KR101201863B1 - Module base diagnosis device for photovoltaic system - Google Patents

Abstract

PURPOSE: A sunlight diagnosis system capable of unit module monitoring is provided to install a module using wired and wireless communication as an external type, thereby measuring a voltage, a current, and power generation and monitoring a situation. CONSTITUTION: A sunlight generating module(100) converts incident light energy from the sun into electronic energy. A diagnosis module(200) transmits diagnosis information and preset identification codes of each solar battery to a coordinator(300). The diagnosis information is information measuring a power level value, a current level value, and a voltage level value about each solar battery. The coordinator monitors a generation situation of the sunlight generating module in real time based on the diagnosis information corresponding to each of the identification codes. [Reference numerals] (100) Sunlight generating module; (200) Diagnosis module; (210) Surge protector; (220) Analyzing unit; (230) Communication module; (AA) ANTENNA; (BB) Current Sensing; (CC) Voltage Sensing; (DD) DC-DC CONVERTER

Description

Solar diagnostic system with unit module monitoring {MODULE BASE DIAGNOSIS DEVICE FOR PHOTOVOLTAIC SYSTEM}

The present invention relates to a photovoltaic diagnostic system capable of monitoring a unit module, and more specifically, to an individual unit photovoltaic module using wireless communication (ZigBee, Wi-fi or Bluetooth) and wired communication (RS232C, RS422 or RS485). It relates to a technique for real-time monitoring of the situation of shadows, failures and power generation.

Conventional technology in photovoltaic power generation processes protocol specifications of power converters to which different communication methods of photovoltaic power generation systems are applied. In addition, a method of constructing a central monitoring system using a remote terminal unit (RTU) that transmits a protocol specification of a power conversion device to a higher server and supports various types of communication methods is disclosed.

In the method of constructing the central monitoring system using the remote terminal unit, it is composed of the same power generation facilities, and the data are collected by each local terminal system with the dependency of the facilities in a plurality of solar power generation facilities in remote areas, and the data is transferred to the central control system. It has the advantage of implementing the control by the local terminal system, implementing the self-monitoring and alarming functions under the command of the transmitting function and the command of the central control system.

However, there has been a problem in that there is no timely confirmation and determination of the identified failure and failure, and only the error signal of the inverter, which is the power converter, has to be checked.

Republic of Korea Patent Publication No. 2009-0002295 (integrated operation and post-management systems and methods of photovoltaic power generation facilities), converts the light energy incident from the sun into electrical energy, and converts the power, voltage and current levels of the converted electrical energy A solar cell to extract; A solar connection panel which prevents reverse current to the solar cell and receives a power level value, a current level value, and a voltage level value received from the solar cell; An inverter which receives the DC power collected from the solar connection panel and converts the DC power into AC power; A meteorological observation device for collecting meteorological data of horizontal and inclined surfaces of a solar power plant for use as variable factors; Disclosed is a technology consisting of a generation control management console connected to a solar cell, a solar connection panel, and an inverter to collect data and determine whether there is an abnormality and report it to a central control center, which is a higher server.

However, the conventional photovoltaic power generation system as described above, in order to monitor the measurement information of the photovoltaic power generation system in the control server, transmitted to the control server through a wireline established at the construction of the photovoltaic power generation system or the photovoltaic power generation system There is a problem to be transmitted to the control server through the wireless communication module established during the construction.

In addition, as the cell lines of the solar modules are all bonded together, it is difficult to monitor and maintain each cell line, and further expansion of each module is difficult.

The present invention has been made to solve the above problems, by installing a module using wired and wireless communication in the solar power generation system externally, by measuring the voltage, current, amount of electricity generated by the direct method or indirect method The purpose is to monitor the situation by applying artificial intelligence system.

In addition, the present invention allows the administrator to monitor the status of solar power generation anytime, anywhere through a personal computer or terminal through wireless communication (ZigBee, Wi-fi or Bluetooth) and wired communication (RS232C, RS422 or RS485). There is a purpose.

In addition, the present invention can be easily applied to the existing photovoltaic power generation system has an object to reflect the design of the existing installed products and new products by continuously checking the efficient monitoring system and the shade, failure and power generation.

Solar diagnosis system capable of monitoring the unit module of the present invention for achieving the technical problem, the solar power generation module 100 for converting light energy incident from the sun into electrical energy; It is provided to be detachable from the photovoltaic module 100 and the diagnostic information measuring the power level value, current level value and voltage level value for each solar cell and a predetermined identification code (ID) for each solar cell information communication network Diagnostic module 200 for transmitting to the coordinator 300 through; And a coordinator 300 for monitoring in real time the power generation status of the photovoltaic module 100 based on the diagnostic information corresponding to each identification code.

According to the present invention as described above, by installing the module using the wired / wireless communication in the solar power generation system externally, by measuring the voltage, current, power generation and applying the solar radiation meter in a direct method, or by applying an artificial intelligence system in an indirect method It is effective to monitor the situation.

In addition, according to the present invention, the administrator can monitor the status of solar power generation anytime, anywhere through a personal computer or terminal through wireless communication (ZigBee, Wi-fi or Bluetooth) and wired communication (RS232C, RS422 or RS485) It is effective.

In addition, according to the present invention, it can be easily applied to the existing solar power generation system, it is effective to reflect the design for the existing installed products and new products by continuously checking the efficient monitoring system and the shade, failure and generation amount. .

1 is a block diagram showing a conventional photovoltaic module and diagnostic module.
Figure 2a is a block diagram showing a solar diagnostic system capable of monitoring the unit module according to the present invention.
Figure 2b is a block diagram showing a photovoltaic module and the diagnostic module of the solar diagnostic system capable of monitoring the unit module according to the present invention.
Figure 2c is an exemplary view showing the components included in the diagnostic module of the solar diagnostic system capable of unit module monitoring according to the present invention.
3 is a diagram illustrating a ZigBee Star & Mesh network configuration of a solar diagnostic system capable of unit module monitoring according to the present invention.
4 is a diagram illustrating a monitoring system diagram of a photovoltaic power generation system of a photovoltaic diagnostic system capable of unit module monitoring according to the present invention.
5 is a diagram illustrating a communication connection diagram of RS232C, RS422, and RS485 to a wired communication unit of a solar diagnostic system capable of monitoring a unit module according to the present invention.
6 is a diagram illustrating an RS422 communication connection diagram for a wired communication unit of a solar diagnostic system capable of monitoring a unit module according to the present invention.
Figure 7a is a diagram showing the power characteristic curve of the solar radiation of the solar diagnostic system capable of unit module monitoring according to the present invention.
Figure 7b is a view showing the power characteristic curve of the maximum power point of the solar diagnostic system capable of unit module monitoring according to the present invention.
8 is a view showing a characteristic curve at the solar radiation and the maximum power point of the solar diagnostic system capable of unit module monitoring according to the present invention.
FIG. 9 is a view showing a fuzzy controller configured in an apparatus for determining a failure of a solar diagnostic system capable of monitoring a unit module according to the present invention. FIG.
FIG. 10 is a diagram illustrating a multiple Fourier neural network model configured in an apparatus for determining a failure of a solar diagnostic system capable of monitoring a unit module according to the present invention.
11 is a conceptual diagram of a failure diagnosis system for a photovoltaic module of the solar diagnostic system capable of monitoring a unit module according to the present invention.

Specific features and advantages of the present invention will become more apparent from the following detailed description based on the accompanying drawings. Prior to this, terms and words used in the present specification and claims are to be interpreted in accordance with the technical idea of the present invention based on the principle that the inventor can properly define the concept of the term in order to explain his invention in the best way. It should be interpreted in terms of meaning and concept. It is to be noted that the detailed description of known functions and constructions related to the present invention is omitted when it is determined that the gist of the present invention may be unnecessarily blurred.

Hereinafter, the solar diagnostic system S capable of monitoring a unit module according to the present invention will be described below with reference to FIGS. 2A and 2B.

As shown in FIG. 2A and FIG. 2B, the photovoltaic diagnostic system S capable of unit module monitoring according to the present invention includes a photovoltaic module 100 for converting light energy incident from the sun into electrical energy, and solar light. Diagnostic information measuring power level value, current level value and voltage level value for each solar cell and a preset identification code (ID) for each solar cell are provided to be detachable from the power generation module 100 through the information communication network. It comprises a diagnostic module 200 to be transmitted to the 300, and the coordinator 300 for monitoring in real time the power generation status of the photovoltaic module 100 based on the diagnostic information corresponding to each identification code.

Specifically, referring to Figures 2a and 2b will be described below for the components of the solar diagnostic system (S) capable of unit module monitoring according to the present invention.

First, the photovoltaic module 100 converts light energy incident from each of the plurality of solar cells 110 into electrical energy, and includes a connection terminal 120 for grounding with the diagnostic module 200. It is composed.

In addition, the diagnostic module 200 is connected to the connection terminal 120 of the photovoltaic module 100 to be detachable, and receives a power level value, a current level value and a voltage level value from each of the solar cells 110. And a surge protector 210 that prevents overpressure and reverse current, and measures power level value, current level value, and voltage level value to generate diagnostic information based on shading history, failure history, and power generation amount for each solar cell 110. The communication module 230 for transmitting the diagnosis unit 220, the diagnosis information received from the diagnosis unit 220, and a predetermined identification code (ID) for each solar cell 110 to the coordinator 300 connected through the information communication network. It is composed of

At this time, the communication module 230 is a wireless communication unit 231 for transmitting data to the coordinator 300 by any one of ZigBee, Wi-fi or Bluetooth communication method, any one of RS232C, RS422 or RS485 communication method It is configured to include a wired communication unit 232 for transmitting data to the coordinator (300).

Specifically, the wireless communication unit 231 of the communication module 230 may be configured as shown in Figure 2c, to transmit data in any one of the communication method of ZigBee, Wi-fi or Bluetooth, the frequency without permission Use available Industrial, Scientific, Medical (ISM) bands.

In addition, the transmission output and transmission distance of the wireless communication unit 231 transmits 30m indoors, 100m outdoor at 1mW (0dBm), and can transmit more than 100m at 1mW or more, the transmission distance may be different for each ZigBee module manufacturer.

In the device configuration and network configuration, Zigbee device is composed of coordinator, router, and end device, and network configuration by coordinator, network expansion using router, end device network participation, and maximum 65536 network connection when using 64-bit address. This is possible.

For example, referring to FIGS. 3 and 4, the wireless communication unit 231 configures a ZigBee Star or ZigBee Mesh network to perform communication.

First, as shown in FIG. 3, a coordinator configures a ZigBee network and communicates with a router / end device.

The router is then connected with the coordinator or router to expand the network and communicate with the coordinator / router / end device.

The end device participates in the ZigBee network and communicates with the router or coordinator.

Accordingly, the wireless communication unit 231 according to the present invention performs wireless communication through the network structure of the ZigBee Star type or the network structure of the ZigBee Mesh type.

In addition, as shown in FIG. 4, the monitoring for each solar power module is performed by measuring a voltage and a current in the diagnostic module 200 to detect a shadow and a failure of the solar power module 100. Is connected to the Internet system through a wireless coordinator to monitor the photovoltaic power generation status by providing the diagnostic information (voltage, current and power) and identification code (ID), which is measured information in real time to the coordinator 300.

On the other hand, the wired communication unit 232 of the communication module 230, as shown in Figure 5, the diagnostic information (voltage, current and power) and the identification code (ID) which is information measured from the photovoltaic module 100 It transmits to the monitoring PC connected with the communication dedicated cable by one of RS232C, RS485 or RS422.

At this time, as shown in Figure 5, through the selector switch provided in the coordinator 300, the RS232C, RS422 and RS485 of each of the wired communication unit 232 can selectively provide a wired communication method, selector switch and dedicated cable With the installation of multiple wired communication is possible.

In addition, as shown in Figure 6, the wired communication unit 232 of the diagnostic module 200 is connected to the communication dedicated cable to the diagnostic information (voltage, current and power) and identification code (ID) by RS422 dedicated communication method. Can be sent to the monitoring PC.

In addition, the diagnostic unit 220 of the diagnostic module 200 of the solar diagnostic system (S) capable of monitoring the unit module according to the present invention, the solar radiation meter determination device 221 for deriving the current level value, and determining whether there is a failure And further comprises an apparatus 222.

First, the solar radiation meter determination device 221 of the diagnosis unit 220 receives the solar radiation amount and temperature of the solar power generation, calculates a reference current at the maximum power point from the maximum solar radiation amount, and determines the degree of deviation from the reference current. Determine whether the power generation system is normal or abnormal, but derive the current value at the maximum power point for the solar radiation and temperature change through the current at the maximum power point.

Here, FIG. 7A is a diagram illustrating a power characteristic curve of solar radiation at a maximum power point tracking (MPPT) based on direct determination, and FIG. 7B is a maximum power point tracking (MPPT) based on direct determination. Is a diagram showing a power characteristic curve with respect to the maximum power point. In addition, the current value at the maximum power point for the amount of insolation and temperature change is shown in Equation 1 below.

[Equation 1]

Here, a and b are coefficient values obtained by analyzing the solar array characteristics, and S is a value of the current solar radiation amount.

In addition, to obtain a more precise Iref of the surface temperature T ≠ Tref (25 ℃) of the solar array can be modified as shown in Equation 2 below, Figure 8 shows the characteristic curve at the solar radiation and the maximum power point One graph.

&Quot; (2) "

Where T is the surface temperature of the current solar array, Tref is the reference temperature of 25 ° C., and a, b, c and d are the coefficient values obtained by analyzing the solar array characteristics, and the coefficient α is simplified by their relationship. , β can be derived.

In addition, as illustrated in FIG. 9, the failure determination device 222 of the diagnosis unit 220 may determine the failure of the photovoltaic module 100 through a fuzzy controller.

At this time, the failure determination unit 222 is fuzzy by converting a control value or a control error into a fuzzy value, and according to the preset reference value of the rule base, output reduction, shading, Inference is performed to determine a failure, and a defuzzification process of converting the failure to a non-fuzzy value is performed to determine whether there is a failure of the photovoltaic module 100.

In addition, as illustrated in FIG. 10, the failure determining unit 222 of the diagnosis unit 200 may determine the failure of the photovoltaic module 100 through a neural network.

At this time, the failure determination unit 222 constitutes a multiple Fourier neural network as shown in Figure 10, the input parameters G and T of the solar system is applied to the cos and sin functions are calculated through each Fourier neural network Finally, the respective output signals are summed together to calculate the final output. In this case, the output signal of the Fourier neural network may be derived as shown in Equation 3 below.

&Quot; (3) "

는 푸리에 신경회로망의 파라미터이고, NG와 NT는 각 노드의 개수를 나타내며 ω0=2πf0로 정의된다. here,

Is a parameter of the Fourier neural network, and NG and NT represent the number of nodes, and is defined as ω 0 = 2πf 0.

In addition, the failure determination apparatus 222 is a neural network modeling of the photovoltaic module 100 through a learning algorithm, which minimizes the error between the output of the PV system and the output of the neural network for a given input vector. The optimal neural network parameters are determined, and the neural network parameter learning algorithm is calculated.

와 같이 정의하며, 최급강하 최적화 기법에 의거하여 신경회로망 파라미터에 대한 수정규칙은 아래의 [수학식 4]와 같이 도출된다.In addition, the objective function using the modeling error signal

Based on the steepest optimization technique, the correction rule for neural network parameters is derived as shown in Equation 4 below.

&Quot; (4) "

Here, tk is a learning time and (eta) has a range of 0 <(eta) <1 as a learning parameter. In addition, each partial derivative term in [Equation 4] may be developed as shown in [Equation 5] by applying the chain law of differential.

[Equation 5]

In addition, when [Equation 5] is substituted into [Equation 4], the neural network parameter modification rule is finally derived as shown in [Equation 6].

&Quot; (6) &quot;

In addition, the fault diagnosis algorithm is composed of a mechanism that compares the neural network modeling and the output of the actual solar system with each other, detects the horseshoe, and determines whether there is a fault according to a given decision method. The deviation signal is composed of a real-time output error ζ (t) between a real photovoltaic system and a neural network model and a Gaussian random noise signal θ (t), which is expressed by Equation 7 below.

[Equation 7]

γ (t) = ζ (t) + θ (t)

Here, θ ~ N (0,1), when a failure does not occur in the photovoltaic module 100, the real time error ζ of [Equation 7] has a value close to 0, but otherwise ζ The absolute value of is in the range greater than zero. Based on this concept, a decision-making method for fault detection is defined using the following binary hypothesis verification as shown in [Equation 8].

[Equation 8]

Here, γ * means that if the absolute value of the horseshoe γ is greater than or equal to the set reference value defined as the reference box, the system is regarded as having a failure, but otherwise it is operating normally. The hypothesis test of [Equation 8] defined by the actual variable can be defined as shown in [Equation 9] using the probability distribution function.

&Quot; (9) &quot;

At this time, the hypothesis test of Equation (9) is an algorithm that detects the random signal γ and compares it with the reference probability distribution N (0,1) to determine the failure.

On the other hand, Figure 11 is a conceptual diagram of the failure diagnosis system for the photovoltaic module 100 of the failure determination device 222 according to the present invention. As shown in FIG. 11, the neural network model and the failure diagnosis algorithm are applied to compare the values detected from each of the photovoltaic modules 100, and the optimal output value is predicted to determine the shade and failure of the photovoltaic system. Diagnosis can be made.

As described above, the diagnostic module 200 of the solar diagnostic system (S) capable of monitoring the unit module according to the present invention is configured to be detachable by the connection terminal 120 of the photovoltaic module 100. In case of shading, breakdown, or cracking, efficient maintenance is possible through replacement.

Then, the coordinator 300 monitors the power generation status of the photovoltaic module 100 in real time based on the diagnostic information corresponding to each identification code from the diagnostic module 200 connected through the information communication network, the operation of the manager The control signal received through the transmission to the analysis module 200 to control the operating state of the analysis module 200.

While the present invention has been particularly shown and described with reference to preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. It will be appreciated by those skilled in the art that numerous changes and modifications may be made without departing from the invention. And all such modifications and changes as fall within the scope of the present invention are therefore to be regarded as being within the scope of the present invention.

S: solar diagnostic system with unit module monitoring
100: solar power module 110: solar cell
120: connection terminal 200: diagnostic module
210: surge protector 220: diagnostic unit
221: solar radiation meter determination device 222: failure determination device
230: communication module 231: wireless communication unit
232: wireless communication unit 300: coordinator

Claims (6)

In the solar diagnostic system,
Solar power generation module 100 for converting light energy incident from the sun into electrical energy;
It is provided to be detachable from the photovoltaic module 100 and the diagnostic information measuring the power level value, current level value and voltage level value for each solar cell and information identification code (ID) preset for each solar cell information communication network Diagnostic module 200 for transmitting to the coordinator 300 through; And
And a coordinator 300 for monitoring in real time the power generation status of the photovoltaic module 100 based on the diagnostic information corresponding to each of the identification codes.
The photovoltaic module 100 may include: a connection terminal 120 for converting light energy incident from the sun into electrical energy, each of the plurality of solar cells 110 into electrical energy; Including,
The diagnostic module 200 is connected to the connection terminal 120 of the photovoltaic module 100 so that detachment is possible, and a power level value, a current level value, and a voltage level value from each of the solar cells 110 are provided. A surge protector 210 that is applied and prevents overvoltage and reverse current; A diagnosis unit 220 measuring the power level value, the current level value, and the voltage level value to generate diagnostic information based on shading history, failure history, and power generation amount for each of the solar cells 110; And a communication module 230 for transmitting the diagnosis information and the identification code (ID) preset for each solar cell 110, which are received from the diagnosis unit 220, to the coordinator 300 connected through the information communication network.
The diagnosis unit 220,
The neural network (Neural network) and fuzzy control based on the indirect determination to determine the failure of the photovoltaic module 100,
Fuzzification by converting control value or control error into fuzzy value by constructing multiple Fourier neural networks, and determining output degradation, shading and failure of photovoltaic module 100 according to preset reference value of rule base An apparatus for determining whether there is a failure of the photovoltaic module 100 is performed by performing an inference, and performing a defuzzification process of converting the result into a non-fuzzy value. 222); solar diagnostic system capable of monitoring the unit module further comprises. delete delete The method of claim 1,
The communication module 230,
A wireless communication unit 231 for transmitting data to the coordinator 300 by any one of ZigBee, Wi-fi, or Bluetooth; And
And a wired communication unit (232) for transmitting data to the coordinator (300) by any one of RS232C, RS422, or RS485 communication method.
The method of claim 1,
The diagnosis unit 220,
Based on the solar radiation and temperature input of the solar power generation to calculate the reference current at the maximum power point from the maximum solar radiation and determine the degree of deviation from the reference current to determine whether the solar power system is normal or abnormal,
And a solar radiation meter determination device 221 for deriving the current value at the maximum power point for the solar radiation and temperature change through the current at the maximum power point tracking (MPPT) based on the direct determination. Solar diagnostic system that can monitor the unit module. delete

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