CN117081262A - Photovoltaic energy storage battery operation monitoring system based on data analysis - Google Patents
Photovoltaic energy storage battery operation monitoring system based on data analysis Download PDFInfo
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- 238000004146 energy storage Methods 0.000 title claims abstract description 84
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- 238000010248 power generation Methods 0.000 claims abstract description 47
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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
- H02J13/00002—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 monitoring
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/378—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC] specially adapted for the type of battery or accumulator
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
- G06F18/2413—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
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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
- 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
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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
- H02J3/00—Circuit arrangements for AC mains or AC distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/381—Dispersed generators
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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
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/0047—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries with monitoring or indicating devices or circuits
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02S—GENERATION OF ELECTRIC POWER BY CONVERSION OF INFRARED RADIATION, VISIBLE LIGHT OR ULTRAVIOLET LIGHT, e.g. USING PHOTOVOLTAIC [PV] MODULES
- H02S50/00—Monitoring or testing of PV systems, e.g. load balancing or fault identification
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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
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/22—The renewable source being solar energy
- H02J2300/24—The renewable source being solar energy of photovoltaic origin
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- 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
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
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Abstract
The invention belongs to the field of photovoltaic power generation, relates to a data analysis technology, and is used for solving the problem that an existing photovoltaic energy storage battery operation monitoring system needs to consume a large amount of time to conduct abnormality cause investigation after abnormal state occurs; the operation monitoring module is used for monitoring and analyzing the operation state of the photovoltaic energy storage battery: generating a monitoring period, and acquiring the discharge depth of the photovoltaic energy storage battery in each natural day in the monitoring period; the invention can monitor and analyze the operation state of the photovoltaic energy storage battery, and feed back the abnormal degree of the operation state of the photovoltaic energy storage battery through the depth coefficient, thereby timely giving an early warning when the abnormal state occurs.
Description
Technical Field
The invention belongs to the field of photovoltaic power generation, relates to a data analysis technology, and particularly relates to a photovoltaic energy storage battery operation monitoring system based on data analysis.
Background
Photovoltaic power generation is a technology that uses the photovoltaic effect of a semiconductor interface to directly convert light energy into electrical energy. The photovoltaic power generation device mainly comprises three parts of a solar panel (assembly), a controller and an inverter, wherein the main parts are composed of electronic components, solar cells are packaged and protected after being connected in series to form a large-area solar cell assembly, and the photovoltaic power generation device is formed by matching with the components such as a power controller.
The operation monitoring system of the photovoltaic energy storage battery in the prior art can only monitor the operation state of the photovoltaic energy storage battery through the operation parameters of the battery, but the operation state of the photovoltaic energy storage battery is related to a plurality of influencing factors in the photovoltaic power generation system as key equipment in the photovoltaic power generation system, so that the photovoltaic energy storage battery needs to consume a large amount of time to conduct abnormality cause investigation after the state abnormality occurs, and the abnormality treatment efficiency is low.
Disclosure of Invention
The invention aims to provide a photovoltaic energy storage battery operation monitoring system based on data analysis, which is used for solving the problem that the existing photovoltaic energy storage battery operation monitoring system needs to consume a large amount of time to conduct abnormality cause investigation after the occurrence of state abnormality;
the technical problems to be solved by the invention are as follows: how to provide a photovoltaic energy storage battery operation monitoring system based on data analysis, which can perform processing decision analysis when state abnormality occurs.
The aim of the invention can be achieved by the following technical scheme:
the photovoltaic energy storage battery operation monitoring system based on data analysis comprises an operation monitoring module, a photovoltaic productivity monitoring module and a behavior analysis module, wherein the operation monitoring module, the photovoltaic productivity monitoring module and the behavior analysis module are sequentially in communication connection;
the operation monitoring module is used for monitoring and analyzing the operation state of the photovoltaic energy storage battery: generating a monitoring period, obtaining the discharge depth of the photovoltaic energy storage battery in each natural day in the monitoring period, and summing the discharge depth of the photovoltaic energy storage battery in each natural day to obtain an average daily depth value; comparing the average daily depth value with a preset depth threshold value, and judging whether the running state of the photovoltaic energy storage battery in the detection period meets the requirement or not according to the comparison result;
the photovoltaic productivity monitoring module is used for monitoring and analyzing productivity of the photovoltaic power generation system: acquiring a power supply value and a charging value of each natural day in a monitoring period, wherein the power supply value is an electric quantity value for directly supplying power to a photovoltaic power generation system in the natural day, and the charging value is an electric quantity value for charging a photovoltaic energy storage battery by the photovoltaic power generation system in the natural day; marking the natural day as a high-yield day, a balance day, a low-load day or a low-yield day through the power supply value and the charging value; marking the number of the high-yield days, the balance days and the low-yield days in the monitoring period as a high-yield value, a balance value and a low-yield value respectively; the balance coefficient of the monitoring period is obtained by carrying out numerical calculation on the high yield value, the balance value and the low yield value; judging whether the productivity of the photovoltaic power generation system in the monitoring period meets the requirement or not through the balance coefficient;
the behavior analysis module is used for monitoring and analyzing the electricity utilization behavior of the load end of the photovoltaic energy storage battery.
As a preferred embodiment of the present invention, the specific process of comparing the average daily depth value with the preset depth threshold value includes: if the average day depth value is smaller than the depth threshold value, judging that the running state of the photovoltaic energy storage battery in the monitoring period meets the requirement; if the average day depth value is greater than or equal to the depth threshold value, judging that the running state of the photovoltaic energy storage battery in the monitoring period does not meet the requirement, generating a capacity analysis signal and sending the capacity analysis signal to the photovoltaic capacity monitoring module.
As a preferred embodiment of the invention, the specific process of marking the natural day as the high-yield day, balance day, low-yield day or low-yield day comprises the following steps: comparing the power supply value and the charging value with a preset power supply threshold value and a preset charging threshold value respectively: if the power supply value is larger than the power supply threshold value and the charging value is larger than the charging threshold value, marking the corresponding natural day as a high-yield day; if the power supply value is larger than the power supply threshold value and the charging value is smaller than or equal to the charging threshold value, marking the corresponding natural day as balance day; if the power supply value is smaller than or equal to the power supply threshold value and the charging value is larger than the charging threshold value, marking the corresponding natural day as the low-load day; and if the power supply value is smaller than or equal to the power supply threshold value and the charging value is smaller than or equal to the charging threshold value, marking the corresponding natural day as the low-birth day.
As a preferred embodiment of the present invention, the specific process for determining whether the capacity of the photovoltaic power generation system in the monitoring period meets the requirement includes: comparing the balance coefficient of the monitoring period with a preset balance threshold value: if the balance coefficient is smaller than the balance threshold, judging that the capacity of the photovoltaic power generation system in the monitoring period meets the requirement, generating a behavior analysis signal and sending the behavior analysis signal to a behavior analysis module; if the balance coefficient is greater than or equal to the balance threshold, judging that the productivity of the photovoltaic power generation system in the monitoring period does not meet the requirement, generating a yield increase signal and sending the yield increase signal to a mobile phone terminal of a manager.
As a preferred embodiment of the invention, the specific process of monitoring and analyzing the electricity utilization behavior of the load end of the photovoltaic energy storage battery by the behavior analysis module comprises the following steps: marking the sum of the power supply value of the natural day and the discharge amount of the photovoltaic energy storage battery as a load value, summing the load values of all the natural days in the monitoring period, taking an average value to obtain a load coefficient, and comparing the load coefficient of the monitoring period with a preset load threshold value: if the load coefficient is greater than or equal to the load threshold, judging that the load state of the photovoltaic power generation system in the monitoring period does not meet the requirement, generating a load abnormal signal and sending the load abnormal signal to a mobile phone terminal of a manager; and if the load coefficient is smaller than the load threshold value, performing deep analysis.
As a preferred embodiment of the present invention, the specific process of depth analysis includes: marking the ratio of the discharge quantity and the load value of the photovoltaic energy storage battery in the natural days as a discharge coefficient, forming a discharge set by the discharge coefficients of all the natural days, calculating variance of the discharge set to obtain a discharge difference coefficient, summing the discharge coefficients of all the natural days, taking an average value to obtain an occupation coefficient, and comparing the discharge difference coefficient and the occupation coefficient with a preset discharge difference threshold and an occupation threshold respectively: if the deviation coefficient is larger than or equal to the deviation threshold, generating a random power consumption signal and sending the random power consumption signal to a mobile phone terminal of a manager; if the deviation coefficient is smaller than the deviation threshold and the occupation coefficient is larger than or equal to the occupation threshold, generating a behavior abnormality signal and sending the behavior abnormality signal to a mobile phone terminal of a manager; if the slip coefficient is smaller than the slip threshold and the occupancy coefficient is smaller than the occupancy threshold, generating a yield increase signal and sending the yield increase signal to a mobile phone terminal of a manager.
As a preferred embodiment of the present invention, the working method of the photovoltaic energy storage battery operation monitoring system based on data analysis comprises the following steps:
step one: monitoring and analyzing the operation state of the photovoltaic energy storage battery: generating a monitoring period, obtaining the depth of discharge of the photovoltaic energy storage battery in each natural day in the monitoring period, summing the depth of discharge of the photovoltaic energy storage battery in each natural day, taking an average value to obtain a mean-day depth value, and judging whether the running state of the photovoltaic energy storage battery in the monitoring period meets the requirement or not through the mean-day depth value;
step two: monitoring and analyzing the productivity of the photovoltaic power generation system: acquiring a power supply value and a charging value of each natural day in a monitoring period, and marking the natural day as a high-yield day, a low-yield day, a balance day or a low-load day through the power supply value and the charging value;
step three: carrying out numerical calculation on the number of high-yield days, low-yield days, balance days or low-load days in the monitoring period to obtain a balance coefficient, and judging whether the productivity of the photovoltaic power generation system in the monitoring period meets the requirement or not through the balance coefficient;
step four: and monitoring and analyzing the electricity consumption behavior of the load end of the photovoltaic energy storage battery to obtain a load coefficient of a monitoring period, judging whether the load state of the photovoltaic power generation system in the monitoring period meets the requirement or not through the load coefficient, generating a random electricity consumption signal, an abnormal behavior signal or a yield increase signal through the difference coefficient and the occupation coefficient when the load state meets the requirement, and sending the random electricity consumption signal, the abnormal behavior signal or the yield increase signal to a mobile phone terminal of a manager.
The invention has the following beneficial effects:
1. the operation monitoring module is used for monitoring and analyzing the operation state of the photovoltaic energy storage battery, the depth coefficient is obtained by analyzing the discharge depth of the photovoltaic energy storage battery in each natural day in the monitoring period, and the abnormal degree of the operation state of the photovoltaic energy storage battery is fed back through the depth coefficient, so that early warning is timely carried out when the state is abnormal;
2. the photovoltaic energy capacity monitoring module can monitor and analyze the energy capacity of the photovoltaic power generation system, the natural day is marked by the power supply value and the charging value of the natural day, then the numerical calculation is carried out according to the marking result to obtain a balance coefficient, and the electric quantity output state of the photovoltaic power generation system is fed back through the balance coefficient;
3. the behavior analysis module can monitor and analyze the electricity consumption behavior of the load end of the photovoltaic energy storage battery, the overall load capacity of the load end in a monitoring period is monitored through the load coefficient, meanwhile, the regularity and the abnormality of the electricity consumption behavior of the load end are analyzed through the deviation coefficient and the occupation coefficient, and corresponding processing decision signals are generated according to analysis results, so that the abnormality processing efficiency is improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a system block diagram of a first embodiment of the present invention;
fig. 2 is a flowchart of a method according to a second embodiment of the invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
As shown in fig. 1, the operation monitoring system of the photovoltaic energy storage battery based on data analysis comprises an operation monitoring module, a photovoltaic productivity monitoring module and a behavior analysis module, wherein the operation monitoring module, the photovoltaic productivity monitoring module and the behavior analysis module are sequentially in communication connection.
The operation monitoring module is used for monitoring and analyzing the operation state of the photovoltaic energy storage battery: generating a monitoring period, obtaining the discharge depth of the photovoltaic energy storage battery in each natural day in the monitoring period, and summing the discharge depth of the photovoltaic energy storage battery in each natural day to obtain an average daily depth value; comparing the average daily depth value with a preset depth threshold value: if the average day depth value is smaller than the depth threshold value, judging that the running state of the photovoltaic energy storage battery in the monitoring period meets the requirement; if the average day depth value is greater than or equal to the depth threshold value, judging that the running state of the photovoltaic energy storage battery in the monitoring period does not meet the requirement, generating a capacity analysis signal and sending the capacity analysis signal to the photovoltaic capacity monitoring module; the operation state of the photovoltaic energy storage battery is monitored and analyzed, the depth coefficient is obtained by analyzing the discharge depth of the photovoltaic energy storage battery in each natural day in a monitoring period, and the abnormal degree of the operation state of the photovoltaic energy storage battery is fed back through the depth coefficient, so that early warning is timely carried out when the state is abnormal.
The photovoltaic productivity monitoring module is used for monitoring and analyzing productivity of the photovoltaic power generation system: acquiring a power supply value and a charging value of each natural day in a monitoring period, wherein the power supply value is an electric quantity value for directly supplying power to a photovoltaic power generation system in the natural day, and the charging value is an electric quantity value for charging a photovoltaic energy storage battery by the photovoltaic power generation system in the natural day; comparing the power supply value and the charging value with a preset power supply threshold value and a preset charging threshold value respectively: if the power supply value is larger than the power supply threshold value and the charging value is larger than the charging threshold value, marking the corresponding natural day as a high-yield day; if the power supply value is larger than the power supply threshold value and the charging value is smaller than or equal to the charging threshold value, marking the corresponding natural day as balance day; if the power supply value is smaller than or equal to the power supply threshold value and the charging value is larger than the charging threshold value, marking the corresponding natural day as the low-load day; if the power supply value is smaller than or equal to the power supply threshold value and the charging value is smaller than or equal to the charging threshold value, marking the corresponding natural day as a low-birth day; marking the number of the high-yield days, the balance days and the low-yield days in the monitoring period as a high-yield value, a balance value and a low-yield value respectively; obtaining a balance coefficient of a monitoring period through a formula PH= (alpha 1 x CD+alpha 2 x JY)/(alpha 3 x CG+M), wherein PH, CG, JY and CD in the formula are respectively values of the balance coefficient, a high yield value, a balance value and a low yield value, the balance coefficient is a value reflecting the overall power generation state of the photovoltaic power generation system in the monitoring period, and the smaller the value of the balance coefficient is, the better the overall power generation state of the photovoltaic power generation system in the monitoring period is; wherein, alpha 1, alpha 2 and alpha 3 are all proportional coefficients, alpha 1 > alpha 2 > alpha 3 > 1, M is the number of natural days in the monitoring period; comparing the balance coefficient of the monitoring period with a preset balance threshold value: if the balance coefficient is smaller than the balance threshold, judging that the capacity of the photovoltaic power generation system in the monitoring period meets the requirement, generating a behavior analysis signal and sending the behavior analysis signal to a behavior analysis module; if the balance coefficient is greater than or equal to the balance threshold value, judging that the productivity of the photovoltaic power generation system in the monitoring period does not meet the requirement, generating a yield increase signal and sending the yield increase signal to a mobile phone terminal of a manager; and monitoring and analyzing the productivity of the photovoltaic power generation system, marking the natural day through a power supply value and a charging value of the natural day, then carrying out numerical calculation according to a marking result to obtain a balance coefficient, and feeding back the electric quantity output state of the photovoltaic power generation system through the balance coefficient.
The behavior analysis module is used for monitoring and analyzing the electricity utilization behavior of the load end of the photovoltaic energy storage battery: marking the sum of the power supply value of the natural day and the discharge amount of the photovoltaic energy storage battery as a load value, summing the load values of all the natural days in the monitoring period, taking an average value to obtain a load coefficient, and comparing the load coefficient of the monitoring period with a preset load threshold value: if the load coefficient is greater than or equal to the load threshold, judging that the load state of the photovoltaic power generation system in the monitoring period does not meet the requirement, generating a load abnormal signal and sending the load abnormal signal to a mobile phone terminal of a manager; if the load factor is smaller than the load threshold, performing depth analysis: marking the ratio of the discharge quantity and the load value of the photovoltaic energy storage battery in the natural days as a discharge coefficient, forming a discharge set by the discharge coefficients of all the natural days, calculating variance of the discharge set to obtain a discharge difference coefficient, summing the discharge coefficients of all the natural days, taking an average value to obtain an occupation coefficient, and comparing the discharge difference coefficient and the occupation coefficient with a preset discharge difference threshold and an occupation threshold respectively: if the deviation coefficient is larger than or equal to the deviation threshold, generating a random power consumption signal and sending the random power consumption signal to a mobile phone terminal of a manager; if the deviation coefficient is smaller than the deviation threshold and the occupation coefficient is larger than or equal to the occupation threshold, generating a behavior abnormality signal and sending the behavior abnormality signal to a mobile phone terminal of a manager; if the slip coefficient is smaller than the slip threshold and the occupancy coefficient is smaller than the occupancy threshold, generating a yield increase signal and sending the yield increase signal to a mobile phone terminal of a manager; and meanwhile, the regularity and the abnormality of the electricity consumption behavior of the load end are analyzed through the difference coefficient and the occupation coefficient, and a corresponding processing decision signal is generated according to an analysis result, so that the abnormality processing efficiency is improved.
Example two
As shown in fig. 2, a method for monitoring operation of a photovoltaic energy storage battery based on data analysis includes the following steps:
step one: monitoring and analyzing the operation state of the photovoltaic energy storage battery: generating a monitoring period, obtaining the depth of discharge of the photovoltaic energy storage battery in each natural day in the monitoring period, summing the depth of discharge of the photovoltaic energy storage battery in each natural day, taking an average value to obtain a mean-day depth value, and judging whether the running state of the photovoltaic energy storage battery in the monitoring period meets the requirement or not through the mean-day depth value;
step two: monitoring and analyzing the productivity of the photovoltaic power generation system: acquiring a power supply value and a charging value of each natural day in a monitoring period, and marking the natural day as a high-yield day, a low-yield day, a balance day or a low-load day through the power supply value and the charging value;
step three: carrying out numerical calculation on the number of high-yield days, low-yield days, balance days or low-load days in the monitoring period to obtain a balance coefficient, and judging whether the productivity of the photovoltaic power generation system in the monitoring period meets the requirement or not through the balance coefficient;
step four: and monitoring and analyzing the electricity consumption behavior of the load end of the photovoltaic energy storage battery to obtain a load coefficient of a monitoring period, judging whether the load state of the photovoltaic power generation system in the monitoring period meets the requirement or not through the load coefficient, generating a random electricity consumption signal, an abnormal behavior signal or a yield increase signal through the difference coefficient and the occupation coefficient when the load state meets the requirement, and sending the random electricity consumption signal, the abnormal behavior signal or the yield increase signal to a mobile phone terminal of a manager.
The operation monitoring system of the photovoltaic energy storage battery based on data analysis generates a monitoring period when in operation, obtains the depth of discharge of the photovoltaic energy storage battery in each natural day in the monitoring period, sums the depth of discharge of the photovoltaic energy storage battery in each natural day, averages the depth values to obtain a daily average depth value, and judges whether the operation state of the photovoltaic energy storage battery in the monitoring period meets the requirement or not according to the daily average depth value; acquiring a power supply value and a charging value of each natural day in a monitoring period, and marking the natural day as a high-yield day, a low-yield day, a balance day or a low-load day through the power supply value and the charging value; carrying out numerical calculation on the number of high-yield days, low-yield days, balance days or low-load days in the monitoring period to obtain a balance coefficient, and judging whether the productivity of the photovoltaic power generation system in the monitoring period meets the requirement or not through the balance coefficient; and generating a random power consumption signal, an abnormal behavior signal or a yield increase signal through the deviation coefficient and the occupation coefficient when the load state meets the requirement, and sending the random power consumption signal, the abnormal behavior signal or the yield increase signal to a mobile phone terminal of a manager.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art can be made to the described embodiments without departing from the scope of the invention or from the scope of the invention as defined in the accompanying claims.
The formulas are all formulas obtained by collecting a large amount of data for software simulation and selecting a formula close to a true value, and coefficients in the formulas are set by a person skilled in the art according to actual conditions; such as: the formula ph= (α1×cd+α2×jy)/(α3×cg+m); collecting a plurality of groups of sample data by a person skilled in the art and setting a corresponding balance coefficient for each group of sample data; substituting the set balance coefficient and the acquired sample data into a formula, forming a ternary one-time equation set by any three formulas, screening the calculated coefficient, and taking an average value to obtain values of alpha 1, alpha 2 and alpha 3 of 4.68, 2.52 and 2.17 respectively;
the size of the coefficient is a specific numerical value obtained by quantizing each parameter, so that the subsequent comparison is convenient, and the size of the coefficient depends on the number of sample data and the corresponding balance coefficient is preliminarily set for each group of sample data by a person skilled in the art; as long as the proportional relation between the parameter and the quantized value is not affected, for example, the balance coefficient is proportional to the value of the low-yield value.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (7)
1. The photovoltaic energy storage battery operation monitoring system based on data analysis is characterized by comprising an operation monitoring module, a photovoltaic productivity monitoring module and a behavior analysis module, wherein the operation monitoring module, the photovoltaic productivity monitoring module and the behavior analysis module are sequentially in communication connection;
the operation monitoring module is used for monitoring and analyzing the operation state of the photovoltaic energy storage battery: generating a monitoring period, obtaining the discharge depth of the photovoltaic energy storage battery in each natural day in the monitoring period, and summing the discharge depth of the photovoltaic energy storage battery in each natural day to obtain an average daily depth value; comparing the average daily depth value with a preset depth threshold value, and judging whether the running state of the photovoltaic energy storage battery in the detection period meets the requirement or not according to the comparison result;
the photovoltaic productivity monitoring module is used for monitoring and analyzing productivity of the photovoltaic power generation system: acquiring a power supply value and a charging value of each natural day in a monitoring period, wherein the power supply value is an electric quantity value for directly supplying power to a photovoltaic power generation system in the natural day, and the charging value is an electric quantity value for charging a photovoltaic energy storage battery by the photovoltaic power generation system in the natural day; marking the natural day as a high-yield day, a balance day, a low-load day or a low-yield day through the power supply value and the charging value; marking the number of the high-yield days, the balance days and the low-yield days in the monitoring period as a high-yield value, a balance value and a low-yield value respectively; the balance coefficient of the monitoring period is obtained by carrying out numerical calculation on the high yield value, the balance value and the low yield value; judging whether the productivity of the photovoltaic power generation system in the monitoring period meets the requirement or not through the balance coefficient;
the behavior analysis module is used for monitoring and analyzing the electricity utilization behavior of the load end of the photovoltaic energy storage battery.
2. The system for monitoring operation of a photovoltaic energy storage battery based on data analysis of claim 1, wherein comparing the average daily depth value with a preset depth threshold comprises: if the average day depth value is smaller than the depth threshold value, judging that the running state of the photovoltaic energy storage battery in the monitoring period meets the requirement; if the average day depth value is greater than or equal to the depth threshold value, judging that the running state of the photovoltaic energy storage battery in the monitoring period does not meet the requirement, generating a capacity analysis signal and sending the capacity analysis signal to the photovoltaic capacity monitoring module.
3. The system for monitoring operation of a photovoltaic energy storage battery based on data analysis according to claim 2, wherein the specific process of marking a natural day as a high-yield day, a balance day, a low-yield day or a low-yield day comprises: comparing the power supply value and the charging value with a preset power supply threshold value and a preset charging threshold value respectively: if the power supply value is larger than the power supply threshold value and the charging value is larger than the charging threshold value, marking the corresponding natural day as a high-yield day; if the power supply value is larger than the power supply threshold value and the charging value is smaller than or equal to the charging threshold value, marking the corresponding natural day as balance day; if the power supply value is smaller than or equal to the power supply threshold value and the charging value is larger than the charging threshold value, marking the corresponding natural day as the low-load day; and if the power supply value is smaller than or equal to the power supply threshold value and the charging value is smaller than or equal to the charging threshold value, marking the corresponding natural day as the low-birth day.
4. A photovoltaic energy storage battery operation monitoring system based on data analysis according to claim 3, wherein the specific process of determining whether the capacity of the photovoltaic power generation system in the monitoring period meets the requirement comprises: comparing the balance coefficient of the monitoring period with a preset balance threshold value: if the balance coefficient is smaller than the balance threshold, judging that the capacity of the photovoltaic power generation system in the monitoring period meets the requirement, generating a behavior analysis signal and sending the behavior analysis signal to a behavior analysis module; if the balance coefficient is greater than or equal to the balance threshold, judging that the productivity of the photovoltaic power generation system in the monitoring period does not meet the requirement, generating a yield increase signal and sending the yield increase signal to a mobile phone terminal of a manager.
5. The photovoltaic energy storage battery operation monitoring system based on data analysis according to claim 4, wherein the specific process of monitoring and analyzing the electricity consumption behavior of the load end of the photovoltaic energy storage battery by the behavior analysis module comprises the following steps: marking the sum of the power supply value of the natural day and the discharge amount of the photovoltaic energy storage battery as a load value, summing the load values of all the natural days in the monitoring period, taking an average value to obtain a load coefficient, and comparing the load coefficient of the monitoring period with a preset load threshold value: if the load coefficient is greater than or equal to the load threshold, judging that the load state of the photovoltaic power generation system in the monitoring period does not meet the requirement, generating a load abnormal signal and sending the load abnormal signal to a mobile phone terminal of a manager; and if the load coefficient is smaller than the load threshold value, performing deep analysis.
6. The photovoltaic energy storage battery operation monitoring system based on data analysis according to claim 5, wherein the specific process of deep analysis comprises: marking the ratio of the discharge quantity and the load value of the photovoltaic energy storage battery in the natural days as a discharge coefficient, forming a discharge set by the discharge coefficients of all the natural days, calculating variance of the discharge set to obtain a discharge difference coefficient, summing the discharge coefficients of all the natural days, taking an average value to obtain an occupation coefficient, and comparing the discharge difference coefficient and the occupation coefficient with a preset discharge difference threshold and an occupation threshold respectively: if the deviation coefficient is larger than or equal to the deviation threshold, generating a random power consumption signal and sending the random power consumption signal to a mobile phone terminal of a manager; if the deviation coefficient is smaller than the deviation threshold and the occupation coefficient is larger than or equal to the occupation threshold, generating a behavior abnormality signal and sending the behavior abnormality signal to a mobile phone terminal of a manager; if the slip coefficient is smaller than the slip threshold and the occupancy coefficient is smaller than the occupancy threshold, generating a yield increase signal and sending the yield increase signal to a mobile phone terminal of a manager.
7. The system for monitoring operation of a photovoltaic energy storage battery based on data analysis according to any one of claims 1 to 6, wherein the method for operating the system for monitoring operation of a photovoltaic energy storage battery based on data analysis comprises the steps of:
step one: monitoring and analyzing the operation state of the photovoltaic energy storage battery: generating a monitoring period, obtaining the depth of discharge of the photovoltaic energy storage battery in each natural day in the monitoring period, summing the depth of discharge of the photovoltaic energy storage battery in each natural day, taking an average value to obtain a mean-day depth value, and judging whether the running state of the photovoltaic energy storage battery in the monitoring period meets the requirement or not through the mean-day depth value;
step two: monitoring and analyzing the productivity of the photovoltaic power generation system: acquiring a power supply value and a charging value of each natural day in a monitoring period, and marking the natural day as a high-yield day, a low-yield day, a balance day or a low-load day through the power supply value and the charging value;
step three: carrying out numerical calculation on the number of high-yield days, low-yield days, balance days or low-load days in the monitoring period to obtain a balance coefficient, and judging whether the productivity of the photovoltaic power generation system in the monitoring period meets the requirement or not through the balance coefficient;
step four: and monitoring and analyzing the electricity consumption behavior of the load end of the photovoltaic energy storage battery to obtain a load coefficient of a monitoring period, judging whether the load state of the photovoltaic power generation system in the monitoring period meets the requirement or not through the load coefficient, generating a random electricity consumption signal, an abnormal behavior signal or a yield increase signal through the difference coefficient and the occupation coefficient when the load state meets the requirement, and sending the random electricity consumption signal, the abnormal behavior signal or the yield increase signal to a mobile phone terminal of a manager.
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