CN115796406A - Optimal adjustment method and system for virtual power plant - Google Patents
Optimal adjustment method and system for virtual power plant Download PDFInfo
- Publication number
- CN115796406A CN115796406A CN202310100600.4A CN202310100600A CN115796406A CN 115796406 A CN115796406 A CN 115796406A CN 202310100600 A CN202310100600 A CN 202310100600A CN 115796406 A CN115796406 A CN 115796406A
- Authority
- CN
- China
- Prior art keywords
- power
- total
- information
- time
- battery
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 19
- 238000007405 data analysis Methods 0.000 claims abstract description 47
- 238000003860 storage Methods 0.000 claims abstract description 36
- 230000002159 abnormal effect Effects 0.000 claims abstract description 35
- 230000008859 change Effects 0.000 claims abstract description 23
- 238000004458 analytical method Methods 0.000 claims abstract description 15
- 230000005611 electricity Effects 0.000 claims description 143
- 238000012806 monitoring device Methods 0.000 claims description 10
- 238000005457 optimization Methods 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 abstract description 2
- 238000012423 maintenance Methods 0.000 abstract description 2
- 238000005516 engineering process Methods 0.000 description 5
- 230000008569 process Effects 0.000 description 4
- 230000002776 aggregation Effects 0.000 description 3
- 238000004220 aggregation Methods 0.000 description 3
- 238000004891 communication Methods 0.000 description 3
- 238000004590 computer program Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 238000004146 energy storage Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression 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
- 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
-
- 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—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
-
- 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
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
The invention provides an optimal adjustment method and system for a virtual power plant, which specifically comprise the following steps: the power plant information acquisition module acquires power utilization information generated by a virtual power plant storage system, and transmits the power utilization information to the power plant data analysis module, and the power plant data analysis module analyzes the power utilization information to obtain stored power utilization data; the storage power utilization data are transmitted to a power statistics module, and the power statistics module performs statistics based on the storage power utilization data to obtain battery power utilization reference data; the battery power utilization reference data are transmitted to a power plant data analysis module to analyze the battery, and the battery use condition is judged; the power utilization information generated by the virtual power plant storage system is acquired, the power utilization information is analyzed to obtain power utilization data, calculation and analysis are carried out according to the past power utilization data, the data normal and abnormal information is judged and acquired, power utilization adjustment is carried out on the power change condition or an alarm is carried out through the power alarm module, and maintenance is carried out in time.
Description
Technical Field
The invention relates to the technical field of power plant regulation, in particular to an optimal regulation method and system for a virtual power plant.
Background
The virtual power plant is a power supply coordination management system which realizes the aggregation and coordination optimization of DER (distributed generation) of DGs (distributed generators), energy storage systems, controllable loads, electric vehicles and the like through an advanced information communication technology and a software system and is used as a special power plant to participate in the operation of the power market and a power grid. The core of the virtual plant concept can be summarized as "communication" and "aggregation". The key technologies of the virtual power plant mainly comprise a coordination control technology, an intelligent metering technology and an information communication technology. The most attractive function of the virtual power plant is to enable the aggregation of DER to participate in the operation of the power market and the auxiliary service market, and provide management and auxiliary services for the power distribution network and the power transmission network. The solution of the virtual power plant has great market potential in China, and is undoubtedly a good choice for China facing the contradiction between electric power shortage and low energy efficiency.
In the prior art, an internal storage system of a virtual power plant usually only plays a role of storage in a storage process when the virtual power plant is used, and when the virtual power plant is used for a long time, the internal storage capacity of the storage system changes and cannot be analyzed according to power consumption information generated in the storage process, so that the virtual power plant cannot be adjusted based on the stored power in the working process.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide an optimal adjustment method and an optimal adjustment system for a virtual power plant.
In order to achieve the purpose, the invention is realized by the following technical scheme: an optimal tuning method for a virtual power plant, the tuning method comprising the steps of:
step S1: acquiring power utilization information generated by a virtual power plant storage system, and transmitting the power utilization information to a power plant data analysis module, wherein the power plant data analysis module analyzes the power utilization information to obtain stored power utilization data;
step S2: the storage power utilization data are transmitted to a power statistics module, and the power statistics module performs statistics based on the storage power utilization data to obtain battery power utilization reference data;
and step S3: the battery power utilization reference data are transmitted to a power plant data analysis module to analyze the battery, and the battery use condition is judged;
and step S4: if the power consumption monitoring device is used normally, the normal data is defined as normal information, the normal information is transmitted to the power adjusting module, power consumption adjustment is carried out through the power adjusting module according to the change condition of the power, if the power consumption monitoring device is used abnormally, the abnormal data is defined as abnormal information, the abnormal information is transmitted to the power alarming module, and the power alarming module gives an alarm.
Further, in the step S1, the power consumption information includes time information, battery usage information, and battery charging frequency information; transmitting the time information, the battery use information and the battery charging frequency information to a power plant data analysis module;
the power plant data analysis module receives the time information, the battery use information and the battery charging frequency information for analysis, and the specific analysis steps are as follows:
step S11: acquiring the service time of each charge according to the time information, acquiring the total charging times according to the charging time information, setting the total charging times as n times, and acquiring time values from the first time to the nth time; thereby obtaining a plurality of usage time values;
step S12: acquiring the use frequency information of the battery during one-time charging according to the use information of the battery, acquiring a time value, a current value and a voltage value of each use, and acquiring the total electricity consumption of each use according to the time value, the current value and the voltage value of each use to obtain the total electricity consumption frequency and the total electricity consumption;
step S13: respectively acquiring the total times of electricity consumption and the total amount of electricity consumption used after the first time to the nth time of charging;
step S14: acquiring the working temperature value of the electric battery according to the battery use information; defining the service time value, the total electricity consumption times, the working temperature value and the total electricity consumption as storage electricity consumption data; and transmitting the stored electricity utilization data to the electricity statistics module.
Further, in step S2, when the power statistics module performs statistics, the specific steps are as follows:
step S21: the power counting module receives and counts the service time value, the total electricity utilization times, the working temperature value and the total electricity utilization amount; setting a working interval according to the working temperature value, and setting a first temperature interval, a second temperature interval, a third temperature interval and a fourth temperature interval according to the temperature sequence;
step S22: arranging a plurality of total electricity utilization values according to the total electricity utilization amount in a time sequence in a first temperature interval, a second temperature interval, a third temperature interval or a fourth temperature interval, and acquiring the total electricity utilization times and the service time value of each total electricity utilization value;
step S23: establishing a first plane rectangular coordinate system by taking an abscissa as a time unit and an ordinate as a total electricity utilization value, expressing a plurality of total electricity utilization values in the first plane rectangular coordinate system through coordinate points, and smoothly connecting the plurality of coordinate points in a curve manner to form a total electricity utilization curve chart;
step S24: establishing a second planar rectangular coordinate system by taking the abscissa as a time unit and the ordinate as the total times of electricity utilization, expressing a plurality of total times of electricity utilization in the second planar rectangular coordinate system through coordinate points, and smoothly connecting the plurality of coordinate points by curves to form a total times of electricity utilization curve chart;
step S25: establishing a third plane rectangular coordinate system by taking the abscissa as a time unit and the ordinate as a use time value, expressing a plurality of use time values in the third plane rectangular coordinate system through coordinate points, and smoothly connecting the plurality of coordinate points by curves to form a use time curve graph;
step S26: and defining the total power consumption graph, the total power consumption time graph and the use time graph as the reference data of the battery power consumption.
Further, in the step S3, when performing the analysis, the specific steps are as follows:
step S31: the power plant data analysis module analyzes according to the battery power consumption reference data, and observes the change of the service time value, the total power consumption times and the total power consumption amount along with the change of time and the change of the service time value, the total power consumption times and the total power consumption amount in different temperature intervals;
step S32: judging the relationship between the temperature and the total power consumption according to the rise and fall of the curve, and judging the relationship among the service time value, the total power consumption and the total times of power consumption;
step S33: if the total power consumption is gradually reduced along with the rise of the temperature, judging that the use is abnormal, and if the total power consumption is gradually increased along with the rise of the temperature, judging that the use is normal;
step S34: if the total power consumption is in direct proportion to the service time value, judging that the service is normal, otherwise, judging that the service is abnormal;
step S35: and if the total power consumption and the total power consumption times are in direct proportion all the time, judging that the use is abnormal, and if the total power consumption and the total power consumption times are in inverse proportion, judging that the use is normal.
An optimization and regulation system for a virtual power plant comprises a power plant information acquisition module, a power plant data analysis module, a power statistics module, a power regulation module, a power alarm module and a server; the power plant information acquisition module, the power plant data analysis module, the power statistics module, the power regulation module and the power alarm module are respectively in data connection with the server;
the power plant information acquisition module acquires power utilization information generated by a virtual power plant storage system, and transmits the power utilization information to the power plant data analysis module, and the power plant data analysis module analyzes the power utilization information to obtain stored power utilization data;
the storage power utilization data are transmitted to a power statistics module, and the power statistics module performs statistics based on the storage power utilization data to obtain battery power utilization reference data;
the battery power utilization reference data are transmitted to a power plant data analysis module to analyze the battery, and the battery use condition is judged;
if the power consumption monitoring device is used normally, the normal data is defined as normal information, the normal information is transmitted to the power adjusting module, power consumption adjustment is carried out through the power adjusting module according to the change condition of the power, if the power consumption monitoring device is used abnormally, the abnormal data is defined as abnormal information, the abnormal information is transmitted to the power alarming module, and the power alarming module gives an alarm.
Further, the electricity utilization information includes time information, battery usage information, and battery charging number information; transmitting the time information, the battery use information and the battery charging frequency information to a power plant data analysis module; the power plant data analysis module receives the time information, the battery use information and the battery charging frequency information for analysis;
acquiring the service time of each charge according to the time information, acquiring the total charging times according to the charging time information, setting the total charging times as n times, and acquiring time values from the first time to the nth time; thereby obtaining a plurality of usage time values;
acquiring the use frequency information of the battery during one-time charging according to the use information of the battery, acquiring a time value, a current value and a voltage value of each use, and acquiring the total electricity consumption of each use according to the time value, the current value and the voltage value of each use to obtain the total electricity consumption frequency and the total electricity consumption;
respectively acquiring the total times of electricity consumption and the total amount of electricity consumption used after the first time to the nth time of charging; acquiring the working temperature value of the electric battery according to the battery use information; defining the service time value, the total electricity consumption times, the working temperature value and the total electricity consumption as storage electricity consumption data; and transmitting the stored electricity utilization data to the electricity statistics module.
Further, the power statistics module receives the service time value, the total electricity utilization times, the working temperature value and the total electricity utilization amount for statistics; setting a working interval according to the working temperature value, and setting a first temperature interval, a second temperature interval, a third temperature interval and a fourth temperature interval according to the temperature sequence;
arranging a plurality of total electricity consumption values according to the total electricity consumption in a first temperature interval, a second temperature interval, a third temperature interval or a fourth temperature interval according to the time sequence, and acquiring the total electricity consumption times and the use time value of each total electricity consumption value;
establishing a first plane rectangular coordinate system by taking an abscissa as a time unit and an ordinate as a total electricity consumption value, expressing a plurality of total electricity consumption values in the first plane rectangular coordinate system through coordinate points, and smoothly connecting the plurality of coordinate points by curves to form a total electricity consumption curve;
establishing a second planar rectangular coordinate system by taking the abscissa as a time unit and the ordinate as the total times of electricity utilization, expressing a plurality of total times of electricity utilization in the second planar rectangular coordinate system through coordinate points, and smoothly connecting the plurality of coordinate points by curves to form a total times of electricity utilization curve chart;
establishing a third plane rectangular coordinate system by taking the abscissa as a time unit and the ordinate as a use time value, expressing a plurality of use time values in the third plane rectangular coordinate system through coordinate points, and smoothly connecting the plurality of coordinate points by curves to form a use time curve graph;
and defining the total power consumption curve graph, the total power consumption times curve graph and the service time curve graph as battery power consumption reference data, and transmitting the battery power consumption reference data to the power plant data analysis module.
Further, the power plant data analysis module analyzes according to the battery power consumption reference data, observes the change of the service time value, the total power consumption times and the total power consumption amount along with the change of time and the change of the service time value, the total power consumption times and the total power consumption amount in different temperature intervals, judges the relation between the temperature and the total power consumption amount according to the rise and fall of the curve, and judges the relation between the service time value, the total power consumption amount and the total power consumption times; if the total power consumption quantity is gradually reduced along with the rise of the temperature, the use is judged to be abnormal, if the total power consumption quantity is gradually increased along with the rise of the temperature, the use is judged to be normal, if the total power consumption quantity is in direct proportion to the use time value, the use is judged to be normal, if the total power consumption quantity is in direct proportion to the total power consumption times, the use is judged to be abnormal, if the total power consumption quantity is in inverse proportion to the total power consumption times, the use is judged to be normal.
The invention has the beneficial effects that:
1. the power utilization information generated by the virtual power plant storage system is acquired, the power utilization information is analyzed to obtain power utilization data, calculation and analysis are carried out according to the past power utilization data, the data normal and abnormal information is judged and acquired, power utilization adjustment is carried out on the power change condition or an alarm is carried out through the power alarm module, and maintenance is carried out in time.
2. According to the invention, the total charging times are acquired, the electric quantity is comprehensively analyzed according to the total charging times and the use condition of each time, and the optimization adjustment is carried out according to the analysis result, so that the optimization effect of the virtual power plant is improved.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
FIG. 1 is a schematic block diagram of an optimal regulation system for a virtual power plant of the present invention;
fig. 2 is a method step diagram of an optimal control method for a virtual power plant according to the invention.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further explained by combining the specific embodiments.
In the present invention, please refer to fig. 1 and fig. 2, an optimization and regulation system for a virtual power plant includes a power plant information acquisition module, a power plant data analysis module, a power statistics module, a power regulation module, a power alarm module, and a server; the power plant information acquisition module, the power plant data analysis module, the power statistics module, the power regulation module and the power alarm module are respectively in data connection with the server;
in this embodiment, the power plant information acquisition module acquires power consumption information generated by the virtual power plant storage system, and transmits the power consumption information to the power plant data analysis module, and the power plant data analysis module analyzes the power consumption information to obtain stored power consumption data;
the electricity utilization information comprises time information, battery use information and battery charging frequency information; transmitting the time information, the battery use information and the battery charging frequency information to a power plant data analysis module;
the power plant data analysis module receives the time information, the battery use information and the battery charging frequency information for analysis;
acquiring the service time of each charge according to the time information, acquiring the total charging times according to the charging time information, setting the total charging times as n times, and acquiring time values from the first time to the nth time; thereby obtaining a plurality of usage time values;
acquiring the use frequency information of the battery during one-time charging according to the use information of the battery, acquiring a time value, a current value and a voltage value of each use, and acquiring the total electricity consumption of each use according to the time value, the current value and the voltage value of each use to obtain the total electricity consumption frequency and the total electricity consumption;
respectively acquiring the total times of electricity consumption and the total amount of electricity consumption used after the first time to the nth time of charging;
acquiring the working temperature value of the electric battery according to the battery use information;
defining the service time value, the total electricity consumption times, the working temperature value and the total electricity consumption as storage electricity consumption data; and transmitting the stored electricity utilization data to the electricity statistics module.
The storage power utilization data are transmitted to a power statistics module, and the power statistics module performs statistics based on the storage power utilization data to obtain battery power utilization reference data;
the power statistics module receives the service time value, the total electricity utilization times, the working temperature value and the total electricity utilization amount for statistics; setting a working interval according to the working temperature value, and setting a first temperature interval, a second temperature interval, a third temperature interval and a fourth temperature interval according to the temperature sequence;
arranging a plurality of total electricity utilization values according to the total electricity utilization amount in a time sequence in a first temperature interval, a second temperature interval, a third temperature interval or a fourth temperature interval, and acquiring the total electricity utilization times and the service time value of each total electricity utilization value;
establishing a first plane rectangular coordinate system by taking an abscissa as a time unit and an ordinate as a total electricity consumption value, expressing a plurality of total electricity consumption values in the first plane rectangular coordinate system through coordinate points, and smoothly connecting the plurality of coordinate points by curves to form a total electricity consumption curve;
establishing a second planar rectangular coordinate system by taking the abscissa as a time unit and the ordinate as the total times of electricity utilization, expressing a plurality of total times of electricity utilization in the second planar rectangular coordinate system through coordinate points, and smoothly connecting the plurality of coordinate points by curves to form a total times of electricity utilization curve chart;
establishing a third plane rectangular coordinate system by taking the abscissa as a time unit and the ordinate as a use time value, expressing a plurality of use time values in the third plane rectangular coordinate system through coordinate points, and smoothly connecting the plurality of coordinate points in a curve to form a use time curve graph;
defining a total power consumption curve graph, a total power consumption frequency curve graph and a use time curve graph as battery power consumption reference data;
the battery power utilization reference data are transmitted to a power plant data analysis module to analyze the battery, and the battery use condition is judged;
the power plant data analysis module analyzes according to the battery power consumption reference data, observes the change of the service time value, the total power consumption times and the total power consumption amount along with the change of time and the change of the service time value, the total power consumption times and the total power consumption amount in different temperature intervals, judges the relation between the temperature and the total power consumption amount according to the rise and fall of the curve, and judges the relation among the service time value, the total power consumption amount and the total power consumption times; if the total power consumption quantity is gradually reduced along with the rise of the temperature, judging that the use is abnormal, if the total power consumption quantity is gradually increased along with the rise of the temperature, judging that the use is normal, if the total power consumption quantity is in direct proportion to the use time value, judging that the use is normal, if the total power consumption quantity is in direct proportion to the total power consumption times, judging that the use is abnormal, and if the total power consumption quantity is in inverse proportion to the total power consumption times, judging that the use is normal;
if the power consumption monitoring device is used normally, the normal data is defined as normal information, the normal information is transmitted to the power adjusting module, power consumption adjustment is carried out through the power adjusting module according to the change condition of the power, if the power consumption monitoring device is used abnormally, the abnormal data is defined as abnormal information, the abnormal information is transmitted to the power alarming module, and the power alarming module gives an alarm.
In the invention, an optimal adjustment method for a virtual power plant specifically comprises the following steps when power utilization adjustment is carried out:
step S1: acquiring power utilization information generated by a virtual power plant storage system, and transmitting the power utilization information to a power plant data analysis module, wherein the power plant data analysis module analyzes the power utilization information to obtain stored power utilization data;
the electricity utilization information comprises time information, battery use information and battery charging frequency information; transmitting the time information, the battery use information and the battery charging frequency information to a power plant data analysis module;
the power plant data analysis module receives the time information, the battery use information and the battery charging frequency information for analysis, and the specific analysis steps are as follows:
step S11: acquiring the service time of each charge according to the time information, acquiring the total charging times according to the charging time information, setting the total charging times as n times, and acquiring time values from the first time to the nth time; thereby obtaining a plurality of usage time values;
step S12: acquiring the use frequency information of the battery during one-time charging according to the use information of the battery, acquiring a time value, a current value and a voltage value of each use, and acquiring the total electricity consumption of each use according to the time value, the current value and the voltage value of each use to obtain the total electricity consumption frequency and the total electricity consumption;
step S13: respectively acquiring the total times of electricity consumption and the total amount of electricity consumption used after the first time to the nth time of charging;
step S14: acquiring the working temperature value of the electric battery according to the battery use information; defining the service time value, the total electricity consumption times, the working temperature value and the total electricity consumption as storage electricity consumption data; and transmitting the stored electricity utilization data to the electricity statistics module.
Step S2: the storage power utilization data are transmitted to a power statistics module, and the power statistics module performs statistics based on the storage power utilization data to obtain battery power utilization reference data;
the power statistics module specifically comprises the following steps in the process of counting:
step S21: the power statistics module receives the service time value, the total electricity utilization times, the working temperature value and the total electricity utilization amount for statistics; setting a working interval according to the working temperature value, and setting a first temperature interval, a second temperature interval, a third temperature interval and a fourth temperature interval according to the temperature sequence;
step S22: arranging a plurality of total electricity utilization values according to the total electricity utilization amount in a time sequence in a first temperature interval, a second temperature interval, a third temperature interval or a fourth temperature interval, and acquiring the total electricity utilization times and the service time value of each total electricity utilization value;
step S23: establishing a first plane rectangular coordinate system by taking an abscissa as a time unit and an ordinate as a total electricity consumption value, expressing a plurality of total electricity consumption values in the first plane rectangular coordinate system through coordinate points, and smoothly connecting the plurality of coordinate points by curves to form a total electricity consumption curve;
step S24: establishing a second planar rectangular coordinate system by taking the abscissa as a time unit and the ordinate as the total times of electricity utilization, expressing a plurality of total times of electricity utilization in the second planar rectangular coordinate system through coordinate points, and smoothly connecting the plurality of coordinate points by curves to form a total times of electricity utilization curve chart;
step S25: establishing a third plane rectangular coordinate system by taking the abscissa as a time unit and the ordinate as a use time value, expressing a plurality of use time values in the third plane rectangular coordinate system through coordinate points, and smoothly connecting the plurality of coordinate points by curves to form a use time curve graph;
step S26: defining a total power consumption curve graph, a total power consumption frequency curve graph and a use time curve graph as battery power consumption reference data;
and step S3: the battery power utilization reference data are transmitted to a power plant data analysis module to analyze the battery, and the battery use condition is judged;
when the analysis is carried out, the specific steps are as follows:
step S31: the power plant data analysis module analyzes according to the battery power consumption reference data and observes the change of the service time value, the total power consumption times and the total power consumption amount along with the change of time and the change of the service time value, the total power consumption times and the total power consumption amount in different temperature intervals;
step S32: judging the relationship between the temperature and the total power consumption according to the rise and fall of the curve, and judging the relationship among the service time value, the total power consumption and the total times of power consumption;
step S33: if the total power consumption is gradually reduced along with the rise of the temperature, judging that the use is abnormal, and if the total power consumption is gradually increased along with the rise of the temperature, judging that the use is normal;
step S34: if the total power consumption is in direct proportion to the service time value, judging that the service is normal, otherwise, judging that the service is abnormal;
step S35: if the total power consumption and the total power consumption times are always in direct proportion, judging that the use is abnormal, and if the total power consumption and the total power consumption times are in inverse proportion, judging that the use is normal;
and step S4: if the electricity consumption regulation device is used normally, the normal data is defined as normal information, the normal information is transmitted to the electricity regulation module, electricity consumption regulation is carried out through the electricity regulation module according to the change condition of the electricity quantity, if the electricity consumption regulation device is used abnormally, the abnormal data is defined as abnormal information, the abnormal information is transmitted to the electricity alarm module, and an alarm is sent out through the electricity alarm module.
The above formulas are all the formulas for taking the numerical value of the dimension, the formula is a formula for obtaining the latest real situation by software simulation of collected mass data, the preset parameters in the formula are set by the technical personnel in the field according to the actual situation, if the weight coefficient and the proportion coefficient exist, the set size is a specific numerical value obtained by quantizing each parameter, the subsequent comparison is convenient, and the size of the weight coefficient and the proportion coefficient can be obtained as long as the proportional relation between the parameter and the quantized numerical value is not influenced.
In the above embodiments of the present application, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media having computer-usable program code embodied in the medium.
The above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (8)
1. An optimal regulation method for a virtual power plant, characterized in that it comprises the following steps:
step S1: acquiring power utilization information generated by a virtual power plant storage system, and transmitting the power utilization information to a power plant data analysis module, wherein the power plant data analysis module analyzes the power utilization information to obtain stored power utilization data;
step S2: the storage power utilization data are transmitted to a power statistics module, and the power statistics module performs statistics based on the storage power utilization data to obtain battery power utilization reference data;
and step S3: the battery power utilization reference data are transmitted to a power plant data analysis module to analyze the battery, and the battery use condition is judged;
and step S4: if the power consumption monitoring device is used normally, the normal data is defined as normal information, the normal information is transmitted to the power adjusting module, power consumption adjustment is carried out through the power adjusting module according to the change condition of the power, if the power consumption monitoring device is used abnormally, the abnormal data is defined as abnormal information, the abnormal information is transmitted to the power alarming module, and the power alarming module gives an alarm.
2. The optimal adjustment method for the virtual power plant as claimed in claim 1, wherein in the step S1, the electricity information includes time information, battery usage information and battery charging times information; transmitting the time information, the battery use information and the battery charging frequency information to a power plant data analysis module;
the power plant data analysis module receives the time information, the battery use information and the battery charging frequency information for analysis, and the specific analysis steps are as follows:
step S11: acquiring the service time of each charge according to the time information, acquiring the total charging times according to the charging time information, setting the total charging times as n times, and acquiring time values from the first time to the nth time; thereby obtaining a plurality of usage time values;
step S12: acquiring the use frequency information of the battery during one-time charging according to the use information of the battery, acquiring a time value, a current value and a voltage value of each use, and acquiring the total electricity consumption of each use according to the time value, the current value and the voltage value of each use to obtain the total electricity consumption frequency and the total electricity consumption;
step S13: respectively acquiring the total times of electricity consumption and the total amount of electricity consumption used after the first time to the nth time of charging;
step S14: acquiring the working temperature value of the electric battery according to the battery use information; defining the service time value, the total electricity consumption times, the working temperature value and the total electricity consumption as storage electricity consumption data; and transmitting the stored electricity utilization data to the electricity statistics module.
3. The optimal adjustment method for the virtual power plant according to claim 1, wherein in the step S2, the power statistics module performs statistics, and the specific steps are as follows:
step S21: the power statistics module receives the service time value, the total electricity utilization times, the working temperature value and the total electricity utilization amount for statistics; setting a working interval according to the working temperature value, and setting a first temperature interval, a second temperature interval, a third temperature interval and a fourth temperature interval according to the temperature sequence;
step S22: arranging a plurality of total electricity utilization values according to the total electricity utilization amount in a time sequence in a first temperature interval, a second temperature interval, a third temperature interval or a fourth temperature interval, and acquiring the total electricity utilization times and the service time value of each total electricity utilization value;
step S23: establishing a first plane rectangular coordinate system by taking an abscissa as a time unit and an ordinate as a total electricity consumption value, expressing a plurality of total electricity consumption values in the first plane rectangular coordinate system through coordinate points, and smoothly connecting the plurality of coordinate points by curves to form a total electricity consumption curve;
step S24: establishing a second planar rectangular coordinate system by taking the abscissa as a time unit and the ordinate as the total electricity utilization times, expressing the plurality of total electricity utilization times in the second planar rectangular coordinate system through coordinate points, and smoothly connecting the plurality of coordinate points in a curve manner to form an electricity utilization total time curve chart;
step S25: establishing a third plane rectangular coordinate system by taking the abscissa as a time unit and the ordinate as a use time value, expressing a plurality of use time values in the third plane rectangular coordinate system through coordinate points, and smoothly connecting the plurality of coordinate points by curves to form a use time curve graph;
step S26: and defining the total power consumption graph, the total power consumption time graph and the use time graph as the reference data of the battery power consumption.
4. The optimal adjustment method for the virtual power plant according to claim 1, wherein in the step S3, when performing the analysis, the specific steps are as follows:
step S31: the power plant data analysis module analyzes according to the battery power consumption reference data, and observes the change of the service time value, the total power consumption times and the total power consumption amount along with the change of time and the change of the service time value, the total power consumption times and the total power consumption amount in different temperature intervals;
step S32: judging the relationship between the temperature and the total power consumption according to the rise and fall of the curve, and judging the relationship among the service time value, the total power consumption and the total times of power consumption;
step S33: if the total power consumption is gradually reduced along with the rise of the temperature, judging that the use is abnormal, and if the total power consumption is gradually increased along with the rise of the temperature, judging that the use is normal;
step S34: if the total power consumption is in direct proportion to the service time value, judging that the service is normal, otherwise, judging that the service is abnormal;
step S35: and if the total power consumption and the total power consumption times are in direct proportion all the time, judging that the use is abnormal, and if the total power consumption and the total power consumption times are in inverse proportion, judging that the use is normal.
5. An optimization and regulation system for a virtual power plant is characterized by comprising a power plant information acquisition module, a power plant data analysis module, a power statistics module, a power regulation module, a power alarm module and a server; the power plant information acquisition module, the power plant data analysis module, the power statistics module, the power regulation module and the power alarm module are respectively in data connection with the server;
the power plant information acquisition module acquires power utilization information generated by a virtual power plant storage system, and transmits the power utilization information to the power plant data analysis module, and the power plant data analysis module analyzes the power utilization information to obtain stored power utilization data;
the storage power utilization data are transmitted to a power statistics module, and the power statistics module performs statistics based on the storage power utilization data to obtain battery power utilization reference data;
the battery power utilization reference data are transmitted to a power plant data analysis module to analyze the battery, and the battery use condition is judged;
if the power consumption monitoring device is used normally, the normal data is defined as normal information, the normal information is transmitted to the power adjusting module, power consumption adjustment is carried out through the power adjusting module according to the change condition of the power, if the power consumption monitoring device is used abnormally, the abnormal data is defined as abnormal information, the abnormal information is transmitted to the power alarming module, and the power alarming module gives an alarm.
6. The optimal tuning system for a virtual power plant of claim 5, wherein the electricity usage information comprises time information, battery usage information, and battery charge times information; transmitting the time information, the battery use information and the battery charging frequency information to a power plant data analysis module; the power plant data analysis module receives the time information, the battery use information and the battery charging frequency information for analysis;
acquiring the service time of each charge according to the time information, acquiring the total charging times according to the charging time information, setting the total charging times as n times, and acquiring time values from the first time to the nth time; thereby obtaining a plurality of usage time values;
acquiring the use frequency information of the battery during one-time charging according to the use information of the battery, acquiring a time value, a current value and a voltage value of each use, and acquiring the total electricity consumption of each use according to the time value, the current value and the voltage value of each use to obtain the total electricity consumption frequency and the total electricity consumption;
respectively acquiring the total times of electricity consumption and the total amount of electricity consumption used after the first time to the nth time of charging; acquiring the working temperature value of the electric battery according to the battery use information; defining the service time value, the total electricity consumption times, the working temperature value and the total electricity consumption as storage electricity consumption data; and transmitting the stored electricity utilization data to the electricity statistics module.
7. The optimal adjustment system for the virtual power plant as claimed in claim 6, wherein the power statistics module receives the usage time value, the total number of times of power utilization, the working temperature value and the total amount of power utilization for statistics; setting a working interval according to the working temperature value, and setting a first temperature interval, a second temperature interval, a third temperature interval and a fourth temperature interval according to the temperature sequence;
arranging a plurality of total electricity utilization values according to the total electricity utilization amount in a time sequence in a first temperature interval, a second temperature interval, a third temperature interval or a fourth temperature interval, and acquiring the total electricity utilization times and the service time value of each total electricity utilization value;
establishing a first plane rectangular coordinate system by taking an abscissa as a time unit and an ordinate as a total electricity consumption value, expressing a plurality of total electricity consumption values in the first plane rectangular coordinate system through coordinate points, and smoothly connecting the plurality of coordinate points by curves to form a total electricity consumption curve;
establishing a second planar rectangular coordinate system by taking the abscissa as a time unit and the ordinate as the total times of electricity utilization, expressing a plurality of total times of electricity utilization in the second planar rectangular coordinate system through coordinate points, and smoothly connecting the plurality of coordinate points by curves to form a total times of electricity utilization curve chart;
establishing a third plane rectangular coordinate system by taking the abscissa as a time unit and the ordinate as a use time value, expressing a plurality of use time values in the third plane rectangular coordinate system through coordinate points, and smoothly connecting the plurality of coordinate points by curves to form a use time curve graph;
and defining the total power consumption curve graph, the total power consumption times curve graph and the service time curve graph as battery power consumption reference data, and transmitting the battery power consumption reference data to the power plant data analysis module.
8. The optimal adjustment system for the virtual power plant according to claim 7, wherein the power plant data analysis module analyzes according to the battery power consumption reference data, observes changes of a usage time value, total power consumption times and total power consumption amount along with changes of time and changes of the usage time value, total power consumption times and total power consumption amount in different temperature intervals, judges a relation between temperature and total power consumption amount according to the rise and fall of a curve, and judges a relation between the usage time value, total power consumption amount and total power consumption times; if the total power consumption quantity is gradually reduced along with the rise of the temperature, the use is judged to be abnormal, if the total power consumption quantity is gradually increased along with the rise of the temperature, the use is judged to be normal, if the total power consumption quantity is in direct proportion to the use time value, the use is judged to be normal, if the total power consumption quantity is in direct proportion to the total power consumption times, the use is judged to be abnormal, if the total power consumption quantity is in inverse proportion to the total power consumption times, the use is judged to be normal.
Priority Applications (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310100600.4A CN115796406B (en) | 2023-02-13 | 2023-02-13 | Optimal adjustment method and system for virtual power plant |
| LU504833A LU504833B1 (en) | 2023-02-13 | 2023-06-16 | Optimization regulation method and system for virtual power plant |
| PCT/CN2023/100558 WO2024027351A1 (en) | 2023-02-13 | 2023-06-16 | Optimization and adjustment method and system for virtual power plant |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310100600.4A CN115796406B (en) | 2023-02-13 | 2023-02-13 | Optimal adjustment method and system for virtual power plant |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115796406A true CN115796406A (en) | 2023-03-14 |
| CN115796406B CN115796406B (en) | 2023-04-18 |
Family
ID=85430824
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310100600.4A Active CN115796406B (en) | 2023-02-13 | 2023-02-13 | Optimal adjustment method and system for virtual power plant |
Country Status (3)
| Country | Link |
|---|---|
| CN (1) | CN115796406B (en) |
| LU (1) | LU504833B1 (en) |
| WO (1) | WO2024027351A1 (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116088400A (en) * | 2023-04-10 | 2023-05-09 | 江苏雄越石油机械设备制造有限公司 | Machining control system of wedge type wellhead gate valve |
| CN116566057A (en) * | 2023-05-25 | 2023-08-08 | 浙江浙能能源服务有限公司 | User terminal fault detection system for virtual power plant |
| CN117077978A (en) * | 2023-10-11 | 2023-11-17 | 浙江浙能能源服务有限公司 | Trans-regional new energy storage method and system |
| CN117332236A (en) * | 2023-10-30 | 2024-01-02 | 国网浙江省电力有限公司乐清市供电公司 | Data tracking detection method, device and storage medium for virtual power plant |
| WO2024027351A1 (en) * | 2023-02-13 | 2024-02-08 | 浙江浙能能源服务有限公司 | Optimization and adjustment method and system for virtual power plant |
| CN116566057B (en) * | 2023-05-25 | 2024-04-26 | 浙江浙能能源服务有限公司 | User terminal fault detection system for virtual power plant |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110336274A (en) * | 2019-07-01 | 2019-10-15 | 上海电力学院 | Add the virtual plant operation method of virtual plant adjuster |
| CN110362031A (en) * | 2019-07-02 | 2019-10-22 | 深圳供电局有限公司 | A kind of virtual plant interruption of service risk real-time detecting system and method |
| WO2019223258A1 (en) * | 2018-05-22 | 2019-11-28 | 金龙联合汽车工业（苏州）有限公司 | Method and device for online updating ocv curve of battery |
| CN114239956A (en) * | 2021-12-15 | 2022-03-25 | 国网冀北电力有限公司秦皇岛供电公司 | Resource allocation method and device of virtual power plant and terminal |
| CN114429274A (en) * | 2021-12-21 | 2022-05-03 | 国网浙江省电力有限公司电力科学研究院 | Virtual power plant regulation capacity assessment method and system based on multiple resource aggregation |
| CN115021280A (en) * | 2022-05-30 | 2022-09-06 | 华能桐乡燃机热电有限责任公司 | System and method for AGC load adjustment of optical storage all-in-one machine based on virtual power plant operation mode |
| CN115389958A (en) * | 2022-10-28 | 2022-11-25 | 江苏海铂德能源科技有限公司 | Lithium ion battery operation safety evaluation method and system |
| CN115498640A (en) * | 2022-11-14 | 2022-12-20 | 江苏海铂德能源科技有限公司 | Virtual power plant-based micro-grid energy control method and system |
| CN115684809A (en) * | 2022-11-11 | 2023-02-03 | 浙江浙能能源服务有限公司 | User side power consumption test system based on virtual power plant |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105631599A (en) * | 2015-12-30 | 2016-06-01 | 国网甘肃省电力公司电力科学研究院 | Multi-target operation scheduling method of virtual power plant |
| KR20190105173A (en) * | 2018-02-22 | 2019-09-16 | (주)솔라라이트 | Virtual power plant using energy storage system |
| CN110298594A (en) * | 2019-07-04 | 2019-10-01 | 北京华建网源电力设计研究院有限公司 | A kind of the load automatic regulating system and method for virtual plant |
| JP7380429B2 (en) * | 2020-06-01 | 2023-11-15 | トヨタ自動車株式会社 | Virtual power plant control device |
| CN112001752A (en) * | 2020-08-18 | 2020-11-27 | 四川大学 | Multi-virtual power plant dynamic game transaction behavior analysis method based on limited rationality |
| CN113922368B (en) * | 2021-10-09 | 2023-06-13 | 浙江浙达能源科技有限公司 | Dynamic optimization reorganization method for virtual power plant cluster |
| CN115018554A (en) * | 2022-06-30 | 2022-09-06 | 天津大学 | Virtual power plant secondary frequency modulation method considering comprehensive energy resources |
| CN115563885A (en) * | 2022-11-09 | 2023-01-03 | 大唐（赤峰）新能源有限公司 | Energy conversion system for energy storage battery of wind power plant |
| CN115796406B (en) * | 2023-02-13 | 2023-04-18 | 浙江浙能能源服务有限公司 | Optimal adjustment method and system for virtual power plant |
-
2023
- 2023-02-13 CN CN202310100600.4A patent/CN115796406B/en active Active
- 2023-06-16 WO PCT/CN2023/100558 patent/WO2024027351A1/en unknown
- 2023-06-16 LU LU504833A patent/LU504833B1/en active IP Right Grant
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2019223258A1 (en) * | 2018-05-22 | 2019-11-28 | 金龙联合汽车工业（苏州）有限公司 | Method and device for online updating ocv curve of battery |
| CN110336274A (en) * | 2019-07-01 | 2019-10-15 | 上海电力学院 | Add the virtual plant operation method of virtual plant adjuster |
| CN110362031A (en) * | 2019-07-02 | 2019-10-22 | 深圳供电局有限公司 | A kind of virtual plant interruption of service risk real-time detecting system and method |
| CN114239956A (en) * | 2021-12-15 | 2022-03-25 | 国网冀北电力有限公司秦皇岛供电公司 | Resource allocation method and device of virtual power plant and terminal |
| CN114429274A (en) * | 2021-12-21 | 2022-05-03 | 国网浙江省电力有限公司电力科学研究院 | Virtual power plant regulation capacity assessment method and system based on multiple resource aggregation |
| CN115021280A (en) * | 2022-05-30 | 2022-09-06 | 华能桐乡燃机热电有限责任公司 | System and method for AGC load adjustment of optical storage all-in-one machine based on virtual power plant operation mode |
| CN115389958A (en) * | 2022-10-28 | 2022-11-25 | 江苏海铂德能源科技有限公司 | Lithium ion battery operation safety evaluation method and system |
| CN115684809A (en) * | 2022-11-11 | 2023-02-03 | 浙江浙能能源服务有限公司 | User side power consumption test system based on virtual power plant |
| CN115498640A (en) * | 2022-11-14 | 2022-12-20 | 江苏海铂德能源科技有限公司 | Virtual power plant-based micro-grid energy control method and system |
Non-Patent Citations (4)
| Title |
|---|
| 刘敦楠: "\"面向新型电力系统的灵活能量块交易出清模型\"" * |
| 张叔禹;刘永江;张国斌;郭瑞君;辛晓钢;唐宁宁;陈曦;: "考虑经济性与快速性的虚拟电厂多目标优化调度" * |
| 王之琦;蒋传文;: "基于峰谷分时电价的虚拟电厂日前申报及运行优化" * |
| 王刚: ""储能参与清洁能源消纳价值链优化模型及信息系统研究"" * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2024027351A1 (en) * | 2023-02-13 | 2024-02-08 | 浙江浙能能源服务有限公司 | Optimization and adjustment method and system for virtual power plant |
| CN116088400A (en) * | 2023-04-10 | 2023-05-09 | 江苏雄越石油机械设备制造有限公司 | Machining control system of wedge type wellhead gate valve |
| CN116566057A (en) * | 2023-05-25 | 2023-08-08 | 浙江浙能能源服务有限公司 | User terminal fault detection system for virtual power plant |
| CN116566057B (en) * | 2023-05-25 | 2024-04-26 | 浙江浙能能源服务有限公司 | User terminal fault detection system for virtual power plant |
| CN117077978A (en) * | 2023-10-11 | 2023-11-17 | 浙江浙能能源服务有限公司 | Trans-regional new energy storage method and system |
| CN117332236A (en) * | 2023-10-30 | 2024-01-02 | 国网浙江省电力有限公司乐清市供电公司 | Data tracking detection method, device and storage medium for virtual power plant |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115796406B (en) | 2023-04-18 |
| LU504833B1 (en) | 2024-03-08 |
| WO2024027351A1 (en) | 2024-02-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN115796406B (en) | Optimal adjustment method and system for virtual power plant | |
| Yan et al. | A cost accounting method of the Li-ion battery energy storage system for frequency regulation considering the effect of life degradation | |
| Tang et al. | Estimation and validation of characteristic load profile through smart grid trials in a medium voltage distribution network | |
| CN115498640B (en) | Micro-grid energy control method and system based on virtual power plant | |
| CN103178990A (en) | Network device performance monitoring method and network management system | |
| CN111009895B (en) | Microgrid optimal scheduling method, system and equipment | |
| CN107907759A (en) | The electricity monitoring system and method for power equipment | |
| CN113746138A (en) | Energy storage intelligent energy management system applied to wind storage power station | |
| CN112564179B (en) | Method, system, device and medium for improving and optimizing power distribution network | |
| CN110020752A (en) | Optimized data collection method, apparatus, equipment and the storage medium of many reference amounts monitoring device | |
| Aksanli | Data center peak power management with energy storage devices | |
| CN115684809A (en) | User side power consumption test system based on virtual power plant | |
| Faranda et al. | SCADA system for optimization of energy exchange with the BESS in a residential case | |
| CN206774638U (en) | A kind of large-scale energy-storage system | |
| CN115000985A (en) | Aggregation control method and system for user-side distributed energy storage facilities | |
| CN111654112B (en) | Reactive compensation capacitor early warning method, device and system | |
| CN114844084A (en) | Electric quantity control method and device, storage medium, processor and electronic device | |
| CN116566057B (en) | User terminal fault detection system for virtual power plant | |
| JP7352385B2 (en) | Power management system, power management method and power management program | |
| CN112598272A (en) | Smart power grid management system based on block chain technology | |
| CN116566057A (en) | User terminal fault detection system for virtual power plant | |
| CN116979514B (en) | Intelligent regulation and control system for power consumption | |
| CN111817305B (en) | Power grid operation efficiency post-evaluation method and system for capacity increase of power transmission and transformation equipment | |
| CN115665590B (en) | Internet of things data acquisition system and method based on eSIM card and 5G communication | |
| CN117134332A (en) | Regional division method for virtual power plant operation simulation |
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 |