JP2021022288A - Power demand prediction system and power demand prediction program - Google Patents

Abstract

To provide a power demand prediction system and a power demand prediction program capable of predicting the whole private power generation amount with high accuracy and predicting a power supply amount with high accuracy.SOLUTION: A plurality of users (population) having a photovoltaic power generation facility includes a population of second users having a first smart meter for measuring a private power generation amount by the photovoltaic power generation facility. A power demand prediction system 1 includes a communication part 11 for acquiring information on a private power generation amount measured by the first smart meter transmitted onto a network through a communication terminal from the network, and a calculation part 14 for calculating an average private power generation amount being an average of private power generation amounts in the population on the basis of the private power generation amount acquired by the communication part 11, calculating the whole private power generation amount being the whole private power generation amount of the population on the basis of the average private power generation amount, and calculating a prediction value of a power supply amount by subtracting the whole private power generation amount from the a prediction value of a power consumption amount.SELECTED DRAWING: Figure 1

Description

The present invention calculates the predicted value of the required power supply amount in the power supply area including a plurality of consumers having solar power generation facilities, at least the power consumption amount in the power supply area calculated from the weather information in the power supply area. It relates to a power demand prediction system and a power demand prediction program that calculate based on the predicted values.

The full liberalization of electricity retailing in 2016 has given consumers the freedom to choose electricity retailers. The retailer procures power from the power generation company through the power system maintained by the general power transmission and distribution business operator, and supplies power to consumers in the power supply area (for example, a local unit area). ..

The retailer predicts the power consumption in the power supply area based on the weather information, etc., and then predicts the power supply amount required for the power supply area based on the predicted power consumption. Then, based on the predicted power supply amount, the day is divided every 30 minutes, and the power supply amount is planned every 30 minutes. However, since the power consumption in the power supply area depends on the weather and the like, the power supply plan of the retailer may have to be revised according to the increase or decrease of the power consumption.

The case of modifying the power supply plan may be, for example, a case where the temperature becomes higher than the temperature predicted by the weather information. In this case, when the customer operates the air conditioning equipment, the power consumption in the power supply area exceeds the plan, so the retailer must supply more power than originally planned. I have to. The retailer then re-estimates the electricity supply and makes a new plan. Then, the amount of electricity that is the difference between the new plan and the original plan is procured from the wholesale electricity trading market.

As described above, the retailer amends the power supply plan in accordance with the ever-changing power consumption, which is the plan of the power supply and the actual supply to the retailer. This is due to the imposition of a supply and demand obligation that must match the actual performance of electricity. If there is a discrepancy between the plan and the actual results, the retailer must pay a penalty to the general transmission and distribution business operator. Therefore, retailers need to accurately predict and plan their power supply in order to minimize penalty payments.

Here, for the prediction of the power consumption actually consumed by the consumer, for example, as disclosed in Non-Patent Document 1, weather information such as temperature, humidity, discomfort index, and amount of solar radiation, daytime data, and the like are explanatory variables. It has been performed conventionally based on the multiple regression equation, and the accuracy is high. However, electricity retailers cannot directly apply the predicted power consumption to the electricity supply plan. This is because the number of consumers who generate in-house power generation is increasing due to the spread of solar power generation equipment, and the power to be supplied by retailers is less than the power consumption due to the in-house power generation. Therefore, in order to reduce the penalty as much as possible, in addition to predicting the power consumption in the power supply area, the total private power generation amount of a plurality of consumers who have solar power generation facilities in the power supply area (total private power generation amount). It is important to make accurate predictions. Here, as a method for predicting the total amount of private power generation, a method for estimating the power generation output of photovoltaic power generation, as disclosed in Patent Document 1 and Patent Document 2, is known.

Japanese Unexamined Patent Publication No. 2012-43853 Japanese Unexamined Patent Publication No. 2016-152644

Written by Ken Fukuda Technology Development News No. 159 "Introduction of Electricity Demand Forecasting System" Chubu Electric Power August 2018

However, the above-mentioned prior art has the following problems.
The method for estimating the power generation output of photovoltaic power generation disclosed in Patent Document 1 and Patent Document 2 predicts the total amount of private power generation from the solar radiation amount data. However, the total amount of private power generation depends on the degree of deterioration of the photovoltaic power generation equipment and the direction in which the solar panels are installed, so even if only the solar radiation amount data is taken into consideration, there is concern that the prediction accuracy of the total amount of private power generation will decline. Will be done. If the prediction accuracy of the total amount of private power generation decreases, it becomes impossible to accurately predict the amount of power supply. If it becomes impossible to accurately predict the amount of power supply, there will be a discrepancy between the plan for the amount of power supply and the actual amount of power actually supplied, and retailers will have a large amount of power transmission and distribution business operators. You will have to pay a good penalty.

In addition, the revision of the power supply amount plan explained above is performed when there is a discrepancy between the power supply amount plan and the actual power supplied, but at present, the retailer has a discrepancy. It takes 30 minutes from the beginning until you can actually grasp that the divergence has occurred. In recent years, smart meters that measure the amount of electricity sold and purchased have become widespread, and the smart meters transmit the measured values to retailers (transmission by the so-called A route), but this transmission is performed every 30 minutes. This is to be retailed. Therefore, there is a risk that the penalty to be paid before the revision of the power supply plan is increased. This point will be described in detail with reference to FIG. In FIG. 5, the horizontal axis is time, and the scale is at intervals of 30 minutes. The vertical axis is the power supply amount, and represents the fluctuation of the planned power supply amount (planned power supply amount ep21) and the actual power supply amount (actual power supply amount er21) with the passage of time. ing. The difference between the planned power supply amount ep21 and the actual power supply amount er21 begins, and the actual power supply amount er21 starts to fall below the planned power supply amount ep21 at the time point t1. Then, the retailer can grasp that this divergence has started at the time point t2, which is 30 minutes after the time point t1. The work for making a new plan starts from this time point t2, and the time point t4 two hours after the time point t1 can actually make a new plan. It can be seen that the planned power supply amount ep21 fluctuates in almost the same transition as the actual power supply amount er21 from the time point t4 due to the new plan being made. As described above, the plan is revised two hours after the start of the discrepancy between the plan and the actual result, and there is a risk that a penalty must be paid for the discrepancy between the plan and the actual result in the two hours. There is. Therefore, it is desirable to shorten the time from the start of the gap between the plan and the actual result until the plan is revised.

The present invention is for solving the above-mentioned problems, and is a power demand forecasting system and a power demand forecasting program capable of accurately predicting the total amount of private power generation and accurately predicting the amount of power supply. The purpose is to provide.

In order to solve the above problems, the electric power demand forecasting system and the electric power demand forecasting program of the present invention have the following configurations.
(1) Prediction of the required power supply in the power supply area including multiple consumers with photovoltaic power generation facilities, at least the prediction of the power consumption in the power supply area calculated from the weather information in the power supply area. In the electric power demand forecasting system calculated based on the value, a plurality of consumers refer to a group of consumers having a smart meter for measuring the amount of private power generated by the photovoltaic power generation facility and a communication terminal capable of communicating with the smart meter. Based on the communication unit that acquires the information of the private power generation amount measured by the smart meter transmitted on the network via the communication terminal from the network and the private power generation amount acquired by the communication unit. Calculate the average private power generation amount, which is the average value of the private power generation amount in the group, calculate the total private power generation amount, which is the total private power generation amount of multiple consumers, based on the average private power generation amount, and predict the power consumption. It is characterized by having a calculation unit for calculating a predicted value of the electric power supply amount by subtracting the total private power generation amount from the value.

(2) In the electric power demand forecasting system described in (1), the total amount of private power generation is calculated by multiplying the average amount of private power generation by the number of cases of a plurality of consumers.

(3) In the power demand forecasting system described in (1), the total private power generation amount is the total value of the power generation output of the total solar power generation facilities of a plurality of consumers, and the average private power generation amount is the total value of the photovoltaic power generation in the group. It is characterized in that it is calculated by multiplying the conversion efficiency, which is the value divided by the average value of the power generation output of the equipment.

(4) Prediction of the required power supply in the power supply area including multiple consumers with photovoltaic power generation facilities, at least the prediction of the power consumption in the power supply area calculated from the weather information in the power supply area. In a power demand forecasting program that calculates based on values, multiple consumers refer to a group of consumers who have a smart meter that measures the amount of private power generated by a photovoltaic power generation facility and a communication terminal that can communicate with the smart meter. Information on the amount of private power generation measured by the smart meter transmitted on the network via the communication terminal, which is included, is acquired from the network, and based on the acquired private power generation amount, the amount of private power generation in the group Calculate the average private power generation amount, which is the average value, calculate the total private power generation amount, which is the total private power generation amount of multiple consumers, based on the average private power generation amount, and calculate the total private power generation amount from the predicted value of the power consumption amount. It is characterized in that the predicted value of the electric power supply amount is calculated by reducing the amount.

(5) In the power demand forecasting program described in (4), the total amount of private power generation is calculated by multiplying the average amount of private power generation by the number of cases of a plurality of consumers.

(6) In the power demand forecasting program described in (4), the total amount of private power generation is the total value of the power generation output of the total solar power generation facilities of multiple consumers, and the average amount of private power generation is the total amount of photovoltaic power generation in the group. It is characterized in that it is calculated by multiplying the conversion efficiency, which is the value divided by the average value of the power generation output of the equipment.

According to the power demand forecasting system described in (1) and the power demand forecasting program described in (4), it is possible to accurately predict the total amount of private power generation and accurately predict the amount of power supply. , Penalty for general power transmission and distribution companies can be suppressed.

The communication unit can obtain an actual measurement value of the amount of private power generation from a group of consumers who have a smart meter for measuring the amount of private power generation by the photovoltaic power generation facility. Then, the calculation unit calculates the average private power generation amount based on the measured private power generation amount, and calculates the total private power generation amount. Since the total amount of private power generation is calculated based on the measured value, it reflects the degree of deterioration of the photovoltaic power generation equipment and the direction in which the solar panel is installed, and as in the past, the total amount of solar radiation is taken into consideration. Prediction accuracy is improved compared to predicting the amount of private power generation.

In addition, the predicted value of the required power supply amount in the power supply area is calculated by subtracting the total private power generation amount from at least the predicted value of the power consumption amount in the power supply area predicted by the weather information in the power supply area. To. As described above, the predicted value of the power consumption is calculated based on the weather information such as temperature, humidity, discomfort index, and amount of solar radiation, and the multiple regression equation using the day data and the like as explanatory variables. This has been done conventionally and has high accuracy. Since the power supply amount is calculated by subtracting the total in-house power generation amount predicted accurately from the predicted value of the power consumption amount calculated accurately, the predicted value of the calculated power supply amount is accurate. It can be said that. The power supply area is an area of a local unit such as the three Tokai prefectures (Aichi prefecture, Gifu prefecture, and Mie prefecture).

Further, the acquisition of information by the A route, which has been conventionally performed, is performed every 30 minutes as described above, but the communication between the smart meter and the communication terminal (for example, the digital grid controller (registered trademark)) (so-called B route). (Communication by) can be performed at a minimum interval of 1 second, so that the retailer can obtain an actually measured value of the amount of private power generation transmitted via the communication terminal in almost real time. Therefore, it is possible to calculate the predicted value of the required power supply amount in the power supply area in real time. When monitoring whether there is a divergence by comparing the planned power supply amount and the actual power supply amount as in the past, it takes as long as 30 minutes from the occurrence of the divergence to grasping the divergence as described above. However, according to the present invention, it is possible to monitor in real time whether or not there is a discrepancy by comparing the planned power supply amount with the predicted value of the power supply amount calculated accurately in real time. .. If it is possible to monitor in real time, it is possible to instantly grasp the occurrence of the divergence, and it is possible to shorten the time until the plan is revised.

Further, according to the electric power demand forecast system described in (1) and the electric power demand forecast program described in (4), the capital investment cost can be suppressed when introducing the electric power demand forecast system and the electric power demand forecast program. ..

It is also considered that the method of estimating the power generation output of photovoltaic power generation disclosed in Patent Document 1 and Patent Document 2 can improve the accuracy by increasing the number of measurement points of the solar radiation amount data. However, in order to increase the number of measurement points, there is a concern that the cost for installing the measurement equipment will increase.

By the way, a service (environmental value purchase service) in which the self-consumption of photovoltaic power generation is regarded as an environmental value and purchased from a consumer who is generating the self-power generation is being tested by a retailer or the like.
Customers who provide environmental value purchase services have smart meters that measure the amount of electricity sold and purchased, and smart meters that measure the amount of private power generated by solar power generation equipment. These smart meters are connected to a communication terminal (for example, a digital grid controller (registered trademark)) by route B, and the communication terminal obtains the data of the smart meter to sell, purchase, and generate electricity. The amount of self-consumption of electricity calculated based on this is traded on the cloud as an environmental value (Reference: "Recycled Energy CO2 Emission Reduction Value Creation Model Project Utilizing Blockchain Technology" Document 4-1 (http: /) /Www.env.go.jp/earth/blockchain.html)).

In other words, the consumer who is the provider of the environmental value purchase service already has a smart meter that measures the amount of private power generation by the solar power generation equipment, and communicates information about the amount of private power generation measured by the smart meter. Since it is transmitted to the cloud via a terminal, if the retailer obtains information on the amount of private power generation from the provider of the environmental value purchase service, the power demand forecasting system and the power demand forecasting program It is not necessary to newly install measuring equipment when introducing the above, and the capital investment cost can be suppressed.

According to the electric power demand forecasting system described in (2) and the electric power demand forecasting program described in (5), the average private power generation amount is calculated based on the private power generation amount which is the measured value, and is the measured value. By multiplying the average private power generation amount calculated based on the above by the actual number of multiple consumers who have solar power generation facilities, the total private power generation amount is calculated, so the prediction of the total private power generation amount is accurate. At the same time, it becomes possible to accurately predict the amount of power supply.

According to the power demand forecast system described in (3) and the power demand forecast program described in (6), it is possible to accurately predict the total amount of private power generation and accurately predict the amount of power supply. Become.

The amount of power generation is determined by the power generation output of the photovoltaic power generation facility, the amount of solar radiation, and the loss coefficient (power generation amount (kWh) = power generation output (kW) x solar radiation amount x loss coefficient). Among these, since the power generation output of the photovoltaic power generation equipment is determined by the installation area of the solar panel, it is a factor that varies widely among consumers (for example, in the case of photovoltaic power generation equipment for general households, 3). ~ 4kW, 10kW or more for commercial photovoltaic power generation equipment). Therefore, when calculating the total amount of private power generation, it is possible to predict the total amount of private power generation with higher accuracy by considering the power generation output with large variations, and by extension, it is possible to predict the amount of power supply with higher accuracy. It will be possible.

In addition, the power generation output of the entire solar power generation facility of a plurality of consumers who have the solar power generation facility can be obtained by the retailer concluding a power sale contract with the consumer, and the photovoltaic power generation can be obtained. The power output of a photovoltaic power generation facility in a group of consumers who have a smart meter that measures the amount of private power generated by the facility can be obtained from the above-mentioned provider of the environmental value purchase service. Therefore, it is not necessary to make a new capital investment to collect information on power generation output.

It is a block diagram which shows the structure of the electric power demand forecasting system. It is a figure which shows the group of the consumer included in the power supply area. It is a figure which shows the equipment which the second customer has. It is a graph which shows the relationship between the power supply amount and time. It is a graph which shows the relationship between the power supply amount and time in the prior art.

<First Embodiment>
The first embodiment of the electric power demand forecasting system and the electric power demand forecasting program of the present invention will be described in detail with reference to the drawings.

The electric power demand forecasting system 1 according to the present embodiment is, for example, a system owned by an electric power retailer, and is for predicting a required electric power supply amount in an electric power supply area 5 (see FIG. 2) including a plurality of consumers. It is a system.

The power supply area 5 assumes a local unit area such as the Tokai 3 prefectures (Aichi prefecture, Gifu prefecture, and Mie prefecture), and includes a plurality of consumers as shown in FIG. The power supply area 5 includes a group 6 composed of a plurality of consumers (first consumers 61A, 61B, 61C, second consumers 71A, 71B, 71C) having a photovoltaic power generation facility, and photovoltaic power generation. It is composed of a plurality of consumers (third consumers 51A, 51B, 51C) who do not have equipment.

Further, the group 6 is provided by a customer (second customers 71A, 71B, 71C) having a first smart meter 713 (see FIG. 3, the details will be described later) for measuring the amount of private power generation by the photovoltaic power generation facility. It contains the constituent group 7. The group 7 is a destination for retailers to provide environmental value purchase services. Details of the environmental value purchase service will be described later.

The rest of the group 6 excluding the group 7 have solar power generation facilities, but are not provided with the environmental value purchase service, and are consumers who do not have the first smart meter 713 (No. 1). It is a group of customers 61A, 61B, 61C).

In FIG. 2, the first consumer 61A, 61B, 61C, the second consumer 71A, 71B, 71C, and the third consumer 51A, 51B, 51C are displayed three by three. As described above, the power supply area 5 is assumed to be a local unit, so that the number is actually larger. Further, each of the first consumer 61A, 61B, 61C, the second consumer 71A, 71B, 71C, and the third consumer 51A, 51B, 51C is simply the first consumer in the following description. It is described as 61, the second customer 71, and the third customer 51.

FIG. 1 is a block diagram showing a configuration of the electric power demand forecasting system 1 according to the present embodiment. The electric power demand forecasting system 1 includes communication units 11 and 15, registration units 12 and 16, databases 13, 17 and 19, calculation units 14, and a display device 18.

The communication unit 11 is connected to the cloud 2 via a communication line 8 (an example of a network) such as the Internet, and relates to the amount of private power generated by the photovoltaic power generation equipment of each of the second consumers 71 from the cloud 2. Get information. Then, the registration unit 12 stores the information acquired by the communication unit 11 in the database 13.

Information on the amount of private power generation of each of the second consumer 71 is transmitted to the cloud 2 by the second consumer 71 via a 3G line or an LTE line. This will be described in detail with reference to FIG.

Each of the second consumers 71 includes a solar panel 711 and a power conditioner (PCS) 712, a first smart meter 713, a second smart meter 714, and a communication terminal 715 (for example,) constituting the photovoltaic power generation facility. It is equipped with a digital grid controller (registered trademark).

Each of the second consumers 71 generates their own power with the solar panel 711, and the generated power is converted from direct current to alternating current and output by the PCS 712 connected to the solar panel 711. The electric power converted into alternating current is supplied to a household load 716 (for example, home appliances such as refrigerators and air conditioners) and consumed. Further, the surplus power that is converted into alternating current by the PCS 712 and remains unconsumed by the household load 716 is sold through the power system 9.

A first smart meter 713 is arranged between the home load 716 and the power system 9 and the PCS 712, and the first smart meter 713 is output from the PCS 712 and is the power consumed by the home load 716. , The total of the electric power sold through the electric power system 9 (that is, the amount of private power generation by the photovoltaic power generation facility) is measured. The measurement interval is, for example, 1 second interval, and measurement is possible in almost real time. Further, a second smart meter 714 is arranged between the power system 9 and the first smart meter 713, and the second smart meter 714 sells the power output from the PCS 712 through the power system 9. We are measuring the amount of electricity sold.

In addition, the second consumer 71 operates the domestic load 716 by the electric power supplied from the retailer through the electric power system 9 during the time zone (nighttime, etc.) when the private power generation cannot be performed by the solar power generation equipment. .. The electric power supplied through the electric power system 9 (that is, the amount of electric power purchased) is measured by the second smart meter 714 in almost real time like the first smart meter 713.

The communication terminal 715 is connected to the first smart meter 713 and the second smart meter 714 (for example, a wireless connection according to the Wi-SUN standard for home use and a wired connection for business use, so-called B route). , The measured values of the first smart meter 713 and the second smart meter 714 are read in real time. Then, for example, the measured value read to the cloud 2 is transmitted in real time by a 3G line or an LTE line. As a result, the electric power demand forecasting system 1 can acquire information on the amount of private power generation of each of the second consumers 71 from the cloud 2 by the communication unit 11.

The communication terminal 715 transmits the measured values of the first smart meter 713 and the second smart meter 714 to the cloud 2. The second consumer 71 receives the environmental value purchase service provided by the retailer. This is because the so-called environmental value is traded on the cloud 2.

The environmental value purchase service is a service that considers the self-consumption of solar power generation as environmental value and purchases it.

Since the environmental value is calculated based on the amount of self-consumption of electricity calculated based on the amount of electricity sold, the amount of electricity purchased, and the amount of private power generation, the second consumer 71, who is the provider of the environmental value purchase service, is the amount of electricity sold. The second smart meter 714 for measuring the amount of electricity purchased and the first smart meter 713 for measuring the amount of private power generated by the photovoltaic power generation facility are indispensable. Then, for the transaction of environmental value, the information on the amount of private power generation measured by the first smart meter 713 and the second smart meter 714 is transmitted on the cloud 2 via the communication terminal 715. , Retailers can easily obtain information on the amount of private power generation from the provider of the environmental value purchase service, and when introducing the power demand forecast system 1, there is no need to newly install measuring equipment, and capital investment The cost can be suppressed.

The first customer 61A, 61B, 61C and the third customer 51A, 51B, 51C may also have the second smart meter 714, and the measured value is sent to the retailer every 30 minutes. It is transmitting (transmission by so-called A route). However, when the third consumers 51A, 51B, 51C who do not have the solar power generation facility have the second smart meter 714, the second smart meter 714 measures only the amount of electricity purchased and transmits it to the retailer. This has traditionally been done for automatic meter reading and power demand forecasting.

Returning to the explanation of FIG. 1, the communication unit 15 is connected to the weather information server 3 via a communication line 8 such as the Internet, and the weather information server 3 provides weather information such as temperature, humidity, discomfort index, and amount of solar radiation. To get. The weather information server 3 is located, for example, in a meteorological observatory or the like, and is located outside the retailer. Then, the registration unit 16 stores the information acquired by the communication unit 15 in the database 17.

The information registered in the databases 13 and 17 is appropriately read out by the calculation unit 14 and used for the prediction of the power supply amount performed by the calculation unit 14.

The calculation unit 14 stores the power consumption prediction program 141, the power demand prediction program 142, and the monitoring program 143.

The power consumption prediction program 141 is a program that predicts the power consumption in the power supply area 5, and is a multiple regression equation using weather information such as temperature, humidity, discomfort index, and solar radiation, and day data as explanatory variables. Based on this, the predicted value of the power consumption of the power supply area 5 is calculated (see Non-Patent Document 1). In this calculation, the weather information obtained from the weather information server 3 and stored in the database 17 is used. Then, the predicted value of the power consumption calculated by the power consumption prediction program 141 is used in the power demand prediction program 142 when the predicted value of the required power supply amount in the power supply area 5 is calculated.

The electric power demand forecast program 142 is a program that calculates a predicted value of the electric power supply amount required for the electric power supply area 5. It can be said that the power supply amount required for the power supply area 5 is a value obtained by subtracting the private power generation amount generated by the photovoltaic power generation facility by the group 6 from the power consumption amount in the power supply area 5. Therefore, the predicted value of the power supply amount is calculated as follows.

First, the average private power generation amount, which is the average value of the private power generation amount in the group 7, is calculated based on the private power generation amount of each of the second consumers 71 stored in the database 13. Specifically, it is calculated by summing up the amount of private power generation per unit time of each of the second consumers 71 and dividing by the number of the second consumers 71.

Next, based on the average private power generation amount, the total private power generation amount, which is the private power generation amount of the entire group 6 composed of the first consumer 61 and the second consumer 71, is calculated. Specifically, it is calculated by multiplying the average amount of private power generation by the total number of cases of the first customer 61 and the second customer 71.

Then, the predicted value of the power supply amount required for the power supply area 5 is calculated by subtracting the total private power generation amount from the predicted value of the power consumption amount in the power supply area 5 calculated by the power demand prediction program 142. To do.

The first smart meter 713 measures the amount of private power generation by the photovoltaic power generation facility in real time, and the communication terminal 715 transmits information on the amount of private power generation in real time to the cloud 2 via, for example, a 3G line or an LTE line. The electric power demand forecasting system 1 can acquire information on the amount of private power generation in real time. Therefore, the power demand forecast program 142 can calculate the predicted value of the power supply amount required for the power supply area 5 in real time.

The monitoring program 143 is a plan of the power supply amount of the power supply amount to the power supply area 5 of the retailer (planned power supply amount) and a predicted value of the power supply amount calculated in real time by the power demand forecast program 142. We constantly monitor whether there is a gap between them. The planned power supply amount is planned in advance, and the retailer divides the day into 30-minute units and plans the power supply amount every 30 minutes. The planned power supply amount can be planned with high accuracy by accumulating the calculation results of the power demand forecast program 142 and converting it into big data, and by using machine learning based on the big data.

In the past, it was monitored whether there was a divergence by comparing the planned power supply amount and the actual power supply amount (actual power supply amount), but after the divergence occurred, the retailer changed the divergence. It took as long as 30 minutes to grasp it. Then, it took time to revise the plan, and there was a penalty to pay for the discrepancy between the plan and the actual result that had occurred before the plan was revised.

For example, as shown in FIG. 5, the difference between the planned power supply amount ep21 and the actual power supply amount er21 begins, and the actual power supply amount er21 starts to fall below the planned power supply amount ep21 at the time point t1. Then, the retailer can grasp that this divergence has started at the time point t2, which is 30 minutes after the time point t1. The work for making a new plan starts from this time point t2, and the time point t4 two hours after the time point t1 can actually make a new plan. It can be seen that the planned power supply amount ep21 fluctuates in almost the same transition as the actual power supply amount er21 from the time point t4 due to the new plan being made. As described above, the plan is revised 2 hours after the start of the discrepancy between the plan and the actual result, and a penalty must be paid for the discrepancy between the plan and the actual result in the 2 hours. It was.

On the other hand, according to the power demand forecast system 1 according to the present embodiment, it is possible to monitor in real time whether or not there is a discrepancy by comparing the planned power supply amount with the predicted value of the power supply amount calculated in real time. It will be possible. If it is possible to monitor in real time, it is possible to instantly grasp the occurrence of the divergence, and it is possible to shorten the time until the plan is revised.

This will be described in detail with reference to FIG. In FIG. 4, the horizontal axis is time, and the scale is at intervals of 30 minutes. The vertical axis represents the power supply amount, and represents the fluctuation of the planned power supply amount ep11 and the predicted value er11 of the power supply amount with the passage of time.

It is time point t1 that the deviation between the planned power supply amount ep11 and the predicted value er11 starts, and the predicted value er11 starts to fall below the planned power supply amount ep11. As described above, since the monitoring program 143 monitors whether or not there is a divergence in real time, the retailer can grasp the divergence immediately after the divergence starts at the time point t1.

Conventionally, it took 30 minutes to grasp the divergence, but in the present embodiment, since the divergence can be grasped instantly, a new plan can be made from the time point t1 onward. At the time point t3 after one and a half hours, which is 30 minutes faster than that. This can be seen from the time point t3, that the planned power supply amount ep11 has been revised, and the fluctuation is almost the same as the predicted value er11. As described above, since the time until the plan is revised is shorter than before, the penalty to be paid due to the discrepancy between the plan and the actual result can be suppressed.

Returning to the description of FIG. 1, the power demand forecasting system 1 includes a display device 18, and the display device 18 displays the predicted values calculated by the power consumption forecasting program 141 and the power demand forecasting program 142. Can be done. This allows retailers to revise their plans.

Further, in the display device 18, the monitoring program 143 causes a discrepancy between the plan of the power supply amount of the power supply amount to the power supply area 5 and the actual power supply of the power supply amount to the power supply area 5. When it is detected, a warning can be displayed. In response to this warning display, the retailer can modify the planned power supply amount ep11 based on the calculation results of the power consumption prediction program 141 and the power demand prediction program 142.

Furthermore, the electric power demand forecasting system 1 includes a database 19, and can store the forecasted values calculated by the calculation unit 14. This makes it possible to use the predicted value calculated by the calculation unit 14 as big data.

In the present embodiment, the power demand forecasting system 1 includes two communication units 11 and 15, but one communication unit is provided, and the communication unit communicates with the cloud 2 and the weather information server 3. May be. Further, although three databases 13, 17 and 19 are provided, the number does not have to be three, and one database may store information acquired from the cloud 2 or the weather information server 3. The number of registration units 12 and 16 does not have to be two, and may be adjusted to match the number of databases.

As described above, according to the power demand forecasting system 1 and the power demand forecasting program 142 of the first embodiment,
(1) Predicted value of the required power supply amount in the power supply area 5 including a plurality of consumers having solar power generation facilities (group 6 composed of the first customer 61 and the second customer 71). In the power demand prediction system 1 calculated based on the predicted value of the power consumption in the power supply area 5 calculated by at least the weather information in the power supply area 5, a plurality of consumers (group 6) generate solar power. The communication terminal 715 includes a group 7 of a second consumer 71 having a first smart meter 713 for measuring the amount of private power generation by the equipment and a communication terminal 715 capable of communicating with the first smart meter 713. In the group 7, based on the communication unit 11 that acquires the information of the private power generation amount measured by the first smart meter 713 transmitted on the network via the network and the private power generation amount acquired by the communication unit 11. Calculate the average private power generation amount, which is the average value of the private power generation amount, and calculate the total private power generation amount, which is the total private power generation amount of multiple consumers (group 6), based on the average private power generation amount, and calculate the total private power generation amount. It is characterized by having a calculation unit 14 for calculating the predicted value of the power supply amount by subtracting the total amount of private power generation from the predicted value of (4) and (4) a plurality of demands having a solar power generation facility. The predicted value of the required power supply amount in the power supply area 5 including the house (group 6 composed of the first customer 61 and the second customer 71) is calculated from at least the weather information in the power supply area 5. In the power demand prediction program 142, which is calculated based on the predicted value of the power consumption in the power supply area 5, a plurality of consumers (group 6) measure the amount of private power generation by the solar power generation facility. The first smart meter transmitted on the network via the communication terminal 715, including the group 7 of the second consumer 71 having the 713 and the communication terminal 715 capable of communicating with the first smart meter 713. Information on the amount of private power generation measured by 713 is acquired from the network, and based on the acquired private power generation amount, the average private power generation amount, which is the average value of the private power generation amount in Group 7, is calculated, and the average private power generation amount is calculated. Based on the above, the total amount of private power generation, which is the total amount of private power generation of multiple consumers (group 6), is calculated, and the predicted value of power supply is calculated by subtracting the total amount of private power generation from the predicted value of power consumption. Because it is characterized by calculating, the total amount of private power generation is accurately predicted, and the amount of power supply is accurately predicted. This makes it possible to reduce the penalty for general power transmission and distribution business operators.

The communication unit 11 can obtain an actually measured value of the amount of private power generation from a group of consumers having a first smart meter 713 that measures the amount of private power generation by the photovoltaic power generation facility. Then, the calculation unit 14 calculates the average private power generation amount based on the measured private power generation amount, and calculates the total private power generation amount. Since the total amount of private power generation is calculated based on the measured value, it reflects the degree of deterioration of the photovoltaic power generation equipment and the direction in which the solar panel 711 is installed, and considers only the solar radiation amount data as in the past. Prediction accuracy is improved compared to predicting the total amount of private power generation.

Further, the predicted value of the required power supply amount in the power supply area 5 is at least the predicted value of the power consumption amount in the power supply area 5 predicted by the weather information in the power supply area 5, and the total private power generation amount is subtracted from the predicted value. It is calculated by.
As described above, the predicted value of the power consumption is calculated based on the weather information such as temperature, humidity, discomfort index, and amount of solar radiation, and the multiple regression equation using the day data and the like as explanatory variables. This has been done conventionally and has high accuracy. Since the power supply amount is calculated by subtracting the total in-house power generation amount predicted accurately from the predicted value of the power consumption amount calculated accurately, the predicted value of the calculated power supply amount is accurate. It can be said that. The power supply area 5 is a local unit area such as the three Tokai prefectures (Aichi prefecture, Gifu prefecture, and Mie prefecture).

Further, although the information acquisition by the A route, which has been conventionally performed, is performed every 30 minutes as described above, the communication between the first smart meter 713 and the communication terminal 715 (communication by the so-called B route) is the shortest. Since it can be performed at 1-second intervals, the retailer can obtain an actually measured value of the amount of private power generation transmitted via the communication terminal in almost real time. Therefore, it is possible to calculate the predicted value of the required power supply amount in the power supply area 5 in real time. When monitoring whether there is a divergence by comparing the planned power supply amount and the actual power supply amount as in the past, it takes as long as 30 minutes from the occurrence of the divergence to grasping the divergence as described above. However, according to the present invention, it is possible to monitor in real time whether or not there is a discrepancy by comparing the planned power supply amount with the predicted value of the power supply amount calculated accurately in real time. .. If it is possible to monitor in real time, it is possible to instantly grasp the occurrence of the divergence, and it is possible to shorten the time until the plan is revised.

Further, according to the electric power demand forecast system 1 described in (1) and the electric power demand forecast program 142 described in (4), the capital investment cost is reduced when the electric power demand forecast system 1 and the electric power demand forecast program 142 are introduced. It can be suppressed.

It is also considered that the method of estimating the power generation output of photovoltaic power generation disclosed in Patent Document 1 and Patent Document 2 can improve the accuracy by increasing the number of measurement points of the solar radiation amount data. However, in order to increase the number of measurement points, there is a concern that the cost for installing the measurement equipment will increase.

By the way, a service (environmental value purchase service) in which the self-consumption of photovoltaic power generation is regarded as an environmental value and purchased from a consumer is being tested by a retailer or the like.
The second consumer 71, who is the provider of the environmental value purchase service, has a second smart meter 714 that measures the amount of power sold and purchased, and a first smart meter 713 that measures the amount of private power generated by the solar power generation equipment. Have. These smart meters are connected to the communication terminal 715, and the communication terminal 715 acquires the data of the first smart meter 713 and the second smart meter 714, and based on the amount of power sold, the amount of power purchased, and the amount of private power generation. The calculated self-consumption of electricity is used as an environmental value for trading on Cloud 2.

That is, the second consumer 71, which is the provider of the environmental value purchase service, already has the first smart meter 713 that measures the amount of private power generation by the solar power generation facility, and is measured by the first smart meter 713. Since the information on the amount of private power generation is transmitted to the cloud 2 via the communication terminal 715, the retailer should obtain the information on the amount of private power generation from the provider of the environmental value purchase service. For example, when introducing the power demand prediction system 1 and the power demand prediction program 142, it is not necessary to newly install measuring equipment, and the capital investment cost can be suppressed.

(2) In the electric power demand forecasting system 1 described in (1), the total amount of private power generation is calculated by multiplying the average amount of private power generation by the number of cases of a plurality of consumers (group 6). In addition, in the power demand forecasting program 142 described in (5) and (4), the total amount of private power generation is calculated by multiplying the average amount of private power generation by the number of cases of a plurality of consumers (group 6). The average private power generation amount is calculated based on the measured private power generation amount, and the average private power generation amount calculated based on the actual measurement value includes a plurality of solar power generation facilities. Since the total amount of private power generation is calculated by multiplying the actual number of consumers (group 6), it is possible to accurately predict the total amount of private power generation and the amount of power supply. It becomes.

<Second embodiment>
Next, a second embodiment of the electric power demand forecasting system and the electric power demand forecasting program of the present invention will be described.

In the power demand prediction program 142 in the power demand prediction system 1 according to the first embodiment, the total private power generation amount is set to the average private power generation amount which is the average value of the private power generation amount in the group 7, and the first consumer 61 is set. It was calculated by multiplying the total number of cases of the second consumer 71, but in the power demand prediction program 142 in the power demand prediction system 1 according to the second embodiment, the total amount of private power generation is calculated by multiplying the total number of private power generation. It is calculated by multiplying the total power generation output of the photovoltaic power generation facility by the conversion efficiency of the photovoltaic power generation facility. Here, the conversion efficiency is a value obtained by dividing the average amount of private power generation by the average value of the power generation output of the photovoltaic power generation equipment in the group 7.

The power demand forecast program 142 according to the second embodiment calculates the predicted value of the power supply amount required for the power supply area 5 as follows.
First, the average private power generation amount, which is the average value of the private power generation amount in the group 7, is calculated based on the private power generation amount of each of the second consumers 71 stored in the database 13. Specifically, it is calculated by summing up the amount of private power generation per unit time of each of the second consumers 71 and dividing by the number of the second consumers 71.

Next, based on the average private power generation amount, the total private power generation amount, which is the total private power generation amount of the group 6 composed of the first consumer 61 and the second consumer 71, is calculated. Specifically, it is calculated by multiplying the total power generation output of the entire photovoltaic power generation facility of the group 6 by the above conversion efficiency.

Then, the predicted value of the power supply amount required for the power supply area 5 is calculated by subtracting the total private power generation amount from the predicted value of the power consumption amount in the power supply area 5 calculated by the power demand prediction program 142. To do.

The amount of power generation is determined by the power generation output of the photovoltaic power generation facility, the amount of solar radiation, and the loss coefficient (power generation amount (kWh) = power generation output (kW) x solar radiation amount x loss coefficient). Of these, the power generation output of the photovoltaic power generation equipment is determined by the installation area of the solar panel 711, which is a factor that varies widely among consumers (for example, in the case of photovoltaic power generation equipment for general households). 3-4 kW, 10 kW or more for commercial photovoltaic power generation equipment). Therefore, when calculating the total amount of private power generation, it is possible to predict the total amount of private power generation with higher accuracy by considering the power generation output with large variations, and by extension, it is possible to predict the amount of power supply with higher accuracy. It will be possible.

It should be noted that the power generation output of the entire photovoltaic power generation facility of the group 6 and the power generation output of the photovoltaic power generation facility in the group 7 are known information. This is because the power generation output of the entire photovoltaic power generation facility of the group 6 can be obtained by the retailer concluding a power sales contract with each customer constituting the group 6. Further, since the second consumer constituting the group 7 receives the above-mentioned environmental value purchase service, the power generation output of the solar power generation facility in the group 7 can be obtained at the time of contracting the service. Therefore, it is not necessary to make a new capital investment to acquire the information.

Other configurations of the power demand forecasting system according to the second embodiment are the same as those of the power demand forecasting system 1 according to the first embodiment.

As described above, according to the power demand forecasting system 1 and the power demand forecasting program 142 of the second embodiment,
(3) In the power demand prediction system 1 described in (1), the total private power generation amount is the average private power generation amount added to the total power generation output of the total solar power generation facilities of a plurality of consumers (group 6). It is characterized in that it is calculated by multiplying the conversion efficiency, which is a value divided by the average value of the power generation output of the solar power generation facility in the group 7, and the power demand forecasting program 142 according to (6) and (4). In, the total private power generation amount is the total value of the power generation output of the total solar power generation equipment of a plurality of consumers (group 6), and the average private power generation amount is the average value of the power generation output of the solar power generation equipment in the group 7. Since it is calculated by multiplying the conversion efficiency, which is the divided value, it is possible to accurately predict the total amount of private power generation and the amount of power supply.

The amount of power generation is determined by the power generation output of the photovoltaic power generation facility, the amount of solar radiation, and the loss coefficient (power generation amount (kWh) = power generation output (kW) x solar radiation amount x loss coefficient). Of these, the power generation output of the photovoltaic power generation equipment is determined by the installation area of the solar panel 711, which is a factor that varies widely among consumers (for example, in the case of photovoltaic power generation equipment for general households). 3-4 kW, 10 kW or more for commercial photovoltaic power generation equipment). Therefore, when calculating the total amount of private power generation, it is possible to predict the total amount of private power generation with higher accuracy by considering the power generation output with large variations, and by extension, it is possible to predict the amount of power supply with higher accuracy. It will be possible.

The power generation output of the entire photovoltaic power generation facility of a plurality of consumers (group 6) having a photovoltaic power generation facility can be obtained by the retailer concluding a power sales contract with the consumer. , The power generation output of the photovoltaic power generation facility in the group 7 of the second consumer 71 having the first smart meter 713 that measures the amount of private power generation by the photovoltaic power generation facility can be obtained from the above-mentioned provider of the environmental value purchase service. Is. Therefore, it is not necessary to make a new capital investment to collect information on power generation output.

It should be noted that the present embodiment is merely an example and does not limit the present invention in any way. Therefore, as a matter of course, the present invention can be improved and modified in various ways without departing from the gist thereof.

1 Power demand forecasting system 5 Power supply area 6 Group (an example of multiple consumers with solar power generation facilities)
7 group 8 communication line (example of network)
14 Calculation unit 61 First consumer 71 Second consumer 713 First smart meter 715 Communication terminal

Claims (6)

The predicted value of the required power supply amount in the power supply area including a plurality of consumers having a solar power generation facility, at least the predicted value of the power consumption amount in the power supply area calculated from the weather information in the power supply area. In the power demand forecasting system calculated based on
The plurality of consumers include a group of consumers having a smart meter for measuring the amount of private power generation by the photovoltaic power generation facility and a communication terminal capable of communicating with the smart meter.
A communication unit that acquires information on the amount of private power generation measured by the smart meter transmitted on the network via the communication terminal from the network.
Based on the private power generation amount acquired by the communication unit, the average private power generation amount, which is the average value of the private power generation amount in the group, is calculated, and based on the average private power generation amount, the entire private power generation of the plurality of consumers is calculated. A calculation unit that calculates the total private power generation amount, which is the amount of power generation, and calculates the predicted value of the power supply amount by subtracting the total private power generation amount from the predicted value of the power consumption amount.
To prepare
A power demand forecasting system featuring. In the power demand forecasting system according to claim 1,
The total amount of private power generation is calculated by multiplying the average amount of private power generation by the number of the plurality of consumers.
A power demand forecasting system featuring. In the power demand forecasting system according to claim 1,
The total private power generation amount is the total value of the power generation output of the solar power generation equipment of the plurality of consumers, and the average private power generation amount is divided by the average value of the power generation output of the solar power generation equipment in the group. It is calculated by multiplying the conversion efficiency, which is the value obtained.
A power demand forecasting system featuring. The predicted value of the required power supply amount in the power supply area including a plurality of consumers having a solar power generation facility, at least the predicted value of the power consumption amount in the power supply area calculated from the weather information in the power supply area. In the power demand forecasting program calculated based on
The plurality of consumers include a group of consumers having a smart meter for measuring the amount of private power generation by the photovoltaic power generation facility and a communication terminal capable of communicating with the smart meter.
Information on the amount of private power generation measured by the smart meter transmitted on the network via the communication terminal is acquired from the network.
Based on the acquired private power generation amount, the average private power generation amount, which is the average value of the private power generation amount in the group, is calculated.
Based on the average private power generation amount, the total private power generation amount, which is the total private power generation amount of the plurality of consumers, is calculated.
To calculate the predicted value of the power supply amount by subtracting the total private power generation amount from the predicted value of the power consumption amount.
A power demand forecasting program featuring. In the power demand forecasting program according to claim 4,
The total amount of private power generation is calculated by multiplying the average amount of private power generation by the number of the plurality of consumers.
A power demand forecasting program featuring. In the power demand forecasting program according to claim 4,
The total private power generation amount is the total value of the power generation output of the solar power generation equipment of the plurality of consumers, and the average private power generation amount is divided by the average value of the power generation output of the solar power generation equipment in the group. It is calculated by multiplying the conversion efficiency, which is the value obtained.
A power demand forecasting program featuring.

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