Power trading system and program

Abstract

To provide a power transaction system and a program capable of appropriately trading power.SOLUTION: A power transaction system includes: a matching related data acquisition unit 100 for acquiring prioritized demand bid information and supplied bid information; an expression rate prediction unit 200 for obtaining a predicted expression rate of the demand bid information and the supplied bid information; an agreement rate prediction unit 300 for obtaining a predicted agreement rate of the demand bid information and the supplied bid information; and a matching unit 400 for matching the demand bid information and the supplied bid information while switching a priority on the basis of the predicted expression rate and the predicted agreement rate.SELECTED DRAWING: Figure 3

Description

Technical Field

[0001] The present invention relates to a power trading system and a program.

Background Art

[0002] Not only conventional centralized power sources such as thermal power generation but also distributed power sources are becoming widespread. Distributed power sources include various types such as power generation type solar power generation and cogeneration systems, and storage type batteries and heat pumps. On the other hand, on the demand side of electricity, there are movements such as the RE100 declaration that all consumed electricity should be generated from renewable energy. Since the amount of renewable energy is not yet sufficient, RE50, which sets 50% of the consumed electricity as the amount generated from renewable energy, is also considered. The ratio of the amount of consumed electricity that is generated from renewable energy is called the RE ratio. It is considered that the RE ratio required by the demand side is not uniform and varies depending on the needs of the demand side.

[0003] The supply side such as power generation and storage and the demand side trade electricity through a power trading system. There are existing power trading systems such as JEPX (Japan Election Power eXchange), but in Europe, power trading systems that trade electricity within a region have also emerged. Therefore, it is necessary to consider not only existing power trading systems but also new forms of power trading systems. Existing power trading systems trade renewable energy power and non-renewable energy power without distinction as types of electricity. And the trading of the power supply capacity from batteries and the like is not fully considered. The trading unit is also often determined mainly in units of 30 minutes. Such a power trading system trades electricity in a standardized form as one type, so the trading itself can be carried out efficiently, but there is a problem that the needs of the demand side and supply side of electricity cannot all be reflected.

[0004] Let's consider the original power needs of both the supply side and the demand side. In the case where the power generation equipment on the supply side is a cogeneration system, it is most efficient when operating at rated capacity. Therefore, it is better to sell in blocks composed of a certain period of time and quantity. Or, if it is decided to self-consume a certain portion within the block, it is better to sell blocks in an uneven shape. In the case of renewable energy, even with predictions, the actual output may differ from the predicted value. Therefore, it is difficult to stably supply power to the demand side of electricity. On the other hand, the demand side has a need for stable renewable energy, but there is also a need for supply that is clean, inexpensive, and has a high output uncertainty, such as producing hydrogen with surplus power from renewable energy. To meet such diverse needs, it is desirable to be able to conduct transactions under various matching conditions. The diverse needs of the supply side and the demand side are manifested in various conditions in the transaction. Here, the various matching conditions indicated by supply and demand refer to the type of electricity and the desired transaction conditions. As a trading form, an auction method is assumed.

[0005] Patent Document 1 shows a power trading device that aims to provide a power trading device capable of giving trading opportunities to a large number of users, and is equipped with an agreement rate determination means for determining the agreement rate, which is the ratio of the agreement on the selling side or the buying side. However, Patent Document 1 does not describe transactions that can reflect the diverse needs of the demand side and the supply side. If there are always sufficient bids that meet the matching conditions of the demand side and the supply side on the trading system, then matching can be implemented using the bid price and the bid quantity as the main parameters of the trading system. However, when the matching conditions diversify, bids may not be sufficient, and it can be assumed that there will not always be corresponding bids. Also, when there are few participants on the demand side or the supply side in the trading system, the same situation will occur.

[0006] Therefore, an object of the present invention is to provide a power trading system capable of appropriately trading electricity.

Prior Art Documents

Patent Documents

[0007]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0008] Patent Document 1 shows a power trading device provided for the purpose of providing a power trading device or the like that can give trading opportunities to a large number of users, and includes a contract rate determination means for determining a contract rate that is the ratio of the contract on the selling power side or the buying power side. However, there is no description regarding trading that can reflect various needs on the demand side and the supply side. When there are always sufficient bids that meet the matching conditions between the demand side and the supply side on the trading system, the matching can be carried out using the bid price and the bid quantity as the main parameters of the trading system. However, when the matching conditions diversify, the bids may not be sufficient, and it can be assumed that there may not always be a corresponding bid. Also, the same situation occurs when the number of participants on the demand side or the supply side in the trading system is small.

[0009] Therefore, an object of the present invention is to provide a power trading system capable of appropriately trading power.

Means for Solving the Problems

[0010] To solve the above problems, one aspect of the present invention includes a matching-related data acquisition unit that acquires prioritized demand bid information and With priority supply bid information, an appearance rate prediction unit that obtains the predicted appearance rate of the demand bid information Predicted occurrence rate and the supply bid information, a contract rate prediction unit that obtains the predicted contract rate of the demand bid information Predicted agreement rate and the supply bid information, and a matching unit that matches the demand bid information and the supply bid information while switching the priority, and is characterized by this. While switching the priority of the demand bidding information based on the product of the predicted occurrence rate and the predicted agreement rate of the demand bidding information, and based on the product of the predicted occurrence rate and the predicted agreement rate of the supply bidding information, the

Effects of the Invention

Effects of the Invention

[0011] According to the present invention, a power trading system capable of appropriately trading power can be provided. Problems, configurations, and effects other than those described above will be clarified by the following description of embodiments.

Brief Description of the Drawings

[0012]

Figure 1

Figure 2

Figure 3

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Figure 5

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Figure 7

Figure 8

Figure 9

Figure 10

Figure 11

Modes for Carrying Out the Invention

[0013] Hereinafter, a plurality of examples of embodiments of the present invention will be described.

Examples

[0014] FIG. 1 is a configuration diagram of a system related to the power trading system according to Embodiment 1. The power trading system 10 here includes a demand-side system 1 which is the demand side of power, and a demand facility 11 which is its facility. Further, it includes a supply-side system 2 which is the supply side of power, and a supply facility 21 which is its facility. Each demand facility 11 and each supply facility 21 are connected by a power supply line 3. The demand-side system 1 and the supply-side system 2 are connected to the power trading system 10 via a communication network 4. The demand-side system 1 and the supply-side system 2 are respectively connected to the demand facility 11 and the supply facility 21 via the communication network 4. The power trading system 10 may also be connected to the demand facility 11 or the supply facility 21 via the communication network 4. The demand-side system 1 acquires demand information such as power consumption from the demand facility 11 and creates demand bidding information for trading power in the power trading system 10. The supply-side system 2 acquires supply information such as power generation amount from the supply facility 21 and creates supply bidding information for trading power in the power trading system 10. The power trading system 10 is a system that acquires demand bidding information and supply bidding information and matches demand and supply.

[0015] FIG. 2 is a hardware configuration diagram of the power trading system 10. The functions of the power trading system 10 are realized by an electronic computer (and its peripheral devices) such as a general-purpose computer or a server. As shown in FIG. 2, the power trading system 10 includes, as its hardware configuration, a CPU 811 (Central Processing Unit), a memory 812, a storage 813, an input device 814, a communication interface 815, and a display device 816. The CPU 811 executes predetermined arithmetic processing based on programs stored in the memory 812 and the storage 813. The memory 812 includes a RAM (Random Access Memory) for temporarily storing data. As the storage 813, for example, an HDD (Hard Disk Drive) or an SSD (Solid State Drive) is used.

[0016] A program 817 is set up in the storage 813, and based on this program 817, the power trading system 10 executes various processes described below. The input device 814 is for inputting data by a user's operation. As such an input device 814, in addition to a keyboard and a mouse, a touch panel or the like is used. Note that, as the input device 814, a keyboard and a mouse of an administrative personal computer may be used. The communication interface 815 performs data conversion based on a predetermined protocol when data exchange is performed between the power trading system 10 and the demand-side system 1, the supply-side system 2, the demand facility 11, and the supply facility 21 via the communication network 4.

[0017] The display device 816 is, for example, a liquid crystal display, and displays the calculation result of the CPU 811 and the like. Note that, as the display device 816, a display of an administrative personal computer may be used. The power trading system 10 may be configured by one device (such as a server), or may be configured such that a plurality of devices (not shown) are connected in a predetermined manner via a communication line or a network.

[0018] FIG. 3 is a functional block diagram of the power trading system 10. The power trading system 10 has functions of a matching-related data acquisition unit 100, an appearance rate prediction unit 200, a conclusion rate prediction unit 300, a matching unit 400, and a transaction management unit 500. The matching-related data acquisition unit 100 acquires matching-related data, the appearance rate prediction unit 200 and the conclusion rate prediction unit 300 predict the appearance rate and the conclusion rate, and based on this, the matching unit 400 matches the bids of demand and supply. The matching result of the matching unit 400 is managed by the transaction management unit 500.

[0019] <Matching-related data acquisition unit> The matching-related data acquisition unit 100 acquires data including demand bid information, supply bid information, weather forecast, and past matching history. The demand bid information and the supply bid information may be collectively referred to as bid information.

[0020] The bid information is information including the matching conditions on the demand side of electric power, and includes information such as a demand bid ID, a demand bid individual ID, the desired purchase power date and time, the desired purchase power type, the desired purchase power (kW), the desired purchase power quantity (kWh), the desired purchase price, the block bid desire, the desired purchase power location, and the priority. FIG. 4 is an example of the demand bid information. The demand bid ID is an identification label of the demand bid information and is automatically assigned by the power trading system 10.

[0021] The demand bid individual ID is an identification label respectively assigned to a plurality of matching conditions for the same demand bid ID. Among the plurality of demand bid individual IDs within one demand bid ID, each one demand bid individual ID is matched. The desired purchase power date and time is information regarding when to use the purchased power. The desired purchase power type is in a form of selecting a power type defined by the power trading system 10 in categories such as renewable energy (renewable energy) and non-renewable energy (non-renewable energy). Here, the renewable energy is the power generated from renewable energy. The non-renewable energy is power generated using fossil fuels or the like rather than renewable energy. Although it is expressed as renewable energy as an example here, it may be detailed such as solar power generation and wind power generation.

[0022] The desired purchase power is the power desired to be purchased, and the desired purchase power quantity is the quantity of power desired to be purchased. The desired purchase power quantity is combined with the quantity obtained by time-integrating the desired purchase power and the desired purchase power date and time. The desired purchase price is the price for the desired purchase power and the desired purchase power quantity. The block bid desire is information regarding whether to match in a form of dividing the demand bid individual ID.

[0023] Figure 5 graphs the demand bidding information. The vertical axis represents the power (kW) of the desired purchase power quantity (kWh), and the horizontal axis represents time. On the demand side of the power, for the demand bidding ID (indicating D100), it is also possible to bid in a form divided into individual demand bidding IDs like the block of D101. If the block bidding desire in the above demand bidding information is "×", no split bidding is done. If the block bidding desire is "〇", it is split and matched. This split follows the splitting method predetermined in the power trading system 10. For example, normalize the vertical and horizontal lengths of D101 in Figure 5 to the values determined by the power trading system 10.

[0024] The desired purchase power location is information regarding where the generated power is to be purchased. It becomes the name of the location or the location ID determined by the power trading system 10. If the desired purchase power location is not relevant anywhere, it becomes a name like the whole country or any. The priority becomes the priority of each individual demand bidding ID within the same demand bidding ID. The method of assigning priorities just needs to follow the rules for assigning priorities determined by the power trading system 10. For example, it is conceivable to set 1 as the highest priority, and then decrease the priorities in the order of 2, 3, 4, etc.

[0025] The supply bidding information (Figure 6) is basically similar to the demand bidding information. The supply bidding information is information including the matching conditions on the supply side of the power, and includes supply bidding ID, individual supply bidding ID, desired selling power date and time, desired selling power type, desired selling power (kW), desired selling power quantity (kWh), desired selling price, block bidding desire, supply power location, and priority information. Figure 6 is an example of supply bidding information. The supply bidding ID is the identification label of the supply bidding information and is automatically assigned by the power trading system 10.

[0026] The individual supply bidding ID is an identification label assigned to each of the multiple matching conditions within the same supply bidding ID. Among the multiple individual supply bidding IDs within the supply bidding ID, each one individual supply bidding ID is matched. The desired selling power date and time is information regarding when the sold power is to be used. The types of electricity for sale are classified into renewable energy, non-renewable energy, etc., and are selected from the types of electricity defined in the power trading system 10. Here, renewable energy is electricity generated from renewable energy. Non-renewable energy is electricity generated using fossil fuels or the like, rather than renewable energy. Although renewable energy is expressed as an example here, it may be specified in detail such as solar power generation and wind power generation.

[0027] The electricity for sale is the electricity that the purchaser wishes to buy, and the quantity of electricity for sale is the quantity of electricity that the seller wishes to sell. The quantity of electricity for sale and the electricity for sale are combined with the quantity obtained by time-integrating them described at the date and time of the electricity for sale. The price for sale is the price for the electricity for sale and the quantity of electricity for sale.

[0028] The hope for block bidding is information regarding whether to match in a form divided into individual sales bid IDs. Fig. 7 graphically shows the supply bid information. The vertical axis represents the power (kW) of the quantity of electricity for sale (kWh), and the horizontal axis represents time. On the demand side of the power, it is also possible to bid in a form divided into individual supply bid IDs like the block of D201 with respect to the supply bid ID (indicating D200). If the hope for block bidding is "×" in the above supply bid information, no divided bidding is done. If the hope for block bidding is "〇", it is divided and matched. This division follows the method of division determined in advance by the power trading system 10. For example, the vertical and horizontal lengths of D201 in Fig. 5 are normalized to the values determined by the power trading system 10.

[0029] The power supply location is information regarding where the electricity was generated. It becomes the name of the location or the ID of the location determined by the power trading system 10. The priority is the priority of each individual supply bid ID with the same supply bid ID. Just follow the rule for determining the priority set by the power trading system 10. For example, it is conceivable to set 1 as the highest priority, and then decrease the priority in the order of 2, 3, 4, etc. The weather forecast is information including historical data of past weather forecasts and future weather forecasts, and is information for each location.

[0030] The past matching history is information including the demand bid information, supply bid information, and matching history information of the past trading system. <Expression rate prediction unit> The expression rate prediction unit 200 obtains the predicted expression rates of each demand bid information and supply bid information. The expression rate for demand bid information is the probability that the supply bid information corresponding to the demand bid information appears at each time. The predicted expression rate for supply bid information is the probability that the demand bid information corresponding to the supply bid information appears at each time. For example, the probability that the supply bid information matching the demand bid information appears is calculated.

[0031] As a prediction method, prediction is made using the past matching history. For example, the past supply bid information corresponding to the demand bid information to be predicted is searched. FIG. 8 shows the search results on the time axis. Suppose that supply bid information A (S10) and supply bid information B (S20) are searched as the supply bid information corresponding to the demand bid information. Suppose that the supply bid information A appears on the trading system at time t1, and the supply bid information B appears on the trading system at time t10. For the total number of days Ttotal of the past matching history, it means that the supply bid information appears at t1 and t10. The calculation formula for the predicted expression rate can be calculated as follows, for example.

[0032] "The predicted expression rate Zt at each time = Tu / Ttotal" Here, Tu is the total number of days when the supply bid information corresponding to the demand bid information to be predicted appears at the target time. When the supply bid information appears only at time t1 in the total number of days, the predicted occurrence rate at time t1 is 1 / Ttotal. From time t2 to time t9, if there are remaining bids without the supply bid information being matched, the predicted occurrence rate takes the same value as the predicted occurrence rate at time t1. If the supply bid information A is matched at time t2, the predicted occurrence rate from time t3 to time t9 is 0. At time t10, if there are remaining bids without the supply bid information being matched, the predicted occurrence rate is 2 / Ttotal. If the supply bid information A is matched at time t2, it is 1 / Ttotal.

[0033] Although Ttotal was explained by taking the total number of days on the trading system as an example, since the predicted occurrence of the demand bid information and the supply bid information also has seasonal factors, it is conceivable to set a seasonal interval, allocate the seasonal interval based on the desired power date and time of the demand bid information, and use the past demand bid information and supply bid information within that interval. For example, it is divided into spring, summer, autumn, and winter as seasons. The way of division can be that spring is from March to May, summer is from June to August, autumn is from September to November, and winter is from December to February. Divide the demand bid information and the supply bid information in such a division. Predict the predicted occurrence rate using the information divided in this way. Furthermore, since it can be assumed that the form of demand is different between weekdays and weekends, it is also conceivable to divide the demand bid information and the supply bid information according to the division of weekdays and weekends for each season. And it is also conceivable to divide the demand bid information and the supply bid information according to the weather.

[0034] Here, the prediction by statistical processing has been explained, but it is not limited to this method only. A method of predicting using a neural network is also conceivable. For example, calculate the past occurrence rate using the demand bid information and the supply bid information. It is possible to predict using a neural network as supervised learning using this data. Furthermore, it is considered that the prediction accuracy can be further improved by using the seasons, weekends / weekdays, and weather explained above as explanatory variables. Also, in addition to the past matching history, it is also conceivable to obtain the occurrence rate in the same way as above from the demand bid information and the supply bid information existing in the trading system at the current time, and use that value as an explanatory variable.

[0035] <Agreement Rate Prediction Unit> The agreement rate prediction unit 300 obtains the predicted agreement rates of each demand bid information and supply bid information. The predicted occurrence rate is an indicator of whether there is a matchable demand bid or supply bid at a certain time, while the predicted agreement rate is an indicator of the amount of power demand or supply. The calculation formula for the predicted agreement rate is, for example, as follows. "The predicted agreement rate Ct at each time = Ni / Nj" Here, Nj is the total of the past demand bid information of the prediction target, and Ni is the total of the past supply bid information of the prediction target. This is the case when the prediction target is the demand for electricity, and in the case of supply, it is the reciprocal of this.

[0036] In the prediction of the predicted agreement rate, similar to the prediction of the predicted occurrence rate, it is also conceivable to assume seasonal factors and classify the demand bid information and supply bid information used for agreement rate prediction by season. Furthermore, it is also conceivable to classify by weekend and weekday. And it is also conceivable to separate the demand bid information and supply bid information by weather. Here, the prediction by statistical processing has been described, but it is not limited to this method only. A method of predicting using a neural network is also conceivable. For example, calculate the past predicted agreement rates using demand bid information and supply bid information. It is possible to use this data to predict using a neural network as supervised learning. Furthermore, it is considered that the prediction accuracy will be further improved if the seasons, weekends / weekdays, and weather described above are used as explanatory variables. Also, in addition to the past matching history, it is also conceivable to obtain the agreement rate in the same manner as above from the demand bid information and supply bid information existing in the trading system at the current time and use that value as an explanatory variable.

[0037] <Matching Unit> The matching unit 400 performs matching between each demand bid information and each supply bid information. FIG. 9 is a flowchart showing the processing of the matching unit. In process S401, as the start of matching, a corresponding bid is submitted on the power trading system 10. First, matching is attempted with demand bid information having a high priority. In S402, it is determined whether the bid for which matching has been attempted has been successfully matched. In S403, based on the predicted occurrence rate and the predicted conclusion rate calculated by the occurrence rate prediction unit 200 and the conclusion rate prediction unit 300, it is determined whether to switch the matching priority. As a criterion for switching, for bids of each priority, the product of the occurrence rate and the conclusion rate is calculated. If the state where matching cannot be achieved continues and the product of the occurrence rate and the conclusion rate becomes lower than that of the bids of the next lower priority, it is considered to switch to the bids of the next lower priority. It is also conceivable to set a fixed period for the state where matching cannot be achieved to continue, and during this period, maintain the bids of the corresponding priority.

[0038] In S404, the demand bid information and the supply bid information are matched. The demand bid information and the supply bid information of the same content are matched with each other. When there are multiple pieces of demand bid information or multiple pieces of supply bid information with the same content, as a matching rule, basically, they are matched in the order of arrival.

[0039] <Transaction Management Department> The transaction management unit 500 acquires the result of the matching from the matching unit 400 and updates the demand bid information and the supply bid information to be matched by the matching unit 400. For those that have been successfully matched according to the matching result, a matched flag is attached and they are removed from the demand bid information and the supply bid information to be matched by the matching unit 400. According to the power trading system 10 described above, by presenting multiple matching conditions in one bid for power demand or supply, the demand bid information and the supply bid information within the power trading system 10 can be increased, making it easier to perform matching.

[0040] Also, according to the power trading system 10, for bids with multiple priorities, the predicted occurrence rate and the predicted matching rate are predicted, and based on those values, to switch the priority, matching is tried starting from the bid with the highest priority, and when the probability of successful matching becomes low, it is possible to switch to the bid with the next priority. Furthermore, according to the power trading system 10, for bids with multiple priorities, the predicted occurrence rate and the predicted matching rate are predicted, and in order to maintain the bid for a certain period of time, it is possible to maintain the bid with the highest priority as much as possible.

[0041] Therefore, according to the first embodiment, it is possible to provide the power trading system 10 that can appropriately trade power.

Embodiment

[0042] In the following embodiments, the technical matters common to the first embodiment will be omitted from the description. In the first embodiment, it was described that priorities are assigned to each bid. The bid information is a fixed value. In the second embodiment, instead of a fixed value, it will be described that a certain range is set for the value of the bid information. For example, for the purchase desired price of the demand bid information, it is conceivable to assign a certain range to the bids of each priority. If the purchase desired price in the first embodiment is 100 yen, a range of ±10% is assigned, and the purchase desired price is set to be from 90 yen to 110 yen. By performing the same processing on the supply bid information, the matching conditions can be relaxed, and the corresponding demand bid information or supply bid information for each bid can be increased.

Embodiment

[0043] FIG. 10 is a functional block diagram of the power trading system 10 according to the third embodiment. Here, a supply power classification unit 600 that collects supply-side predicted value information and classifies the supply power into a stable component of renewable energy, a fluctuating component of renewable energy, a charge / discharge capacity of renewable energy, a discharge capacity of renewable energy, non-renewable energy, a charge / discharge capacity of non-renewable energy, and a discharge capacity of non-renewable energy is added to the first embodiment (FIG. 3). In Example 1, it was proposed to classify power types into renewable energy or non-renewable energy, and further classify renewable energy into solar power and wind power. However, it is also possible to classify power types from other perspectives. For example, power types can be classified into a stable portion of renewable energy, a variable portion of renewable energy, the charge-discharge capacity of renewable energy, the discharge capacity of renewable energy, non-renewable energy, the charge-discharge capacity of non-renewable energy, and the discharge capacity of non-renewable energy. Since the power generation amount of renewable energy may differ from the predicted value, although the transaction is made in advance, there are fluctuations in the output, and it may not be possible to actually provide the power generation amount that was transacted. The stable portion of renewable energy and the variable portion of renewable energy represent the power generation amount of renewable energy with a high probability of being provided and a low probability of being provided, respectively. By doing so, the demand side that wants to stably secure the power generation amount of renewable energy will purchase the stable portion of renewable energy, and the demand side that wants to purchase renewable energy at a low cost even if it is unstable will purchase the variable portion of renewable energy. The charge-discharge capacity of renewable energy and the charge-discharge capacity of non-renewable energy are the capabilities to charge and discharge the battery with renewable energy and non-renewable energy, respectively, by classifying the power for charging and discharging the battery. Different from the stable portion of renewable energy and the variable portion of renewable energy that can only be used at a certain fixed time in order to utilize the battery capacity, it is the ability to discharge renewable energy or non-renewable energy from the battery or charge renewable energy or non-renewable energy into the battery during a certain time period. Non-renewable energy is the power generated from fossil fuels, etc., as described in Example 1.

[0044] The power supply classification unit 600 performs a process of dividing the power generation amount of renewable energy into a stable portion of renewable energy and a variable portion of renewable energy. As a method of dividing the power generation amount of renewable energy into a stable portion of renewable energy and a variable portion of renewable energy, there is a method using a confidence interval. The predicted value of renewable energy for the period during which the supply side wishes to sell is acquired.

[0045] Figure 11 shows an example of the predicted value of renewable energy. G402 is the average value of the predicted value, and G401 and G403 are the predicted values within a certain confidence interval. The method for obtaining the confidence level can be obtained by using the prediction error obtained by comparing the past predicted value with the actual value. The stable part of renewable energy and the variable part of renewable energy are separated based on the output probability. The probability serving as the criterion can take any arbitrary value. For example, if G401 and G403 are based on a normal distribution of 3σ (σ is the standard deviation), when the power generation amount below G403 is regarded as the stable part, the stable part of renewable energy and the variable part of renewable energy are separated based on an output probability of 99.7%.

[0046] In the matching-related data acquisition unit 100A, in the case of the stable part of renewable energy and the variable part of renewable energy, the processing results of the supply power classification unit 600 are automatically filled in for the power supply bidding information including the desired power supply date and time, the type of desired power supply, the desired power supply, and the desired power supply amount. And this value is updated when the updated data of the predicted value of renewable energy is input. In the prediction of the prediction occurrence rate and the prediction agreement rate, it is basically the same as in the first embodiment. However, when the stable part of renewable energy and the variable part of renewable energy are updated by the supply power classification unit 600 and the matching-related data acquisition unit 100A, the prediction occurrence rate and the prediction agreement rate described in the first embodiment are updated based on the updated supply bidding information.

[0047] According to the third embodiment, by dividing the power generation amount of renewable energy using the confidence interval, it can be divided into the stable part of renewable energy with a high supply probability and the variable part of renewable energy with a low supply probability, and matching can be performed.

Example

[0048] In Example 1, it is conceivable that the demand bidding information increases at a certain point in time. For example, the power consumption changes depending on the temperature, and for the procurement of the power, it is conceivable that a large amount of demand requests supply in the power trading system 10. Or, it is conceivable that the bids for a specific type of power concentrate. And, it is also conceivable that renewable energy is not generated due to the weather, and the supply bidding information that can be matched in the power trading system 10 disappears. In such a case, the renewable energy charging and discharging capacity can be utilized. That is, information enabling utilization of the renewable energy charging and discharging capacity is added as a matching condition for the demand bidding information. When the information enabling utilization of the renewable energy charging and discharging capacity is available, in the matching unit 400, before switching to the matching condition of the demand bidding individual ID of the next priority, a combination of the supply bidding information of the stable portion or the variable portion of the renewable energy outside the desired purchase time zone and the renewable energy charging and discharging capacity is searched for and matched. At that time, the conditions other than the desired purchase power date and time need to match. For example, in the case of Example 1, the total of the supply bidding price of the variable portion of the renewable energy to be set and the supply desired price of the renewable energy charging and discharging capacity needs to match the desired purchase price. In the case of Example 2, it needs to be within the set range. The stable portion or the variable portion of the renewable energy is charged using the renewable energy charging and discharging capacity. And the amount charged at the time of the desired purchase power date and time of the demand bidding information is provided.

[0049] Note that the present invention is not limited to the above-described examples, and includes various modifications. For example, the above-described examples have been described in detail for easy understanding of the present invention, and are not necessarily limited to those having all the configurations described. Also, a part of the configuration of one example can be replaced with the configuration of another example, and the configuration of another example can also be added to the configuration of one example. Further, for a part of the configuration of each example, addition, deletion, or replacement with other configurations is also possible.

[0050] Furthermore, each of the above-described configurations, functions, processing units, processing means, etc. may be implemented in hardware by designing part or all of them, for example, using an integrated circuit. Also, each of the above-described configurations, functions, etc. may be implemented in software by a processor interpreting and executing a program that realizes each function. Information such as programs, tables, files, etc. that realize each function can be stored in a memory, a recording device such as a hard disk or SSD (Solid State Drive), or a recording medium such as an IC card, SD card, or DVD.

[0051] Also, the control lines and information lines show those considered necessary for explanation, and not necessarily all control lines and information lines are shown on the product. In reality, it can be considered that almost all components are interconnected.

Explanation of Reference Numerals

[0052] 10 Power trading system 100, 100A Matching-related data acquisition unit 200 Expression rate prediction unit 300 Execution rate prediction unit 400 Matching unit 817 Program

Claims

1. A matching-related data acquisition unit that acquires priority demand bidding information and priority supply bidding information, An occurrence rate prediction unit that obtains the predicted occurrence rate of the demand bidding information and the predicted occurrence rate of the supply bidding information, A conclusion rate prediction unit that obtains the predicted conclusion rate of the demand bidding information and the predicted conclusion rate of the supply bidding information, A power trading system comprising: a matching unit that matches the demand bidding information and the supply bidding information while switching the priority of the demand bidding information based on the product of the predicted occurrence rate and the predicted conclusion rate of the demand bidding information, and while switching the priority of the supply bidding information based on the product of the predicted occurrence rate and the predicted conclusion rate of the supply bidding information.

2. The power trading system according to claim 1, characterized in that a range is set for the value of the demand bidding information and / or the supply bidding information.

3. The power trading system according to claim 1, characterized in that the supplied power is classified into a stable portion of renewable energy, a variable portion of renewable energy, a charge / discharge capacity of renewable energy, a discharge capacity of renewable energy, non-renewable energy, a charge / discharge capacity of non-renewable energy, and a discharge capacity of non-renewable energy, and the occurrence rate prediction unit and the conclusion rate prediction unit predict the predicted occurrence rate and the predicted conclusion rate for each supplied power.

4. The power trading system according to claim 3, characterized in that a confidence interval based on the predicted value and the actual value of renewable energy is calculated for the stable portion of renewable energy and the variable portion of renewable energy, and when the weather changes, the predicted occurrence rate and the predicted conclusion rate are updated using the confidence interval and the predicted value based on the changed weather.

5. The power trading system according to claim 3, characterized in that before switching to the following priority matching condition, the matching unit searches for a combination of the stable portion of renewable energy or the variable portion of renewable energy and the charge / discharge capacity of renewable energy, and matches the supply bidding information and the demand bidding information when they match according to the combination.

6. A matching-related data acquisition unit that acquires priority demand bidding information and priority supply bidding information, An occurrence rate prediction unit that obtains the predicted occurrence rate of the demand bidding information and the predicted occurrence rate of the supply bidding information, A conclusion rate prediction unit that obtains the predicted conclusion rate of the demand bidding information and the predicted conclusion rate of the supply bidding information, A program characterized by causing a computer to execute a matching unit that matches the demand bidding information and the supply bidding information while switching the priority of the demand bidding information based on the product of the predicted occurrence rate of the demand bidding information and the predicted agreement rate of the demand bidding information, and while switching the priority of the supply bidding information based on the product of the predicted occurrence rate of the supply bidding information and the predicted agreement rate of the supply bidding information.

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