Information processing method and program

Abstract

To provide an information processing method and a program capable of contributing to prevention of global warning by supporting creation of a carbon credit using an electric vehicle.SOLUTION: An information processing method processes information on a carbon credit created by reducing a greenhouse effect gas by a computer. The carbon credit is created on the basis of reduction of the greenhouse effect gas emitted by charging behavior of an electric vehicle 10, and the information processing method includes a generation step for generating candidates for charging behavior including other charging behavior having an emission amount of the greenhouse effect gas smaller than reference charging behavior and selectable by a user of the electric vehicle 10, an emission amount calculation step for calculating each of prediction values of emission amounts of the greenhouse effect gas emitted by each charging behavior, and a reduction amount calculation step for calculating a prediction value of a reduction amount of the greenhouse effect gas in each of the other charging behavior.SELECTED DRAWING: Figure 11

Description

[Technical Field]

[0001] The present invention relates to an information processing method and program for processing, by a computer, information on carbon credits created by reducing greenhouse gases. [Background technology]

[0002] In recent years, research and development into renewable energy sources that contribute to energy efficiency has been underway to ensure that more people have access to affordable, reliable, sustainable and advanced energy.

[0003] Various countries and regions operate greenhouse gas emissions trading systems as a system to encourage the reduction of greenhouse gas emissions such as carbon dioxide (hereinafter also referred to as CO2), which is one cause of global warming. For example, if a company participating in an emissions trading system reduces greenhouse gas emissions by introducing power generation facilities that use renewable energy such as solar power generation or energy-saving equipment, it can acquire carbon credits based on the amount of reduction. Carbon credits can be traded with other companies, and can be sold, for example, to other companies that have not been able to sufficiently reduce their emissions (for example, Patent Document 1). [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2003-331088 Summary of the Invention [Problem to be solved by the invention]

[0005] In conventional emissions trading systems, many companies that own buildings and factories that generally emit large amounts of greenhouse gases participate. However, ordinary households and other entities rarely participate in emissions trading systems because their greenhouse gas emissions are lower than those of businesses, and the acquisition of certification data and calculations required to obtain carbon credits are complicated.

[0006] In recent years, electric vehicles and other electrically powered vehicles equipped with large-capacity drive batteries have become widespread, and they are expected to serve as a power resource that can supply stored electricity to homes and power grids. There has been a demand for technology that can use such electric vehicles to encourage ordinary households to participate in emissions trading schemes and contribute to the prevention of global warming.

[0007] The present invention provides an information processing method and program that can support the creation of carbon credits using electric vehicles and contribute to the prevention of global warming, and ultimately contribute to energy efficiency. [Means for solving the problem]

[0008] The present invention provides An information processing method for processing information on carbon credits created by reducing greenhouse gases using a computer, comprising: The carbon credits are generated based on the reduction of greenhouse gases emitted by charging a battery mounted on an electric vehicle using an external power source, The information processing method includes: a generating step of generating candidate charging actions selectable by a user of the electric vehicle, the candidate charging action including at least one other charging action that emits less greenhouse gas than a reference charging action that is a reference charging action; an emission calculation step of calculating a predicted value of the amount of greenhouse gas emitted by each charging action; and a reduction amount calculation step of calculating a predicted value of the greenhouse gas reduction amount for each of the at least one other charging action based on the predicted value of the greenhouse gas emissions for the reference charging action and the predicted value of the greenhouse gas emissions for the other charging action.

[0009] The present invention also provides A program for processing information regarding carbon credits created by greenhouse gas reductions, The carbon credits are generated based on the reduction of greenhouse gases emitted by charging a battery mounted on an electric vehicle using an external power source, The program a generating step of generating candidate charging actions selectable by a user of the electric vehicle, the candidate charging action including at least one other charging action that emits less greenhouse gas than a reference charging action that is a reference charging action; an emission calculation step of calculating a predicted value of the amount of greenhouse gas emitted by each charging action; The computer is caused to execute a reduction amount calculation step of calculating a predicted value of the greenhouse gas reduction amount for each of the at least one other charging action based on the predicted value of the greenhouse gas emission amount for the reference charging action and the predicted value of the greenhouse gas emission amount for the other charging action.

[0010] The present invention also provides An information processing method for processing information on carbon credits created by reducing greenhouse gases using a computer, comprising: the carbon credits are created based on a reduction in the greenhouse gases emitted by charging batteries mounted on a plurality of electric vehicles using an external power source; The information processing method includes: an addition step of calculating and adding up, for each user of the plurality of electric vehicles, actual values ​​of the greenhouse gas reduction amounts calculated based on a predicted value of the greenhouse gas emission amount for a reference charging action that is a reference charging action and an actual value of the greenhouse gas emission amount when another charging action that has a lower greenhouse gas emission amount than the reference charging action is actually performed; a selling step of executing a selling process of the carbon credits created based on the sum of the actual values ​​of the greenhouse gas reduction amounts; and a distribution step of distributing a portion of the profits obtained in the selling step to each user. [Effects of the Invention]

[0011] According to the present invention, it is possible to support the creation of carbon credits using electric vehicles and contribute to the prevention of global warming. [Brief explanation of the drawings]

[0012] [Figure 1] This is a stakeholder relationship diagram summarizing the parties involved in the creation and trading of carbon credits. [Figure 2] FIG. 1 is a diagram illustrating an overview of carbon offsetting. [Figure 3] 1 is a block diagram showing the functional configuration of a system 1 including an electric vehicle 10, a terminal device 20, and a server 30. FIG. [Figure 4] FIG. 1 shows a schematic diagram of a reference charging behavior (top) and a graph showing CO 2 emissions for the reference charging behavior (bottom). [Figure 5] FIG. 1 is a diagram illustrating charging options A to C. [Figure 6] FIG. 10 is a diagram illustrating charging options D and E. [Figure 7] 10 is a bar graph showing CO2 emissions and CO2 reductions for the reference charging behavior and charging behaviors of charging options A to E. [Figure 8] 10 is an example of a screen displaying charging options A to E displayed on the terminal device 20. [Figure 9]10 is an example of a screen displayed on the terminal device 20, showing the reference charging action and the chargeable energy amounts of the charging actions in each of the charging options A to E. [Figure 10] 3 is a sequence diagram showing an example of processing carried out among the server 30, the terminal device 20, and the electric vehicle 10. FIG. [Figure 11] 10 is a control flow illustrating an example of a charging option generation process executed by the server 30. [Figure 12] 10 is a control flow diagram showing an example of a process for managing carbon credits executed by the server 30. [Figure 13] 10 is a sequence diagram showing a modified example of processing performed among the server 30, the terminal device 20, and the electric vehicle 10. FIG. DETAILED DESCRIPTION OF THE INVENTION

[0013] An embodiment of an information processing method and a program according to the present invention will be described below with reference to the accompanying drawings.

[0014] First, an example of the interrelationships among parties involved in the creation and trading of carbon credits will be described with reference to Figure 1. The parties include, for example, an electric power company, a general household, business A, a certification body, and business B.

[0015] Carbon credits are issued by a certification body as credits (emission rights) for projects to reduce greenhouse gas emissions by introducing energy-saving equipment or renewable energy equipment, etc., so that the difference between the predicted greenhouse gas emissions, etc., if the project were not implemented and the actual greenhouse gas emissions, etc., can be traded between countries, companies, etc. In this embodiment, a case where the greenhouse gas is carbon dioxide (CO2) will be described as an example.

[0016] An "electric power company," for example, owns power generation facilities, supplies the generated electricity to the power grid, and sells it to businesses, households, etc. The electricity supplied to the power grid by electric power companies is generated by various power generation methods, such as thermal power generation, nuclear power generation, hydroelectric power generation, and renewable energy. The proportion of each power generation method varies from one electric power company to another and also depending on the time of day.

[0017] "Ordinary households" use electricity supplied to each dwelling unit from the power grid and pay electricity bills to the power company. In this specification, "ordinary households" are explained as multiple households that own or use electric vehicles 10 equipped with batteries 11 and participate in a project related to the creation of carbon credits implemented by business operator A.

[0018] The electric vehicle 10 is a vehicle that can be charged with power from an external power source, such as a battery-powered electric vehicle, a plug-in hybrid vehicle, or a fuel cell vehicle. For example, ordinary households participating in the project are equipped with charging facilities that allow for normal charging, making it possible to charge the battery 11 of the electric vehicle 10 at home. The power used for charging at home can be power supplied from the power grid, or, if the home is equipped with renewable energy facilities such as solar power generation facilities, power generated by the facilities can also be used. Note that in this specification, "charging the battery 11" can also be referred to as "charging the electric vehicle 10," and these terms are synonymous.

[0019] "Business A" is a business that generates carbon credits based on the amount of CO2 reduced by ordinary households that participate in the project, and is sometimes called a resource aggregator. Business A has previously applied to a certification body for a project related to the creation of carbon credits, and the project has been registered as a result of the certification body's review.

[0020] Business operator A acquires power usage information (charging information, etc.) for the electric vehicle 10 of each general household. As will be described in detail later, business operator A aggregates the amount of CO2 reduced by each general household through changes in the charging behavior of the electric vehicle 10 for all general households. Business operator A also acquires power supply information from the power company, including information such as the proportion of renewable energy used. Business operator A applies for carbon credits to a certification organization based on the amount of CO2 reduced by all general households participating in the project.

[0021] A "certification body" registers projects and certifies applications for carbon credits resulting from the implementation of projects. Once the certification body certifies an application for carbon credits from business A, it issues carbon credits to business A. Note that the certification procedure by a certification body generally requires payment of a fee to the certification body.

[0022] Business B is a business that wishes to purchase carbon credits owned by business A. Business A sells the carbon credits to business B. The transaction (buying and selling) between business A and business B may be conducted directly or through an intermediary, or may be conducted on the market. The sold carbon credits are used, for example, for carbon offsetting. Carbon offsetting will be described later with reference to FIG. 2.

[0023] Business A distributes a portion of the profits it makes from selling carbon credits to each ordinary household participating in the project. In this way, even ordinary households can participate in the creation of carbon credits by collaborating with Business A and enjoy incentives for reducing greenhouse gas emissions. This incentive increases the motivation of ordinary households to reduce greenhouse gas emissions, and ultimately contributes to preventing global warming.

[0024] Figure 2 is a diagram explaining the outline of carbon offsetting. In the example shown in Figure 2, it is assumed that business A itself owns a factory, building, etc., and emits more CO2 than an average household.

[0025] Graph (a) in Figure 2 shows the expected CO2 emissions of business operator A and several ordinary households if the project were not implemented. Although the CO2 emissions of each ordinary household are very small compared to the CO2 emissions of business operator A, the combined CO2 emissions of several ordinary households could be on the same order of magnitude as the CO2 emissions of business operator A.

[0026] Graph (b) shows the actual CO2 emissions and CO2 reductions of Business A, as well as the actual CO2 emissions and CO2 reductions of an average household, if the project is implemented. In graph (b), the white areas correspond to CO2 emissions, and the shaded areas correspond to CO2 reductions.

[0027] Graph (c) is a graph in which the actual CO2 emissions of business A and an average household are summarized at the bottom of graph (b), and the actual CO2 reductions of business A and an average household are summarized at the top. In this way, business A is summarizing its own CO2 reductions and those of average households.

[0028] Graphs (d-1), (d-2), and (d-3) show the CO2 emissions of business operator B. Graph (d-1) shows the projected CO2 emissions, while graph (d-2) shows the actual CO2 emissions. It can be seen that business operator B's actual CO2 emissions exceed the projected amount. By purchasing carbon credits from business operator A, which are created based on the CO2 reductions compiled by business operator A, business operator B can offset the excess CO2 emissions (i.e., carbon offset) as shown in graph (d-3).

[0029] Next, a system 1 including a server 30 managed by a business operator A, and an electric vehicle 10 and a terminal device 20 owned by an ordinary household will be described with reference to Fig. 3. Fig. 3 is a block diagram showing the functional configuration of the system 1.

[0030] The system 1 includes an electric vehicle 10, a terminal device 20 used by the owner or user of the electric vehicle 10, and a server 30. The server 30 is managed by business operator A, and provides a service of a predetermined software application (hereinafter also referred to as a user app) to ordinary households participating in a project organized by business operator A. On the other hand, the terminal device 20 is a client that uses the service. Note that while only one electric vehicle 10 and one terminal device 20 are shown in FIG. 3, the system 1 includes electric vehicles 10 and terminal devices 20 owned or used by multiple ordinary households participating in the project. The ordinary households are users of the user app provided by the server 30, and in the following description, ordinary households participating in the project will also be referred to as users U.

[0031] The electric vehicle 10 has a high-voltage battery 11 capable of supplying power to a drive source of the electric vehicle 10, and a communication unit 12 capable of wireless or wired communication with a terminal device 20 and / or a server 30. The battery 11 is configured by stacking multiple battery cells, such as lithium-ion batteries or nickel-metal hydride batteries. The electric vehicle 10 is a vehicle that can be charged with power from an external power source.

[0032] The electric vehicle 10 may be configured to be capable of automatic charging, which automatically performs charging operations. For example, the electric vehicle 10 may be configured to automatically start charging at a preset time when plugged into charging equipment. The electric vehicle 10 may also be configured to automatically drive (i.e., move autonomously without being driven by a driver) to a predetermined charging equipment and automatically start charging. Hereinafter, the automatic start of charging may also be referred to as automatic charging.

[0033] The terminal device 20 is, for example, a smartphone, a tablet terminal, or a PC (Personal Computer) on which the above-mentioned user application is installed. The terminal device 20 may also be a navigation device or the like that is mounted on the electric vehicle 10 and on which the user application is installed. Here, a case where the terminal device 20 is a smartphone used by a user U will be described as an example.

[0034] The terminal device 20 includes a touch panel 21, a communication unit 22, a GPS (Global Positioning System) sensor 23, a control unit 24, and a storage unit 25.

[0035] The touch panel 21 functions as an interface unit of the terminal device 20. Specifically, the touch panel 21 has, as functions related to input and output of the terminal device 20, an information display unit that displays various information to the user U and an information input unit that accepts information input by the user U through touch operations.

[0036] The communication unit 22 includes a short-range communication unit that wirelessly communicates with the electric vehicle 10 based on a communication standard such as Bluetooth (registered trademark) or Wi-Fi (registered trademark), and a network communication unit that wirelessly communicates with the server 30 via a network NW using, for example, mobile communication. The short-range communication unit may be configured to communicate with the electric vehicle 10 via a wired connection such as a USB (Universal Serial Bus).

[0037] The GPS sensor 23 receives signals transmitted from GPS satellites and acquires location information of the terminal device 20, specifically, the latitude and longitude.

[0038] In the control unit 24, a processor such as a CPU (Central Processing Unit) capable of performing various calculations executes a user application stored in a storage unit 25 such as a ROM (Read Only Memory) that stores various information. The user application is downloaded in advance by the user U and stored in the storage unit 25.

[0039] The server 30 processes information related to carbon credits. The server 30 is a remote computer that can communicate with the terminal device 20, which is a local terminal, and / or the electric vehicle 10 via a network NW. The server 30 may be a distributed server made up of multiple servers, or a distributed virtual server (cloud server) created in a cloud environment.

[0040] The server 30 includes a communication unit 31, a storage unit 32, an application management unit 33 that manages user applications, and a carbon credit management unit 34 that manages carbon credits.

[0041] The communication unit 31 is configured to be able to wirelessly communicate with the terminal device 20 and / or the electric vehicle 10 via the network NW.

[0042] The storage unit 32 stores various information received from the terminal device 20, and various information calculated by the application management unit 33 and the carbon credit management unit 34. In the illustrated example, the storage unit 32 stores the actual value of the CO2 reduction amount for each user U.

[0043] The application management unit 33 manages a user application for supporting the creation of carbon credits by the user U. The user application has, for example, a function for suggesting to the user U charging actions for the electric vehicle 10 that contribute to reducing CO2 emissions, and a function for managing acquired actual charging results, etc. When the terminal device 20 is logged in to the server 30, the application management unit 33 communicates with the terminal device 20 and transmits predetermined display information to the terminal device 20 to display a screen on the user application.

[0044] The application management unit 33 includes a charging option generation unit 33a that generates charging options described below, a calculation unit 33b that performs predetermined calculation processing to calculate predicted values ​​of CO2 emissions and predicted values ​​of CO2 reduction amounts, etc., and an output unit 33c that outputs display information for displaying on the terminal device 20 the charging options generated by the charging option generation unit 33a and the calculation results by the calculation unit 33b, etc.

[0045] The carbon credit management unit 34 manages carbon credits by, for example, processing information required for applying for carbon credits and executing processing for utilizing (buying and selling) issued carbon credits. The carbon credit management unit 34 has a calculation unit 34a that calculates a total value obtained by adding up the CO2 reduction amounts of multiple users U, a credit buying and selling processing unit 34b that executes processing when buying and selling carbon credits, and a profit distribution unit 34c that executes processing to distribute a portion of the profits obtained from the sale of carbon credits to each user U as an incentive.

[0046] Next, generation of charging options by the application management unit 33 of the server 30 will be described with reference to Figs. 4 to 11. In this specification, charging the battery 11 mounted on the electric vehicle 10 using an external power source is also referred to as a "charging action." This charging action includes charging performed by manual operation by the user U of the electric vehicle 10, as well as the automatic charging described above.

[0047] The server 30 generates candidates (charging options) for other charging actions with lower CO2 emissions for a reference charging action (reference charging action). The server 30 generates the charging options based on, for example, location information of the electric vehicle 10 and the terminal device 20. In this embodiment, as shown in FIG. 4, for example, a case will be described where the reference charging action is an action of charging the electric vehicle 10 at night at home 100 with power supplied from a power grid.

[0048] The graph shown in Figure 4 shows an example of the time history of predicted values ​​of CO2 emissions per unit of power per hour in a power grid. The information included in this graph is obtained by server 30 performing predetermined processing based on information provided by, for example, an electric power company. During the day, the amount of power generated by solar power generation is large, so the proportion of power generated by solar power generation, etc. in the amount of power generated by the electric power company is relatively large, and CO2 emissions per unit of power per hour are low. On the other hand, during the night, the amount of power generated by solar power generation is low, so the proportion of power generation methods with high CO2 emissions, such as thermal power generation, is large, and the amount of CO2 generated per unit of power per hour is high.

[0049] When charging the electric vehicle 10 at home 100 at night using power supplied from the power grid, the amount of CO2 emissions is expected to correspond to the area surrounded by the thick line in the graph. Specifically, the amount of CO2 emissions corresponding to this area is calculated by multiplying the predicted value of CO2 emissions per unit of power time [ton-CO2 / kWh] by the amount of power charged [kWh]. In this way, the server 30 can calculate the amount of CO2 emissions estimated to have been emitted due to charging the electric vehicle 10 based on the amount of CO2 emissions per unit of power time from the power grid and the amount of power charged. Note that the method of calculating CO2 emissions described here is merely an example, and various calculation methods are possible.

[0050] The server 30 generates a plurality of charging options that are expected to reduce CO2 emissions by comparing them with the predicted value of CO2 emissions for a reference charging behavior, and proposes the options to the terminal device 20 in a predetermined manner.

[0051] 5 and 6, charging options A to E will be described as examples of charging options in this embodiment. Note that charging options A to E are merely examples, and the server 30 can generate various types of charging options.

[0052] Charging option A is a charging action performed at home 100 during the daytime, in which the electric vehicle 10 is charged using power generated by a solar panel 101 installed at home 100. Because the electric vehicle 10 is charged using power generated by solar power generation, CO2 emissions per unit time of power are zero, and the CO2 emissions emitted by charging the electric vehicle 10 are also zero. Note that if the amount of power required to charge the electric vehicle 10 cannot be covered by power generated by solar power alone, power supplied from the power grid may be used. Therefore, in charging option A, the CO2 emissions per unit time of power are not necessarily zero, and as a result, the calculated CO2 emissions may be greater than zero. The same applies to charging options C, D, and E, which will be described later.

[0053] Charging option B is a charging action performed at home during the daytime, in which the electric vehicle 10 is charged using power supplied from the power grid. Charging option B is a charging action performed during a time period when CO2 emissions per unit time of power from the power grid are low, and therefore results in lower CO2 emissions than the reference charging action even if the amount of charged power is the same as the reference charging action.

[0054] Charging option C is a charging action performed at home at night, in which the electric vehicle 10 is charged with electricity stored in a power storage device 102 installed in the home 100. The power storage device 102 stores electricity generated during the day by, for example, a solar panel 101 installed in the home 100. Charging option C is a charging action in which the electric vehicle 10 is charged using electricity originally generated by the solar panel 101, and is therefore expected to reduce CO2 emissions.

[0055] Charging option D is a charging action performed during the day at a charging station 200 (for example, an off-grid charging station) located in a place other than the home 100, and is a charging action in which the electric vehicle 10 is charged with power generated by, for example, a solar panel 201 or the like installed on the charging station 200. Because this is a charging action in which the electric vehicle 10 is charged with power generated by the solar panel 101 or the like, a reduction in CO2 emissions can be expected. Note that the charging station 200 may also have other renewable energy facilities such as wind power generation facilities.

[0056] Charging option E is a charging action performed at night at a charging station 200 located in a place different from home 100, in which the electric vehicle 10 is charged with electricity generated by solar panels 201 or the like during the day and stored in a power storage device 202 installed at the charging station 200. Since this is a charging action in which the electric vehicle 10 is charged using electricity originally generated by solar panels 201 or the like, a reduction in CO2 emissions can be expected.

[0057] In this way, the charging options generated by the server 30 include charging actions at times and / or locations different from the reference charging actions, charging actions using power supplied from a power supply source different from the reference charging actions, etc.

[0058] 7 is a bar graph showing the CO2 emissions and CO2 reduction amounts for a reference charging behavior (denoted as "Base" in the figure) and charging behaviors for charging options A to E. Note that the CO2 emissions and CO2 reduction amounts here are not actual values ​​but predicted values ​​calculated by the server 30.

[0059] For the charging options A, B, and C, the server 30 calculates the CO2 reduction amount by subtracting the CO2 emission amount for the charging action of each of the charging options A, B, and C from the CO2 emission amount for the reference charging action.

[0060] For charging options D and E, the server 30 calculates the CO2 reduction amount by subtracting the CO2 emissions for the charging actions of each charging option D and E from the CO2 emissions for the reference charging action, and further subtracting the CO2 emissions resulting from the movement of the electric vehicle 10. This is because, for charging options D and E, charging is performed at the charging station 200, which is a location different from the home 100, and therefore it is necessary to take into account the CO2 emissions for charging the amount of power consumed by the battery 11 during movement of the electric vehicle 10 between the home 100 and the charging station 200. The server 30 calculates the CO2 emissions resulting from the movement of the electric vehicle 10 based on the travel distance and electricity cost between the home 100 and the charging station 200, etc.

[0061] In this way, the server 30 automatically calculates the predicted CO2 reduction amount for each charging option based on the predicted CO2 emissions for the standard charging behavior and the predicted CO2 emissions for the charging option, and can therefore suggest charging options that contribute to CO2 reduction to the user U.

[0062] In addition, when there are multiple charging stations near home 100, and server 30 proposes charging actions to be performed at charging stations located in locations other than home 100, such as charging options D and E, server 30 may decide which charging station to propose to user U based on the electricity cost.

[0063] The server 30 displays a screen on the terminal device 20 that has launched the user application, proposing the generated charging options A to E to the user U. This enables the server 30 to encourage the user U to change their charging behavior to one that produces less CO2 emissions.

[0064] 8 is an example of a proposal screen for charging options A to E displayed on the terminal device 20. The server 30 visually displays the CO2 emissions, CO2 reductions, and electricity costs for charging for the reference charging behavior and each of the charging behaviors of the charging options A to E. Here, an example is shown in which the CO2 emissions, CO2 reductions, and electricity costs are displayed as bar graphs.

[0065] In this way, the server 30 visually displays the CO2 emissions and CO2 reduction amount for each charging option on the terminal device 20, allowing the user U to easily understand the effect of CO2 emission reductions due to changes in charging behavior. Furthermore, the server 30 visually displays the reference charging behavior and the electricity cost for each charging option, so it can also suggest profitable charging behaviors to the user U. Note that the server 30 does not need to display all of the CO2 emissions, CO2 reduction amount, and electricity cost for each charging option on the terminal device 20, and may be configured to display at least one of these.

[0066] Furthermore, by selecting a charging option suggested by the server 30 and reducing CO2 emissions, the user U can receive an incentive from the business operator A. This can increase the motivation of the user U to take actions that contribute to preventing global warming.

[0067] Furthermore, the server 30 may display the amount of chargeable energy for each charging option on the terminal device 20 that has started the user application.

[0068] 9 is an example of a screen displayed on the terminal device 20 that visually shows the reference charging behavior and the chargeable energy amount for each of the charging options A to E. For example, if the amount of energy stored in the power storage device 102 is small for the charging option C, the chargeable energy amount for the charging option C is displayed as low. In this way, by displaying the chargeable energy amounts for the charging options A to E, the user U can have more information to make a decision when selecting one of the charging options.

[0069] Incidentally, when calculating the CO2 reduction amount for charging options C to E in which solar-generated electricity (including electricity stored in the power storage devices 102 and 202) is charged to the battery 11, the server 30 may calculate the CO2 reduction amount further based on weather data provided from a weather server (not shown) or the like. The weather data here includes at least one of past weather data and future (predicted) weather data.

[0070] Specifically, the server 30 may calculate the CO2 reduction amount by multiplying the value obtained by subtracting the CO2 emissions for the charging option from the CO2 emissions for the reference charging behavior by a predetermined weather coefficient obtained from weather data. For example, the higher the probability of good weather (sunny), the higher the weather coefficient value, and the higher the probability of bad weather (cloudy, rainy, etc.), the lower the weather coefficient value.

[0071] In this way, the server 30 calculates the amount of CO2 reduction due to solar power generation, which is highly dependent on the weather, based additionally on meteorological data, and therefore can calculate the amount of CO2 reduction with higher accuracy.

[0072] Furthermore, the server 30 may display information that can be acquired based on weather data on the terminal device 20. For example, when proposing a charging option for charging the battery 11 with power generated by solar power generation, the server 30 may display on the terminal device 20 the amount of power that will be charged to the battery 11 by solar power generation, estimated based on weather data. When proposing a charging option for charging the battery 11 with power generated by solar power generation, the server 30 may display on the terminal device 20 the amount of power generated by solar power generation, estimated based on weather data. This allows the user U to understand whether the amount of power obtained by solar power generation, which depends on the weather, can sufficiently charge the battery 11.

[0073] FIG. 10 is a sequence diagram showing an example of processing performed among the server 30, the terminal device 20, and the electric vehicle 10. As shown in FIG.

[0074] When electrically powered vehicle 10 is able to communicate with server 30, it transmits information relating to the state of charge (SOC) of battery 11 to server 30 at predetermined time intervals (step S110). Note that electrically powered vehicle 10 may transmit the SOC of battery 11 to server 30 via terminal device 20.

[0075] When the server 30 determines that the SOC of the battery 11 has decreased, specifically that the SOC of the battery 11 has become less than a predetermined threshold (e.g., 30%), the server 30 executes a process for generating a charging option (sometimes referred to as a charging option generation process) (step S120). Note that the server 30 may be configured to execute the charging option generation process when, based on a travel plan preset in the electric vehicle 10, it is predicted that the SOC of the battery 11 will become less than a predetermined threshold when the electric vehicle 10 travels according to the travel plan (i.e., when it is predicted in advance that charging of the battery 11 is required).

[0076] 11 is a flow diagram showing an example of a charging option generation process. The server 30 generates, as charging options, a plurality of candidate charging actions that can be proposed to the user U of the electric vehicle 10 (step S121), and calculates a predicted value of CO2 emissions for each charging option (step S122).

[0077] The server 30 then calculates a predicted CO2 reduction amount for each charging option based on the predicted CO2 emissions for the reference charging behavior and the predicted CO2 emissions for the charging options that are other charging behaviors (step S123). Specifically, the predicted CO2 reduction amount for each charging option is calculated by subtracting the predicted CO2 emissions for each charging option from the predicted CO2 emissions for the reference charging behavior. After calculating the predicted CO2 reduction amount, the server 30 generates display information for displaying the charging options together with the CO2 emissions and CO2 reduction amount on the terminal device 20 (step S124).

[0078] Returning to FIG. 10, the server 30 transmits the display information generated in step S124 to the terminal device 20, and displays each charging option selectable by the user U, together with the CO2 emissions and CO2 reduction amounts, on the terminal device 20 that has launched the user application (step S130).

[0079] The user U charges the electric vehicle 10 with reference to the charging options displayed on the terminal device 20 (step S140). Note that the charging action performed by the electric vehicle 10 is not limited to the charging option proposed by the server 30, and may naturally be the reference charging action or another charging action.

[0080] After charging is completed, the electric vehicle 10 transmits predetermined charging information to the server 30 (step S150). The predetermined charging information includes the amount of charged power, the charging time, the charging location, the time period during which charging was performed, the charging method (power from the power grid, power generated by solar power, or power from a power storage device), etc. The electric vehicle 10 may transmit the predetermined charging information to the server 30 directly, or may transmit it to the server 30 via the terminal device 20.

[0081] The server 30 calculates the actual values ​​of CO2 emissions and CO2 reductions for the actual charging action based on the charging information transmitted from the electric vehicle 10 (step S160) and stores the calculated values ​​in the storage unit 32 (step S170). Specifically, the server 30 identifies the location where the electric vehicle 10 was actually charged based on the location information of the electric vehicle 10 or the location information of the terminal device 20. The server 30 then calculates the CO2 emissions per unit of power time at the charging location based on information provided by the electric power company or the like, and calculates the actual values ​​of CO2 emissions and CO2 reductions for the actual charging action based on the CO2 emissions per unit of power time and the amount of charged power, etc. As will be described in detail later, carbon credits are created based on the actual values ​​of CO2 reductions. The server 30 may display the actual values ​​of CO2 emissions and CO2 reductions on the terminal device 20 that has launched the user app.

[0082] 10 is repeatedly executed for a predetermined monitoring period (for example, one month or one year) for electric vehicles 10 owned or used by multiple users U. The server 30 accumulates, for each user U, the actual CO2 reduction values ​​for multiple charging actions actually performed during the monitoring period.

[0083] 12 is a control flow showing an example of a process for managing carbon credits by the server 30. After the monitoring period has elapsed, the server 30 sums up the actual values ​​of the CO2 reduction amounts for each user U that have been accumulated during the monitoring period (step S200).

[0084] The server 30 applies to a certification body for issuing carbon credits based on the total CO2 reduction performance (step S210). Once the certification body has completed the carbon credit certification, the server 30 acquires the certified carbon credits (step S220).

[0085] When the carbon credits are utilized by selling them, the server 30 determines a buyer of the carbon credits (step S230) and then executes a process to sell the carbon credits (step S240). The process of step S240 is automatically executed by the server 30.

[0086] After the carbon credits are sold, the server 30 distributes a portion of the profits obtained from the sale to each user U (step S250). The processing of step S250 is automatically executed by the server 30. This allows the user U to receive an incentive for participating in a project to reduce greenhouse gas emissions by business operator A and contributing to CO2 reduction. At this time, the server 30 determines the incentive to distribute to each user U based on, for example, the amount of CO2 reduction for each user U.

[0087] (Variation) 13 is a sequence diagram showing a modified example of the processing performed among the server 30, the terminal device 20, and the electric vehicle 10. In this modified example, the electric vehicle 10 performs automatic charging based on the charging option selected by the user U. Note that steps S110 to S130 and steps S150 to S170 are the same as those in FIG. 10, and therefore description thereof will be omitted.

[0088] After the server 30 displays the charging options on the terminal device 20 (step S130), the user U selects one charging option from the multiple charging options displayed on the terminal device 20, and the selection of the charging option is input to the terminal device 20 (step S131).

[0089] The terminal device 20 transmits the charging option selected by the user U to the electric vehicle 10 (step S132), and the electric vehicle 10 performs automatic charging based on the selected charging option (step S133). For example, if the user U selects the above-mentioned charging option E and the electric vehicle 10 is at home 100, the electric vehicle 10 will travel to the charging station 200 by automatic driving at night and automatically start charging. Note that the server 30 may be configured to recognize the charging option selected by the user U and transmit the charging option to the electric vehicle 10. In this case, the server 30 may be configured to remotely operate the electric vehicle 10 to cause automatic charging.

[0090] The information processing method described above can be realized by executing a prepared program on a computer. The program is stored in a computer-readable storage medium and executed by being read from the storage medium. The program may be provided in a form stored in a non-transitory storage medium such as a flash memory, or may be provided via a network such as the Internet. The computer that executes the program may be the server 30, a terminal device 20 that has downloaded the program from the server 30, a control device (e.g., an ECU (Electronic Control Unit)) that is mounted on the electric vehicle 10 and has downloaded the program from the server 30, or a combination of these.

[0091] Although one embodiment of the present invention has been described above with reference to the accompanying drawings, it goes without saying that the present invention is not limited to such an embodiment. It is clear that a person skilled in the art can conceive of various modifications or alterations within the scope of the claims, and it is understood that these also naturally fall within the technical scope of the present invention. Furthermore, the components of the above embodiment may be combined in any manner without departing from the spirit of the invention.

[0092] For example, in the embodiment described above, an example in which the server 30 executes the charging option generation process (step S120) and the calculation of the actual values ​​of CO2 emissions and CO2 reduction amounts (step S160) has been described with reference to Fig. 10, but this is not limiting. For example, these processes may be executed by a control device mounted on the terminal device 20 and / or the electric vehicle 10. However, if the server 30 executes the charging option generation process (step S120) and the calculation of the actual values ​​of CO2 emissions and CO2 reduction amounts (step S160), the processing load can be reduced compared to when these processes are executed by the control device of the terminal device 20 or the electric vehicle 10. As a result, the power consumption of the terminal device 20 and the electric vehicle 10 can be reduced.

[0093] Furthermore, some certification bodies may not allow the creation (application) of carbon credits based on the amount of electricity used to drive the electric vehicle 10 out of the amount of electricity charged to the battery 11. Therefore, carbon credits may be created based on the amount of electricity charged to the battery 11 by an actually performed charging action, excluding the amount of electricity used to drive the electric vehicle 10 after the charging action. Specifically, carbon credits may be created based on the amount of electricity used to supply power to a home, a power grid, etc. out of the amount of electricity charged to the battery 11 by an actually performed charging action. More specifically, the server 30 calculates the amount of CO2 reduction equivalent to the amount of electricity used to supply power to a home, a power grid, etc., and uses the calculated amount of CO2 reduction as data at the time of applying for carbon credits.

[0094] This specification describes at least the following: In parentheses, components corresponding to those in the above-described embodiments are shown as examples, but the present invention is not limited to these.

[0095] (1) An information processing method for processing information on carbon credits generated by greenhouse gas reductions using a computer (server 30), The carbon credits are generated based on the reduction of greenhouse gas emissions caused by the charging action of charging a battery (battery 11) mounted on an electric vehicle (electric vehicle 10) using an external power source, The information processing method includes: a generation step (step S121) of generating candidate charging actions selectable by a user of the electric vehicle, the candidate charging action including at least one other charging action that emits less greenhouse gas than a reference charging action that is a reference charging action; an emission calculation step (step S122) of calculating a predicted value of the amount of greenhouse gas emitted by each charging action; a reduction amount calculation step (step S123) of calculating a predicted value of the greenhouse gas reduction amount for each of the at least one other charging actions based on a predicted value of the greenhouse gas emission amount for the reference charging action and a predicted value of the greenhouse gas emission amount for the other charging action; Information processing methods.

[0096] According to (1), it is possible to propose charging actions that contribute to reducing greenhouse gas emissions to electric vehicle users, and to support the creation of carbon credits using electric vehicles, which in turn contributes to the prevention of global warming.

[0097] (2) The information processing method according to (1), The method further includes a display step (step S130) of displaying the charging action candidates on a terminal device of the user (terminal device 20) or a terminal device mounted on the electric vehicle, the display step displays, on the terminal device, at least one of the predicted value of the greenhouse gas emission amount and the predicted value of the greenhouse gas reduction amount together with the candidate charging action. Information processing methods.

[0098] According to (2), users can visually check the greenhouse gas emissions and / or reductions resulting from each charging action.

[0099] (3) The information processing method according to (1) or (2), the at least one other charging behavior includes a charging behavior at a time and / or a place different from a time and / or a place where the reference charging behavior is performed; Information processing methods.

[0100] According to (3), it is possible to suggest to the user charging behaviors that can contribute to reducing greenhouse gas emissions by changing the time and / or location.

[0101] (4) The information processing method according to (3), the at least one other charging action includes a charging action at a location other than a location where the reference charging action is performed; the reduction amount calculation step calculates a predicted value of the greenhouse gas reduction amount of the charging action performed at the other location, further based on an amount of greenhouse gas emissions resulting from movement of the electric vehicle between a location where the reference charging action is performed and the other location. Information processing methods.

[0102] According to (4), greenhouse gas emissions resulting from the movement of electric vehicles are taken into consideration, so that the predicted value of greenhouse gas emissions can be calculated with high accuracy.

[0103] (5) An information processing method according to any one of (1) to (4), the at least one other charging action includes a charging action of charging the battery with solar-generated power; The reduction amount calculation step calculates a predicted value of the greenhouse gas reduction amount resulting from the charging action using solar power generation further based on meteorological data. Information processing methods.

[0104] According to (5), the predicted amount of greenhouse gas reductions due to solar power generation, which is easily dependent on the weather, is calculated based on meteorological data as well, so that the predicted amount of greenhouse gas reductions can be calculated with higher accuracy.

[0105] (6) The information processing method according to (5), The method further includes a display step (step S130) of displaying the charging action candidates on a terminal device of the user (terminal device 20) or a terminal device mounted on the electric vehicle, The display step includes: Information about the amount of power charged to the battery by the solar power generation estimated based on the weather data; and information about the amount of power generated by the solar power generation estimated based on the weather data; and further displaying at least one of the following on the terminal device. Information processing methods.

[0106] According to (6), information specific to solar power generation can be displayed on the terminal device.

[0107] (7) An information processing method according to any one of (1) to (6), The method further includes an actual reduction amount calculation step (step S160) of calculating an actual value of a reduction amount of the greenhouse gas based on an actual value of the greenhouse gas emission amount in the actually performed charging action and a predicted value of the greenhouse gas emission amount in the reference charging action, The carbon credits are generated based on the actual greenhouse gas reductions. Information processing methods.

[0108] According to (7), it is possible to create highly reliable carbon credits based on the actual measured amount of greenhouse gas reduction.

[0109] (8) The information processing method according to (7), The carbon credits are generated based on the actual greenhouse gas reduction amount accumulated over a predetermined period. Information processing methods.

[0110] According to (8), although the amount of greenhouse gas reduction per charging action is relatively small, by accumulating it over a certain period of time, it is possible to create carbon credits based on a sufficient amount of greenhouse gas reduction.

[0111] (9) The information processing method according to (7) or (8), The carbon credits are generated based on the amount of electricity charged to the battery by the actually performed charging action, excluding the amount of electricity used for running the electric vehicle after the charging action. Information processing methods.

[0112] According to (9), the amount of electricity used to drive the electric vehicle after charging can be excluded from the data used to create carbon credits.

[0113] (10) A program that processes information regarding carbon credits created by greenhouse gas reductions, The carbon credits are generated based on the reduction of greenhouse gas emissions caused by the charging action of charging a battery (battery 11) mounted on an electric vehicle (electric vehicle 10) using an external power source, The program a generation step (step S121) of generating candidate charging actions selectable by a user of the electric vehicle, the candidate charging action including at least one other charging action that emits less greenhouse gas than a reference charging action that is a reference charging action; an emission calculation step (step S122) of calculating a predicted value of the amount of greenhouse gas emitted by each charging action; a reduction amount calculation step (step S123) of calculating a predicted value of the greenhouse gas reduction amount for each of the at least one other charging actions based on the predicted value of the greenhouse gas emission amount for the reference charging action and the predicted value of the greenhouse gas emission amount for the other charging action; program.

[0114] According to (10), it is possible to propose charging behaviors that contribute to reducing greenhouse gas emissions to electric vehicle users, and to support the creation of carbon credits using electric vehicles, which in turn contributes to the prevention of global warming.

[0115] (11) An information processing method for processing information on carbon credits generated by reducing greenhouse gases using a computer (server 30), comprising: The carbon credits are generated based on a reduction in the greenhouse gases emitted by charging batteries (batteries 11) mounted on a plurality of electric vehicles (electric vehicles 10) using an external power source, The information processing method includes: an addition step (step S200) of calculating and adding up, for each user of the plurality of electric vehicles, actual values ​​of greenhouse gas reduction amounts calculated based on a predicted value of the greenhouse gas emission amount for a reference charging action that is a reference charging action and an actual value of the greenhouse gas emission amount when another charging action that has a lower greenhouse gas emission amount than the reference charging action is actually performed; A selling step (step S240) of executing a selling process of the carbon credits created based on the sum of the actual values ​​of the greenhouse gas reduction amounts; A distribution step (step S250) of distributing a portion of the profits obtained in the selling step to each user. Information processing methods.

[0116] According to (11), the computer executes the process of distributing a portion of the profits obtained from the sale of carbon credits to users, thereby encouraging users to charge their cars in order to reduce greenhouse gas emissions, thereby contributing to the prevention of global warming. [Explanation of symbols]

[0117] 10 Electric vehicles 11 Battery 20 Terminal equipment 30 servers (computers)

Claims

1. An information processing method for processing information on carbon credits created by reducing greenhouse gases using a computer, comprising: The carbon credits are generated based on a reduction in the greenhouse gases emitted by charging a battery mounted on an electric vehicle using an external power source, The information processing method includes: a generating step of generating candidate charging actions selectable by a user of the electric vehicle, the candidate charging action including at least one other charging action that emits less greenhouse gas than a reference charging action that is a reference charging action; an emission calculation step of calculating a predicted value of the amount of greenhouse gas emitted by each charging action; a reduction amount calculation step of calculating a predicted value of the greenhouse gas reduction amount for each of the at least one other charging actions based on a predicted value of the greenhouse gas emission amount for the reference charging action and a predicted value of the greenhouse gas emission amount for each of the other charging actions, Information processing methods.

2. 2. The information processing method according to claim 1, a display step of displaying the charging action candidates on a terminal device of the user or a terminal device mounted on the electric vehicle; the display step displays, on the terminal device, at least one of the predicted value of the greenhouse gas emission amount and the predicted value of the greenhouse gas reduction amount together with the candidate charging action. Information processing methods.

3. 2. The information processing method according to claim 1, The at least one other charging behavior includes a charging behavior at a time and / or a place different from a time and / or a place where the reference charging behavior is performed. Information processing methods.

4. 4. The information processing method according to claim 3, the at least one other charging action includes a charging action at a location other than a location where the reference charging action is performed; the reduction amount calculation step calculates a predicted value of the greenhouse gas reduction amount of the charging action performed at the other location, further based on an amount of greenhouse gas emissions resulting from movement of the electric vehicle between a location where the reference charging action is performed and the other location. Information processing methods.

5. 2. The information processing method according to claim 1, the at least one other charging action includes a charging action of charging the battery with solar-generated power; The reduction amount calculation step calculates a predicted value of the greenhouse gas reduction amount resulting from the charging action using solar power generation further based on meteorological data. Information processing methods.

6. 6. The information processing method according to claim 5, a display step of displaying the charging action candidates on a terminal device of the user or a terminal device mounted on the electric vehicle; The display step includes: Information about the amount of power charged to the battery by the solar power generation estimated based on the weather data; and information about the amount of power generated by the solar power generation estimated based on the weather data; and further displaying at least one of the following on the terminal device. Information processing methods.

7. 7. An information processing method according to claim 1, further comprising an actual reduction amount calculation step of calculating an actual value of a greenhouse gas reduction amount based on an actual value of the greenhouse gas emission amount in an actually performed charging action and a predicted value of the greenhouse gas emission amount in the reference charging action; The carbon credits are generated based on the actual greenhouse gas reductions. Information processing methods.

8. 8. The information processing method according to claim 7, The carbon credits are generated based on the actual greenhouse gas reduction amount accumulated over a predetermined period. Information processing methods.

9. 8. The information processing method according to claim 7, The carbon credits are generated based on the amount of electricity charged to the battery by the actually performed charging action, excluding the amount of electricity used for running the electric vehicle after the charging action. Information processing methods.

10. A program for processing information regarding carbon credits created by greenhouse gas reductions, The carbon credits are generated based on a reduction in the greenhouse gases emitted by charging a battery mounted on an electric vehicle using an external power source, The program a generating step of generating candidate charging actions selectable by a user of the electric vehicle, the candidate charging action including at least one other charging action that emits less greenhouse gas than a reference charging action that is a reference charging action; an emission calculation step of calculating a predicted value of the amount of greenhouse gas emitted by each charging action; a reduction amount calculation step of calculating a predicted value of the greenhouse gas reduction amount for each of the at least one other charging actions based on a predicted value of the greenhouse gas emission amount for the reference charging action and a predicted value of the greenhouse gas emission amount for each of the other charging actions; program.

11. An information processing method for processing information on carbon credits created by reducing greenhouse gases using a computer, comprising: the carbon credits are created based on a reduction in the greenhouse gases emitted by charging batteries mounted on a plurality of electric vehicles using an external power source; The information processing method includes: an addition step of calculating and adding up, for each user of the plurality of electric vehicles, actual values ​​of the greenhouse gas reduction amounts calculated based on a predicted value of the greenhouse gas emission amount for a reference charging action that is a reference charging action and an actual value of the greenhouse gas emission amount when another charging action that has a lower greenhouse gas emission amount than the reference charging action is actually performed; a selling step of executing a selling process of the carbon credits created based on the sum of the actual values ​​of the greenhouse gas reduction amounts; A distribution step of distributing a portion of the profits obtained in the selling step to each user. Information processing methods.

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