JP5835675B2 - Collective trading support system for small power and aggregate trading support method for small power - Google Patents

Description

  The present invention relates to an aggregate trading support system for small power and an aggregate trading support method for small power, and more specifically, based on the estimation accuracy of surplus power in general households subject to aggregation and transactions, The present invention relates to a technology capable of suppressing the balance cost and supporting the maximization of profits from power trading.

  Due to the recent reform of the power system, so-called full-scale liberalization of power retailing is scheduled, and various forms of operation and management techniques for power trading systems are being proposed accordingly. Therefore, the following techniques have been proposed as a management method for such power trading. In other words, taking into account differences in the customer's load profile depending on the month, day, and day of the week, the use of power by each consumer that is the target of power supply in order to achieve an appropriate revenue evaluation when trading market products A system (see Patent Document 1) that calculates how many types of patterns exist within a calculation period and evaluates the profit within the calculation period from the profits of each day and the number of days of each type has been proposed.

JP 2006-285351 A

  However, out of the amount of power generated by a very small power generation unit using renewable energy, such as solar panels installed in ordinary homes, surplus power obtained by subtracting the amount of power consumed in the home with the power generation unit between homes No technology has yet been proposed for aggregating and handling this as power for sale in the electricity market.

  On the other hand, as is generally known, the amount of power generated by solar panels, wind power generators, and the like continues to fluctuate due to natural conditions that change from moment to moment, such as solar radiation and wind speed. In addition, the power consumption in each household tends to fluctuate due to temperature, humidity, and entry / exit of householders, and there are many situations in which real-time power consumption cannot be measured without a smart meter installed.

  Therefore, the above-described surplus power itself that is subject to aggregation is likely to fluctuate due to a plurality of factors, and there may be a situation in which the amount of power after aggregation is less than the initial assumption. When such surplus electricity is purchased from each household, aggregated, presented as a bid object in the electricity market, and bids are received, sometimes the power supply / demand balance regulation of “30 minutes at the same amount” cannot be achieved, resulting in a large imbalance. There are cases where costs are required.

  Accordingly, an object of the present invention is to provide a technology that can suppress imbalance costs in the electric power market and support the maximization of electric power trading profits while taking into account the estimation accuracy of surplus electric power in general households subject to aggregation and transactions. It is to provide.

Further, the collective buying and selling support system for small power according to the present invention includes the actual power consumption for each predetermined period in each general household in a predetermined area, the power generation capacity of the power generation unit by the renewable energy provided in each general household, and every predetermined period. A storage device that stores information on the actual power generation amount and the weather forecast from the present time to the future ahead of a predetermined period, and a predetermined algorithm that estimates the power generation amount in the power generation unit according to the power generation capacity and weather conditions Applying each information of the power generation capacity in the power generation unit of the general weather forecast and the general household, and a power generation amount estimation process for estimating the predicted power generation amount in the general household until the future ahead of the predetermined period; from the expected amount of power generation of the households, by subtracting the electric power consumption record of predetermined period in the relevant households, the calculated expected excess power amount of each private households, each such general world Predict the sum of the excess power amount, distributed to each unit period forming a predetermined period until the future, the excess power expected process of storing information expected excess power amount for each said unit period in a storage device, a storage device Is calculated as a prediction error between the actual surplus power amount based on the predetermined past power generation result and the actual power consumption stored in the predetermined past expected surplus power amount, and the amount of power corresponding to the prediction error is calculated. Transaction target power amount calculation process for subtracting from the expected surplus power amount for each unit period, calculating the transaction target power amount in the power market for each unit period, and outputting information on the transaction target power amount to an output device And an arithmetic unit that executes the above.

In addition, the method for collecting and selling small power consumption according to the present invention includes the actual amount of power used for each predetermined period in each general household in a predetermined area, the power generation capacity of the power generation unit using the renewable energy provided in each general household, and every predetermined period. The information processing device equipped with a storage device that stores each information of the actual power generation amount and the weather forecast from the present time to the future ahead of a predetermined period of time is the power generation amount in the power generation unit according to the power generation capacity and weather conditions Applying the weather forecast and the power generation capability information of the power generation unit of each household to a predetermined algorithm for estimating the power generation amount estimation for estimating the predicted power generation of each household until the future ahead of the predetermined period Calculate the expected surplus power of each general household by subtracting the actual amount of power used for the specified period from the processing and the predicted power generation of each general household , Surplus power expected to store the the sum of the expected excess power amount of each households, allocated to each unit period forming a predetermined period until the future, the information of the estimated surplus power amount per the unit time period in the storage device Calculating a difference between the actual surplus power amount based on the process and the predetermined past power generation amount and actual power consumption stored in the storage device and the predetermined past past surplus power amount as a prediction error, and the prediction error A transaction for subtracting the amount of energy for the minute from the expected surplus power amount for each unit period, calculating the transaction target power amount in the power market for each unit period, and outputting information on the transaction target power amount to the output device And a target electric energy calculation process.

  ADVANTAGE OF THE INVENTION According to this invention, the imbalance cost in an electric power market can be suppressed and the maximization of an electric power trading profit can be supported, based on the estimation precision of the surplus electric power in the general household used as an object of aggregation and transaction.

It is a network block diagram including the collective trading support system of small power of this embodiment. It is a figure which shows the hardware structural example of the collective trading support system of the small electric power of this embodiment. It is a figure which shows the data structural example of the use performance database in this embodiment. It is a figure which shows the data structural example of the power generation capability database in this embodiment. It is a figure which shows the data structural example of the electric power generation performance database in this embodiment. It is a figure which shows the example of a data structure of the weather database in this embodiment. It is a figure which shows the data structural example of the price information database in this embodiment. It is a flowchart which shows the process sequence example of the collective buying and selling support method of small electric power in this embodiment.

--- System configuration ---
Embodiments of the present invention will be described below in detail with reference to the drawings. FIG. 1 is a diagram illustrating an example of a network configuration including a small-capacity aggregate trading support system 100 according to the present embodiment. The aggregate power trading support system 100 (hereinafter referred to as the system 100) shown in FIG. 1 suppresses imbalance costs in the power market while taking into account the estimation accuracy of surplus power in general households that are subject to aggregation and transactions. And a computer system for enabling the maximization of power trading profits.

  As the small power in this embodiment, surplus power that is not consumed in the corresponding household among the power generated by the solar power generation unit installed in the general household (general household) is assumed as an example. Such small-scale electric power of each general household is purchased by a predetermined operator, aggregated, that is, aggregated, and provided as a bidding target in the electric power transaction market (electric power market). Therefore, the system 100 assumes a server device operated by this business operator (hereinafter, aggregator) as an example.

  An example of a network configuration between devices corresponding to the relationship between the general household, the aggregator, and the electric power market is as shown in FIG. The house 10 of each general household in this case is fed by the distribution board 11 from the two systems of the photovoltaic power generation unit 1 installed on the rooftop and the like and the system power supply 2 provided by the electric power company, and this distribution board 11 The power receiving / distributing configuration is such that the electrical equipment 15 at each location is operated with power distributed from the power source (including at least one of power derived from renewable energy and power received from the system power source).

  The amount of power actually consumed by the electrical equipment 15 in the house 10, that is, the amount of power used, is measured by a watt hour meter 12 provided in the distribution board 11. The indicated value of the watt-hour meter 12 is read by a meter reader dispatched by a power company at a predetermined pace, for example, once a month, and the read value is read from the terminal owned by the meter meter or the system 100 or the power business. Transferred to the person's computer. Alternatively, the distribution board 11 described above has a communication function and is connected to the system 100 via the network 50 so that the data on the power consumption measured by the watt hour meter 12 can be obtained every predetermined time. 100 may be transmitted.

  Moreover, when the above-mentioned distribution board 11 can cover the power consumption of the electric equipment 15 only with the electric power received from the solar power generation unit 1, the surplus electric power at that time (the amount of power generated by the solar power generation unit 1−the electric equipment) 15) is supplied to, for example, the system power supply 2 described above. Between the above-mentioned aggregator and the electric power company that manages the system power supply 2, an arrangement has been made in advance for the transmission processing of surplus power, and surplus power generated from a general household 10 located in a certain area Is received by the system power supply 2, and power is supplied to the facility 20 of the successful bidder of the corresponding power according to the bid result in the power market.

  The system 100 according to the present embodiment is connected via the network 50 so as to be able to communicate with at least the transaction server 200 in the power market, in addition to the distribution board 11 described above. The transaction server 200 receives the bid information regarding the surplus power aggregated by the system 100 via the network 50 and distributes it to the bidder terminal 300 provided by other companies, new power, etc. It is an information processing apparatus that performs each process of bidding, bids and bids. Regarding the configuration and function of the transaction server 200, an existing technology that performs a series of auction transactions from bidding to successful bids may be employed.

  In addition, the system 100 of this embodiment may include the distribution board 11 and the transaction server 200 described above.

  The hardware configuration of the above-described aggregate power support system 100 for power consumption in the present embodiment is as follows. FIG. 2 is a diagram illustrating a hardware configuration example of the aggregate power support system 100 for small power according to the present embodiment. The system 100 reads out a storage device 101 composed of an appropriate non-volatile storage device such as a hard disk drive, a memory 103 composed of a volatile storage device such as a RAM, and a program 102 held in the storage device 101 to the memory 103. And a control device 104 for performing overall control of the device itself and performing various determinations, calculations and control processing, an input device 105 for receiving key input and voice input from a user, and an output device 106 such as a display for displaying processing data. And a communication device 107 connected to the network 50 and responsible for communication processing with other devices. When data is exchanged only with the other devices described above, the system 100 may not include the input device 105 and the output device 106.

  Then, the function with which the aggregate sales support system 100 of the small electric power of this embodiment is provided is demonstrated. As described above, it can be said that the functions described below are implemented by executing the program 102 included in the system 100, for example. Note that the system 100 includes a usage record database 125 that stores information on the amount of power used for each predetermined period in the homes 10 of the general households in the predetermined area in the storage device 101, and the photovoltaic power generation provided in the homes 10 of the general households. A power generation capacity database 126 that stores information on the power generation capacity of the unit 1, a power generation result database 127 that stores information on the amount of power generation for each predetermined period of the solar power generation unit 1 provided in the house 10 of each general household, It is assumed that a weather database 128 storing weather forecast information for the future ahead of a predetermined period is stored.

  The system 100 of the present embodiment uses a power generation prediction algorithm 110 (FIG. 2) that estimates the amount of power generated by the solar power generation unit 1 according to the power generation capacity and weather conditions, and the weather prediction obtained from the above-described weather database 128. Applying the information and the information on the power generation capacity in the solar power generation unit 1 of each general household obtained from the above-described power generation capacity database 126, for example, has a function of estimating the predicted power generation amount in each general household up to one month ahead ing.

  In addition, the system 100 subtracts, for example, the actual amount of power used for the last one month in the corresponding general household obtained from the above-described usage record database 125 from the predicted power generation amount of each general household up to the above-mentioned one month ahead, Calculate the expected surplus power amount of each general household, and distribute the total value of the expected surplus power amount evenly for each unit period such as 30 minutes that constitute the period up to the above-mentioned one month ahead, and the expected surplus for each unit period A function of storing information on the amount of power in the storage device 101 is provided.

  In addition, the system 100 has a predetermined past power generation record such as the most recent year stored in the above-described power generation record database 127 and a predetermined past use power record such as the most recent one year stored in the above-described use record database 125. The difference between the actual surplus power based on and the predicted surplus power obtained for the same most recent year is calculated as a forecast error, and the power for the forecast error is calculated this time, that is, one month from now Subtracted from the expected surplus power amount for each unit period until the transaction target power amount in the power market for each unit period is calculated, and information on the transaction target power amount is output to the output device 106 or the communication device 107 Via the transaction server 200 described above.

  Note that the weather forecast information in the above-mentioned weather database 128 includes a long-term weather forecast 128A for a certain period of time, such as half a year or one year, and a short-term weather forecast for the future closer to the target time of the long-term weather forecast 128A, for example, the next day. It is preferable to store 128B information.

  In this case, in the above-described power generation amount estimation process, the system 100 causes the power generation prediction algorithm 110 to include the information on the long-term weather prediction 128A described above and the power generation in the solar power generation unit 1 of each general household obtained from the power generation capability database 126. The above-mentioned short-term weather related to a predetermined time point in the future such as the next day every time a predetermined time period such as 30 minutes elapses after the estimated power generation amount in each general household is estimated up to the future one month ahead, for example. Whether or not there is a difference between the prediction 128B and the long-term weather prediction 128A described above is determined, and if there is a difference, the information of the short-term weather prediction 128B is applied to the power generation prediction algorithm 110 as weather prediction information, The function of estimating the expected power generation amount is further provided.

  At this time, the system 100 uses the estimated power generation amount estimated in the above-described manner every time a predetermined time such as 30 minutes elapses in the above-described surplus power prediction process. Calculate the expected surplus power amount of each general household by subtracting the actual results, and distribute the total value of the expected surplus power amount evenly for each unit period such as 30 minutes in one month from the present to one month ahead The storage device 101 further includes a function of storing information on the expected surplus power amount for each unit period.

  At this time, the system 100 subtracts the power amount corresponding to the prediction error from the expected surplus power amount for each unit period every time a predetermined time such as 30 minutes elapses in the calculation process of the power amount for transaction described above. A function for calculating the amount of power to be traded in the power market for each unit period and outputting information on the amount of power to be traded to the output device 106 or to the transaction server 200 described above via the communication device 107. I have.

  It is preferable that the storage device 101 of the system 100 further stores price information 129 including a power purchase unit price 129A from a general household and a power sale unit price 129B in the power market. In this case, the system 100 calculates the power purchase amount by multiplying the expected surplus power amount for each unit period described above by the power purchase unit price 129A read from the storage device 101, and obtains the amount of power to be traded for each unit period described above. A function of calculating a power sale amount by multiplying the power sale unit price 129B read from the storage device 101, subtracting the power purchase amount from the power sale amount, calculating a profit amount, and outputting the profit amount to the output device 106. In addition.

  In addition, it is preferable that the storage device 101 of the system 100 further stores information on a subsidized unit price 129C from a predetermined organization for a unit power generation amount by sunlight (renewable energy). In this case, in the profit calculation process described above, the system 100 calculates the subsidy amount by multiplying the expected surplus power amount for each unit period by the subsidy unit price 129C read from the storage device 101, and uses the subsidy amount as the power sale amount. A function of calculating a profit amount by subtracting the power purchase amount from the added value and outputting the profit amount to the output device 106 is further provided.

  Note that the system 100 receives the above-mentioned information on the actual power consumption, the actual power generation, and the weather forecast via a predetermined interface such as the input device 105 or the communication device 107, and receives the information. It is preferable that each information is stored in the corresponding database of the storage device 101.

--- Data structure example ---
Next, an example of a data structure in a database used by the collective trading support system 100 for small power according to this embodiment will be described. FIG. 3 is a diagram showing a data configuration example of the usage record database 125 in the present embodiment. The usage record database 125 is a database that stores information on the amount of power used for each predetermined period in the house 10 of each general household in a predetermined region. Specifically, the household ID that uniquely identifies a general household is used as a key. , A data collection period, and a set of records associated with values such as the amount of power used in the corresponding period. The power consumption value stored in the usage record database 125 is acquired by the system 100 from the information distribution server of the power company in which the reading value of the watt hour meter 12 by the meter reader of the power company is stored, or the house 10 is a value acquired by the system 100 via the network 50 from the smart meter 10. The system 100 receives the data on the amount of power used from the information distribution server and smart meter described above at regular intervals and stores the data in the usage record database 125.

  FIG. 4 is a diagram showing a data configuration example of the power generation capacity database 126 in the present embodiment. The power generation capacity database 126 is a database that stores information on the power generation capacity of the solar power generation unit 1 provided in the house 10 of each general household. Specifically, the power generation capacity value is associated with the above-described household ID as a key. It is a collection of recorded records.

  FIG. 5 is a diagram illustrating a data configuration example of the power generation result database 127 in the present embodiment. The power generation result database 127 is a database that stores information on the amount of power generation for each predetermined period of the solar power generation unit 1 provided in the house 10 of each general household. Specifically, the data is recorded using the above-mentioned household ID as a key. It is a collection of records in which values such as the collection period and the actual power generation amount in the corresponding period are associated.

  The value of the power generation result stored in the power generation result database 127 is acquired by the system 100 from the smart meter provided in the house 10 via the network 50, or the power generation meter of the solar power generation unit 1 by a resident of the house 10 or the like. This is a value acquired by the system 100 from the user terminal to which the read value is input. The system 100 receives data transmission of the power generation results from the smart meter and the user terminal at regular intervals and stores them in the power generation results database 127.

  FIG. 6 is a diagram showing a data configuration example of the weather database 128 in the present embodiment. The weather database 128 is a database that stores weather forecast information from the present time to the future ahead of a predetermined period. Specifically, the weather database 128 predicts the weather forecast for a forecast period such as one month or one year from the present time, that is, a certain period. This is a set of records in which values such as the long-term weather forecast 128A described above and the future closer to the target time of the long-term weather forecast 128A, for example, the short-term weather forecast 128B until the next day, are associated.

  FIG. 7 is a diagram showing a data configuration example of the price information database 129 in the present embodiment. The price information database 129 stores information on the unit price of electricity purchased from a general household 129A, the unit price of electricity sold in the electricity market 129B, and the subsidized unit price 129C from a predetermined institution for unit power generation by sunlight (renewable energy). Database.

--- Processing procedure example ---
Hereinafter, an actual procedure of the aggregate power support method for the small power according to this embodiment will be described with reference to the drawings. FIG. 8 is a flowchart showing an example of a processing procedure of the aggregate power support method for small power according to this embodiment. Here, first, the collective buying and selling support system 100 for the small-lot electric power is the weather such as the amount of solar radiation that directly affects the amount of power generated by the photovoltaic power generation unit 1 and the temperature, humidity, and precipitation that affects the power consumption in the house 10 of a general household. Necessary number of data (for example, latest observation) from a predetermined device (for example, an information providing server of a weather observation organization or a weather observation device operated by an aggregator itself) via a predetermined interface such as the input device 105 or the communication device 107 The number of data traced back to the past for a certain period of time) is applied and applied to a predetermined weather prediction algorithm 111 (see FIG. 2; an existing weather prediction program may be adopted), for example, one day from the present time, one week, etc. Make forecasts of weather forecasts by forecasting the amount of solar radiation, temperature, humidity, and precipitation for a short period of time and for a long period of time, such as one month. Get the distribution (i.e., short-term weather forecast 128B and long term weather forecast 128A), and stores it in the weather database 128 of the storage device 101 (s100).

  The meteorological data given to the above-mentioned weather forecasting algorithm 111 includes observation values for the most recent one week, statistical values related to observation values for the same month in the past one year and ten years, and the like. It is assumed that the prediction algorithm 111 is given.

  In addition, regarding the weather prediction information obtained by the weather prediction algorithm 111, the system 100 can detect actual weather data (meteorological observation devices and weathers) after a certain period of time has elapsed since the corresponding weather prediction processing was performed by the weather prediction algorithm 111. The prediction error is calculated as compared with the information obtained from the information providing server of the observation institution, and the weather error is finely corrected daily by using, for example, a Bayesian statistical method (s101). Note that uncertainty such as forecast errors in weather forecasts may be evaluated using Monte Carlo simulation.

  Further, the weather forecast information obtained in step s100 described above is not only obtained by applying weather data to the weather forecast algorithm 111, but also information previously announced by the weather forecasting organization is obtained from the server device of the relevant organization. It may be acquired.

  Subsequently, the system 100 adds the information of the short-term weather prediction 128B and the long-term weather prediction 128A read from the weather database 128 to the above-described power generation prediction algorithm 110 and the solar power generation unit 1 of each general household obtained from the power generation capacity database 126. For example, the predicted power generation amount in each general household up to the future one month ahead is estimated (s102).

  Further, every time a predetermined time such as 30 minutes (time corresponding to the update interval of the short-term weather prediction 128B) elapses, the system 100 performs the above-described short-term weather prediction 128B related to a predetermined future time point such as the next day and the above-described long-term weather prediction 128A. If there is a difference, the information of the short-term weather forecast 128B is applied as the weather forecast information to the power generation prediction algorithm 110 to estimate the predicted power generation amount from the present time to one month ahead (s103). .

  Subsequently, the system 100 obtains the power consumption record for the most recent month obtained from the use record database 125 from the predicted power generation amount of each general household up to one month ahead obtained in step s103. By subtracting, the expected surplus power amount of each general household is calculated (s104). In addition, the system 100 sums up the calculated expected surplus electric energy of each household and distributes the total value obtained in this way evenly for each unit period such as 30 minutes, which is the period up to the above one month ahead. Information on the expected surplus power amount for each period is stored in the storage device 101 (s105). A series of processes such as the calculation of the predicted power generation amount and the equal distribution for each unit period is performed in the above-described predicted power generation amount (estimated in step s103) that can be updated every 30 minutes (predetermined time) that matches the unit period. ), It may be repeatedly executed.

  The background to performing such an equal distribution process is the situation where smart meters are not yet widely used in general households. In such a case, actual data on the amount of power used every short time (eg, in units of 30 minutes) is stored in the system 100. Can not grasp immediately. Therefore, the system 100 predicts the surplus power amount one month ahead in a month, and distributes it to each 30 minutes (16 frames) in a time zone from 8 o'clock to 16 o'clock where solar power generation is performed, for example, It is regarded as a resource for the amount of electricity sold to be presented to the electricity market.

  In the present embodiment, an example is shown in which the expected surplus electric energy is calculated through each of the above-described steps s102 to s104. However, the weather forecast to the future ahead of a predetermined period such as the above-mentioned one month (irradiation amount) , Temperature, humidity, discomfort index, etc.) and the power generation capacity of the solar power generation unit 1 as parameters, the expected surplus power to the future in each household where surplus power is generated by the power generation by the solar power generation unit 1 The system 100 is provided with an algorithm for estimating the estimated surplus electric energy by this algorithm. In this case, the above-described steps s102 to s104 are not necessary, and the expected surplus power amount is directly calculated by the corresponding algorithm in step s105. As such an algorithm, a linear regression model, a multivariate autoregressive model, a multiple regression model, or the like using the past actual power value or the above-mentioned weather information as input values may be employed.

  Next, the system 100 generates a predetermined past power generation record such as the most recent year stored in the above-described power generation record database 127 and a predetermined past power consumption stored in the above-described use record database 125 such as the last one year. A difference between the actual surplus power amount based on the actual result and the expected surplus power amount obtained for the same most recent year is calculated as a prediction error (s106).

  In this case, the amount of power corresponding to the prediction error is subtracted from the expected surplus power amount for each unit period from this time, that is, from the present time to one month ahead (obtained in step s105), and the power market for each unit period The amount of power to be traded in is calculated (s107). In this transaction target power amount calculation process, the system 100 subtracts the power amount corresponding to the prediction error from the expected surplus power amount that can be updated each time a predetermined time such as 30 minutes elapses, thereby generating a power market for each unit period. It is preferable to calculate the amount of power to be traded at.

  As already mentioned, when a bid is received in the power market using the total amount of surplus power as the supply amount, if a surplus power amount fluctuates more than a certain amount depending on the weather conditions, etc., a successful bid is made in the market. A difference, that is, an imbalance is generated between the amount of electric power at the time and the amount of electric power that can be actually supplied, and an imbalance cost is generated based on the difference. Therefore, by subtracting the power amount corresponding to the prediction error from the surplus power amount in advance and determining the transaction target power amount, it is possible to allow a certain amount of fluctuation of the surplus power amount and suppress the above-mentioned imbalance. It is.

  Next, the system 100 multiplies the expected surplus power amount for each unit period obtained in step s105 by the power purchase unit price 129A read from the price information database 129 of the storage device 101 to calculate the power purchase amount (s108). . Similarly, the system 100 multiplies the transaction target power obtained in step s107 by the unit price 129B read from the price information database 129 of the storage device 101 to calculate the amount of power sold (s109). ). Further, the system 100 calculates the subsidy amount by multiplying the expected surplus power amount for each unit period obtained in step s105 by the subsidy unit price 129C read from the price information database 129 of the storage device 101 (s110).

  In this way, the system 100 that has calculated the amount of power sold, the amount of power purchased, and the amount of subsidy calculates the amount of power by subtracting the amount of power purchased from the value obtained by adding the calculated amount of subsidy to the amount of power sold, and outputs the amount of profit The data is output to the device 106 (s111). The user of the system 100, that is, the aggregator, can suppress the imbalance cost in the electric power market and maximize the electric power trading profit while taking into account the estimation accuracy of surplus electric power in general households that are subject to aggregation and transaction.

  Although the best mode for carrying out the present invention has been specifically described above, the present invention is not limited to this, and various modifications can be made without departing from the scope of the invention.

  According to the present embodiment, an operator (aggregator) that consolidates and sells small-scale electric power while suppressing imbalance costs in the electric power market while taking into account the estimation accuracy of surplus electric power in general households subject to aggregation and transactions. Can help maximize profits from power trading.

  At least the following will be clarified by the description of the present specification. That is, the storage device of the aggregate power support system for small power in the present embodiment uses the long-term weather forecast for a predetermined period or more and the short-term weather to the future closer to the target time of the long-term weather forecast as the weather forecast information. The calculation device applies the information on the long-term weather prediction and the information on the power generation capacity of the power generation unit of each general household to the predetermined algorithm in the power generation amount estimation process. Then, after estimating the predicted power generation amount in each general household to the future ahead of the predetermined period, every time a predetermined time elapses, whether or not there is a difference between the short-term weather prediction and the long-term weather prediction for a predetermined future time point If there is a difference, short-term weather forecast information is applied to the predetermined algorithm as weather forecast information, the expected power generation amount is estimated, and the surplus In the power forecasting process, every time the predetermined time elapses, the expected surplus power amount of each general household is calculated by subtracting the actual power consumption amount of the general household from the estimated predicted power generation amount for a predetermined period. And allocating the total value of the predicted surplus power amount for each unit period forming the predetermined period until the future, storing information on the expected surplus power amount for each unit period in a storage device, and the transaction target power amount In the calculation process, every time the predetermined time elapses, the power amount corresponding to the prediction error is subtracted from the expected surplus power amount for each unit period to calculate the transaction target power amount in the power market for each unit period. And it is good also as what outputs the information of the said transaction object electric energy to an output device.

  According to this, with reference to long-term weather forecasts, for example, the power generation amount prediction from the present time to one month ahead is performed, and the expected surplus power amount and the target power amount based on this are obtained in advance and presented to the power market. On the other hand, on the previous day when the bid for the electricity market was actually awaited the next day, etc., the above-mentioned estimation of the predicted power generation amount was re-executed based on the weather forecast for the very near future, and a highly accurate predicted surplus power amount. It is possible to calculate and output the target electric energy. Therefore, the difference between the transaction target power amount presented to the power market and the actual surplus power amount becomes smaller, and further suppression of imbalance costs and maximization of power trading profit can be supported.

  Further, the storage device of the aggregate power support system for small power in this embodiment further stores the unit price of power purchase from a general household and the unit price of power sold in the power market, and the arithmetic unit is configured as described above. Calculate the power purchase amount by multiplying the expected surplus power amount per unit period by the power purchase unit price, multiply the transaction target power amount per unit period by the power sale unit price, and calculate the power sale amount. It is also possible to further execute profit calculation processing for calculating the profit amount by subtracting the power purchase amount from the amount and outputting the profit amount to the output device.

  According to this, for the users of this system (businesses that collect and sell small-lot electricity such as general households), the amount of profits obtained by purchasing power from general households and selling power in the power market is This is clearly indicated before the transaction target power amount is presented, and the user can recognize the profit amount in advance.

  In addition, the storage device of the small-capacity collective buying and selling support system in the present embodiment further stores information on the subsidized unit price from a predetermined organization for the unit power generation amount by renewable energy, In the profit calculation process, the subsidy amount is calculated by multiplying the expected surplus power amount for each unit period by the subsidy unit price, and the power purchase amount is subtracted from the value obtained by adding the subsidy amount to the power sale amount. The amount may be calculated and the profit amount may be output to the output device.

  According to this, it is possible to accurately calculate the amount of profit by including subsidies from public institutions, etc., that may greatly affect the amount of profit.

  In addition, the computing device of the small-capacity aggregate trading support system in the present embodiment stores each information of the actual power consumption record, the actual power generation record, and the weather forecast via a predetermined interface or communication device for a certain period. The information may be received every time and the received information may be stored in a storage device.

  According to this, for example, a terminal provided in a meter reader for checking the power consumption of a general household, or a smart meter installed in a general household (measures the power consumption and power generation, and the measured values are , Etc.) to regularly acquire the latest information on the amount of power used and the amount of power generated by each general household, and periodically update the latest information on weather forecasts from the server of the weather forecasting organization. It is possible to calculate the expected surplus power amount and the transaction target power amount with high accuracy based on these information.

DESCRIPTION OF SYMBOLS 1 Photovoltaic power generation unit 2 System power supply 10 House 11 Distribution board 12 Electricity meter 15 Electric equipment 50 Network 100 Small power collective buying and selling support system 101 Storage device 102 Program 103 Memory 104 Arithmetic device 105 Input device 106 Output device 107 Communication device 110 Power Generation Prediction Algorithm 111 Weather Prediction Algorithm 125 Usage Result Database 126 Power Generation Capacity Database 127 Power Generation Result Database 128 Weather Database 129 Price Information Database 200 Electricity Market Transaction Server 300 Bidder Terminal

Claims (6)

From the current time to the future ahead of the specified period, the actual power consumption for each specified period in each general household in the specified area, the power generation capacity of the power generation unit by the renewable energy provided in each general household and the actual generated power amount for each specified period A storage device for storing each information of
Apply each information of the weather forecast and the power generation capacity in the power generation unit of each general household to a predetermined algorithm for estimating the power generation amount in the power generation unit according to the power generation capacity and weather conditions, and until the future ahead of the predetermined period A power generation amount estimation process for estimating an expected power generation amount in each of the general households,
By subtracting the actual amount of electric power used for a predetermined period from the expected power generation amount of each general household, the expected surplus power amount of each general household is calculated, and the expected surplus power amount of each general household is calculated. A surplus power prediction process for allocating a total value for each unit period forming a predetermined period until the future, and storing information on an expected surplus power amount for each unit period in a storage device;
The difference between the actual surplus power amount based on the past actual power generation amount and the actual power consumption stored in the storage device and the predetermined past expected surplus power amount is calculated as a prediction error, and the power corresponding to the prediction error Subtracting the amount from the expected surplus power amount for each unit period, calculating the transaction target power amount in the power market for each unit period, and outputting the information on the transaction target power amount to the output device An arithmetic unit that executes the calculation process;
A collective buying and selling support system for small-scale electric power, comprising: The storage device
As the weather forecast information, long-term weather forecast for a predetermined period or more ahead and short-term weather forecast information to the future closer to the target period of the long-term weather forecast,
The arithmetic unit is:
In the power generation amount estimation process, the information on the long-term weather forecast and the information on the power generation capacity of the power generation unit of each general household are applied to the predetermined algorithm, and the prediction of each general household up to the future ahead of the predetermined period After estimating the power generation amount, every time a predetermined time elapses, it is determined whether or not there is a difference between the short-term weather forecast and the long-term weather forecast for a predetermined future time point. Is applied to the predetermined algorithm as the information of the
In the surplus power prediction process, every time the predetermined time elapses, the expected power generation amount of each general household is subtracted from the estimated predicted power generation amount by subtracting the actual power consumption amount for a predetermined period in the corresponding general household. And the total value of the expected surplus power amount of each general household is allocated to each unit period forming the predetermined period until the future, and information on the expected surplus power amount for each unit period is stored in the storage device. ,
In the transaction target power amount calculation process, every time the predetermined time elapses, the power amount for the prediction error is subtracted from the expected surplus power amount for each unit period, and the transaction in the power market for each unit period is performed. The target power amount is calculated, and the information on the transaction target power amount is output to the output device.
The collective buying and selling support system for small power according to claim 1 . The storage device
It also stores the unit price of electricity purchased from general households and the unit price of electricity sold in the electricity market.
The arithmetic unit is:
The amount of power purchase is calculated by multiplying the expected surplus power amount for each unit period by the unit price of power purchase, the amount of power to be traded for each unit period is multiplied by the unit price of power sale, and the amount of power sold is calculated. Subtracting the amount of electricity purchased from the amount of electricity to calculate the amount of profit, and further executing a profit calculation process for outputting the amount of profit to the output device,
The collective buying and selling support system for small power according to claim 1 or 2 . The storage device
It further stores information on the subsidy unit price from the specified organization for the unit power generation amount by renewable energy,
The arithmetic unit is:
In the profit calculation process, a subsidy amount is calculated by multiplying the expected surplus power amount for each unit period by the subsidy unit price, and the power purchase amount is subtracted from a value obtained by adding the subsidy amount to the power sale amount. The amount of profit is calculated and the amount of profit is output to the output device.
The collective buying and selling support system for small power according to claim 3 . The arithmetic unit is:
Each information of the actual power consumption record, the actual power generation record, and the weather forecast is received every predetermined period via a predetermined interface or communication device, and each received information is stored in a storage device. is there,
The collective buying and selling support system for small power according to any one of claims 1 to 4 . From the current time to the future ahead of the specified period, the actual power consumption for each specified period in each general household in the specified area, the power generation capacity of the power generation unit by the renewable energy provided in each general household and the actual generated power amount for each specified period An information processing apparatus equipped with a storage device for storing each information of the weather forecast of
Apply each information of the weather forecast and the power generation capacity in the power generation unit of each general household to a predetermined algorithm for estimating the power generation amount in the power generation unit according to the power generation capacity and weather conditions, and until the future ahead of the predetermined period A power generation amount estimation process for estimating an expected power generation amount in each of the general households,
By subtracting the actual amount of electric power used for a predetermined period from the expected power generation amount of each general household, the expected surplus power amount of each general household is calculated, and the expected surplus power amount of each general household is calculated. A surplus power prediction process for allocating a total value for each unit period forming a predetermined period until the future, and storing information on an expected surplus power amount for each unit period in a storage device;
The difference between the actual surplus power amount based on the past actual power generation amount and the actual power consumption stored in the storage device and the predetermined past expected surplus power amount is calculated as a prediction error, and the power corresponding to the prediction error Subtracting the amount from the expected surplus power amount for each unit period, calculating the transaction target power amount in the power market for each unit period, and outputting the information on the transaction target power amount to the output device Calculation process,
A method for supporting the collective buying and selling of small power, characterized in that

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