Photovoltaic energy anomaly detection system based on digital communication

Abstract

The invention discloses a photovoltaic energy anomaly detection system based on digital communication, and the system comprises the steps: constructing a standard operation parameter array of energy equipment, and constructing a historical operation parameter matrix of the energy equipment, calculating a historical overload matrix of the energy equipment based on the historical operation parameter matrix of the energy equipment and the standard operation parameter array of the energy equipment, screening a historical operation overload array, and determining an operation state index of each energy equipment in the historical operation overload array, and judging whether the running state of the energy equipment is in the energy equipment standard running parameter interval, if so, judging that the energy equipment is in a normal running state, and if not, judging that the energy equipment is in an abnormal running state. The system has the advantages that on-line monitoring, analysis and early warning of equipment are realized, and potential safety hazards are reduced.

Description

Technical Field

[0001] The present application relates to the field of robotics, and in particular to a photovoltaic energy anomaly detection system based on digital communication. Background Art

[0002] Photovoltaic (PV) refers to a technology that uses the photovoltaic effect of semiconductor materials to directly convert solar energy into electrical energy. Photovoltaic technology is one of the important ways to achieve solar power generation, and has the advantages of being clean, renewable and pollution-free.

[0003] During operation, photovoltaic equipment is prone to operating in an overload state due to external factors and improper human management, resulting in serious equipment loss. However, as photovoltaic equipment is usually connected in series, slight fluctuations caused by corresponding losses are difficult to detect, and continued operation will increase losses and lead to equipment loss. Summary of the invention

[0004] In order to solve the above technical problems, an efficient testing method for storage chips based on timing analysis is provided. This technical solution solves the above-mentioned problem that photovoltaic equipment is very likely to operate in an overload state due to external factors and improper human management during operation, resulting in serious equipment loss. However, since photovoltaic equipment is usually connected in series, slight fluctuations caused by corresponding losses are not easy to be detected, and continued operation will expand the losses and cause equipment loss.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] A photovoltaic energy anomaly detection system based on digital communication, comprising:

[0007] The standard data acquisition module and the standard comparison module are used to input the standard operating parameters of all energy equipment in the energy system and construct the array of standard operating parameters of energy equipment;

[0008] The historical data acquisition module, the matrix construction module and the standard control module are connected by wires. The matrix construction module is used to obtain the historical operating parameters of all energy devices in the energy system and construct the historical operating parameter matrix of the energy devices.

[0009] A load assessment module, the load assessment module is connected to the standard data acquisition module and the historical data acquisition module by wires, and the load assessment module is used to calculate the historical overload matrix of the energy device based on the historical operation parameter matrix of the energy device and the standard operation parameter array of the energy device;

[0010] A load screening module, the screening module is electrically connected to the load evaluation module, and the screening module is used to screen a historical operating overload matrix based on a historical overload matrix of energy equipment;

[0011] A state evaluation module, the state evaluation module is electrically connected to the load screening module, and the state evaluation module is used to determine the operation state index of each energy device in the historical operation overload array based on the historical operation overload array screened out;

[0012] The abnormal judgment module is electrically connected to the status evaluation module. The abnormal judgment module is used to judge whether the operating status of the energy equipment is within the standard operating parameter range of the energy equipment based on the operating status index of each energy equipment in the historical operating overload array. If so, it is determined that the energy equipment is in a normal operating state; if not, it is determined that the energy equipment is in an abnormal operating state.

[0013] Preferably, the load assessment module specifically includes:

[0014] The load calculation unit calculates the overload index of each set of historical operating parameters based on the standard operating parameter array, and obtains several historical operating parameter overload arrays;

[0015] A matrix construction unit, which arrays several historical operation parameters overload arrays to construct a historical operation load matrix;

[0016] Among them, the overload index of each set of historical operation parameters is calculated, specifically:

[0017]

[0018] Among them, S i For overload array, l ij is the overload index between the jth parameter of the i-th group of historical operating parameters and the standard operating parameters, m is the total number of operating equipment, r ij is the actual load of the jth device of the i-th group of historical operating parameters, g j is the rated load of the jth device;

[0019] Among them, the historical operation load matrix is ​​constructed as follows:

[0020]

[0021] Where M is the historical operating load matrix.

[0022] Preferably, the load screening module specifically includes:

[0023] The overload marking unit selects each energy device whose load index is greater than the rated index based on the historical operating load matrix and marks it as an overloaded device.

[0024] The screening unit constructs a historical operation overload array based on the equipment marked as overloaded;

[0025] Among them, merging the overload indicator array into the historical running overload array is as follows:

[0026]

[0027] Where t is the historical operation overload array, It is an overload energy device whose jth load index is greater than the rated index.

[0028] Preferably, the status assessment module specifically includes:

[0029] The load duration unit determines the overload operation duration in each group where the load index is greater than the rated load based on the historical operation overload array;

[0030] The equipment evaluation unit calculates the status index of each energy equipment based on the overload operation time when the load index in each group is greater than the rated index;

[0031] Among them, the energy equipment status indicators are as follows:

[0032]

[0033] Q is the energy equipment status indicator, ε is the loss coefficient under standard operating conditions, P 基 is the basic loss under standard operating conditions, ε1 is the loss coefficient under overload operating conditions, and p 超 It is the basic loss under overload operation condition.

[0034] Preferably, the abnormality judgment module specifically includes:

[0035] A critical value evaluation unit, which calculates the critical value of energy equipment operation within the standard operating parameter range of the energy equipment based on the standardized parameter array;

[0036] The judgment unit judges whether each energy equipment state indicator is greater than the equipment operation critical value based on the energy equipment operation critical value. If not, it is judged that the energy equipment at that time has no risk hidden danger. If so, it is judged that the current energy equipment has risk hidden danger;

[0037] Among them, the critical values ​​of energy equipment operation are as follows:

[0038]

[0039] U is the critical value of equipment operation.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] The present invention analyzes the historical operating parameters of the energy equipment, takes the maximum load value between the historical operating parameters of the energy equipment and the standard operating parameters of the energy equipment as the worst indicator, and constructs a historical operation overload array for analysis, analyzes the operating status of each energy device after load operation in the historical operation overload array, determines whether there is a risk hidden danger in the current equipment status, realizes online monitoring of the equipment, analyzes early warning, reduces safety hazards, and improves the reliability of the entire system, thereby achieving stable operation and sustainable development of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a framework diagram of a photovoltaic energy anomaly detection system based on digital communication proposed by the present invention;

[0043] Figure 2 A flow chart of a method for calculating a historical overload matrix of energy equipment in the present invention;

[0044] Figure 3 A flow chart of the method for running an overload array for screening history in the present invention;

[0045] Figure 4 A flow chart of a method for determining an operating status index of each energy device in the present invention;

[0046] Figure 5 A flow chart of a method for determining whether the operating state of an energy device is within a standard operating parameter range of the energy device, as proposed by the present invention;

[0047] Figure 6 It is a schematic diagram of the structure of the electronic device of the present invention;

[0048] Figure 7 It is a schematic diagram of the computer-readable storage medium structure of the present invention. DETAILED DESCRIPTION

[0049] In order to better understand the present application, a more detailed description will be made of various aspects of the present application with reference to the accompanying drawings. It should be understood that these detailed descriptions are only descriptions of exemplary embodiments of the present application, and are not intended to limit the scope of the present application in any way. Throughout the specification, the same reference numerals refer to the same elements. The expression "and / or" includes any and all combinations of one or more of the associated listed items.

[0050] In the accompanying drawings, the size, dimensions and shapes of the elements have been slightly adjusted for ease of illustration. The drawings are for illustration only and are not strictly drawn to scale. As used herein, the terms "substantially", "approximately" and similar terms are used as terms of approximation, not as terms of degree, and are intended to illustrate the inherent deviations in measurements or calculations that will be recognized by those of ordinary skill in the art. In addition, in this application, the order in which the steps are described does not necessarily represent the order in which these processes occur in actual operation, unless otherwise specified or can be derived from the context.

[0051] It should also be understood that expressions such as "include", "including", "have", "contain" and / or "comprising" are open rather than closed expressions in this specification, which indicate the presence of the stated features, elements and / or components, but do not exclude the presence of one or more other features, elements, components and / or combinations thereof. In addition, when expressions such as "at least one of..." appear after a list of listed features, they modify the entire list of features rather than just the individual elements in the list. In addition, when describing embodiments of the present application, "may" is used to mean "one or more embodiments of the present application". And, the term "exemplary" is intended to refer to an example or illustration.

[0052] Unless otherwise specified, all words (including engineering terms and scientific and technological terms) used in this article have the same meaning as those commonly understood by ordinary technicians in the field to which this application belongs. It should also be understood that, unless clearly stated in this application, words defined in common dictionaries should be interpreted as having the same meaning as their meaning in the context of the relevant technology, and should not be interpreted in an idealized or overly formal sense.

[0053] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0054] Reference Figure 1 As shown, a photovoltaic energy anomaly detection system based on digital communication includes:

[0055] The standard data acquisition module and the standard comparison module are used to input the standard operating parameters of all energy equipment in the energy system and construct the array of standard operating parameters of energy equipment;

[0056] The historical data acquisition module, the matrix construction module and the standard control module are connected by wires. The matrix construction module is used to obtain the historical operating parameters of all energy devices in the energy system and construct the historical operating parameter matrix of the energy devices.

[0057] A load assessment module, the load assessment module is connected to the standard data acquisition module and the historical data acquisition module by wires, and the load assessment module is used to calculate the historical overload matrix of the energy device based on the historical operation parameter matrix of the energy device and the standard operation parameter array of the energy device;

[0058] A load screening module, the screening module is electrically connected to the load evaluation module, and the screening module is used to screen a historical operating overload matrix based on a historical overload matrix of energy equipment;

[0059] A state evaluation module, the state evaluation module is electrically connected to the load screening module, and the state evaluation module is used to determine the operation state index of each energy device in the historical operation overload array based on the historical operation overload array screened out;

[0060] The abnormal judgment module is electrically connected to the status evaluation module. The abnormal judgment module is used to judge whether the operating status of the energy equipment is within the standard operating parameter range of the energy equipment based on the operating status index of each energy equipment in the historical operating overload array. If so, it is determined that the energy equipment is in a normal operating state; if not, it is determined that the energy equipment is in an abnormal operating state.

[0061] This solution analyzes the historical operating parameters of the energy equipment, takes the maximum load value between the historical operating parameters of the energy equipment and the standard operating parameters of the energy equipment as the worst indicator, and constructs a historical operation overload array for analysis. It analyzes the operating status of each energy equipment in the historical operation overload array after load operation, determines whether there are risks in the current equipment status, realizes online monitoring of the equipment, analyzes early warning, reduces safety hazards, improves the reliability, production efficiency, and cost control of the entire system, thereby achieving stable operation and sustainable development of the system.

[0062] Reference Figure 2 As shown, the calculation of the historical overload matrix of the energy equipment based on the historical operating parameter matrix of the energy equipment and the standard operating parameter array of the energy equipment specifically includes:

[0063] Based on the standard operating parameter array, the overload index of each set of historical operating parameters is calculated to obtain several historical operating parameter overload arrays;

[0064] Overload arrays of several historical operating parameters are used to construct a historical operating load matrix;

[0065] Among them, the overload index of each set of historical operation parameters is calculated, specifically:

[0066]

[0067] Among them, S iFor overload array, l ij is the overload index between the jth parameter of the i-th group of historical operating parameters and the standard operating parameters, m is the total number of operating equipment, r ij is the actual load of the jth device of the i-th group of historical operating parameters, g j is the rated load of the jth device;

[0068] Among them, the historical operation load matrix is ​​constructed as follows:

[0069]

[0070] Where M is the historical operating load matrix.

[0071] Reference Figure 3 As shown, the screening of the historical operation overload matrix based on the historical overload matrix of energy equipment specifically includes:

[0072] Based on the historical operating load matrix, each energy device with a load index greater than the rated index is screened out and marked as an overloaded device.

[0073] Based on the equipment marked as overloaded, a historical overload array is constructed;

[0074] Among them, merging the overload indicator array into the historical running overload array is as follows:

[0075]

[0076] Where t is the historical operation overload array, It is an overload energy device whose jth load index is greater than the rated index.

[0077] It can be understood that based on the standard operating parameter array, the load index of each energy device in each historical operating data is calculated, and according to the standard operating rated load, the overloaded energy equipment that exceeds the standard operating rated load is screened out, and each overloaded equipment is concentrated into a historical operating overload array, which is conducive to subsequent analysis and management and reduces the amount of data processing.

[0078] Reference Figure 4 As shown, the operation status index of each energy device in the historical operation overload array is determined based on screening out the historical operation overload array, and specifically includes:

[0079] Based on the historical operation overload array, determine the overload operation duration in which the load index in each group is greater than the rated load;

[0080] Calculate each energy equipment status indicator based on the overload operation time in which the load indicator in each group is greater than the rated indicator;

[0081] Among them, the energy equipment status indicators are as follows:

[0082]

[0083] Q is the energy equipment status indicator, ε is the loss coefficient under standard operating conditions, P 基 is the basic loss under standard operating conditions, ε1 is the loss coefficient under overload operating conditions, and p 超 It is the basic loss under overload operation condition.

[0084] By obtaining the overload operation time of each energy device in the historical overload array, the energy equipment loss index of each energy device under overload operation is calculated. The equipment loss index can intuitively reflect the equipment performance, operation efficiency, and equipment life of each energy device. The smaller the energy equipment loss index, the smaller the probability of the current energy equipment being within the design operation safety range, and the smaller the probability of potential risks. The larger the energy equipment loss index, the larger the probability of the current energy equipment being beyond the design operation safety range, and the greater the probability of potential risks.

[0085] Reference Figure 5 As shown, the operation status indicator of each energy device in the historical operation overload array is used to determine whether the operation status of the energy device is within the standard operation parameter range of the energy device, specifically including:

[0086] Based on the standardized parameter array, calculate the energy equipment standard operating parameter range and the energy equipment operation critical value;

[0087] Based on the critical value of energy equipment operation, determine whether each energy equipment status indicator is greater than the critical value of equipment operation. If not, it is determined that the energy equipment at that time has no risk hazards. If so, it is determined that the current energy equipment has risk hazards.

[0088] Among them, the critical values ​​of energy equipment operation are as follows:

[0089]

[0090] U is the critical value of equipment operation.

[0091] Through the standard operating parameter array, the operating critical value of each energy device is calculated. Energy equipment that exceeds the critical value indicates that the current operating status of the energy equipment is not within the designed safe operating range and there may be hidden risks. By judging whether the operating status indicator of each energy device is greater than the energy equipment operating critical value, the energy equipment that is greater than the critical value is maintained or replaced to reduce the occurrence of safety hazards. By reducing safety hazards, the reliability, production efficiency and cost control of the entire system are improved, thereby achieving stable operation and sustainable development of the system.

[0092] The use process of the above-mentioned specialized modeling and analysis system based on digital energy system is as follows:

[0093] Step 1: Input the standard operating parameters of all energy devices in the energy system and construct an array of standard operating parameters of energy devices;

[0094] Step 2: Obtain the historical operating parameters of all energy devices in the energy system and construct a historical operating parameter matrix of energy devices

[0095] Step 3: Based on the standard operating parameter array, calculate the overload index of each set of historical operating parameters, and obtain several historical operating parameter overload arrays;

[0096] Step 4: Array several historical operating parameters into overload arrays to construct a historical operating load matrix;

[0097] Step 5: Based on the historical operating load matrix, select each energy device whose load index is greater than the rated index and mark it as an overloaded operating device;

[0098] Step 6: Based on the equipment marked as overloaded, construct a historical overload array;

[0099] Step 7: Based on the historical operation overload array, determine the overload operation duration in which the load index in each group is greater than the rated load;

[0100] Step 8: Calculate each energy equipment status indicator based on the overload operation time in which the load indicator in each group is greater than the rated indicator;

[0101] Step 9: Based on the standardized parameter array, calculate the energy equipment operation critical value of the energy equipment standard operation parameter range;

[0102] Step 10, based on the energy equipment operation critical value, determine whether each energy equipment status indicator is greater than the equipment operation critical value.

[0103] To sum up, this scheme analyzes the historical operating parameters of the energy equipment, takes the maximum load value between the historical operating parameters of the energy equipment and the standard operating parameters of the energy equipment as the worst indicator, and constructs a historical operation overload array for analysis. It analyzes the operating status of each energy equipment after load operation in the historical operation overload array, determines whether there are risks in the current equipment, realizes online monitoring of the equipment, analyzes early warning, reduces safety hazards, and improves the reliability of the entire system, thereby achieving stable operation and sustainable development of the system.

[0104] Furthermore, the method or system according to the embodiment of the present application can also be Figure 6 The architecture of the electronic device shown is implemented. Figure 6 As shown, the electronic device 500 may include a bus 501, one or more CPUs 502, a read-only memory (ROM) 503, a random access memory (RAM) 504, a communication port 505 connected to a network, an input / output component 506, a hard disk 507, etc. The storage device in the electronic device 500, such as the ROM 503 or the hard disk 507, can store a photovoltaic energy anomaly detection system based on digital communication provided by the present application, including: constructing an array of standard operating parameters of energy equipment, constructing a historical operating parameter matrix of energy equipment, calculating the historical overload matrix of energy equipment based on the historical operating parameter matrix of energy equipment and the standard operating parameter array of energy equipment, screening the historical operating overload array, determining the operating status indicator of each energy device in the historical operating overload array, and judging whether the operating status of the energy equipment is within the standard operating parameter range of the energy equipment. If so, it is determined that the energy equipment is in a normal operating state. If not, it is determined that the energy equipment is in an abnormal operating state. The electronic device 500 may also include a user interface 508. Of course, Figure 6 The architecture shown is only exemplary and can be omitted according to actual needs when implementing different devices. Figure 6 One or more components of an electronic device are shown.

[0105] Figure 7 Schematic diagram of a computer-readable storage medium structure provided by an embodiment of the present application. Figure 7 As shown, a computer-readable storage medium 600 according to an embodiment of the present application is shown. Computer-readable instructions are stored on the computer-readable storage medium 600. When the computer-readable instructions are executed by the processor, the path planning method according to the embodiment of the present application described with reference to the above figures can be executed. The storage medium 600 includes, but is not limited to, for example, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory (cache), etc. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0106] In addition, according to the implementation mode of the present application, the process described with reference to the flowchart above can be implemented as a computer software program. For example, construct a standard operating parameter array of energy equipment, construct a historical operating parameter matrix of energy equipment, calculate the historical overload matrix of energy equipment based on the historical operating parameter matrix of energy equipment and the standard operating parameter array of energy equipment, screen the historical operating overload array, determine the operating status index of each energy equipment in the historical operating overload array, and judge whether the operating status of the energy equipment is in the standard operating parameter interval of the energy equipment. If so, it is determined that the energy equipment is in a normal operating state, and if not, it is determined that the energy equipment is in an abnormal operating state. When the computer program is executed by the central processing unit (CPU), the above functions defined in the method of the present application are executed.

[0107] The methods, apparatuses, and devices of the present application may be implemented in many ways. For example, the methods, apparatuses, and devices of the present application may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above order of steps for the method is for illustration only, and the steps of the method of the present application are not limited to the order specifically described above unless otherwise specified. In addition, in some embodiments, the present application may also be implemented as programs recorded in a recording medium, which include machine-readable instructions for implementing the method according to the present application. Therefore, the present application also covers recording media storing programs for executing the method according to the present application.

[0108] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A photovoltaic energy anomaly detection system based on digital communication, characterized in that: include: The standard data acquisition module and the standard comparison module are used to input the standard operating parameters of all energy equipment in the energy system and construct the array of standard operating parameters of energy equipment; The historical data acquisition module, the matrix construction module and the standard control module are connected by wires. The matrix construction module is used to obtain the historical operating parameters of all energy devices in the energy system and construct the historical operating parameter matrix of the energy devices. A load assessment module, the load assessment module is connected to the standard data acquisition module and the historical data acquisition module by wires, and the load assessment module is used to calculate the historical overload matrix of the energy device based on the historical operation parameter matrix of the energy device and the standard operation parameter array of the energy device; A load screening module, the screening module is electrically connected to the load evaluation module, and the screening module is used to screen a historical operating overload matrix based on a historical overload matrix of energy equipment; A state evaluation module, the state evaluation module is electrically connected to the load screening module, and the state evaluation module is used to determine the operation state index of each energy device in the historical operation overload array based on the historical operation overload array screened out; The abnormal judgment module is electrically connected to the status evaluation module. The abnormal judgment module is used to judge whether the operating status of the energy equipment is within the standard operating parameter range of the energy equipment based on the operating status index of each energy equipment in the historical operating overload array. If so, it is determined that the energy equipment is in a normal operating state; if not, it is determined that the energy equipment is in an abnormal operating state.

2. According to claim 1, a photovoltaic energy anomaly detection system based on digital communication is characterized in that: The load assessment module specifically includes: The load calculation unit calculates the overload index of each set of historical operating parameters based on the standard operating parameter array, and obtains several historical operating parameter overload arrays; A matrix construction unit, which arrays several historical operation parameters overload arrays to construct a historical operation load matrix; Among them, the overload index of each set of historical operation parameters is calculated, specifically: Among them, S i For overload array, l ij is the overload index between the jth parameter of the i-th group of historical operating parameters and the standard operating parameters, m is the total number of operating equipment, r ij is the actual load of the jth device of the i-th group of historical operating parameters, g j is the rated load of the jth device; Among them, the historical operation load matrix is ​​constructed as follows: Where M is the historical operating load matrix.

3. According to claim 2, a photovoltaic energy anomaly detection system based on digital communication is characterized in that: The load screening module specifically includes: The overload marking unit selects each energy device whose load index is greater than the rated index based on the historical operating load matrix and marks it as an overloaded device. The screening unit constructs a historical operation overload array based on the equipment marked as overloaded; Among them, merging the overload indicator array into the historical running overload array is as follows: Where t is the historical operation overload array, It is an overload energy device whose jth load index is greater than the rated index.

4. According to claim 3, a photovoltaic energy anomaly detection system based on digital communication is characterized in that: The status assessment module specifically includes: The load duration unit determines the overload operation duration in each group where the load index is greater than the rated load based on the historical operation overload array; The equipment evaluation unit calculates the status index of each energy equipment based on the overload operation time when the load index in each group is greater than the rated index; Among them, the energy equipment status indicators are as follows: Q is the energy equipment status indicator, ε is the loss coefficient under standard operating conditions, P 基 is the basic loss under standard operating conditions, ε1 is the loss coefficient under overload operating conditions, and p 超 It is the basic loss under overload operation condition.

5. According to claim 4, a photovoltaic energy anomaly detection system based on digital communication is characterized in that: The abnormal judgment module specifically includes: A critical value evaluation unit, which calculates the critical value of energy equipment operation within the standard operating parameter range of the energy equipment based on the standardized parameter array; The judgment unit judges whether each energy equipment state indicator is greater than the equipment operation critical value based on the energy equipment operation critical value. If not, it is judged that the energy equipment at that time has no risk hidden danger. If so, it is judged that the current energy equipment has risk hidden danger; Among them, the critical values ​​of energy equipment operation are as follows: U is the critical value of equipment operation.

6. An electronic device, characterized in that: include: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a photovoltaic energy anomaly detection system based on digital communication as described in any one of claims 1-5.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, a photovoltaic energy anomaly detection system based on digital communication according to any one of claims 1 to 5 is implemented.

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