Mine scene CCHP integrated system configuration scheme optimization method and system

Abstract

The invention relates to the technical field of integrated system configuration, and provides a CCHP integrated system configuration scheme optimization method and system for a mine scene. The method for optimizing the configuration scheme of the CCHP integrated system in the mine scene comprises the following steps of: constructing a multi-target mixed integer linear programming model comprising an economical target, an energy consumption target and an environmental target on the basis of operating parameters of the mine CCHP integrated system; based on a multi-target mixed integer linear programming model, an economical target is used as a main target by adopting a constraint method, an energy consumption target and an environmental target are limited in a set interval and are converted into constraint conditions, and the optimal equipment model, the optimal equipment number and the optimal real-time output strategy are determined to serve as a final configuration scheme of the mine CCHP integrated system. According to the method, automatic optimization type selection of the equipment can be realized, the optimal equipment type, number and real-time output strategy are determined, a scientific basis is provided for equipment configuration of the mine energy system, and the rationality and accuracy of equipment configuration are improved.

Description

Technical Field

[0001] This invention relates to the field of integrated system configuration technology, and in particular to an optimization method and system for CCHP integrated system configuration in mining scenarios. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Mines are complex industrial systems integrating energy conversion, transmission, distribution, and end-use. Mining production is highly dependent on primary energy sources such as fossil fuels, making energy supply stability susceptible to external market fluctuations and posing a risk of supply disruptions. The system's load structure is complex, with high-energy-consuming components, and the load fluctuates dramatically with production schedules, resulting in low overall system energy efficiency and a continuous increase in carbon emission intensity. This makes traditional energy models unsuitable for the low-carbon development requirements of green mine construction. Therefore, constructing a new multi-energy synergistic energy system and establishing an optimization configuration method based on a real equipment database have become key pathways to solving the energy dilemma of mines and promoting green mine construction.

[0004] Existing research, when targeting the specific scenario of mines, has some models that do not adequately consider the high volatility of mine loads and the complexity of multiple energy demands, leading to challenges in achieving efficient coordination of sources, grids, loads, and storage. Moreover, in terms of equipment selection and modeling, the construction of equipment databases based on real-world operating performance parameters is relatively weak, which makes it necessary to verify the accuracy and engineering applicability of optimization schemes in the complex and harsh environment of mines. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a method and system for optimizing the configuration of a CCHP integrated system in a mining scenario. This system enables automatic optimization and selection of equipment, determines the optimal equipment model, number of units, and real-time output strategy, provides a scientific basis for the configuration of mining energy system equipment, and improves the rationality and accuracy of equipment configuration.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: The first aspect of this invention provides an optimization method for the configuration scheme of a CCHP integrated system in a mining scenario.

[0007] In one or more embodiments, a method for optimizing the configuration of a CCHP integrated system in a mining scenario is provided, including: Based on the operating parameters of the integrated CCHP system in a mine, a multi-objective mixed integer linear programming model is constructed, which includes economic, energy consumption, and environmental objectives. The economic objective is to minimize the annualized total cost of the integrated CCHP system in the mine; the energy consumption objective is to minimize the total primary energy consumed by the operation of the integrated CCHP system in the mine; and the environmental objective is to minimize the total greenhouse gas emissions caused by the operation of the integrated CCHP system in the mine. Based on a multi-objective mixed-integer linear programming model, using The constraint method takes economic objectives as the primary objective, restricts energy consumption and environmental objectives within a set range, and transforms them into constraints to determine the optimal equipment model, number of units, and real-time output strategy, which serves as the final configuration scheme for the mine CCHP integrated system.

[0008] As one implementation method, the process of determining the optimal equipment model, number of units, and real-time output strategy is as follows: In terms of energy consumption targets and environmental targets Within the limits, the multi-objective mixed integer linear programming model is solved to obtain a set of system scheme configurations for equipment type, number of units, and real-time output strategy; Construct indicators at the economic level, such as annualized total cost, investment payback period, and investment efficiency assessment; construct indicators at the energy level, such as primary energy consumption and primary energy saving rate; and construct indicators at the environmental level, such as annual carbon emissions and carbon reduction rate; and standardize all of the above indicators. The subjective weights of each standardized indicator are calculated using the analytic hierarchy process (AHP), and the objective weights of each standardized indicator are calculated using the principal component analysis (PCA). Based on the game theory-based combination weighting method, the optimal combination weights of each standardized indicator are obtained with the goal of achieving Nash equilibrium. The optimal system configuration is determined by the weighted sum of the optimal combination weights of each standardized indicator, which is the highest score. This means the optimal equipment model, number of units, and real-time output strategy.

[0009] As one implementation method, in the process of obtaining the optimal combination weights of various standardized indicators using a game theory-based combinatorial weighting method, subjective weights and objective weights are regarded as two sides in a game, and an optimal set of combination coefficients is found through mathematical optimization. and This determines the final weight of each standardized indicator. = and and The overall deviation is the smallest; among them, Subjective weighting; For objective weighting.

[0010] As one implementation method, a positive standardization formula is used for benefit-oriented indicators such as primary energy saving rate and carbon emission reduction rate:

[0011] in, For the first The first scheme The standardized values ​​of each indicator; For the first The first scheme The original values ​​of each indicator; For the first The maximum value of each indicator across all options; For the first The minimum value of each indicator among all possible solutions.

[0012] As one implementation method, negative standardization formulas are used for cost-related indicators such as total annual cost, payback period, primary energy consumption, and annual carbon emissions:

[0013] in, For the first The first scheme The standardized values ​​of each indicator; For the first The first scheme The original values ​​of each indicator; For the first The maximum value of each indicator across all options; For the first The minimum value of each indicator among all possible solutions.

[0014] As one implementation method, the following is adopted: The constraint method takes economic objectives as the primary objective, restricts energy consumption and environmental objectives within a set range, and transforms these objectives into constraints.

[0015] in, The objective function is the economic performance. The objective function is energy consumption. The objective function is environmental. and These are the upper and lower limits for primary energy consumption. and These are the upper and lower limits for carbon emissions; Configure the system solution, including equipment model, number of units, and real-time output strategy; A set of system solution configurations.

[0016] As one implementation method, calculation The range of values ​​and The process of determining the range of values ​​is as follows: To obtain and Minimize respectively , and These three single objectives yield their corresponding optimal solutions; The ideal point is the minimum value That is, to minimize individually The optimal value obtained at that time; The ideal point is the minimum value That is, to minimize individually The optimal value obtained at that time; To obtain and ,Will , and The three single-objective optimal solutions and their corresponding objective function values ​​are listed in a pre-defined storage table; maximum value For storage table The maximum value in this column; maximum value For storage table The maximum value in this column; Ultimately, obtain The range of values and The range of values .

[0017] The second aspect of the present invention provides an optimized system for the configuration of a CCHP integrated system in a mining scenario.

[0018] In one or more embodiments, a CCHP integrated system configuration optimization system for a mining scenario includes: The model building module is used to construct a multi-objective mixed integer linear programming model based on the operating parameters of the mine CCHP integrated system, including economic, energy consumption, and environmental objectives. The economic objective is to minimize the annualized total cost of the mine CCHP integrated system; the energy consumption objective is to minimize the total primary energy consumed by the operation of the mine CCHP integrated system; and the environmental objective is to minimize the total greenhouse gas emissions caused by the operation of the mine CCHP integrated system. The scheme optimization module is used for multi-objective mixed-integer linear programming models, employing... The constraint method takes economic objectives as the primary objective, restricts energy consumption and environmental objectives within a set range, and transforms them into constraints to determine the optimal equipment model, number of units, and real-time output strategy, which serves as the final configuration scheme for the mine CCHP integrated system.

[0019] A third aspect of the present invention provides a computer-readable storage medium.

[0020] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the CCHP integrated system configuration scheme optimization method for a mining scenario as described above.

[0021] A fourth aspect of the present invention provides an electronic device.

[0022] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the CCHP integrated system configuration scheme optimization method for mining scenarios described above.

[0023] Compared with the prior art, the beneficial effects of the present invention are: The CCHP integrated system configuration optimization method of the present invention takes a multi-objective mixed integer linear programming model as its core, and uses the constraint method to take the economic objective as the main objective and transform the energy consumption objective and environmental objective into constraint conditions to obtain the optimal equipment model, number of units and real-time output strategy. It realizes the automatic optimization selection of equipment, provides a scientific basis for the equipment configuration of mining energy system, and improves the rationality and accuracy of equipment configuration.

[0024] This invention employs a game theory-based combination weighting method with the goal of achieving Nash equilibrium. It determines the optimal combination weights for each standardized indicator and finally determines the optimal system configuration based on the weighted sum of the optimal combination weights for each standardized indicator. This improves the accuracy of equipment selection and system stability under complex working conditions, and achieves scientific decision-making that takes into account technical feasibility, economic efficiency, and environmental protection. Thus, it provides a key technical path and engineering practice solution for overcoming the energy dilemma of mines and promoting the construction of green mines. Attached Figure Description

[0025] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0026] Figure 1 This is a flowchart of the CCHP integrated system configuration optimization method in a mining scenario according to an embodiment of the present invention; Figure 2This is a schematic diagram of a natural gas combined cooling, heating and power (CCHP) system coupled with ground source heat pump and energy storage in a mining scenario according to an embodiment of the present invention. Figure 3 This is a flowchart of the optimization solution for the CCHP integrated system configuration scheme in a mining scenario according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the optimized system structure of the CCHP integrated system configuration scheme in a mining scenario according to an embodiment of the present invention; Figure 5 This is a schematic diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0027] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0028] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0029] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0030] To address the problems in the background technology, embodiments of the present invention provide a method and system for optimizing the configuration of a CCHP integrated system in a mining scenario. Addressing the diverse energy demands, energy efficiency improvement requirements, and low-carbon development needs of mines, this method enables automatic optimization and selection of CCHP equipment. Simultaneously, it constructs a multi-dimensional evaluation system to provide direction for optimizing the system's economy, energy efficiency, and low-carbon aspects, ultimately promoting the sustainable operation of the mining energy system.

[0031] Figure 1 A schematic diagram of the optimization method for a combined cooling, heating, and power (CCHP) system configuration in a mining scenario, according to an embodiment of the present invention, is provided. Based on the characteristics of mining loads—massive heat demand, significant peak-to-valley electricity load differences, and strong seasonal contrasts in heating and cooling loads—a natural gas CCHP system coupling a ground-source heat pump and energy storage is constructed. This system aims to achieve cascaded energy utilization and multi-energy complementarity; its core architecture is as follows: Figure 2 As shown.

[0032] The CCHP integrated system in the mine is centered around a gas-fired internal combustion engine, which prioritizes the generation of electricity to meet the basic electrical load. It also recovers waste heat from flue gas and cylinder liner water to drive lithium bromide units for cooling and heating, achieving efficient cascaded energy utilization. Ground source heat pumps, as renewable energy devices, leverage their high energy efficiency to handle the basic cooling and heating loads. Thermal / cold storage devices enhance system flexibility and optimize operational economy through peak shaving and valley filling. Gas-fired boilers and electric chillers serve as peak-shaving and backup units, ensuring reliable power supply during extreme loads or main equipment maintenance.

[0033] according to Figure 1 The CCHP integrated system configuration optimization method for the mining scenario in this embodiment may include the following steps S101~S102.

[0034] The specific implementation process of steps S101 to S102 is as follows: Step S101: Based on the operating parameters of the mine CCHP integrated system, construct a multi-objective mixed integer linear programming model that includes economic, energy consumption, and environmental objectives; wherein, the economic objective is to minimize the annualized total cost of the mine CCHP integrated system; the energy consumption objective is to minimize the total primary energy consumed by the operation of the mine CCHP integrated system; and the environmental objective is to minimize the total greenhouse gas emissions caused by the operation of the mine CCHP integrated system.

[0035] In response to the operational characteristics of mines, such as large fluctuations in production load, high proportion of heat demand, and complex energy structure, a complete system mathematical model was established, which includes gas internal combustion engines (GE), gas boilers (GB), electric chillers (EC), lithium bromide absorption waste heat units (LA), ground source heat pumps (GH), batteries (BS), thermal storage tanks (TES), and ice storage (IS), providing a theoretical basis for subsequent equipment selection.

[0036] GE generates electricity, and its flue gas and cylinder liner water waste heat can be used for cooling / heating in the LA, achieving energy cascade utilization. GB, as a supplementary combustion device, converts chemical energy into thermal energy for heating. EC, as a supplementary cooling device, consumes electricity for cooling. LA (dual-effect flue gas hot water type) can efficiently recover the flue gas and hot water waste heat from GE to meet cooling and heating needs. GH is an electrically driven heat pump, and its electro-cooling / heating conversion during cooling / heating is calculated. BS performs peak shaving and valley filling, TES utilizes water for thermal storage, and IS utilizes water-ice phase change for cold storage; all three are used to improve the flexibility and economy of system operation.

[0037] Meanwhile, each device has an upper limit on its installed capacity; the actual output must be within its technical output range. The system must simultaneously meet the real-time balance of electricity, heat, and cooling energy, with electricity supplied collaboratively by the generation unit and the grid. Energy storage devices (BS, TES, IS) must comply with capacity and charge / discharge power constraints, and the capacity must remain balanced at the beginning and end of the operating cycle. In addition, both LA and GH are subject to operating mode constraints, and cannot simultaneously cool and heat within the same time period.

[0038] To achieve coordinated optimization of equipment selection and operation strategies in the CCHP integrated system of mines, a multi-objective mixed-integer linear programming model was constructed. This model includes three core optimization objectives: economic objective... Energy consumption targets Environmental goals .

[0039] Economic objectives The aim is to minimize the system's annualized total cost, expressed as: =

[0040] in, For equipment investment costs, For equipment maintenance costs, For fuel consumption costs, For the electricity purchase fee of the power grid, This is for civil engineering and installation costs.

[0041] Energy consumption target The aim is to minimize the total amount of primary energy consumed by the system during operation, and its expression is: =

[0042] in, and The annual gas heat consumption of gas-fired internal combustion engines and gas-fired boilers, in kWh; The amount of electricity purchased from the grid each year, in kWh; For power grid transmission line loss rate; This represents the average efficiency of a traditional coal-fired power plant.

[0043] Environmental goals The aim is to minimize the total greenhouse gas emissions caused by the system's operation, expressed as: =

[0044] in, Indirect carbon emissions from purchased electricity The direct carbon emissions generated from natural gas consumption.

[0045] To achieve synergistic optimization of the above three objectives, the following approach is adopted: The constraint method is used to obtain the optimal solution set. This method takes one objective function as the main optimization objective and restricts the values ​​of the other objective functions to a specific range, thus transforming them into constraints.

[0046] use The constraint method takes economic objectives as the primary objective, restricts energy consumption and environmental objectives within a set range, and transforms these objectives into constraints.

[0047] in, The objective function is the economic performance. The objective function is energy consumption. The objective function is environmental. and These are the upper and lower limits for primary energy consumption. and These are the upper and lower limits for carbon emissions; Configure the system solution, including equipment model, number of units, and real-time output strategy; A set of system solution configurations.

[0048] Here , and The calculation formulas are respectively , and .

[0049] In the specific implementation process, calculation The range of values ​​and The process of determining the range of values ​​is as follows: To obtain and Minimize respectively , and These three single objectives yield their corresponding optimal solutions; The ideal point is the minimum value That is, to minimize individually The optimal value obtained at that time; The ideal point is the minimum value That is, to minimize individually The optimal value obtained at that time; To obtain and ,Will , and The three single-objective optimal solutions and their corresponding objective function values ​​are listed in a pre-defined storage table; maximum value For storage table The maximum value in this column; maximum value For storage table The maximum value in this column; Ultimately, obtain The range of values and The range of values .

[0050] Step S102: Based on the multi-objective mixed-integer linear programming model, adopt... The constraint method takes economic objectives as the primary objective, restricts energy consumption and environmental objectives within a set range, and transforms them into constraints to determine the optimal equipment model, number of units, and real-time output strategy, which serves as the final configuration scheme for the mine CCHP integrated system.

[0051] In the specific implementation process, combined with Figure 3 The process of determining the optimal equipment model, number of units, and real-time output strategy is as follows: Step a: In terms of energy consumption targets and environmental targets Within the specified limits, a multi-objective mixed-integer linear programming model is solved to obtain a set of system configuration schemes for equipment models, number of units, and real-time output strategies.

[0052] Step b: Construct indicators such as annualized total cost, investment payback period, and investment efficiency at the economic target level; construct indicators such as primary energy consumption and primary energy saving rate at the energy consumption target level; and construct indicators such as annual carbon emissions and carbon reduction rate at the environmental target level; standardize all of the above indicators.

[0053] Based on the characteristics of mining energy systems, a comprehensive evaluation system is constructed from three dimensions: economic efficiency, energy consumption, and environmental impact. All indicators are uniformly categorized as either "cost-based" (lower indicator values ​​are better) or "benefit-based" (higher indicator values ​​are better), laying the foundation for subsequent standardization.

[0054] In terms of economics, in addition to the core indicator of annualized total cost, an investment payback period is added to assess investment efficiency. Regarding energy consumption and the environment, besides the basic indicators of primary energy consumption and annual carbon emissions, primary energy saving rate and carbon emission reduction rate are introduced respectively. By comparing with traditional distributed energy supply systems, the relative performance improvement of the system in terms of energy saving and emission reduction is intuitively reflected. This indicator system achieves a comprehensive measurement of the system's absolute performance and relative degree of improvement.

[0055] Because the dimensions and directions of advantage and disadvantage of each indicator are different, standardization is necessary for comprehensive comparison. The purpose of standardization is to convert all indicator values ​​into dimensionless values ​​between 0 and 1, and to unify them into benefit-oriented indicators where "the larger the value, the better the performance".

[0056] It has One proposed solution to be evaluated. 1 evaluation index, construct the original decision matrix ,in Indicates the first The first scheme The original values ​​of each indicator.

[0057] For benefit-oriented indicators such as primary energy saving rate and carbon emission reduction rate, a positive standardization formula is used:

[0058] in, For the first The first scheme The standardized values ​​of each indicator; For the first The first scheme The original values ​​of each indicator; For the first The maximum value of each indicator across all options; For the first The minimum value of each indicator among all possible solutions.

[0059] For cost-related indicators such as total annual cost, payback period, primary energy consumption, and annual carbon emissions, a negative standardization formula is used:

[0060] in, For the first The first scheme The standardized values ​​of each indicator; For the first The first scheme The original values ​​of each indicator; For the first The maximum value of each indicator across all options; For the first The minimum value of each indicator among all possible solutions.

[0061] After the above standardization process, the original decision matrix... Transformed into a normalized matrix :

[0062] Among them, all Indicates the first The first scheme is in the It performed best on all indicators; This indicates the worst performance.

[0063] Standardization eliminates the dimensional differences between different indicators, unifies the direction of indicator performance, and makes different indicators comparable, thus creating conditions for subsequent comprehensive evaluation based on combined weights.

[0064] Step c: Calculate the subjective weights of each standardized indicator using the analytic hierarchy process (AHP), calculate the objective weights of each standardized indicator using principal component analysis (PCA), and obtain the optimal combination weights of each standardized indicator using a game theory-based combination weighting method with the goal of achieving Nash equilibrium.

[0065] It should be noted that the process of calculating the subjective weights of each standardized indicator using the analytic hierarchy process (AHP) is existing technology and will not be detailed here. Similarly, the process of calculating the objective weights of each standardized indicator using principal component analysis (PCA) is also existing technology and will not be detailed here.

[0066] In other embodiments, those skilled in the art can determine subjective weights using methods such as fuzzy hierarchical analysis, or objective weights using methods such as entropy, depending on the actual situation; these will not be described in detail here.

[0067] By introducing a game theory-based combinatorial weighting method, subjective and objective weights are treated as two sides in a game. The game revolves around the subjectivity and objectivity of multi-objective optimization, aiming to achieve Nash equilibrium. It seeks consistency or compromise between subjective and objective weights to obtain the optimal combinatorial weights for multi-objective optimization. Let the subjective weight of the objective be... Objective weight is In obtaining the optimal combination weights for various standardized indicators using a game theory-based combinatorial weighting method, subjective and objective weights are treated as two sides in a game, and an optimal set of combination coefficients is found through mathematical optimization. and This determines the final weight of each standardized indicator. = and and The overall deviation is the smallest; among them, Subjective weighting; For objective weighting.

[0068] Step d: Based on the weighted sum of the optimal combination weights of each standardized indicator, determine the highest score as the optimal system configuration, i.e., the optimal equipment model, number of units, and real-time output strategy.

[0069] Using the obtained combined weights Each solution will be given a final score:

[0070] in, It is the first The combined weights of each indicator are used. All solutions are ranked according to their comprehensive scores, and the one with the highest score is the optimal solution.

[0071] This embodiment takes the actual load characteristics of a mine as the research object, and generates a Pareto optimal solution set through a multi-objective mixed integer linear programming algorithm based on the ε-constraint method. A comprehensive evaluation system is then used to scientifically evaluate and select the best solution. Specifically, by systematically adjusting the constraint boundaries of economic indicators (annualized total cost), energy consumption indicators (primary energy consumption), and environmental indicators (annual carbon emissions), candidate solutions covering different performance tendencies are generated. Subsequently, a game theory-based combination weighting method is applied to determine the weights of each indicator, calculate the comprehensive score of each solution, and select the system configuration solution with the best overall performance.

[0072] It should be noted that in other embodiments, the game theory combined weighting method can be replaced by the CRITIC objective weighting method or the AHP-entropy weighting hybrid method.

[0073] Specifically, at the equipment selection level, a complete equipment database was constructed, including gas-fired internal combustion engines, lithium bromide waste heat recovery units, gas-fired boilers, electric chillers, ground source heat pumps, and various energy storage devices. This database includes key parameters such as power, efficiency, lifespan, and cost for each device. Based on the optimal equipment configuration, the gas-fired internal combustion engine serves as the core energy supply unit, handling the basic electrical load, while the energy storage devices achieve energy transfer and peak shaving. The system adopts a seasonal operation strategy: in spring, internal combustion engines are prioritized for power and heating, supplemented by heat pumps; during peak summer electricity demand periods, electricity is purchased in moderation, with heat pumps primarily handling cooling and storing cold; in autumn, waste heat is fully recovered and stored; in winter, the ground source heat pumps and lithium bromide units operate at near full load, with the heat storage devices meeting most of the heat demand without starting the gas-fired boiler.

[0074] like Figure 4 As shown, the CCHP integrated system configuration scheme optimization system for mining scenarios provided in this embodiment of the invention can be implemented in software. The CCHP integrated system configuration scheme optimization system for mining scenarios includes the following software modules: model building module 401 and scheme optimization module 402.

[0075] The following is an introduction to the functions of each software module in the CCHP integrated system configuration scheme optimization system for mining scenarios: The model building module 401 is used to construct a multi-objective mixed integer linear programming model based on the operating parameters of the mine CCHP integrated system, including economic, energy consumption, and environmental objectives. The economic objective is to minimize the annualized total cost of the mine CCHP integrated system; the energy consumption objective is to minimize the total primary energy consumed by the operation of the mine CCHP integrated system; and the environmental objective is to minimize the total greenhouse gas emissions caused by the operation of the mine CCHP integrated system. The scheme optimization module 402 is used for a multi-objective mixed-integer linear programming model, employing... The constraint method takes economic objectives as the primary objective, restricts energy consumption and environmental objectives within a set range, and transforms them into constraints to determine the optimal equipment model, number of units, and real-time output strategy, which serves as the final configuration scheme for the mine CCHP integrated system.

[0076] It should be noted that each module in the CCHP integrated system configuration scheme optimization system for mining scenarios in this embodiment of the invention corresponds one-to-one with each step in the CCHP integrated system configuration scheme optimization method for mining scenarios in the above embodiments, and their specific implementation processes are the same, so they will not be repeated here.

[0077] The structure of the electronic device according to an embodiment of the present invention will be described in detail below. Figure 5 This is a schematic diagram of the composition structure of an electronic device provided in an embodiment of the present invention. It can be understood that... Figure 5 The diagram shows only an exemplary structure of the electronic device, not the entire structure. Some or all of the structures shown may be implemented as needed.

[0078] The electronic device provided in this embodiment of the invention includes: at least one processor 501, a memory 502, a user interface 503, and at least one network interface 504. The various components in the CCHP integrated system configuration scheme optimization system for mining scenarios are coupled together through a bus system 505. It can be understood that the bus system 505 is used to realize the connection and communication between these components. In addition to a data bus, the bus system 505 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 5 The general designated all buses as Bus System 505.

[0079] The user interface 503 may include a monitor, keyboard, mouse, trackball, click wheel, buttons, touchpad, or touch screen.

[0080] It is understood that memory 502 can be volatile memory or non-volatile memory, or both. In this embodiment of the invention, memory 502 is capable of storing data to support the operation of the terminal. Examples of this data include any computer programs used to operate on the terminal, such as operating systems and applications. The operating system includes various system programs, such as framework layers, core library layers, driver layers, etc., used to implement various basic services and handle hardware-based tasks. Applications can include various applications.

[0081] In some embodiments, the CCHP integrated system configuration optimization system for mining scenarios provided in this invention can be implemented using a combination of hardware and software. For example, the CCHP integrated system configuration optimization system for mining scenarios provided in this invention can be a processor in the form of a hardware decoding processor, programmed to execute the CCHP integrated system configuration optimization method for mining scenarios provided in this invention. For instance, the hardware decoding processor can employ one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), or other electronic components.

[0082] As an example, processor 501 can be an integrated circuit chip with signal processing capabilities, such as a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc., wherein the general-purpose processor can be a microprocessor or any conventional processor, etc.

[0083] As an example of the hardware implementation of the CCHP integrated system configuration scheme optimization system for mining scenarios provided in this embodiment of the invention, the device provided in this embodiment of the invention can be directly executed by a processor 501 in the form of a hardware decoding processor. For example, it can be executed by one or more application specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), or other electronic components to implement the CCHP integrated system configuration scheme optimization method for mining scenarios provided in this embodiment of the invention.

[0084] The memory 502 in this embodiment of the invention is used to store various types of data to support the operation of the CCHP integrated system configuration scheme optimization system in mining scenarios, or to store data for execution. Figure 1 The program code for the method shown. Examples of this data include: any executable instructions for operation on the CCHP integrated system configuration scheme optimization system in a mining scenario, such as executable instructions, and the program implementing the CCHP integrated system configuration scheme optimization method for a mining scenario according to embodiments of the present invention can be included in the executable instructions.

[0085] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including functions for executing... Figure 1 The program code for the method shown. In such an embodiment, the computer program can be downloaded and installed from a network via a communication component, and / or installed from a removable medium. When the computer program is executed by the central processing unit, it performs the various functions defined in the apparatus of this application.

[0086] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart. Figure 1One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0087] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for optimizing the configuration scheme of a CCHP integrated system in a mining scenario, characterized in that, include: Based on the operating parameters of the integrated CCHP system in a mine, a multi-objective mixed integer linear programming model is constructed, which includes economic, energy consumption, and environmental objectives. The economic objective is to minimize the annualized total cost of the integrated CCHP system in the mine; the energy consumption objective is to minimize the total primary energy consumed by the operation of the integrated CCHP system in the mine; and the environmental objective is to minimize the total greenhouse gas emissions caused by the operation of the integrated CCHP system in the mine. Based on a multi-objective mixed-integer linear programming model, using The constraint method takes economic objectives as the primary objective, restricts energy consumption and environmental objectives within a set range, and transforms them into constraints to determine the optimal equipment model, number of units, and real-time output strategy, which serves as the final configuration scheme for the mine CCHP integrated system.

2. The CCHP integrated system configuration optimization method for mining scenarios as described in claim 1, characterized in that, The process of determining the optimal equipment model, number of units, and real-time output strategy is as follows: In terms of energy consumption targets and environmental targets Within the limits, the multi-objective mixed integer linear programming model is solved to obtain a set of system scheme configurations for equipment type, number of units, and real-time output strategy; Construct indicators at the economic level, such as annualized total cost, investment payback period, and investment efficiency assessment; construct indicators at the energy level, such as primary energy consumption and primary energy saving rate; and construct indicators at the environmental level, such as annual carbon emissions and carbon reduction rate; and standardize all of the above indicators. The subjective weights of each standardized indicator are calculated using the analytic hierarchy process (AHP), and the objective weights of each standardized indicator are calculated using the principal component analysis (PCA). Based on the game theory-based combination weighting method, the optimal combination weights of each standardized indicator are obtained with the goal of achieving Nash equilibrium. The optimal system configuration is determined by the weighted sum of the optimal combination weights of each standardized indicator, which is the highest score. This means the optimal equipment model, number of units, and real-time output strategy.

3. The CCHP integrated system configuration optimization method for mining scenarios as described in claim 2, characterized in that, In obtaining the optimal combination weights for various standardized indicators using a game theory-based combinatorial weighting method, subjective and objective weights are considered as two sides in a game, and an optimal set of combination coefficients is found through mathematical optimization. and This determines the final weight of each standardized indicator. = and and The overall deviation is the smallest; among them, Subjective weighting; For objective weighting.

4. The method for optimizing the CCHP integrated system configuration scheme in a mining scenario as described in claim 2, characterized in that, For benefit-oriented indicators such as primary energy saving rate and carbon emission reduction rate, a positive standardization formula is used: in, For the first The first scheme The standardized values ​​of each indicator; For the first The first scheme The original values ​​of each indicator; For the first The maximum value of each indicator across all options; For the first The minimum value of each indicator among all possible solutions.

5. The method for optimizing the CCHP integrated system configuration scheme in a mining scenario as described in claim 2, characterized in that, For cost-related indicators such as total annual cost, payback period, primary energy consumption, and annual carbon emissions, a negative standardization formula is used: in, For the first The first scheme The standardized values ​​of each indicator; For the first The first scheme The original values ​​of each indicator; For the first The maximum value of each indicator across all options; For the first The minimum value of each indicator among all possible solutions.

6. The method for optimizing the CCHP integrated system configuration scheme in a mining scenario as described in claim 1, characterized in that, use The constraint method takes economic objectives as the primary objective, restricts energy consumption and environmental objectives within a set range, and transforms these objectives into constraints. in, The objective function is the economic performance. The objective function is energy consumption. The objective function is environmental. and These are the upper and lower limits for primary energy consumption. and These are the upper and lower limits for carbon emissions; Configure the system solution, including equipment model, number of units, and real-time output strategy; A set of system solution configurations.

7. The CCHP integrated system configuration optimization method for mining scenarios as described in claim 5, characterized in that, calculate The range of values ​​and The process of determining the range of values ​​is as follows: To obtain and Minimize respectively , and These three single objectives yield their corresponding optimal solutions; The ideal point is the minimum value That is, to minimize individually The optimal value obtained at that time; The ideal point is the minimum value That is, to minimize individually The optimal value obtained at that time; To obtain and ,Will , and The three single-objective optimal solutions and their corresponding objective function values ​​are listed in a pre-defined storage table; maximum value For storage table The maximum value in this column; maximum value For storage table The maximum value in this column; Ultimately, obtain The range of values and The range of values .

8. A CCHP integrated system configuration optimization system for mining scenarios, characterized in that, The CCHP integrated system configuration optimization method based on any one of claims 1-7 includes: The model building module is used to construct a multi-objective mixed integer linear programming model based on the operating parameters of the mine CCHP integrated system, including economic, energy consumption, and environmental objectives. The economic objective is to minimize the annualized total cost of the mine CCHP integrated system; the energy consumption objective is to minimize the total primary energy consumed by the operation of the mine CCHP integrated system; and the environmental objective is to minimize the total greenhouse gas emissions caused by the operation of the mine CCHP integrated system. The scheme optimization module is used for multi-objective mixed-integer linear programming models, employing... The constraint method takes economic objectives as the primary objective, restricts energy consumption and environmental objectives within a set range, and transforms them into constraints to determine the optimal equipment model, number of units, and real-time output strategy, which serves as the final configuration scheme for the mine CCHP integrated system.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps in the CCHP integrated system configuration scheme optimization method for mining scenarios as described in any one of claims 1-7.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the CCHP integrated system configuration scheme optimization method for mining scenarios as described in any one of claims 1-7.

Images