Power transaction support device, power transaction support method, and computer program

Abstract

To provide a power transaction support device in which deterioration of a power storage element is taken into consideration.SOLUTION: A power transaction support device includes: a price acquisition unit for acquiring price transition of power generated based on a short-term predicted price and a long-term predicted price; a degradation simulator for estimating degradation in a power storage element according to an input temporary operation pattern; and a determination unit for determining a charge / discharge pattern of the power storage element for power transaction by using price transition of acquired power and estimation results by the degradation simulator.SELECTED DRAWING: Figure 6

Description

[Technical field]

[0001] The present invention relates to an energy trading support device, an energy trading support method, and a computer program that are applicable to energy trading using a power adjustment function by an energy storage element. [Background technology]

[0002] Patent Document 1 discloses an energy trading support device. A plurality of charge / discharge patterns are generated, each having a first time for charging a storage battery, a second time for discharging the storage battery, and a third time for not charging or discharging. For each charge / discharge pattern, a profit is calculated based on the difference between the procurement price or predicted price at the first time and the procurement price or predicted price at the second time, when purchasing electricity according to the charge / discharge pattern. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2019-152999 A Summary of the Invention [Problem to be solved by the invention]

[0004] In Patent Document 1, the deterioration of storage elements such as storage batteries is not taken into consideration. One aspect of the present invention provides an apparatus, a method, and a computer program for supporting energy trading, in which deterioration of an energy storage element is taken into consideration. [Means for solving the problem]

[0005] According to one embodiment of the present invention, an energy trading support device includes a price acquisition unit that acquires electricity price trends generated based on short-term predicted prices and long-term predicted prices, a degradation simulator that estimates degradation of a storage element according to an input hypothetical operation pattern, and a determination unit that determines a charging / discharging pattern of the storage element for energy trading using the acquired electricity price trends and the estimation results by the degradation simulator. Effect of the Invention

[0006] According to the above aspect, an energy trading support device is provided that takes into account the deterioration of storage elements, making it possible to consider profit maximization through energy trading in which storage elements are operated for long periods of time (e.g., until the storage elements reach their EoL (End of Life)). [Brief description of the drawings]

[0007] [Figure 1] FIG. 11 is a diagram showing the relationship between the operation year and the operation profit from electricity trading for a plurality of hypothetical charging and discharging patterns. [Diagram 2] FIG. 1A is a diagram showing an example of a charge / discharge pattern in which a storage battery is charged / discharged with a large SOC swing width, and FIG. 1B is a diagram showing an example of a charge / discharge pattern in which a storage battery is charged / discharged with a small SOC swing width. [Diagram 3] FIG. 13 is a diagram illustrating an example of a predicted value of electricity price. [Figure 4] 1 is a graph showing the relationship between the number of cycles and the capacity deterioration rate (deterioration value). [Diagram 5] 13 is a graph showing a change in capacity deterioration rate according to the magnitude of SOC fluctuation of a storage element in an early stage of operation. [Figure 6] FIG. 1 is a schematic diagram illustrating a power storage system and an energy trading support device. [Figure 7] 1A and 1B are diagrams illustrating an example of a hierarchical structure of a power storage module group and a connection form of communication devices. [Figure 8] FIG. 2 is a schematic diagram showing the operation of a degradation simulator; [Figure 9]FIG. 13 is a diagram illustrating a method for preventing a degradation value from substantially increasing while the characteristics of a storage element are maintained or improved. [Figure 10] FIG. 11 is a diagram illustrating an example of automatic setting of charging and discharging time periods. [Figure 11] FIG. 11 is a diagram for explaining another example of operation pattern search. [Figure 12] FIG. 13 is a diagram illustrating an example of a power price difference-lower limit SOC map. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0008] An outline of the embodiment will be described below. (1) The energy trading support device includes a price acquisition unit that acquires electricity price trends generated based on a short-term predicted price and a long-term predicted price, a degradation simulator that estimates degradation of a storage element according to an input hypothetical operation pattern, and a determination unit that determines a charging / discharging pattern of the storage element for energy trading using the acquired electricity price trends and the estimation results by the degradation simulator.

[0009] In this specification, a "storage element" may include a plurality of storage cells, a plurality of storage modules (storage packs), or a plurality of banks (strings). Alternatively, a "storage element" may be a single storage cell.

[0010] When large facilities such as energy storage systems (ESS) are used in electricity trading, it is desirable to aim to maximize overall profits based on information such as the initial cost of constructing the facilities, the operation period (expected life) of the facilities, the predicted price of electricity, etc. It is known that the operation period during which a storage battery facility can operate as expected varies depending on operation patterns such as charging and discharging patterns and temperature patterns.

[0011] For energy trading, storage battery facilities using lithium-ion batteries, which have excellent cycle performance, are often applied. Alternatively, storage battery facilities using lead-acid batteries may be applied.

[0012] The degradation simulator (1) above estimates the degradation of the energy storage element according to the input tentative charge / discharge pattern and / or tentative temperature pattern. The degradation simulator may estimate the degradation of the energy storage element for each of a plurality of tentative operation patterns. For example, the degradation simulator may estimate the degradation and operation period of the energy storage element for each of a charge / discharge pattern with a large SOC swing width that performs deep charge / discharge and a charge / discharge pattern with a small SOC swing width that performs shallow charge / discharge.

[0013] The determination unit determines a charging and discharging pattern of the energy storage element for energy trading, using the transition of the predicted value of the electricity price determined according to the supply and demand balance (time series change in price) and the estimation result by the degradation simulator. With the support of such an energy trading support device, it is possible to pursue maximization of profits from energy trading in which the energy storage element is operated for a long period of time, while taking into account the degradation of the energy storage element.

[0014] Figure 1 shows a simulation example of the transition of operating profit when electricity trading is conducted with a storage battery facility using lithium-ion batteries operated at a large SOC swing range, and the transition of operating profit when electricity trading is conducted with a small SOC swing range.

[0015] In this specification, the swing width of SOC (state of charge) means the difference between the SOC upper limit value (alternatively, the voltage upper limit value) when charging the storage element and the SOC lower limit value (alternatively, the voltage lower limit value) when discharging the storage element. The upper limit value may be set to a value lower than the upper limit value of the usage range of the storage element, and the lower limit value may be set to a value higher than the lower limit value of the usage range of the storage element. The upper limit value and the lower limit value may be changed as the operation period of the storage element elapses.

[0016] Figure 1 shows that in the early stages of operation, operation in which the storage element is charged and discharged with a large SOC swing range (solid line) results in greater operational profits. Figure 1 also shows that after 11 years from the start of operation, operation in which the storage element is charged and discharged with a small SOC swing range (dashed line) results in greater operational profits. The details are explained below.

[0017] Figure 2(A) shows a simplified example of a charge / discharge pattern for charging and discharging a storage element with a large SOC swing range. There is one cycle (one charge, one discharge) per day, and in the early stages of operation, charging at 400 kilowatts (kW) or more (positive direction on the Y axis of the graph) and discharging at 400 kW or more (negative direction on the Y axis) are performed. Figure 2(B) shows an example of a charge / discharge pattern for charging and discharging the energy storage element with a small SOC swing range. Charging and discharging are performed at less than 400 kW in one cycle per day from the beginning of operation.

[0018] Many lithium-ion batteries tend to deteriorate more when the SOC swing is large, and deteriorate less when the SOC swing is small. On the other hand, the larger the SOC swing, the larger the charge / discharge power amount and the greater the amount of power trading.

[0019] As shown in Figure 2(A), when the SOC swing is large, the chargeable and dischargeable power decreases early due to the large deterioration of the battery with cycling, and the battery reaches EoL in about 10 years. Therefore, the chargeable and discharged power of the battery after the 10th year is 0 kW. When the SOC swing range is small, as in Figure 2(B), the battery degradation due to cycling is small, making it possible to operate the battery for 15 years.

[0020] The solid line in Figure 1 (corresponding to Figure 2(A)) indicates that after the 10th year from the start of operation, the battery's charge / discharge power amount will reach zero, and the operating profit will become zero. The dotted line in Figure 1 (corresponding to Figure 2(B)) indicates that it is possible to continue earning investment profits by continuing electricity trading using batteries for 15 years from the start of operation, and from the 11th year onwards, the investment profits exceed the solid line.

[0021] The deterioration simulator and determination unit described above in (1) make it possible to determine a charge / discharge pattern that takes into account the deterioration of the storage elements and maximizes profits from a long-term perspective, rather than determining a charge / discharge pattern in a short-term perspective. In this specification, "determining a charge / discharge pattern" may mean at least any one of selecting or generating a waveform as shown in FIG. 2, determining an upper limit and / or a lower limit of SOC (voltage), determining a time period for charging / discharging, and changing the waveform or the upper and lower limits of SOC (voltage) at a predetermined timing.

[0022] Furthermore, the above-mentioned (1) energy trading support device improves the accuracy of profit calculation by acquiring electricity price trends generated based on short-term predicted prices and long-term predicted prices. This energy trading support device aims to maximize profits from the operation of an energy storage element over a long period of time (for example, until EoL), and therefore requires a corresponding long-term electricity price forecast value. The accuracy of the electricity price forecast value generally varies depending on the period (short term, medium term, long term). A highly accurate short-term forecast value can be combined with a long-term forecast value, or multiple short-term forecast values ​​can be combined, to generate a forecast value of the electricity price trend over a long period of time.

[0023] A specific example of the generated price forecast value will be described. Fig. 3(A) shows the price forecast value (short-term forecast value) for the smallest time unit (e.g., 30 minutes) in the electricity trading market, Fig. 3(B) shows the price forecast value (medium-term forecast value) for each time period of a day, and Fig. 3(C) shows the price forecast value (long-term forecast value) for each month. The short-term, medium-term, and long-term forecast values ​​are not limited to these. Figure 3(D) shows a forecast value of the price trend of electricity that combines short-term, medium-term, and long-term forecast values. In the example of Figure 3(D), in order to improve the accuracy of profit calculation, a short-term forecast value is applied for a period when it is available, and a medium-term forecast value is applied for a period when it is available. Other examples of forecast values ​​of the price trend of electricity will be described later.

[0024] (2) In the energy trading support device described in (1) above, the degradation simulator may estimate a first degradation of the storage element at the first time point based on an operation history of the storage element from the start of operation to the first time point, and may estimate a second degradation of the storage element according to a hypothetical operation pattern of the storage element from the first time point to a later second time point based on the first degradation.

[0025] In this specification, the "operation history" may include the charge / discharge history (current history, voltage history, SOC history, etc.) and / or temperature history that the energy storage element has experienced up to a certain point in time. The degradation simulator preferably uses a mathematical model that represents the state of the energy storage element and parameters that are applied to the mathematical model. The "state of the energy storage element" here may include not only the state of the energy storage element itself but also the state of the surrounding environment, such as the arrangement of the energy storage element.

[0026] The mathematical model mathematically describes the characteristics of the storage element and its surroundings using, for example, algebraic equations, differential equations, and characteristic parameters. The mathematical model may be executable code executed by a programming language or numerical analysis software, or may be definition information or a library file referenced by the programming language or numerical analysis software.

[0027] The deterioration simulator described above in (2) can accurately estimate how the energy storage element has actually been operated and how much it has deteriorated up to a first point in time (e.g., the present time), and then estimate the deterioration at a second point in time (e.g., a future point in time). Based on the estimation result, the determination unit can select or generate a waveform of a charge / discharge pattern, determine an upper limit value and / or a lower limit value, and determine a time period for charge / discharge.

[0028] The deterioration state of an energy storage element varies depending on the environment and how it is charged and discharged. For example, the deterioration that occurs during operation of a lithium-ion battery includes various deterioration modes, such as the isolation of active material particles, a decrease in charge carriers (charge carriers that exist in the solid or liquid phase; lithium ions Li+) involved in charging and discharging, an increase in electrical resistance, and a decrease in the conductivity of the electrolyte.

[0029] In an estimation method that uses only physical quantities that can be measured from the energy storage element at a first time point (e.g., the present time) without considering the operation history of the energy storage element, it is not possible to specify the details of the state of the energy storage element, such as which degradation mode is progressing, etc. Therefore, it is difficult to improve the accuracy of estimating the second degradation at the second time point. In contrast, the degradation simulator of (2) above can accurately estimate the first degradation by referring to the operation history of the energy storage element up to the first time point, and can also improve the accuracy of estimating the second degradation. It is also possible to perform simulations for multiple hypothetical future operation patterns and change the operation pattern at a predetermined timing so as to improve future operation profits.

[0030] (3) The degradation simulator described in (1) or (2) above may be configured not to substantially increase a degradation value indicating degradation of the storage element during the initial period of operation of the storage element, during which characteristics are maintained or improved.

[0031] Here, the "characteristics" may be the full charge capacity or high rate characteristics of the storage element, but are not limited to these. The "deterioration value" is preferably a capacity deterioration rate that indicates the degree of decrease in the full charge capacity as a percentage. Alternatively, the "deterioration value" may be a value that reflects other deterioration factors such as an increase in internal resistance (ohmic resistance, non-ohmic resistance). "Not substantially increasing the degradation value" may mean that, while the characteristics of the storage element are maintained or improved, (a) the degradation value is maintained at a value close to zero, or (b) the degradation value is set to a negative initial value and is gradually increased, so that the degradation value is not increased to a positive value.

[0032] The inventors of the present invention have come up with the above configuration (3) by noting that in a storage cell such as a lithium-ion battery, characteristics are maintained or improved, such as an increase in full charge capacity at the beginning of operation (the beginning of a charge / discharge cycle). The increase in full charge capacity is presumably due to the penetration of an electrolyte into the positive electrode plate, the negative electrode plate, and the separator, or between the positive electrode plate or the negative electrode plate and the separator, or due to the charge / discharge of the storage cell (expansion and contraction of the positive electrode active material), which causes cracks in the secondary particles of the positive electrode active material, thereby increasing the surface area of ​​the positive electrode active material that contributes to the charge / discharge reaction, thereby improving the high-rate characteristics.

[0033] The conventional estimation line shown by the solid line in Figure 4, which simulates the degradation value by starting to increase from the beginning of the cycle, may deviate from the degradation behavior of the actual energy storage cell shown by the dashed line (an approximation line fitting the actual measured values ​​shown by the circles). This is because the conventional estimation line does not take into account the maintenance / improvement of the characteristics of the energy storage element that occurs in the early stages of operation. As shown by the dashed approximation line in Figure 4, by not substantially increasing the degradation value in the early stages of operation (for example, up to about 200 to 350 cycles), the accuracy of degradation estimation can be improved, and therefore the accuracy of calculation of profits from energy trading can be improved. 4 indicates the number of times (cycle number) that charging and discharging were repeated between 0% and 100% SOC. The "cycle" referred to in this specification is not limited to this example, and may refer to repetition of charging and discharging in a partial range between 0% and 100% SOC.

[0034] (4) The degradation simulator described in (3) above may make a decision regarding an increase in the degradation value based on a magnitude of a fluctuation in SOC at an early stage of operation of the energy storage element.

[0035] The inventors found that different degradation behaviors occur depending on the magnitude of fluctuation in the SOC of the storage element in the initial operation stage, and came up with the above configuration (4). The above configuration can improve the accuracy of estimating the degradation of the storage element and improve the accuracy of calculating the profit from electricity trading.

[0036] (5) The degradation simulator described in (4) above may increase the full charge capacity of the storage element at the beginning of operation to a greater extent the greater the magnitude of the fluctuation in SOC, and may increase the degradation value of the storage element whose full charge capacity has been increased.

[0037] As shown in FIG. 5, the capacity degradation rate of a storage element in the early stage of operation may take a negative value (i.e., the full charge capacity increases) as the number of cycles increases. In FIG. 5, the solid line indicates the change in the capacity degradation rate when the storage element is charged and discharged between SOC 75% and 100%, and the dashed line indicates the change in the capacity degradation rate when the storage element is charged and discharged between SOC 0% and 100%. There is a tendency that the capacity degradation rate of a storage element in the early stage of operation takes a large negative value (i.e., the full charge capacity increases) as the magnitude of the SOC fluctuation increases. Therefore, by taking this tendency into consideration (reflecting it in the estimation), the accuracy of the estimation of the degradation of the storage element can be improved, and the accuracy of the calculation of the profit from electricity trading can be improved.

[0038] (6) In any of the energy trading support devices described above in (1) to (5), the degradation simulator may estimate degradation of the energy storage element according to a tentative charge / discharge pattern generated using a power purchase threshold and a power sale threshold set to the price trend of the electricity, and the determination unit may determine a charge / discharge pattern of the energy storage element for energy trading using the generated tentative charge / discharge pattern and an estimation result by the degradation simulator.

[0039] With the above configuration, it is possible to automatically determine the time periods for buying and selling electricity (time periods for charging and discharging the energy storage element) based on the predicted electricity price trends, which contributes to maximizing profits from electricity trading while taking into account the deterioration of the energy storage element. Details will be described later (Figure 10).

[0040] (7) In any one of the energy trading support devices (1) to (5) above, the determination unit may determine a charging / discharging pattern of the storage elements for energy trading in accordance with an energy price difference within a predetermined time period.

[0041] With the above configuration, it is possible to automatically determine a charge / discharge pattern that contributes to maximizing profits from electricity trading while taking into account the deterioration of the storage elements. Details will be described later (Fig. 11 and Fig. 12).

[0042] (8) An electricity trading support method includes a computer acquiring electricity price trends generated based on short-term and long-term predicted prices, estimating deterioration of a storage element according to a hypothetical operation pattern, and determining a charging / discharging pattern of the storage element for electricity trading using the acquired electricity price trends and the estimation result.

[0043] (9) The computer program causes the computer to execute a process of acquiring electricity price trends generated based on short-term predicted prices and long-term predicted prices, estimating deterioration of a storage element according to a hypothetical operation pattern, and determining a charging / discharging pattern of the storage element for electricity trading using the acquired electricity price trends and the estimation result.

[0044] The above-mentioned energy trading support method and computer program may be executed by a computer located close to the energy storage element, or may be executed by a computer located remotely from the energy storage element. The above-mentioned energy trading support method and computer program may be applied to a method equivalent to the configurations described in (2) to (6) above.

[0045] Hereinafter, the embodiment will be described in detail with reference to the drawings. Fig. 6 shows an example of remote monitoring of a plurality of energy storage systems for energy trading installed in a certain area or site. The plurality of power storage systems may be distributed across a plurality of sites, or may be centrally located in one place. The container C that houses the power storage module group L may be a battery panel or rack installed indoors, or a cubicle installed outdoors. The container C may be the housing of a storage battery-equipped device (for example, a power conditioner with a storage battery or a backup power supply).

[0046] Each of the multiple energy storage systems may be communicatively connected to a local network CN via a communication device 1 and transmit status data of each energy storage element to a local management device 2A. The status data may include a cell voltage value, a cell internal resistance value, a bank current value, a temperature, and the like.

[0047] The communication device 1 may be a measurement monitor that communicates with a battery management unit (BMU) provided in the power storage element to receive information about the power storage element, or may be a controller compatible with ECHONET / ECHONETLite (registered trademark). The communication device 1 may be a network card type device. One communication device 1 is provided for each group consisting of multiple power storage modules in order to obtain information about a power storage module group L in the power storage system.

[0048] The status data transmitted from the multiple power storage systems is received by a server device 2 for remote monitoring via a dedicated line DN or a network N. The status data is stored in the server device 2 as an operation history in association with identification data for identifying the power storage systems.

[0049] The energy trading support apparatus 300 is communicatively connected to a server apparatus 2 for remote monitoring and a price data management apparatus 400 that generates or stores predicted values ​​of electricity prices. In this embodiment, the energy trading support apparatus 300, the server apparatus 2, and the price data management apparatus 400 are managed by a manufacturer of the energy storage element or energy storage system, and are communicatively connected to each other via a local network MN or a dedicated line for the manufacturer. The network MN may include a VPN (Virtual Private Network).

[0050] Alternatively, the server device 2 may incorporate the functions of the energy trading supporting apparatus 300, or the server device 2 may provide the functions / services of supporting energy trading as a subset of the functions / services of remote monitoring. The server device 2 may include a Web server function, and may present information obtained from the communication device 1 mounted on / connected to each power storage system to be monitored in response to access from the client device 3.

[0051] The energy trading supporting apparatus 300 may use a server computer 301 and include a storage unit 311. In this embodiment, the server computer 301 is described as a single server computer, but processing may be distributed among a plurality of server computers. In this embodiment, the server computer 301 functions as a degradation simulator 3a, a price acquisition unit, and a determination unit, which will be described later.

[0052] The server computer 301 includes a control unit and a communication unit, not shown. The control unit is a processor using a CPU or a GPU (Graphics Processing Unit), and controls each component unit and executes processing using built-in memories such as ROM and RAM. The control unit executes communication and information processing based on a server program stored in the storage unit 311. The program may include a Web server program, and the control unit may function as a Web server that executes the provision of Web pages to the client device 3.

[0053] The storage unit 311 uses a non-volatile memory such as a hard disk or a flash memory. The above-mentioned server program and data processing program are stored in the storage unit 311. The server program P and data processing program stored in the storage unit 311 may be a server program and a data processing program that are read out from a recording medium (not shown) and copied to the storage unit 311.

[0054] The network N includes a public communication network, which is the so-called Internet, and a carrier network that realizes wireless communication according to a predetermined mobile communication standard. The public communication network includes a general optical line, and the network N includes a dedicated line to which the server device 2 is connected. The carrier network includes a base station BS, and the client device 3 can communicate with the server device 2 from the base station BS via the network N.

[0055] An access point AP is connected to the network MN, and the client device 3 can transmit and receive information to and from the server computer 301 via the access point AP.

[0056] The client device 3 may be a desktop or laptop personal computer, or may be a so-called smartphone or tablet communication terminal. The client device 3 includes a control unit, a storage unit, a communication unit, a display unit 33, and an operation unit 34, all of which are not shown.

[0057] The display unit 33 uses a display such as a liquid crystal display or an organic EL (Electro Luminescence) display. The display unit 33 displays an image of a Web page provided by the server device 2. The display unit 33 is preferably a display with a built-in touch panel, but may be a display without a built-in touch panel.

[0058] The operation unit 34 is a user interface such as a keyboard and a pointing device, or a voice input unit, capable of inputting and outputting data to and from the control unit 30. The operation unit 34 may be a touch panel of the display unit 33, or physical buttons provided on the housing. The operation unit 34 notifies the control unit of operation information by the user.

[0059] The storage module group L of the energy storage system has a hierarchical structure. FIG. 7 shows an example of the hierarchical structure of the storage module group L and a connection form of the communication device 1. The storage module group L is configured in a hierarchical structure of, for example, a storage module in which a plurality of storage cells are connected in series, and a bank in which a plurality of storage modules are connected in series. In the example of FIG. 7, one management device M as a BMU is provided for each of the banks numbered (#) 1 to N and for each bank group (also called a domain) in which the banks are connected in parallel. The management device M provided for each bank communicates with a control board (CMU: Cell Management Unit) with a communication function built into each storage module by serial communication, and acquires measurement data (current, voltage, temperature) of the storage cells in the storage module. The management devices M of the banks transmit the measurement data obtained from the storage modules of the respective banks to the management device M provided in the domain. The management device M of the domain collects information such as the measurement data obtained from the management devices M of the banks belonging to the domain, and detected abnormalities.

[0060] Although not shown in detail, the energy storage cell may include a hollow rectangular parallelepiped case and a pair of cell terminals with different polarities provided on one side (terminal surface, top surface) of the case. The case contains an electrode assembly formed by stacking a positive electrode, a separator, and a negative electrode, and an electrolyte (electrolytic solution). The storage cell is not limited to a prismatic cell, but may be a cylindrical lithium ion battery or a laminated (pouch) lithium ion battery. The storage cell may be an all-solid-state lithium ion battery using a solid electrolyte.

[0061] The communication device 1 receives an operation pattern transmitted from the management device 2A or the energy trading support device 300 shown in FIG. 6, and charges and discharges each bank in accordance with the operation pattern via the management device M of the domain and the management device M for each bank.

[0062] Fig. 8 is a schematic diagram showing the operation of the degradation simulator 3a. The degradation simulator 3a receives time-series data of SOC (charge / discharge pattern) and time-series data of temperature (temperature pattern) as input data, and estimates (calculates) the degradation value of the storage element. As shown in Fig. 8, the time-series data of SOC indicates the fluctuation of SOC from time t1 to time tn (e.g., n SOC values ​​at each time), and the time-series data of temperature indicates the fluctuation of temperature from time t1 to time tn (e.g., n temperature values ​​at each time).

[0063] The degradation simulator 3a can estimate the decrease (degradation value) of the SOH of the storage element from time t1 to time tn based on the fluctuation of the SOC and temperature from time t1 to time tn. If the SOH at time t1 is SOHt1 and the SOH at time tn is SOHtn, the degradation value is (SOHt1 -SOHtn). That is, if the SOH at time t1 is known, the SOH at time tn can be obtained based on the degradation value. Here, the time t1 can be a time in the past, present, or future, and the time tn can be a time when a predetermined time has passed from the time t1 toward the future. The time difference between the time t1 and the time tn is the degradation prediction target period of the degradation simulator 3a, and can be appropriately set depending on how far into the future the degradation value is predicted. The time difference between the time t1 and the time tn can be, for example, one month, half a year, one year, two years, or the like.

[0064] In the example of FIG. 8, time-series data of temperature is input to the deterioration simulator 3a, but alternatively, a representative temperature (for example, an average temperature from time t1 to time tn) may be input to the deterioration simulator 2a.

[0065] The deterioration simulator 3a in this embodiment is configured so as not to substantially increase the deterioration value indicating deterioration (in this embodiment, the deterioration rate of the full charge capacity) during the initial period of operation of the storage element, during which the characteristics are maintained or improved.

[0066] The degradation simulator 3a estimates the extent to which the characteristics of the energy storage element are maintained / improved from the magnitude of the SOC fluctuation and temperature at the beginning of operation of the energy storage element, and determines from which cycle number the capacity degradation rate is increased as a positive value. In the estimated line in FIG. 9, the capacity degradation rate increases as a positive value from about 350 cycles. The capacity degradation rate is maintained at zero up to 350 cycles. In other words, the cycle degradation value is maintained at zero while the full charge capacity of the energy storage element is increasing.

[0067] The conventional estimated line shown by the dashed line in FIG. 9 starts increasing from the beginning of the cycle to simulate the degradation value. The conventional estimated line does not take into account the maintenance / improvement of the characteristics of the energy storage element seen in the early stage of operation, and therefore deviates from the actual measured value shown by the triangular points. In contrast, the estimated line according to the present embodiment shown by the solid line in FIG. 9 maintains the capacity degradation rate at zero in the early stage of the cycle, and then increases the capacity degradation rate so as to follow the approximation line fitted to the actual measured value. In this way, the accuracy of degradation estimation can be improved by taking into account the maintenance / improvement of the characteristics of the energy storage element in the early stage of operation and not substantially increasing the degradation value during that operation period. The improved accuracy of degradation estimation can reduce the occurrence of events such as failure of the energy storage system and failure to meet requirements.

[0068] The server computer 301 shown in Fig. 6 acquires short-term, medium-term, and long-term electricity price forecast values ​​(e.g., see Figs. 3(A)-(C)) from the price data management device 400, and combines them to generate a long-term electricity price trend forecast value (e.g., see Fig. 3(D)). The server computer 301 may acquire a long-term electricity price trend forecast value (Fig. 3(D)) that has been generated in advance and stored in the price data management device 400.

[0069] A server computer 301 shown in FIG. 6 inputs a tentative operation pattern for the future into a deterioration simulator 3a, and estimates a deterioration value according to the operation pattern. The server computer 301 determines a charge / discharge pattern of the storage element for power trading using the predicted value of the power price transition obtained from the price data management device 400 and the estimation result by the degradation simulator 3a. For example, when the simulation result shown in Fig. 1 is obtained, a charge / discharge pattern with a small SOC swing width is selected.

[0070] Next, with reference to FIG. 10, another method for determining the charge / discharge pattern will be described.

[0071] The times of day when electricity prices are lowest (best for buying electricity) and highest (best for selling electricity) vary depending on the season and / or the operating status of existing power plants, such as nuclear power plants.

[0072] Fig. 10(A) shows the future price trends of electricity, which are predicted taking into account the season and the operating status of existing power plants. A power purchase threshold (a criterion for determining whether electricity can be purchased when the electricity price is below that value) and a power sale threshold (a criterion for determining whether electricity can be sold when the electricity price is above that value) are set for the price trends of generated electricity. In this example, the electricity purchase threshold is set to 27 yen / kilowatt-hour [kWh], and the electricity sale threshold is set to 40 yen / kWh.

[0073] The server computer 301 (FIG. 6) generates a tentative charging and discharging pattern of FIG. 10(B) from the information of FIG. 10(A). This tentative charging and discharging pattern is set to charge when the power price is equal to or lower than the power purchase threshold, and to discharge when the power price is equal to or higher than the power sale threshold. The server computer 301 inputs this tentative charging and discharging pattern into the deterioration simulator 3a, estimates the deterioration value according to the operation pattern, and then generates an operational charging and discharging pattern that takes the deterioration into account, as shown in Figure 10 (C).

[0074] According to the above configuration, the time periods for buying and selling electricity (time periods for charging and discharging the storage element) can be automatically determined based on predicted trends in electricity prices, and at the same time, it is possible to maximize profits through electricity trading by operating the storage element for a long period of time.

[0075] Next, with reference to FIG. 11, another method for determining the charge / discharge pattern will be described.

[0076] The difference in electricity prices during the day varies depending on the season and other factors. When the price difference is large (solid line in Figure 11(A)), the amount of charging and discharging electricity (electricity trading volume) is increased to increase operational profits. Conversely, when the price difference is small (dashed line in Figure 11(A)), the amount of charging and discharging electricity is reduced to suppress the progression of deterioration of the storage elements. An example of a charging and discharging pattern determined by such an algorithm is shown in Figure 11(B).

[0077] In order to generate the charge / discharge pattern of FIG. 11(B), a rule (map) of the power price difference and the lower limit SOC shown in FIG. 12 may be used. In the example of Figure 12, when the power price difference is 10 yen or less, the lower limit SOC of the storage element is set to 100%, so that charging and discharging (power trading) of the storage element is not performed. Considering the efficiency of the power conditioner (PCS) and the power loss according to the charging and discharging efficiency of the storage element, charging and discharging are not performed when the price difference is small.

[0078] The map in Figure 12 is optimized to maximize the profits from energy trading by operating the storage elements for a long period of time. In Figure 12, when the electricity price difference exceeds 10 yen, the lower limit SOC gradually decreases from 50%. Instead of decreasing the lower limit SOC linearly, the lower limit SOC is decreased nonlinearly (in a downward convex curve, and the decrease in the lower limit SOC as the price difference increases) in consideration of the fact that deterioration increases as the SOC swing width increases.

[0079] The present invention is not limited to the above-described embodiment, and can be modified as appropriate. The degradation simulator 3a and other computer programs may be executed by the local management device 2A or the remote monitoring server device 2, or may be executed by the client device 3, instead of the server computer 301 shown in FIG. [Explanation of symbols]

[0080] 301 Server computer (power trading support device) 311 Storage section 400 Price data management device

Claims

1. a price acquisition unit that acquires price trends of electricity generated based on a short-term predicted price and a long-term predicted price; a deterioration simulator that estimates deterioration of the storage element according to a tentative operation pattern that is input; a determination unit that determines a charge / discharge pattern of the energy storage element for energy trading using the acquired price transition of the energy and the estimation result by the degradation simulator; An energy trading support device comprising:

2. 2. The energy trading support device of claim 1, wherein the deterioration simulator estimates a first deterioration of the storage element at the first time point based on an operation history of the storage element from the start of operation to the first time point, and estimates a second deterioration of the storage element according to a hypothetical operation pattern of the storage element from the first time point to a later second time point based on the first deterioration.

3. 3. The energy trading support device according to claim 1 or claim 2, wherein the deterioration simulator is configured not to substantially increase a deterioration value indicating deterioration of the storage element during an initial period of operation of the storage element during which characteristics are maintained or improved.

4. 4. The energy trading supporting apparatus according to claim 3, wherein the degradation simulator makes a decision regarding an increase in the degradation value based on a magnitude of a fluctuation in a state of charge (SOC) of the energy storage element at an early stage of operation.

5. 5. The energy trading support device according to claim 4, wherein the degradation simulator increases the full charge capacity of the storage element in an initial stage of operation to a greater extent as the magnitude of fluctuation in SOC increases, and increases the degradation value of the storage element whose full charge capacity has been increased.

6. the deterioration simulator estimates deterioration of the energy storage element according to a tentative charge / discharge pattern generated using a power purchase threshold and a power sale threshold set in accordance with the price transition of the electricity; 3. The energy trading supporting apparatus according to claim 1, wherein the determination unit determines a charge / discharge pattern of the energy storage element for energy trading by using the generated tentative charge / discharge pattern and an estimation result by the degradation simulator.

7. 3. The energy trading supporting apparatus according to claim 1, wherein the determination unit determines a charging / discharging pattern of the energy storage elements for energy trading in accordance with a difference in an energy price within a predetermined time period.

8. The computer Obtaining price trends of electricity generated based on short-term predicted prices and long-term predicted prices; Deterioration of the storage element according to a tentative operating pattern is estimated; determining a charge / discharge pattern of the energy storage element for energy trading using the obtained price transition of the energy and the estimation result; A method for supporting electricity trading.

9. On the computer, Obtaining price trends of electricity generated based on short-term predicted prices and long-term predicted prices; Deterioration of the storage element according to a tentative operating pattern is estimated; determining a charge / discharge pattern of the energy storage element for energy trading using the obtained price transition of the energy and the estimation result; A computer program for executing a process.

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