KR20200031420A - Apparatus for estimating photovoltaic power generation - Google Patents

Abstract

The present invention relates to an apparatus for predicting the amount of solar power generation, which estimates a solar cell temperature, and predicts the amount of solar power generation on the basis of the estimated solar cell temperature. According to an embodiment of the present invention, the apparatus for predicting the amount of power generation of a solar power generation system including a plurality of solar cells, comprises: a variable acquisition unit for acquiring the amount of solar radiation, an external air temperature, and wind velocity in a solar power generation system; a wind velocity weight applying unit for applying the weight to the wind velocity through regression analysis on the basis of a temperature of a solar cell; a cell temperature calculating unit for calculating a temperature of the solar cell on the basis of the amount of solar radiation, the external air temperature, and the wind velocity applied with the weight; a predicted power generation amount calculating unit for calculating a predicted power generation amount of the solar power generation system on the basis of the amount of solar radiation, the external air temperature, and the temperature of the solar cell; a power generation weight determining unit for determining a power generation weight for the solar power generation system; a characteristic value determining unit for determining a characteristic value for the predicted power generation amount through the regression analysis on the basis of corrected power generation amount obtained by applying the power generation weight to the predicted power generation amount; and an abnormal power generation amount calculating unit for calculating an abnormal power generation amount of the solar power generation system by applying the calculated characteristic value to the predicted power generation amount.

Description

Apparatus for predicting solar power generation {APPARATUS FOR ESTIMATING PHOTOVOLTAIC POWER GENERATION}

The present invention relates to an apparatus for estimating solar cell temperature based on wind speed and predicting solar power generation based on the estimated solar cell temperature.

Recently, renewable energy has been spotlighted by the depletion of coal and oil. Accordingly, the importance of a new and renewable energy power generation system is emerging.

Among them, the photovoltaic power generation has the advantage of being able to freely determine the size of the installation according to needs, as there are few restrictions on the installation location.

However, from the perspective of the user who built the photovoltaic power generation system, the only indicator that can determine the actual power generation status is the measured value through the watt-hour meter, so there is a limit for the user to understand the state of the photovoltaic power generation system through the measured value have.

Accordingly, in consideration of various environmental factors, there is a need for a method capable of providing a user with an ideal power generation amount of a photovoltaic power generation system.

An object of the present invention is to provide a photovoltaic power generation prediction device capable of predicting a photovoltaic power generation in consideration of various environmental factors.

An apparatus for predicting the amount of photovoltaic power generation according to an embodiment of the present invention for achieving this object is a device for predicting the amount of power generation of a photovoltaic power generation system including a plurality of photovoltaic cells, the amount of solar radiation in the photovoltaic power generation system, outdoor air Variable obtaining unit for obtaining temperature and wind speed, wind speed weight applying unit to apply weight to the wind speed through regression analysis based on the temperature of the photovoltaic cell, based on the solar radiation, the outside temperature and the wind speed to which the weight is applied Cell temperature calculation unit for calculating the temperature of the photovoltaic cell, the estimated generation amount calculation unit for calculating the expected amount of power generation of the photovoltaic power generation system based on the solar radiation, the outside temperature and the temperature of the photovoltaic cell, the photovoltaic power generation system Power generation weight determination unit for determining the power generation weight for, the power generation weight is applied to the expected power generation It includes a feature value determining unit for determining a characteristic value for the expected power generation through a regression analysis based on the corrected power generation amount and an abnormal power generation amount calculating unit for calculating the abnormal power generation amount of the solar power system by applying the calculated characteristic value to the expected power generation amount It is characterized by.

According to the present invention as described above, by predicting the amount of photovoltaic power generation in consideration of various environmental factors, it is possible to provide the user with an ideal amount of current photovoltaic power generation and allow the user to grasp the abnormality of the photovoltaic power generation system early. It has the effect of making.

In addition, according to the present invention, in calculating the solar cell temperature, by reflecting the cooling effect of the solar cell by the wind, there is an effect that can improve the accuracy of calculating the solar cell temperature and the calculation of abnormal power generation.

In addition, according to the present invention, by reflecting the past development trend of the photovoltaic power generation system in calculating the amount of abnormal power generation, there is an effect that can reflect the temporal and geographical power generation factors inherent to the photovoltaic power generation system.

In addition, according to the present invention, by calculating the efficiency of the inverter constituting the photovoltaic power generation system in calculating the abnormal power generation, it is possible to calculate the more accurate abnormal power generation by reflecting the system performance.

1 is a view showing a photovoltaic power generation prediction device according to an embodiment of the present invention.
FIG. 2 is a diagram illustrating a state in which the photovoltaic power generation prediction device shown in FIG. 1 is connected to a photovoltaic power generation system.
3 is a view showing a photovoltaic cell photovoltaic module and a photovoltaic array for performing photovoltaic power generation in a photovoltaic power generation system, respectively.
Figure 4 is a flow chart showing a regression analysis process based on the temperature of the solar cell on.
5 is a graph showing solar cell temperature over time according to each regression analysis method.
6 is a flowchart illustrating a process of calculating an abnormal power generation amount from an expected power generation amount.
7 is a graph showing an efficiency curve of an inverter according to voltage.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. However, the embodiments of the present invention exemplified below may be modified in various other forms, and the scope of the present invention is not limited to the embodiments described below. The embodiments of the present invention are provided to more fully describe the present invention to those skilled in the art.

In the drawings, the same reference numerals are used to indicate the same or similar components.

When a certain part of the specification "includes" a certain component, this means that other components may be further included instead of excluding other components unless specifically stated otherwise. In addition, terms such as “... unit” and “module” described in the specification mean a unit that processes at least one function or operation, which may be implemented in hardware or software, or a combination of hardware and software. .

The present invention relates to an apparatus for estimating a photovoltaic cell temperature based on wind speed in a photovoltaic power generation system including a plurality of photovoltaic cells, and predicting the amount of photovoltaic power generation based on the estimated photovoltaic cell temperature.

Hereinafter, a photovoltaic power generation prediction device according to an embodiment of the present invention will be described in detail with reference to FIGS. 1 to 6.

1 is a diagram illustrating a photovoltaic power generation prediction device according to an embodiment of the present invention, and FIG. 2 is a view showing a state in which the photovoltaic power generation prediction device shown in FIG. 1 is connected to a photovoltaic power generation system.

FIG. 3 is a view showing a solar cell photovoltaic module and a photovoltaic array for performing photovoltaic power generation in a photovoltaic power generation system, respectively.

4 is a flowchart illustrating a regression analysis process based on the temperature of the solar cell on, and FIG. 5 is a graph showing the solar cell temperature over time according to each regression analysis method.

6 is a flowchart illustrating a process of calculating an abnormal power generation amount from an expected power generation amount.

7 is a graph showing the efficiency curve of the inverter according to the voltage.

Referring to FIG. 1, the photovoltaic power generation predictor 100 according to an embodiment of the present invention includes a variable acquiring unit 110, a wind speed weight applying unit 120, a cell temperature calculating unit 130, and an estimated power generating unit 140, a power generation weight determination unit 150, a characteristic value determination unit 160, and an abnormal power generation amount calculation unit 170. The photovoltaic power generation prediction apparatus 100 illustrated in FIG. 1 is exemplary, and its components are not limited to the embodiment illustrated in FIG. 1, and some components may be added, changed, or deleted as necessary. .

Meanwhile, referring to FIG. 2, the photovoltaic power generation system 200 to which the photovoltaic power generation prediction apparatus 100 shown in FIG. 1 is applied includes a photovoltaic array 210, a plurality of inverters 220, and a cell temperature sensor ( 230) and a variable measuring unit 240. The photovoltaic system 200 shown in FIG. 2 is exemplary, and the components are not limited to the embodiment illustrated in FIG. 2, and some components may be added, changed, or deleted as necessary.

The variable acquiring unit 110 may acquire solar radiation, outdoor temperature, and wind speed in the solar power system 200.

), 외기 온도(T_a) 및 풍속(v)을 제공받을 수 있다.In one example, the variable acquiring unit 110 is irradiated from the variable measuring unit 240 located in the solar power system 200 (

), Outside temperature (T _a ) and wind speed (v) can be provided.

)을 [W/m²]의 단위로 측정할 수 있다. 또한, 외기 온도계(240b) 및 풍속계(240c)는 태양광 발전 시스템(200)이 설치된 위치의 외기 온도(T_a)와 풍속(v)을 각각 [^oC] 및 [m/s]단위로 측정할 수 있다.As illustrated in FIG. 2, the variable measurement unit 240 of the solar power system 200 may include an insolation meter 240a, an outdoor thermometer 240b, an anemometer 240c, and the like. The solar radiation meter 240a is a solar radiation (

) Can be measured in [W / m ² ]. In addition, the outside air thermometer 240b and the anemometer 240c measure the outside air temperature T _a and the wind speed v at the location where the solar power system 200 is installed in [ ^o C] and [m / s], respectively. can do.

), 외기 온도(T_a) 및 풍속(v)을 획득할 수도 있다. 예를 들어, 변수 측정부(240)는 기상청의 서버로부터 태양광 발전 시스템(200)이 설치된 위치의 일사량(

), 외기 온도(T_a) 및 풍속(v)을 각각 획득할 수 있다.On the other hand, the variable measuring unit 240 communicates with an external server to inject solar radiation (

), Outside temperature (T _a ) and wind speed (v) may be obtained. For example, the variable measuring unit 240 is the amount of solar radiation at the location where the solar power generation system 200 is installed from the server of the Korea Meteorological Administration (

), Outside temperature (T _a ) and wind speed (v) can be obtained respectively.

), 외기 온도(T_a) 및 풍속(v)을 변수 측정부(240)로부터 제공받을 수 있다.The variable acquisition unit 110 measures or acquires the amount of solar radiation measured by the variable measurement unit 240 (

), The outside temperature (T _a ) and the wind speed (v) can be provided from the variable measurement unit 240.

), 외기 온도(T_a) 및 풍속(v)을 획득할 수 있다. 또한, 태양광 발전량 예측 장치(100)가 물리적으로 태양광 발전 시스템(200) 내부에 위치하는 경우, 변수 획득부(110)는 일사량계(240a), 외기 온도계(240b), 풍속계(240c)를 통해 스스로 일사량(

), 외기 온도(T_a) 및 풍속(v)을 획득할 수도 있다.In another example, the variable acquiring unit 110 communicates with an external server by itself to inject radiation (

), Outside temperature (T _a ) and wind speed (v) can be obtained. In addition, when the photovoltaic power generation prediction device 100 is physically located inside the photovoltaic power generation system 200, the variable acquiring unit 110 includes an insolation meter 240a, an outdoor thermometer 240b, and an anemometer 240c. Through insolation yourself (

), Outside temperature (T _a ) and wind speed (v) may be obtained.

The wind speed weight applying unit 120 may apply the weight to the wind speed through a regression analysis based on the temperature Tc of the solar cell.

In addition, the cell temperature calculating unit 130 may calculate the temperature Tc of the solar cell based on the solar radiation applied from the variable acquiring unit 110 and the external temperature and the wind speed weighted by the wind speed weight applying unit 120. have.

In the present invention, a solar cell may mean a unit cell that performs solar power generation. More specifically, referring to FIG. 3, the photovoltaic power generation system 200 may include at least one PV array 210. At this time, the solar array 210 may be composed of a plurality of PV modules (PV module), the PV module (PV module) may be composed of a plurality of PV cells (PV cell).

On the other hand, the temperature (Tc) of the photovoltaic cell described in the present invention is a temperature inside the photovoltaic cell and cannot be measured. Accordingly, the temperature (Tc) of the photovoltaic cell is measured by the cell temperature sensor 230 described later. It may be different from the outer surface temperature (T _m ) of the solar cell.

First, in order to explain the reason for applying the weight to the wind speed, a method for calculating the temperature Tc of the solar cell by the cell temperature calculator 130 will be described.

The cell temperature calculator 130 may calculate the temperature Tc of the solar cell according to Equation 1 below.

는 일사량,

는 태양광 셀의 에너지 흡수율,

는 태양광 셀 상면에 구비된 유리의 투과율,

는 태양광 셀의 발전 효율,

는 태양광 셀의 온도 변화에 따른 발전 효율 변동률, T_r는 기준 온도(25^oC))(Tc is the solar cell temperature, U _PV is the weighted wind speed, T _a is the outside temperature,

Is insolation,

Is the energy absorption rate of the solar cell,

Is the transmittance of the glass provided on the upper surface of the solar cell,

Is the solar cell power generation efficiency,

Is the rate of change in power generation efficiency according to the temperature change of the photovoltaic cell, T _r is the reference temperature (25 ^o C))

), 태양광 셀 상면에 구비된 유리의 투과율(

), 태양광 셀의 발전 효율(

) 및 태양광 셀의 온도 변화에 따른 발전 효율 변동률(

)은 태양광 셀의 성능에 따라 결정되는 상수값(constant)일 수 있다.Here, the energy absorption rate of the solar cell (

), The transmittance of the glass provided on the upper surface of the solar cell (

), Solar cell power generation efficiency (

) And the rate of change in power generation efficiency according to the temperature change of the solar cell (

) May be a constant value determined according to the performance of the solar cell.

Meanwhile, the weighted wind speed U _PV is a parameter for reflecting the cooling effect of the solar cell by the wind, and may be a value determined by using the wind speed v as an independent variable.

In one example, the wind speed weight applying unit 120 creates an nth-order equation or an exponential equation in which wind speed (v) is an independent variable and U _PV is a dependent variable, and is independent variable (e ^x) in the corresponding equation through regression analysis. , v, v ² Etc.) and constants.

Hereinafter, it will be described by assuming that the wind speed weight applying unit 120 performs a regression analysis by creating a linear linear equation with wind speed (v) as an independent variable and U _PV as a dependent variable.

More specifically, the wind speed weight applying unit 120 may set the weighted wind speed (U _PV ) according to Equation 2 below.

(a, b are weight constants, v is wind speed)

Here, the wind speed weight applying unit 120 is a regression analysis that maximizes R ² (R Square), a root mean square error (RMSE), a mean absolute error (MAE), or a regression analysis that minimizes Mean Bias Error (MBE). A weight may be applied to the wind speed v through at least one of the following. In other words, the wind speed weight applying unit 120 may determine the weight constants (a, b) in the above equation (2) through regression analysis.

Referring to FIG. 4, when the temperature Tc of the photovoltaic cell is calculated by the cell temperature calculator 130 (S410), the wind speed weighting unit 120 is based on the calculated temperature Tc of the photovoltaic cell. By performing a regression analysis (S420).

More specifically, the wind speed weight applying unit 120 sets the weight constant so that the temperature Tc of the photovoltaic cell calculated in the current period through regression analysis follows the temperature Tc 'of the photovoltaic cell calculated in the previous period. Can decide.

Here, the temperature Tc 'of the photovoltaic cell calculated in the previous cycle may include not only the temperature of the photovoltaic cell calculated in the immediately preceding period, but also all the temperature of the photovoltaic cell calculated in the previous period. That is, the temperature Tc 'of the photovoltaic cell calculated in the previous cycle may include all the temperature of the photovoltaic cell calculated in the past.

The wind speed weight applying unit 120 may extract the temperature of the photovoltaic cell calculated in a specific period from the temperature of the photovoltaic cell of the past stored in the database.

More specifically, the wind speed weight applying unit 120 may extract the temperature of the photovoltaic cells calculated on the same day, the same month, the same season, etc. in consideration of the similarity of solar power generation.

In addition to this, the wind speed weight applying unit 120 may extract the temperature of the solar cell calculated at any time in the past according to the user's needs.

The wind speed weight applying unit 120 may determine a weight constant such that the temperature Tc of the photovoltaic cell calculated at every period follows the temperature Tc 'of the past photovoltaic cell extracted from the database (S430).

Referring to FIG. 5, the wind speed weight applying unit 120 extracts the temperature Tc ′ of the past solar cell calculated from 7:12 AM to 7:12 PM, and the aforementioned R ² , RMSE, MBE Through the regression analysis according to the method, the currently calculated temperature of the solar cell (Cell Temp. Tc) can be made to follow the temperature of the past solar cell (Tc ').

More specifically, the wind speed weight applying unit 120 calculates the temperature Tc of the photovoltaic cell while adjusting the weighting constants (a, b) of [Equation 2] described above, and the calculated temperature of the photovoltaic cell ( It is possible to determine the weighting constants a and b that allow Tc) to track the temperature Tc 'of the past solar cell.

For example, wind velocity weighted section 120 (Optimised R ²⁾ a R ² represents the degree of similarity of the history data and current data by regression analysis of the R ² method to be the maximum weighting constant (a, b) Can decide.

In addition, the wind speed weight applying unit 120 through the regression analysis according to the RMSE or MBE method to minimize the size of the RMSE or MBE representing the error between the past data and the current data (Optimized RMSE or MBE) weight constant (a , b).

When the weight constants (a, b) are determined, the wind speed weight applying unit 120 may apply the determined weight constants (a, b) to [Equation 2] described above to apply the weight to the wind speed (S440). .

Steps S410 to S440 of FIG. 4 described above may be performed at every cycle in which the temperature Tc of the solar cell is calculated.

However, as described above, when the temperature Tc 'of the solar cell calculated in the past is not stored in the database, the surface temperature T _m of the solar cell measured through the cell temperature sensor 230 is measured. You can also perform regression analysis based on that.

At this time, the wind speed weight applying unit 120 calculates the temperature (Tc) of the photovoltaic cell while adjusting the weighting constants (a, b) of [Equation 2] described above, and the calculated temperature (Tc) of the photovoltaic cell ) May determine weighting constants (a, b) to follow the surface temperature (T _m ) of the solar array 210 measured by the cell temperature sensor 230.

As described above, the present invention can improve the accuracy of the solar cell temperature calculation and the accuracy of the abnormal power generation calculation described later by reflecting the cooling effect of the solar cell by wind in calculating the solar cell temperature.

), 외기 온도(T_a) 및 태양광 셀의 온도(Tc)에 기초하여 태양광 발전 시스템(200)의 예상 발전량(Pp)을 산출할 수 있다.Estimated power generation unit 140 is the amount of solar radiation (

), The estimated power generation amount Pp of the photovoltaic power generation system 200 may be calculated based on the outside temperature T _a and the temperature Tc of the photovoltaic cell.

), 외기 온도(T_a) 및 태양광 셀의 온도(Tc)를 이용하여 단일 태양광 셀의 예상 발전량을 산출하고, 단일 태양광 셀의 예상 발전량에 기초하여 전체 태양광 발전 시스템(200)의 예상 발전량(Pp)을 산출할 수 있다.More specifically, the estimated power generation unit 140 includes solar radiation (

), Using the outside temperature (T _a ) and the temperature (Tc) of the photovoltaic cell to calculate the expected amount of power generation of a single photovoltaic cell, based on the expected amount of power generation of a single photovoltaic cell of the entire photovoltaic system (200) Estimated power generation (Pp) can be calculated.

), 외기 온도(T_a) 및 태양광 셀의 온도(Tc)에 기초하여 태양광 셀의 출력 전압(Vc) 및 출력 전류(Ic)를 산출하고, 산출된 출력 전압(Vc) 및 출력 전류(Ic)를 이용하여 태양광 셀의 예상 발전량을 산출할 수 있다.First, the estimated power generation unit 140 is the amount of solar radiation (

), The output voltage Vc and the output current Ic of the photovoltaic cell are calculated based on the outside temperature T _a and the temperature Tc of the photovoltaic cell, and the calculated output voltage Vc and the output current ( Ic) can be used to calculate the estimated amount of power generated by a photovoltaic cell.

), 외기 온도(T_a) 및 태양광 셀의 온도(Tc)에 기초하여 태양광 셀의 출력 전압(Vc) 및 출력 전류(Ic)를 산출하는 방법은 당해 기술분야에서 알려진 다양한 방법이 이용될 수 있다.Insolation

), A method for calculating the output voltage (Vc) and the output current (Ic) of the photovoltaic cell based on the outside temperature (T _a ) and the temperature (Tc) of the photovoltaic cell, various methods known in the art may be used. You can.

In one example, the estimated power generation unit 140 calculates the output voltage Vc of the photovoltaic cell according to Equation 3 below, and the output current Ic of the photovoltaic cell according to Equation 4 below. Can be calculated.

는 일사량, V_STC는 기준 온도에서 MPPT(Maximum Power Point Tracking)에 따른 최대 전압,

는 온도에 따른 태양광 셀의 전압 변동률, T_C는 태양광 셀의 온도, n은 태양광 셀의 이상계수(ideality factor), K는 볼츠만 상수, q는 단일 전자의 전하량, X는 일사량 파라미터)(Vc is the output voltage of the solar cell, T _a is the outside temperature,

Is the solar radiation, V _STC is the maximum voltage according to MPPT (Maximum Power Point Tracking) at the reference temperature,

Is the voltage fluctuation rate of the photovoltaic cell according to temperature, T _C is the photovoltaic cell temperature, n is the ideality factor of the photovoltaic cell, K is the Boltzmann constant, q is the charge amount of a single electron, and X is the solar radiation parameter)

는 온도에 따른 태양광 셀의 전류 변동률)(Ic is the output current of the solar cell, ISTC is the maximum current according to MPPT at the reference temperature,

Is the rate of change in current of a solar cell with temperature)

Here, V _STC , I _STC is the maximum voltage and maximum current that can output the maximum power when the photovoltaic system 200 operates in accordance with MPPT at a reference temperature of 25 ^o C, to the performance of the solar cell. It is a constant value determined by. On the other hand, MPPT is a method widely known in the art in the operation of the solar power generation system 200, so a detailed description thereof will be omitted here.

), 태양광 셀의 이상계수(n) 또한 태양광 셀의 성능에 따라 결정되는 상수값이고, 볼츠만 상수(K), 단일 전자의 전하량(q,

)은 물리학 분야에서 널리 알려진 상수값이다.On the other hand, voltage and current fluctuation rate according to temperature (

), The photovoltaic cell's ideal coefficient (n) is also a constant value determined by the performance of the photovoltaic cell, Boltzmann's constant (K), and the amount of charge of a single electron (q,

) Is a constant value widely known in the field of physics.

The solar radiation parameter (X) is a parameter obtained by converting a unit of solar radiation, and may be a parameter in which solar radiation of 1000 [W / m ² ] is converted in units of 1 [suns].

The estimated power generation unit 140 may calculate the expected power generation amount of a single photovoltaic cell by multiplying the output voltage Vc and the output current Ic of the photovoltaic cell calculated by the above formula.

As illustrated in FIG. 2, the solar module is composed of a predetermined number of solar cells, and the solar array 210 may be composed of a predetermined number of solar modules.

Accordingly, the estimated power generation unit 140 may calculate the expected power generation amount of the solar module by multiplying the expected power generation amount of a single photovoltaic cell by the number of photovoltaic cells per photovoltaic module. In addition, the estimated power generation unit 140 may calculate the expected power generation amount of the solar array 210 by multiplying the number of the photovoltaic modules per solar array 210 by the expected power generation amount of a single solar module.

On the other hand, when the photovoltaic power generation system 200 includes a plurality of photovoltaic arrays 210, the predicted amount of power generation unit 140 corresponds to the expected amount of power generation of the single photovoltaic array 210, The total estimated power amount Pp of the solar power system 200 may be calculated by multiplying the number.

Referring to FIG. 6, when the estimated power generation amount Pp of the photovoltaic power generation system 200 is calculated by the estimated power generation unit 140 (S610), the power generation weight determining unit 150 displays the solar power generation system 200 The power generation weight for is determined, and the power generation weight can be applied to the expected power generation amount Pp (S620).

More specifically, the power generation weight determining unit 150 may determine the power generation weight for the solar power generation system 200 based on various factors affecting the total amount of power generation of the solar power generation system 200. The power generation weight may be determined as a ratio according to the total power generation within a certain standard.

In one example, the power generation weight determining unit 150 may determine the power generation weight according to the average power generation amount per month or the average power generation amount per month.

The average annual power generation amount and the monthly average power generation amount of the solar power generation system 200 installed in a specific region may be as shown in Table 1 below.

season month Average power generation Seasonal development weights Monthly development weight spring In March 10 [kW] 0.033 0.15 April 15 [kW] 0.05 In May 20 [kW] 0.067 summer June 40 [kW] 0.133 0.467 In July 50 [kW] 0.167 August 50 [kW] 0.167 autumn September 40 [kW] 0.133 0.317 October 35 [kW] 0.117 November 20 [kW] 0.067 winter December 10 [kW] 0.033 0.067 January 5 [kW] 0.017 February 5 [kW] 0.017

The power generation weight determining unit 150 may determine a ratio of the average power generation by season or month in the total power generation as the power generation weight.

The generation weight determining unit 150 corresponds to the expected generation amount Pp calculated in a specific season or month in order to reflect the development trend over time in the expected generation amount Pp calculated by the expected generation amount calculation unit 140 Alternatively, the power generation weight set for the month can be applied.

More specifically, the estimated generation amount Pp calculated within each season and the adjusted generation amount Pc to which the weight set for the season is applied may be as shown in [Table 2].

season Estimated power generation Corrected power generation spring 160 [kW] 24 summer 280 [kW] 130.76 autumn 120 [kW] 38.04 winter 60 [kW] 4.02

Referring to [Table 2], the power generation weight determining unit 150 may identify power generation weights for spring, summer, autumn, and winter as 0.15, 0.467, 0.317, and 0.067, respectively, with reference to [Table 1]. Subsequently, the power generation weight determining unit 150 may calculate the corrected generation amount Pc by multiplying the estimated power generation amount Pp calculated for each season by the seasoned generation weight in the estimated power generation unit 140.

Meanwhile, in another example, the power generation weight determining unit 150 may determine the power generation weight according to the capacity of the inverter 220 to which the photovoltaic cell is connected and the distance between the photovoltaic cell and the inverter 220.

Hereinafter, an example in which the power generation weight determination unit 150 determines the power generation weight according to the capacity of the inverters (inv. # 1 to inv. # N) to which the photovoltaic cells are connected will be described.

In one example, the solar power system 200 includes three inverters (inv. # 1 ~ inv. # 3), and the amount of power generated by each inverter (inv. # 1 ~ inv. # 3) is as follows [Table 3] Can be equal to

inverter Average power generation Power generation weight by inverter inv. # 1 500 [kW] 0.5 inv. # 2 300 [kW] 0.3 inv. # 3 200 [kW] 0.2

The power generation weight determination unit 150 may determine a ratio of the average power generation amount of the inverters (inv. # 1 to inv. # 3) in the total power generation amount of the solar power system 200 as the power generation weight.

The generation weight determination unit 150 corresponds to the estimated generation amount Pp calculated for a specific inverter in order to reflect the development trend of each inverter 220 in the expected generation amount Pp calculated by the expected generation amount calculation unit 140 The power generation weight set for the inverter can be applied.

More specifically, the estimated generation amount Pp calculated for each inverter (inv. # 1 ~ inv. # 3) and the corrected generation amount applied with the weight set for the inverter (inv. # 1 ~ inv. # 3) ( Pc) may be as shown in Table 4 below.

inverter Estimated power generation Corrected power generation inv. # 1 450 [kW] 225 inv. # 2 320 [kW] 96 inv. # 3 190 [kW] 38

The characteristic value determining unit 160 may perform a regression analysis based on the corrected generating amount Pc to which the generating weight is applied to the expected generating amount Pp (S630), thereby determining the characteristic value for the expected generating amount (S640). .

The characteristic value determining unit 160, like the wind speed weighting unit 120 described above, regression analysis that maximizes R ² (R Square), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), or Mean Bias (MBE) Any regression analysis that minimizes the error) can be performed.

More specifically, as shown in FIG. 6, the characteristic value determining unit 160 may determine a characteristic value for the expected power generation so that the corrected power generation amount Pc follows the corrected power generation amount Pc ′ calculated in the previous cycle.

Here, the corrected generation amount Pc 'calculated in the previous cycle may include all of the corrected generation amounts calculated in the previous cycle as well as the corrected generation amount calculated in the previous cycle.

The characteristic value determining unit 160 may extract the amount of the corrected power generated in a specific period from the amount of the corrected power generated in the past stored in the database.

More specifically, the characteristic value determining unit 160 may extract the corrected power generation amount Pc 'calculated on the same day, the same month, the same season, and the like last year in consideration of the similarity (trend) of solar power generation.

In addition to this, the characteristic value determining unit 160 may extract the amount of correction power generated at any time in the past according to a user's need.

The characteristic value determining unit 160 may determine a characteristic value by performing a regression analysis so that the corrected generating amount Pc calculated at every cycle follows the past corrected generating amount Pc 'extracted from the database.

More specifically, the characteristic value determining unit 160 may determine the characteristic value for the expected amount of power generation as the R ² value determined through the regression analysis described above.

Referring to the above [Table 4] as an example, the characteristic value determining unit 160 has the corrected generating amount Pc 'for inv. # 1 to inv. # 3 in the past. Regression analysis can be performed to follow (Pc '), and the characteristic values determined as a result of the regression analysis can be as shown in [Table 5] below.

inverter Estimated power generation Characteristics Abnormal power generation inv. # 1 450 [kW] 0.98 441 [kW] inv. # 2 320 [kW] 0.96 307.2 [kW] inv. # 3 190 [kW] 0.95 180.5 [kW]

The abnormal power generation unit 170 may calculate the abnormal power generation amount of the solar power generation system 200 by applying a characteristic value to the expected power generation amount Pp (S650).

More specifically, the abnormal power generation calculating unit 170 may calculate the abnormal power generation by multiplying the estimated power generation Pp by a characteristic value.

In the above, the method of calculating the abnormal power generation amount of the solar power generation system 200 based on the estimated power generation amount of each inverter described in [Table 4] by the abnormal power generation calculation unit 170 is described. It is natural that the abnormal power generation amount of the photovoltaic power generation system 200 may be calculated based on the estimated power generation amount by season and month described with reference to Table 1] and [Table 2].

As described above, according to the present invention, by reflecting the past development trend of the photovoltaic system in calculating the amount of abnormal power generation, it is possible to reflect the temporal and geographical development factors inherent in the photovoltaic system.

Meanwhile, the abnormal power generation unit 170 may correct the abnormal power generation amount of the solar power system 200 based on the efficiency of the inverter 220 to which the photovoltaic cell is connected.

Here, the efficiency of the inverter 220 may mean a ratio of DC power input to the inverter 220 to AC power converted from the DC power after the corresponding DC power is converted.

Referring to FIG. 7, an efficiency curve of an arbitrary inverter 220 may vary according to a voltage output from the solar array 210. The abnormal power generation unit 170 may extract an inverter efficiency curve corresponding to the output voltage of the solar cell (more specifically, the solar array 210) among the plurality of inverter efficiency curves stored in the database. Subsequently, the abnormal power generation unit 170 of the inverter 220 corresponding to the total output power of the photovoltaic cell (more specifically, the photovoltaic array 210) connected to the corresponding inverter 220 in the extracted inverter efficiency curve. The efficiency value can be identified.

Accordingly, the abnormal power generation amount calculating unit 170 may correct the abnormal power generation amount by applying the efficiency value of the identified inverter 220 to the expected power generation amount of the inverter 220.

As described above, according to the present invention, by calculating the efficiency of the inverter constituting the photovoltaic power generation system in calculating the abnormal power generation amount, more accurate abnormal power generation amount can be calculated by reflecting the system performance.

The above-described present invention, the above-described embodiments and the accompanying drawings because various substitutions, modifications and changes are possible within the scope of the technical spirit of the present invention to those skilled in the art to which the present invention pertains It is not limited by.

Claims (11)

In the apparatus for predicting the amount of power generation of a photovoltaic power generation system comprising a plurality of photovoltaic cells,
A variable acquiring unit that acquires solar radiation, outdoor temperature, and wind speed in the solar power system;
A wind speed weighting unit applying weight to the wind speed through a regression analysis based on the temperature of the solar cell;
A cell temperature calculator configured to calculate a temperature of the solar cell based on the solar radiation, the outdoor temperature, and the wind speed to which the weight is applied;
An estimated power generation unit calculating an expected power generation amount of the photovoltaic power generation system based on the solar radiation, the outside temperature, and the temperature of the solar cell;
A power generation weight determination unit that determines power generation weights for the solar power system;
A characteristic value determination unit for determining a characteristic value for the expected generation amount through a regression analysis based on a calibrated generation amount to which the generation weight is applied to the expected generation amount; And
And an abnormal power generation unit calculating an abnormal power generation amount of the photovoltaic power generation system by applying the calculated characteristic value to the expected power generation amount.
Solar power generation prediction device.
According to claim 1,
The wind speed weighting unit and the characteristic value determining unit
Prediction of solar power generation that performs at least one of regression analysis that maximizes R ² (R Square), regression analysis that minimizes Root Mean Square Error (RMSE), Mean Absolute Error (MAE), or Mean Bias Error (MBE) Device.
According to claim 1,
The wind speed weighting unit
An apparatus for predicting solar power generation by performing the regression analysis by setting the wind speed as a variable of a linear equation.
According to claim 3,
The wind speed weighting unit
An apparatus for predicting a photovoltaic power generation amount that applies a weight to the wind speed so that the temperature of the photovoltaic cell calculated based on the weighted wind speed tracks the temperature of the photovoltaic cell calculated in a previous cycle.
According to claim 1,
The cell temperature calculator
A photovoltaic power generation prediction device for calculating the temperature of the photovoltaic cell according to Equation 1 below.
[Equation 1]

(T _C is the solar cell temperature, U _PV is the weighted wind speed, T _a is the outside temperature,

Is the insolation,

Is the energy absorption rate of the solar cell,

The transmittance of the glass provided on the upper surface of the solar cell,

Is the power generation efficiency of the solar cell,

Is the rate of change of power generation efficiency according to the temperature change of the photovoltaic cell, T _r is the reference temperature (25 ^o C))
According to claim 1,
The estimated power generation unit
Calculate the output voltage and output current of the photovoltaic cell based on the solar radiation, the outside temperature and the temperature of the photovoltaic cell, and calculate the estimated amount of power generation of the photovoltaic cell using the calculated output voltage and output current Solar power generation prediction device.
The method of claim 6,
The estimated power generation unit
An apparatus for predicting the amount of photovoltaic power generation that calculates an output voltage of the photovoltaic cell according to Equation 2 below and calculates an output current of the photovoltaic cell according to Equation 3 below.
[Equation 2]

(V is the output voltage of the solar cell, T _a is the outside temperature,

Is the solar radiation, V _STC is the maximum voltage according to MPPT (Maximum Power Point Tracking) at the reference temperature,

Is the voltage fluctuation rate of the photovoltaic cell according to temperature, T _C is the temperature of the photovoltaic cell, n is the ideality factor of the photovoltaic cell, K is the Boltzmann constant, q is the charge amount of a single electron, X is Insolation parameter)
[Equation 3]

(Ic is the output current of the solar cell, ISTC is the maximum current according to MPPT at the reference temperature,

Is the current fluctuation rate of the solar cell according to the temperature)
According to claim 1,
The power generation weight determining unit
A solar power generation amount predicting device for determining a power generation weight according to the seasonal average power generation amount or a monthly average power generation amount or for determining the power generation weight according to the capacity of the inverter to which the solar cell is connected.
According to claim 1,
The characteristic value determining unit
An apparatus for predicting solar power generation by performing a regression analysis so as to follow the corrected power generation calculated in the previous cycle, and determining a characteristic value for the expected power generation.
According to claim 1,
The characteristic value determining unit
A device for predicting solar power generation, which determines a characteristic value for the expected power generation as an R ² value determined through the regression analysis.
According to claim 1,
The abnormal power generation calculation unit
A photovoltaic power generation amount predicting device that corrects an abnormal power generation amount of the photovoltaic power generation system based on the efficiency of the inverter to which the photovoltaic cell is connected.

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