Hydrogen production plant revenue calculation device, hydrogen production plant expected revenue calculation device, hydrogen production volume calculation device, hydrogen production plant equipment capacity calculation device

Abstract

To provide a hydrogen production plant profit calculation device, an expected profit calculation device, a facility capacity calculation device and a hydrogen production amount calculation device which calculate further optimal profit calculation and facility capacity when there are a future sales price and subsidy.SOLUTION: A hydrogen production plant profit calculation device 1 includes: an input unit for acquiring a hydrogen production sales plan in a hydrogen production plant, an operation parameter of the hydrogen production plant, a facility capacity plan of the hydrogen production plant and estimated model construction data of hydrogen production; a sales income calculation unit for predicting a sales income of hydrogen on the basis of the hydrogen production sales plan; an operation cost calculation unit for predicting an operation cost required for hydrogen production on the basis of the operation parameter; a facility cost calculation unit for predicting a facility cost required for the facility of the hydrogen production on the basis of the facility capacity plan; an auxiliary calculation unit for predicting auxiliary amounts for at least one or more of the sales income, the operation cost and the facility cost; and a profit calculation unit for predicting a profit of the hydrogen production plant on the basis of the sales income, the operation cost, the facility cost and the auxiliary amount.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a hydrogen production plant revenue calculation device such as a hydrogen production plant, a hydrogen production plant expected revenue calculation device, a hydrogen production amount calculation device, and a hydrogen production plant equipment capacity calculation device.

Background Art

[0002] Towards the realization of a carbon-neutral society, the production and utilization of hydrogen are being considered. Among these, hydrogen production technology that suppresses CO2 emissions (hereinafter referred to as green hydrogen) is expected to play an important role. Generally, since the production of green hydrogen is considered to be costly, there is a possibility that it will not spread if left to market principles. Therefore, there is a movement to accelerate the spread of green hydrogen by introducing a subsidy system for green hydrogen producers and the like.

[0003] When investing in a plant such as a hydrogen production plant, the revenue is estimated assuming equipment costs, operating costs, the sales volume of the product, etc., and the equipment capacity, operating method, etc. are determined. As a system to support this, an energy system optimization device that can calculate the optimal energy flow rate and equipment capacity considering CO2 emissions and manufacturing costs has been proposed. Here, the energy system refers to a hydrogen production factory or the like, and the energy flow rate indicates the power consumption required for its production. In such an optimization device, the optimal operating cost and equipment capacity in the factory are calculated using mathematical optimization techniques.

[0004] In such an energy system optimization device, the current to future selling prices and subsidies of the factory's products are not considered. Also, subsidies that may be obtained according to the selling price and sales volume of the product are not considered. Since selling prices and subsidies, etc. may change in the future depending on the prices of substitute products of the goods to be sold and the social situation, it is necessary to consider these changes in order to optimize the equipment capacity and operating method of the energy system.

Prior Art Documents

[0005] [Patent Document 1] Japanese Patent Publication No. 2019-102006 [Overview of the project] [Problems that the invention aims to solve]

[0006] Thus, conventional hydrogen production plant revenue calculation devices, hydrogen production plant expected revenue calculation devices, hydrogen production volume calculation devices, and hydrogen production plant equipment capacity calculation devices have the problem of not taking into account future sales prices, possible subsidies, or changes in these. The objective of the present invention is to enable more optimal revenue calculation and equipment capacity calculation for hydrogen production plants that produce green hydrogen, when future sales prices and subsidies exist. [Means for solving the problem]

[0007] The hydrogen production plant revenue calculation device of the embodiment includes an input unit that acquires a hydrogen production and sales plan for the hydrogen production plant, operational parameters of the hydrogen production plant, equipment capacity plan for the hydrogen production plant, and data for constructing an estimated model of hydrogen production, The system includes a sales price estimation model construction unit that constructs a sales price estimation model based on the aforementioned estimation model construction data, and a sales revenue calculation unit that predicts hydrogen sales revenue based on the sales price estimation model and the hydrogen production and sales plan. Sales revenue calculation department, The system includes: an operating cost estimation model construction unit that constructs an estimation model for the operating costs required for hydrogen production based on the estimation model construction data; and an operating cost calculation unit that predicts the operating costs based on the estimation model for operating costs, the hydrogen production and sales plan, and the operating parameters. An operating cost calculation unit, and an equipment cost calculation unit that predicts the equipment costs required for the hydrogen production equipment based on the equipment capacity plan, A sales revenue subsidy calculation unit having a sales price subsidy calculation unit that predicts a first subsidy amount according to the sales price of hydrogen, and a sales volume subsidy calculation unit that predicts a second subsidy amount according to the sales volume of hydrogen, an operating cost subsidy estimation model construction unit that constructs an estimation model for the subsidy to the operating costs based on the estimation model construction data, an operating cost subsidy calculation unit that predicts a third subsidy amount to the operating costs based on the estimation model for the subsidy to the operating costs, the hydrogen production and sales plan, and the operating parameters, an equipment cost subsidy calculation unit having an equipment cost subsidy estimation model construction unit that constructs an estimation model for the subsidy to the equipment costs based on the estimation model construction data, and an equipment cost subsidy calculation unit that predicts a fourth subsidy amount to the equipment costs based on the estimation model for the subsidy to the equipment costs and the equipment capacity plan of the hydrogen production plant, The aforementioned sales revenue, the aforementioned operating expenses, the aforementioned equipment expenses and the aforementioned The first through fourth A revenue calculation unit that predicts the revenue of a hydrogen production plant based on the amount of subsidies, The sales price subsidy calculation unit comprises a sales price subsidy estimation model construction unit that constructs an estimation model for the subsidy corresponding to the sales price of hydrogen based on the estimation model construction data, and a sales price subsidy calculation unit that predicts the first subsidy amount corresponding to the sales price of hydrogen based on the estimation model for the subsidy corresponding to the sales price of hydrogen and the hydrogen production and sales plan. The aforementioned The sales volume subsidy calculation unit is characterized by comprising: a sales volume subsidy estimation model construction unit that constructs a subsidy estimation model corresponding to the sales volume of hydrogen based on the estimation model construction data; and a sales volume subsidy calculation unit that predicts the second subsidy amount corresponding to the sales volume of hydrogen based on the estimation model corresponding to the sales volume of hydrogen and the hydrogen production and sales plan. . [Brief explanation of the drawing]

[0008] [Figure 1] This is a block diagram showing the functional configuration of the hydrogen production plant revenue calculation device in the first and second embodiments. [Figure 2]It is a block diagram showing the functional configuration of the sales revenue calculation unit of the first and second embodiments. [Figure 3] It is a diagram showing an example of a regression tree. [Figure 4] It is a diagram showing an example of deep learning. [Figure 5] It is a block diagram showing the functional configuration of the sales assistance calculation unit of the first and second embodiments. [Figure 6] It is a block diagram showing the functional configuration of the sales price assistance calculation unit of the first and second embodiments. [Figure 7] It is a diagram showing an example of an auxiliary amount calculation method. [Figure 8] It is a diagram showing an example of an auxiliary amount calculation method using the price of raw materials. [Figure 9] It is a diagram showing an example of an auxiliary amount calculation method using the prices of products with similar uses. [Figure 10] It is a diagram showing an example of an auxiliary amount calculation method using the prices of multiple products with similar uses. [Figure 11] It is a diagram showing an example of an auxiliary amount calculation method using the actual sales price of hydrogen. [Figure 12] It is a diagram showing an example of an auxiliary amount calculation method using the hydrogen market price. [Figure 13] It is a diagram showing an example of an auxiliary amount calculation method when combining two reference prices. [Figure 14] It is a diagram showing the functional configuration of the sales volume assistance calculation unit of the first and second embodiments. [Figure 15] It is a diagram explaining partial buyout. [Figure 16] It is a diagram explaining residual quantity buyout. [Figure 17] It is a diagram explaining residual quantity buyout with an upper limit. [Figure 18] It is a diagram explaining sales volume slope assistance. [Figure 19] It is a block diagram showing the functional configuration of the operating cost calculation unit of the first and second embodiments. [Figure 20] It is a block diagram showing the functional configuration of the operating cost assistance calculation unit of the first and second embodiments. [Figure 21] It is a diagram showing the functional configuration of a hydrogen production device. [Figure 22] It is a block diagram showing the functional configuration of the equipment cost subsidy calculation unit of the first and second embodiments. [Figure 23] It is a block diagram showing the functional configuration of the hydrogen production amount calculation device of the third embodiment. [Figure 24] It is a diagram showing a calculation example of the relationship between hydrogen production amount and hydrogen production unit price. [Figure 25] It is a diagram showing a calculation example of the relationship between hydrogen production amount and annual equipment cost hydrogen unit price. [Figure 26] It is a diagram showing an example of the hydrogen unit price required for recovering manufacturing costs and equipment costs. [Figure 27] It is a diagram showing the relationship between hydrogen production amount, revenue, expenditure, and profit. [Figure 28] It is a diagram showing the relationship between hydrogen production amount, revenue, expenditure, and profit in the case of fixed subsidy amount. [Figure 29] It is a block diagram showing the functional configuration of the hydrogen production plant expected profit calculation device of the fourth embodiment. [Figure 30] It is a block diagram showing the functional configuration of the multi-year hydrogen production plant expected profit calculation device of the fifth embodiment. [Figure 31] It is a block diagram showing the functional configuration of the hydrogen production plant equipment capacity calculation device of the sixth embodiment. [Figure 32] It is a diagram showing a comparison of scenarios using the distribution of expected profits.

Embodiments for Carrying Out the Invention

[0009] (First Embodiment) Hereinafter, an example of an operation plan creation device according to the present invention will be described with reference to the drawings. FIG. 1 shows the functional configuration of a hydrogen production plant profit calculation device 1 according to the first embodiment. As shown in FIG. 1, the profit calculation device of this embodiment includes an input unit 10, a calculation unit 20, a storage unit 30, and an output unit 40.

[0010] The input unit 10 is an interface for acquiring information such as the hydrogen production and sales plan 10a, the operation parameters 10b of the hydrogen production equipment, the equipment capacity plan 10c of the hydrogen production equipment, and model construction data 10d. The hydrogen production plant revenue calculation device 1 uses this information to calculate the revenue of the hydrogen production plant. Examples of input units 10 include transceivers that receive information from other devices, and keyboards and mice that receive information directly from users.

[0011] The calculation unit 20 is an operation block that performs calculations using the information acquired by the input unit 10 and the information stored in the storage unit 30. The calculation unit 20 stores the calculation result in the storage unit 30 and passes it to the output unit 40.

[0012] The storage unit 30 is a storage medium that temporarily stores data received from the calculation unit 20 and provides it to the calculation unit 20. The storage unit 30 can be implemented, for example, by non-volatile memory or a hard disk drive.

[0013] The output unit 40 is an interface that outputs the calculation results performed by the calculation unit 20. Examples of the output unit 40 include a display device that provides information to the user, a printer device, and a transmitting / receiving device that sends information to other devices.

[0014] The hydrogen production plant revenue calculation device 1 can be implemented using, for example, a computer or a server. The hydrogen production plant revenue calculation device 1 may be connected to other devices via a network (not shown).

[0015] As shown in Figure 1, the calculation unit 20 has functional elements such as a sales revenue calculation unit 211, a sales revenue auxiliary calculation unit 221, an operating expense calculation unit 231, an operating expense auxiliary calculation unit 241, an equipment expense calculation unit 251, an equipment expense auxiliary calculation unit 261, and a revenue calculation unit 271. These functional elements can be realized by loading and executing computer programs on a computer device.

[0016] (1) Sales revenue calculation unit 211 As shown in Figure 2, the sales revenue calculation unit 211 is a calculation block that calculates sales revenue based on the estimated model construction data 10d and the hydrogen production and sales plan 10a. The sales revenue calculation unit 211 has a sales price estimation model construction unit 212 and a sales revenue calculation unit 213 as functional elements.

[0017] The sales price estimation model construction unit 212 constructs a model to estimate future sales prices from the model construction data 10d. The model to be constructed can, for example, take past hydrogen sales unit prices as input to the model construction data 10d, and output a unit price if these values ​​are all the same. If past hydrogen sales unit prices have fluctuated, a predicted value may be calculated using techniques such as an autoregressive model that predicts the future from its own past data.

[0018] One approach to constructing estimation models is to build models that predict based on other time-series data. For example, a model can be constructed to predict future hydrogen sales prices using techniques such as multivariate analysis and deep learning, based on trends in natural gas prices and exchange rates.

[0019] Furthermore, in environments where a fixed-price purchase system such as FIT (Feed in Tariff) is introduced, a model that shows the purchase price may be constructed. In environments where a premium is added to the hydrogen market price, such as FIP (Feed in Premium), a hydrogen market price prediction model may be constructed from historical data of the hydrogen market price, and a hydrogen sales price estimation model may be created based on the amount obtained by adding a premium to this value. The model constructed in this case is referred to as a "sales price estimation model (t)" that calculates the hydrogen sales price at a future point in time t.

[0020] The sales revenue calculation unit 213 calculates sales revenue from the estimated sales price model and the hydrogen production and sales plan 10a using the following formula. Sales revenue (t) = Estimation model of sales price (t) × Hydrogen sales plan (t) …(1) Furthermore, by integrating this sales revenue (t), we can calculate the sales revenue for a certain future period. Note that if the sales price fluctuates according to the sales volume v, the sales revenue can also be calculated using the following formula as a "sales price estimation model (t, v)". Sales revenue (t) = Sales price estimation model (t, Hydrogen sales plan (t)) × Hydrogen sales plan (t) …(2)

[0021] In the following explanation, we will omit the price estimation model for cases where the price fluctuates according to sales volume, but this approach will also be applied when constructing the sales price estimation model.

[0022] (Method for constructing estimation models) Here, we will explain how to build a model to estimate future values ​​of a time series of data (for example, future values ​​of sales prices).

[0023] Let y(t) be the time series we want to estimate. t is a future time, and we assume that the values ​​up to t-1 are known. An autoregressive model calculates the value of y(t) using past values ​​such as y(t-1), y(t-2), ... In the AR (Auto Regressive) model, a technique within autoregressive models, y(t)=φ1y(t-1)+φ2y(t-2)+ … +φ p y(tp) …(3) The equation used to estimate y(t) is as follows. At this time, the counts φ1~φ used in the model are p This model learns using values ​​from past examples. Other examples of autoregressive models include the Moving Average (MA) model, the Auto Regressive Moving Average (ARMA) model, and the Auto Regressive Integrated Moving Average (ARIMA) model.

[0024] Next, we will explain a method for predicting future values ​​using not only the time series itself but also other time series data. This method can be predicted using the following formula. y(t)=φ1X(t-1)+φ2X(t-2)+ … + φ p X(tp) …(4) Here, Φ is a vector, and X is a multivariate time series. For example, if y is the hydrogen sales price and X is the time series of natural gas and the exchange rate, then the hydrogen sales price will be predicted from the natural gas and exchange rate. Φ will be determined by learning from past cases, and a commonly known parameter calculation method for multiple regression analysis can be used for this purpose.

[0025] As a variation, y may be included in X, and if future predicted values ​​for X are given, it is also possible to use values ​​where t ≥ 0.

[0026] The modeling technique obtained by applying a function g(), known as an exponential family distribution, to the left-hand side of the above equation (4) is called generalized linear regression. g(y(t))=φ1X(t-1)+φ2X(t-2)+ … +φ p X(tp) …(5) Equation (5), in the form of g(), can be expressed as a method such as logistic regression or Poisson regression, and by using these modeling techniques, nonlinear estimation can be performed.

[0027] Another known prediction method utilizes tree-like conditional branching. A typical example is the regression tree. This method creates a tree that performs conditional branching using the variables used for prediction, and the value reached at a leaf is taken as the prediction result. Figure 3 shows the prediction process using a regression tree. Algorithms for creating regression trees include C4.5 and CART. Similar predictions can also be made using the Random Forest algorithm, which creates multiple regression trees and performs predictions.

[0028] Furthermore, deep learning can also be used as a prediction method. Figure 4 shows the prediction process using deep learning. Deep learning is a method that performs operations defined by the structure of a multi-layered neural network on input data and finds a solution. A prediction model can be constructed by weighting the neural network using past data.

[0029] The above describes some representative machine learning methods, but the methods described are not limited to these. Other methods can also be applied. The methods described above are used in the construction of estimation models.

[0030] (2) Sales revenue subsidy calculation unit 221 The sales revenue subsidy calculation unit 221 is a calculation block that calculates the amount of subsidy related to the production of green hydrogen. As shown in Figure 5, the sales revenue subsidy calculation unit 221 has a sales price subsidy calculation unit 222 that determines the amount of subsidy according to the hydrogen sales price and a sales volume subsidy calculation unit 223 that calculates the amount of subsidy according to the amount of hydrogen sold.

[0031] (2a) Sales price sub-calculation unit 222 As shown in Figure 6, the sales price subsidy calculation unit 222 includes a sales price subsidy estimation model construction unit 224 and a sales price subsidy calculation unit 225. The sales price subsidy estimation model construction unit 224 constructs a sales price subsidy estimation model for the hydrogen sales price, and the sales price subsidy calculation unit 225 calculates the sales price subsidy using the sales price subsidy estimation model.

[0032] The following explanation, using Figure 7, describes an example of a method for determining the subsidy amount, specifically a method using a benchmark price and a reference price. The benchmark price is the unit price at which a hydrogen production plant can recover its investment, or the unit price obtained by adding a profit margin to the amount at which the investment can be recovered. The reference price is a benchmark value of the market hydrogen sales unit price at a given point in time, and may be the market unit price of hydrogen, or a value calculated from another indicator. In this case, the subsidy amount is determined by the difference between the benchmark price and the reference price. For example, if the reference price is lower than the benchmark price, the difference will be subsidized, and if the reference price is higher than the benchmark price, the difference will be returned.

[0033] The benchmark price can be calculated by dividing the annual operating expenses calculated by the operating expense calculation unit (described later) and the annual equipment costs calculated by the equipment cost calculation unit by the annual hydrogen sales volume in the hydrogen production and sales plan, or by adding a profit margin to this value.

[0034] Reference prices can be calculated using several methods: (i) using the price of raw materials required for hydrogen production; (ii) using products with similar applications; (iii) using multiple products with similar applications; (iv) using actual sales prices; (v) using market prices; (v) using carbon prices; and (vi) combining multiple indicators. Examples of each calculation method will be shown below.

[0035] (i) Methods that utilize the price of raw materials As shown in Figure 8, the method of using raw material prices involves determining a reference price using electricity prices as a benchmark, for example. The inputs to the sales price subsidy estimation model construction unit 224 are, for example, historical reference price trend data and electricity price data. The relationship between these is modeled, and a reference price estimation model is constructed from future electricity price forecasts. If the sales price subsidy unit price at a future point in time t is called the "sales price subsidy estimation model (t)", the sales price subsidy calculation unit 225 takes the hydrogen sales plan (t) as input and calculates the sales price subsidy (t) at a certain point in time t using the following formula. Sales price subsidy (t) = Sales price subsidy estimation model (t) × Hydrogen sales plan (t) …(6) Furthermore, by integrating this with respect to t, we can calculate the sales price subsidy for a certain future period.

[0036] (ii) A method of referring to the price of products with similar uses. One method that utilizes the prices of products with similar uses is to determine a reference price using natural gas prices as a benchmark, as shown in Figure 9. The input to the sales price subsidy estimation model construction unit 224 is, for example, data on past natural gas price trends. From the natural gas price trend data, future natural gas price trends are modeled using techniques such as autoregressive models, and a sales price subsidy estimation model is constructed. If this is called the "sales price subsidy estimation model (t)", the sales price subsidy calculation unit 225 takes the hydrogen sales plan as input and calculates the sales price subsidy (t) at a certain point in time t using the following formula. Sales price subsidy (t) = Sales price subsidy estimation model (t) × Hydrogen sales plan (t) …(7) Furthermore, by integrating this with respect to t, we can calculate the sales price subsidy for a certain future period.

[0037] (iii) A method of referencing multiple products with similar uses. One method that utilizes the prices of multiple products with similar uses is to determine two reference prices using natural gas prices and gasoline prices as benchmarks, as shown in Figure 10. Within the sales price subsidy estimation model construction unit 224, models for the two reference prices are constructed. In constructing the model that uses natural gas prices as the reference price, the input is data on past natural gas price trends, and a model for estimating future natural gas price trends is constructed using techniques such as autoregressive models. Similarly, in constructing the model that uses gasoline prices as the reference price, the input is data on past gasoline price trends, and a model for estimating future gasoline price trends is constructed using techniques such as autoregressive models. These two models are named "sales price subsidy estimation model_gasoline(t)" and "sales price subsidy estimation model_natural gas(t)," and the sales price subsidy calculation unit 225 calculates the sales price subsidy (t) at a certain time t using the following formula, with the hydrogen sales plan to be sold to the transportation sector as a substitute for gasoline at a future time t being "hydrogen sales plan_gasoline(t)" and the hydrogen sales plan to be sold to the heating sector as a substitute for natural gas being "hydrogen sales plan_natural gas(t)." Selling price subsidy (t) = Estimation model for sales price subsidies: Gasoline (t) × Hydrogen sales plan: Gasoline (t) + Estimation model for sales price subsidy_natural gas (t) × hydrogen sales plan_natural gas (t) …(8) Furthermore, by integrating this with respect to t, the sales price subsidy for a certain future period can be calculated. Note that when calculating the subsidy using multiple reference prices, it is necessary to use data created for each sales sector as the hydrogen production and sales plan 10a.

[0038] (iv) Using the actual selling price One method that utilizes actual sales prices is to use the hydrogen sales price of a certain hydrogen production plant as a reference price, as shown in Figure 11. The reference price may differ from plant to plant. The input to the sales price subsidy estimation model construction unit 224 is, for example, data on the trend of hydrogen sales prices of a certain hydrogen production plant in the past. From this data, the future trend of hydrogen sales prices is modeled using techniques such as an autoregressive model, and a sales price subsidy estimation model is constructed. If this is called the "sales price subsidy estimation model (t)", the sales price subsidy calculation unit 225 takes the hydrogen sales plan as input and calculates the sales price subsidy (t) at a certain time t using the following formula. Sales price subsidy (t) = Sales price subsidy estimation model (t) × Hydrogen sales plan (t) …(9) Furthermore, by integrating this with respect to t, we can calculate the sales price subsidy for a certain future period.

[0039] (v) Using market prices One method that utilizes market prices is, for example, as shown in Figure 12, to use the hydrogen market price as a reference price when a hydrogen trading market is established. The input to the sales price subsidy estimation model construction unit 224 is, for example, data on the trend of a certain hydrogen market price in the past. From this data, the future hydrogen market price is modeled using techniques such as an autoregressive model, and a sales price subsidy estimation model is constructed. If this is called the "sales price subsidy estimation model (t)", the sales price subsidy calculation unit 225 takes the hydrogen sales plan as input and calculates the sales price subsidy (t) at a certain time t using the following formula. Sales price subsidy (t) = Sales price subsidy estimation model (t) × Hydrogen sales plan (t) …(10) Furthermore, by integrating this with respect to t, we can calculate the sales price subsidy for a certain future period.

[0040] (vi) How to combine multiple indicators Figure 13 shows an overview of the method for calculating the subsidy amount when combining multiple indicators. Here, natural gas price and actual sales price are used as the multiple indicators, and the larger of the two indicators is used as the reference indicator. The calculation method for each reference price is as follows: the natural gas sales price subsidy estimation model and the sales price subsidy estimation model based on sales performance are designated as "Sales Price Subsidy Estimation Model_Natural Gas(t)" and "Sales Price Subsidy Estimation Model_Sales Price(t)", respectively. The sales price subsidy calculation unit 225 takes the hydrogen sales plan as input and calculates the sales price subsidy (t) at a certain time t using the following formula. Sales price subsidy (t) = Hydrogen sales plan (t) × max(Sales price subsidy estimation model_natural gas(t), Sales price subsidy estimation model_sales price(t)) …(11) Furthermore, by integrating this with respect to t, we can calculate the sales price subsidy for a certain future period.

[0041] (2b) Sales volume subsidy calculation unit As shown in Figure 14, the sales volume subsidy calculation unit 223 includes a sales volume subsidy estimation model construction unit 226 and a sales volume subsidy calculation unit 227. The sales volume subsidy estimation model construction unit 226 calculates a sales volume subsidy amount estimation model for the hydrogen sales price, and the sales volume subsidy calculation unit 227 calculates the sales volume subsidy using the sales volume subsidy amount estimation model. Examples of sales volume subsidy calculation methods include partial purchase (i), residual purchase (ii), residual purchase with an upper limit (iii), sales volume gradient subsidy (iv), etc.

[0042] (i) Explanation of partial purchase As shown in Figure 15, partial purchase is a method in which a public institution purchases a predetermined fixed amount. The sales volume support estimation model construction unit 226 constructs a public institution purchase volume model and a public institution purchase price model.

[0043] The public institution purchase volume model estimates the purchase volume if it is predetermined, and if it is not predetermined, it estimates the purchase volume at a future point in time (t) using methods such as an autoregressive model based on past purchase volumes. The public institution purchase price model estimates the purchase price if it is predetermined, and if it is not predetermined, it estimates the purchase price at a future point in time (t) using methods such as an autoregressive model based on past purchase prices. If these models are referred to as the "public institution purchase volume estimation model (t)" and the "public institution purchase price estimation model (t)," the sales volume subsidy calculation unit 227 takes the hydrogen sales plan as input and calculates the sales volume subsidy (t) at a certain point in time (t) using the following formula. Sales volume subsidy (t) = Public institution purchase volume estimation model (t) x Public institution purchase price estimation model (t) …(12) Furthermore, by integrating this, we can calculate the sales volume subsidy for a certain future period.

[0044] (ii) Explanation of remaining battery purchase As shown in Figure 16, residual purchase is a method in which a public institution purchases the remaining amount of hydrogen if the amount of hydrogen sold is less than the plant's capacity. In this method, the sales volume subsidy estimation model construction unit 226 constructs a public institution purchase price model. If the purchase price is predetermined, the public institution purchase price model uses that price as an estimation model; if it is not predetermined, it estimates the amount to be purchased at a future point in time (t) using a method such as an autoregressive model based on past purchase prices. The sales volume subsidy calculation unit 227 can calculate the sales volume subsidy (t) at a certain point in time (t) using the following formula, with the hydrogen sales plan and equipment capacity as input for the "public institution purchase price estimation model (t)". Sales volume subsidy (t) = Hydrogen sales price estimation model (t) × (Installation capacity - Hydrogen sales plan (t)) …(13) Furthermore, by integrating this with respect to t, we can calculate the sales volume subsidy for a certain future period.

[0045] (iii) Explanation of the purchase of remaining amount with a limit As shown in Figure 17, the capped residual purchase is a method in which a public institution purchases a predetermined fixed amount. The sales volume subsidy estimation model construction unit 226 constructs a hydrogen sales price estimation model, a public institution purchase volume model, and a public institution purchase price model. The public institution purchase volume model uses the predetermined purchase volume as the estimation model if it is predetermined, and if it is not predetermined, it estimates the purchase volume at a future point in time (t) using a method such as an autoregressive model from past purchase volumes. The public institution purchase price model uses the predetermined purchase price as the estimation model if it is predetermined, and if it is not predetermined, it estimates the purchase price at a future point in time (t) using a method such as an autoregressive model from past purchase prices. The sales volume subsidy calculation unit 227 takes the hydrogen sales plan as input for the "public institution purchase volume estimation model (t)" and the "public institution purchase price estimation model (t)" and calculates the sales volume subsidy (t) at a certain point in time (t) using the following formula. If the public institution purchase volume estimation model (t) < hydrogen sales plan (t) Sales volume subsidy (t) = 0 If the public institution purchase volume estimation model (t) >= hydrogen sales plan (t) Sales volume subsidy (t) = Public institution purchase price estimation model (t) × (Estimated amount of hydrogen purchased by public institutions (t) - Hydrogen sales plan (t)) …(14) Furthermore, by integrating this with respect to t, we can calculate the sales volume subsidy for a certain future period.

[0046] (iv) Explanation of sales volume-based subsidies As shown in Figure 18, the sales volume-based subsidy is a method of providing a subsidy to the sales price according to the sales volume. When the sales volume is low, it becomes difficult to recover the investment in the plant, so a subsidy is added to the sales price. The sales volume subsidy estimation model construction unit 226 constructs a hydrogen unit price subsidy estimation model.

[0047] The hydrogen unit price subsidy estimation model can, if the relationship between the hydrogen unit price subsidy and sales volume is determined, simply return that amount according to the sales volume. If it is undetermined, it estimates the hydrogen unit price subsidy for a sales volume v at a future point in time t using methods such as a multiple regression model based on past estimates of the hydrogen unit price subsidy and the relationship between sales volume. The sales volume subsidy calculation unit 227 can calculate the sales volume subsidy (t) at a certain point in time t using the following formula, with the hydrogen sales plan as input for the "hydrogen unit price subsidy estimation model (t, v)". Sales volume subsidy (t) = Hydrogen sales plan (t) × Hydrogen unit price subsidy estimation model (t, Hydrogen sales plan (t)) …(15) Furthermore, by integrating this with respect to t, we can calculate the sales volume subsidy for a certain future period.

[0048] (3) Operation cost calculation department The operating cost calculation unit 231 is a calculation block that calculates the operating costs of a hydrogen production plant and the like. As shown in Figure 19, the operating cost calculation unit 231 has an operating cost estimation model construction unit 232 and an operating cost calculation unit 233.

[0049] The operating cost estimation model construction unit 232 constructs a model to estimate future operating costs from the estimation model construction data, and calculates operating costs from this model, the hydrogen production and sales plan, and operating parameters. Examples of operating cost estimation models include the power consumption estimation model (v), the water consumption estimation model (v), and the production days estimation model (v). Here, v is the amount of hydrogen produced.

[0050] The power consumption estimation model (v) models past hydrogen production and power consumption using, for example, a linear regression model. Alternatively, nonlinear modeling techniques such as generalized linear regression models or deep learning may be used. The water consumption estimation model (v) models past hydrogen production and water consumption using, for example, a linear regression model. Alternatively, nonlinear modeling techniques such as generalized linear regression models or deep learning may be used. The production time estimation model (v) models past hydrogen production and production time using, for example, a linear regression model. Alternatively, nonlinear modeling techniques such as generalized linear regression models or deep learning may be used. These will be referred to as the "power consumption estimation model (v)", "water consumption estimation model (v)", and "production time estimation model (v)".

[0051] An example of operational parameter 10b is the unit cost of raw materials used in hydrogen production, such as electricity and water. These are referred to as the unit cost of electricity (t), the unit cost of water (t), and the unit cost of labor (t). Here, t represents a future point in time. Using the operational cost estimation model and operational parameters, the operational cost calculation unit 233 can calculate the operational cost using the following formula. Operating cost (t) = Energy consumption estimation model (v) × Energy unit price (t) + Estimation model for water consumption (v) × Water cost per unit (t) + Estimation model for manufacturing days (v) × Labor cost per unit (t) …(16) Here, v = hydrogen production amount (t).

[0052] When calculating operating expenses, other terms that can be considered variable expenses may be added. By integrating the operating expenses with respect to t, the operating expenses for a certain future period can be calculated.

[0053] (4)Operating Cost Subsidy Calculation Department The operating cost subsidy calculation unit 241 is a calculation block that calculates the amount of subsidy for operating costs related to the production of green hydrogen. As shown in Figure 20, the operating cost subsidy calculation unit 241 has an operating cost subsidy estimation model construction unit 242 and an operating cost subsidy calculation unit 243.

[0054] The operating cost subsidy estimation model construction unit 242 constructs a model to estimate future operating cost subsidies from the estimation model construction data, and calculates the operating cost subsidy from this model, the hydrogen sales plan, and the unit prices of raw materials used in hydrogen production, such as electricity and water. Examples of operating cost subsidy estimation models include the electricity consumption unit price subsidy estimation model (t) and the water consumption unit price subsidy estimation model (t). Here, t represents a point in the future.

[0055] The electricity consumption unit price subsidy estimation model, if there is a history of electricity consumption unit price subsidies, constructs a model that calculates the value of t at a certain point in time using techniques such as autoregressive models. The water consumption unit price subsidy estimation model, if there is a history of water consumption unit price subsidies, constructs a model that calculates the value of t at a certain point in time using techniques such as autoregressive models. These will be referred to as the "electricity consumption unit price subsidy estimation model (t)" and the "water consumption unit price subsidy estimation model (t)". ​​Examples of operational parameters used are electricity unit price (t), water unit price (t), and labor cost unit price (t). Here, t represents a certain point in the future.

[0056] By obtaining the power consumption estimation model (v) and the water consumption estimation model (v) from the operating cost calculation unit 231 via the storage unit 30, the operating cost subsidy calculation unit 243 can calculate the operating cost subsidy for a future time point t using the following formula. Operating cost subsidy (t) = Power consumption subsidy estimation model (power consumption unit price (t)) × Power consumption estimation model (v) + Water consumption estimation model (water unit price (t)) × Water consumption estimation model (v) …(17) Here, v = hydrogen production amount (t).

[0057] (5)Equipment cost calculation department The equipment cost calculation unit is a calculation block that calculates the equipment cost per unit time (for example, per year) from the equipment capacity plan. For example, if a hydrogen production plant consists of a power system 52, a water electrolyzer 54, a hydrogen storage tank 56, and a discharge device 58 as shown in Figure 21, the equipment cost is obtained by dividing the cost of the water electrolyzer 54, the cost of the hydrogen storage tank 56, the cost of the discharge device 58, and other costs by their respective useful lives, as shown below. Equipment cost = Cost of water electrolysis equipment / Useful life of water electrolysis equipment + Cost of hydrogen storage tank / Lifespan of hydrogen storage tank + Cost of shipping equipment / Useful life of shipping equipment + Other equipment costs / Useful life of other equipment costs …(18)

[0058] (6) Equipment cost subsidy calculation department The equipment cost subsidy calculation unit 261 is a calculation unit that calculates the amount of subsidy for equipment costs. For example, if a hydrogen capacity market is established, the value obtained at that time corresponds to the equipment cost subsidy. Also, if a public institution sets a subsidy for equipment costs or hydrogen production capacity, that amount becomes the equipment cost subsidy. As shown in Figure 22, the equipment cost subsidy calculation unit 261 has an equipment cost subsidy estimation model construction unit 262 and an equipment cost subsidy calculation unit 263.

[0059] The equipment cost subsidy estimation model construction unit 262 constructs a model to estimate future equipment cost subsidies from model construction data, and calculates equipment costs from this model and the equipment capacity plan. An example of an equipment cost subsidy estimation model is the hydrogen capacity market estimation model (t), where t is a certain future point in time. If a hydrogen capacity market has been established and its historical data has been accumulated, a model of the future hydrogen capacity market can be constructed using, for example, an autoregressive model. Let this be called the "hydrogen capacity market model (t)," and if its unit is the amount per unit of equipment capacity, the equipment cost subsidy calculation unit 263 can calculate the equipment cost subsidy using the following formula. Equipment cost subsidy (t) = Hydrogen capacity market model (t) × Equipment capacity plan …(19) If a public institution has published the subsidy amount per unit of equipment capacity, that value may be used.

[0060] (7) Revenue Accounting Department The revenue calculation unit 271 is a calculation block that calculates the revenue amount related to the production of green hydrogen. The revenue calculation unit 271 calculates the revenue of the hydrogen production plant by aggregating the sales revenue, sales revenue subsidies, operating expenses, operating expense subsidies, equipment expenses, and equipment expense subsidies for a certain period, which are calculated by the sales revenue calculation unit 211, sales revenue subsidy calculation unit 221, operating expense calculation unit 231, operating expense subsidy calculation unit 241, equipment expense calculation unit 251, and equipment expense subsidy calculation unit 261, using the following formula. Water production plant revenue (T) = Sales revenue (T) + Sales revenue subsidy (T) - Operating cost (T) + Operating cost subsidy (T) - Equipment cost (T) + Equipment cost subsidy (T) …(20)

[0061] By using the method described above, it becomes possible to calculate the profitability of a hydrogen production plant by considering future fluctuations in the selling price and quantity of green hydrogen, as well as subsidies for its production and for the electricity and water used as raw materials.

[0062] (Second Embodiment) Next, a second embodiment will be described in which mathematical optimization techniques are applied to the calculations of the operating cost calculation unit of the first embodiment. In the following description, components common to the first embodiment will be denoted by the same reference numerals, and redundant explanations will be omitted.

[0063] (1) Operating cost calculation department Mathematical optimization techniques model plant operations using an objective function and constraints derived from optimization variables, and calculate operating costs by finding the operation that minimizes the objective function. Below, the method for constructing a mathematical optimization model is shown in the following order: constants, optimization variables, objective function, and constraints. t represents time, and d represents day.

[0064] (2) Constant T: Set of computation time points (t∈T) D: Set of dates to be calculated (d∈D) a: Constant for converting kW to kWh in 30 minutes C_ELCOST(t): Purchased electricity cost per unit C_WACOST(t): Purchase cost per unit of water C_H2OUT(d): Daily hydrogen shipment volume C_ECGAS_EF: EC efficiency (Nm3 / kWh) C_ECEL_LL: Water electrolysis device lower limit power (kW) C_ECEL_UL: Water electrolysis device upper limit power (kW) C_H2ST_LL: Minimum storage capacity of H2 tank (Nm3) C_H2ST_UL: H2 tank storage limit (Nm3)

[0065] (3) Optimization variable (lower limit is 0, upper limit is ∞) X_ECEL(t): EC power (kW) X_ECWA(t): EC water (m3) X_ECH2(t): EC hydrogen production amount (Nm3) X_H2ST(t): Hydrogen tank storage capacity (Nm3) X_H2OUT(t): Hydrogen shipment volume (Nm3)

[0066] (4) Objective function The objective function is minimizing OBJ, which is the sum of electricity and water costs purchased from the grid.

[0067]

number

[0068] (5) Constraint expression The constraints are as follows (created for t ∈ T): Relationship between power consumption and hydrogen production volume of a water electrolysis device X_ECH2(t) = X_ECEL(t) × C_ECGASEF × a X_ECEL(t) ≥ C_ECEL_LL X_ECEL(t) ≦ C_ECEL_UL …(22) Relationship between water consumption and hydrogen production volume of water electrolysis equipment X_ECWA(t) = X_ECH2(t) × C_GAS_WA …(23) Hydrogen tank balance X_H2ST(t) = X_H2TANK(t-1) + X_ECH2(t) - X_H2OUT(t) X_H2ST(t) ≥ C_H2ST_LL X_H2ST(t) ≦ C_H2ST_UL …(24) A constraint on the amount of hydrogen shipped from the hydrogen tank, where t∈d represents the time period included in d.

[0069]

number

[0070] In the constraint equations, the constraint equation for the water electrolysis device describes the relationship between the input power of the water electrolysis device and the amount of hydrogen produced, as well as the upper and lower limits of the input power of the water electrolysis device. The constraint equation for water consumption describes the relationship between the amount of hydrogen produced and the amount of water used. The constraint equation for the hydrogen tank describes the balance between the remaining amount in the tank, the amount of hydrogen produced, the amount of hydrogen shipped, and the upper and lower limits of the hydrogen tank.

[0071] By solving the mathematical model described above, we can find the values ​​of the optimization variables that minimize the objective function, and simultaneously determine the operating costs of the hydrogen production plant. To find the solution to the mathematical model, a general-purpose mathematical optimization package can be used to solve a linear programming problem or a mixed-integer programming problem. This embodiment enables more accurate calculation of operating costs tailored to the plant's specifications.

[0072] (Third embodiment) A third embodiment will be described, which is a modified version of the hydrogen plant revenue calculation device 1 of the first and second embodiments, with a changed configuration of the calculation unit 20. The hydrogen production amount calculation device 3 of the third embodiment calculates the optimal hydrogen production amount for hydrogen production that maximizes revenue, given the plant's equipment capacity. In the following description, components common to the first and second embodiments are denoted by the same reference numerals, and redundant explanations are omitted.

[0073] Figure 23 shows the functional configuration of the hydrogen production amount calculation device 3 according to the third embodiment. As shown in Figure 23, the hydrogen production amount calculation device of this embodiment includes an input unit 13, a calculation unit 23, a storage unit 30, and an output unit 40.

[0074] The input unit 13 is an interface for acquiring information such as the operation parameters 10b of the hydrogen production equipment, the equipment capacity plan 10c of the hydrogen production equipment, and model construction data 10d. The hydrogen production amount calculation device 3 uses this information to calculate the amount of hydrogen produced by the hydrogen production plant. Examples of input units 13 include transceivers that receive information from other devices, and keyboards and mice that receive information directly from the user.

[0075] The calculation unit 23 is an operation block that performs calculations using the information acquired by the input unit 13 and the information stored in the storage unit 30. The calculation unit 23 stores the calculation result in the storage unit 30 and passes it to the output unit 40.

[0076] The memory unit 30 is a storage medium that temporarily stores data received from the calculation unit 23 and provides it to the calculation unit 23. The memory unit 30 can be implemented using, for example, non-volatile memory or a hard disk drive. The memory unit 30 also enables information exchange with the hydrogen plant revenue calculation device 1 of the first and second embodiments.

[0077] The output unit 40 is an interface that outputs the calculation results performed by the calculation unit 23. Examples of the output unit 40 include a display device that provides information to the user, a printer device, and a transmitting / receiving device that sends information to other devices.

[0078] The hydrogen production amount calculation device 3 can be implemented using, for example, a computer or a server. The hydrogen production amount calculation device 3 may be connected to other devices via a network (not shown).

[0079] As shown in Figure 23, the calculation unit 23 has functional elements such as a hydrogen production cost calculation unit 281 and a hydrogen production amount calculation unit 291. These functional elements can be realized by loading and executing computer programs into a computer device.

[0080] The hydrogen production cost calculation unit 281 is a calculation block that calculates the hydrogen production cost and various subsidies for each hydrogen production amount given multiple annual hydrogen production amounts up to the equipment capacity limit. The hydrogen production amount calculation unit 291 is a calculation block that calculates the expenditure, income, and profit of the hydrogen production plant for each hydrogen production amount from the hydrogen production cost and various subsidies, and determines the hydrogen production amount that maximizes income.

[0081] (1) Hydrogen production cost calculation unit 281 The inputs used by the hydrogen production cost calculation unit 281 for calculations include the plant's capacity, electricity rate, and water rate. Here, multiple hydrogen production volumes below the plant's capacity are assumed, and the hydrogen production cost and various subsidies are calculated for each hydrogen production volume using the hydrogen production plant revenue calculation device 1. Here, the hydrogen production cost is divided into variable costs and fixed costs. Visualizing the hydrogen production cost, which corresponds to the variable costs, is shown in Figure 24. The horizontal axis represents the hydrogen production volume (let's call it v), and the vertical axis represents the hydrogen production cost (v).

[0082] In Figure 24, the reason why the unit price increases as the amount of hydrogen produced increases is that, for example, if electricity rates are variable, hydrogen production can be carried out during times when electricity rates are low if the amount of hydrogen produced is small, but as the amount of hydrogen produced increases, it becomes necessary to pay higher electricity rates.

[0083] Next, we calculate the value obtained by dividing fixed costs (e.g., annual equipment costs) by the amount of hydrogen produced (this is called the annual equipment cost-per-unit hydrogen cost). Figure 25 shows the relationship between the amount of hydrogen produced and the annual equipment cost-per-unit hydrogen cost. The calculation can be performed using the following formula. Annual equipment cost hydrogen unit price (v) = Annual equipment cost / v …(26)

[0084] This unit price represents the amount that must be paid per 1 Nm3 of hydrogen produced to cover the annual equipment costs. The more hydrogen produced, the lower the burden. Note that this amount may also include fixed costs related to hydrogen production.

[0085] Next, we calculate the sum of the hydrogen production cost and the annual equipment cost per unit of hydrogen (called the hydrogen cost per unit for recovering production and equipment costs), the value with a profit-based subsidy added to this sum (called the hydrogen cost per unit for recovering production and equipment costs with profit), and the value with an upper limit set on the sum after the addition (called the hydrogen cost per unit for recovering production and equipment costs with a profit limit). Figure 26 shows the hydrogen cost per unit required to recover production and equipment costs. The calculation can be achieved using the following formula. Manufacturing cost, equipment cost, and hydrogen recovery cost per unit (v) = Hydrogen production cost per unit (v) + Annual equipment cost and hydrogen recovery cost per unit (v) Profit-bearing hydrogen cost per unit (v) = Profit-bearing hydrogen cost per unit (v) × Multiplier Hydrogen unit price for recovering manufacturing and equipment costs with profit cap (v) = min(profit-bearing hydrogen unit cost for recovering manufacturing costs and equipment costs (v), upper limit) …(27)

[0086] Here, the subsidy amount is calculated by subtracting the hydrogen sales price from the hydrogen unit price at which manufacturing and equipment costs are recovered with a profit cap. Subsidy amount (v) = Hydrogen unit price that recovers manufacturing costs and equipment costs with profit cap (v) - Hydrogen sales unit price (v) ... (28) The calculation method for the subsidy amount obtained here is just one example, and the subsidy amount may be calculated using the value calculated by the hydrogen production plant revenue device 1, or it may be calculated using the hydrogen production amount calculation device 3.

[0087] (2) Hydrogen production amount calculation unit 291 The hydrogen production volume calculation unit 291 uses the calculation results of the hydrogen production unit price calculation unit 281 to calculate the revenue per unit of hydrogen produced, or the revenue of the hydrogen production plant if subsidies are provided, as follows: Revenue (without subsidies) = Hydrogen sales price (v) × v Revenue (with subsidies) = Profit capped manufacturing costs, equipment costs, recovered hydrogen unit price (v) × v Expenditure = Hydrogen production cost (v) × v + Annual equipment costs Revenue = Income (with subsidies) - Expenses …(29) Here, v, which maximizes annual revenue, represents the appropriate hydrogen production amount relative to the installed capacity. This relationship is shown in Figure 27.

[0088] Next, the hydrogen production amount calculation unit 291 calculates the revenue of the hydrogen production plant when the subsidy amount is fixed. In the method shown in Figure 27, the subsidy amount takes the form of depending on the amount of hydrogen produced, but in reality, when receiving a subsidy, it is conceivable that the subsidy is determined based on the hydrogen production amount applied for in advance, and the subsidy amount does not depend on the actual amount of hydrogen produced. Thus, the calculation method for finding the amount of hydrogen produced that maximizes revenue with respect to a fixed subsidy amount is as follows. In this case, the subsidy amount given in the following formula is the value of v at which the balance is maximized in the hydrogen unit price (v) that recovers production costs and equipment costs with a profit limit. Income (with subsidy) = Amount of subsidy given × v Expenditure = Hydrogen production cost (v) × v + Annual equipment costs Revenue = Income (with subsidies) - Expenses …(30) The above relationship is shown in Figure 28. The maximum profit is achieved when the amount of hydrogen produced is less than in the case shown in Figure 27.

[0089] By using the method described above, it becomes possible to calculate an appropriate amount of hydrogen to be produced in relation to the plant's equipment capacity, taking into account subsidies that fluctuate depending on the amount of hydrogen produced, as well as fixed subsidies. Furthermore, the graphs used in explaining this method may be presented to the user, thereby providing them with useful information.

[0090] (Fourth Embodiment) A fourth embodiment will be described, which calculates the expected value of plant revenue using the hydrogen production plant revenue calculation device of the first and second embodiments. Figure 29 shows the configuration of the hydrogen production plant revenue expected value calculation device 4 according to the fourth embodiment.

[0091] The hydrogen production plant revenue expectation calculation device 4 is an improved version of the hydrogen production plant revenue calculation device 1 of the first and second embodiments, further equipped with an expected value calculation unit 60, and with the addition of occurrence probability and, if necessary, a model construction method as input data. Components common to the first and second embodiments are indicated with common reference numerals, and redundant explanations are omitted.

[0092] In the hydrogen production plant expected revenue calculation device 4 of the fourth embodiment, a scenario having multiple input data sets is taken as input, and the revenue for each input data is calculated in the same manner as in the first and second embodiments. The expected value calculation unit 60 then calculates the expected revenue using the obtained results and the probability of occurrence of the input data. The expected value calculation unit 60 is an operation block that realizes probability calculations.

[0093] The specific calculation steps in the fourth embodiment are as follows: Step 1: Calculate the revenue for each input data i and set it as revenue(i). Step 2: Let p(i) be the probability of input data i occurring.

[0094]

number

[0095] In summary, for example, by fixing the equipment capacity within a scenario and varying the electricity rate and its probability of occurrence for each data set, we can calculate the expected return when the assumed value of the electricity rate has a range. Similarly, by changing the model construction data and model construction method and calculating the expected return, we can calculate the expected aggregate when the assumed values ​​of various subsidy amounts have a range.

[0096] Here, the hydrogen production volume calculation device 3 of the third embodiment may be provided instead of the hydrogen production plant revenue calculation device 1 of the first and second embodiments. In this case, in addition to the expected revenue, the expected revenue when the subsidy amount is fixed will be calculated, and it will be possible to output the expected hydrogen production volume that maximizes the revenue instead of the revenue.

[0097] (Fifth embodiment) A fifth embodiment will be described in which the hydrogen production plant revenue expectation calculation device of the fourth embodiment calculates expected revenue over multiple years. Figure 30 shows the configuration of the hydrogen production plant revenue expectation calculation device 5 according to the fifth embodiment.

[0098] The fifth embodiment differs from the fourth embodiment in the input data. As shown in Figure 30, in this embodiment, each input data 10x to 10z in the fourth embodiment is divided into periods (T1 to T3 in the figure), and together they constitute scenario 10h.

[0099] In this embodiment, the hydrogen production plant revenue calculation device 1 calculates revenue for each period in the input data, sums the revenues based on these calculations, and then calculates the expected value of the final scenario by multiplying the probability of occurrence of multiple input data by the probability of occurrence to calculate the overall expected value.

[0100] The specific calculation steps in the fifth embodiment are as follows: Step 1: Calculate the revenue for each input data i and each period j, and set it as period revenue (i,j). Step 2: For each input data i, sum the total over all periods to obtain the total revenue (i). Step 3: Let p(i) be the probability of input data i occurring.

[0101]

number

[0102] Here, the hydrogen production volume calculation device 3 of the third embodiment may be provided instead of the hydrogen production plant revenue calculation device 1 of the first and second embodiments. In this case, in addition to the expected revenue for the entire period, the expected revenue for the entire period when the subsidy amount is fixed will be calculated, and furthermore, instead of revenue, it will be possible to output the expected hydrogen production volume for each period or scenario that maximizes revenue.

[0103] (Sixth Embodiment) A sixth embodiment will be described, which uses the hydrogen production plant expected revenue calculation device 4 of the fourth embodiment to calculate the appropriate equipment capacity of a hydrogen production plant. Figure 31 shows the configuration of the hydrogen production plant equipment capacity calculation device 6 of the sixth embodiment.

[0104] The hydrogen production plant equipment capacity calculation device 6 according to this embodiment assigns occurrence probabilities to the scenarios in the fourth or fifth embodiment, and uses this group of scenarios as input to calculate the expected return for each individual scenario using the method of the fourth or fifth embodiment. Then, using this calculation result and the occurrence probabilities of the scenarios, it calculates the expected return for each individual scenario. Furthermore, the comparison unit selects the one with the highest expected return and calculates the equipment capacity for that scenario.

[0105] The specific calculation steps in the sixth embodiment are as follows: Step 1: Calculate the revenue for each input scenario k and set it as the expected revenue (k). Step 2: Output the equipment capacity for the largest scenario among the expected revenues. Using the method described above, it is possible to calculate the equipment capacity that minimizes the expected value among multiple equipment capacity scenarios.

[0106] In addition, the expected value calculation unit in the fourth or fifth embodiment may output pairs of probability and return. In this case, in the sixth embodiment, the comparison unit will compare the pairs of probability and return. For example, when the distributions of scenario A and scenario B are as shown in Figure 32, scenario A is selected in terms of expected return, but because scenario A has a broad-tailed distribution, there is a risk that the return will be low. In such a case, the risk of low return can be avoided by taking a method in which the probability of the return being lower than a certain threshold 1 is calculated, and if that probability is greater than threshold 2 (for example, 5%), the scenario is not selected.

[0107] Although several embodiments of the present invention have been described above, these embodiments are presented as examples only and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims of the invention and its equivalents. [Explanation of symbols]

[0108] 1...Hydrogen production plant revenue calculation device, 3...Hydrogen production volume calculation device, 4,5...Hydrogen production plant expected revenue calculation device, 6...Hydrogen production plant equipment capacity calculation device, 10...Input unit, 20...Calculation unit, 30...Storage unit, 40...Output unit, 211...Sales revenue calculation unit, 221...Sales revenue auxiliary calculation unit, 231...Operating cost calculation unit, 241...Operating cost auxiliary calculation unit, 251...Equipment cost calculation unit, 261...Equipment cost auxiliary calculation unit, 271...Revenue calculation unit.

Claims

1. An input unit for acquiring a hydrogen production and sales plan for a hydrogen production plant, operational parameters of the hydrogen production plant, equipment capacity plan for the hydrogen production plant, and data for constructing an estimated model of hydrogen production, A sales revenue calculation unit comprising: a sales price estimation model construction unit that constructs a sales price estimation model based on the estimation model construction data; and a sales revenue calculation unit that predicts hydrogen sales revenue based on the sales price estimation model and the hydrogen production and sales plan. An operating cost calculation unit comprising: an operating cost estimation model construction unit that constructs an estimation model for the operating costs required for hydrogen production based on the estimation model construction data; and an operating cost calculation unit that predicts the operating costs based on the estimation model for operating costs, the hydrogen production and sales plan, and the operating parameters, A cost calculation unit that predicts the cost of the hydrogen production equipment based on the aforementioned equipment capacity plan, A sales revenue subsidy calculation unit having a sales price subsidy calculation unit that predicts a first subsidy amount according to the sales price of hydrogen, and a sales volume subsidy calculation unit that predicts a second subsidy amount according to the sales volume of hydrogen, An operating cost subsidy calculation unit comprising: an operating cost subsidy estimation model construction unit that constructs an estimation model for the subsidy for the operating costs based on the estimation model construction data; and an operating cost subsidy calculation unit that predicts a third subsidy amount for the operating costs based on the estimation model for the subsidy for the operating costs, the hydrogen production and sales plan, and the operating parameters, An equipment cost subsidy calculation unit having: an equipment cost subsidy estimation model construction unit that constructs an estimation model for the subsidy for the equipment cost based on the estimation model construction data; and an equipment cost subsidy calculation unit that predicts a fourth subsidy amount for the equipment cost based on the estimation model for the subsidy for the equipment cost and the equipment capacity plan of the hydrogen production plant, The system comprises a revenue calculation unit that predicts the profitability of the hydrogen production plant based on the aforementioned sales revenue, the aforementioned operating expenses, the aforementioned equipment costs, and the aforementioned first to fourth subsidy amounts, The aforementioned sales price subsidy calculation unit is: A sales price subsidy estimation model construction unit constructs a subsidy estimation model corresponding to the sales price of hydrogen based on the aforementioned estimation model construction data, The system includes a sales price subsidy calculation unit that predicts the first subsidy amount based on the sales price of hydrogen, using an estimation model for the subsidy based on the sales price of hydrogen and the hydrogen production and sales plan. The aforementioned sales volume auxiliary calculation unit is: A sales volume auxiliary estimation model construction unit constructs an auxiliary estimation model corresponding to the sales volume of hydrogen based on the estimation model construction data, The system includes an estimation model for the subsidy corresponding to the hydrogen sales volume and a sales volume subsidy calculation unit that predicts the second subsidy amount corresponding to the hydrogen sales volume based on the hydrogen production and sales plan. A hydrogen production plant revenue calculation device characterized by the following:

2. A hydrogen production plant revenue calculation device according to Claim 1, The hydrogen production plant revenue calculation device is characterized in that the operating cost calculation unit calculates the minimized operating cost by solving a mathematical optimization problem consisting of an objective function that minimizes operating costs and constraints that determine the constraints on operation, based on the hydrogen production and sales plan, the operating parameters, and the equipment capacity plan.

3. A hydrogen production plant revenue calculation device according to Claim 1, An expected value calculation unit takes a scenario consisting of a data set in which probabilities are assigned to each of multiple input data as input, and calculates the expected return from the return and probability for each input data, A hydrogen production plant expected revenue calculation device equipped with the following features.

4. A hydrogen production plant revenue calculation device according to Claim 1, The system takes a scenario consisting of a set of input data with multiple periods and probabilities as input, and calculates the expected return for the entire period from the return and probability for the entire period for each input data, and A hydrogen production plant expected revenue calculation device equipped with the following features.

5. A hydrogen production plant expected revenue calculation device according to claim 3 or claim 4, A comparison unit compares and selects the expected revenue calculated from multiple scenarios, and outputs the equipment volume for that scenario. A hydrogen production plant equipment capacity calculation device equipped with the following features.

6. The hydrogen production plant revenue calculation device according to claim 1, characterized in that the equipment cost calculation unit predicts the equipment cost by dividing the equipment cost of the hydrogen production equipment by its useful life.

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