Driving assistance device, driving assistance method, and driving assistance program

Abstract

To provide a driving assistance device, a driving assistance method, and a driving assistance program to prevent surplus electric power from being generated in renewable energy power generation facilities.SOLUTION: A driving assistance device determines start of preparation for driving a load device. The load device requires preparation time from the start of preparation for driving to the start of the driving, and is capable of consuming at least either of power generated by a power generating device using renewable energy and discharging power in an energy storage device capable of charging power generated by the power generating device during driving. The driving assistance device includes a determination unit that determines the start of preparation for driving the load device when historical information representing the history of the amount of energy stored in the energy storage device corresponds to a predetermined state.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a driving assistance device, a driving assistance method, and a driving assistance program that determine whether a load device has started preparation for operation. [Background technology]

[0002] In order to reduce greenhouse gas emissions, synthetic methane production technology (methanation) has been attracting attention. Synthetic methane is produced by reacting carbon dioxide with hydrogen. Methanation is recognized as an important technology toward realizing so-called carbon neutrality, as synthetic methane produced using carbon dioxide emitted from factories and other sources can be used in factories and other sources, and the produced synthetic methane can be sent through city gas pipelines. In order for synthetic methane produced by methanation to be carbon neutral, it is desirable that the electricity used in its production is derived from renewable energy sources such as wind power and solar power.

[0003] Power supply from renewable energy sources may be unstable due to weather, time of day, and other factors. The generated power can be stored in a power storage system configured in a microgrid to which the power generation device belongs, but if the SoC (State of Charge) of the power storage system exceeds an upper operational limit, surplus power will be generated. When surplus power is generated, it becomes necessary to transmit the power to an external power system or to suppress power generation, so it is preferable to consume the power by operating a load device such as a methanation device. The following Patent Document 1 describes a system that formulates a power transmission plan based on a predicted value of surplus power based on the difference between a predicted value of power generation by renewable energy and a predicted value of power demand, and produces hydrogen when the SoC of a storage battery exceeds a set value. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2020-54085 A Summary of the Invention [Problem to be solved by the invention]

[0005] However, load devices such as methanation devices cannot immediately operate in a state where they can consume power even when they receive a startup command, and a preparation time is required from the start of operation preparation based on the startup command until the start of operation when they can consume power.The system described in Patent Document 1 is based on the premise that the hydrogen production equipment will be able to consume power immediately after a startup command is issued, and does not take the preparation time into consideration, so there are cases where the generation of surplus power cannot be prevented.

[0006] Therefore, an object of one aspect of the present disclosure is to provide a technique capable of preventing the generation of surplus power in renewable energy power generation facilities. [Means for solving the problem]

[0007] In order to solve the above problems, a driving assistance device according to one aspect of the present disclosure is a driving assistance device that determines when a load device has started preparation for operation, wherein the load device is a device that requires preparation time from when preparation for operation starts to when operation starts, and is capable of consuming at least one of the generated power of a power generation device using renewable energy and the discharged power of an energy storage device that can charge the power generated by the power generation device during operation, and the driving assistance device is equipped with a determination unit that determines when preparation for operation of the load device has started when history information representing the history of the amount of energy stored in the energy storage device corresponds to a predetermined state.

[0008] In order to solve the above problems, a driving assistance method according to one aspect of the present disclosure is a driving assistance method in a driving assistance device that determines when a load device has started preparing for operation, wherein the load device is a device that requires a preparation time from when preparation for operation starts to when operation starts, and is capable of consuming at least one of the generated power of a power generation device using renewable energy and the discharged power of an energy storage device that can charge the power generated by the power generation device during operation, and the driving assistance method includes a determination step of determining when preparation for operation of the load device has started when history information representing the history of the amount of energy stored in the energy storage device corresponds to a predetermined state.

[0009] In order to solve the above problems, a driving assistance program according to one aspect of the present disclosure is a driving assistance program for causing a computer to function as a driving assistance device that determines the start of preparation for operation of a load device, wherein the load device is a device that requires preparation time from the start of preparation for operation to the start of operation, and is capable of consuming at least one of the generated power of a power generation device using renewable energy and the discharged power of an energy storage device that can charge the power generated by the power generation device during operation, and the driving assistance program realizes a determination function that determines the start of preparation for operation of the load device when historical information representing the history of the amount of energy stored in the energy storage device corresponds to a predetermined state.

[0010] According to the above aspect, when the history information of the energy storage amount corresponds to a predetermined state, a determination is made as to whether or not to start preparation for operation of a load device that requires preparation time before it can be in an operating state in which it can consume electric power. Therefore, by performing the determination process of whether or not to start preparation for operation in advance at an appropriate timing, it is possible to put the load device in an operating state in which it can consume electric power at a desired timing.

[0011] In a driving assistance device according to another aspect, the historical information may include a first value representing the amount of stored energy at a first point in time that is a point in time before the present, and a second value representing the amount of stored energy at at least one point in time before the first point in time.

[0012] According to the above aspect, not only the value of the energy storage amount at a certain point in time but also the value of the energy storage amount before that point in time is used to determine whether preparation for operation has started, so that the tendency of transition of the energy storage amount is taken into consideration, and therefore it is possible to accurately determine whether preparation for operation has started.

[0013] In a driving assistance device relating to another aspect, the judgment unit may make a start judgment when the historical information corresponds to a predetermined state in which surplus power is predicted to be generated in a certain range of a power grid that includes at least a power generation device and an energy storage device.

[0014] According to the above aspect, when the generation of surplus power is predicted, a determination is made in advance as to whether or not to start preparations for operation of the load device, so that the generation of surplus power is prevented.

[0015] In a driving assistance device according to another aspect, the determination unit may make a start determination when the history information corresponds to a predetermined state in which the amount of energy stored in the energy storage device is predicted to exceed a given first threshold value.

[0016] According to the above aspect, since the determination is made based on whether or not it is predicted that the amount of stored energy will exceed the first threshold, the occurrence of surplus power is predicted with high accuracy.

[0017] In a driving assistance device according to another aspect, the determination unit may make a start determination when the amount of energy stored at the first time point is equal to or greater than a given second threshold, or when the amount of energy stored at the first time point is equal to or greater than a given third threshold and an increase in the amount of energy stored at the first time point compared to a second time point that is a given time back from the first time point is equal to or greater than a predetermined degree.

[0018] According to the above aspect, the start determination is made when the energy storage amount at the first time point is equal to or greater than a predetermined value, or when the rate of increase in the energy storage amount during a predetermined period leading up to the first time point is equal to or greater than a predetermined level. In other words, since not only the value of the energy storage amount at a certain point in time but also the tendency of increase in the energy storage amount is taken into consideration, it is possible to appropriately determine whether or not it is a state in which surplus power is predicted to occur.

[0019] In a driving assistance device according to another aspect, the determination unit may make a start determination when a transition in the energy storage amount from a second point in time, which is a given time from the first point in time, to the first point in time corresponds to at least one surplus power generation pattern preset as an energy storage amount transition pattern in which the energy storage amount exceeds a first threshold value.

[0020] According to the above aspect, a determination process is performed based on whether or not the transition in the energy storage amount during a specified period leading up to a first point in time corresponds to a given transition pattern of the energy storage amount, making it easy to predict the generation of surplus power and to determine when preparation for operation has begun.

[0021] In a driving assistance device according to another aspect, the determination unit may use a predetermined prediction model constructed based on actual information regarding transitions in the amount of energy stored in the energy storage device to calculate a predicted value of the amount of energy stored after the current time in a time series based on historical information, and make a start determination when the predicted value within a given prediction period after the current time exceeds a first threshold value.

[0022] According to the above aspect, a transition in the amount of stored energy after the current time is predicted using a prediction model for predicting a transition in the amount of stored energy, and a determination is made to start preparation for operation when a predicted value within a prediction target period exceeds a predetermined threshold. This makes it possible to easily predict the generation of surplus power and to determine whether preparation for operation should be started.

[0023] In a driving assistance device according to another aspect, the determination unit may perform the determination when operation of the load device has not started.

[0024] According to the above aspect, the process of determining whether to start operation is not performed when the load device is already in an operating state, thereby preventing unnecessary execution of the process of determining whether to start preparation for operation.

[0025] A driving assistance device according to another aspect may further include an output unit that outputs information indicating the start determination in a predetermined manner.

[0026] According to the above aspect, the result of the determination of the start of preparation for operation can be used for starting up the load device.

[0027] In a driving assistance device according to another aspect, the output unit may transmit information indicating the start determination to the load device as driving preparation start information for causing the load device to start driving preparation.

[0028] According to the above aspect, the operation preparation start information is transmitted to the load device, so that the load device can be immediately started.

[0029] In a driving assistance device according to another aspect, the output unit may output the information indicating the start determination in at least one form of a display or a sound that can be recognized by a person.

[0030] According to the above aspect, since information indicating the start determination is output in the form of a display, sound, or the like, it is possible to prompt the operator of the load device to make a decision as to whether to start the load device. Effect of the Invention

[0031] According to one aspect of the present disclosure, it is possible to prevent surplus power from being generated in a renewable energy power generation facility. [Brief description of the drawings]

[0032] [Figure 1]1 is a schematic diagram of a power supply system according to an embodiment; [Diagram 2] FIG. 2 is a block diagram showing the functional configuration of an EMS. [Diagram 3] FIG. 2 is a diagram illustrating the hardware configuration of an EMS. [Figure 4] 4 is a flowchart showing a determination process of the driving assistance method according to the first embodiment. [Diagram 5] FIG. 13 is a diagram illustrating an example of a transition of SoC when a determination is made to start preparation for operation. [Figure 6] 11 is a diagram illustrating an example of a transition of an SoC when a start of preparation for operation is not determined. [Figure 7] FIG. 11 is a block diagram showing the functional configuration of an EMS according to a second embodiment. [Figure 8] FIG. 11 is a diagram illustrating a determination process according to the second embodiment. [Figure 9] Fig. 9(a) is a diagram showing an example of a non-excess power generation pattern among transition patterns of the stored energy amount, and Fig. 9(b) is a diagram showing an example of a surplus power generation pattern among transition patterns of the stored energy amount. [Figure 10] 10 is a flowchart showing a determination process of a driving assistance method according to a second embodiment. [Figure 11] FIG. 13 is a diagram for explaining labeling regarding the occurrence of surplus power for a transition pattern. [Figure 12] FIG. 11 is a block diagram showing a functional configuration of an EMS according to a third embodiment. [Figure 13] FIG. 13 is a diagram illustrating a determination process according to the third embodiment. [Figure 14] FIG. 13 is a diagram for explaining calculation of a predicted value of an energy storage amount by an autoregressive model. [Figure 15] 13 is a flowchart showing a determination process of a driving assistance method according to a third embodiment. [Figure 16] FIG. 13 is a schematic diagram showing another example of a power supply system. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0033] Hereinafter, an embodiment of the present invention will be described in detail with reference to the accompanying drawings. In the description of the drawings, the same or equivalent elements are designated by the same reference numerals, and duplicated description will be omitted.

[0034] FIG. 1 is a schematic diagram of a power supply system 1 according to an embodiment. As shown in FIG. 1, the power supply system 1 includes a microgrid 2 and an energy management system 3 (driving support device). Hereinafter, the "energy management system" is referred to as "EMS." A microgrid is generally a small-scale power network that brings together energy supply sources and consumption facilities within a certain range, and the microgrid 2 of this embodiment includes a photovoltaic power generation facility 21, a methanation device 22 (load device), a power storage system 23, a connection unit 24, a received power measurement unit 25, and a transmitted power measurement unit 26. The microgrid 2 is also connected to an external power system 90, and can transmit and receive power to and from the power system 90.

[0035] The solar power generation facility 21 is an example of a power generation device that uses renewable energy. The solar power generation facility 21 is a system that generates power using sunlight (Photovoltaic: PV), and includes a solar panel 21a and a power conditioner (Power Conditioning System: PCS) not shown. The power conditioner may also be called a PV-PCS. The PV-PCS converts direct current into alternating current.

[0036] In the present disclosure, the type of power generation equipment using renewable energy is not limited to solar power generation. For example, the power generation equipment using renewable energy may be a wind power generation system, a geothermal power generation system, a biomass power generation system, and a waste-to-energy generation system. In a solar power generation facility, the amount of power generation fluctuates due to the influence of weather conditions (sun radiation, temperature, snowfall, etc.). In a wind power generation facility, the amount of power generation fluctuates due to the influence of wind speed. In biomass power generation and waste-to-energy generation, the properties of the raw materials, biomass and waste (waste, sludge, etc.), are generally unstable, and further, the output is unstable due to temporary inclusion of materials unsuitable for incineration. Therefore, the above various power generation methods are methods to which the technique described in the present disclosure can be effectively applied, similar to solar power generation.

[0037] The methanation device 22 is an example of a load device. The methanation device 22 is a device for producing synthetic methane, and produces synthetic methane by reacting carbon dioxide with hydrogen. The methanation device 22 consumes at least one of the generated power of the solar power generation facility 21 and the discharged power of the power storage system 23 that can be charged with the generated power of the solar power generation facility 21 during operation. The methanation device 22 of this embodiment requires a preparation time from the start of preparation for operation until the start of operation when power consumption becomes possible. Although the methanation reaction using a catalyst is an exothermic reaction, it is necessary to raise the temperature to a certain temperature (250°C to 450°C) in order to start the reaction, so it is difficult to instantaneously start methane production from a stopped state of the device (room temperature and normal pressure). Therefore, the methanation device 22 needs to be heated before starting production. The time required for this temperature increase varies depending on the heating method (electric heater type, steam heating type), the size of the device, and the device temperature at the start of the temperature increase, but requires, for example, 15 minutes to 5 hours. The preparation time for the methanation device 22 may be 5 minutes or more.

[0038] The load devices in the microgrid 2 are not limited to the methanation device 22 and may be other load devices. The load devices applied to the microgrid 2 in this embodiment are devices that require a preparation time from the start of operation preparation until the start of operation when power consumption is possible.

[0039] The power storage system 23 is an example of an energy storage device. The power storage system 23 stores the power generated by the solar power generation facility 21 and supplies the power to the methanation device 22. The power storage system 23 includes a storage battery.

[0040] The power storage system 23 of this embodiment charges surplus power generated by photovoltaic power generation during the day and discharges it at night to supply power to consumers (not shown). Such a method of using the power storage system is called power peak shift or energy shift, and is widely practiced in factories, public facilities, buildings, etc. that have introduced storage batteries, with the aim of reducing the amount of purchased power. The charge and discharge command may be generated within the power storage system 23 or may be generated by the EMS 3.

[0041] The storage battery is a general term for devices that have the function of storing and supplying electric power. For example, the storage battery may be a general type storage battery such as a lead acid battery, a lithium ion secondary battery, an all-solid-state battery, a nickel-metal hydride storage battery, a nickel-cadmium storage battery, a nickel-iron storage battery, a nickel-zinc storage battery, a silver oxide-zinc storage battery, or a cobalt titanium lithium secondary battery. The storage battery may be a liquid circulation type storage battery such as a redox flow battery, a zinc-chlorine battery, or a zinc-bromine battery. The storage battery may be a mechanical charge type storage battery such as an aluminum-air battery, an air-zinc battery, or an air-iron battery. The storage battery may be a high-temperature operating type storage battery such as a sodium-sulfur battery, a lithium-iron sulfide battery, an electron trap type, or a semiconductor secondary battery. In addition, the storage battery (secondary battery) is a general term for devices that can charge and / or discharge electric power. The storage battery PCS that converts the direct current of the power storage system 23 to alternating current and a monitoring device for the remaining battery charge are also included in the power storage system 23. Batteries may be replaced with energy storage devices that perform similar functions, such as capacitors, flywheels, compressed air energy storage (CAES) plants, pumped hydroelectric plants, and thermal energy storage plants that temporarily store electricity as heat and then reconvert the heat into electricity when needed.

[0042] The connection unit 24 has a function of distributing power to each unit including the external power system 90. The connection unit 24 is, for example, a distribution board. The connection unit 24 distributes power to each unit based on, for example, an instruction from the EMS 3. The received power measurement unit 25 and the transmitted power measurement unit 26 measure the received power and transmitted power to and from the external power system 90, respectively.

[0043] Fig. 2 is a block diagram showing the functional configuration of the EMS 3 according to this embodiment. The EMS 3 functions as an operation support device that determines whether to start preparation for operation of the methanation device 22, which is a load device. The EMS 3 is also a device that monitors the transfer and exchange of power in the microgrid 2. Of the various functions of the EMS 3, Fig. 2 shows only functional units related to the functions of the operation support device in this disclosure. The EMS 3 has functions other than those shown in Fig. 2, such as a trend data storage function and a demand monitoring function, but these functional units are omitted.

[0044] 2, the EMS 3 includes an acquisition unit 31, a determination unit 32, and an output unit 33. The EMS 3 may further include a history information DB 41.

[0045] Next, the hardware configuration of the EMS 3 will be described with reference to Fig. 3. Fig. 3 is a diagram showing an example of the hardware configuration of the EMS 3. The EMS 3 includes one or more computers 100. The computer 100 has a processor 101, a main memory unit 102, an auxiliary memory unit 103, a communication control unit 104, an input device 105, and an output device 106. The EMS 3 is configured by one or more computers 100 configured by this hardware and software such as programs.

[0046] When the EMS 3 is composed of multiple computers 100, these computers 100 may be connected locally or via a communication network such as the Internet or an intranet. This connection logically constitutes one EMS 3.

[0047] The processor 101 executes an operating system and application programs. The main memory 102 is composed of a ROM (Read Only Memory) and a RAM (Random Access Memory). The auxiliary memory 103 is a storage medium composed of a hard disk and a flash memory. The auxiliary memory 103 generally stores a larger amount of data than the main memory 102. The communication control unit 104 is composed of a network card or a wireless communication module. At least a part of the communication function with other devices in the EMS 3 may be realized by the communication control unit 104. The input device 105 is composed of a keyboard, a mouse, a touch panel, a microphone for voice input, etc. The output device 106 is composed of a display, a printer, etc.

[0048] The auxiliary storage unit 103 stores in advance a program 110 and data necessary for processing. The program 110 causes the computer 100 to execute each functional element of the EMS 3. Each functional unit 31-33 of the EMS 3 is realized by loading the program 110 (driving assistance program) into the processor 101 and executing the program. Note that, although in this embodiment, each functional unit 31-33 is configured in the EMS 3, it may be configured in a distributed manner in a plurality of computers.

[0049] By the program 110, for example, processing related to a driving assistance method by the EMS3 as a driving assistance device is executed in the computer 100. For example, the program 110 is read by the processor 101 or the main memory unit 102, and operates at least one of the processor 101, the main memory unit 102, the auxiliary memory unit 103, the communication control unit 104, the input device 105, and the output device 106. For example, the program 110 reads and writes data in the main memory unit 102 and the auxiliary memory unit 103.

[0050] The program 110 may be provided in a form recorded on a tangible storage medium such as a CD-ROM, a DVD-ROM, a semiconductor memory, etc. The program 110 may be provided as a data signal via a communication network.

[0051] Referring again to Fig. 2, the functional units of the EMS 3 will be described. The acquisition unit 31 periodically acquires an SoC indicating the amount of energy stored in the storage battery from the power storage system 23. The acquisition unit 31 accumulates the chronological SoC in the power storage system 23 as history information in the history information DB 41. Note that, although the amount of energy stored in the power storage system is represented by the SoC in this embodiment, it may be represented by the amount of power (unit: KWh).

[0052] The determination unit 32 determines whether to start preparation for operation of the load device when history information indicating the history of the energy storage amount in the energy storage device corresponds to a predetermined state. In this embodiment, the determination unit 32 determines whether to start preparation for operation of the methanation device 22 when history information indicating the history of the SoC in the power storage system 23 corresponds to a predetermined state. The determination unit 32 performs the determination process by referring to the history information accumulated in the history information DB 41.

[0053] The historical information to be determined includes at least a first value representing the amount of stored energy at a first point in time before the present, and a second value representing the amount of stored energy at least at one point in time before the first point in time.

[0054] Specifically, the first point in time may be the current point in time when the determination is made, or may be a point in time before the current point in time. That is, the history information may include a value of the SoC at the first point in time, which is the current point in time or a point in time before the current point in time, and a value of the SoC at least one point in time in the past before the first point in time.

[0055] In this way, not only the value of the energy storage amount at a certain point in time but also the value of the energy storage amount before that point in time is used to determine whether preparation for operation has started, so that the tendency of transition of the energy storage amount is taken into consideration, and therefore it is possible to accurately determine whether preparation for operation has started.

[0056] The determination unit 32 may make a start determination when the history information corresponds to a predetermined state in which surplus power is predicted to occur in a power grid of a certain range that includes at least the power generation device and the energy storage device.

[0057] Specifically, in this embodiment, the judgment unit 32 may make a start judgment when the historical information corresponds to a predetermined state in which surplus power is predicted to be generated in the microgrid 2 including the solar power generation equipment 21 and the storage system 23.

[0058] In this way, when the generation of surplus power is predicted, a determination is made in advance as to whether or not the load device should start preparing for operation, thereby preventing the generation of surplus power.

[0059] The determination unit 32 may make a start determination when the history information corresponds to a predetermined state in which the amount of energy stored in the energy storage device is predicted to exceed a given first threshold. Specifically, in this embodiment, the determination unit 32 may make a start determination when the history information corresponds to a predetermined state in which the SoC of the power storage system 23 is predicted to exceed an upper operational limit.

[0060] In this manner, since the determination is made based on whether or not it is predicted that the amount of stored energy will exceed the first threshold, the occurrence of surplus power can be predicted with high accuracy.

[0061] The output unit 33 outputs the information indicating the start determination in a predetermined form. As an example, the output unit 33 may transmit the information indicating the start determination to the load device as operation preparation start information for causing the load device to start preparation for operation.

[0062] Specifically, in this embodiment, when the determination unit 32 determines to start, the output unit 33 transmits operation preparation start information to the methanation device 22. The methanation device 22 starts operation preparation upon receiving the operation preparation start information. The operation preparation is, for example, raising the temperature of the device. This allows the methanation device 22 to start operation involving consumption of power generated by the solar power generation facility 21 or power discharged from the power storage system 23 when a certain time has elapsed after the start of operation preparation.

[0063] Furthermore, the output unit 33 may output information indicating the start determination in at least one of the modes of a display and a sound that can be recognized by a person. Specifically, in this embodiment, the output unit 33 may prompt the operator of the methanation device 22 to start the operation to prepare for operation of the methanation device 22 by a monitor display that is visible to the operator of the methanation device 22, lighting of a lamp, a notification by e-mail, etc., an alarm sound, etc. In this way, since information indicating the start determination is output in the form of a display, a sound, etc., it is possible to prompt the operator of the load device to make a decision to start the load device.

[0064] The determination process by the determination unit 32 according to the first embodiment will be described with reference to Fig. 4 to Fig. 6. In the first embodiment, the determination unit 32 performs a start determination when the amount of stored energy at a first time point is equal to or greater than a given second threshold, or when the amount of stored energy at the first time point is equal to or greater than a given third threshold and an increase in the amount of stored energy at the first time point compared to a second time point that is a given time going back from the first time point is equal to or greater than a predetermined degree.

[0065] Fig. 4 is a flowchart showing the determination process of the driving support method according to the first embodiment. The determination process shown in Fig. 4 may be performed at a predetermined time (for example, 10:00) in one day. For example, in solar power generation, which is one of renewable energies, the amount of generated power starts to increase from sunrise, peaks during the day, and decreases toward sunset. In consideration of such changes in SoC accompanying increases and decreases in the amount of generated power, the determination process for starting operation is performed at a predetermined time before the peak time so that the SoC in the power storage system 23 does not exceed the operation upper limit at the peak time of the amount of generated power.

[0066] In step S1, the determination unit 32 acquires information indicating the operating state of the methanation device 22 through communication with the methanation device 22, and determines whether the methanation device 22 has been started. If it is determined that the methanation device 22 has been started, there is no need to determine whether preparations for operation of the methanation device have begun, and the process proceeds to step S4. If it is not determined that the methanation device 22 has been started, the process proceeds to step S2.

[0067] In step S2, the determination unit 32 determines whether or not the SoC of the power storage system 23 at 10:00 (current time, an example of a "first time point") when this example of the determination process is performed is 70% or more (an example of a second threshold value). That is, it is determined whether or not the SoC is already in a relatively high state at a time point before the power generation in the microgrid 2 reaches its peak. Note that the second threshold value used in this determination is not limited to 70%. If it is determined that the SoC is 70% or more, the process proceeds to step S5. On the other hand, if it is not determined that the SoC is 70% or more, the process proceeds to step S3.

[0068] In step S3, the determination unit 32 determines whether the SoC at 10:00 (first time point) is 35% (an example of a third threshold value) or more and whether the SoC at 10:00 has increased by 5% (a predetermined degree) or more compared to 9:00 (second time point). That is, it is determined whether the SoC is higher than a certain degree and is showing an increasing tendency of at least a certain degree before the power generation in the microgrid 2 reaches its peak. Note that the third threshold value, the second time point, and the degree of increase used in this determination are not limited to 35%, 9:00, and 5%, respectively.

[0069] If it is determined that the SoC at 10:00 is 35% or more and is increased by 5% or more compared to the SoC at 9:00, the process proceeds to step S5. On the other hand, if it is not determined that the SoC at 10:00 is 35% or more and is increased by 5% or more compared to the SoC at 9:00, the process proceeds to step S5.

[0070] 5 and 6 are diagrams showing an example of SoC transition. At 10:00, the solid line portion of the SoC transition shown in Fig. 5 and Fig. 6 is stored as history information in the history information DB 41. In the example shown in Fig. 5, the SoC transition shown by the history information at 10:00 is about 50% at 10:00, which is an increase of 5% or more compared to the value of about 40% at 9:00, so the determination unit 32 determines to advance the process to step S5.

[0071] In the example shown in FIG. 6, the transition of the SoC indicated by the history information at 10:00 is about 30% at 10:00, so the determination unit 32 determines to advance the process to step S4.

[0072] In step S4, the determination unit 32 does not make a start determination. On the other hand, in step S5, the determination unit 32 makes a start determination.

[0073] Thus, in the first embodiment, the start determination is made when the SoC at the first time point is equal to or greater than the second threshold, or when the SoC at the first time point is equal to or greater than the third threshold and the increase rate of the SoC during a predetermined period leading up to the first time point is equal to or greater than a predetermined level. That is, since not only the value of the energy storage amount at a certain point in time but also the tendency of the increase in the energy storage amount is taken into consideration, it is possible to appropriately determine whether or not the state is one in which surplus power is predicted to occur.

[0074] The judgment process by the judgment unit 32 according to the second embodiment will be described with reference to Fig. 7 to Fig. 11. Fig. 7 is a functional block diagram of the EMS according to the second embodiment. Compared to the EMS 3 shown in Fig. 2, the EMS 3A includes a judgment unit 32A instead of the judgment unit 32, and further includes a judgment pattern DB 42.

[0075] In the second embodiment, the determination unit 32A performs a start determination when a transition of the energy storage amount from a second time point, which is a time point going back a given time from the first time point, to the first time point corresponds to at least one surplus power generation pattern preset as a transition pattern of the energy storage amount in which the energy storage amount exceeds a first threshold. The determination pattern DB 42 is a database that stores the transition patterns of the energy storage amount in advance.

[0076] 8 is a diagram illustrating an outline of the determination process of the second embodiment. The determination pattern DB 42 prestores a transition pattern tp that defines a transition of an SoC from a starting point time (an example of a second time point) to a determination time (an example of a first time point, which may be the current time, for example). As indicated by the reference symbol pd1, the determination unit 32A performs a matching determination between the SoC transition from the starting point time to the current time, which is indicated in the history information, and the transition pattern tp. Then, as indicated by the reference symbol dt1, the determination unit 32A determines, based on the result of the matching determination, whether or not surplus power will be generated in the microgrid 2 after the preparation time of the methanation device 22 has elapsed from the first time point.

[0077] Fig. 9 is a diagram showing an example of generation of a transition pattern tp. The SoC transition curve sta shown in Fig. 9(a) shows the transition results of the SoC on Z0 of Y month of X year. In the transition curve sta, the SoC does not exceed the upper operational limit even at the peak. Therefore, the portion of the transition curve sta from the starting time to the judgment time is stored in advance in the judgment pattern DB 42 as an surplus power non-generation pattern tpa, which is a transition pattern in which surplus power is not generated, in association with a label lba indicating that surplus power is not generated.

[0078] 9(b) shows the transition of the SoC on Z1 of Y month of X year. In the transition curve stb, the SoC exceeds the upper operational limit at the peak. Therefore, the portion of the transition curve stb from the starting time to the judgment time is stored in advance in the judgment pattern DB 42 as an surplus power generation pattern tpb, which is a transition pattern in which surplus power is not generated, in association with a label lbb indicating the generation of surplus power.

[0079] The time from the determination time to the time when the SoC on the transition curve stb reaches the upper operational limit must be longer than the preparation time of the methanation device 22 to which the EMS 3A of this embodiment is applied.

[0080] Fig. 10 is a flowchart showing the determination process of the driving support method according to the second embodiment. The determination process shown in Fig. 10 may be performed at a predetermined time in a day, or may be performed at any time at a given time interval.

[0081] In step S11, the judgment unit 32A acquires information indicating the operating state of the methanation device 22 through communication with the methanation device 22, and judges whether the methanation device 22 has been started. If it is judged that the methanation device 22 has been started, there is no need to judge whether the methanation device has started preparing for operation, and the process proceeds to step S14. If it is not judged that the methanation device 22 has been started, the process proceeds to step S12.

[0082] In step S12, the determination unit 32A performs a matching determination between the transition of the SoC from the start time to the determination time shown in the history information and the transition pattern tp. Specifically, the determination unit 32A may perform matching using a K-nearest neighbor method in which the difference between each value of the SoC from the start time to the determination time shown in the history information and the value at each corresponding time in the transition pattern tp is set as the Euclidean distance.

[0083] As described above, the judgment pattern DB42 stores a plurality of transition patterns tp that are either a non-surplus power generation pattern tpa associated with a label lba indicating no surplus power generation, or an surplus power generation pattern tpb associated with a label lbb indicating surplus power generation, so the judgment unit 32A extracts a plurality of transition patterns tp that are similar to the transitions indicated in the history information by pattern matching, and tallies the number of labels lba and lbb associated with the extracted transition patterns tp.

[0084] In step S13, the determination unit 32A determines whether or not surplus power will occur. Specifically, when the labels lbb with surplus power occurring are greater than the labels lba with no surplus power occurring among the labels counted in step S12, the determination unit 32A may determine that surplus power will occur. If it is not determined that surplus power will occur, the process proceeds to step S14. On the other hand, if it is determined that surplus power will occur, the process proceeds to step S15.

[0085] In step S14, the determination unit 32A does not make a start determination. On the other hand, in step S15, the determination unit 32A makes a start determination.

[0086] The SoC performance values ​​for the transition pattern tp generated in advance and stored in the judgment pattern DB 42 do not need to be data of the SoC from the start time to the end time, and may be, for example, the SoC performance values ​​from the start time to a predetermined judgment time. The transition pattern tp used for the judgment does not need to include all the SoC performance values ​​from the start time to the judgment time consecutively, and may include, for example, the SoC performance values ​​at three points of time, the start time, the judgment time, and an intermediate time between them. The transition pattern tp used for the judgment may be composed of two points of performance values, for example, 9:00 and 10:00, as in the first embodiment. The transition pattern tp used for the judgment does not need to be composed of the SoC performance values, and may be composed of values ​​obtained by processing the SoC performance values, or may be composed of the difference value of the SoC performance values ​​between the judgment time and the starting time and the SoC performance value at the judgment time. stomach.

[0087] Next, automatic labeling of the transition pattern tp will be described with reference to Fig. 11. The performance information including the performance values ​​of the SoC transition for generating the transition pattern tp includes, for example, the performance values ​​from a predetermined start time t1 to an end time t2 in the operation time of the photovoltaic power generation facility 21, the performance values ​​from the start time t1 to the determination time t3 constitute the transition pattern tp and are used for pattern matching, and the performance values ​​after the determination time t3 are used to determine whether the transition pattern tp corresponds to a surplus power generation pattern or not.

[0088] A preparation time T1 (for example, 2 hours) for the load device such as the methanation device 22 is set in advance, and the time from time t4, when the preparation time T1 has elapsed since the judgment time t3, to the end time t2 is the operable time T2 when the load device starts preparation for operation at the judgment time t3. Therefore, in automatic labeling of the transition pattern tp, if the total time during which the SoC actual value is equal to or greater than (SoC operation upper limit value-δ) within the operable time T2 is equal to or greater than a given time (for example, 3 hours), the transition pattern tp may be associated with a label indicating surplus power generation, and if the total time is less than the given time, a label indicating no surplus power generation may be associated (δ is a setting parameter such as, for example, 1%). By labeling in this way, it is possible to prevent wasteful operation such as immediately suspending the operation of the load device due to little generation of surplus power after the load device starts preparation for operation and starts operation. Note that labeling of the transition pattern may be performed automatically by a program or by a person such as a microgrid operator.

[0089] The determination process by the determination unit according to the third embodiment will be described with reference to Fig. 12 to Fig. 15. Fig. 12 is a functional block diagram of an EMS according to the third embodiment. Compared to the EMS 3 shown in Fig. 2, an EMS 3B includes a determination unit 32B instead of the determination unit 32, and further includes an autoregressive model storage unit 43.

[0090] In the third embodiment, the determination unit 32B uses a predetermined prediction model constructed based on performance information regarding the transition of the energy storage amount in the energy storage device to calculate a predicted value of the energy storage amount after the current time in a time series based on history information, and performs a start determination when the predicted value within a given prediction target period after the current time exceeds a first threshold. The prediction model may be a predetermined autoregressive model, for example. In this embodiment, the determination unit 32B performs the start determination using the autoregressive model. The autoregressive model storage unit 43 is a storage means that stores in advance the learned and constructed autoregressive model.

[0091] 13 is a diagram illustrating an outline of the determination process of the third embodiment. In the third embodiment, as indicated by the symbol pd2, the determination unit 32B predicts the transition of the SoC value of the storage battery of the power storage system 23 in the future prediction target period by time series analysis using the actual value of the SoC from a certain time ago (e.g., a starting point time, 5 hours ago) to a determination time (e.g., the current time). In the third embodiment, an AR model (autoregressive model) is used as an example.

[0092] Furthermore, if the prediction period is shorter than the preparation time of the operating device, it will be impossible to complete preparation for operation of the load device before surplus power is generated, so the prediction period must be at least longer than the preparation time of the load device.

[0093] Then, as indicated by the reference symbol dt2, the determination unit 32B determines that surplus power will occur when the predicted value of the SoC in the prediction period exceeds a first threshold value (for example, the operational upper limit value of the SoC).

[0094] 14 is a diagram for explaining calculation of a predicted value of the energy storage amount by an autoregressive model. The AR model is generated based on performance information regarding the transition of the SoC of the storage battery. The generation of the AR model md will be described below.

[0095] Time series data consisting of actual values ​​of SoC over time {y i}(i=1, ,N), the AR model md is given the time series data y i is expressed by the following equation.

number

[0096] where m is the order of the autoregression, a i is the coefficient, v n has mean 0 and variance σ 2 is a normally distributed white noise.

[0097] In this embodiment, the performance value {y i}(i=1, ,N), the order m of the AR model and the coefficient a are chosen so that the AIC (Akaike Information Criteria) is minimized. i (i=1,2,...,m) is determined. AIC is a type of statistic, and the smaller the AIC, the better the balance between the model's complexity and its fit to the data. The AIC of an AR model md of order m is expressed by the following formula: AIC=-2(maximum log-likelihood)+2(m+1) The trained AR model md is stored in, for example, the autoregressive model storage unit 43.

[0098] In the prediction stage, the determination unit 32B predicts the SoC for the prediction target period using the obtained AR model md. n is usually treated as zero. For example, the determination unit 32B determines the predicted value of the next time

number

number

number

number

[0099] The judgment unit 32B repeatedly calculates the predicted value in a time series by using the predicted value of the previous time. Note that, in order to prevent the predicted value calculated by the AR model md from being too large or too small, the final predicted value may be limited within a range of maximum and minimum values ​​designated by the user.

[0100] When the predicted value of the SoC in the prediction target period exceeds a first threshold, the determination unit 32B determines that surplus power will be generated and performs a start determination. Note that the determination unit 32B may also obtain the time when the predicted value of the SoC is predicted to exceed the threshold using the AR model, and the output unit 33 may output the obtained time to present it to the user.

[0101] The determination unit 32B may obtain the start time and end time of the period during which surplus power occurs due to the predicted value of the SoC exceeding the threshold value, using the AR model md. The output unit 33 may output the start time and end time of the surplus power occurrence to present to the user.

[0102] Fig. 15 is a flowchart showing the determination process of the driving support method according to the third embodiment. The determination process shown in Fig. 15 may be performed at a predetermined time in a day, or may be performed at any time at a given time interval.

[0103] In step S21, the determination unit 32B acquires information indicating the operating state of the methanation device 22 through communication with the methanation device 22, and determines whether the methanation device 22 has been started. If it is determined that the methanation device 22 has been started, there is no need to determine whether preparation for operation of the methanation device has begun, and the process proceeds to step S24. If it is not determined that the methanation device 22 has been started, the process proceeds to step S22.

[0104] In step S22, the determination unit 32B calculates a predicted value of SoC in the prediction target period using the autoregressive model md. As described above, the prediction target period is set to a time longer than the preparation time of the methanation device 22.

[0105] In step S23, the determination unit 32B determines whether or not surplus power will occur. That is, when the predicted value exceeds a given first threshold (e.g., an upper operational limit value of the SoC), the determination unit 32B determines that surplus power will occur. If it is not determined that surplus power will occur, the process proceeds to step S24. On the other hand, if it is determined that surplus power will occur, the process proceeds to step S25.

[0106] In step S24, the determination unit 32B does not make a start determination. On the other hand, in step S25, the determination unit 32B makes a start determination.

[0107] In this way, the autoregressive model md for predicting the transition of SoC is used to predict the transition of SoC after the judgment time (for example, the current time), and when the predicted value of SoC during the prediction target period exceeds a predetermined threshold, it is determined that the operation preparation should be started. This makes it possible to easily predict the generation of surplus power and determine the start of the operation preparation.

[0108] According to the EMS 3, 3A, 3B (driving assistance device), driving assistance method, and driving assistance program of the present embodiment described above, when the SoC history information corresponds to a predetermined state, a determination is made as to whether to start preparation for operation of the methanation device 22 (load device), which requires preparation time before it can reach an operating state in which it can consume power. Therefore, by performing the process of determining whether to start preparation for operation in advance at an appropriate timing, it is possible to put the load device into an operating state in which it can consume power at a desired timing. In addition, the driving assistance device of this embodiment does not require a predicted value of the power generation of renewable energy such as solar power generation, or a predicted value of the power demand, for the judgment process of the start judgment. If the predicted values ​​of the power generation and the power demand are used, if the prediction is incorrect, the operation plan of the power generation equipment and the load device will become inappropriate. The driving assistance device of this embodiment prevents the operation plan from becoming inappropriate due to the accuracy of these predicted values. Furthermore, many costs are incurred in order to use the predicted values ​​of the power generation and power demand. For example, weather forecast data including the amount of solar radiation is required to predict the power generation of photovoltaic power generation, and the provision of weather forecast data is often a paid service. In addition, the prediction of the power generation and power demand requires initial costs and maintenance costs for computational resources and communication equipment. These costs are not incurred in the driving assistance device of this embodiment.

[0109] The present invention has been described in detail above based on the embodiments. However, the present invention is not limited to the above embodiments. The present invention can be modified in various ways without departing from the gist of the present invention.

[0110] In the second and third embodiments, the judgment units 32A and 32B may perform the judgment process at a given time interval Δt. In this case, if the time when the surplus power is predicted to occur is after the time (load device operation preparation time + Δt) has elapsed from the current time, the judgment units 32A and 32B may not perform the start judgment. In this case, since the time when the surplus power is predicted to occur is far in the future from the current time, the prediction accuracy may be low, and therefore the operation start judgment based on the low-accuracy prediction can be prevented. Even if the start judgment at this point is postponed, the start judgment is performed based on the next judgment performed after the time Δt has elapsed from the current time, so that the operation preparation of the load device can be completed by the time when the surplus power occurs.

[0111] In addition, in this embodiment, the methanation device 22 is illustrated as an example of the load device, but the load device is not limited to the methanation device 22. For example, the load device may be a hydrogen production system that produces hydrogen by water electrolysis. In general, the higher the temperature, the lower the theoretical electrolysis voltage, and therefore the higher the efficiency of water electrolysis. Some hydrogen production systems, such as steam water electrolysis that electrolyzes high-temperature steam, require time for preparation for operation. Furthermore, the load device is not limited to hydrogen and methane, and may be a production device for olefins (ethylene, propylene) that are raw materials for resins and plastics. The load device may also be an electric boiler. The load device may also be an electric furnace that melts scrap iron, or an electrolytic / electric refining device that produces crude iron from iron ore. Furthermore, the load device may be other chemical process devices, plastic processing devices such as rolling, food processing devices, distillation devices, and heat treatment furnaces such as surface heat treatment. These devices that require thermal energy are often devices that require preparation time for operation, such as heating and pressure increase. If a heating pipe is required to prevent water hammer from occurring in piping for steam, the time for this may also be included in the preparation time. If the loading equipment requires purging to replace the toxic gas in the tank with nitrogen or air before starting operation, the time for this operation may be included in the preparation time. If the loading equipment requires water supply before starting up, the time for water supply may be included in the preparation time. If the loading equipment requires on-site monitoring at the start-up for safety or legal reasons, the travel time of the workers may be included in the preparation time. Work such as start-up inspection (checking the residual pressure, opening and closing the cocks, etc., visually checking that there are no water leaks, and checking the water level gauge) and recording performed before starting up the equipment may also be included in the preparation time. The time for cooling down and lowering the pressure of the equipment may also be included in the preparation time. The time required to prepare the operation of auxiliary equipment, such as the storage equipment for the product manufactured by the loading equipment, rather than the loading equipment itself, may also be included in the preparation time.

[0112] In the above embodiment, the preparation time of the load device is set by the user, but it may be set by other means. For example, the preparation time may be automatically calculated by the EMS using information such as the temperature of the load device before the start of operation preparation and the outside air temperature, and the time it takes to reach a desired temperature using a formula, a table, a function, a statistical model created in advance, or the like.

[0113] In the above embodiment, the microgrid 2 includes one power storage system 23 and a storage battery, but there may be a plurality of power storage systems 23. In this case, the total SoC may be calculated by regarding the plurality of power storage systems 23 as one storage battery. Furthermore, the total SoC may be calculated by excluding a storage battery that is out of order or out of operation among the plurality of power storage systems 23 and storage batteries. When there are the same number of load devices and power storage systems 23, one load device may be assigned to one power storage system 23.

[0114] In the present embodiment, as shown in FIG. 1, all of the photovoltaic power generation equipment 21 (power generation facility using renewable energy), the storage system 23, and the methanation device 22 (load device) are present in one microgrid 2, but the present embodiment is not limited to this. FIG. 16 is a schematic diagram showing another example of a power supply system. The system to which the driving support devices 3, 3A, and 3B of the present embodiment are applied may be a power supply system 1B in which each facility has a virtual connection via a power system owned by a general power transmission and distribution company, as shown in FIG. 16. That is, the driving support devices 3, 3A, and 3B may be applied by regarding a group of devices connected in the manner shown in FIG. 16 as a virtual microgrid. The power supply system 1B includes a photovoltaic power generation system 21B owned by a power generation company A, a process device 22B (an example of a load device) owned by a company B, and a storage system 23B owned by a company C. The photovoltaic power generation system 21B, the process device 22B, and the storage system 23B are connected via a power system 9B. In other words, each system may be owned by a different company. In this case, the contract between the companies may be a transaction via the electricity market or a bilateral transaction.

[0115] Renewable energy is not limited to photovoltaic power generation. In the case of photovoltaic power generation, the history information and performance information of the SoC can be information on the time from before sunrise (start time) to after sunset (end time) in one day. In contrast, in the case of wind power generation, the unit is not limited to one day as in photovoltaic power generation. Based on performance information consisting of information indicating continuous transitions of the SoC, for example, for a set of SoC performance values ​​from a start time to an end time, such as a set in which the interval between the start time and the end time is a predetermined time (for example, 5 hours), by setting a predetermined time (for example, 1 hour) before the judgment time as the start time, it is possible to predict the generation of surplus power within a predetermined time (4 hours) after the judgment time. In this way, the example of the transition pattern shown in the second embodiment can be applied not only to photovoltaic power generation but also to wind power generation and the like.

[0116] In the K-nearest neighbor method in the second embodiment, the similarity between the transition of the SoC shown in the history information and the transition pattern is defined by the Euclidean distance of the difference between them, but the similarity may be calculated using other information. For example, a flag may be associated with each transition pattern, which may be set to 1 if the pattern is based on the performance value on weekdays (working days) and 0 if the pattern is based on the performance value on holidays and public holidays (non-working days), and the difference between the flag of the transition pattern and the attribute flag of the history information to be judged (a flag indicating whether the judgment time is a weekday or not) may be included in the calculation of the Euclidean distance. In addition to the Euclidean distance, a distance calculation method such as the L1 norm may be applied.

[0117] In the second embodiment, the K-nearest neighbors algorithm is used as an example, but other algorithms may be used, such as linear discriminant analysis, logistic regression, naive Bayes classifier, decision tree, random forest, neural network, support vector machine, or other statistical methods.

[0118] In the third embodiment, prediction is performed using an AR model, but the model applied to prediction is not limited to the AR model. Nearby data may be extracted using the K-nearest neighbor method used in the second embodiment, and a future predicted value may be calculated using the average and median of the nearby data (judgment time to end time). Furthermore, other mathematical models (machine learning models, deep learning models) such as a Moving Average (MA) model, an Auto Regressive Moving Average (ARMA) model, an Auto Regressive Integrated Moving Average (ARIMA) model, a Holt-Winters model, a Gradient Boosting Decision Tree (GBDT) model, a Long short-term memory (LSTM) model, or a gated recurrent unit (GRU) model may be used. In addition, instead of the estimation / prediction method using the minimum AIC model, another method, for example, an estimation / prediction method using a Kalman filter may be used.

[0119] The location where the computer constituting the EMS is provided is not limited to within the microgrid 2 or near the microgrid 2, but may be remote or in the so-called cloud.

[0120] In this embodiment, the microgrid 2 is assumed to be a power network covering a certain range including a power generation device and an energy storage device, but the form is not limited to a single factory or business establishment, and may be, for example, an industrial complex that bundles together multiple factories.

[0121] In this embodiment, even if the load device is operated to prepare for operation, the impact on the storage capacity of the power storage system is minor, that is, the rated capacity of the load device is small relative to the capacity of the storage battery. However, when the load device is operated to prepare for operation and has a non-negligible impact on the storage capacity of the power storage system, the method of assigning the label of surplus power generation or non-generation of surplus power associated with the transition pattern in the second embodiment can be devised. Specifically, two thresholds are set for predicting the generation of surplus power from the judgment time to the end point time, when the load device is operated and when it is not operated. That is, when the load device is not operated, the threshold is set to the operation upper limit value of the SoC, and when the load device is operated, the threshold is set to a lower value (for example, the SoC operation upper limit value -10%). By setting in this way, it is possible to perform labeling indicating the presence or absence of generation of surplus power, taking into account the impact of the operation of the load device itself.

[0122] [Note] The present invention relates to a technology for effectively utilizing surplus electricity from renewable energy sources to operate production facilities. Therefore, the present invention contributes to the achievement of the following goals of the Sustainable Development Goals (SDGs) led by the United Nations: Goal 7: Ensure access to affordable, reliable, sustainable and modern energy for all Goal 9: Build resilient infrastructure, promote inclusive and sustainable industrialization, and foster innovation.

[0123] The gist of the present invention is as follows. [1] A driving assistance device that determines whether a load device is ready to operate, The load device is The device requires preparation time from the start of preparation for operation until the start of operation. At least one of the power generated by a power generation device using renewable energy and the discharged power of an energy storage device capable of storing the power generated by the power generation device can be consumed during operation, The driving assistance device includes: a determination unit that determines whether preparation for operation of the load device has started when history information representing a history of an energy storage amount in the energy storage device corresponds to a predetermined state; A driving assistance device comprising: [2] The history information includes a first value representing the energy storage amount at a first time point that is a time point before the present, and a second value representing the energy storage amount at at least one time point before the first time point. [1] A driving assistance device according to the present invention. [3] the determination unit makes the start determination when the history information corresponds to a predetermined state in which surplus power is predicted to be generated in a power grid of a certain range including at least the power generation device and the energy storage device. [2] A driving assistance device according to the present invention. [4] The determination unit makes the start determination when the history information corresponds to a predetermined state in which an amount of energy stored in the energy storage device is predicted to exceed a given first threshold value. [3] A driving assistance device according to the present invention. [5] The determination unit is The start determination is made when the amount of stored energy at the first time point is equal to or greater than a given second threshold, or when the amount of stored energy at the first time point is equal to or greater than a given third threshold and an increase in the amount of stored energy at the first time point compared to a second time point that is a given time back from the first time point is equal to or greater than a predetermined degree. [4] A driving assistance device according to the present invention. [6] the determination unit performs the start determination when a transition of the energy storage amount during a time period from a second time point, which is a time point going back a given time from the first time point, to the first time point corresponds to at least one surplus power generation pattern that is preset as a transition pattern of the energy storage amount in which the energy storage amount exceeds the first threshold value; [4] A driving assistance device according to the present invention. [7] The determination unit calculates a predicted value of the energy storage amount after the current time in a time series based on the history information using a predetermined prediction model constructed based on actual information regarding transition of the energy storage amount in the energy storage device, and performs the start determination when the predicted value within a given prediction target period after the current time exceeds the first threshold value. [4] A driving assistance device according to the present invention. [8] The determination unit performs the determination when the operation of the load device has not been started. The driving support device according to any one of [1] to [7]. [9] An output unit that outputs information indicating the start determination in a predetermined manner. A driving assistance device according to any one of [1] to [8].

[10] The output unit transmits information indicating the start determination to the load device as operation preparation start information for causing the load device to start operation preparation. [9] A driving assistance device according to the present invention.

[11] The output unit outputs information indicating the start determination in at least one form of a display or a sound that can be recognized by a human. [9] A driving assistance device according to the present invention.

[12] A driving assistance method for a driving assistance device that determines whether a load device is ready to start operation, comprising: The load device is The device requires preparation time from the start of preparation for operation until the start of operation. At least one of the power generated by a power generation device using renewable energy and the discharged power of an energy storage device capable of storing the power generated by the power generation device can be consumed during operation, The driving assistance method includes: a determination step of determining whether or not preparation for operation of the load device has started when history information representing a history of an energy storage amount in the energy storage device corresponds to a predetermined state; A driving assistance program with

[13] A driving assistance program for causing a computer to function as a driving assistance device that determines whether or not a load device is ready to operate, comprising: The load device is The device requires preparation time from the start of preparation for operation until the start of operation. At least one of the power generated by a power generation device using renewable energy and the discharged power of an energy storage device capable of storing the power generated by the power generation device can be consumed during operation, The driving assistance program includes: a determination function for determining whether preparation for operation of the load device has started when history information representing a history of the amount of energy stored in the energy storage device corresponds to a predetermined state; A driving assistance program that makes this possible. [Explanation of symbols]

[0124] 1. Power supply system 2. Microgrid 3. Energy Management System (EMS) 21 Solar power generation equipment 21a Solar Panel 22 Methanation device 23 Energy Storage System 24 Connection 25 Receiving power measurement section 26 Transmission power measurement section 31 Acquisition Department 32,32A,32B Judgment section 33 Output section 41 History Information DB 42 Judgment pattern DB 43 Autoregressive model memory section 90 Power system

Claims

1. A driving assistance device that determines whether a load device is ready to operate, The load device is The device requires preparation time from the start of preparation for operation until the start of operation. At least one of the power generated by a power generation device using renewable energy and the discharged power of an energy storage device capable of storing the power generated by the power generation device can be consumed during operation, The driving assistance device includes: a determination unit that determines whether preparation for operation of the load device has started when history information representing a history of an energy storage amount in the energy storage device corresponds to a predetermined state; A driving assistance device comprising:

2. The history information includes a first value representing the amount of stored energy at a first time point that is a time point before the present, and a second value representing the amount of stored energy at least one time point before the first time point. The driving assistance device according to claim 1 .

3. the determination unit makes the start determination when the history information corresponds to a predetermined state in which surplus power is predicted to be generated in a power grid of a certain range including at least the power generation device and the energy storage device. The driving assistance device according to claim 2 .

4. The determination unit makes the start determination when the history information corresponds to a predetermined state in which an amount of energy stored in the energy storage device is predicted to exceed a given first threshold. The driving assistance device according to claim 3.

5. The determination unit is The start determination is made when the amount of stored energy at the first time point is equal to or greater than a given second threshold, or when the amount of stored energy at the first time point is equal to or greater than a given third threshold and an increase in the amount of stored energy at the first time point compared to a second time point that is a given time back from the first time point is equal to or greater than a predetermined degree. The driving assistance device according to claim 4.

6. the determination unit performs the start determination when a transition of the energy storage amount during a time period from a second time point, which is a time point going back a given time from the first time point, to the first time point corresponds to at least one surplus power generation pattern that is preset as a transition pattern of the energy storage amount in which the energy storage amount exceeds the first threshold value; The driving assistance device according to claim 4.

7. the determination unit calculates a time-series prediction value of the energy storage amount after the current time based on the history information using a predetermined prediction model constructed based on actual information regarding transition of the energy storage amount in the energy storage device, and performs the start determination when the prediction value within a given prediction target period after the current time exceeds the first threshold value; The driving assistance device according to claim 4.

8. The determination unit performs the determination when the operation of the load device has not been started. The driving assistance device according to claim 1 .

9. An output unit that outputs information indicating the start determination in a predetermined manner. The driving assistance device according to claim 1.

10. The output unit transmits information indicating the start determination to the load device as operation preparation start information for causing the load device to start operation preparation. A driving assistance device according to claim 9.

11. The output unit outputs information indicating the start determination in at least one form of a display or a sound that can be recognized by a human. A driving assistance device according to claim 9.

12. A driving assistance method for a driving assistance device that determines whether a load device is ready to start operation, comprising: The load device is The device requires preparation time from the start of preparation for operation until the start of operation. At least one of the power generated by a power generation device using renewable energy and the discharged power of an energy storage device capable of storing the power generated by the power generation device can be consumed during operation, The driving assistance method includes: a determination step of determining whether or not preparation for operation of the load device has started when history information representing a history of an energy storage amount in the energy storage device corresponds to a predetermined state; A driving assistance method comprising the steps of:

13. A driving assistance program for causing a computer to function as a driving assistance device that determines whether or not a load device is ready to operate, comprising: The load device is The device requires preparation time from the start of preparation for operation until the start of operation. At least one of the power generated by a power generation device using renewable energy and the discharged power of an energy storage device capable of storing the power generated by the power generation device can be consumed during operation, The driving assistance program includes: a determination function for determining whether preparation for operation of the load device has started when history information representing a history of the amount of energy stored in the energy storage device corresponds to a predetermined state; A driving assistance program that makes this possible.

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