KR20200112009A - Method for predicting photovoltaic generation considering environmental factors and power system management apparatus - Google Patents

Abstract

The present invention relates to a method for predicting a solar power generation amount in consideration of environmental factors and a power system management device using the same. According to an embodiment of the present invention, the method for predicting a solar power generation amount in consideration of environmental factors comprises the steps of: calculating a power generation constant for all solar power plants in a specific area as location information of the specific area in which a solar power generation amount is to be predicted is inputted; checking the number of days for each weather in the specific area by using regional weather information; calculating a temperature constant representing a power generation constant change value in accordance with an average temperature change value of the specific area using the power generation constant and the number of days for each weather; calculating efficiency for each terrain of a predicted place belonging to the specific area in accordance with a terrain type of the specific area; and calculating a first predicted power generation amount for solar power generation in the specific area using the power generation constant, the number of days for each weather, the temperature constant, and the efficiency for each terrain.

Description

Solar power generation forecasting method considering environmental factors and power system management device using the same {METHOD FOR PREDICTING PHOTOVOLTAIC GENERATION CONSIDERING ENVIRONMENTAL FACTORS AND POWER SYSTEM MANAGEMENT APPARATUS}

The present invention relates to a method of predicting solar power generation in consideration of environmental factors and a power system management apparatus using the same, and more particularly, by predicting solar power generation in a specific region in consideration of environmental factors such as weather, temperature, and topography, The present invention relates to a method for predicting solar power generation in consideration of environmental factors, and a power system management device using the same, in order to measure the profitability of a solar power plant to improve power system management and operational efficiency.

In general, the method of using solar energy is largely divided into a method of using solar heat and a method of using sunlight. The method of using solar heat is a method of heating and power generation using water heated by the sun, and the method of using sunlight is a method of generating electricity using the light of the sun so that various machines and appliances can be operated with this electricity. This method is called photovoltaic generation.

In particular, solar power generation uses the photovoltaic effect, in which electromotive force is generated by electrons and holes due to light energy when sunlight is irradiated on a solar panel with pn junction by n-type doping on silicon crystals. To generate electricity.

Such solar power generation includes power generation facilities such as a solar cell for condensing sunlight, a photovoltaic module, which is a collection of solar cells, and a solar array in which solar cells are arranged regularly. Required.

In addition, solar power generation is limited in places where the sun shines, and it can be manufactured in various forms desired by the operator, from small facilities to large facilities.

However, before the solar power generation facility is installed, it is necessary to predict the solar power generation amount at the location where the power generation facility is to be installed and examine the feasibility.

Therefore, in the past, a method of simply estimating the amount of solar power generation was applied in consideration of the capacity of the power generation facility and the sunlight time.

In the case of solar power generation, since it does not take into account the influence of the environmental factors (ie, climate, temperature, and geographic characteristics) of the location where the power generation facility is installed, it does not reflect the environmental factors that differ from region to region. Not only is it difficult to predict the amount of photovoltaic power generation, but even if it is predicted, there is a limit that the value cannot be trusted.

Therefore, when predicting the amount of solar power generation, it is necessary to prepare a method for predicting the amount of solar power generation in consideration of environmental factors that differ by region.

Republic of Korea Patent Publication No. 10-2018-0023078

An object of the present invention is to estimate the amount of solar power generation in a specific area in consideration of environmental factors such as weather, temperature, and topography, thereby measuring the profitability of a nationwide solar power plant to improve power system management and operational efficiency, and to determine environmental factors. It is to provide a method for predicting the amount of solar power generation in consideration and a power system management device using the same.

According to an exemplary embodiment of the present invention, a method for predicting solar power generation in consideration of environmental factors includes: calculating power generation constants for all solar power plants in the specific region as location information of a specific region for predicting solar power generation is input; Checking the number of days for each weather in the specific region by using regional weather information; Calculating a temperature constant representing a power generation constant change value according to the average temperature change value of the specific region using the power generation constant and the number of days for each weather; Calculating the topographic efficiency of the predicted place belonging to the specific area according to the topographic type of the specific area; And calculating a first predicted amount of power generation for photovoltaic power generation in the specific region using the power generation constant, the number of days for each weather, the temperature constant, and the efficiency for each terrain.

According to an embodiment, after the step of calculating the first predicted power generation, calculating a second predicted power generation amount for photovoltaic power generation in the specific region by applying an exponential smoothing method on past generation amount data; And calculating a final predicted generation amount using the first predicted generation amount and the second predicted generation amount.

According to an embodiment, after the step of calculating the final predicted power generation, calculating a power generation profit by applying a system limit price (SMP) and a renewable energy supply certificate (REC) to the final predicted power generation amount; I can.

(여기서, P_m은 발전상수, W_i는 m월 특정지역의 개별 태양광 발전소 발전량, K_i는 m월 특정지역의 개별 태양광 발전소 발전용량)로 정의되는 것일 수 있다.The power generation constant is Equation

(Here, P _m may be defined as the power generation constant, W _i is the power generation amount of an individual solar power plant in a specific region per month, and K _i is the power generation capacity of an individual solar power plant in a specific region per month).

The average temperature change value is the difference between the average temperature in m month (T _mc ) and the average temperature in m-1 month (T _(m-1)c ), and the power generation constant change value is power generation on a clear day in m month It may be the difference between the constant average (P _m ／D _ms ) and the average power generation constant on a clear day in _m-January (P _(m-1) ／D _(m-1)s ).

(여기서, T_m은 온도상수, D_ms는 m월의 기후 중 맑은 날 일수, D_(m-1)s는 m-1월의 기후 중 맑은 날 일수, T_mc는 m월의 평균 기온, T_(m-1)c는 m-1월의 평균 기온)로 정의되는 것일 수 있다.The temperature constant is Equation

(Where, T _m is the temperature constant, D _ms is the number of sunny days in the climate in month _m , D _(m-1)s is the number of sunny days in the climate in m-1 month, T _mc is the average temperature in month m, T _(m-1)c may be defined as the average temperature in m-1 month).

(여기서, L_%는 지형별 효율, PL_m은 특정지역 평지(L)의 태양광 발전소 발전량, P_i(x)는 예측장소 동일지형(x)의 태양광 발전소 발전량)로 정의되는 것일 수 있다.The efficiency for each terrain is Equation

(In this case, L _% may be defined as the efficiency of each terrain, PL _m is the amount of solar power plant generation on the flat land (L) of a specific area, and P _i (x) is the generation amount of the solar power plant on the same terrain (x) of the predicted location). .

The first predicted generation amount is,

(여기서, F1_(m+1)은 제1예측발전량, D_m은 m월의 전체 일수, D_(m+1)은 m+1월의 전체 일수, D_(m+1)c는 m+1월의 기후 중 맑은 날을 제외한 일수)로 정의되는 것일 수 있다.Equation

(Where F1 _(m+1) is the first predicted power generation, D _m is the total number of days in month m, D _(m+1) is the total number of days in month m+1, and D _(m+1)c is m+1 It may be defined as the number of days excluding sunny days in the climate of the month.

The second predicted generation amount is,

(여기서, F2_(m+1)는 제2 예측발전량, a는 가중치(지수평활상수))로 정의되는 것일 수 있다.Equation

(Here, F2 _(m+1) may be defined as the second predicted power generation, and a is a weight (exponential smoothing constant)).

The final predicted power generation may be calculated as an average value of the first predicted power generation and the second predicted power generation.

In addition, a power system management apparatus according to an embodiment of the present invention, comprising: at least one processor; And a memory for storing computer-readable instructions, wherein the instructions, when executed by the at least one processor, cause the power system management device to input location information of a specific area to predict solar power generation amount. As a result, the generation constants for all solar power plants in the specific region are calculated, the number of days per weather in the specific region is checked using the regional weather information, and the specified number of days by the weather is used. Calculates a temperature constant representing the change in the power generation constant according to the average temperature change value of the region, calculates the terrain-specific efficiency of the predicted place belonging to the specific region according to the terrain type of the specific region, and calculates the power generation constant, the The number of days for each weather, the temperature constant, and the efficiency for each terrain may be used to calculate a first predicted amount of power generation for solar power generation in the specific region.

The instructions, when executed by the at least one processor, cause the power system management device to calculate the first predicted power generation amount, and then apply an exponential smoothing method to the past generation amount data to provide solar power in the specific area. A second predicted power generation amount for power generation may be calculated, and a final predicted power generation amount may be calculated using the first predicted power generation amount and the second predicted power generation amount.

The instructions, when executed by the at least one processor, cause the power system management device to calculate the final predicted power generation amount, and then, the system limit price (SMP) and a renewable energy supply certificate ( REC) can be applied to calculate the generation profit.

The present invention estimates the amount of solar power generation in a specific area in consideration of environmental factors such as weather, temperature, and topography, thereby measuring the profitability of a nationwide solar power plant to improve power system management and operational efficiency.

In addition, the present invention does not predict the amount of solar power generation using only the data of the past power generation amount, but appropriately reflects the amount of power generation of photovoltaic power generation affected by environmental factors such as weather, temperature and topography to external environmental changes, so accuracy And it is possible to provide a method of predicting the amount of power generation with improved reliability.

In addition, the present invention not only predicts the power generation amount of solar power generation by reflecting environmental factors, but also calculates the final predicted power generation amount by predicting the power generation amount of photovoltaic power generation using past power generation amount data based on the exponential smoothing method. You can predict the amount of solar power generation.

1 is a diagram for a method of predicting solar power generation in consideration of environmental factors according to an embodiment of the present invention;
2 is a diagram showing an exponential smoothing constant table.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. However, in the following description and the accompanying drawings, detailed descriptions of known functions or configurations that may obscure the subject matter of the present invention will be omitted. In addition, it should be noted that the same components are indicated by the same reference numerals as possible throughout the drawings.

The terms or words used in the present specification and claims described below should not be construed as being limited to a conventional or dictionary meaning, and the inventors are appropriately defined as terms for describing their own invention in the best way. It should be interpreted as a meaning and concept consistent with the technical idea of the present invention based on the principle that it can be done.

Therefore, the embodiments described in the present specification and the configurations shown in the drawings are only the most preferred embodiments of the present invention, and do not represent all the technical ideas of the present invention, and thus various alternatives that can be substituted for them at the time of application It should be understood that there may be equivalents and variations.

In the accompanying drawings, some components are exaggerated, omitted, or schematically illustrated, and the size of each component does not entirely reflect the actual size. The invention is not limited by the relative size or spacing drawn in the accompanying drawings.

When a part of the specification is said to "include" a certain component, it means that other components may be further included rather than excluding other components unless otherwise stated. Further, when a part is said to be "connected" with another part, this includes not only the case of being "directly connected" but also the case of being "electrically connected" with another element interposed therebetween.

Singular expressions include plural expressions unless the context clearly indicates otherwise. Terms such as “comprise” or “have” are intended to designate the presence of features, numbers, steps, actions, components, parts, or combinations of these described in the specification, but one or more other features, numbers, or steps. It is to be understood that it does not preclude the possibility of the presence or addition of, operations, components, parts, or combinations thereof.

In addition, the term "unit" used in the specification refers to a hardware component such as software, FPGA, or ASIC, and "unit" performs certain roles. However, "unit" is not meant to be limited to software or hardware. The “unit” may be configured to be in an addressable storage medium or may be configured to reproduce one or more processors. Thus, as an example, "unit" refers to components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, procedures, Includes subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, database, data structures, tables, arrays and variables. The functions provided within the components and "units" may be combined into a smaller number of components and "units" or may be further separated into additional components and "units".

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those of ordinary skill in the art may easily implement the present invention. However, the present invention may be implemented in various different forms and is not limited to the embodiments described herein. In the drawings, parts irrelevant to the description are omitted in order to clearly describe the present invention, and similar reference numerals are assigned to similar parts throughout the specification.

Hereinafter, preferred embodiments of the present invention will be described with reference to the accompanying drawings.

1 is a diagram for a method of predicting solar power generation in consideration of environmental factors according to an embodiment of the present invention.

The method of predicting solar power generation in consideration of environmental factors according to an embodiment of the present invention may be performed by the power system management apparatus. This power system management device is an auxiliary component included in the AMI (Advanced Metering Infrastructure), or is an independent component interlocked with the AMI, and is used in the field of measuring the profitability of solar power generation to improve power system management and operational efficiency. I can.

The power system management apparatus may include at least one processor and a memory for storing computer-readable instructions.

When computer-readable instructions stored in a memory are executed by at least one processor, the power system management apparatus can perform a method of predicting solar power generation in consideration of environmental factors according to an embodiment of the present invention.

Hereinafter, a method of predicting solar power generation in consideration of environmental factors performed by the power system management device will be described in detail.

First, the power system management apparatus calculates a power generation constant (P _m ) of a specific region for all solar power plants in a specific region as location information of a specific region to predict solar power generation is input (S101). The location information of a specific area is an area of a certain range that is uniformly divided, for example, can be divided into administrative district units.

Specifically, the power generation constant (P _m ) may be defined and calculated as shown in [Equation 1] below.

Here, W _i is the power generation capacity of each solar power plant in a specific region per month, and K _i is the power generation capacity of each solar power plant in a specific region per month.

Moreover, W _i is the amount of power actually produced by an individual solar power plant, and K _i is the maximum amount of power that can be produced by an individual solar power plant. Accordingly, W _i /K _i is a value representing the power generation efficiency because it is a value obtained by dividing'the amount of power actually produced by an individual solar power plant'by'the maximum amount of power that can be produced by an individual solar power plant'.

Looking at the above [Equation 1], the power generation constant (P _m ) is defined as the sum of the power generation efficiency of each solar power plant located in a specific area.

Next, the power system management device checks the number of days by weather in a specific area by using the weather information by region in units of one month (S102). In this case, the power system management device may receive weather information for each region through an external weather information server. For example, the power system management device uses 30 days of regional weather information, and the number of days when the weather in a specific area is'clear' is 15 days, the number of days is'cloudy' is 6 days, and the number of days is'cloudy' is 4 days. , You can check the number of'rain' days as 5 days.

However, since solar power generation is meaningful when the weather is'clear', the number of days on a sunny day is applied to [Equation 2] and [Equation 5] to be described later.

Then, the power system management apparatus calculates a temperature constant (T _m ) of a specific region representing a change value of the generation constant according to the average temperature change value of the specific region (S103).

At this time, the power system management apparatus calculates an average temperature change value of a specific region by using the temperature information for each region per month. Here, the average temperature change value corresponds to the difference between the average temperature in m-month (T _mc ) and the average temperature in m-1 month (T _(m-1)c ).

In addition, the power system management device calculates the change value of the power generation constant using the power generation constant of a specific region and the number of sunny days.

Here, the change value of the generation constant is the difference between the average of the generation constant on a clear day in m month (P _m ／D _ms ) and the average of the generation constant on clear days in m-1 month (P _(m-1) ／D _(m-1)s ) Corresponds to. D _ms is the number of sunny days in month _m , and D _(m-1)s is the number of sunny days in month m-1.

Specifically, the temperature constant T _m may be defined and calculated as in Equation 2 below.

Where D _ms is the number of sunny days in the m-month climate, D _(m-1)s is the number of sunny days in the m-1 month climate, T _mc is the average temperature in m month, and T _(m-1)c is This is the average temperature in m-January.

Looking at [Equation 2], the temperature constant (T _m ) is defined as a value obtained by dividing the change value of the power generation constant of all solar power plants located in a specific area by the average temperature change value.

Next, the power system management device checks the topographic type (flat, hilly, mountainous, etc.) of a specific area using topographic information (field, answer, forest, etc.) classified according to the cadastral map (S104). In this case, the power system management apparatus may receive geographical information for each region through an external geographic information server.

In addition, the power system management apparatus calculates the efficiency (L _% ) for each specific area, representing the amount of power generation according to the type of terrain in the specific area (S105).

Specifically, the power system management apparatus may calculate the efficiency (L _% ) for each terrain of a specific area through Equation 3 below.

Here, PL _m is the power generation amount of the solar power plant on the flat land (L) of a specific region, and P _i (x) is the power generation amount of the solar power plant at the same terrain (x) of the predicted location.

In other words, PL _m is the average of the power generation of all solar power plants located on the flat land (L) of a specific region, and P _i (x) corresponds to the power generation of individual solar power plants located on the predicted land (L) of the specific region. .

As described above, since the efficiency (L _% ) of a specific area by terrain considers the amount of power generation according to the terrain type limited to the predicted place belonging to the specific area, not the entire area, it reflects the topographic characteristics of the local predicted place to be more accurate and precise. It makes it possible to predict photovoltaic power generation.

In this way, the power system management device calculates the power generation constant for a specific region, the number of days per weather, the temperature constant for a specific region, and the efficiency for each terrain in a specific region. ) Is calculated (S106).

That is, the power system management device reflects weather information, temperature information, and terrain information for a specific area in calculating the first predicted power generation amount for solar power generation in a specific area.

Specifically, the first predicted power generation (F1 _(m+1) ) is the predicted power generation amount of solar power generation in m+1 month in a specific region, and may be defined and calculated as shown in [Equation 4] below.

Here, P _m is the development constant of a specific region, D _m is the total number of days in month m, D _(m+1) is the total number of days in _{m + January} , and D _{(m + 1) c} is the rainy weather in m + January. Days and cloudy days, L _% is the topographical efficiency of a specific area, and T _m is the temperature constant of a specific area in month. The number of days in which solar power generation is possible (D _(m+1) -D _(m+1)c ) is when the climate is classified into 4 types (i.e., sunny, little cloud, heavy cloud, rain). Shows the number of sunny days and days with little clouds, excluding cloudy days

Looking at the above [Equation 4], the first predicted power generation is the number of days in which solar power generation is possible (D _(m+1) -D _(m+1)c ) in the power generation constant (P _m ／D _m ) per day per m month. After predicting the amount of solar power generation by multiplying by ), the terrain-specific efficiency (L _% ) is applied to reflect the terrain characteristics of the predicted place, and the increase or decrease of solar power generation according to the temperature is adjusted.

And, the power system management device calculates the predicted power generation amount of solar power generation (hereinafter referred to as'second predicted power generation amount') of m+1 month in a specific area by applying exponential smoothing to the past generation amount data. (S107). Here, in the exponential smoothing method, a high weight is given to the recent power generation, and a weight that decreases exponentially as the distance increases.

Specifically, the second predicted power generation (F2 _(m+1) ) is the predicted power generation amount of m+1 month predicted using N past generation data, and may be defined and calculated as shown in [Equation 5] below.

Here, a is a weight (ie, an exponential smoothing constant), and may have a value in the range of 0.3 to 1.3.

As shown in FIG. 2, a may be calculated through the past generation data and organized into a table by month. 2 is a diagram showing an exponential smoothing constant table.

The table of FIG. 2 was prepared by obtaining a relative amount of power generation according to an installation angle and azimuth angle based on 30 degrees facing south. The amount of power generation decreases as the direction of installation changes based on 30 degrees southward.

As described above, the power system management apparatus considers both the first predicted generation amount and the second predicted generation amount.

The first predicted power generation is to directly predict future power generation using past power generation data, while the second predicted power generation is statistical and exponential in which the value of the weight applied to the past power generation data through the exponential smoothing method decreases or increases monthly. This is to predict future generation by giving objectivity.

The power system management apparatus predicts solar power by considering both the first predicted power generation amount and the second power generation amount, thereby reducing an error in the predicted power generation amount of solar power generation, and calculating a reliable and accurate predicted power generation amount.

For this reason, the power system management apparatus calculates the final predicted generation amount in consideration of the first predicted generation amount and the second predicted generation amount (S108).

Specifically, the final predicted power generation amount may be defined and calculated as shown in [Equation 6] and [Equation 7] below. That is, the final predicted power generation is calculated as the average value of the first predicted power generation and the second predicted power generation.

Thereafter, the power system management device calculates the generation profit by applying the system marginal price (SMP) and Renewable Energy Certificates (REC) to the final predicted generation amount (S109).

Here, the system limit price (SMP) represents the market price of the power exchange (KRW/㎾h) applied to the power amount of general generators by transaction time, and the renewable energy supply certificate (REC) uses renewable energy facilities. It represents a certificate issued by the Korea Energy Management Corporation when generating electricity. This applies to the Renewable Portfolio Standard (RPS) system.

The method according to some embodiments may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like alone or in combination. The program instructions recorded on the medium may be specially designed and configured for the present invention, or may be known and usable to those skilled in computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CDROMs and DVDs, and magnetic-optical media such as floptical disks. And hardware devices specially configured to store and execute program instructions such as magneto-optical media, and ROM, RAM, flash memory, and the like. Examples of the program instructions include not only machine language codes such as those produced by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like.

Although the above description has been described with focus on the novel features of the present invention applied to various embodiments, those skilled in the art will have the above-described apparatus and method without departing from the scope of the present invention. It will be appreciated that various deletions, substitutions, and changes are possible in the form and detail of a. Accordingly, the scope of the invention is defined by the appended claims rather than by the above description. All modifications within the equivalent range of the claims are included in the scope of the present invention.

Claims (20)

Calculating power generation constants for all solar power plants in the specific region as location information of a specific region for predicting solar power generation is input;
Checking the number of days for each weather in the specific region by using regional weather information;
Calculating a temperature constant representing a power generation constant change value according to the average temperature change value of the specific region using the power generation constant and the number of days for each weather;
Calculating the topographic efficiency of the predicted place belonging to the specific area according to the topographic type of the specific area; And
Calculating a first predicted amount of power generation for photovoltaic power generation in the specific region using the power generation constant, the number of days for each weather, the temperature constant, and the efficiency for each terrain;
Solar power generation forecasting method in consideration of environmental factors including.
The method of claim 1,
After the step of calculating the first predicted power generation, calculating a second predicted power generation amount for photovoltaic power generation in the specific region by applying an exponential smoothing method to the past generation amount data; And
Calculating a final predicted generation amount using the first predicted generation amount and the second predicted generation amount;
Solar power generation amount prediction method in consideration of environmental factors further including.
The method of claim 2,
After the step of calculating the final predicted power generation, calculating a power generation profit by applying a system limit price (SMP) and a renewable energy supply certificate (REC) to the final predicted power generation;
Solar power generation amount prediction method in consideration of environmental factors further including.
The method of claim 1,
The power generation constant is,
Equation

(Here, P _m is the power generation constant, W _i is the power generation amount of an individual solar power plant in a specific area per month, and K _i is the power generation capacity of an individual photovoltaic power plant in a specific region per month). Prediction method.
The method of claim 1,
The average temperature change value is,
It is the difference between the average temperature in month m (T _mc ) and the average temperature in month m-1 (T _(m-1)c ),
The power generation constant change value is,
Solar light considering environmental factors, which is the difference between the average power generation constant in m-month on a sunny day (P _m ／D _ms ) and the mean power generation constant in m-month on a sunny day (P _(m-1) ／D _(m-1)s ) How to predict power generation.
The method of claim 5,
The temperature constant is,
Equation

(Where, T _m is the temperature constant, D _ms is the number of sunny days in the climate in month _m , D _(m-1)s is the number of sunny days in the climate in m-1 month, T _mc is the average temperature in month m, T _(m-1)c is the average temperature in m-1 month), which is a method of predicting solar power generation in consideration of environmental factors.
The method of claim 1,
The efficiency for each terrain is,
Equation

(Where, L _% is the efficiency of each terrain, PL _m is the amount of solar power plant generation in a specific area (L), and P _i (x) is the amount of solar power plant generation in the same terrain (x) of the predicted location). Solar power generation forecasting method considering factors.
The method of claim 2,
The first predicted generation amount is,
Equation

(Where F1 _(m+1) is the first predicted power generation, D _m is the total number of days in month m, D _(m+1) is the total number of days in month m+1, and D _(m+1)c is m+1 A method of predicting solar power generation in consideration of environmental factors, which is defined as the number of days excluding sunny days among the monthly climate.
The method of claim 8,
The second predicted generation amount is,
Equation

(Here, F2 _(m+1) is the second predicted power generation, a is the weight (exponential smoothing constant)), which is a method of predicting solar power generation in consideration of environmental factors.
The method of claim 9,
The final predicted power generation is,
The solar power generation amount prediction method in consideration of environmental factors, which is calculated as an average value of the first predicted power generation amount and the second predicted power generation amount.
As a power system management device,
At least one processor; And
Including; a memory for storing computer-readable instructions,
The instructions, when executed by the at least one processor, cause the power system management device,
As the location information of a specific area to predict solar power generation amount is input, the generation constants for all solar power plants in the specific area are calculated,
It allows you to check the number of days by weather in the specific area using the weather information by region,
The power generation constant and the number of days for each weather are used to calculate a temperature constant representing a power generation constant change value according to the average temperature change value of the specific region,
To calculate the topographical efficiency of the predicted place belonging to the specific area according to the topographic type of the specific area,
The power system management apparatus to calculate a first predicted amount of power generation for solar power generation in the specific region using the power generation constant, the number of days per weather, the temperature constant, and the efficiency for each terrain.
The method of claim 11,
The instructions, when executed by the at least one processor, cause the power system management device,
After calculating the first predicted generation amount, applying an exponential smoothing method to the past generation amount data to calculate a second predicted generation amount for solar power generation in the specific region,
The power system management apparatus to calculate a final predicted power generation amount using the first predicted power generation amount and the second predicted power generation amount.
The method of claim 12,
The instructions, when executed by the at least one processor, cause the power system management device,
After calculating the final predicted power generation, the power system management device to calculate the power generation profit by applying a system limit price (SMP) and a renewable energy supply certificate (REC) to the final predicted power generation.
The method of claim 11,
The power generation constant is,
Equation

(Here, P _m is the power generation constant, W _i is the power generation amount of an individual solar power plant in a specific region per month, and K _i is the power generation capacity of an individual solar power plant in a specific region per month).
The method of claim 11,
The average temperature change value is,
It is the difference between the average temperature in month m (T _mc ) and the average temperature in month m-1 (T _(m-1)c ),
The power generation constant change value is,
Power system management device that is the difference between the average of the generation constants on a sunny day in m-month (P _m ／D _ms ) and the average of generation constants on a sunny day in _m-January (P _(m-1) ／D _(m-1)s ).
The method of claim 15,
The temperature constant is,
Equation

(Where, T _m is the temperature constant, D _ms is the number of sunny days in the climate in month _m , D _(m-1)s is the number of sunny days in the climate in m-1 month, T _mc is the average temperature in month m, T _(m-1)c is the average temperature in m-1 month).
The method of claim 11,
The efficiency for each terrain is,
Equation

(Where, L _% is the efficiency of each terrain, PL _m is the amount of solar power plant generation on the flat land (L) of a specific area, and P _i (x) is the power generation amount of the solar power plant on the same terrain (x) of the predicted location) Grid management device.
The method of claim 12,
The first predicted generation amount is,
Equation

(Where F1 _(m+1) is the first predicted power generation, D _m is the total number of days in month m, D _(m+1) is the total number of days in month m+1, and D _(m+1)c is m+1 A power system management device that is defined as the number of days excluding sunny days in the climate of the month.
The method of claim 18,
The second predicted generation amount is,
Equation

(Where, F2 _(m+1) is the second predicted power generation, a is the weight (exponential smoothing constant)) that will be defined as the power system management device.
The method of claim 19,
The final predicted power generation is,
The power system management apparatus is calculated as an average value of the first predicted generation amount and the second predicted generation amount.

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