KR102460279B1 - An information provision system of solar distributed energy resources - Google Patents

Abstract

The present invention relates to a solar distributed energy resource information providing system that predicts the amount of power generation using a measured amount of power generation when there is the measured amount of power generation by commercial operation in other regions and predicts the amount of power generation by reflecting the installation conditions of a facility compared to standard installation conditions and correcting insolation in a region when there is no measured amount of power generation. The system comprises: a climate information collection unit that collects climate information including insolation by region; a geographic information collection unit that collects geographic information including the latitude, longitude, and altitude of a specific point; an installation target input unit that receives information (hereinafter referred to as installation target information) on an installation target of a photovoltaic power generation facility including an installation location and installation conditions; and a power generation amount prediction unit that predicts the amount of power generation of the power generation facility of the installation target and predicts the amount of power generation by using the insolation by region of the region of the installation location of the installation target and the amount of power generation of a commercial operation facility. By the system as described above, the amount of power generation of the photovoltaic power generation facility can be predicted accurately and immediately in real time by estimating the amount of power generation using an actually measured amount if there is an actually measured power generation amount and correcting the insolation, etc. if there is not.

Description

{ An information provision system of solar distributed energy resources }

The present invention predicts the expected generation amount of a specific area using the measured generation amount when there is the amount of power measured by the commercial operation facility in another area, but when there is no measured generation amount, the specific installation condition of the facility compared to the standard installation condition It relates to a system for providing information on distributed solar energy resources that converts and reflects the amount of solar energy in a specific area and reflects the amount of insolation in the area.

In addition, the present invention, in predicting the expected generation amount of the solar power generation facility in a specific area based on the generation amount measured by the commercial operation facility in another area, obtains the power generation amount measured by the standard installation condition of the commercial operation area, and the corresponding facility It relates to a system for providing information on distributed solar energy resources, which converts and predicts the expected amount of power generation of power generation facilities to specific installation conditions by reflecting local insolation.

In general, power generation using petroleum, coal, or gas not only destroys the environment, but also has several problems, such as damaging the global environment due to the emission of greenhouse gases such as carbon dioxide generated during combustion. Accordingly, in recent years, power generation facilities using eco-friendly energy sources such as hydro power, wind power, solar power, etc. have been developed. The power generation facility of such an eco-friendly energy source has several advantages such as not destroying the environment and not consuming resources.

Among them, solar power generation has the least space restrictions as it can be installed in an area where the sun shines, and it can be installed and operated in various shapes and sizes desired by the operator, from small power generation facilities to large power generation facilities. Therefore, it is more preferred.

On the other hand, an operator who wants to build a new solar power generation facility analyzes and predicts the investment cost, operating cost, sales and net profit related to the installation and operation of the power generation facility prior to the installation of the power generation facility, and according to the result, You want to decide to install. That is, in order to examine the feasibility of the new construction of solar power generation facilities, it is necessary to accurately predict in detail the construction cost of power generation facilities, the amount of power generation according to the types of power generation facilities, and operating profitability from them.

However, since the amount of solar power generation varies depending on the installation location, the installation method, the amount of insolation in the area, etc., there is a problem that the amount of power generation cannot be easily predicted.

Accordingly, the conventional power generation prediction was calculated by making a simple product by reflecting only the capacity of the power generation facility and the amount of sunlight [Patent Documents 1 and 2]. However, when the amount of solar power generation is predicted according to this conventional method, it is difficult to accurately calculate because it does not reflect the meteorological and climatic conditions such as the amount of sunlight, the time of day, and the temperature that differ by region. Unexpected results may appear, and even if predicted, problems such as unreliability of the value occur.

In order to solve this problem, a technique for predicting the amount of solar power generation based on an image of the sky or clouds [Patent Document 3] has been proposed. However, this prior art has a problem in that it is necessary to collect cloud images over a long period of time, such as one year, even though it is possible to predict the amount of power generation more accurately.

Therefore, there is a need for a technology that can accurately and immediately predict the amount of power generation of a solar power plant in real time. In other words, no matter what stage the user or operator is at in the entire cycle, such as information search, consultation, contract, pre-construction licensing, construction, post-construction licensing, commercial operation and asset management, the expected power generation, sales, and investment costs can be accurately calculated. You need skills to calculate.

Japanese Laid-Open Patent Publication No. 2004-47875 (published on Dec. 12, 2004) Korean Patent Publication No. 10-2020-0052432 (published on May 15, 2020) Korean Patent Publication No. 10-2136106 (2020.07.22. Announcement)

An object of the present invention is to solve the above-described problems, and when there is a power generation measured by a commercial operation facility in another area, predicting the expected power generation amount in a specific area using the measured power generation amount, but the measured power generation amount In the absence of this, it is to provide a system for providing information on distributed solar energy resources that converts and reflects the specific installation conditions of the facility compared to the standard installation conditions and predicts the amount of power generation in a specific area by reflecting the amount of insolation in the area.

In addition, it is an object of the present invention to predict the amount of power generation of a specific solar power generation facility based on the national average daily operating time, but generate electricity reflecting the specific installation condition of the facility compared to the standard installation condition applied to the national average daily operating time The power generation amount of a specific area is calculated using the coefficient, the installation location coefficient reflecting the conditions of a specific location and elevation, the power generation efficiency coefficient of the solar module that changes according to the atmospheric temperature and wind speed, and the insolation weight reflecting the amount of insolation in the area. It is to provide an information provision system of a solar distributed energy resource that is predicted by correcting it.

In addition, it is an object of the present invention in predicting the expected power generation amount of the solar power generation facility in a specific area based on the generation amount measured by the commercial operation facility in another area in order to more accurately predict the generation amount, the reference installation conditions of the commercial operation area It is to provide an information providing system for distributed energy resources of solar energy that calculates the amount of power generated by

In addition, an object of the present invention is to predict the amount of insolation for one year based on the current time or to predict the amount of insolation for tomorrow for the prediction of the amount of annual generation of the current year or the amount of generation of tomorrow. Solar power that uses insolation or forecast solar insolation, predicts the remaining insolation in the current year as past insolation, and uses it to predict annual power generation, and specifically predicts tomorrow's power generation using tomorrow's insolation predicted based on the present time. It is to provide a system for providing information on distributed energy resources.

In order to achieve the above object, the present invention relates to a system for providing information on distributed solar energy resources, comprising: a climate information collecting unit for collecting climate information including regional insolation; a geographic information collection unit for collecting geographic information including latitude, longitude, and elevation of a specific point; an installation target input unit for receiving information (hereinafter, installation target information) on an installation target of a photovoltaic power generation facility including an installation location and installation conditions; an operation information collection unit that collects power generation of commercial operation facilities; a generation amount predicting unit for predicting the generation amount of the power generation facility of the installation target, and predicting the generation amount using the solar insolation by region of the installation location of the installation target, and the generation amount of the commercial operation facility; And, it characterized in that it comprises a display unit for displaying the input installation target information, the calculated amount of power generation prediction information.

In addition, in the present invention, in the information providing system of the solar distributed energy resource, the generation amount prediction unit, (a) If there is no information on the measured generation amount of the commercial operation facility, the installation target using the solar radiation of the installation target area predicting the expected power generation of (b) If the measured power generation information of the commercial operation facility is less than one year, the measured power generation amount is used during the period in which the measured power generation amount exists, and the estimated power generation amount of the installation target is calculated using the solar insolation of the area for the remaining period. predicting; And, (c) if the measured power generation information of the commercial operation facility is more than one year, predicting the expected power generation amount of the installation target using the measured power generation amount is characterized in performing a method comprising.

In addition, in the present invention, in the information providing system of the solar distributed energy resource, in the step (a), the generation amount predicting unit predicts the expected generation amount of the installation target with a pre-determined national average daily operating time, It is characterized in that the predicted generation amount is predicted by weighting the national average daily operating time as the regional insolation weight of the installation target area.

In addition, in the present invention, in the information providing system of the solar distributed energy resource, in the step (a), the generation amount prediction unit, the regional insolation weight weighted for the generation amount prediction is the regional insolation weight of the past year and the future insolation weight of the current year It is characterized by calculating the insolation weight for each region of the current year, the regional insolation weight of the past year is obtained by the regional insolation measured in the current year, and the regional insolation weight for the future year is calculated by predicting and obtaining the regional insolation weight of the past year.

In addition, in the present invention, in the information providing system of the solar distributed energy resource, in the step (a), the power generation amount prediction unit has insolation for each region of the future including tomorrow, predicted based on the present time, and the predicted future It is characterized by using the insolation of each region.

In addition, in the present invention, in the information providing system of the solar distributed energy resource, in the step (b), the power generation amount prediction unit is converted into the measured power generation amount of commercial operation facilities in at least one other area (hereinafter referred to as the second area) The power generation coefficient is applied and converted into the measured power generation of the standard installation condition of the second area, and the converted power generation amount of the standard installation condition of the second area is weighted by the regional insolation weight of the installation target area (hereinafter referred to as the first area). to calculate the regional operating time of the first region during the operation period of the commercial operation facility, and calculate the expected power generation amount of the installation target by the daily operation time, but during the operation period of the commercial operation facility, the calculated regional operating time of the first area It is characterized in that the operation time is applied, and the average daily average operation time determined in advance for the rest of the period other than the operation period is weighted and applied by the local insolation weight of the installation target area.

In addition, in the present invention, in the information providing system of the solar distributed energy resource, in the step (c), the power generation amount prediction unit corresponds to the measured power generation amount of the commercial operation facility in at least one other area (hereinafter referred to as the second area), The converted power generation factor of commercial operation equipment is applied to convert the generation amount measured by region of the standard installation condition of the second region, and to the converted power generation amount of the standard installation condition for each region of the second region, the installation target region (hereinafter referred to as the first region) ) by weighting the insolation weight for each region to calculate the expected generation amount of the installation target.

In addition, in the present invention, in the information providing system of the solar distributed energy resource, in the step (c), the power generation amount prediction unit, for the operating period of the commercial operation facility in the current year (hereinafter the first period), The estimated power generation of the installation target is calculated by weighting the measured power generation by region of the reference installation condition of the second area of the year with the regional solar insolation weight of the first area, and for the remainder of the year (hereinafter referred to as the second period) , by weighting the measured power generation amount by region in the future of the reference installation condition of the second region of the current year by the regional solar insolation weight of the first region to calculate the expected power generation amount of the installation target, to the measured power generation amount of the previous year of the commercial operation facility, By reflecting the efficiency reduction rate according to the annual facility aging, and applying the converted power generation factor of the commercial operation facility to the reflected power generation amount of the previous year, the future regional power generation amount of the reference installation condition of the second area of the current year is calculated, characterized in that do.

In addition, in the present invention, in the information providing system of the solar distributed energy resource, in the step (c), the power generation amount prediction unit applies the local insolation weight of the first region to the first period of the past year of the year. The insolation weight for each region and the regional insolation weight for the future of the current year applied to the second period are divided and obtained. It is characterized by predicting and obtaining the solar insolation for each region in the past year.

In addition, in the present invention, in the information providing system of the solar distributed energy resource, the system further includes a power generation information calculation unit for calculating additional sales, investment cost, and commercial operation period with an input value input through the installation target input unit. characterized by including.

As described above, according to the information providing system of the solar distributed energy resource according to the present invention, if there is an actual amount of power generation, the amount of power generation of the solar power generation facility is accurately predicted by using the actual amount of power generation, and if not, by correcting it with the amount of insolation, etc. However, the effect that can be predicted in real time is obtained immediately.

In addition, according to the information providing system of the solar distributed energy resource according to the present invention, in order to predict the amount of power generation, the insolation actually measured or predicted up to the current point in the current year is used, and the future insolation based on the current point in the current year is in the past By estimating and using the insolation amount or using the predicted insolation value of tomorrow to specifically use tomorrow's insolation, it is possible to increase the prediction accuracy of the generation amount by reflecting climate information such as the recent insolation amount.

1 is a block diagram of an entire system for implementing the present invention.
Figure 2 is a block diagram of the configuration of the information providing system of the solar distributed energy resource according to an embodiment of the present invention.
3 is an exemplary screen for inputting information on an installation target according to an embodiment of the present invention.
4 is a flowchart illustrating a method of predicting a generation amount prediction unit according to an embodiment of the present invention.
5 is an exemplary screen for displaying an expected power generation amount according to an embodiment of the present invention.

Hereinafter, specific contents for carrying out the present invention will be described with reference to the drawings.

In addition, in demonstrating this invention, the same part is attached|subjected by the same code|symbol, and the repetition description is abbreviate|omitted.

First, the configuration of the entire system according to an embodiment of the present invention will be described with reference to FIG. 1 .

As shown in Figure 1, the entire system according to an embodiment of the present invention is a smart terminal 10 used by a user or operator, an information providing client 20 installed in the smart terminal 10, and solar power generation It consists of an information providing server 30 that predicts the amount of power generation or installation cost for the facility and provides it. Database 40 for storing additional necessary data, or climate information server 50 providing climate information such as solar radiation, geographic information server 60 providing geographic information, and power generation information on commercially operated power generation facilities It may be configured to further include a power generation facility management server 70 to provide. In addition, the smart terminal 10 and the information providing server 30 perform data communication through the network 80 .

First, the smart terminal 10 is a terminal used by a user or an operator, and is a terminal equipped with a normal computing function, such as a smartphone, a phablet, a tablet PC, a PC, and a notebook computer. In particular, the smart terminal 10 is a terminal in which applications or mobile applications (or apps, applications), etc. are installed and executed.

In addition, the smart terminal 10 is a display capable of displaying an output such as an image or video, a speaker for outputting audio, an input device such as a touch screen, a communication device for communicating through a network such as a mobile communication network/internet, data or a program It consists of a memory for storing (application, etc.), etc., and a central processing unit that can install and execute applications, etc.

Next, the information providing client 20 is an application or mobile application (or app, application) installed in the smart terminal 10, in conjunction with the information providing server 30, the amount of power generation, sales, commercial operation of the solar power generation facility We provide a service that provides a possible period or installation cost. The information provision service of photovoltaic power generation facilities provides information calculated along with input information by estimating the amount of power generation for a given specific photovoltaic facility, calculating expected sales, installation cost (or investment cost), and commercial operation period. includes services.

Next, the information providing server 30 is a normal server, connected to a network (not shown), and provides a service for estimating the amount of power generation, sales, commercial operation period, or installation cost estimation for solar facilities. In particular, the information providing server 30 is a device having a computing processing function, such as a server device, and is connected to the smart terminal 10 through a wired/wireless network.

In particular, the information providing server 30 may be built to serve as a normal app service server. A web page or an app page of a web application or mobile application (mobile app or application, etc.) for estimating the amount of power generation, sales, commercial operation period, or installation cost for a solar power facility is provided to the user or operator. That is, the information providing server 30 shows the processed result on the application or the application, or receives necessary input data through the application. The mobile page includes driving software for performing specific tasks such as applications in addition to simple text, images, and multimedia.

Next, the climate information server 50 is a server that provides climate information, such as insolation, atmospheric temperature, and wind speed. Preferably, the climate information server 50 is a server of a government agency such as the Korea Meteorological Administration, or a server that professionally provides climate information.

In addition, the climate information server 50 provides not only the climate information of the day, but also the past climate information and forecasted climate information. Past climate information data is provided on a daily basis, climate data prior to a predetermined period (eg, 5 years, 10 years, etc.) is provided, and forecasted climate information is provided on an hourly basis. In addition, climate information is provided subdivided according to latitude and longitude.

Next, the geographic information server 60 is a general geographic information server and provides geographic information, in particular, geographic information related to construction.

Geographic information includes location information such as latitude and longitude of a specific point, such as a specific building, and information such as elevation above sea level. In addition, from the geographic information and the arrangement information of a specific building or facility on the geographic information, an azimuth of a specific surface of the corresponding building/facility may be extracted.

Next, the power generation facility management server 70 is a server that collects and provides power generation information, ie, power generation status information, measured power generation amount, etc. of a solar power generation facility that is being operated commercially.

Preferably, the power generation facility management server 70 collects the amount of power measured in the corresponding facility from each photovoltaic power generation facility being operated. As an embodiment, it is possible to collect measured power generation data by being connected to a wireless network through a wireless communication module or the like from a data acquisition device of a solar power generation facility in commercial operation.

Alternatively, the corresponding generation amount information may be received and accumulated from an operator who operates each solar power generation facility.

Preferably, the measured power generation of the commercial operating facility may be collected on an hourly basis.

In addition, the power generation facility management server 70 manages and provides facility information of each commercial operation facility in addition to the measured power generation amount. Facility information of commercial operation facilities consists of installation location, installation conditions, and the like. The installation location is the installation location, installation area, etc., and the installation conditions are the installation type, installation direction, installation capacity, etc.

Meanwhile, the information providing client 20 and the information providing server 30 may be implemented according to a typical method of configuring a client and a server. That is, the functions of the entire system can be divided according to the performance of the client or the amount of communication between the server and the server. For example, the information providing client 20 performs only the interface role, and the server 30 can perform most of the tasks for estimating the amount of power generation, sales, commercial operation period, or installation cost calculation of the solar power plant. . Alternatively, the information providing client 20 performs most of the generation amount, sales, commercial operation possible time estimation or installation cost calculation work, and the server 30 stores data for calculation, but may perform only a backup function. Hereinafter, it will be described as an information providing system, but it may be implemented in various forms according to the server-client configuration method.

Next, the database 40 is composed of a climate information DB 41 that stores climate information such as insolation, atmospheric temperature, and wind speed, and a power generation information DB 42 that stores measurement information such as generation measured by commercial operation. can be However, the configuration of the database 40 is only a preferred embodiment, and in developing a specific device, it may be configured in a different structure according to the database construction theory in consideration of the ease and efficiency of access and search.

Next, the configuration of the information providing system 300 of the solar distributed energy resource according to an embodiment of the present invention will be described in more detail with reference to FIG. 2 .

The information providing system 300 is a client-server system of the client 20 and the server 30 described above. Depending on the specific implementation technique of the client-server, the function of each component to be described below may be configured by being shared by the client or the server.

As shown in FIG. 2 , the information providing system 300 of the solar distributed energy resource according to an embodiment of the present invention includes a climate information collection unit 31 that collects climate information such as insolation, atmospheric temperature, wind speed, and a specific point. A geographic information collection unit 32 that collects geographic information such as latitude, longitude, and elevation above sea level, an installation target input unit 33 that receives information about an installation target of a solar power plant, and a driving information collection unit that collects power generation from commercial operation It is composed of a unit 34 and a power generation amount prediction unit 35 for estimating the generation amount of a specific facility. In addition, in addition to providing a trend by calculating power generation information by region, such as sales, commercial operation period, and investment cost based on the standard installed capacity, so that a third party other than the person concerned can know, as well as providing the target facility with a specific installed capacity It may be configured to further include a power generation information calculation unit 36 for calculating the generation information of, or, a generation information display unit 37 for displaying and providing the calculated generation information.

First, the climate information collection unit 31 collects climate information such as solar radiation, atmospheric temperature, and wind speed. In particular, the climate information collection unit 31 collects and accumulates climate information from the climate information server 50 .

In addition, the climate information collection unit 31 collects and accumulates not only the climate information of the day, but also past climate information and predicted climate information. Preferably, the past climate information data is collected on a daily basis, and climate data for a predetermined period (eg, 5 years, 10 years, etc. to the present) is collected and stored.

In addition, climate information is divided into latitude and longitude and collected. That is, climate data is collected and stored by region, by hour or by day.

Next, the geographic information collection unit 32 collects general geographic information. In particular, geographic information may be received and collected from the geographic information server 60 or the like.

Geographic information includes location information such as latitude and longitude at a specific point or a specific building/facility, and information such as elevation above sea level. In addition, from the geographic information and the arrangement information of a specific building or facility on the geographic information, an azimuth of a specific surface of the corresponding building/facility may be extracted.

Next, the installation target input unit 33 receives information on the installation target of the solar installation.

The installation target information refers to information on a target to be installed, that is, a solar installation to be installed. The installation target information consists of an installation location, installation conditions, and the like.

The installation location is the location where the photovoltaic facility will be installed or the location of the building or facility where the facility will be installed, and is composed of latitude and longitude or address. The installation area is determined by the installation location. The installation area is a geographically divided area, and refers to the area to which the place (location) where the relevant solar power facility will be installed.

On the other hand, the latitude, longitude, elevation, etc. of the photovoltaic facility are determined or calculated according to the installation location, and the installation area is determined according to the installation location.

In addition, the installation conditions refer to specific conditions (specific values) for installation type, installation direction, installation capacity, and the like. Installation type consists of installation type (land/building) and module specification (single-sided module or double-sided module), and installation direction consists of azimuth and inclination angle. The installed capacity refers to the capacity of the equipment to be installed.

That is, the specific installation conditions of the photovoltaic power generation facility are the contents set by the party (or user) who desires to build the facility as detailed specifications for the facility, and the specific installation capacity that can be installed, the module specification (single-sided module or double-sided module) , means the azimuth and inclination angle conditions of the module. These specific installation conditions are set in the process of the server operator reviewing the layout drawing, estimate, and quantity calculation statement according to the installation type (land/building) at the planned installation site selected in the consultation or contract stage.

As described above, the installation conditions for a specific facility will be referred to as a specific installation condition, and a standard installation condition that is not limited to a specific facility will be referred to as a reference installation condition. Standard installation conditions are limited to pre-determined conditions. As an example, the installation capacity is set to 100 kW, the module specification is a single-sided module, the azimuth is set to the south (0 degrees), and the inclination angle determined by latitude is set to 30 degrees. These standard installation conditions are conditions used to convert specific installation conditions that are different for each installation location of a number of consultations or contracts into a certain installation condition.

An example of a screen for receiving information on an installation target is shown in FIG. 3 .

Next, the operation information collection unit 34 collects facility state information of commercial operation equipment and the measured power generation amount.

Commercial operation facilities refer to facilities that can measure the amount of power generation as actual photovoltaic power generation facilities operated commercially.

Facility information of commercial operation equipment consists of installation location, installation conditions, and the like. The installation location is the installation location, installation area, etc. The installation location consists of latitude and longitude, address, etc.

Installation conditions include installation type, installation direction, and installation capacity. Installation type is divided into installation type and module specification, and installation direction consists of azimuth and inclination angle. The installed capacity refers to the capacity of the corresponding operating facility.

In addition, the power generation amount of the commercial operation facility is actually the measured power generation amount. Preferably, the operation information collecting unit 34 receives and collects power generation data from the power generation facility management server 70 .

Preferably, the amount of electricity generated by the commercial operation facility is collected on an hourly basis (per day).

Next, the generation amount prediction unit 35 predicts the generation amount of the solar power generation facility of the installation target.

At this time, the generation amount prediction unit 35 predicts the generation amount by the following three methods.

First, in the first method, by reflecting the climate information (or weather information) of the installation area of the installation target, and correcting the national average daily average power generation (or national average daily operating hours), the generation amount of the target facility is predicted. .

Next, in the second method, the measured power generation amount of commercial operation operation facilities in other regions within one year (initial stage of commercial operation) and climate information of the installation area of the installation target are simultaneously reflected, predict power generation.

Next, the third method reflects the measured power generation amount of commercial operation facilities in other regions for more than one year (commercial operation maturity stage) and climate information of the installation area of the target facility at the same time for more accurate prediction, and the generation amount of the target facility predict

The method of setting the first, second, and third predicted generation amount prediction method according to the conditions is as follows. A specific setting method is shown in FIG. 4 .

Step 0) As shown in FIG. 4 , first, it is determined whether there is measurement information of commercial operation equipment (S10).

Step 1) If there is no measurement information of commercial operation equipment, the first method is applied as a method for estimating the amount of electricity basically applied to the power generation equipment (S20).

Step 2) If the measurement information of the commercial operation equipment exists, it is determined whether only the measurement information of the initial stage exists (S30).

Step 3) In the initial stage of commercial operation, if there is at least one commercial operation photovoltaic power generation facility that does not secure enough power generation data but is measuring power generation, the second method is applied as the power generation amount prediction method (S40).

Here, if there are several commercial operation photovoltaic power generation facilities that measure power generation without securing sufficient power generation data in the initial stage of commercial operation, the second method is applied to each region in order to more accurately predict the expected power generation amount.

Step 4) If there are photovoltaic power generation facilities in commercial operation that have sufficient power generation data secured in one place and the amount of power generation is still being measured, the third method is applied for the generation amount prediction method (S50) ).

Here, if there are several commercial operation photovoltaic power generation facilities that have sufficient power generation data for the photovoltaic power generation facilities in commercial operation, the third method is applied to each region in order to more accurately predict the expected power generation amount.

Methods 1, 2, and 3 of the power generation amount prediction method will be described in detail below.

Next, the power generation information calculating unit 36 calculates expected power generation information such as investment cost, sales, and commercial operation period of the target facility, that is, the solar power facility to be analyzed.

Preferably, the power generation information calculation unit 36 calculates the investment cost, sales or commercial operation period of a specific installation capacity using the input information of the target facility through the installation target input unit 33, but is not a party. It is calculated based on the standard installed capacity by region so that third parties can understand it, and the trend of fluctuations in investment costs, sales, or commercial operation period is provided. Accordingly, the investment cost, sales, or commercial operation period of the target facility may be calculated by reflecting the specific installed capacity of the target facility in the investment cost, sales, or commercial operation available period calculated on the basis of the reference installed capacity for each region.

First, a method of calculating the investment cost of a specific installed capacity of a target facility will be described.

The investment cost is calculated by the construction cost set at the time of the contract as shown in the following formula, and the option cost and additional cost directly borne by the party.

[Equation 1-1]

Investment cost = contract construction cost + option cost + additional cost

where, contract construction cost = direct construction cost + all business expenses,

Direct construction cost = material cost + electrical construction cost + structure construction cost,

Material cost = module cost + inverter cost + structure cost + fan cost + data acquisition unit (RTU) cost,

All business expenses = design/supervision expenses + other service expenses (surveying/safety diagnosis) + licensing fees,

Option cost = civil construction cost + building reinforcement construction cost,

Additional cost = KEPCO line construction cost + government payment (farm land conservation contribution, land development contribution, etc.).

On the other hand, the power generation information calculation unit 36 obtains the average value of the direct construction cost, general business cost, option cost, additional cost, etc. for each region. At this time, direct construction cost, general service cost, option Costs and additional costs are averaged for each region based on the standard installed capacity to calculate the regional cost (the cost of each item). All service costs are converted into standard installed capacity using the installed capacity factor of the facility and averaged. It is as follows.

[Equation 1-2]

Here, the overall service cost i represents the overall service cost of the facility _i in the area, and n represents the number of all facilities in the area.

The direct construction cost is converted into the standard installed capacity using the installed capacity factor of the facility and averaged. It is as follows.

[Equation 1-3]

Here, the direct construction cost _i and the installed capacity factor _i represent the direct construction cost and the installed capacity factor of the facility i in the corresponding area, respectively.

In addition, the installed capacity coefficient represents the ratio of the installed capacity of the corresponding facility to the standard installed capacity. As an example, if the standard installed capacity is 100kW, the installed capacity factor is 1 if the installed capacity of the facility is 100kW, 0.8 for 80kW, and 1.5 for 150kW.

The option cost is averaged by converting it to the standard installed capacity using the installed capacity factor of the relevant facility. It is as follows.

[Equation 1-4]

The additional cost is converted into the standard installed capacity using the installed capacity factor of the relevant facility and averaged. It is as follows.

[Equation 1-5]

Next, the power generation information calculation unit 36 calculates the investment cost for each region by using the cost of each item by region.

Preferably, the regional investment cost m based on the standard installed capacity is calculated by the following equation (where m means the average value)

[Equation 1-6]

Regional investment cost m = Regional direct construction cost m + Regional option cost m + Regional additional cost m + Regional operating cost m

As described above, not only calculates the trend of change in investment cost based on the standard installed capacity for each region so that a third party other than the party can know, but also calculates the investment cost based on the standard installed capacity for each region, that is, the specific installed capacity of the target facility. It is possible to calculate the investment cost of the target facility even without inputting the investment cost of the target facility through the installation target input unit 33 reflecting .

[Equation 1-7]

Calculation target facility investment cost p = (direct construction cost m in the region + option cost m in the region + additional cost m in the region) x installation capacity factor p + business cost m in the region (here, p means the project)

Next, a method of calculating the commercial operation period of a specific installed capacity of a target facility will be described.

The available period for commercial operation based on the subcontract contract is calculated by inputting through the installation target input unit 33 according to the licensing period and the construction period as shown in the following equation.

[Equation 2-1]

Available period for commercial operation = period of permit before start of construction + period of construction + period of permit after completion

Here, the permit period before construction starts = power generation business permit period + development activity permit period + power supply contract period + construction plan reporting period,

Construction period = construction period after the start of construction,

Permit period after completion = development activity completion inspection period + pre-use inspection period + facility confirmation period.

On the other hand, the power generation information calculation unit 36 calculates the licensing period before the start of construction, the construction period, and the license and permission period after completion by region. The period for each region (period of each item by region) is calculated by averaging the licensing period, etc., based on the standard installation capacity. It is as follows.

[Equation 2-2]

Here, the pre-construction licensing period _i represents the pre-construction licensing period of facility i in the corresponding area, and n represents the number of all facilities in the corresponding area.

In particular, the construction period is averaged by converting it to the standard installation capacity using the specific installation capacity coefficient. It is as follows.

[Equation 2-3]

Here, the construction period _i and the installed capacity factor _i represent the direct construction cost and the installed capacity factor of the facility i in the area.

[Equation 2-4]

Here, the post-completion licensing period i represents the post-completion licensing period for facility i in the area, and n represents the number of all facilities in the area.

Next, the power generation information calculating unit 36 calculates the commercial operation possible period for each region by using the period of each item by region.

Preferably, the commercial operation period _m for each region based on the standard installed capacity is calculated by the following equation.

[Equation 2-5]

Period for commercial operation by region m = Permit period before construction start by region m + Construction period by region m + Permit period after construction by region m

Here, m means an average value.

In order to make it possible for a third party other than the party to know, as described above, not only the fluctuation trend of the commercial operation period is calculated based on the standard installed capacity by region, but also the target facilities, i.e., in the available commercial operation period calculated based on the standard installed capacity by region. , it is possible to calculate the commercial operation period of the target facility by reflecting the specific installed capacity of the calculation target facility without inputting the target facility through the installation target input unit 33 .

[Equation 2-6]

Available period for commercial operation of the calculation target facility m = Permit period before construction start in the area m + Construction period in the area m × Installation capacity factor p + Permit period after construction in the area is completed m

Here, p means the calculation target facility.

On the other hand, if the target facility is still under construction and is in the pre-commercial operation stage, measurement information (measured power generation, inverter operation status, inverter input/output status) of the photovoltaic power generation facility cannot be collected. In such a situation, by predicting the time when commercial operation is possible in the consultation or contract process of consultation, contract, pre-construction licensing, construction, and post-construction licensing, it is possible to calculate a more accurate expected power generation amount or expected sales accordingly. That is, it is possible to more accurately predict the expected power generation or expected sales of a specific consultation or contract by estimating the expected power generation amount, etc., assuming that the corresponding power generation facility is operated based on the time when commercial operation is possible.

Next, the power generation information display unit 37 displays the expected power generation information such as the expected power generation amount.

As shown in FIG. 5 , the power generation information display unit 37 displays the expected generation amount predicted for the installation target, the expected sales according to the expected generation amount, the expected investment cost, the expected commercial operation time, and the like on the screen.

Next, a description will be given of a power generation amount prediction method of the generation amount prediction unit 35 according to an embodiment of the present invention.

Prior to the detailed description, a power generation coefficient, an installation location coefficient, or a power generation efficiency coefficient used in each process will be described.

First, the power generation coefficient is a coefficient representing a specific installation condition compared to the standard installation condition. That is, the power generation coefficient is a coefficient for indicating a specific installation condition as a reference installation condition.

The generation factor _p of a specific facility p is calculated by the following equation.

[Equation 3-1]

Power generation coefficient _p = Azimuth coefficient _p × Inclination angle coefficient _p × Module specification coefficient _p × Installation capacity coefficient _p

Here, each coefficient _p represents each coefficient of the power generation facility p.

Each coefficient represents the relative ratio or size of the specific installation condition of the relevant facility compared to the standard installation condition.

Preferably, the azimuth coefficient is set as follows according to the azimuth angle of the power generation facility p. At this time, the azimuth angle of the standard installation condition is the south direction.

Southwest = 1, Southwest/Southeast 30 degrees = 0.98, Southwest/Southeast 45 degrees = 0.95

Also, preferably, the inclination angle coefficient is set as follows according to the inclination angle of the power generation facility p. At this time, the inclination angle of the standard installation condition is 30 degrees.

30 degrees of inclination = 1, 15 degrees of inclination or 45 degrees of inclination = 0.97

Also, preferably, the module specification coefficient is set as follows according to the model specification of the power generation facility p. At this time, the model specification of the standard installation condition is a single-sided module.

1 for single-sided module, 1.1 for double-sided module

Also, preferably, the installed capacity factor is set as follows according to the installed capacity of the power generation facility p. At this time, the installation capacity of the standard installation condition is 100kW.

1 for 100kW, 0.8 for 80kW, 1.5 for 150kW

On the other hand, if the installation condition of a specific facility p is the same as the standard installation condition, the power generation coefficient of the facility p = 1.

Next, the installation position coefficient will be described.

The installation location coefficient is a coefficient to reflect the influence of the location conditions of power generation facilities such as latitude and elevation above sea level.

The installation location coefficient _p of the power plant p is defined by the following equation.

[Equation 3-2]

Installation location coefficient _p = Latitude coefficient _p × Elevation coefficient _p

Here, the latitude coefficient _p and the elevation coefficient _p are the latitude coefficient and the elevation coefficient of the power plant p, respectively.

Preferably, the latitude coefficient is set as follows according to the latitude. The range of latitude is set to 1.1 ~ 0.9, at this time, the latitude of Korea is in the range of 34 ~ 38 degrees. On the other hand, in the case of the northern hemisphere such as Korea, the latitude coefficient is set to decrease as the latitude increases as an experimental result.

Also, preferably, the elevation coefficient is set as follows according to the elevation above sea level. The range of the elevation coefficient is set to 0.9 ~ 1.1. At this time, the elevation of Korea rises from the west to the east. As a result of the experiment, the elevation coefficient increases as the elevation increases.

Next, the power generation efficiency coefficient will be described.

The power generation efficiency coefficient is a coefficient to reflect the influence of climatic conditions (conditions that affect temperature other than solar radiation) such as air temperature and wind speed.

The power generation efficiency factor _p of the power plant p is defined by the following equation.

[Equation 3-3]

Power generation efficiency coefficient _p = a ₀ + a ₁ T _u + a ₂ W _u - a ₃ T _u ² - a ₄ T _u W _u - a ₅ W _u ²

Here, a ₀ , a ₁ , ..., a ₅ are predetermined constants. Preferably, the constants a ₀ = 0.7284, a ₁ =0.003492, a ₂ = 0.1731, a ₃ = 0.000148, a ₄ = 0.0007319, a ₅ = 0.01289.

In addition, T _u and W _u represent the atmospheric temperature (°C) and the wind speed (m/s) of the installation area u of the power generation facility p, respectively.

The power generation efficiency coefficient is the increase/decrease coefficient of the power generation efficiency that is affected by the temperature of the solar module, and the temperature of the solar module rises due to the increase in atmospheric temperature, thereby reducing the power generation efficiency and increasing the wind speed. It is an experimental formula for the phenomenon that the power generation efficiency increases due to a decrease in the temperature of In addition, it is possible to calculate the power generation efficiency coefficient in units of time by applying the collected air temperature and wind speed in units of time.

Next, a method of predicting the amount of power generation will be described.

First, as the first method, the generation amount prediction unit 35 predicts the generation amount of the target facility based on the national average daily operating time, but the generation coefficient reflecting the installation conditions of the target facility and the installation reflecting the installation location of the area It is predicted by reflecting the location coefficient, the power generation efficiency coefficient reflecting the efficiency of the module that changes according to the atmospheric temperature and wind speed, and the insolation weight reflecting the amount of insolation (S30).

The conventional power generation forecasting method collects the measured power generation from solar power generation facilities in commercial operation, calculates the annual power generation by accumulating the measured power generation by day, and considers the efficiency reduction rate of 0.3 to 0.5% due to the aging of the annual facility. Thus, it is possible to predict the annual power generation amount of the solar power generation facility in the next year under specific installation conditions.

A more preferable method is to calculate the national average daily operating time based on the annual power generation as shown in the following equation, and utilize the national average daily operating time of a certain value as a major variable for predicting the amount of power generation of photovoltaic power generation facilities under specific installation conditions. can

[Equation 4-1]

Here, N represents the number of all facilities in all regions.

However, there is a national average daily operating time, which was revealed based on the amount of electricity measured through a number of solar power generation facilities that have been in commercial operation for a long time in the industry. That is, the national average daily operating time is a constant value determined in advance by experiment or experience, and preferably the value is 3.6 ~ 4.0 h.

If no measurement information (measured power generation, inverter operation status, inverter input/output status) can be collected from solar power generation facilities because all facilities are under construction, the expected power generation and estimated sales according to the expected power generation can be calculated using the measurement information. can't In this case, in order to predict the expected power generation and sales in any of the consulting, contract, pre-construction licensing, construction, and post-construction licensing phases, calculate the daily average daily operation time for each region from the national average daily operation time, which is a constant value, and , it is possible to predict the expected daily power generation by using the daily average daily operating hours for each region. That is, by obtaining the national average daily operating time by region and by day, it is possible to predict the expected generation amount more accurately than the method using the constant value of the national average daily operating time.

The daily average daily operating hours _d by region for d days are calculated as follows.

[Equation 4-2]

Daily average daily operating hours by region _d = National average daily operating hours × Daily insolation weight by region _d

Here, the national average daily operating time is calculated by the above [Equation 4-1], but if there is no measurement information or is insufficient, a constant value of 3.6 ~ 4.0 h is used. In addition, the daily insolation weight _d for each region is the daily insolation weight for each region on the d day. Day d represents the dth day (day) in 365 days of a year.

The daily insolation weight prediction for each region on the d day is based on the insolation for a certain past year, and is obtained as follows.

Step 1) Calculate the daily insolation _d by region for d days (during the past year) by averaging the daily insolation for each region for a certain past year (for example, the past 10 years).

Step 2) Calculate the national average daily insolation (during the past year) by averaging the daily insolation for each region (during the past year) on day d. At this time, the daily insolation for all 365 days of the past year and by region for all regions is averaged.

Step 3) Calculate the daily insolation weight _d by region (during the past certain years) on day d by applying the daily insolation by region and the national average daily insolation on day d. It is as follows.

[Equation 4-3]

Daily insolation weights by region for the past year _d

= Average daily insolation _d by region for a certain past year / National average daily insolation _d for a certain past year, provided that 1≤d≤365

Here, the average daily insolation weight _d by region for a certain past year is used to estimate the daily insolation for each region in the future based on the present year. That is, the average value for a certain past year is used as the daily insolation weight for each region in the future to predict the expected annual power generation.

Specifically, the average daily insolation d by region (national average) for a certain past year refers to the average of all regional (national average) daily insolation for the _d days in the past certain year.

However, if it is specifically to predict tomorrow's regional power generation more accurately, it is possible to predict tomorrow's regional power generation amount by calculating tomorrow's solar radiation weight using tomorrow's solar radiation forecast based on the present time.

Tomorrow's insolation (insolation weight by region) refers to a part of the future, and it is intended to predict by designating tomorrow.

Step 4) Calculate the daily insolation weight _d for each region in the past based on the present on the d day of the year according to the following formula.

[Equation 4-4]

Daily insolation weight by region in the past year _d = Daily insolation by region in the past of the current year _d / National average daily insolation in the past year _d , provided that 1≤d≤d ₀ -1

Here, the daily insolation d for each region on the d day of the current year is the value measured or predicted for each region in the current year, and if the current date is the d _0th day of the year, d is 1,2,..., d It has a value of ₀ -1. That is, day d represents the dates from the first day of the year to yesterday.

Step 5) Predict the daily insolation weight for each region on the d day of the year according to the following equation.

[Equation 4-5]

Here, d ₀ represents the current day, and D represents the total number of days in one year, preferably 365.

In addition, the regional insolation weight _d in the past for the current year is the daily insolation weight for each region calculated based on the insolation value measured for each region or the predicted insolation value, and the daily insolation weight _d for each region in the future of the current year is the above [Equation 4 - 3] is used as the daily insolation weight _d for each region for a certain past year.

If, specifically, in order to predict tomorrow's regional power generation more accurately, tomorrow's insolation weight is used by using tomorrow's insolation predicted based on the present time.

Next, by applying the daily insolation weight for each region of the current year to predict the generation amount, the average daily operating time for each region on the d day of the current year is predicted. It is as follows.

[Equation 4-6]

Average daily operating hours by region in the current year _d = National average daily operating hours × Daily insolation weight _d by region in the current year, provided that 1≤d≤D

In addition, the expected daily power generation by region on the d day of the current year is predicted as follows.

[Equation 4-7]

Estimated daily power generation _p,d by region for the current year

= Specific installed capacity _p × Average daily operating time per region in the current year _d

× Daily generation efficiency coefficient by region in the current year _d × Installation location coefficient _p × Generation coefficient _p

However, 1≤d≤D

Here, the specific installation capacity _p , the installation location coefficient _p , and the generation coefficient _p represent the installed capacity of the power generation facility p to be predicted, the installation location coefficient, and the generation coefficient of the specific installation condition, respectively. In addition, the national average daily average operating time is a constant value, preferably set to 3.6 ~ 4.0 h.

Therefore, it can be seen that the above [Equation 4-7] is for estimating the expected power generation amount of the power generation facility under a specific installation condition.

On the other hand, in the above equation, the power generation efficiency coefficient by region for the current year and the future regional power generation efficiency coefficient for the current year are calculated in the same way as in the method of obtaining the past or future value of the current year for the insolation weight.

In addition, in Equation 4-7, when the installed capacity is set to the standard installed capacity, that is, 100 kW and the power generation coefficient is set to 1, the expected power generation amount of the power generation facility under the standard installation condition can be calculated.

Therefore, as described above, the expected generation amount fluctuation trend is calculated based on the standard installed capacity for each region so that a third party other than the person concerned can know, and the target facility, that is, the calculation target facility It is possible to estimate the expected generation amount of the target facility by reflecting the specific installed capacity and generation coefficient of

As described above, as the facility is still under construction, it is not possible to collect any measurement information (measured power generation, inverter operation status, inverter input/output status) of solar power generation facilities. If calculation is not possible, in order to predict the expected power generation and sales in any one stage of consultation, contract, pre-construction permit, construction, and post-construction permitting and permitting, according to the first method as described above, insolation weight using weather information By applying the power generation efficiency coefficient, the installation location coefficient according to the expected installation location of the photovoltaic power generation facility, and the power generation coefficient according to the specific installation conditions of the photovoltaic power generation facility, the expected power generation amount can be predicted.

Next, as the second method, the generation amount prediction unit 35 predicts the generation amount of the target facility based on the national average daily operating time as in the first method, but partially reflects the measured generation amount of the commercial operation facility ( S40).

The second method collects measurement information (measured power generation) of solar power generation facilities in commercial operation under specific installation conditions in order to more accurately predict the expected generation amount and the expected sales according to the expected generation amount, and calculates the measured generation amount in time units by day It is accumulated and reflected in the forecast of expected daily power generation by region.

In this case, since the commercial operation facility is in the initial stage of commercial operation, it is a case in which sufficient measured power generation amount is not secured. In particular, it is the case that the measured power generation of commercial operation facilities is less than one year.

Specifically, commercial operation facilities are operated from d1 to d2 of the current year, and d2 is considered as the current time. Therefore, the power generation measured by the commercial operation facility was collected from d1 to d2-1, and it is considered that there is no measured power generation before and after d1 days and d2 days.

The detailed process of estimating the expected power generation of the second method is as follows.

Step 1) Calculate the daily measured power generation _{v, q, d} of commercial operation facility q on d day by summing the daily hourly power generation amount of commercial operation facility q in the address area v within specific installation condition.

[Equation 5-1]

Daily measured power generation under specific installation conditions _{v, q, d} = Cumulative total of time unit measured power generation for d days under specific installation condition _q

Step 2) In order to convert the daily measured power generation of commercial operation equipment (address in a specific area v) under specific installation condition _q into the standard installation condition, calculate the converted power generation coefficient _q of the commercial operation facility q by the following equation do.

[Equation 5-2]

Conversion power generation factor _q = [ 1 + (1 - azimuth coefficient _q ) ] × [ 1 + (1 - inclination angle coefficient _q ) ] × [ 1 + (1 - module specification coefficient _q ) ] x [ 1 + (1 - installed capacity) coefficient _q ) ]

Here, the azimuth coefficient _q , the inclination angle coefficient _q , the module specification coefficient _q , and the installed capacity coefficient _q respectively represent the azimuth coefficient, the inclination angle coefficient, the module specification coefficient, and the installed capacity coefficient of the commercial operation facility q.

Step 3) Convert the daily measured power generation _{v, q, d} of the standard installation condition of the d day of the commercial operation facility in the address v in a specific area according to the following formula.

[Equation 5-3]

Daily measured power generation _{v, q, d} under the standard installation condition = Daily measured power generation _{v, q, d} × converted power generation factor _q under specific installation conditions

Step 4) By reflecting the measured power generation amount measured from commercial operation facility q in area v for each region, calculate the expected daily power generation _u,d by region under the standard installation condition on day d in area u as shown in the following equation.

[Equation 5-4]

Estimated daily power generation by region under standard installation conditions _u,d = Daily measured power generation under standard installation conditions _v,q,d × daily insolation weight by region _u,d

Here, the daily insolation weights _{u, d} for each region are the daily insolation weights for each region on the d day of the region u.

Step 5) Convert the expected daily power generation amount of the regional standard installation condition into the daily operating hours _u,d of the regional standard installation condition on the d day of the region u as shown in the following equation.

[Equation 5-5]

Daily operating hours _u,d by region under standard installation conditions

= Estimated daily power generation _u,d / standard installation capacity by region under standard installation conditions

= Measured daily power generation by region _{v, q, d} × regional insolation weight _{u, d} / standard installed capacity

= Daily measured power generation under specific installation conditions _{v, q, d} × converted power generation factor _q × daily insolation weight for each region _{u, d} / standard installed capacity

Here, preferably, the reference installation capacity is set to 100 kW.

In addition, the daily insolation weight _u by region of region u is the daily insolation weight for each region in the past from the time when power generation from commercial operation facility q was started to be measured.

Step 6) The daily insolation weight for each region of the current year is predicted according to Equation 4-5.

Step 7) Next, using the predicted daily insolation weights for each region of the current year, the estimated daily operating hours _u,d for each region of the current year's standard installation conditions are predicted by the following equation.

[Equation 5-6]

Here, commercial operation facilities are operated from d1 to d2 of the current year, and d2 is regarded as the present time. Therefore, the power generation measured by the commercial operation facility was collected from d1 to d2-1, and it is considered that there is no measured power generation before and after d1 days and d2 days.

In addition, the insolation weights _{u ,d} by region in the past for the current year are the daily insolation weights for each region calculated based on the insolation values measured for each region or the predicted insolation values for each region. Equation 4-3] is used as the daily insolation weights _{u, d} for each region for the past predetermined year.

If, specifically, in order to predict tomorrow's regional power generation more accurately, tomorrow's insolation weight is used by using tomorrow's insolation predicted based on the present time.

As can be seen from the above equation, it is a power generation facility that cannot predict the amount of power generation based on the measured power generation because it is a stage prior to commercial operation by reflecting the daily hourly measured power generation of the commercial operation facilities in a specific area under specific installation conditions. 1 It is possible to predict more accurately by using the measured power generation in a specific area rather than the predicted power generation forecasting method.

Step 8) That is, the estimated daily power generation _{u, d} by region in the current year under the standard installation conditions of region u is predicted as follows.

[Equation 5-7]

Estimated daily power generation by region for the current year _u,d = Standard installed capacity × Estimated daily operating time for each region in the current year _u,d × Installation location coefficient _u , provided that 1≤d≤D

Here, the reference installation capacity is 100 kW, and the generation coefficient is set to 1 as a coefficient of the reference installation condition. In addition, the installation location coefficient _u is the installation location coefficient of the target facility p in the relevant area u.

Step 9) In addition, the average expected power generation _u,p,d per day of the current year of the (region u) power generation facility p under specific installation conditions is predicted as follows.

[Equation 5-8]

Estimated daily generation of power generation facilities _u,p,d = Specific installed capacity _p × Estimated daily operating time by region for the current year _u,d × Installation location coefficient _u × Generation coefficient _p , provided that 1≤d≤D

Here, the specific installation capacity _p , the installation location coefficient _u , and the generation coefficient _p represent the installation capacity, installation location coefficient, and generation coefficient of the power generation facility p, respectively.

Next, as a third method, the generation amount prediction unit 35 predicts the generation amount of the target facility by using the measured generation amount of the commercial operation facility (S50).

The first method described above is a method of forecasting by applying weather information, and the second method is in the early stage of commercial operation, so sufficient measured power generation data is not secured. This is a more accurate way to predict.

Therefore, even if there is only one measured power generation, if the measured power generation data is sufficient, for example, if the measured power generation data for more than one year is secured, the predicted power generation amount can be predicted more accurately. That is, the third method is applied when sufficient measured power generation data is secured.

The detailed process of the third method is as follows.

Step 1) Based on the daily measured power generation of the previous year, in order to estimate the expected daily measured power generation for the current year, the efficiency reduction rate index according to the annual facility aging is set as follows.

[Equation 6-1]

Efficiency decrease rate index = 0.003 ~ 0.005 (efficiency decrease 0.3 ~ 0.5%)

The efficiency reduction rate index according to the annual equipment aging is a constant value determined in advance and may be changed.

Step 2) Estimated daily power generation in the future d days of the current year for commercial operation facility q in area v under specific installation conditions is calculated by the following formula.

[Equation 6-2]

Estimated daily power generation in the current year _v,q,d = Measured daily power generation in the previous year _v,q,d × ( 1 - Efficiency Decrease Index ) , where 1≤d≤D

Here, v is the area of commercial operation equipment q, q is a subscript indicating commercial operation equipment, and d is a subscript indicating date.

Step 3) In order to convert the expected daily power generation amount of the commercial operation facility q in the specific area within the specific installation condition to the standard installation condition, the converted power generation factor is calculated as in [Equation 5-2].

[Equation 5-2]

Conversion power generation factor _q = [ 1 + (1 - azimuth coefficient _q ) ] × [ 1 + (1 - inclination angle coefficient _q ) ] × [ 1 + (1 - module specification coefficient _q ) ] x [ 1 + (1 - installed capacity) coefficient _q ) ]

Here, the azimuth coefficient _q , the inclination angle coefficient _q , the module specification coefficient _q , and the installed capacity coefficient _q respectively represent the azimuth coefficient, the inclination angle coefficient, the module specification coefficient, and the installed capacity coefficient of the commercial operation facility q.

Step 4) Convert the expected daily power generation by region in the future on the d day of the current year under the standard installation conditions according to the following formula.

[Equation 6-3]

Estimated daily power generation in the current year under standard installation conditions _v,d = Estimated future daily power generation in the current year under specific installation conditions _v,q,d × converted power generation coefficient _q , where d ₀ + 1≤d≤D

Here, d ₀ represents the current time point, that is, the current day. Therefore, the expected daily generation _{v, q, d} for the current year is the expected future generation for the current year based on the current point in time at which the generation is measured. Also, v represents the area where the commercial operation q is installed.

Step 5) Based on the current point d ₀ of the equipment q in commercial operation under specific installation conditions, the daily measured power generation by region for the past d days of the current year is converted into the standard installation conditions.

[Equation 6-4]

Measured daily power generation in the past year _v,q,d = daily measured power generation _v,q,d × converted power generation factor _q , provided that 1≤d≤d ₀ - 1

Here, d ₀ represents the current time point, that is, the current day. Therefore, the daily measured power generation under the standard installation condition is the measured power generation amount in the past based on the current point in time when the power generation amount is measured.

Step 6) Next, the expected daily power generation for each region on the d day of the current year under the standard installation conditions of commercial operation equipment q in the address in a specific area v in the specific installation condition is predicted according to the following equation.

[Equation 6-5]

Step 7) As a method of reflecting the daily expected power generation amount of the commercial operation facility for the current year by region, the daily average expected power generation amount of the regional standard installation conditions for the d day of the area u is calculated by the following equation.

[Equation 6-6]

Here, the commercial operation facility is currently operating from the 1st day of the current year to the d ₀ -1 day based on the d ₀ day, so the amount of power generated by the commercial operation facility was collected from the 1 day to the d ₀ -1 day, d ₀ It is considered that there is no measured power generation from day to day 365.

In addition, the insolation weights _{u ,d} by region in the past for the current year are the daily insolation weights for each region calculated based on the insolation values measured for each region or the predicted insolation values for each region. Equation 4-3] is used as the daily insolation weights _{u, d} for each region for the past predetermined year.

If, specifically, in order to predict tomorrow's regional power generation more accurately, tomorrow's insolation weight is used by using the predicted tomorrow's solar radiation based on the current d ₀ day.

In addition, the regional installation location coefficient u is the regional installation location coefficient of the region u.

Step 8) Calculate the daily expected power generation _u,p,d under the specific installation conditions of the power generation facility p by the following equation.

[Equation 6-7]

Here, the installation location coefficient _u and the generation coefficient _p represent the u-region installation location coefficient and the generation coefficient of the power generation facility p, respectively.

Consultation, contract, pre-construction licensing, construction, post-construction licensing, commercial operation, and asset management in any case, the estimated power generation and expected sales according to the expected power generation, total estimated investment cost, and commercial operation time by region of the desired installation address In order to more accurately predict with specific installation conditions or reference installation conditions, according to the first method to which weather information is applied, the second method to apply the fusion of weather information and measured generation information, and the third method to apply the measured generation information, multiple By setting the set value, the expected power generation can be predicted more accurately.

On the other hand, in all the predicted power generation forecasting methods that are predicted for each region, preferably, the point refers to the meteorological information measurement location of the Meteorological Agency, the weather forecast location or modeling location of the Meteorological Agency at regular intervals according to latitude and longitude. A point within a radius of 1km is defined as a point, and the area on the administrative district containing several points is used as a region, and the point values are averaged and used as a representative value.

In the above, the invention made by the present inventors has been described in detail according to the embodiments, but the present invention is not limited to the embodiments, and various changes can be made without departing from the gist of the present invention.

10: smart terminal 20: information providing client
30: information providing server 31: climate information collection unit
32: geographic information collection unit 33: installation target input unit
34: operation information collection unit 35: generation amount prediction unit
36: power generation information calculation unit 37: power generation information display unit
40: database
50: climate information server 60: geographic information server
70: power generation facility management server
80: network

Claims (10)

In the information providing system of the solar distributed energy resource,
a climate information collection unit that collects climate information including regional solar insolation;
a geographic information collection unit for collecting geographic information including latitude, longitude, and elevation of a specific point;
an installation target input unit for receiving information (hereinafter, installation target information) on an installation target of a photovoltaic power generation facility including an installation location and installation conditions;
an operation information collection unit that collects power generation of commercial operation facilities;
a generation amount predicting unit for predicting the generation amount of the power generation facility of the installation target, and predicting the generation amount using the solar insolation by region of the installation location of the installation target, and the generation amount of the commercial operation facility; and,
Includes a power generation information display unit for displaying the input installation target information, the calculated power generation forecast information,
The power generation prediction unit,
(a) if there is no information on the measured power generation amount of the commercial operation facility, predicting the expected power generation amount of the installation target using the solar insolation of the installation target area;
(b) If the measured power generation information of the commercial operation facility is less than one year, the measured power generation amount is used during the period in which the measured power generation amount exists, and the estimated power generation amount of the installation target is calculated using the solar insolation of the area for the remaining period. predicting; and,
(c) if the measured power generation information of the commercial operation facility is more than one year, predicting the expected power generation amount of the installation target by using the measured power generation amount,
In the step (a), the generation amount prediction unit predicts the expected generation amount of the installation target with a predetermined national average daily operating time, but with the regional solar radiation weight of the installation target area, the national average daily operating time Predict the expected power generation by weighting
In step (a), the power generation forecasting unit obtains the regional insolation weight weighted to predict the generation amount from the regional insolation weight of the past year and the regional insolation weight of the current year in the future, and the regional insolation weight of the past year is the current year The solar energy distributed energy resource information providing system, characterized in that it is obtained by the insolation measured by region, and the weight of insolation by region in the future of the current year is obtained by predicting the insolation by region in the past year.
delete delete delete According to claim 1,
In the step (a), the power generation amount prediction unit, there is solar insolation for each region in the future, including tomorrow, predicted based on the present time, and information on distributed solar energy resources, characterized in that using the predicted future regional insolation delivery system.
According to claim 1,
In the step (b), the power generation prediction unit converts the measured power generation amount of the reference installation condition of the second area by applying a converted power generation factor to the measured power generation amount of commercial operation facilities in at least one other area (hereinafter referred to as the second area) And, by weighting the converted power generation amount of the standard installation condition of the second area by the regional solar radiation weight of the installation target area (hereinafter referred to as the first area), the operating time of each region of the first area during the operation period of the commercial operation facility , and calculate the expected power generation amount of the installation target by the daily operation time, but apply the calculated regional operation time of the first region during the operation period of the commercial operation facility, and nationwide for the remainder of the period other than the operation period The system for providing information on distributed energy resources for solar energy, characterized in that the average daily average operating time is weighted and applied by the local solar radiation weight of the installation target area.
According to claim 1,
In the step (c), the power generation forecasting unit applies the converted power generation coefficient of the commercial operation facility to the measured power generation amount of the commercial operation facility in at least one other area (hereinafter referred to as the second area) to apply the standard installation condition of the second area Converting to the regional measured power generation of Information providing system of solar distributed energy resources, characterized in that.
8. The method of claim 7,
In step (c), the generation amount prediction unit,
For the operating period of the commercial operation facility in the current year (hereinafter referred to as the first period), the measured power generation amount by region of the reference installation condition of the second region of the current year is weighted by the regional insolation weight of the first region, and the installation target Calculate the expected power generation of
For the remaining period of the current year (hereinafter referred to as the second period), the estimated generation amount of the installation target is weighted by the insolation weight of the region in the first area to the future regional power generation of the reference installation condition of the second area of the current year to calculate,
In the previous year's measured power generation of the commercial operation facility, the efficiency reduction rate due to annual facility aging is reflected, and the converted power generation coefficient of the commercial operation facility is applied to the reflected previous year's measured power generation amount to determine the future of the standard installation conditions for the second area of the current year. A system for providing information on solar distributed energy resources, characterized in that it calculates the measured power generation amount by region.
9. The method of claim 8,
In the step (c), the power generation forecasting unit, the regional insolation weight of the first region, the regional insolation weight of the past year applied to the first period, and the region in the future of the current year applied to the second period Solar distributed energy, characterized in that it is obtained by dividing it by insolation weights, the regional insolation weights of the past year are obtained by the regional insolation measured in the current year, and the regional insolation weights of the future year are obtained by predicting the regional insolation in the past year Information provision system of resources.
According to claim 1,
The system, solar distributed energy resource information providing system, characterized in that it further comprises a power generation information calculation unit that additionally calculates sales, investment cost, and commercial operation period with the input value input through the installation target input unit.

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