be regulated and controlled.
The concentrator receives a scheduling instruction of the power operation end, sends the scheduling instruction to the corresponding user electric energy collector through a power line, and sends the scheduling instruction to the corresponding intelligent circuit breaker by the electric energy collector;
the system comprises a power operation end, a user end and an electric energy control end, wherein the power operation end is used for receiving scheduling information or offer information of the power operation end, and returning offer feedback information to the electric energy control end according to user operation after receiving the offer information;
the power operation terminal distributes users needing power dispatching, analyzes power consumption peak period power consumption conditions of the power grid and the users according to the power grid daily load curve and the user daily load curve, obtains the users with high power consumption peak period curve matching degree of the power grid and the users, selects the selected time period with the most power consumption in the power consumption peak period matched with the users as the power dispatching time period of the users, and converts the dispatching time period into an instruction to be issued to the intelligent circuit breaker of the corresponding user for power dispatching.
The power operation end sends an instruction to control the user intelligent circuit breaker to be disconnected in response time during power consumption peak, idle loads of users are transferred, flexible power consumption loads are released, power grid peak capacity is enhanced, load pressure during power consumption peak periods is greatly relieved, peak clipping and valley filling are achieved, energy is saved, emission is reduced, equipment utilization rate is improved, and power transmission and distribution infrastructure investment is reduced.
The cardinality of low-voltage users is huge, idle loads of the low-voltage users are mobilized, and thousands of households are enabled to participate in the construction of the multi-high-elasticity power grid through low-voltage demand side response to awaken 'sleeping resources', so that the method contributes to huge product value for the all-round evolution to the energy Internet, and has very important practical significance for promoting the construction and development of a multi-element fusion high-elasticity power grid.
The existing low-voltage users in the whole province range are more than 2000 million, the response potential of the low-voltage users is huge, the users have two modes of inviting and signing through the online national network APP to participate in electric energy mobilization, the low-voltage users are enabled to participate in response spontaneously, and a part of non-important electric loads (idle loads) are made.
The intelligent circuit breaker replaces the original ordinary circuit breaker for the user who participates in the electric energy dispatching, and after the power line of registering one's residence is connected into the intelligent circuit breaker, the interconnection and intercommunication with the electric power operation end is automatically realized through power line broadband carrier communication (HPLC) (the same principle as automatic meter searching, the concentrator automatically searches the asset number of the intelligent circuit breaker and communicates with the electric power operation end, establishes the archive of the intelligent circuit breaker, and is automatically matched under the house number). The contract signing mode is that a user signs an agreement with a power supply enterprise, and the power supply enterprise can cut off and transmit power in a set scheduling time period. The invitation mode is that the power supply enterprise sends invitation information to a user terminal of a user, the invitation information comprises a time period required to be switched off, the user operates on the user terminal to confirm receiving of the invitation, the confirmation information is fed back to the power utilization enterprise, and the power supply enterprise cuts off and transmits power in the calculated scheduling time period.
The highest power utilization load of 9628 ten thousand kilowatts in Zhejiang whole society at present is calculated according to 1kW responded by each low-voltage user, and in a response period, the demand response capacity of more than 2000 ten thousand kW can be theoretically formed, which accounts for about 20% of the highest load of the whole province, so that the load pressure in the power utilization peak period can be greatly relieved, the peak clipping and valley filling are achieved, and the effects of energy conservation and emission reduction are achieved. The intelligent switch at the low-voltage demand side awakens 'sleeping resources', and contributes to huge product value for building multiple high-elasticity power grids and comprehensively evolving to an energy internet.
A holographic sensing electric energy scheduling method for power line carrier communication comprises the following steps:
s1, a power operation end sets a load to be dispatched, wherein the load comprises a signed user load and an invitation user load, and candidate invitation users are determined through invitation; calculating the dynamic scheduling time period of the invited user; the method specifically comprises the following steps:
s11, the power operation terminal sets loads to be scheduled, calculates the loads of the signed users according to the number of the signed users, and calculates the loads of the invited users by subtracting the loads of the signed users; the load to be scheduled can be adjusted according to the situation regularly through direct setting, for example, the load to be scheduled is set to be 1000 kW according to the potential power load situation. And the next day of power load can be predicted in advance through load prediction, and then the set power grid load threshold value is subtracted according to the power grid operation condition to calculate the load to be scheduled. In this embodiment, it is assumed that 2000 ten thousand users in the whole province install an intelligent circuit breaker, and total load statistics is performed, that is, total load that can participate in scheduling in a response pool is total, the total load in the response pool includes a load of a contracted user and a load of an invited user, for example, 2000 ten thousand kW in total, the contracted user is 500 ten thousand users, the load of the contracted user is 500 ten thousand kW, and the load that needs to be invited is 1500 ten thousand kW. The load to be scheduled is set to be 1000 ten thousand kW in the present embodiment, and according to the assumption, 500 ten thousand kW is subtracted from the load of the contracted user, and 500 ten thousand kW is left to be invited.
S12, the power operation end sends invitation information to a user end of a non-signed user; not limited to the user, i.e., the remaining 1500 ten thousand users. The user side can be a mobile phone provided with a national network APP.
And S13, after receiving the invitation information by the user, wherein the invitation information comprises information of the local spouse period to be scheduled, and the user selects acceptance or rejection. The user side returns offer feedback information to the power operation side according to user operation, the power operation side judges whether the offer feedback information is an agreement or not, and the user with the feedback information as the agreement is determined as a candidate offer user.
S2, acquiring historical daily load data of the power grid and the candidate invited users, normalizing, and fitting a power grid daily load curve and a user daily load curve on the same coordinate system; the specific process comprises the following steps:
s21, acquiring load history data of the power grid and the user in the past n days, wherein the load history data of the past 30 days is adopted in the embodiment. And acquiring load historical data at set time points to obtain sampling data, wherein the time points are separated by delta t minutes, and the delta t is 20 minutes. Averaging the historical sampling data at the same time point every day to obtain daily average sampling data Ai of a power grid and daily average sampling data Bi of users respectively, wherein i =1, 2 … … and 72; the sample data record form includes time points and corresponding load values.
S23, obtaining the maximum value A of the daily average sampling data set Ai of the power gridmaxAnd a minimum value AminSetting a plurality of load values by taking 500 ten thousand kw as unit load, and selecting the load value which is greater than and closest to AmaxThe load value is determined as the upper limit value of the daily load of the power grid, and the load value is selected to be less than and closest to AminThe load value is determined as the lower limit value of the daily load of the power grid, and the maximum value B of the daily average data set Bi adopted by the user is obtainedmaxAnd minimum value BminSetting a plurality of load values with 1kw as unit load, selecting the load value greater than and closest to BmaxDetermining the upper limit value of the daily load of the user, and selecting the value which is less than and closest to BminThe load value of the user is determined as the lower limit value of the daily load of the user; as shown in a power grid load graph in FIG. 2, load values of 5000 ten thousand kw and 5500 ten thousand kw are set by taking 500 ten thousand kw as unit loadkw … … 9500 ten thousand kw, maximum value AmaxBetween 9000 ten thousand kW and 9500 ten thousand kW, 9500 ten thousand kW is the daily load upper limit value of the power grid, and the minimum value AminAnd the daily load is 4500 ten thousand kW and 5000 ten thousand kW, and 4500 ten thousand kW is the lower limit value of the daily load of the power grid. As shown in the user load graph of fig. 3, the upper limit value of the user daily load of 10kW and the lower limit value of the user daily load of 0 can be obtained.
And S24, respectively carrying out normalization processing on the daily average sampling data set Ai of the power grid and the daily average sampling data Bi of the user, and respectively fitting a daily load curve of the power grid and a daily load curve of the user in the same coordinate system according to the processed data as shown in figure 4. For convenience of explanation, the present embodiment selects approximate curves, and there are curves with larger differences in practical applications.
S3, setting a peak time period, selecting a power grid peak area on a power grid daily load curve section in the peak time period by adopting a square frame, and selecting a user peak area on a user daily load curve by adopting the square frame; selecting a power grid peak area comprises:
s311, setting a peak period according to historical daily load data of the power grid; according to the power grid data research, the power grid load is set to be peak time between 18 o 'clock and 22 o' clock at night, and the peak time is set to be 18:00-22: 00.
S312, obtaining the maximum value HA on the daily load curve section of the power grid in the peak period, setting an end value DA as a point a in FIG. 4, wherein DA = HA-C, C is a peak difference value, the peak difference value is 20% of the upper limit value of the coordinate X axis, searching points which are equal to the end value DA along the load curve on two sides of the maximum value H, and marking the points as left end values DALAnd a right end value DARFinding points a1 and a2 as in fig. 4;
s313, drawing a square frame by taking the left end point and the right end point as two bottom angles and the maximum value HA as the top, wherein the area surrounded by the square frame is a power grid peak area.
The process of selecting the user peak area comprises the following steps:
s321, searching a maximum HB on a daily load curve, judging whether the maximum HB is greater than a peak threshold M1 as shown in a point b in FIG. 4, wherein M1 is 60% of an upper limit value of a coordinate X axis, if not, ending the process of selecting a user peak area, and if so, entering a next step;
s322, setting an end value DB, DB = HB-C, wherein C is a peak difference value which is 20% of an upper limit value of a coordinate X axis, searching points which are equal to the end value DB along a load curve at two sides of the maximum value HB, and marking as a left end value DBLAnd a right end value DBRPoints b1 and b2 in fig. 4;
the process of determining the left and right end values further comprises,
when one end is located in or crosses over another peak area, the abscissa of the end is set as the abscissa of the end of the adjacent other peak area, and the ordinate of the end is set as the ordinate of the other end.
S323, judging left end value DBLAnd a right end value DBRWhether the time t between the first and second steps is greater than a time threshold M2, if yes, the process proceeds to step S324, and if no, the process proceeds to step S325; the time threshold M2 is set to 2 hours and the scheduling period is set to 2 hours, and scheduling is not facilitated when the peak area time width is less than 2 hours.
S324, drawing a square frame by taking the left end point and the right end point as two bottom angles and the maximum HB as the top, wherein the area surrounded by the square frame is a user peak area;
and S325, removing the selected user peak area, and repeating the steps S31-S33 on the rest daily load curves until all user peak areas are found. A peak area a is found in the power load curve as in fig. 4, and then a second peak area c is found based on the second maximum value c.
S4, acquiring a power grid peak area and a user peak area which are coincident, calculating the coincidence degree, and screening out a peak area with the coincidence degree greater than N1 to be recorded as a candidate peak area; n1 is preferably set to 50%, when the coincidence degree of the peak area of the user and the peak area of the power grid is less than 50%, the curve coincidence part in the coincidence area is less, the matching degree is not high, and some users which obviously do not meet the conditions are excluded through the coincidence degree. In this embodiment, the user peak area c is excluded from the power grid peak area, and the user peak area a coincides with the power grid peak area, and the coincidence degree is greater than 50%.
S5, finding out an overlapping part of a candidate peak area and a curve in the power grid peak area, calculating the area ratio of the overlapping part, recording the area ratio as the matching degree of the load of the user power consumption peak and the power grid peak area, screening out the candidate peak area with the load matching degree larger than N2, recording as an invitation peak area, and recording a user corresponding to the invitation peak area as an invitation user; the specific process comprises the following steps:
s51, acquiring an overlapped part of a power grid daily load curve and a user daily load curve in an overlapped area, such as a hatched part in FIG. 4, and calculating the volume of the overlapped part; and calculating the area by adopting the unit lines to divide the overlapped part, connecting the top ends of the unit lines by straight lines to form each trapezoidal strip, and calculating the area of each trapezoidal strip and obtaining the approximate area of the overlapped part.
S52, calculating the area ratio of the overlapped part, wherein the area ratio of the overlapped part = (the area of the overlapped part/the area of a power grid peak area) × 100%, and recording as the matching degree Q of the load of the user power consumption peak and the power grid peak area; the matching degree reflects whether the power load condition of a user is close to the power load condition of the power grid or not in the peak time period of the power grid, the higher the matching degree is, the higher the power load of the user is in the peak time period of the power grid, and the user is also in the peak time period of the load, so that the power utilization scheduling is carried out on the user, the load can be effectively reduced, and the load pressure in the peak time period of the power grid is relieved; and when the matching degree is low, the power load of the user is low in the peak time of the power grid, the load for scheduling and reducing the user is small, and the effect of relieving the load pressure in the peak time of the power grid is small. The matching degree is used for selecting users whose peak time electricity load conditions are close to the electricity load conditions of the power grid, so that the effect of relieving the load pressure of the power grid in the peak time is more obvious.
And S53, judging whether the matching degree is greater than N2, and if so, recording the user corresponding to the user peak area as an invited user. Preferably, N2 is 50%. In addition, all the inviting users are obtained, calculation is carried out according to the regulation and control of each inviting user by 1kW, the actual inviting electric load is obtained, the actual inviting electric load is compared with the set inviting electric load, if the actual inviting electric load is larger than the set inviting electric load, the inviting users are sorted according to the matching degree Q, the inviting users are selected from high to low according to the matching degree Q, and electric energy scheduling control is carried out on the selected inviting users.
S6, selecting a set time interval with the most power consumption in an invitation peak area as a scheduling time interval of the invitation user, and generating a user dynamic scheduling instruction; the specific process comprises the following steps:
s61, setting a detection frame, wherein the width of the detection frame is the length of a set time interval; in the embodiment, the electric energy of the user is scheduled in two hours, the time duration of the set time period is 2 hours, the width of the detection frame is 2 hours, and the height of the detection frame is the height of the overlapping area.
S62, moving a detection frame in an invitation peak area by taking a unit time point as a step length, and recording the part of the overlapped part in the detected frame as a scheduling part; in this embodiment, the detection frame is moved by using 20 minutes as a step length, and a part of the detection frame is detected each time.
And S63, calculating the area of each scheduling part, selecting the scheduling part with the largest area, such as a double-slope part in FIG. 4, and recording the time period corresponding to the selected scheduling part as the scheduling time period of the invited user, wherein the obtained time period is 19:14-21:14 in the figure. And selecting the part with the maximum electric load within 2 hours in the overlapping part as a scheduling part, and acquiring two endpoint time points of a scheduling part time period and recording the two endpoint time points as a scheduling time period.
And S7, generating a fixed scheduling instruction according to a fixed time interval, sending the fixed scheduling instruction to the intelligent circuit breaker of the subscriber, and sending a dynamic scheduling instruction to the intelligent circuit breaker of the subscriber. In the fixed time period, a time period is set in advance in the peak time period of the power grid, for example, 18 to 20 points are selected in the embodiment, and subscribers are scheduled at fixed time every day.
The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications or additions may be made to the described embodiments or alternatives may be employed by those skilled in the art without departing from the spirit or ambit of the invention as defined in the appended claims.
Although the terms user side, power operation side, power control side, concentrator, power collector, etc. are used more often herein, the possibility of using other terms is not excluded. These terms are used merely to more conveniently describe and explain the nature of the present invention; they are to be construed as being without limitation to any additional limitations that may be imposed by the spirit of the present invention.

Claims (10)

1. The utility model provides a holographic perception electric energy dispatch system of power line carrier communication which characterized in that: comprises a user terminal, an electric power operation terminal and an electric energy control terminal which are connected through a wireless network,
the concentrator is in communication connection with the power operation end, the concentrator is respectively connected with the collectors, the collectors are respectively connected with the intelligent circuit breakers in the user room, the concentrator receives a scheduling instruction of the power operation end, sends the scheduling instruction to the corresponding user electric energy collectors through a power line, and sends the scheduling instruction to the corresponding intelligent circuit breakers through the electric energy collectors;
the system comprises a power operation end, a user end and an electric energy control end, wherein the power operation end is used for receiving scheduling information or offer information of the power operation end, and returning offer feedback information to the electric energy control end according to user operation after receiving the offer information;
the power operation terminal distributes users needing power dispatching, analyzes power consumption peak period power consumption conditions of the power grid and the users according to the power grid daily load curve and the user daily load curve, obtains the users with high power consumption peak period curve matching degree of the power grid and the users, selects the selected time period with the most power consumption in the power consumption peak period matched with the users as the power dispatching time period of the users, and converts the dispatching time period into an instruction to be issued to the intelligent circuit breaker of the corresponding user for power dispatching.
2. A method for holographic sensing power scheduling of power carrier communication, using the system of claim 1, comprising the steps of:
s1, a power operation end sets a load to be dispatched, wherein the load comprises a signed user load and an invitation user load, and candidate invitation users are determined through invitation; calculating the dynamic scheduling time period of the invited user;
s2, acquiring historical daily load data of the power grid and the candidate invited users, normalizing, and fitting a power grid daily load curve and a user daily load curve on the same coordinate system;
s3, setting a peak time period, selecting a power grid peak area on a power grid daily load curve section in the peak time period by adopting a square frame, and selecting a user peak area on a user daily load curve by adopting the square frame;
s4, acquiring a power grid peak area and a user peak area which are coincident, calculating the coincidence degree, and screening out a peak area with the coincidence degree greater than N1 to be recorded as a candidate peak area;
s5, finding out an overlapping part of a candidate peak area and a curve in the power grid peak area, calculating the area ratio of the overlapping part, recording the area ratio as the matching degree of the load of the user power consumption peak and the power grid peak area, screening out the candidate peak area with the load matching degree larger than N2, recording as an invitation peak area, and recording a user corresponding to the invitation peak area as an invitation user;
s6, selecting a set time interval with the most power consumption in an invitation peak area as a scheduling time interval of the invitation user, and generating a user dynamic scheduling instruction;
and S7, generating a fixed scheduling instruction according to a fixed time interval, sending the fixed scheduling instruction to the intelligent circuit breaker of the subscriber, and sending a dynamic scheduling instruction to the intelligent circuit breaker of the subscriber.
3. The method according to claim 2, wherein the step S1 specifically includes:
s11, the power operation terminal sets loads to be scheduled, calculates the loads of the signed users according to the number of the signed users, and calculates the loads of the invited users by subtracting the loads of the signed users;
s12, the power operation end sends invitation information to a user end of a non-signed user;
and S13, the user side returns offer feedback information to the power operation side according to user operation, whether the offer feedback information is an agreement or not is judged, and the user with the feedback information as the agreement is determined as a candidate offer user.
4. The method according to claim 2, wherein the step S2 includes the following steps:
s21, acquiring load historical data of a power grid and a user in the past n days, acquiring the load historical data at set time points to obtain sampling data, wherein the time points are separated by delta t minutes, and averaging the sampling data at the same time point every day of the history to respectively obtain daily average sampling data Ai of the power grid and daily average sampling data Bi of the user, i =1, 2 … …, k = 1440/[ delta ] t;
s23, obtaining the maximum value A of the daily average sampling data set Ai of the power gridmaxAnd a minimum value AminSetting a plurality of load values by taking 500 ten thousand kw as unit load, and selecting the load value which is greater than and closest to AmaxThe load value is determined as the upper limit value of the daily load of the power grid, and the load value is selected to be less than and closest to AminThe load value is determined as the lower limit value of the daily load of the power grid, and the maximum value B of the daily average data set Bi adopted by the user is obtainedmaxAnd minimum value BminSetting a plurality of load values with 1kw as unit load, selecting the load value greater than and closest to BmaxDetermining the upper limit value of the daily load of the user, and selecting the value which is less than and closest to BminThe load value of the user is determined as the lower limit value of the daily load of the user;
and S24, respectively carrying out normalization processing on the daily average sampling data set Ai of the power grid and the daily average sampling data Bi of the user, and respectively fitting a daily load curve of the power grid and a daily load curve of the user in the same coordinate system according to the processed data.
5. The method of claim 2, wherein the step S3 of selecting the peak area of the power grid includes:
s311, setting a peak period according to historical daily load data of the power grid;
s312, obtaining a maximum value HA on a daily load curve section of a power grid in a peak period, setting an end value DA, DA = HA-C, wherein C is a peak difference value, the peak difference value is 20% of an upper limit value of a coordinate X axis, and searching a load curve along two sides of the maximum value H to be in phase with the end value DAEqual point, is recorded as the left end value DALAnd a right end value DAR；
S313, drawing a square frame by taking the left end point and the right end point as two bottom angles and the maximum value HA as the top, wherein the area surrounded by the square frame is a power grid peak area.
6. The method of claim 2, wherein the step of selecting the peak user area comprises:
s321, searching a maximum HB on a daily load curve, and judging whether the maximum HB is greater than a peak threshold M1, wherein M1 is 60% of an upper limit value of a coordinate X axis, if not, ending the process of selecting a user peak area, and if so, entering the next step;
s322, setting an end value DB, DB = HB-C, wherein C is a peak difference value which is 20% of an upper limit value of a coordinate X axis, searching points which are equal to the end value DB along a load curve at two sides of the maximum value HB, and marking as a left end value DBLAnd a right end value DBR；
S323, judging left end value DBLAnd a right end value DBRWhether the time t between the first and second steps is greater than a time threshold M2, if yes, the process proceeds to step S324, and if no, the process proceeds to step S325;
s324, drawing a square frame by taking the left end point and the right end point as two bottom angles and the maximum HB as the top, wherein the area surrounded by the square frame is a user peak area;
and S325, removing the selected user peak area, and repeating the steps S31-S33 on the rest daily load curves until all user peak areas are found.
7. The method of claim 6, wherein the step of determining the left end value and the right end value in step S322 further comprises:
when one end is located in or crosses over another peak area, the abscissa of the end is set as the abscissa of the end of the adjacent other peak area, and the ordinate of the end is set as the ordinate of the other end.
8. The method according to claim 2, wherein the step S4 includes the following steps:
s41, screening out the coincident power grid peak area and user peak area pair, and detecting the coincident area of the power grid peak area and the user peak area;
and S42, calculating the contact ratio of the overlapping area, wherein the contact ratio = (the area of the overlapping area/the area of the power grid peak area) × 100%, judging whether the contact ratio is greater than N1, and if so, marking the peak area as a candidate peak area.
9. The method according to claim 2, wherein the step S5 includes the following steps:
s51, acquiring an overlapped part of a power grid daily load curve and a user daily load curve in an overlapped area, and calculating the volume of the overlapped part;
s52, calculating the area ratio of the overlapped part, wherein the area ratio of the overlapped part = (the area of the overlapped part/the area of a power grid peak area) × 100%, and recording as the matching degree Q of the load of the user power consumption peak and the power grid peak area;
and S53, judging whether the matching degree is greater than N2, and if so, recording the user corresponding to the user peak area as an invited user.
10. The method according to claim 4, wherein the step S6 includes the following steps:
s61, setting a detection frame, wherein the width of the detection frame is the length of a set time interval;
s62, moving a detection frame in an invitation peak area by taking a unit time point as a step length, and recording the part of the overlapped part in the detected frame as a scheduling part;
and S63, calculating the area of each scheduling part, selecting the scheduling part with the largest area, and recording the time period corresponding to the selected scheduling part as the scheduling time period of the invited user.
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