Prediction method, prediction device, and information terminal control method

Abstract

A prediction method according to the present invention: formulates a plan to introduce a distributed power supply system, which includes at least one of a natural-energy power generation device and a fuel cell device, over a plurality of years on the basis of at least one of a target value of a first index pertaining to CO2 emissions by an electricity consumer over a plurality of years and a budget plan for reducing the amount of CO2 emissions; and predicts a second index pertaining to CO2 emissions by the electricity consumer over a plurality of years when the distributed power supply system is introduced on the basis of the introduction plan.

Description

Prediction method, prediction apparatus, and control method for information terminal

[0001] The present disclosure relates to a prediction method for an indicator related to CO2 emissions, a prediction apparatus, and a control method for an information terminal.

[0002] Patent Document 1 below discloses a technology for evaluating distributed power sources such as solar cells, fuel cells, and storage batteries from an environmental perspective and presenting combinations of distributed power sources when introducing such distributed power sources.

[0003] Japanese Patent No. 7058254

[0004] The technology described in Patent Document 1 evaluates distributed power supply systems from an environmental perspective, but there are still insufficient points in the evaluation for the introduction of distributed power supply systems.

[0005] An object of the present disclosure is to provide a prediction method for an indicator, a prediction apparatus for the indicator, and a control method for an information terminal that displays the indicator, for performing a more appropriate evaluation from an environmental perspective compared to conventional techniques regarding the introduction of a distributed power supply system.

[0006] In order to solve the above problem, a prediction method according to an aspect of the present disclosure predicts a first indicator related to CO2 emissions of a power consumer over a plurality of years after introducing a distributed power supply system including at least one of a natural energy power generation apparatus and a fuel cell apparatus, in consideration of deterioration of the distributed power supply system.

[0007] Furthermore, a prediction apparatus according to an aspect of the present disclosure comprises: a storage that stores information related to deterioration of a distributed power supply system including at least one of a power storage device, a natural energy power generation apparatus, and a fuel cell apparatus; and a controller that predicts a first indicator related to CO2 emissions of a power consumer over a plurality of years after introducing the distributed power supply system in consideration of the information related to deterioration of the distributed power supply system stored in the storage.

[0008] Furthermore, a control method for an information terminal in one aspect of the present disclosure includes the step of displaying on the display of the information terminal information indicating a first indicator of CO2 emissions of an electricity consumer over several years after the introduction of a distributed power system including an energy storage device and at least one of a renewable energy power generation device and a fuel cell device, wherein the first indicator is predicted taking into account the deterioration of the distributed power system.

[0009] A prediction method and prediction apparatus according to one aspect of this disclosure have the effect of enabling a more appropriate evaluation from an environmental perspective compared to the prior art when introducing a distributed power supply system. Furthermore, a control method for an information terminal according to one aspect of this disclosure has the effect of enabling a more appropriate evaluation from an environmental perspective compared to the prior art when introducing a distributed power supply system.

[0010] Figure 1 shows an example of a distributed power system implementation. Figure 2 is a conceptual diagram of an information terminal. Figure 3 is a flowchart of the prediction method. Figure 4 shows the renewable energy rate of electricity consumers over several years. Figure 5 shows a multi-year implementation plan for a distributed power system. Figure 6 shows a breakdown of the amount of electricity supplied to electricity consumers over several years. Figure 7 shows the predicted CO2 emissions of electricity consumers over several years. Figure 8 shows the predicted CO2 emission reductions of electricity consumers over several years. Figure 9 shows the predicted electricity emission coefficients of electricity consumers over several years. Figure 10 shows the predicted CFP of products produced by electricity consumers over several years.

[0011] In recent years, due to growing environmental awareness, there has been an increasing trend for electricity consumers to introduce distributed power systems, including distributed power sources such as renewable energy generators, fuel cell systems, and energy storage systems. In these distributed power systems, various combinations of distributed power sources can be freely combined, so various combinations of distributed power sources were evaluated from an environmental perspective, and the configuration of the distributed power system was then considered.

[0012] Here, the inventors investigated the relationship between the degradation of distributed power systems and CO2 emissions. As a result, they found that when a distributed power system degrades, the efficiency of its output decreases, leading to a reduction in the amount of electricity supplied to consumers from the distributed power system, and an increase in the amount of electricity supplied to consumers from the power grid, which emits more CO2 than the distributed power system. Therefore, while considering the degradation of distributed power systems may reduce the environmental evaluation of their introduction, it is possible to conduct a more appropriate evaluation from an environmental perspective than before.

[0013] Therefore, the prediction method of the first aspect of this disclosure predicts a first indicator of CO2 emissions from electricity consumers over several years after the introduction of a distributed power system including at least one of a renewable energy power generation device and a fuel cell device, taking into account the deterioration of the distributed power system.

[0014] This prediction method forecasts a first indicator of CO2 emissions from electricity consumers, taking into account the degradation of distributed power generation systems. Therefore, by using this first indicator, it is possible to evaluate the introduction of distributed power generation systems by electricity consumers from an environmental perspective more appropriately than with conventional technologies.

[0015] A second aspect of the prediction method of the present disclosure is a prediction method of the first aspect, wherein the distributed power system includes the renewable energy power generation device, and the first indicator is predicted over several years after the introduction of the distributed power system, taking into account the degradation of the renewable energy power generation device.

[0016] This prediction method takes into account the degradation of renewable energy power generation equipment and predicts the first indicator over several years after the introduction of a distributed power generation system. Therefore, by using this first indicator, electricity consumers can make a more appropriate environmental assessment of the introduction of a distributed power generation system, including renewable energy power generation equipment, compared to conventional technologies.

[0017] A third aspect of the prediction method of the present disclosure is a prediction method of the first aspect, wherein the distributed power system includes the fuel cell device, and the first indicator is predicted over several years after the introduction of the distributed power system, taking into account the degradation of the fuel cell device.

[0018] This prediction method takes into account the degradation of fuel cell equipment and predicts the first indicator over several years after the introduction of a distributed power system. Therefore, by using this first indicator, electricity consumers can make a more appropriate environmental assessment of the introduction of a distributed power system, including fuel cell equipment, compared to conventional technologies.

[0019] A fourth aspect of the prediction method of the present disclosure is a prediction method of the first aspect, wherein the distributed power system includes the renewable energy power generation device and the fuel cell device, and the first indicator is predicted over several years after the introduction of the distributed power system, taking into account the degradation of the renewable energy power generation device and the fuel cell device, respectively.

[0020] This prediction method takes into account the degradation of both renewable energy power generation equipment and fuel cell equipment, and predicts the first indicator over several years after the introduction of a distributed power system. Therefore, by using this first indicator, electricity consumers can make a more appropriate environmental assessment of the introduction of a distributed power system, including renewable energy power generation equipment and fuel cell equipment, compared to conventional technologies.

[0021] A fifth aspect of the present disclosure is a prediction method in any one of the first to fourth aspects, wherein the distributed power system further includes an energy storage device, and the first indicator is predicted over several years after the introduction of the distributed power system, taking into account the degradation of the energy storage device.

[0022] This prediction method takes into account the degradation of energy storage devices and predicts the first indicator over several years after the introduction of a distributed power system. Therefore, by using this first indicator, electricity consumers can make a more appropriate environmental assessment of the introduction of a distributed power system, including energy storage devices, compared to conventional technologies.

[0023] The sixth aspect of the prediction method of this disclosure is a prediction method in any one of the first to fifth aspects, wherein the first indicator includes CO2 emissions.

[0024] This forecasting method predicts a first indicator, which includes CO2 emissions. Therefore, this forecasting method allows for a more appropriate evaluation from an environmental perspective of the introduction of distributed power generation systems for electricity consumers compared to conventional technologies. Here, "CO2 emissions" refers to the amount of CO2 emitted during the process of supplying electricity to electricity consumers.

[0025] The seventh aspect of the prediction method of this disclosure is the prediction method of the sixth aspect, wherein the first indicator further includes a reduction in CO2 emissions.

[0026] This forecasting method predicts a first indicator, which includes CO2 emission reductions. Therefore, this forecasting method allows for a more appropriate evaluation from an environmental perspective of the introduction of distributed power generation systems by electricity consumers compared to conventional technologies. Here, "CO2 emission reductions" refers to the amount of CO2 emissions reduced during the process of supplying electricity to electricity consumers.

[0027] The prediction method of the eighth aspect of this disclosure is the prediction method of the sixth aspect, wherein the first index further includes a power emission coefficient.

[0028] This forecasting method predicts a first indicator, which includes the power emission factor. Therefore, this forecasting method allows for a more appropriate evaluation from an environmental perspective of the introduction of distributed power generation systems by power consumers compared to conventional technologies. The "power emission factor" referred to here is the value obtained by dividing the amount of CO2 emitted in the process of supplying electricity to power consumers by the amount of electricity supplied.

[0029] The prediction method of the ninth aspect of this disclosure is a prediction method of any one of the first to eighth aspects, wherein the first indicator includes the renewable energy rate.

[0030] This forecasting method predicts a first indicator, which includes the renewable energy ratio. Therefore, this forecasting method allows for a more appropriate evaluation from an environmental perspective of the introduction of distributed power generation systems by electricity consumers compared to conventional technologies. The "renewable energy ratio" here refers to the proportion of electricity generated from renewable energy sources in the total electricity supplied to electricity consumers or the electricity consumed by electricity consumers.

[0031] A prediction method according to the ninth aspect of this disclosure is a prediction method according to any one of the first to ninth aspects, wherein the first indicator includes CFP.

[0032] This forecasting method predicts a first indicator, which includes CFP. Therefore, this forecasting method allows for a more appropriate evaluation of the introduction of distributed power systems from an environmental perspective compared to conventional technologies. Here, "CFP" refers to the value obtained by converting the greenhouse gas emissions from a product or service throughout its entire lifecycle, from raw material procurement to disposal and recycling, into CO2 equivalents.

[0033] In recent years, governments and local authorities have sometimes set CO2 emission limits for electricity consumers. In this case, if an electricity consumer's CO2 emissions exceed their limit, they must purchase surplus emission allowances from others as CO2 emission credits to cover the excess amount. There is also a system in place to buy and sell the aforementioned CO2 emission reductions as CO2 emission reduction credits. Therefore, electricity consumers may purchase CO2 emission credits or CO2 emission reduction credits if their CO2 emissions exceed predetermined target values.

[0034] Therefore, the prediction method of the eleventh aspect of this disclosure predicts the amount of CO2 emission rights or CO2 emission reduction rights to be purchased based on the target CO2 emission amount as a target value of a second indicator relating to the CO2 emissions of the electricity consumer over a multi-year period, and the CO2 emission amount, in the prediction method of the sixth aspect.

[0035] This forecasting method predicts the amount of CO2 emission credits or CO2 emission reduction credits to be purchased. Therefore, this forecasting method allows for a more appropriate evaluation from an environmental perspective of the introduction of distributed power generation systems by electricity consumers compared to conventional technologies.

[0036] Furthermore, electricity consumers can purchase renewable energy certificates (electricity certificates) that prove that the grid electricity supplied by power generators is generated from renewable energy sources (solar, wind, hydro, geothermal, etc.). Therefore, electricity consumers may purchase electricity certificates if their renewable energy rate falls below a predetermined target value.

[0037] Therefore, the prediction method of the twelfth aspect of this disclosure predicts the amount of electricity certificates to be purchased based on the target renewable energy rate as a target value of the first indicator over a multi-year period and the renewable energy rate, in the prediction method of the ninth aspect.

[0038] This forecasting method predicts the amount of electricity certificates to be purchased. Therefore, this forecasting method allows for a more appropriate evaluation from an environmental perspective of the introduction of distributed power generation systems by electricity consumers compared to conventional technologies.

[0039] A prediction method according to a thirteenth aspect of this disclosure is a prediction method according to any one of the first to twelve aspects, in which a multi-year introduction plan for the distributed power system is formulated based on a target value for a second indicator relating to the CO2 emissions of the electricity consumer over a multi-year period and a budget plan for reducing CO2 emissions, and the first indicator over a multi-year period after the introduction of the distributed power system is predicted based on the introduction plan, taking into account the deterioration of the distributed power system.

[0040] This prediction method forecasts a first indicator over several years after the introduction of a distributed power system, taking into account the degradation of the distributed power system, based on a multi-year introduction plan for the distributed power system. Therefore, using this first indicator, it is possible to evaluate the introduction of distributed power systems by electricity consumers from an environmental perspective more appropriately than with conventional technology.

[0041] A prediction device according to a fourteenth aspect of the present disclosure comprises: a storage device that stores information relating to degradation of a distributed power supply system including a power storage device and at least one of a natural energy power generation device and a fuel cell device; and a controller that predicts a first indicator relating to CO₂ emissions of a power consumer over a plurality of years after introduction of the distributed power supply system in consideration of the information relating to degradation of the distributed power supply system stored in the storage device.

[0042] In this prediction device, the controller predicts the first indicator relating to CO₂ emissions of the power consumer in consideration of degradation of the distributed power supply system. Therefore, by using this first indicator, more appropriate evaluation from an environmental perspective can be performed for introduction of the distributed power supply system by the power consumer compared to conventional techniques.

[0043] A control method for an information terminal according to a fifteenth aspect of the present disclosure is a control method for an information terminal, comprising the step of causing a display of the information terminal to display information indicating a first indicator relating to CO₂ emissions of a power consumer over a plurality of years after introduction of a distributed power supply system including a power storage device and at least one of a natural energy power generation device and a fuel cell device, wherein the first indicator is predicted in consideration of degradation of the distributed power supply system.

[0044] In this control method, information indicating the first indicator relating to CO₂ emissions of the power consumer predicted in consideration of degradation of the distributed power supply system is caused to be displayed on the display. Therefore, a proposer of introduction of the distributed power supply system who is a user of the information terminal, or a power consumer who has been presented with the information displayed on the display by the proposer, can perform more appropriate evaluation from an environmental perspective for introduction of the distributed power supply system by the power consumer compared to conventional techniques.

[0045] A control method according to a sixteenth aspect of the present disclosure is the control method according to the fifteenth aspect, further comprising the step of causing the display to display an introduction plan for the distributed power supply system formulated based on at least one of a target value of a second indicator relating to CO₂ emissions of the power consumer and a budget plan for CO₂ emission reduction.

[0046] In this control method, an introduction plan for a distributed power supply system is displayed on a display device. Therefore, the proposer or the power consumer can easily grasp the introduction plan of the distributed power supply system for the power consumer.

[0047] Specific examples of the above aspects of the present disclosure will be described below with reference to the accompanying drawings. All the specific examples described below are examples of the above aspects of the present disclosure. Therefore, the shapes, numerical values, constituent elements, arrangement positions of constituent elements, connection forms, and the like shown below do not limit the scope of the claims, unless recited in the claims.

[0048] In addition, among the constituent elements described below, those not recited in the independent claims representing the most generic concept of the present disclosure are described as optional constituent elements. In the drawings, descriptions of elements denoted by the same reference numerals may be omitted. The drawings schematically illustrate each constituent element for ease of understanding, and shapes, dimensional ratios, and the like may not be accurately represented.

[0049] Furthermore, in the operation of the device, the order of steps may be changed or known steps may be added as necessary.

[0050] (Example of Introduction of Distributed Power Supply System) First, an example of introduction of a distributed power supply system 12 by a power consumer 10 will be described. FIG. 1 is a diagram showing an example of introduction of the distributed power supply system 12. FIG. 1(a) shows a mode of power supply to the power consumer 10 before the start of introduction of the distributed power supply system 12. The power consumer 10 of the present embodiment is a factory that manufactures products, and the power consumer 10 includes power consuming equipment 11 such as production equipment that manufactures products. In the present embodiment, as shown in FIG. 1(a), before the start of introduction of the distributed power supply system 12, power is supplied to the power consuming equipment 11 of the power consumer 10 only from a power generation business operator 20 such as an electric power company. Hereinafter, the power supplied from the power generation business operator 20 to the power consumer 10 is referred to as "grid power".

[0051] Figure 1(b) shows the configuration of power supply to the power consumer 10 during an intermediate stage of the introduction of the distributed power system 12. In this embodiment, as shown in Figure 1(b), during an intermediate stage of the introduction of the distributed power system 12, power is supplied not only from the grid but also from the distributed power system 12 to the power consumption equipment 11 of the power consumer 10. The distributed power system 12 includes distributed power sources such as a renewable energy power generation device 13, a fuel cell device 14, and an energy storage device 15. However, the distributed power system 12 is not limited to the above configuration. For example, the distributed power system 12 may include only one of the above-mentioned distributed power sources.

[0052] The above-mentioned natural energy power generation device 13 is a device that generates electricity using natural energy, and includes solar power generation devices and wind power generation devices. The fuel cell device 14 is a device that generates electricity by chemically reacting hydrogen, which is the fuel, with oxides such as oxygen. There are several types of hydrogen that can be used as fuel for the fuel cell device 14, such as gray hydrogen extracted from fossil resources and green hydrogen produced using renewable energy. Furthermore, the energy storage device 15 is a device that temporarily stores and supplies electricity generated by other devices.

[0053] Figure 1(c) shows the configuration of power supply to the power consumer 10 after the completion of the installation of the distributed power system 12. In this embodiment, as shown in Figure 1(c), after the completion of the installation of the distributed power system 12, power is supplied to the power consumption equipment 11 of the power consumer 10 only from the distributed power system 12. However, even after the completion of the installation of the distributed power system 12, power may be supplied to the power consumption equipment 11 of the power consumer 10 from both the power generator 20 and the distributed power system 12. In particular, if the amount of power supplied from the distributed power system 12 to the power consumer 10 decreases due to deterioration of the distributed power system 12, power will be supplied to the power consumption equipment 11 of the power consumer 10 from both the power generator 20 and the distributed power system 12.

[0054] (Information Terminal) Next, the information terminal 30 used in the prediction method according to this embodiment will be described. Figure 2 is a conceptual diagram of the information terminal 30. In this embodiment, the information terminal 30 functions as a prediction device that predicts a first indicator, which will be described later. The information terminal 30 includes a controller 31, a memory 32, an input 33, and a display 34.

[0055] The controller 31 comprises an arithmetic processing unit and a memory unit for storing control programs. The arithmetic processing unit is, for example, a processor, and the memory unit is, for example, volatile memory. The controller 31 may be a single controller or a group of controllers working together. The memory unit 32 is, for example, non-volatile memory and is a device for storing various programs and information. The input device 33 is, for example, a keyboard operated by an operator and is a device for inputting various information. The display device 34 is, for example, a monitor and is a device for displaying various information.

[0056] Furthermore, the information terminal 30 is connected to an information server (not shown) in a communicative manner, and this information server may execute the processing of the controller 31, which will be described later. In other words, the controller 31 may consist of multiple devices, including a server that is connected in a communicative manner.

[0057] (Flowchart of Prediction Method) Next, the prediction method according to this embodiment will be described. The prediction method according to this embodiment is a method for predicting an indicator for evaluating the introduction of the distributed power system 12 from an environmental perspective, taking into account the deterioration of the distributed power system 12. Specifically, in the prediction method according to this embodiment, a first indicator regarding the CO2 emissions of electricity consumers 10 over several years after the introduction of the distributed power system is predicted, taking into account the deterioration of the distributed power system. This will be explained in detail below.

[0058] <Setting Target Values> Figure 3 is a flowchart of the prediction method according to this embodiment. As shown in Figure 3, in the flowchart of the prediction method according to this embodiment, the operator first sets target values ​​(step S10). Specifically, the operator sets target values ​​for a second indicator related to the CO2 emissions of the electricity consumer 10 over several years (the first indicator will be described later). The second indicator is, for example, CO2 emissions, CO2 emission reduction, electricity emission coefficient, renewable energy rate, etc.

[0059] In this embodiment, a target renewable energy rate over multiple years is set as the target value for the second indicator. The renewable energy rate refers to the proportion of electricity generated from renewable energy sources in the electricity supplied to electricity consumers or the electricity consumed by electricity consumers. Figure 4 shows the renewable energy rate of electricity consumer 10 over multiple years. The dashed line in Figure 4 represents the target renewable energy rate of electricity consumer 10. The worker sets the target renewable energy rate for electricity consumer 10 over multiple years, as shown by the dashed line in Figure 4, based on information such as the standard values ​​and benchmark values ​​for renewable energy rates of the industry, country, and local government to which electricity consumer 10 belongs, as well as electricity consumer 10's decarbonization plan. The above standard values ​​and benchmark values ​​are the target renewable energy rate to be achieved in the industry to which electricity consumer 10 belongs, the target renewable energy rate of other electricity consumers (e.g., other companies) in the industry to which electricity consumer 10 belongs, and the target renewable energy rate to be achieved in the country or local government to which electricity consumer 10 belongs.

[0060] In the example shown in Figure 4, the 20-year period is divided into four 5-year periods, from the first to the fourth, with target renewable energy rates set for each period. The first period is before the introduction of the distributed power system 12 and corresponds to the state shown in Figure 1(a). In the first period, no target renewable energy rate is set. The second and third periods are intermediate stages in the introduction of the distributed power system 12 and correspond to the state shown in Figure 1(b). Target renewable energy rates are set in the second and third periods, with the target renewable energy rate for the third period being higher than that for the second period. The fourth period is after the completion of the introduction of the distributed power system 12 and corresponds to the state shown in Figure 1(c). In the fourth period, the target renewable energy rate is set at 100%. Note that the first to fourth periods shown in Figures 5 to 10 correspond to the first to fourth periods shown in Figure 4, respectively.

[0061] Furthermore, a target value other than the target renewable energy rate may be set as the target value for the first indicator. In this case, the target value can be set in the same way as the target renewable energy rate. For example, a target CO2 emission may be set as the target value for the first indicator. In this case, the worker can set multi-year target CO2 emission for electricity consumer 10 based on information such as the baseline values ​​and standard values ​​of CO2 emissions in the industry, country, or local government to which electricity consumer 10 belongs, as well as electricity consumer 10's decarbonization plan. The baseline values ​​and standard values ​​mentioned above are the target CO2 emission values ​​that electricity consumer 10 wants to achieve in the industry to which electricity consumer 10 belongs, the target CO2 emission values ​​of other electricity consumers (for example, other companies) in the industry to which electricity consumer 10 belongs, and the target CO2 emission values ​​that electricity consumer 10 wants to achieve in the country or local government to which electricity consumer 10 belongs.

[0062] <Formulation of Implementation Plan> Next, in the flow of the prediction method according to this embodiment, the worker formulates a multi-year implementation plan for the distributed power system 12 (step S20). In this embodiment, the worker formulates a multi-year implementation plan for the distributed power system 12 based on the multi-year target value (target renewable energy rate) of the second indicator set in step S10 and the multi-year budget plan for CO2 emission reduction. The multi-year implementation plan for the distributed power system 12 may also be formulated by the controller 31.

[0063] Figure 5 shows a multi-year implementation plan for the distributed power system 12. In Figure 5, the multi-year implementation plan is shown using the rated output of the distributed power sources that make up the distributed power system 12 (the units of rated output are kW, MW, etc.). In the implementation plan shown in Figure 5, no distributed power sources are introduced in the first phase, a renewable energy power generation device 13, a fuel cell device 14, and an energy storage device 15 are introduced in the second phase, the number of fuel cell devices 14 is increased in the third phase, and the number of fuel cell devices 14 is further increased in the fourth phase.

[0064] The introduction plan for the distributed power system 12 is not limited to that shown in Figure 5. For example, an introduction plan may be formulated to introduce at least one of the renewable energy power generation device 13 and the fuel cell device 14, or an introduction plan may be formulated to introduce at least one of the renewable energy power generation device 13 and the fuel cell device 14 and the energy storage device 15.

[0065] Furthermore, the introduction plan for the distributed power system 12 may include an introduction plan for the replacement of at least a portion of the distributed power system 12. For example, if at least one of the renewable energy power generation device 13, fuel cell device 14, and energy storage device 15 needs to be replaced every few years, a multi-year introduction plan for the distributed power system 12 may be formulated that includes an introduction plan for the replacement of that device. In addition, the replacement timing of the renewable energy power generation device 13, fuel cell device 14, and energy storage device 15 may be predicted based on degradation information described in step S40 below. In this case, the replacement timing will be equivalent to the guaranteed service life for each distributed power source if the degradation information, such as the operating frequency of each distributed power source and the operating time of each distributed power source during a specified period, corresponds to standard operating conditions, but will be predicted to be earlier than the guaranteed service life if it corresponds to operating conditions with a heavier load than standard.

[0066] Furthermore, in this embodiment, the multi-year introduction plan for the distributed power system 12 is formulated based on both the target value of the second indicator (target renewable energy rate) and the budget plan for CO2 emission reduction, but it may also be formulated based on either one of them. Moreover, in this embodiment, the introduction plan for the distributed power system 12 is formulated based on the target renewable energy rate, but instead of this target renewable energy rate, or in addition to the target renewable energy rate, the introduction plan for the distributed power system 12 may also be formulated based on the target value of other CO2 emission indicators, such as the target value of CO2 emissions.

[0067] <Display of Implementation Plan> Next, in the flow of the prediction method according to this embodiment, the operator displays the multi-year implementation plan for the distributed power system 12 using the information terminal 30 (step S30). In this embodiment, the operator inputs the data related to the multi-year implementation plan for the distributed power system 12 formulated in step S20 into the input device 33, and the controller 31 of the information terminal 30 displays the multi-year implementation plan for the distributed power system 12 on the display device 34 based on that implementation data.

[0068] <Acquisition of Degradation Information> Next, in the flow of the prediction method according to this embodiment, the controller 31 acquires degradation information from the memory 32 (step S40). The degradation information is information relating to the degradation of each distributed power supply. The degradation information stored in the memory 32 may be input by the operator using the input device 33 each time step S40 is performed, or it may be information that the memory 32 has acquired in advance.

[0069] The degradation information may include, for example, at least one of the following: the degradation rate relative to the usage period of the distributed power source, the degradation rate relative to the number of times the distributed power source is operated, and the degradation rate relative to the operating time of the distributed power source. The usage period of the distributed power source is the elapsed time since the introduction of the distributed power source, and the operating time of the distributed power source is the time during which the distributed power source is in operation within the above usage period. Operation means power generation if the distributed power source is a natural energy power generation device 13 or a fuel cell device 14, and charging or discharging if it is an energy storage device 15. Furthermore, if the degradation information acquired by the controller 31 includes the degradation rate relative to the number of times the distributed power source is operated, the degradation information may also include the frequency of operation of the distributed power source (for example, the number of times it is operated in one year). In addition, if the degradation information acquired by the controller 31 includes the degradation rate relative to the operating time of the distributed power source, the degradation information may also include the operating time of the distributed power source during a specified period (for example, the operating time in one year).

[0070] Furthermore, the above degradation rate includes an output degradation rate, which is the percentage decrease in the power supply (output) of the distributed power source due to degradation. In addition, the degradation rate of the energy storage device 15 may include a capacity degradation rate, which is the percentage decrease in power capacity due to degradation.

[0071] <Prediction of the breakdown of electricity consumption> Next, in the flow of the prediction method according to this embodiment, the controller 31 calculates the breakdown of the amount of electricity supplied to the electricity consumer 10 from each power supply source over several years, taking into account the deterioration of the distributed power supply system 12 (step S50). The breakdown of electricity consumption includes the amount of electricity supplied to the electricity consumer 10 from the renewable energy power generation device 13, the amount of electricity supplied to the electricity consumer 10 from the fuel cell device 14, the amount of electricity supplied to the electricity consumer 10 from the energy storage device 15, and the amount of grid power supplied to the electricity consumer 10.

[0072] Of the above breakdown, the amount of electricity supplied to the electricity consumer 10 from each distributed power source (natural energy power generation device 13, fuel cell device 14, energy storage device 15) can be predicted based on the introduction plan for the distributed power system 12 formulated in step S20 and the degradation information acquired in step S40. Here, the output degradation rate and capacity degradation rate of each distributed power source are mainly used from the degradation information.

[0073] For example, in the breakdown above, for the first year of the second phase, since each distributed power source has not yet deteriorated, the same amount of electricity as the first year of the second phase of the introduction plan formulated in step S20 is reflected. On the other hand, for the second year and beyond of the second phase, the amount of electricity reflected for each distributed power source is the amount of electricity obtained by subtracting the amount of electricity corresponding to the output deterioration rate (and capacity deterioration rate) of each distributed power source from the amount of electricity one year prior. As a result, the breakdown of the amount of electricity supplied from each distributed power source to the electricity consumer 10 decreases from the first to the fifth year of the same period due to the deterioration of each distributed power source.

[0074] Furthermore, of the above breakdown, the amount of grid power supplied to the electricity consumer 10 can be predicted by subtracting the amount of power supplied to the electricity consumer 10 by the distributed power system 12 from the amount of electricity demanded (amount of electricity consumed) by the electricity consumer 10. In this embodiment, since the electricity demand of the electricity consumer 10 is predicted to be the same every year, the breakdown of the amount of grid power supplied to the electricity consumer 10 will increase from the first to the fifth year within the same period due to the deterioration of each distributed power source. In other words, the CO2 emissions of the electricity consumer will increase due to the deterioration of each distributed power source. Note that the prediction that the electricity demand of the electricity consumer 10 will be the same every year is just an example and is not limited to this.

[0075] Figure 6 shows the breakdown of electricity supplied to electricity consumer 10 over several years (units of electricity are kHh, MHh, etc.). In the example shown in Figure 6, in the first period, all of the electricity supplied to electricity consumer 10 is grid electricity. From the second to the fourth period, the proportion of electricity supplied by the distributed power system 12 (renewable energy power generation device 13, fuel cell device 14, energy storage device 15) to the total electricity supplied to electricity consumer 10 gradually increases. However, from the second to the fourth period, due to the deterioration of the distributed power system 12, the amount of electricity supplied by the distributed power system 12 to electricity consumer 10 decreases little by little from the first to the fifth year of each period.

[0076] <Prediction of the First Indicator> Next, in the flow of the prediction method according to this embodiment, the controller 31 predicts a first indicator regarding the CO2 emissions of the electricity consumer 10 over several years after the introduction of the distributed power supply system 12, taking into account the deterioration of the distributed power supply system 12 (step S60). Note that "after the introduction of the distributed power supply system 12" may refer to the period after the start of the introduction of the distributed power supply system 12, or after the completion of the introduction of the distributed power supply system 12. However, in this embodiment, the period from the second period onward, which is after the start of the introduction of the distributed power supply system 12, is referred to as "after the introduction of the distributed power supply system 12".

[0077] Furthermore, the "first indicators relating to CO2 emissions of the electricity consumer 10" in this embodiment include the CO2 emissions of the electricity consumer 10, the amount of CO2 emission reduction, the electricity emission coefficient, the renewable energy rate, the amount of environmental value purchased, and CFP. In this embodiment, these first indicators are predicted in steps S61 to S66. The methods for predicting these indicators will be described in order below.

[0078] [CO2 Emission Prediction] First, the controller 31 predicts the CO2 emissions of the electricity consumer 10 over several years after the introduction of the distributed power system 12, taking into account the degradation of the distributed power system 12 (step S61). CO2 emissions are the CO2 emissions released during the process of supplying electricity. Based on the breakdown of the amount of electricity supplied to the electricity consumer 10 predicted in step S50 (i.e., the amount of grid power supplied to the electricity consumer 10 and the amount of electricity supplied to the electricity consumer 10 by each distributed power source), and the power emission coefficients of the grid power and each distributed power source over several years, the controller 31 predicts the CO2 emissions of each distributed power source.

[0079] The "electricity emission factor" mentioned above refers to the value obtained by dividing the amount of CO2 emitted in the process leading to electricity supply by the amount of electricity supplied. The electricity emission factors for grid power and each distributed power source over several years are stored in the memory 32 of the information terminal 30, and the controller 31 predicts the CO2 emissions of electricity consumers 10 based on the electricity emission factors for grid power and each distributed power source over several years obtained from the memory 32. In this embodiment, the memory 32 stores the electricity emission factors for grid power and each distributed power source "over several years." This is because the electricity emission factors for grid power and each distributed power source may fluctuate from year to year. For example, the electricity emission factor for grid power may fluctuate due to the updating of power generation equipment by power generators.

[0080] As described above, the CO2 emissions of the electricity consumer 10 in this embodiment are predicted based on the breakdown of the amount of electricity supplied to the electricity consumer 10 predicted in step S50. As previously stated, the breakdown of the amount of electricity supplied to the electricity consumer 10 in this embodiment is predicted based on the degradation information of each distributed power source. Therefore, it can be said that the CO2 emissions of the electricity consumer 10 in this embodiment are predicted taking into account the degradation of the distributed power system 12.

[0081] Figure 7 shows the projected CO2 emissions of electricity consumer 10 over several years (the units for CO2 emissions are kg-CO2 or t-CO2, etc.). In Figure 7, it is assumed that the power emission coefficient of the grid power is constant (the same applies to Figures 8 and onward). In the example shown in Figure 7, the projected CO2 emissions of electricity consumer 10 gradually decrease from the first to the fourth period. However, from the second to the fourth period, which is after the introduction of the distributed power system 12, the projected CO2 emissions of electricity consumer 10 increase from the first to the fifth year of each period. This is because, due to the deterioration of the distributed power system 12, the CO2 emissions of the distributed power system 12 increase, and the amount of electricity supplied to electricity consumer 10 from the grid power, which has high CO2 emissions, also increases (see Figure 6).

[0082] [Prediction of CO2 Emission Reduction] Next, the controller 31 predicts the amount of CO2 emission reduction for the electricity consumer 10 over several years after the introduction of the distributed power system 12, taking into account the deterioration of the distributed power system 12 (step S62). The "amount of CO2 emission reduction" here refers to the amount of CO2 emissions reduced in the process of supplying electricity to the electricity consumer 10. In this embodiment, the amount of CO2 emissions reduced by introducing the distributed power system 12 is considered the amount of CO2 emission reduction for the electricity consumer 10. The controller 31 predicts the amount of CO2 emission reduction for the electricity consumer 10 by subtracting the amount of CO2 emissions for the electricity consumer 10 predicted in step S61 from the amount of CO2 emissions assuming that all the electricity supplied to the electricity consumer 10 is grid power.

[0083] As described above, the amount of CO2 emission reduction for the electricity consumer 10 in this embodiment is predicted based on the CO2 emissions of the electricity consumer 10, taking into account the deterioration of the distributed power system 12. Therefore, it can be said that the prediction takes into account the deterioration of the distributed power system 12.

[0084] Figure 8 shows the projected CO2 emission reductions for electricity consumer 10 over several years (the units for CO2 emission reductions are kg-CO2, t-CO2, etc.). In the example shown in Figure 8, the projected CO2 emission reductions for electricity consumer 10 increase from the first to the fourth period. From the second to the fourth period, which is after the introduction of the distributed power system 12, the projected CO2 emission reductions for electricity consumer 10 decrease from the first to the fifth year of each period. This is because, due to the deterioration of the distributed power system 12, the amount of electricity supplied to electricity consumer 10 from the distributed power system 12, which has low CO2 emissions, decreases, while the amount of electricity supplied to electricity consumer 10 from the grid power, which has high CO2 emissions, increases (see Figure 6).

[0085] [Prediction of Power Emission Factor] Next, the controller 31 predicts the power emission factor of the power consumer 10 over several years after the introduction of the distributed power system 12, taking into account the deterioration of the distributed power system 12 (step S63). The controller 31 predicts the power emission factor of the power consumer 10 by dividing the CO2 emissions of the power consumer 10 predicted in step S61 by the amount of electricity demanded by the power consumer 10 (amount of electricity consumed). The amount of electricity demanded by the power consumer 10 is also the total amount of electricity supplied to the power consumer 10.

[0086] As described above, the power emission factor of the power consumer 10 in this embodiment is predicted based on the CO2 emissions of the power consumer 10 predicted in step S61. However, as previously stated, the CO2 emissions of the power consumer 10 predicted in step S61 take into account the degradation of the distributed power system 12. Therefore, it can be said that the power emission factor of the power consumer 10 in this embodiment is predicted taking into account the degradation of the distributed power system 12.

[0087] Figure 9 shows the predicted values ​​of the power emission coefficient for electricity consumer 10 over several years (the units of the power emission coefficient are kg-CO2 / kWh or t-CO2 / kWh, etc.). The trend of the predicted power emission coefficient for electricity consumer 10 shown in Figure 9 is similar to the trend of the predicted CO2 emissions for electricity consumer 10 shown in Figure 7. That is, the predicted power emission coefficient for electricity consumer 10 gradually decreases from the first to the fourth period, but from the second to the fourth period, the predicted power emission coefficient for electricity consumer 10 increases from the first to the fifth year of each period. The reason why the trend of the predicted power emission coefficient for electricity consumer 10 is the same as the trend of the predicted CO2 emissions for electricity consumer 10 is that, in this embodiment, the amount of electricity demanded by electricity consumer 10 used to predict the power emission coefficient for electricity consumer 10 is predicted to be the same every year (see Figure 6). The prediction that the amount of electricity demanded by electricity consumer 10 is the same every year is just one example and is not limited to this.

[0088] [Prediction of Renewable Energy Rate] Next, the controller 31 predicts the renewable energy rate of the electricity consumer 10 over several years after the introduction of the distributed power system 12, taking into account the degradation of the distributed power system 12 (step S64). The controller 31 predicts the renewable energy rate of the electricity consumer 10 by calculating the proportion of the electricity consumer 10's demand that is generated from renewable energy supplied to the electricity consumer 10 from the distributed power system 12. The proportion of the electricity consumer 10's demand that is generated from renewable energy supplied to the electricity consumer 10 from the distributed power system 12 can be calculated from the breakdown of the electricity supplied to the electricity consumer 10 predicted in step S50.

[0089] However, the amount of electricity generated from renewable energy supplied from the distributed power system 12 to the electricity consumer 10 does not include the amount of electricity supplied from the fuel cell device 14 to the electricity consumer 10 when the fuel cell device 14 generates electricity using gray hydrogen, but does include the amount of electricity supplied from the fuel cell device 14 to the electricity consumer 10 when the fuel cell device 14 generates electricity using green hydrogen. Since green hydrogen is hydrogen obtained by water electrolysis using electricity generated using renewable energy, it is included in renewable energy in this disclosure.

[0090] As described above, the renewable energy rate of the electricity consumer 10 in this embodiment is predicted based on the breakdown of the amount of electricity supplied to the electricity consumer 10 predicted in step S50. However, as previously mentioned, the breakdown of the amount of electricity in this embodiment is predicted based on the degradation information of each distributed power source. Therefore, it can be said that the renewable energy rate of the electricity consumer 10 in this embodiment is predicted taking into account the degradation of the distributed power source system 12.

[0091] In Figure 4, the white areas represent the predicted renewable energy rate (internal renewable energy rate) of electricity consumer 10. In the example shown in Figure 4, the predicted renewable energy rate is zero in the first period, and increases from the second to the fourth period. However, as the distributed power system 12 deteriorates, the amount of electricity generated from renewable energy supplied from the distributed power system 12 to electricity consumer 10 decreases. Therefore, in Figure 4, the renewable energy rate of electricity consumer 10 gradually decreases from the first to the fifth year of each period from the second to the fourth period.

[0092] [Prediction of Environmental Value Purchase Amount] Next, the controller 31 predicts the amount of environmental value purchased by the electricity consumer 10 over several years after the introduction of the distributed power system 12, taking into account the deterioration of the distributed power system 12 (step S65). Environmental value includes CO2 emission rights, CO2 emission reduction rights, and electricity certificates. The controller 31 may predict the purchase amount of all environmental value, or it may predict the purchase amount of some of the environmental value. The methods for predicting the purchase amounts of CO2 emission rights, CO2 emission reduction rights, and electricity certificates will be explained in order below.

[0093] For example, the government or local authorities may set CO2 emission limits for electricity consumers 10. If the CO2 emissions exceed these limits, electricity consumers 10 must purchase surplus emission limits from others as CO2 emission credits to cover the excess amount. In this embodiment, the controller 31 predicts the amount of CO2 emission credits to be purchased over several years when a distributed power system 12 is introduced.

[0094] The controller 31 predicts the amount of CO2 emission allowances to be purchased by subtracting the predicted CO2 emission value of the electricity consumer 10, which was predicted in step S61, from the target CO2 emission value of the electricity consumer 10. The target CO2 emission value may be the upper limit of the CO2 emission allowance, or it may be any other value. The memory 32 stores the target CO2 emission value, and the controller 31 retrieves the target CO2 emission value from the memory 32 and predicts the amount of CO2 emission allowances to be purchased.

[0095] Furthermore, in recent years, in addition to the aforementioned CO2 emission credits, there has been a growing movement to allow the buying and selling of CO2 emission reduction credits (CO2 emission reduction rights) resulting from CO2 emission reduction measures such as the introduction of energy-saving equipment and the use of renewable energy. Therefore, in this embodiment, the controller 31 predicts the amount of CO2 emission reduction credits to be purchased over several years when the distributed power supply system 12 is introduced.

[0096] The controller 31 predicts the amount of CO2 emission reduction credits to be purchased by subtracting the predicted CO2 emission reduction amount predicted in step S62 from the target CO2 emission reduction amount of the electricity consumer 10. The memory 32 stores the target CO2 emission reduction amount, and the controller 31 retrieves the target CO2 emission reduction amount from the memory 32 and predicts the amount of CO2 emission reduction credits to be purchased.

[0097] Alternatively, the controller 31 may predict the amount of CO2 emission allowances to be purchased by subtracting the predicted CO2 emission value of the electricity consumer 10, which was predicted in step S61, from the target CO2 emission value of the electricity consumer 10, and convert the predicted amount of CO2 emission allowances to be purchased into the amount of CO2 emission reduction allowances to be purchased. In other words, the controller 31 may predict the amount of CO2 emission reduction allowances to be purchased based on the target CO2 emission value and the predicted CO2 emission value of the electricity consumer 10.

[0098] Furthermore, electricity consumers 10 can purchase renewable energy certificates (electricity certificates) that prove that the grid electricity supplied by power generators 20 is generated from renewable energy sources (solar, wind, hydro, geothermal, etc.). By purchasing these electricity certificates, electricity consumers 10 can demonstrate that the electricity supplied by power generators 20 is generated from renewable energy sources. In this embodiment, the controller 31 predicts the amount of electricity certificates to be purchased over several years when the distributed power system 12 is introduced.

[0099] The controller 31 predicts the amount of electricity certificates to be purchased by subtracting the predicted renewable energy rate, which was predicted in step S64, from the target renewable energy rate set in step S10. In other words, the external renewable energy rate, which is the difference between the target renewable energy rate and the predicted renewable energy rate (internal renewable energy rate) shown in Figure 4, corresponds to the amount of electricity certificates to be purchased.

[0100] In the example shown in Figure 4, electricity consumer 10 purchases environmental value in the second through fourth phases (excluding the first year of the fourth phase). As a result, the sum of the renewable energy rate predicted in step S64 (internal renewable energy rate) and the renewable energy rate corresponding to the amount of electricity certificates purchased (external renewable energy rate) reaches the target renewable energy rate. On the other hand, since the first phase is before the introduction of the distributed power generation system 12, electricity consumer 10 does not purchase environmental value in the first phase. Note that electricity certificates can be mutually complementary with CO2 emission reduction rights.

[0101] As described above, the amount of environmental value purchased by the electricity consumer 10 in this embodiment is predicted based on the CO2 emissions, CO2 emission reductions, and renewable energy rate predicted in steps S61, S62, and S64, respectively. However, as mentioned above, all of these indicators take into account the deterioration of the distributed power system 12. Therefore, it can be said that the amount of environmental value purchased by the electricity consumer 10 in this embodiment is predicted taking into account the deterioration of the distributed power system 12.

[0102] [CFP Forecast] Next, the controller 31 forecasts the CFP of the products produced by the electricity consumer 10 over several years after the introduction of the distributed power system 12, taking into account the degradation of the distributed power system 12 (step S66). In recent years, a system has been spreading in which greenhouse gas emissions from goods and services throughout their entire lifecycle, from raw material procurement to disposal and recycling, are converted into CO2 and displayed as CFP. For example, when considering products produced at the production facilities (electricity consumption facilities 11) of the electricity consumer 10, the CFP is the sum of all CO2 emissions generated from material procurement, production, distribution, use, and disposal / recycling for each product.

[0103] In this embodiment, the controller 31 predicts the multi-year CO2 emissions for products produced by the power consumer 10 when a distributed power system 12 is introduced. The controller 31 predicts the CO2 emissions per product in the non-production phases of the lifecycle (material procurement, distribution, use, and waste recycling) by adding the predicted CO2 emissions per product in the non-production phases of the lifecycle to the predicted CO2 emissions per product in the production phase of the lifecycle.

[0104] The CO2 emissions per product during production within the lifecycle can be predicted by dividing the adjusted CO2 emissions by the number of products produced by the electricity consumer 10. The "adjusted CO2 emissions" are the CO2 emissions of the electricity consumer 10 predicted in step S61 minus the CO2 emissions corresponding to the amount of environmental value purchased, as predicted in step S65. However, the CO2 emissions per product during production may also be predicted by dividing the unadjusted CO2 emissions by the number of products produced by the electricity consumer 10. The "unadjusted CO2 emissions" are the CO2 emissions of the electricity consumer 10 predicted in step S61. Furthermore, predicted values ​​for CO2 emissions per product in items other than production within the lifecycle are stored in memory 32, and the controller 31 can retrieve this information from memory 32. The predicted values ​​for CO2 emissions per product in items other than production within the lifecycle may remain constant over several years, or they may change year by year.

[0105] As described above, the CFP of the products produced by the electricity consumer 10 in this embodiment is predicted based on the CO2 emissions of the electricity consumer 10 predicted in step S61 and the amount of environmental value purchased predicted in step S65. However, as previously mentioned, these indicators take into account the degradation of the distributed power system 12. Therefore, it can be said that the CFP of the products produced by the electricity consumer 10 in this embodiment is predicted taking into account the degradation of the distributed power system 12.

[0106] Figure 10 shows the projected CFP values ​​for products produced by electricity consumer 10 over several years (CFP units include kg-CO2 / product and t-CO2 / product). As shown in Figure 10, if the CO2 emissions per product in items other than production remain constant throughout the lifecycle, the projected CFP gradually decreases from the first to the fourth period. Furthermore, even if the actual CO2 emissions of electricity consumer 10 (uncorrected CO2 emissions) increase due to the deterioration of the distributed power system 12, the corrected CO2 emissions of electricity consumer 10 will not change within the same period by purchasing the corresponding environmental value, and therefore the CFP will also not change.

[0107] <Display of the First Indicator> Next, in the flow of the prediction method according to this embodiment, the controller 31 displays the first indicator (step S70). Specifically, the controller 31 displays information on the display 34 that indicates the first indicator (CO2 emissions, electricity emission coefficient, renewable energy rate, amount of environmental value purchased, CFP) predicted in step S60. Note that the display method of the first indicator is not limited, and the first indicator may be displayed as a graph or as numerical values. When step S70 is completed, the flow of the prediction method according to this embodiment is finished. The above is a description of the flow of the prediction method according to this embodiment.

[0108] As described above, the prediction method according to this embodiment predicts a first indicator of CO2 emissions from electricity consumers 10 over several years after the introduction of the distributed power system 12, taking into account the deterioration of the distributed power system 12. Therefore, by evaluating the introduction of the distributed power system 12 using this first indicator, a more appropriate evaluation from an environmental standpoint can be made compared to the conventional technology.

[0109] From the above description, many improvements and other embodiments of the disclosure will be apparent to those skilled in the art. Therefore, the above description should be construed as illustrative only and is provided for the purpose of teaching those skilled in the art the best mode of carrying out the disclosure. The details of its structure and / or function can be substantially modified without departing from the spirit of the disclosure.

[0110] One aspect of this disclosure can be used in a method for predicting indicators for evaluating the introduction of a distributed power supply system from an environmental perspective more appropriately than conventional technologies, a device for predicting said indicators, and a method for controlling an information terminal that displays said indicators.

[0111] 10: Electricity consumers 11: Electricity consumption equipment 12: Distributed power generation systems 13: Renewable energy power generation equipment 14: Fuel cell equipment 15: Energy storage equipment 20: Power generation operators 30: Information terminals 31: Controllers 32: Memory devices 33: Input devices 34: Displays

Claims

1. A prediction method for predicting a first indicator of CO2 emissions from electricity consumers over several years after the introduction of a distributed power system including at least one of a renewable energy power generation device and a fuel cell device, taking into account the deterioration of the distributed power system.

2. The prediction method according to claim 1, wherein the distributed power system includes the renewable energy power generation device, and the first indicator is predicted over several years after the introduction of the distributed power system, taking into account the deterioration of the renewable energy power generation device.

3. The prediction method according to claim 1, wherein the distributed power system includes the fuel cell device, and the first indicator is predicted over several years after the introduction of the distributed power system, taking into account the deterioration of the fuel cell device.

4. The prediction method according to claim 1, wherein the distributed power system includes the renewable energy power generation device and the fuel cell device, and the prediction method predicts the first indicator over several years after the introduction of the distributed power system, taking into account the deterioration of the renewable energy power generation device and the fuel cell device, respectively.

5. The prediction method according to any one of claims 1-4, wherein the distributed power system further includes an energy storage device, and the prediction method for the first indicator over several years after the introduction of the distributed power system also takes into account the deterioration of the energy storage device.

6. The prediction method according to any one of claims 1 to 5, wherein the first indicator includes CO2 emissions.

7. The prediction method according to claim 6, wherein the first indicator further includes a reduction in CO2 emissions.

8. The prediction method according to claim 6, wherein the first indicator further includes a power emission factor.

9. The prediction method according to any one of claims 1 to 8, wherein the first indicator includes the renewable energy rate.

10. The prediction method according to any one of claims 1 to 9, wherein the first indicator includes CFP.

11. The prediction method according to claim 6, which predicts the amount of CO2 emission rights or CO2 emission reduction rights to be purchased based on the target CO2 emission amount as a target value of a second indicator relating to the CO2 emissions of the electricity consumer over several years and the CO2 emission amount.

12. The prediction method according to claim 9, which predicts the amount of electricity certificates to be purchased based on the target renewable energy rate as a target value of the first indicator over several years and the renewable energy rate.

13. A prediction method according to any one of claims 1 to 12, comprising: formulating a multi-year introduction plan for the distributed power system based on the target value of a second indicator relating to the CO2 emissions of the electricity consumer over a multi-year period and a budget plan for reducing CO2 emissions; and predicting the first indicator over a multi-year period after the introduction of the distributed power system based on the introduction plan, taking into account the deterioration of the distributed power system.

14. A prediction device comprising: a storage device; a memory for storing information regarding the deterioration of a distributed power system including at least one of a renewable energy power generation device and a fuel cell device; and a controller for predicting a first indicator of CO2 emissions from electricity consumers over several years after the introduction of the distributed power system, taking into account the information regarding the deterioration of the distributed power system stored in the memory.

15. A method for controlling an information terminal, comprising the step of causing a display on the information terminal to show information indicating a first indicator of a power consumer's CO2 emissions over several years after the introduction of a distributed power system including an energy storage device and at least one of a renewable energy power generation device and a fuel cell device, wherein the first indicator is predicted taking into account the deterioration of the distributed power system.

16. The control method for an information terminal according to claim 15, further comprising the step of displaying on the display a plan for introducing the distributed power system, which is formulated based on at least one of a target value for a second indicator relating to the CO2 emissions of the electricity consumer and a budget plan for reducing CO2 emissions.

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