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

Abstract

This prediction method involves predicting, with consideration to the target reduction rate in the annual electricity demand of electricity consumers, a first indicator relating to the CO2 emissions of the electricity consumers over multiple years after the introduction of a distributed power system including at least one of a natural energy power generation device and a fuel cell device.

Description

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

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

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

[0003] Japanese Patent No. 7058254

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

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

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

[0007] Further, the prediction apparatus according to one aspect of the present disclosure includes: a storage that stores information related to a target reduction rate of annual required electric energy of an electric power consumer; and a controller that predicts a first index related to CO2 emissions of the electric power consumer over a plurality of years after the introduction of a distributed power supply system including at least one of a natural energy power generation apparatus and a fuel cell apparatus, in consideration of the information 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 a power consumer's CO2 emissions over several years since the introduction of a distributed power system including 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 target reduction rate of the power consumer's annual electricity demand.

[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 system. Furthermore, a control method for an information terminal according to one aspect of this disclosure has the effect of displaying indicators for a more appropriate evaluation from an environmental perspective compared to the prior art when introducing a distributed power 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] In this context, consumers who adopt the distributed power sources described above generally consume large amounts of electricity. In Japan, it is necessary to report actual and planned energy usage to government agencies, and there are also targets to strive for improving energy consumption intensity (electricity demand) by a predetermined percentage or more on an annual average over the medium to long term. Therefore, the inventors focused on the need to consider the target reduction rate (energy saving rate) of the consumer's future annual electricity demand when introducing a distributed power source system.

[0013] The first aspect of the prediction method predicts a first indicator of a power consumer's CO2 emissions 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 target reduction rate of the power consumer's annual electricity demand.

[0014] This forecasting method predicts a first indicator related to CO2 emissions from electricity consumers, taking into account the target reduction rate of the electricity consumers' annual electricity demand. Therefore, evaluating the introduction of distributed power generation systems by electricity consumers using this first indicator allows for a more appropriate evaluation from an environmental perspective compared to conventional technologies. Furthermore, the above forecasting method predicts the first indicator related to CO2 emissions from electricity consumers over several years after the introduction of the distributed power generation system. Therefore, it is possible to appropriately understand the trend of the above first indicator over several years, taking into account the target reduction rate of the electricity consumers' annual electricity demand, when introducing distributed power generation systems by electricity consumers.

[0015] A second aspect of the prediction method of the present disclosure further includes, in the first aspect of the prediction method, a distributed power system which further includes an energy storage device.

[0016] This prediction method allows for a more appropriate evaluation from an environmental perspective compared to conventional technologies regarding the introduction of distributed power generation systems, including energy storage devices, by electricity consumers.

[0017] The third aspect of the prediction method of this disclosure is the prediction method of the first or second aspect, wherein the first indicator includes CO2 emissions.

[0018] This prediction method allows for the prediction of appropriate CO2 emissions as the first indicator. Therefore, it enables a more appropriate evaluation from an environmental perspective of the introduction of distributed power generation systems by electricity consumers compared to conventional technologies.

[0019] A fourth aspect of the prediction method of this disclosure is a prediction method of any one of the first to third aspects, wherein the first indicator includes a reduction in CO2 emissions.

[0020] This prediction method allows for the prediction of an appropriate CO2 emission reduction as the first indicator. Therefore, it enables a more appropriate evaluation from an environmental perspective of the introduction of distributed power generation systems by electricity consumers compared to conventional technologies.

[0021] A fifth aspect of the prediction method of this disclosure is a prediction method in any one of the first to fourth aspects, wherein the first indicator includes the power emission coefficient.

[0022] This prediction method allows for the prediction of an appropriate power emission factor as the first indicator. Therefore, it enables 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" refers to the value obtained by dividing the amount of CO2 emitted during the process of supplying electricity by the amount of electricity supplied.

[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 the renewable energy rate.

[0024] This prediction method allows for the prediction of an appropriate renewable energy rate as the first indicator. Therefore, it enables 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 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.

[0025] 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 the excess amount as CO2 emission credits from other consumers. There is also a system in place to buy and sell CO2 emission reduction credits (CO2 emission reduction rights) for CO2 emission reductions achieved through measures such as CO2 emission reduction. Therefore, electricity consumers may purchase CO2 emission credits or CO2 emission reduction credits if their CO2 emissions exceed predetermined target values.

[0026] Therefore, the seventh aspect of the present 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 related to CO2 emissions over multiple years for electricity consumers, and the above CO2 emission amount, in the prediction method of the third aspect. Furthermore, the eighth aspect of the present disclosure predicts the amount of CO2 emission rights or CO2 emission reduction rights to be purchased based on the target CO2 emission reduction amount as a target value of a second indicator related to CO2 emissions over multiple years for electricity consumers, and the above CO2 emission reduction amount, in the prediction method of the fourth aspect.

[0027] The above prediction method allows for a more appropriate environmental assessment of the introduction of distributed power generation systems by electricity consumers compared to conventional technologies, in order to predict the amount of CO2 emission credits or CO2 emission reduction credits to be purchased.

[0028] Here, 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.). By purchasing these electricity certificates, electricity consumers can demonstrate that the electricity supplied by power generators is generated from renewable energy sources. Therefore, electricity consumers may purchase electricity certificates if their renewable energy rate falls below a predetermined target value.

[0029] Therefore, the prediction method of the ninth aspect of this disclosure predicts the amount of electricity certificates to be purchased based on the target renewable energy rate as a target value for a second indicator relating to CO2 emissions over multiple years of electricity consumers and the above renewable energy rate, in the prediction method of the sixth aspect.

[0030] This prediction method allows for a more appropriate environmental assessment of electricity consumers' adoption of distributed power generation systems compared to conventional technologies, in order to predict the amount of electricity certificates to be purchased.

[0031] Traditionally, indicators for evaluating distributed power systems have been calculated based on the assumption that the system would be implemented all at once. However, the inventors focused on the possibility that distributed power systems may be implemented in stages over several years. For example, considering factors such as the gradual implementation of CO2 emission regulations and the high costs involved in implementing distributed power systems, it may be preferable to implement a distributed power system in stages over several years rather than all at once.

[0032] Therefore, the prediction method of the tenth aspect of this disclosure, in any one of the prediction methods of the first to ninth aspects, formulates a multi-year introduction plan for a distributed power system based on the target value of a second indicator related to the CO2 emissions of electricity consumers over a multi-year period and a budget plan for reducing CO2 emissions, and predicts 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 target reduction rate of the annual electricity demand of electricity consumers.

[0033] This forecasting method predicts a first indicator over multiple years, based on a multi-year deployment plan for distributed power systems, taking into account the target reduction rate of annual electricity demand by power consumers. Therefore, evaluating the deployment of distributed power systems by power consumers using this first indicator allows for a more appropriate assessment from an environmental perspective compared to conventional technologies. Furthermore, it allows for an accurate understanding of the trend of the first indicator over multiple years, taking into account the target reduction rate of annual electricity demand by power consumers.

[0034] A prediction device according to an eleventh aspect of the present disclosure includes a memory that stores information regarding a target reduction rate for an electricity consumer's annual electricity demand, and a controller that predicts a first indicator of a electricity consumer's CO2 emissions over several years since 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 information stored in the memory.

[0035] This prediction device forecasts a first indicator of CO2 emissions from electricity consumers, taking into account the target reduction rate of the electricity consumers' annual electricity demand. Therefore, evaluating the introduction of distributed power generation systems by electricity consumers using this first indicator allows for a more appropriate evaluation from an environmental perspective compared to conventional technologies. Furthermore, the prediction device forecasts the first indicator of CO2 emissions from electricity consumers over several years after the introduction of the distributed power generation system. Therefore, it is possible to appropriately understand the trend of the first indicator over several years, taking into account the target reduction rate of the electricity consumers' annual electricity demand, when introducing distributed power generation systems by electricity consumers.

[0036] A control method for an information terminal in a twelfth aspect of the present disclosure includes the step of displaying on a display of the information terminal information indicating a first indicator of a power consumer's CO2 emissions over several years since the introduction of a distributed power system including 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 target reduction rate of the power consumer's annual electricity demand.

[0037] In this control method, information indicating a first indicator of a power consumer's CO2 emissions, taking into account the target reduction rate of the power consumer's annual electricity demand, is displayed on the display unit. Therefore, power consumers who are users of the information terminal and propose the introduction of a distributed power system, or power consumers who are presented with the information displayed on the display unit by the proposer, can evaluate the introduction of a distributed power system using this first indicator, thereby enabling a more appropriate evaluation from an environmental perspective compared to conventional technology.

[0038] Furthermore, the above control method predicts the first indicator over several years following the introduction of the distributed power system. Therefore, it is possible to appropriately understand the trend of the first indicator over several years, taking into account the target reduction rate of the electricity consumer's annual electricity demand, in relation to the introduction of a distributed power system by the electricity consumer.

[0039] A control method for an information terminal according to the 13th aspect of this disclosure includes a step, in the control method for an information terminal according to the 12th aspect, of displaying on the display a plan for introducing a distributed power system, which is formulated based on at least one of a target value for a second indicator related to the CO2 emissions of electricity consumers and a budget plan for reducing CO2 emissions.

[0040] This control method displays the distribution power system implementation plan on a display unit. Therefore, the proposer or electricity consumer can easily understand the distribution power system implementation plan.

[0041] The following describes specific examples of the above embodiments of this disclosure with reference to the attached drawings. The specific examples described below are all examples of the above embodiments of this disclosure. Therefore, the shapes, numerical values, components, arrangement positions of components, and connection configurations shown below do not limit the scope of the claims unless they are described in the claims.

[0042] Furthermore, among the components described below, those not described in the independent claim representing the highest-level concept of this disclosure will be described as optional components. Also, in the drawings, components with the same reference numeral may not be described. The drawings are schematic representations of each component for ease of understanding, and the shape and dimensional ratios may not be accurately represented.

[0043] Furthermore, in the operation of the apparatus, the order of the processes may be changed or known processes may be added as needed.

[0044] (Example of Installation of Distributed Power System) First, an example of installation of a distributed power system 12 by a power consumer 10 will be described. Figure 1 is a diagram showing an example of installation of a distributed power system 12. Figure 1(a) shows a mode of power supply to the power consumer 10 before the start of installation of the distributed power system 12. The power consumer 10 of the present embodiment is a factory that produces products, and the power consumer 10 includes power consumption equipment 11 such as production equipment for producing products. In the present embodiment, as shown in FIG. 1(a), before the start of installation of the distributed power system 12, power is supplied to the power consumption equipment 11 of the power consumer 10 only from a power generation business operator 20 such as an electric power company. Note that, hereinafter, the power supplied from the power generation business operator 20 to the power consumer 10 is referred to as "grid power".

[0045] Figure 1(b) shows a mode of power supply to the power consumer 10 in an intermediate stage of installation of the distributed power system 12. In the present embodiment, as shown in FIG. 1(b), in the intermediate stage of installation of the distributed power system 12, power is supplied not only from the grid power but also from the distributed power system 12 to the power consumption equipment 11 of the power consumer 10. Note that the distributed power system 12 includes distributed power sources such as a natural energy power generation device 13, a fuel cell device 14, and a power 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-described distributed power sources.

[0046] The natural energy power generation device 13 is a device that generates power using natural energy, and corresponds to a photovoltaic power generation device, a wind power generation device, or the like. Further, the fuel cell device 14 is a device that generates power through a chemical reaction between hydrogen as a fuel and an oxide such as oxygen. There are multiple types of hydrogen that serve 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 power storage device 15 is a device that temporarily stores and supplies power generated by other devices.

[0047] Fig. 1(c) shows a mode of power supply to the power consumer 10 after the completion of installation of the distributed power supply system 12. In the present embodiment, as shown in Fig. 1(c), after the completion of installation of the distributed power supply system 12, power is supplied to the power consumption facility 11 of the power consumer 10 only from the distributed power supply system 12. However, even after the completion of installation of the distributed power supply system 12, power may be supplied to the power consumption facility 11 of the power consumer 10 from both the power generation business operator 20 and the distributed power supply system 12 in some cases.

[0048] (Information Terminal) Next, the information terminal 30 used in the prediction method according to the present embodiment will be described. Fig. 2 is a conceptual diagram of the information terminal 30. The information terminal 30 includes a prediction device 35, an input device 33, and a display device 34. The prediction device 35 includes a controller 31 and a storage device 32.

[0049] The controller 31 includes an arithmetic processing unit and a storage unit that stores a control program. The arithmetic processing unit is, for example, a processor, and the storage unit is, for example, a volatile memory. The controller 31 may be a single controller, or may be a controller group in which a plurality of controllers cooperate. The storage device 32 is, for example, a non-volatile memory, and is a device that stores various programs and information. The input device 33 is, for example, a keyboard operated by an operator, and is a device for inputting various types of information. The display device 34 is, for example, a monitor, and is a device that displays various types of information.

[0050] In the present embodiment, the storage device 32 stores information related to a target reduction rate of annual power demand of the power consumer 10 (hereinafter may be referred to as "energy saving rate"). The controller 31 predicts a first index related to CO₂ emissions of the power consumer 10 over a plurality of years after the introduction of the distributed power supply system 12 in consideration of the information stored in the storage device 32.

[0051] Here, the "energy saving rate" can be represented, for example, by an annual reduction rate (%) of power demand with respect to the previous year's power demand of the power consumer 10. The "energy saving rate" may be, for example, around approximately 1%, but is not limited thereto.

[0052] Furthermore, if energy-saving rates are set by dividing the next several decades into multiple periods of predetermined number of years, appropriate values ​​may be set for each individual period.

[0053] For example, the "energy saving rate" may be set so that energy saving of approximately 0.5% is achieved in stages as each period progresses, such as "0%" in the first period, "0.5%" in the second period, "1%" in the third period, and "1.5%" in the fourth period.

[0054] The information terminal 30 is connected to the evaluation system 40 via a network such as the Internet. The evaluation system 40 is a system operated by an external organization and can calculate the environmental contribution, which will be described later. The information terminal 30 may also be connected to an information server (not shown in the figure) which may perform 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 via communication.

[0055] (Flowchart of the prediction method) Next, the prediction method according to this embodiment will be described. The prediction method according to this embodiment is a method that can evaluate the introduction of the distributed power system 12 from an environmental perspective. Specifically, in the prediction method according to this embodiment, a first indicator regarding the CO2 emissions of the electricity consumer 10 over several years after the introduction of the distributed power system 12 is predicted, taking into account the target reduction rate of the annual electricity demand of the electricity consumer 10. This will be explained in detail below.

[0056] <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 S1). Specifically, the operator sets target values ​​for a second indicator related to the CO2 emissions of the electricity consumer 10 over several years. The second indicator is, for example, CO2 emissions, CO2 emission reduction, electricity emission coefficient, renewable energy rate, etc.

[0057] However, the above is merely an example and is not limited to this example. The worker may set a target value for a second indicator regarding the CO2 emissions of the electricity consumer 10 over a single year. In other words, the target value for the CO2 emission indicator for evaluating the distributed power system 12 may be calculated on the premise that the distributed power system 12 is introduced all at once over a single year, rather than being introduced in stages over several years.

[0058] The following example illustrates a case where the worker sets a target value for a second indicator related to the multi-year CO2 emissions of electricity consumer 10.

[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 total electricity supplied or consumed. 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 over multiple years. 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 the 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 second 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 second 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 (e.g., 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 operator formulates a multi-year implementation plan for the distributed power system 12 (step S2). In this embodiment, the operator 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 S1 and the multi-year budget plan for CO2 emission reduction. The multi-year implementation plan for the distributed power system 12 may 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 devices among the renewable energy power generation device 13, fuel cell device 14, and energy storage device 15 has a predetermined service life and requires replacement every few years, a multi-year introduction plan for the distributed power system 12 that includes an introduction plan for the replacement of that device may be formulated.

[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 target CO2 emissions.

[0067] The above describes a multi-year implementation plan for the distributed power system 12, but is not limited to this. A single-year implementation plan for the distributed power system 12 may be formulated based on the single-year target value (target renewable energy rate) of the second indicator set in step S1 and the single-year budget plan for CO2 emission reduction. In other words, the above implementation plan may be formulated on the premise that the distributed power system 12 will be implemented all at once in a single year.

[0068] <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 S3). In this embodiment, the operator inputs the data related to the multi-year implementation plan for the distributed power system 12 formulated in step S2 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.

[0069] <Prediction of the breakdown of electricity consumption> Next, in the flow of the prediction method according to this embodiment, the controller 31 predicts the breakdown of the amount of electricity supplied to the electricity consumer 10 from each power supply source over several years (step S4). This 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.

[0070] In predicting the breakdown of electricity supplied to the electricity consumer 10, the controller 31 first predicts or obtains 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, and the amount of electricity supplied to the electricity consumer 10 from the energy storage device 15, based on the data regarding the introduction plan of the distributed power supply system 12 entered by the operator in step S3. Furthermore, the controller 31 predicts the amount of grid power supplied to the electricity consumer 10 by subtracting the amount of electricity supplied to the electricity consumer 10 by the distributed power supply system 12 (renewable energy power generation device 13, fuel cell device 14, and energy storage device 15) from the electricity consumer 10's demand amount (amount of electricity consumed). In this embodiment, the electricity demand amount of the electricity consumer 10 is predicted to gradually decrease, taking into account the target reduction rate of the electricity consumer 10's annual demand amount. This is for the following reasons.

[0071] Electricity consumers 10 that introduce a distributed power generation system 12 generally consume large amounts of electricity. In this case, in Japan, it is necessary to report actual and planned energy usage to government agencies, etc., and there is a target to strive for improving the energy consumption intensity (amount of electricity demanded) by a predetermined percentage or more on an annual average over the medium to long term. For this reason, when introducing a distributed power generation system 12, it may be desirable to set a target reduction rate (energy saving rate) for the consumer's future annual electricity demand.

[0072] Figure 6 shows a breakdown of the amount of electricity supplied to electricity consumer 10 over several years (units of electricity are kHh, MHh, etc.). Of the two adjacent bar graphs in Figure 6, the left bar graph shows the annual electricity demand of electricity consumer 10.

[0073] In this example, the annual electricity demand of electricity consumer 10 is calculated when the annual rate of reduction (%) of electricity demand compared to the previous year's electricity demand for electricity consumer 10 is "0%" in the first period, "0.5%" in the second period, "1%" in the third period, and "1.5%" in the fourth period. As a method for calculating the annual electricity demand of electricity consumer 10 using such an annual rate of reduction (%) of electricity demand, for example, one method is to calculate the total amount of electricity for each year in the above period, and one method is to calculate the amount of electricity for the first year and the last year in each period, and then calculate the amount of electricity for the years in between using linear interpolation from the amount of electricity for the first year and the last year. The latter method of calculating electricity takes less time than the former method, so the latter method is used in this example.

[0074] In Figure 6, the rightmost of the two adjacent bar graphs shows the breakdown of the amount of electricity supplied to electricity consumer 10 in order to meet the annual electricity demand of electricity consumer 10.

[0075] In the example shown in Figure 6, in the first phase, all of the electricity supplied to the electricity consumer 10 is from the grid. From the second to the fourth phase, the proportion of electricity supplied to the electricity consumer 10 from the distributed power system 12 (natural energy power generation device 13, fuel cell device 14, energy storage device 15) gradually increases, and in the fourth phase, all of the electricity supplied to the electricity consumer 10 is supplied from the distributed power system 12.

[0076] <First Prediction> Next, in the flow of the prediction method according to this embodiment, the controller 31 performs a first prediction (step S5). In this embodiment, a first indicator for evaluating the introduction of the distributed power system 12 is predicted. In the first prediction, predictions are made for the first CO2 emissions, the first CO2 emission reduction, the first power emission coefficient, and the first renewable energy rate among the first indicators. The prediction methods for these indicators will be described in order below.

[0077] [First CO2 Emissions] In this embodiment, the first CO2 emissions are also called unadjusted CO2 emissions and represent the amount of CO2 emitted during the process of supplying electricity. In this embodiment, the controller 31 predicts the first CO2 emissions of the electricity consumer 10 over several years after the introduction of the distributed power supply system 12, taking into account the target reduction rate of the annual electricity demand of the electricity consumer 10. These first CO2 emissions of the electricity consumer 10 can be predicted based on the breakdown of the amount of electricity supplied to the electricity consumer 10 predicted in step S4 (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), the power emission coefficient of the grid power, and the power emission coefficient of each distributed power source.

[0078] In this context, "electricity emission factor" refers to the value obtained by dividing the amount of CO2 emitted during the process of supplying electricity by the amount of electricity supplied. The electricity emission factors for grid power and each distributed power source are stored in the memory 32 of the information terminal 30, and the controller 31 predicts the first CO2 emission amount based on the electricity emission factors for grid power and each distributed power source 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 multiple 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.

[0079] Furthermore, as mentioned above, there are multiple types of hydrogen, which are the fuel for the fuel cell device 14. Therefore, the power emission coefficient of the fuel cell device 14 stored in the memory 32 will differ depending on the type of hydrogen used for power generation. In addition, it is possible to change the type of hydrogen after the introduction of the fuel cell device 14. In this case, a plan for switching the type of hydrogen used for power generation by the fuel cell device 14 may be formulated based on the budget plan of the distributed power system 12, and the memory 32 may store the power emission coefficient of the fuel cell device 14 based on the switching plan. This allows the controller 31 to predict the first CO2 emissions corresponding to the change in the type of hydrogen. Note that the plan for switching the type of hydrogen used for power generation by the fuel cell device 14 may be formulated by an operator or by the controller 31.

[0080] Figure 7 shows the predicted CO2 emissions of electricity consumer 10 over several years (the unit of CO2 emissions is kg-CO2 or t-CO2, etc.). Of the two adjacent bar graphs in Figure 7, the left bar graph shows the predicted value of the first CO2 emissions. Figure 7 also shows the CO2 emissions assuming that all the electricity supplied to electricity consumer 10 is grid power, indicated by a dashed line. In the example shown in Figure 7, the predicted value of the first CO2 emissions gradually decreases from the first to the fourth period, and in the fourth period, the predicted value of the first CO2 emissions is zero. In this embodiment, the first CO2 emissions are predicted taking into account the change in the power emission coefficient of grid power. Therefore, even in the first period, when all the electricity supplied to electricity consumer 10 is grid power, the predicted value of the first CO2 emissions changes.

[0081] [First CO2 Emission Reduction Amount] In this embodiment, the first CO2 emission reduction amount is also called the unadjusted CO2 emission reduction amount, and is the amount of CO2 emissions reduced by implementing CO2 emission reduction measures. In this embodiment, the first CO2 emission reduction amount of the electricity consumer 10 over several years after the introduction of the distributed power system 12 is predicted considering the target reduction rate of the annual electricity demand of the electricity consumer 10. The first CO2 emission reduction amount can be predicted by subtracting the first CO2 emissions amount described above from the CO2 emissions amount assuming that all the electricity supplied to the electricity consumer 10 is grid power (CO2 emissions corresponding to the dashed line in Figure 7).

[0082] Figure 8 shows the projected CO2 emission reductions for electricity consumers 10 over several years (the units for CO2 emission reductions are kg-CO2 or t-CO2, etc.). Of the two adjacent bar graphs in Figure 8, the left bar graph shows the projected value of the first CO2 emission reduction. In the example shown in Figure 8, the projected value of the first CO2 emission reduction is zero in the first period, increases in the second period compared to the first period, increases in the third period compared to the second period, and is about the same as the third period in the fourth period. The reason why the projected value of the first CO2 emission reduction is about the same in the third and fourth periods is that the CO2 emission reduction of grid power, which is used as the basis for projecting the first CO2 emission reduction, decreases year by year.

[0083] [First Power Emission Factor] In this embodiment, the first power emission factor is also called the unadjusted power emission factor and is the power emission factor for the entire power consumer 10. In this embodiment, the controller 31 predicts the first power emission factor of the power consumer 10 over several years since the introduction of the distributed power supply system 12, taking into account the target reduction rate of the annual power demand of the power consumer 10. The first power emission factor can be predicted by dividing the first CO2 emissions of the power consumer 10 described above by the amount of power demanded by the power consumer 10. The amount of power demanded by the power consumer 10 is also the total amount of power supplied to the power consumer 10.

[0084] 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 and t-CO2 / kWh, etc.). Of the two adjacent bar graphs in Figure 9, the left bar graph shows the predicted value of the first power emission coefficient. In addition, Figure 9 also shows the first power emission coefficient as a dashed line, assuming that all the electricity supplied to electricity consumer 10 is grid power. The trend of the predicted value of the first power emission coefficient shown in Figure 9 is similar to the trend of the predicted value of the first CO2 emissions shown in Figure 7. That is, the predicted value of the first power emission coefficient gradually decreases from the first to the fourth period, and in the fourth period, the predicted value of the first power emission coefficient is zero. Thus, the reason why the trend of the predicted value of the first power emission coefficient for power consumer 10 follows the same trend as the trend of the predicted value of the first CO2 emissions for power consumer 10 is that, in this embodiment, the target reduction rate of the amount of electricity demanded by power consumer 10 used to predict the first power emission coefficient for power consumer 10 is a small value of about 1% (see Figure 6).

[0085] [First Renewable Energy Rate] In this embodiment, the first renewable energy rate is also called the internal renewable energy rate or the unadjusted renewable energy rate, and refers to the proportion of electricity generated from renewable energy among the amount of electricity supplied to the electricity consumer 10. In this embodiment, the controller 31 predicts the first renewable energy rate of the electricity consumer 10 over several years after the introduction of the distributed power system 12, taking into account the target reduction rate of the annual electricity demand of the electricity consumer 10. The first renewable energy rate of the electricity consumer 10 can be predicted by calculating the proportion of electricity generated from renewable energy supplied from the distributed power system 12 among the amount of electricity supplied to the electricity consumer 10. However, the amount of electricity generated from renewable energy mentioned above does not include the amount of electricity generated by the fuel cell device 14 if the fuel cell device 14 uses gray hydrogen, but it does include the amount of electricity generated by the fuel cell device 14 if the fuel cell device 14 uses green hydrogen. Note that green hydrogen is hydrogen obtained by water electrolysis using electricity generated using renewable energy, and therefore in this disclosure, it is included in renewable energy.

[0086] In the bar graph shown in Figure 4, the white areas represent the predicted values ​​for the first renewable energy rate. In the example shown in Figure 4, the predicted value for the first renewable energy rate is zero in the first period, and it increases from the second to the fourth period. In the example shown in Figure 4, the first renewable energy rate does not reach the target renewable energy rate in the second and third periods.

[0087] <Secondary Forecast> Next, in the forecasting method flow according to this embodiment, the controller 31 performs a secondary forecast (step S6). In the secondary forecast, the purchase quantities of CO2 emission rights, CO2 emission reduction rights, and electricity certificates are predicted from the first indicators. Hereinafter, CO2 emission rights, CO2 emission reduction rights, and electricity certificates will be referred to as "environmental value". In the secondary forecast, the purchase quantities of all environmental values ​​may be predicted, or the purchase quantities of some environmental values ​​may be predicted. The method for predicting the purchase quantities of each environmental value will be explained below.

[0088] [CO2 Emission Rights] For example, a government or local authority may set CO2 emission limits for electricity consumers 10. If an electricity consumer 10's CO2 emissions exceed these limits, the consumer 10 must purchase the excess amount as CO2 emission rights from others. Therefore, electricity consumers 10 may also purchase target CO2 emission rights.

[0089] Therefore, in this embodiment, CO2 emission allowances are predicted based on the target CO2 emission and CO2 emission values, which are the target values ​​of a second indicator related to the CO2 emissions of the electricity consumer 10 over several years. In other words, the controller 31 predicts the amount of CO2 emission allowances to be purchased over several years since the introduction of the distributed power system 12, taking into account the target reduction rate of the electricity consumer 10's annual electricity demand. The controller 31 predicts the amount of CO2 emission allowances to be purchased by subtracting the first predicted value of CO2 emissions predicted in the primary forecast from the target CO2 emission of the electricity consumer 10. The target CO2 emission 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, and the controller 31 retrieves the target CO2 emission from the memory 32 and predicts the amount of CO2 emission allowances to be purchased.

[0090] [CO2 Emission Reduction Rights] In recent years, in addition to the CO2 emission rights mentioned above, there has been a growing movement to allow the buying and selling of CO2 emission reductions achieved by implementing CO2 emission reduction measures such as the introduction of energy-saving equipment and the use of renewable energy, as CO2 emission reduction rights (credits). Therefore, electricity consumers 10 may also purchase target CO2 emission reduction rights.

[0091] Therefore, in this embodiment, the amount of CO2 emission reduction rights to be purchased is predicted based on the target CO2 emission reduction amount, which is the target value of the second indicator related to the CO2 emissions of the electricity consumer 10 over several years, and the actual CO2 emission reduction amount. In other words, the controller 31 predicts the amount of CO2 emission reduction rights to be purchased over several years since the introduction of the distributed power system 12, taking into account the target reduction rate of the electricity consumer 10's annual electricity demand. The controller 31 predicts the amount of CO2 emission reduction rights to be purchased by subtracting the predicted value of the first CO2 emission reduction amount predicted in the primary forecast from the predetermined target CO2 emission reduction amount. The memory 32 stores the target CO2 emission reduction amount, and the controller 31 obtains the target CO2 emission reduction amount from the memory 32 and predicts the amount of CO2 emission reduction rights to be purchased.

[0092] However, the above is merely an example and is not limited to this example. For example, the controller 31 may predict the amount of CO2 emission allowances to be purchased by subtracting the predicted value of the first CO2 emission predicted in the initial forecast from the target CO2 emission 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 of the electricity consumer 10 and the predicted value of the first CO2 emission, or it may predict the amount of CO2 emission allowances to be purchased based on the target CO2 emission reduction of the electricity consumer 10 and the predicted value of the first CO2 emission reduction.

[0093] [Electricity Certificates] Here, electricity consumer 10 can purchase renewable energy electricity certificates (electricity certificates) that prove that the grid electricity supplied by power generator 20 is electricity generated from renewable energy sources (solar, wind, hydro, geothermal, etc.). By purchasing these electricity certificates, electricity consumer 10 can demonstrate that the electricity supplied by power generator 20 is generated from renewable energy sources. For this reason, electricity consumer 10 may purchase electricity certificates.

[0094] Therefore, in this embodiment, the amount of electricity certificates to be purchased is predicted based on the target renewable energy rate and the renewable energy rate, which are the target values ​​of the second indicator related to CO2 emissions of the electricity consumer 10 over several years. In other words, the controller 31 predicts the amount of electricity certificates to be purchased over several years since the introduction of the distributed power system 12, taking into account the target reduction rate of the annual electricity demand of the electricity consumer 10. The controller 31 predicts the amount of electricity certificates to be purchased by subtracting the predicted value of the first renewable energy rate predicted in the primary prediction from the target renewable energy rate set in step S1. In other words, the external renewable energy rate, which is the difference between the target renewable energy rate and the predicted value of the first renewable energy rate shown in Figure 4, corresponds to the amount of electricity certificates to be purchased.

[0095] In this embodiment, electricity consumer 10 purchases environmental value in the second and third phases. However, since the introduction of the distributed power system 12 has not yet begun in the first phase, electricity consumer 10 does not purchase environmental value in the first phase. Furthermore, in the fourth phase, the first CO2 emissions, the first CO2 emission reduction, and the first renewable energy rate have all reached their target values; therefore, electricity consumer 10 does not purchase environmental value in the fourth phase.

[0096] <Third-order prediction> Next, in the flow of the prediction method according to this embodiment, the controller 31 performs a third-order prediction (step S7). In the third-order prediction, the second CO2 emissions, the second CO2 emission reduction, the second electricity emission coefficient, and the second renewable energy rate are predicted from the first indicators. The prediction methods for these indicators will be explained in order below.

[0097] [Second CO2 Emissions] In this embodiment, the second CO2 emissions are also called adjusted CO2 emissions and are a modified version of the first CO2 emissions. In this embodiment, the controller 31 predicts the second CO2 emissions of the electricity consumer 10 over several years after the introduction of the distributed power system 12, taking into account the target reduction rate of the electricity consumer 10's annual electricity demand. The second CO2 emissions can be predicted based on the purchase amount of environmental values ​​(CO2 emission rights, CO2 emission reduction rights, and electricity certificates) predicted in the second prediction. More specifically, the second CO2 emissions can be predicted by subtracting the CO2 emissions corresponding to the purchase amount of each environmental value predicted in the second prediction from the first CO2 emissions predicted in the first prediction.

[0098] In Figure 7, the rightmost of the two adjacent bar graphs shows the predicted value of the second CO2 emission. As shown in Figure 7, in this embodiment, environmental value is purchased in the second and third phases, so the predicted value of the second CO2 emission (adjusted CO2 emission) in the second and third phases is less than the predicted value of the first CO2 emission (unadjusted CO2 emission).

[0099] [Second CO2 Emission Reduction] In this embodiment, the second CO2 emission reduction is also called the adjusted CO2 emission reduction, and is a modified version of the first CO2 emission reduction. In this embodiment, the controller 31 predicts the second CO2 emission reduction of the electricity consumer 10 over several years after the introduction of the distributed power supply system 12, taking into account the target reduction rate of the electricity consumer 10's annual electricity demand. The second CO2 emission reduction can be predicted based on the purchase amount of environmental value predicted in the second prediction. More specifically, the second CO2 emission reduction can be predicted by adding the CO2 emission reduction amount corresponding to the purchase amount of each environmental value predicted in the second prediction to the predicted value of the first CO2 emission reduction predicted in the first prediction.

[0100] In Figure 8, the rightmost of the two adjacent bar graphs shows the predicted value of the second CO2 emission reduction. As shown in Figure 8, in this embodiment, environmental value is purchased in the second and third phases, so the predicted value of the second CO2 emission reduction (adjusted CO2 emission reduction) in the second and third phases is greater than the predicted value of the first CO2 emission reduction (unadjusted CO2 emission reduction).

[0101] [Second Power Emission Factor] The second power emission factor in this embodiment is also called the adjusted power emission factor and is a modified version of the first CO2 emission reduction. In this embodiment, the controller 31 predicts the second power emission factor of the power consumer 10 over several years after the introduction of the distributed power system 12, taking into account the target reduction rate of the power consumer 10's annual power demand. The second power emission factor can be predicted based on the amount of environmental value purchased predicted in the second prediction. More specifically, the second power emission factor can be predicted by dividing the second CO2 emission amount predicted based on the amount of environmental value purchased by the power consumer 10's power demand.

[0102] In Figure 9, the rightmost of the two adjacent bar graphs shows the predicted value of the second power emission factor. As shown in Figure 9, in this embodiment, environmental value is purchased in the second and third phases, so the predicted value of the second power emission factor (adjusted power emission factor) in the second and third phases is smaller than the predicted value of the first power emission factor (unadjusted power emission factor).

[0103] [Second Renewable Energy Rate] In this embodiment, the second renewable energy rate is also called the adjusted renewable energy rate, and is a modified version of the first renewable energy rate. In this embodiment, the controller 31 predicts the second renewable energy rate of the electricity consumer 10 over several years after the introduction of the distributed power system 12, taking into account the target reduction rate of the electricity consumer 10's annual electricity demand. The second renewable energy rate can be predicted based on the amount of environmental value purchased predicted in the second forecast. More specifically, the second renewable energy rate can be predicted by adding the renewable energy rate (external renewable energy rate) corresponding to the amount of environmental value purchased predicted in the second forecast to the first renewable energy rate (internal renewable energy rate) predicted in the first forecast. Note that electricity certificates can be mutually complementary with CO2 emission reduction rights.

[0104] In the bar graph in Figure 4, the shaded portion represents the external renewable energy rate. The value obtained by adding the external renewable energy rate to the predicted value of the first renewable energy rate (the white portion) is the predicted value of the second renewable energy rate. As shown in Figure 4, in this embodiment, in the second and third phases, the predicted value of the first renewable energy rate (unadjusted renewable energy rate) does not reach the target renewable energy rate. However, in the second and third phases, by purchasing environmental value, the predicted value of the second renewable energy rate (adjusted renewable energy rate) reaches the target renewable energy rate.

[0105] <Fourth-order prediction> Next, in the flow of the prediction method according to this embodiment, the controller 31 performs a fourth-order prediction (step S8). In the fourth-order prediction, the CFP (Carbon Footprint of Products) of the first indicator is predicted.

[0106] In recent years, a system has been gaining traction in which greenhouse gas emissions from products and services throughout their entire lifecycle, from raw material procurement to disposal and recycling, are converted to CO2 equivalents and displayed as CFP (Coefficient of Foods). For example, when considering products produced at the production facilities (electricity consumption facilities 11) of electricity consumers 10, the CFP is the sum of the CO2 emissions generated from material procurement, production, distribution, use, and disposal / recycling for each unit of that product.

[0107] In this embodiment, the controller 31 predicts the CO2 emissions per product produced by the electricity consumer 10 over several years after the introduction of the distributed power system 12, taking into account the target reduction rate of the electricity consumer 10's annual electricity demand. The controller 31 predicts the CO2 emissions per product in production by adding the predicted CO2 emissions per product in the non-production phases of the lifecycle (material procurement, distribution, use, and waste recycling).

[0108] The CO2 emissions per product in the above-mentioned production can be predicted by dividing the second CO2 emissions (adjusted CO2 emissions) predicted in the third forecast by the number of products produced by the electricity consumer 10. However, the CO2 emissions per product in production may also be predicted by dividing the first CO2 emissions (unadjusted CO2 emissions) predicted in the first forecast by the number of products produced by the electricity consumer 10. Furthermore, the predicted values ​​of CO2 emissions per product for items other than production are stored in the memory 32 in advance, and the controller 31 can obtain this information from the memory 32. Note that the predicted values ​​of CO2 emissions per product for items other than production may remain constant over several years, or they may change from year to year.

[0109] Figure 10 shows the projected CFP values ​​for products produced by electricity consumer 10 over several years (CFP units include kg-CO2 / 1 product and t-CO2 / 1 product). As shown in Figure 10, if the CO2 emissions per product in items other than production remain constant, the projected CFP gradually decreases from the first to the fourth period. This is because the projected CO2 emissions per product in production decrease as the second CO2 emission gradually decreases (see Figure 7).

[0110] <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 S9). Specifically, the controller 31 displays information on the display 34 indicating the first indicator (CO2 emissions, power emission coefficient, renewable energy rate, amount of CO2 emission rights purchased, amount of CO2 emission reduction rights purchased, amount of electricity certificates purchased, CFP) predicted in the first to fourth predictions. Note that the display method of the first indicator is not limited, and the first indicator may be displayed as a graph or as a numerical value.

[0111] <Evaluation of Environmental Contribution> Next, in the prediction method according to this embodiment, the operator uses the information terminal 30 (see Figure 2) to have the evaluation system 40 evaluate the environmental contribution of the electricity consumer 10 (step S10). The evaluation system 40 is operated by an organization such as CDP (Carbon Disclosure Project), and when predetermined indicators are input, it evaluates the environmental contribution of the electricity consumer 10 with a score such as A to D.

[0112] In this embodiment, the worker accesses the evaluation system 40 using the information terminal 30 and inputs a first indicator and a second indicator for a power consumer 10 over several years into the evaluation system 40 via the input device 33. The evaluation system 40 then evaluates the environmental contribution of the power consumer 10 over several years. As explained in step S2, the second indicator is an indicator used when formulating the introduction plan for the distributed power system 12 (in this embodiment, the renewable energy rate), and as explained in steps S5 to S8, the first indicator is an indicator predicted in the first to fourth forecasts. The evaluation system 40 only needs to input the first indicator; it does not need to input the second indicator.

[0113] Furthermore, in this embodiment, the second indicator input to the evaluation system 40 is the renewable energy rate, but it may also be other indicators related to CO2 emissions, such as CO2 emissions, CO2 emission reductions, and electricity emission factors. Moreover, in this embodiment, the first indicator input to the evaluation system 40 is CO2 emissions, electricity emission factors, renewable energy rate, amount of CO2 emission rights purchased, amount of CO2 emission reduction rights purchased, amount of electricity certificates purchased, and CFP, but the first indicator is not limited to these indicators.

[0114] <Determination of Environmental Contribution Evaluation> Next, in the flow of the prediction method according to this embodiment, the operator determines whether the environmental evaluation score of the power consumer 10 evaluated by the evaluation system 40 is equal to or greater than the target environmental evaluation score (step S11). For example, if the target environmental evaluation score is "A", and the environmental evaluation score of the power consumer 10 evaluated in step S10 is "B", the operator determines that the environmental evaluation score of the power consumer 10 evaluated by the evaluation system 40 is not equal to or greater than the target environmental evaluation score.

[0115] <Revision of the Implementation Plan> If, in step S11, the operator determines that the environmental evaluation level of the power consumer 10, as evaluated by the evaluation system 40, is not equal to or greater than the target environmental evaluation level (NO in step S11), the operator revises the implementation plan for the distributed power system 12 (step S12). For example, the operator may revise the plan by increasing the amount of the distributed power system 12 to be implemented or by accelerating the implementation period compared to the original implementation plan for the distributed power system 12.

[0116] After the worker modifies the implementation plan for the distributed power system 12 in step S12, they return to step S3 and repeat steps S3 onward. In other words, the worker modifies the multi-year implementation plan for the distributed power system 12 so that the environmental contribution evaluated by the evaluation system 40 matches the environmental contribution targeted by the electricity consumer 10.

[0117] On the other hand, if the operator determines in step S11 that the environmental evaluation level of the power consumer 10 evaluated by the evaluation system 40 is equal to or greater than the target environmental evaluation level (YES in step S11), the flow of the prediction method according to this embodiment ends. The above is a description of the flow of the prediction method according to this embodiment.

[0118] As explained above, steps S1 to S12 are performed by an operator or the controller 31, respectively, but the entity performing each step is not limited to those described above. For example, the controller 31 may perform all of steps S1 to S12.

[0119] As described above, the prediction method according to this embodiment predicts a first indicator of CO2 emissions from electricity consumers 10 over a multi-year period when a distributed power system 12 is introduced based on a multi-year introduction plan for the distributed power system 12, taking into account the target reduction rate of the electricity consumer's annual electricity demand. Therefore, if the introduction of the distributed power system 12 by electricity consumers 10 is evaluated using this first indicator, it can be evaluated more appropriately from an environmental standpoint compared to conventional technology. Furthermore, the above prediction method predicts the first indicator of CO2 emissions from electricity consumers over a multi-year period after the introduction of the distributed power system 12. Therefore, with regard to the introduction of the distributed power system by electricity consumers 10, it is possible to appropriately know the trend of the first indicator over a multi-year period, taking into account the target reduction rate of the electricity consumer's annual electricity demand.

[0120] 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.

[0121] One aspect of this disclosure can be used in a prediction method and prediction device that can perform a more appropriate evaluation from an environmental standpoint compared to the prior art for the introduction of a distributed power supply system, as well as a control method for an information terminal that displays indicators for performing such evaluation.

[0122] 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 35: Prediction devices 40: Evaluation systems

Claims

1. A forecasting method for predicting a first indicator of a power consumer's CO2 emissions 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 target reduction rate of the power consumer's annual electricity demand.

2. The prediction method according to claim 1, wherein the distributed power system further includes an energy storage device.

3. The forecasting method according to claim 1 or 2, wherein the first indicator includes CO2 emissions.

4. The prediction method according to any one of claims 1 to 3, wherein the first indicator includes the amount of CO2 emission reduction.

5. The prediction method according to any one of claims 1-4, wherein the first indicator includes the power emission factor.

6. The prediction method according to any one of claims 1 to 5, wherein the first indicator includes the renewable energy rate.

7. The prediction method according to claim 3, 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.

8. The prediction method according to claim 4, which predicts the amount of CO2 emission rights or CO2 emission reduction rights to be purchased based on a target CO2 emission reduction amount as a target value of a second indicator relating to the CO2 emissions of the electricity consumer over several years.

9. The prediction method according to claim 6, which predicts the amount of electricity certificates to be purchased based on the target renewable energy rate as a target value for a second indicator relating to the electricity consumer's CO2 emissions over several years and the renewable energy rate.

10. A prediction method according to any one of claims 1 to 9, comprising: formulating a multi-year introduction plan for the distributed power system 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 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 target reduction rate of the electricity consumer's annual electricity demand.

11. A prediction device comprising: a memory for storing information on the target reduction rate of an electricity consumer's annual electricity demand; and a controller for predicting a first indicator of an electricity consumer's CO2 emissions over several years since 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 information stored in the memory.

12. A method for controlling an information terminal, comprising the step of displaying information on a display of the information terminal that indicates a first indicator of a power consumer's CO2 emissions over several years since the introduction of a distributed power system including at least one of a natural energy power generation device and a fuel cell device, wherein the first indicator is predicted taking into account the target reduction rate of the power consumer's annual electricity demand.

13. The method for controlling an information terminal according to claim 12, 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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