Method for predicting costs and establishing production plan for integrated coal gasification combined cycle

Abstract

The present invention provides a method for predicting costs and establishing a production plan for an integrated coal gasification combined cycle, the method comprising the steps of: a) analyzing a heating value of coal for each mixing ratio on the basis of a fuel, which is coal or mixed coal, energy sources including power, thermal energy, and synthesis gas, and physical properties and amounts of changes in the physical properties of the fuel; b) analyzing a production amount and production quality of a finally produced energy source according to the physical properties of the fuel; c) identifying a stock and a scheduled stock of the fuel; d) predicting demand for the energy source according to at least one of season, region, and consumer; e) calculating the optimal fuel mixing ratio for each finally produced energy source on the basis of the stock and the scheduled stock of the fuel; f) calculating a unit price of the fuel; g) calculating a production cost of an integrated coal gasification combined cycle, which reflects the unit price of the fuel calculated in step f), and comparing the calculated production cost with a planned profit; and h) when the production cost calculated in step g) falls short of the planned profit, setting the optimal fuel mixing ratio of step e) to a mixing ratio corresponding to the planned profit.

Description

Methods for Cost Forecasting and Production Planning of Coal Gasification Combined Cycle Power Generation

[0001] The present invention relates to a method for cost prediction and production planning of coal gasification combined cycle power generation. Specifically, it relates to a method for predicting costs by determining an optimal mixing ratio based on the physical properties of coal and the production environment, and based on this, enabling the establishment of an efficient production plan and economical operation.

[0002] Although coal is one of the raw materials with guaranteed supply stability due to its abundant and extensive global reserves, the volatility of coal prices has increased as the global supply and demand structure undergoes real-time changes driven by factors such as rising demand for thermal coal in countries like China and India, and export restrictions imposed by major coal-producing nations. Furthermore, demand from developed countries has begun to rise as the value of clean coal utilization technologies, such as the Integrated Gasification Combined Cycle (IGCC), which emits lower levels of pollutants like carbon dioxide and sulfur dioxide compared to conventional coal power generation, increases. Consequently, as coal supply volumes and costs fluctuate sensitively depending on international affairs and natural disasters, it is necessary to diversify coal sources and secure process technologies capable of maintaining a certain level of gasification efficiency to ensure the stable operation of IGCC.

[0003] Korean Registered Patent Publication No. 10-0695222 relates to a method for evaluating coal operating costs and a computer-readable recording medium storing a program for implementing the method. In a method for evaluating coal operating costs in a thermal power plant using a coal blending program executed by a computer equipped with an input device, an output device, a computing device, and a storage means, the method comprises: (a) receiving a selection signal for an incoming coal characteristics mode among menu icons on the main screen of a coal operating cost evaluation system; (b) receiving incoming coal characteristics and storing said incoming coal characteristics as database information; (c) receiving a selection signal for a coal management mode among said menu icons and receiving a coal blending type selection signal. and (d) receiving a selection signal of an item icon in the coal management mode, and calculating the operating costs of one or more detailed items of each item classified into unloaded coal items, loaded coal items, combustion items, and emission and byproduct treatment items using a calculation formula based on a theoretical formula and an empirical correlation formula based on the incoming coal characteristics stored in the database information, and outputting the results to a monitoring screen of the coal management mode, wherein the calculation formula based on the theoretical formula is a calculation formula for dry exhaust gas, a calculation formula for fuel moisture, a calculation formula for fuel hydrogen, and a calculation formula for air moisture, and the empirical correlation formula is a calculation formula representing the trend of combustion characteristic data calculated over a certain period according to combustion characteristics. The present invention provides a method for evaluating coal operating costs according to coal type and co-consumption ratio.

[0004] Chinese Published Patent Application No. 2024-10738096 relates to a method, apparatus, facility, and medium for determining a coke-optimized blend of coal, comprising the steps of: determining a quality index of coke obtained after coking with different cooperating coals and a coal blending cost of said cooperating coals; the quality index including at least one of coke sulfur content, coke ash content, crushing strength, abrasion strength, and post-reaction strength; determining the degree of adaptation of said blended coals based on said quality index and said blended coal cost; and selecting said blended coal with the smallest degree of adaptation as the optimal blended coal.

[0005] Chinese Patent Publication No. 2023-11522314 discloses a coal blending method with equivalent performance.

[0006] European Patent Publication No. 2015-198285 relates to a method for gasifying a carbonaceous material at an optimized material yield and production cost, a process for thermochemically converting the charge of a carbonaceous material into a synthesis gas to produce a fuel or other product of interest, in particular a liquid fuel or other synthetic product, wherein the step of gasifying the charge of the carbonaceous material in a reactor (1) is performed, the step of purifying the synthesis gas produced by gasification is performed, the step of decarbonizing the purified gas is performed, and the step of synthesizing the fuel or fuel is performed, and further comprising an intermediate step selected from one of the following three intermediate steps a) to c): a) a step of reacting the synthesis gas with water (WGS) upstream of the decarbonization step, or b) hydrogen produced by water electrolysis is added to the synthesis gas downstream of the gas purification step, or c) a mixture of the synthesis gas and hydrogen produced by water electrolysis downstream of the gas purification step undergoes a reverse gas-water reaction step (RWGS) to produce hydrogen by water electrolysis. It includes a method for selecting one or another of steps a) to c) depending on the function of the required electricity cost.

[0007] (Prior Art Literature)

[0008] (Patent Literature)

[0009] Korean Registered Patent Publication No. 10-0695222

[0010] Chinese Published Patent Application No. 2024-10738096

[0011] Chinese Published Patent Application No. 2023-11522314

[0012] The objective of the present invention is to provide a process control method for coal gasification combined cycle power generation using coal having different properties as feedstocks, wherein the coal blending method for coal gasification combined cycle power generation.

[0013] To achieve this purpose, a method for predicting costs and establishing production plans for coal gasification combined cycle power generation is provided, comprising: a) a step of analyzing the calorific value of coal according to the mixing ratio based on the physical properties and changes in physical properties of the fuel, an energy source including coal or mixed coal, electricity, thermal energy, and syngas; b) a step of analyzing the production volume and production quality of the final produced energy source according to the physical properties of the fuel; c) a step of confirming the current amount and planned amount of the fuel; d) a step of predicting the demand for one or more of the energy source by season, region, and consumer; e) a step of calculating the optimal fuel mixing ratio for each final produced energy source based on the current amount and planned amount of the fuel; f) a step of calculating the unit price of the fuel; g) a step of calculating the production cost of coal gasification combined cycle power generation reflecting the fuel unit price calculated through step f) and comparing it with the planned profit; and h) a step of setting the optimal fuel mixing ratio of step e) to the mixing ratio corresponding to the planned profit if the production cost calculated in step g) is less than the planned profit.

[0014] In addition, in step a) above, the physical properties include one or more of the fuel particle size, particle shape, fixed carbon, volatile matter, moisture, ash content, and ratio, and the amount of change in physical properties may include one or more of the production environment information of the final production energy source production date and the scheduled production date.

[0015] In addition, to calculate the unit price of coal in step f) above, one or more of coal prices, coal production volume by country, policy information, policy trends, and situational information may be used.

[0016] In addition, the optimal fuel mixture ratio corresponding to the planned profit of step g) and the planned profit of step h) above may utilize data stored in a separate database storage means.

[0017] In addition, the above production environment information is temperature and humidity data, and based on the above temperature and humidity data, the calorific value can be analyzed by predicting one or more of the changes in moisture absorption and volatile components.

[0018] In addition, step b) above may utilize one or more of the energy source efficiency, fixed carbon, and volatile matter ratios for analysis.

[0019] In addition, to predict the above costs and establish a production plan, one or more of artificial intelligence means and big data means can be used to calculate the profit or mixing ratio.

[0020] In addition, the production cost of step g) above includes one or more of the operating rate of the coal gasification combined cycle power plant, maintenance costs, carbon dioxide emission costs, environmental regulation costs, and fuel costs, and can be adjusted in real time in conjunction with market conditions.

[0021] In addition, the optimal fuel blend ratio corresponding to the above-mentioned planned profit may be data calculated using a multivariable optimization algorithm that incorporates profitability and environmental regulation information to optimize production efficiency or costs.

[0022] In addition, the demand forecast in step d) above may utilize one or more of the following information: contract conditions between suppliers and consumers, power grid operation status, and energy market trends.

[0023] The present invention can also be provided in a form that combines various means for solving the above problem.

[0024] According to the present invention, energy efficiency can be optimized by mixing fuels with different characteristics in an Integrated Gasification Combined Cycle (IGCC) system.

[0025] In addition, the profitability of various energy sources (electricity, thermal energy, syngas) can be predicted by reflecting seasonal electricity demand and fuel import and export costs.

[0026] In addition, it can provide a method to determine the optimal energy source and operating conditions based on predicted data.

[0027] In addition, it is possible to provide a production plan that calculates the optimal coal mixing ratio considering the type of final production energy source, power generation cost, and product quality, based on production unit cost, production volume, and demand forecast information.

[0028] FIG. 1 is a schematic diagram of the steps for establishing cost forecasting and production planning, which is an embodiment of the present invention.

[0029] Embodiments that enable a person skilled in the art to easily implement the present invention are described in detail below with reference to the attached drawings. However, in describing the operating principles of preferred embodiments of the present invention in detail, if it is determined that a detailed description of related known functions or configurations may unnecessarily obscure the essence of the present invention, such detailed description is omitted.

[0030] In addition, the same reference numerals are used for parts having similar functions and operations throughout the drawings. Throughout the specification, when a part is described as being connected to another part, this includes not only cases where they are directly connected, but also cases where they are indirectly connected with other elements in between. Furthermore, unless specifically stated otherwise, the inclusion of a certain component does not exclude other components but implies that additional components may be included.

[0031] In addition, any limitation or addition to an embodiment in this specification may apply not only to a specific embodiment but also to other embodiments.

[0032] Additionally, throughout the description and claims of the present invention, items indicated in the singular include items indicated in the plural unless otherwise noted.

[0033] The present invention will be described in detail with reference to the drawings and embodiments.

[0034] A person skilled in the art to which this invention pertains will be able to perform various applications and modifications within the scope of this invention based on the above content.

[0035] FIG. 1 is a schematic diagram of the steps for establishing cost forecasting and production planning, which is an embodiment of the present invention.

[0036] The present invention provides a method for predicting costs and establishing production plans for coal gasification combined cycle power generation, comprising: a) a step of analyzing the calorific value of coal according to a mixing ratio based on the physical properties and changes in physical properties of the fuel, an energy source including coal or mixed coal, electricity, thermal energy, and synthesis gas; b) a step of analyzing the production volume and production quality of the final produced energy source according to the physical properties of the fuel; c) a step of confirming the current amount and planned amount of the fuel; d) a step of predicting demand for one or more of the energy source by season, region, and consumer; e) a step of calculating the optimal fuel mixing ratio for each final produced energy source based on the current amount and planned amount of the fuel; f) a step of calculating the unit price of the fuel; g) a step of calculating the production cost of coal gasification combined cycle power generation reflecting the fuel unit price calculated through step f) and comparing it with the planned profit; and h) a step of setting the optimal fuel mixing ratio of step e) to the mixing ratio corresponding to the planned profit if the production cost calculated in step g) is less than the planned profit.

[0037] In addition, in step a) above, the physical properties include one or more of the fuel particle size, particle shape, fixed carbon, volatile matter, moisture, ash content, and ratio, and the amount of change in physical properties may include one or more of the production environment information of the final production energy source production date and the scheduled production date.

[0038] In addition, to calculate the unit price of coal in step f) above, one or more of coal prices, coal production volume by country, policy information, policy trends, and situational information may be used.

[0039] In addition, the optimal fuel mixture ratio corresponding to the planned profit of step g) and the planned profit of step h) above may utilize data stored in a separate database storage means.

[0040] In addition, the above production environment information is temperature and humidity data, and based on the above temperature and humidity data, the calorific value can be analyzed by predicting one or more of the changes in moisture absorption and volatile components.

[0041] In addition, step b) above may utilize one or more of the energy source efficiency, fixed carbon, and volatile matter ratios for analysis.

[0042] In addition, the above step b) can analyze product quality based on efficiency, the calorific value of the energy source, and the ratio of fixed carbon and volatile matter of the fuel.

[0043] In addition, to predict the above costs and establish a production plan, one or more of artificial intelligence means and big data means can be used to calculate the profit or mixing ratio.

[0044] In addition, step c) above may utilize one or more of the following information: contract volume and delivery schedule by fuel supplier, fuel inventory status and estimated consumption, fuel procurement costs and logistics costs, and fuel holding regions and storage facility capacities.

[0045] In addition, step e) above may use one or more of the calorific value and energy efficiency by fuel mixing ratio, production costs and maintenance costs by fuel mixing ratio, carbon dioxide emissions and environmental regulation compliance costs by fuel mixing ratio, and estimated production volume and market demand data by final production energy source to calculate the optimal fuel mixing ratio.

[0046] In addition, step e) above may utilize a multivariable optimization algorithm.

[0047] In addition, if a multivariate optimization algorithm is used in step e) above, it can be calculated to simultaneously optimize production efficiency and cost.

[0048] In addition, the production cost of step g) above includes one or more of the operating rate of the coal gasification combined cycle power plant, maintenance costs, carbon dioxide emission costs, environmental regulation costs, and fuel costs, and can be adjusted in real time in conjunction with market conditions.

[0049] In addition, the optimal fuel blend ratio corresponding to the above-mentioned planned profit may be data calculated using a multivariable optimization algorithm that incorporates profitability and environmental regulation information to optimize production efficiency or costs.

[0050] In addition, the above profitability and environmental regulation information can be reflected in the above multivariable optimization algorithm, and the above stored database can be utilized.

[0051] In addition, the demand forecast in step d) above may utilize one or more of the following information: contract conditions between suppliers and consumers, power grid operation status, and energy market trends.

[0052] In addition, a heat generation correction factor may be additionally applied according to the above temperature and humidity changes.

[0053] In addition, the optimal production volume can be automatically calculated by reflecting the aforementioned seasonal power demand patterns.

[0054] In addition, a prediction model learned from past fuel supply volumes, market trends, and electricity usage patterns by consumer can be applied.

[0055] In addition, an algorithm that optimizes carbon dioxide emission reduction can be applied when calculating the above fuel mixture ratio.

[0056] In addition, the following [Equation 1] may be used to calculate the calorific value of coal according to the mixing ratio in step a) above.

[0057] [Formula 1]

[0058]

[0059] In addition, the following [Equation 2] can be used for production cost optimization and efficiency maximization in step e) above.

[0060] [Equation 2]

[0061]

[0062] In addition, the following [Equation 3] may be used to predict production costs in step g) above.

[0063] [Equation 3]

[0064]

[0065] In addition, carbon dioxide emissions according to the fuel mixture ratio can be calculated using the following [Equation 4].

[0066] [Equation 4]

[0067]

[0068] Therefore, the scope of the present invention should not be limited to the described embodiments, but should be defined by the claims set forth below as well as equivalents thereof.

Claims

1. Fuel that is coal or mixed coal; Energy sources including electric power, thermal energy, and syngas; a) Step of analyzing the calorific value of coal according to mixing ratio based on the physical properties and changes in physical properties of the above fuel; b) Step of analyzing the production volume and quality of the final energy source according to the physical properties of the above fuel; c) Step of verifying the amount of fuel held and the planned amount of fuel held; d) Step of predicting one or more of the seasonal, regional, and consumer-specific demand for the above energy source; e) Step of calculating the optimal fuel mixing ratio for each final produced energy source based on the above fuel holdings and planned holdings; f) Step of calculating the unit price of the above fuel; Step g) of calculating the production cost of a coal gasification combined cycle power generation reflecting the fuel unit price calculated through the above step f), and comparing it with the planned profit; A method for predicting costs and establishing production plans for coal gasification combined cycle power generation, comprising: a step h) in which, if the production cost calculated in step g) is less than the planned revenue, the optimal fuel mixing ratio in step e) is set to a mixing ratio corresponding to the planned revenue.

2. In Paragraph 1, In step a) above, the physical properties include one or more of the fuel particle size, particle shape, fixed carbon, volatile matter, moisture, ash content, and ratio, and A method for predicting costs and establishing production plans for coal gasification combined cycle power generation, comprising one or more of the production environment information of the final production energy source production date and the scheduled production date, wherein the above change in physical properties.

3. In Paragraph 1, A method for predicting costs and establishing production plans for coal gasification combined cycle power generation, using one or more of coal prices, coal production volumes by country, policy information, policy trends, and situational information to calculate the unit price of coal in step f) above.

4. In Paragraph 1, A method for predicting costs and establishing production plans for coal gasification combined cycle power generation using data stored in a separate database storage means, wherein the optimal fuel mixing ratio corresponding to the planned profit of step g) and the planned profit of step h) above.

5. In Paragraph 2, The above production environment information is temperature and humidity data, and A method for predicting costs and establishing production plans for coal gasification combined cycle power generation by predicting one or more of changes in moisture absorption and volatile components based on the above temperature and humidity data to analyze calorific value.

6. In Paragraph 1, The above step b) is a method for predicting costs and establishing production plans for coal gasification combined cycle power generation, utilizing at least one of the energy source efficiency, fixed carbon, and volatile matter ratios in the analysis.

7. In Paragraph 1, A method for predicting costs and establishing production plans for coal gasification combined cycle power generation, which calculates revenue or mixing ratios by using one or more of artificial intelligence means and big data means to predict the costs and establish production plans as described above.

8. In Paragraph 1, The production cost of step g) above includes one or more of the operating rate of the coal gasification combined cycle power plant, maintenance costs, carbon dioxide emission costs, environmental regulation costs, and fuel costs, and Method for predicting coal gasification combined cycle power generation costs and establishing production plans that are adjusted in real-time in conjunction with market conditions.

9. In Paragraph 4, A method for predicting costs and establishing production plans for coal gasification combined cycle power generation, wherein the optimal fuel mixing ratio corresponding to the above-mentioned planned revenue is data calculated using a multivariable optimization algorithm that reflects profitability and environmental regulation information to optimize production efficiency or costs.

10. In Paragraph 1, A method for predicting costs and establishing production plans for coal gasification combined cycle power generation, wherein the demand forecasting in step d) above utilizes one or more of the following information: contract conditions between suppliers and consumers, power grid operation status, and energy market trends.

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