A method, system, equipment, and storage medium for low-carbon steel industrial park grid load planning.

Abstract

This invention discloses a method, system, equipment, and storage medium for low-carbon steel industrial park grid load planning, relating to the field of industrial production process optimization technology. The method includes: constructing an analytical model to analyze the low-carbon integrated energy flow path in the steel industrial park and obtain the energy network structure; based on the energy network structure and considering constraints in the steel production process, constructing a steel production process model to obtain load-side demand information for energy equipment; based on the load-side demand information, constructing an operation model for energy equipment in the steel industrial park and analyzing the technical operation characteristics of energy; considering the characteristics of transmission lines, constructing a transmission line expansion planning method based on an improved heuristic step-by-step expansion method; and co-optimizing the technical operation characteristics of energy and the transmission line expansion planning method to obtain a planning method that coordinates transmission network expansion planning with steel production time-series operation simulation. This invention improves the accuracy of hydrogen energy consumption prediction and the coordinated optimization capability of multi-source supply and demand matching.

Description

Technical Field

[0001] This invention relates to the field of industrial production process optimization technology, specifically to a method, system, equipment, and storage medium for low-carbon steel industrial park grid load planning. Background Technology

[0002] Against the backdrop of the low-carbon energy transition, renewable energy sources, represented by wind power and solar power, continue to develop rapidly. As the proportion of wind and solar power generation increases, the strong random fluctuations in power generation output increase the demand for flexible regulation in the power system, posing new technical challenges to traditional transmission network expansion planning. Simultaneously, with the gradual development of the energy internet, demand-side resources are playing an increasingly significant role in the power system. Industrial loads, with their large response capacity and high level of automation, can flexibly participate in demand response, contributing to a more economical and greener approach to achieving power system supply and demand balance. This provides new insights for power system planning that considers flexible regulation capabilities.

[0003] Power system planning that effectively integrates multiple flexibility resources across the power generation, grid, load, and storage sides can reduce redundancy in single resource allocation and lower construction costs while meeting flexibility requirements. Currently, research considering demand-side resources to enhance power system planning flexibility is limited, or while demand response is considered, demand-side resources are simply modeled as loads that can be reduced or transferred, without considering the internal response mechanisms of the loads. This lack of practical and in-depth exploration of load-side resource flexibility is problematic. Meanwhile, steel enterprises, with their massive energy consumption and high carbon emissions, face urgent pressure for transformation and upgrading. From the perspective of the steel industry's long-term goal of "zero carbon," hydrogen metallurgy and short-process electric arc furnaces using all-scrap steel are feasible development directions. Low-carbon process transformation promotes the development of integrated energy systems (IES) within enterprises, which couple multiple energy forms such as hydrogen, electricity, and heat. This not only improves energy efficiency and reduces carbon emissions but also provides potential flexibility resources for the power system. Therefore, it is urgent to analyze steel industrial parks after process upgrades as dedicated flexibility resources and explore coordinated planning schemes between transmission lines and steel industrial parks to achieve power balance and enhanced flexibility. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by this invention is that the existing optimization methods for separating energy supply and power grid planning in steel industrial parks have problems such as not considering the coordinated interaction between hydrogen-using equipment and the power grid within the park and insufficient system flexibility, as well as how to achieve optimized configuration of transmission lines while ensuring the matching of power-hydrogen energy flow.

[0006] To address the aforementioned technical problems, this invention provides the following technical solution: a low-carbon steel industrial park grid load planning method, comprising: constructing an analysis model to analyze the low-carbon integrated energy flow path of the steel industrial park and obtain the energy network structure; based on the energy network structure, considering constraints in the steel production process, constructing a steel production process model to obtain load-side demand information for energy equipment; based on the load-side demand information for energy equipment, constructing an operation model for energy equipment in the steel industrial park and analyzing the technical operation characteristics of energy; considering the characteristics of transmission lines, constructing a transmission line expansion planning method based on an improved heuristic step-by-step expansion method; and integrating the technical operation characteristics of energy with the transmission line expansion planning method. The collaborative optimization yields a planning method that coordinates the expansion planning of the power grid with the time-series operation simulation of steel production. Analysis of energy technology operation characteristics includes constructing an operation model of energy equipment in the steel industrial park, dynamically analyzing energy supply and demand changes based on load-side demand information, and obtaining time-series characteristics of energy supply and demand and energy storage. Collaborative optimization of energy technology operation characteristics and power transmission line expansion planning methods involves constructing a grid-load coordination optimization model for the steel industrial park, considering both energy technology operation characteristics and power transmission line expansion planning methods, and combining the energy consumption time-series patterns of steel production. This model determines a grid-load coordination optimization scheduling scheme that balances energy supply and demand and the economic constraints of power grid expansion.

[0007] As a preferred embodiment of the low-carbon steel industrial park grid load planning method described in this invention, the construction of the analysis model includes: introducing energy conversion equipment and energy-consuming equipment, identifying the energy interaction relationship between hydrogen conversion equipment and energy-consuming equipment in the steel industrial park, analyzing the energy flow path in the park, and determining the network structure of low-carbon integrated energy.

[0008] As a preferred embodiment of the low-carbon steel industrial park grid load planning method described in this invention, the construction of the steel production process model includes, based on the blast furnace hydrogen injection process and the electric arc furnace short-process steelmaking process, constructing a functional relationship between energy and energy consumption, and calculating the energy demand information of equipment in the steel industrial park.

[0009] As a preferred embodiment of the low-carbon steel industrial park grid load planning method of the present invention, the blast furnace hydrogen injection process includes constraining the production rate of the hydrogen metallurgical process.

[0010] The electric arc furnace short-process steelmaking process includes calculating the electric arc furnace power and constraining the power adjustment of the electric arc furnace.

[0011] As a preferred embodiment of the low-carbon steel park grid load planning method described in this invention, the analysis of the technical operation characteristics of energy includes: constructing an operation model of the steel park energy equipment based on the load-side demand information of the energy equipment; analyzing the technical operation characteristics of the entire energy consumption process; analyzing the supply and demand changes during the energy regulation process; and generating the results of changes in energy supply, demand, and reserves in a time series.

[0012] As a preferred embodiment of the low-carbon steel industrial park grid load planning method described in this invention, the method for constructing the expansion planning method of transmission lines based on the improved heuristic stepwise expansion method includes: establishing an economic evaluation mechanism for the expansion process of transmission lines based on the energy network structure and the technical operation characteristics of energy; iteratively optimizing the transmission lines; calculating the economic indicators of the transmission lines in the set of transmission lines to be expanded in each iteration; adding a transmission line that meets the preset economic conditions to the transmission network; and stopping the iteration if the addition of a new transmission line cannot reduce costs.

[0013] As a preferred embodiment of the low-carbon steel industrial park grid-load planning method described in this invention, the method of synergistically optimizing the technical operating characteristics of energy and the expansion planning method of transmission lines includes coupling the technical operating characteristics of energy equipment with the transmission line expansion planning scheme obtained based on the improved heuristic stepwise expansion method, combining the energy consumption time sequence of steel production, constructing a grid-load coordination and synergistic optimization model for the steel industrial park, and determining a grid-load coordination and optimization scheduling scheme that takes into account both energy supply and demand balance and the economic constraints of transmission network expansion.

[0014] Another objective of this invention is to provide a low-carbon steel industrial park grid-load planning system. This system analyzes the flow paths of various energy sources within the steel industrial park across different equipment to form an energy network structure. Furthermore, based on this energy network structure, it establishes production process models and energy equipment operation models in conjunction with the steel production process, analyzing the operational characteristics of energy technologies. Then, based on the characteristics of energy and transmission lines, it constructs a transmission line expansion planning scheme using a heuristic step-by-step expansion method. Finally, it coordinates and optimizes the energy operation characteristics and the expansion scheme to form a grid-load coordination and scheduling scheme that synergizes with the sequential operation of steel production. This solves the problem of current grid-load coordination technologies lacking optimization and coordination for the entire process of low-carbon transformation in steel industrial parks.

[0015] As a preferred embodiment of the low-carbon steel industrial park grid-load planning system of the present invention, it includes: an energy flow path analysis module, a production process modeling module, an energy equipment operation modeling module, a transmission line expansion planning module, and a collaborative optimization planning module; the energy flow path analysis module is used to analyze the flow paths of various types of energy between different equipment in the steel industrial park to form an energy network structure; the production process modeling module is used to establish a process model based on the energy network structure and considering the constraints of the steel production process, and to obtain energy load-side demand information; the energy equipment operation modeling module is used to construct an energy equipment operation model for the park according to the load-side demand and analyze the technical operation characteristics of energy; the transmission line expansion planning module is used to construct a transmission line expansion planning scheme based on energy and transmission characteristics and using an improved heuristic step-by-step expansion method; the collaborative optimization planning module is used to collaboratively optimize the energy operation characteristics and the expansion scheme to form a grid-load coordination planning scheme that is coordinated with the time sequence operation of steel production.

[0016] Another object of the present invention is to provide a low-carbon steel industrial park grid load planning device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement a low-carbon steel industrial park grid load planning method.

[0017] Another object of the present invention is to provide a storage medium for grid load planning in a low-carbon steel industrial park, on which a computer program is stored, and when the computer program is executed by a processor, the steps of a grid load planning method for a low-carbon steel industrial park are implemented.

[0018] The beneficial effects of this invention are as follows: The low-carbon steel industrial park grid-load planning method provided by this invention, through sequential analysis of the hydrogen energy process, steel production process model, and hydrogen equipment operation model, gradually realizes the identification of hydrogen flow paths within the park, accurate prediction of hydrogen demand, and time-series supply and demand matching of multi-source equipment, providing a complete data foundation for grid-load coordination. Specifically, by analyzing the hydrogen energy process, unified modeling of energy flow paths among various types of hydrogen conversion equipment is achieved, effectively clarifying the structure of the park's hydrogen system and improving the systematic nature of energy flow analysis; by constructing an operation model of energy equipment, quantification of hydrogen demand based on production rhythm is achieved, establishing a coupling mechanism between process flow and energy modeling, and improving the time-series accuracy of demand data; by constructing an operation model of hydrogen equipment, dynamic output analysis of multi-source hydrogen production and storage devices is realized, providing quantitative support for supply and demand balance and flexible operation. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is an overall flowchart of a low-carbon steel industrial park grid load planning method provided in Embodiment 1 of the present invention.

[0021] Figure 2 The diagram shows the GARVER-6 system structure of a low-carbon steel industrial park grid load planning method provided in Embodiment 2 of the present invention. Detailed Implementation

[0022] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0023] Example 1, referring to Figure 1 As an embodiment of the present invention, a low-carbon steel industrial park grid load planning method is provided, comprising:

[0024] S1: Construct analysis model 100 to analyze the low-carbon integrated energy flow path of the steel industrial park and obtain the energy network structure.

[0025] Furthermore, the construction of the analysis model 100 includes introducing energy conversion equipment and energy-consuming equipment, identifying the energy interaction relationship between hydrogen conversion equipment and energy-consuming equipment in the steel industrial park, analyzing the energy flow path in the park, and determining the network structure 101 of low-carbon integrated energy.

[0026] It should be noted that hydrogen is a preferred energy source.

[0027] It should be noted that the hydrogen production equipment includes water electrolysis, natural gas, hydrogen storage tanks, industrial by-product coal gas, hydrogen storage tanks, hydrogen blending gas turbines, and electric arc furnaces. Based on the spatial layout, process function attributes, and hydrogen interface types of the hydrogen conversion equipment and energy-consuming equipment, a connection map of the hydrogen conversion equipment and energy-consuming equipment within the park is constructed. The coal feeding equipment is used as nodes in the map, and the connecting paths are used as edges. The flow direction, maximum flow capacity, physical length, and medium state of each path are identified to determine the actual flow path of hydrogen between different devices. The starting point, ending point, intermediate equipment nodes, and transportation methods involved in each path are clearly defined, forming a complete flow path of hydrogen from the supply side, storage side, to the energy-consuming side.

[0028] It should also be noted that by introducing all types of hydrogen-related equipment and constructing equipment connection maps, and combining multi-dimensional path parameters for accurate identification, the entire process of hydrogen energy supply, storage and consumption in the steel industrial park has been analyzed. This provides accurate input data for subsequent timing matching and capacity configuration, and significantly enhances the overall intelligence and scheduling optimization capabilities of hydrogen regulation within the park.

[0029] S2: Based on the energy network structure and considering the constraints in the steel production process, a steel production process model 200 is constructed to obtain the load-side demand information of energy equipment.

[0030] Furthermore, the steel production process model 200 includes constructing a functional relationship between energy and energy consumption based on the blast furnace hydrogen injection process and the electric arc furnace short-process steelmaking process, and calculating the energy demand information of equipment in the steel industrial park 201.

[0031] It should be noted that the production input constraints and equipment technology constraints in the actual steel production process include those for both the long-process steelmaking process using blast furnace hydrogen injection and the short-process steelmaking process using electric arc furnace. For the long-process steelmaking process using blast furnace hydrogen injection, the functional relationship between hydrogen energy and hydrogen consumption can be expressed as follows:

[0032] ,

[0033] in, This indicates the steel production rate of the hydrogen metallurgical process. The hydrogen consumption coefficient represents the hydrogen consumption factor in hydrogen metallurgical processes. Indicated by the iron ore coefficient, This indicates the power consumption coefficient of the hydrogen metallurgical process. This indicates the rate at which hydrogen is consumed in hydrogen metallurgical processes. This indicates the rate at which iron ore is consumed in the hydrogen metallurgical process. This indicates the power consumption of the hydrogen metallurgical process.

[0034] The functional relationship between hydrogen energy and hydrogen consumption was applied to each relevant piece of equipment in the steel industrial park. By substituting the parameters into each item according to the actual operating power or planned output of the equipment, the hydrogen consumption per unit time of each piece of equipment was obtained.

[0035] It should also be noted that by converting different process parameters in the ironmaking process into function models, and by establishing a functional relationship between hydrogen consumption and variables such as output, power consumption, and material rate, the standardized calculation of hydrogen demand for various equipment in the steel industrial park has been achieved. This provides an accurate data foundation for subsequent supply and demand matching and hydrogen energy regulation, effectively improving the credibility and operability of low-carbon energy modeling.

[0036] Furthermore, the blast furnace hydrogen injection process includes constraining the production rate of the hydrogen metallurgical process.

[0037] The electric arc furnace short-process steelmaking process includes calculating the electric arc furnace power and constraining the power adjustment of the electric arc furnace.

[0038] It should be noted that the process of hydrogen injection for iron reduction in a blast furnace is subject to equipment technical constraints; that is, the equipment must operate within permissible limits, and its output must not exceed the maximum limit or fall below the minimum limit. At any given time... Hydrogen metallurgical processes should meet the following constraints:

[0039] ,

[0040] in, Indicates any time period Steel production rate of hydrogen metallurgical process This indicates the maximum production rate of the hydrogen metallurgical process. This indicates the minimum production rate of the hydrogen metallurgical process.

[0041] Electric arc furnace (EAF) short-process steelmaking uses scrap steel as the main raw material, utilizing the high-temperature energy of the electric arc to melt scrap steel and other metal waste into molten steel. It is characterized by high efficiency, low consumption, and environmental friendliness. The relationship between the production rate of EAF short-process steelmaking and the material consumption rate and electricity consumption rate can be expressed as:

[0042] ,

[0043] in, This indicates the steel production rate of the electric arc furnace short-process steelmaking. This represents the scrap steel consumption coefficient in electric arc furnace short-process steelmaking. This represents the power consumption coefficient of electric arc furnace short-process steelmaking. This indicates the rate of scrap steel consumption in the electric arc furnace short-process steelmaking. This indicates the power consumption of short-process steelmaking in electric arc furnaces.

[0044] Electric arc furnace short-process steelmaking offers greater flexibility in electricity usage; the furnace power can be adjusted flexibly, and the time period can be customized. The power of the electric arc furnace is expressed as:

[0045] ,

[0046] in, Indicates the time of the electric arc furnace The actual total power, Indicates that the electric arc furnace is in Oven power during the time period, Indicates the smelting power of the electric arc furnace. Indicates that the electric furnace is Power adjustment amount during the time period A 0-1 variable representing the production status of an electric arc furnace; a value of 1 indicates that the electric arc furnace is in operation. The time period is in the material feeding and discharging state; a value of 0 indicates that the electric arc furnace is in the smelting state.

[0047] The power adjustment of an electric arc furnace is limited by upper and lower limits, as shown below:

[0048] ,

[0049] in, This indicates the lower limit of the electric arc furnace power adjustment. This indicates the upper limit of the power adjustment for the electric arc furnace.

[0050] It should also be noted that the hydrogen injection process in the blast furnace is subject to physical constraints of equipment limits. By modeling the upper and lower limits of production capacity, ineffective or overloaded hydrogen injection behaviors can be effectively avoided, and the safe allocation of hydrogen resources in the process flow can be achieved. This ensures the stability of the blast furnace smelting capacity and the accuracy of hydrogen use. By logically segmenting and modeling the response of power regulation under different conditions and constraining the upper and lower limits of adjustment, the situation of abnormal energy consumption or sudden increase in hydrogen use caused by excessive fluctuations in power regulation is avoided. This improves the robustness of scheduling and enhances the adaptability of the energy-consuming side of the industrial park to the uncertainty of hydrogen supply timing.

[0051] S3: Based on the load-side demand information of energy equipment, construct the operation model 300 of energy equipment in the steel industrial park and analyze the technical operation characteristics of energy.

[0052] Furthermore, the analysis of the technical operation characteristics of energy includes constructing an operation model 300 for energy equipment in the steel industrial park based on the load-side demand information of energy equipment, analyzing the technical operation characteristics of the entire energy consumption process, analyzing the supply and demand changes in the energy regulation process, and generating the results of changes in energy supply, demand and reserves in a time series.

[0053] It should be noted that modeling the operational characteristics of the entire hydrogen consumption process includes constructing an operational model for the hydrogen supply side and an operational model for the hydrogen consumption side.

[0054] The construction of the hydrogen supply-side operation model includes the construction of a water electrolysis hydrogen production model, in which hydrogen is introduced as an auxiliary reducing agent into the blast furnace ironmaking process. The hydrogen produced by the water electrolysis process is green hydrogen, and the hydrogen output of the electrolytic hydrogen production equipment is expressed as:

[0055] ,

[0056] in, Indicates that the electrolytic cell is in The amount of hydrogen output during the time period, Indicates the electrical power of the electrolytic cell. This indicates the electrolysis efficiency of the electrolytic cell. This represents the electro-hydrogen conversion coefficient.

[0057] The power constraint condition of the electrolytic cell is expressed as follows:

[0058] ,

[0059] in, This indicates the lower limit of the installed capacity of hydrogen production equipment. This indicates the upper limit of the installed capacity of the electro-hydrogen production equipment.

[0060] Constructing a natural gas-to-hydrogen model includes the production of blue hydrogen from natural gas, which often employs a combination of natural gas steam reforming and PSA hydrogen production, represented as:

[0061] ,

[0062] in, express Natural gas-to-blue hydrogen production during the period Indicates the efficiency of natural gas to hydrogen conversion. express The amount of natural gas consumed in hydrogen production during a given period.

[0063] The production constraints for blue hydrogen from natural gas are expressed as follows:

[0064] ,

[0065] in, This indicates the lower limit of blue hydrogen production from natural gas. This indicates the upper limit of blue hydrogen production from natural gas.

[0066] Constructing a hydrogen production model from by-product coal gas involves considering that hydrogen production from by-product coal gas relies on by-products such as coke oven gas generated during steel production. The commonly used physical separation methods for hydrogen production from by-product coal gas are represented as follows:

[0067] ,

[0068] in, express The production of blue hydrogen from by-product coal gas during a given period. This indicates the efficiency of converting coal gas to hydrogen. express The gas consumption for hydrogen production from by-product coal gas during a given period.

[0069] The constraint condition for producing blue hydrogen from by-product coal gas is expressed as follows:

[0070] ,

[0071] in, This indicates the lower limit of the blue hydrogen production yield from by-product coal gas. This indicates the upper limit of the production of blue hydrogen from by-product coal gas.

[0072] Both green hydrogen and blue hydrogen are stored uniformly in standardized high-pressure gaseous hydrogen storage tanks, the model of which is represented as follows:

[0073] ,

[0074] in, express The volume of hydrogen stored in the time-limited hydrogen storage tank. express The volume of hydrogen stored in the time-limited hydrogen storage tank. express The volume of hydrogen gas input to the hydrogen storage tank during the time period. express The volume of hydrogen gas output from the hydrogen storage tank during a given period. This indicates the duration of each time period. This indicates the maximum capacity of the hydrogen storage tank.

[0075] Introducing hydrogen blending technology into conventional CHP units, which involves the combustion of a mixture of hydrogen and natural gas, can be represented as follows:

[0076] ,

[0077] in, express The power generation capacity of hydrogen-blended gas turbines during specific time periods. express Energy conversion efficiency of time-phase hydrogen-blended gas turbines This indicates the energy conversion efficiency of the gas turbine without hydrogen addition. express The volume of hydrogen consumed by the hydrogen-blended gas turbine during a given period. express The volume of natural gas consumed by the hydrogen-blended gas turbine during a given period. express The volumetric calorific value of the mixture of hydrogen and natural gas during that period is high. Indicates hydrogen production time. Indicates the hydrogen doping ratio. This indicates the volumetric calorific value of hydrogen. This indicates the volumetric calorific value of natural gas.

[0078] The power generation constraints of a hydrogen-blended gas turbine are expressed as follows:

[0079] ,

[0080] in, This indicates the lower limit of the power generation capacity of a hydrogen-blended gas turbine. This indicates the upper limit of the power generation capacity of a hydrogen-blended gas turbine.

[0081] The hydrogen supply from all sources, including water electrolysis, natural gas, by-product coal gas, consumption, and inventory changes, is summarized over time. The hydrogen supply for each period is determined based on the different sources. The hydrogen demand for each period is determined based on the hydrogen-blended load consumption. The hydrogen storage changes for each period are determined by combining the remaining adjustable resources in the storage tanks.

[0082] It should also be noted that by constructing a multi-source-multi-terminal integrated dynamic modeling framework for hydrogen supply and demand, the time-series expression of hydrogen production through water electrolysis, natural gas reforming, hydrogen production from by-product coal gas, hydrogen-blended gas turbine consumption, and high-pressure hydrogen storage processes has been realized under a unified mathematical system. This solves the problems of disconnect between the supply and consumption sides, poor time-domain consistency, and lack of inventory constraints in traditional models. Furthermore, through refined modeling that links the energy efficiency of hydrogen-blended gas turbines with the hydrogen blending ratio, the impact of hydrogen blending calorific value on unit power generation efficiency and hydrogen consumption has been clarified, providing a feasible strategy for optimized scheduling of blending ratios.

[0083] S4: Considering the characteristics Q of the transmission line, construct a transmission line expansion planning method based on an improved heuristic stepwise expansion method 400.

[0084] Furthermore, the proposed method 400 for expanding transmission lines based on an improved heuristic stepwise expansion approach includes: establishing an economic evaluation mechanism for the expansion process of transmission lines based on the energy network structure and the technical operation characteristics of energy; iteratively optimizing the transmission lines; calculating the economic indicators of the transmission lines in the set of transmission lines to be expanded in each iteration; adding a transmission line that meets the preset economic conditions to the transmission network; and stopping the iteration if the addition of a new transmission line cannot reduce costs.

[0085] It should be noted that the transmission line expansion plan is based on an improved heuristic stepwise expansion method. This means that in each iteration, a line with optimal performance is added to the transmission network until adding any new line fails to reduce the total system cost, at which point the iteration terminates. The annualized cost of the transmission line investment is expressed as:

[0086] ,

[0087] in, Indicates transmission line Construction costs and other annual values, Indicates the annual interest rate. This indicates the economic service life of the transmission line. Indicates transmission line One-time construction cost, This indicates a set of alternative routes to be expanded.

[0088] To establish an economically sound selection mechanism for expanding transmission lines, the ratio of the cost reduction (excluding the investment cost) after adding a transmission line to the construction cost of the transmission line is defined as the economic index of the transmission line, expressed as:

[0089] ,

[0090] in, Indicates transmission line Economic indicators Indicates the addition of a power transmission line The initial cost, Indicates the addition of a power transmission line The subsequent costs.

[0091] In each iteration, all transmission lines in the candidate transmission line set are calculated. Based on the economic indicators, the line with the highest economic indicator is selected to join the transmission network. This process is iterated until the termination condition is met, as expressed as:

[0092] ,

[0093] At this point, constructing new transmission lines within the power grid cannot reduce the total cost, and the result of the previous iteration is the final planning scheme for the power grid lines.

[0094] It should also be noted that by combining the technical operating characteristics of hydrogen with the investment economics of power transmission line expansion, and measuring the input-output ratio of each candidate power transmission line through economic indicators, the expansion plan achieves a balance between economic input and operational benefits, thus improving the practicality and economy of the plan. By using a step-by-step iterative approach, the power transmission line with the best economic indicators is selected in each round, ensuring that each step has clear economic benefits. When all candidate lines no longer have the ability to reduce costs, the process automatically terminates, forming a final reasonable power transmission network structure, thereby improving the convergence and automation of the system planning.

[0095] S5: By co-optimizing the technical operation characteristics of energy and the expansion planning method of transmission lines, a planning method 500 is obtained that coordinates the expansion planning of the power grid and the time-series operation simulation of steel production.

[0096] Furthermore, the collaborative optimization of energy technology operation characteristics and transmission line expansion planning methods includes coupling the technology operation characteristics of energy equipment with the transmission line expansion planning scheme obtained based on the improved heuristic stepwise expansion method, and combining the energy consumption time sequence pattern of steel production to construct a grid-load coordination optimization model for steel industrial parks, and determine a grid-load coordination optimization scheduling scheme that takes into account both energy supply and demand balance and the economic constraints of transmission network expansion.

[0097] It should be noted that minimizing the low-carbon transformation cost of the industrial park by introducing blast furnace hydrogen injection and electric arc furnace steelmaking processes means maximizing the park's net benefits. The park's net benefits are expressed as follows:

[0098] ,

[0099] in, This indicates the net revenue of the steel industrial park. The steel industrial park is the first Annual income This indicates the operating cycle of the steel industrial park. This indicates the initial investment cost for energy and low-carbon production upgrades in steel industrial parks. It represents the residual economic value of energy and production in steel industrial parks.

[0100] Steel Industrial Park Annual income It mainly consists of revenue from hydrogen energy substitution, revenue from electricity substitution, and revenue from hydrogen sales minus operation and maintenance costs:

[0101] ,

[0102] in, Indicates the first Annual hydrogen energy substitution benefits Indicates the first The annual reduction in purchased electricity costs, i.e., the revenue from electricity substitution, Indicates the first The annual cost of selling hydrogen. Indicates the first Annual maintenance costs This indicates the depreciation rate.

[0103] No. Annual hydrogen substitution benefits This includes benefits for businesses such as carbon reduction, reduced coal purchase costs, and reduced natural gas purchase costs.

[0104] ,

[0105] in, This indicates the amount of carbon reduction per unit of electricity. This indicates the amount of carbon reduction per unit in hydrogen metallurgy. This indicates the carbon reduction per unit of hydrogen energy replaced by a hydrogen-blended gas turbine. This indicates a reduction in externally purchased electricity. This indicates the annual amount of hydrogen used in hydrogen metallurgy. This indicates the annual amount of hydrogen used as fuel for hydrogen-blended gas turbines. express Carbon emissions from hydrogen production using gas during specific time periods. This indicates the annual equivalent utilization hours of the gas-to-hydrogen equipment. Indicates the first Annual carbon price This indicates the amount of hydrogen required to produce one unit mass of molten iron. This indicates the amount of coal required to produce one unit of molten iron. Indicates the first The average annual coal price Indicates the first The average annual price of natural gas.

[0106] No. The annual reduction in purchased electricity is represented by the electricity consumption in the industrial park replaced by self-generated power equipment such as hydrogen-blended gas turbines, minus the electricity consumption of the hydrogen production equipment.

[0107] ,

[0108] in, Indicates the first The annual reduction in purchased electricity Indicates the rated capacity of the hydrogen-blended gas turbine. Indicates the rated capacity of the electro-hydrogen production equipment. This indicates the annual equivalent utilization hours of a hydrogen-blended gas turbine. This indicates the annual equivalent utilization hours of the electro-hydrogen production equipment.

[0109] No. Annual reduction in purchased electricity costs The benefits of electricity substitution are expressed as:

[0110] ,

[0111] in, Indicates the first Annual reduction in purchased electricity costs This indicates the unit's electricity costs.

[0112] No. Annual cost of selling hydrogen The factors that depend on include domestic hydrogen production, the proportion of hydrogen metallurgical substitution, the proportion of hydrogen-blended gas turbine substitution, and the price of hydrogen, are expressed as follows:

[0113] ,

[0114] ,

[0115] in, This indicates the amount of hydrogen produced by the steel industrial park itself. This indicates the price at which hydrogen is sold or purchased. This is especially relevant when hydrogen consumption is high in hydrogen metallurgy and hydrogen-blended gas turbines. The calculation result is negative, indicating that the hydrogen supply in the park is insufficient and hydrogen needs to be purchased from outside.

[0116] No. Annual maintenance costs Relevant to the actual situation, it is expressed as follows:

[0117] ,

[0118] in, Indicates the first Annual maintenance costs This represents the ratio of operation and maintenance costs.

[0119] Initial investment for low-carbon transformation of the park's energy and production systems The term "equipment used for purchasing electric arc furnaces, water electrolysis, natural gas hydrogen production, by-product coal gas hydrogen production, hydrogen storage tanks, and hydrogen blending gas turbines" is represented as follows:

[0120] ,

[0121] in, Indicates the device type. The components, in order, are an electric arc furnace, water electrolysis, hydrogen production from natural gas, hydrogen production from by-product coal gas, a hydrogen storage tank, and a hydrogen-blending gas turbine. Indicates device unit price, Indicates device Configuration capacity.

[0122] Equipment such as water electrolysis units, hydrogen-blended gas turbines, hydrogen storage tanks, and electric arc furnaces in the park's energy and production systems can be recycled and reused at the end of their service life according to the corresponding depreciation rate. The remaining economic value is:

[0123] ,

[0124] in, This indicates the residual economic value of equipment in the park's energy and production systems. This indicates the economic value of the park's energy and production systems. This indicates the depreciation rate.

[0125] It should also be noted that by accurately deriving the load-side characteristics through the time constraints and energy demands of the processes, operating models of equipment such as water electrolysis, hydrogen gas turbines, and hydrogen storage tanks are constructed. Starting from the annual equivalent utilization hours, their supply and demand capacity is scientifically assessed. In response to the problem of unstable hydrogen sources, a hydrogen supply and demand balance mechanism is constructed, which automatically introduces external purchases to supplement when self-production is insufficient. By linking energy equipment operation data with power transmission planning, a multi-objective optimization scheme that takes into account safety, flexibility, and economy is formed.

[0126] Example 2, refer to Figure 2 As an embodiment of the present invention, a low-carbon steel industrial park grid load planning method is provided. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiment.

[0127] The improved GARVER-6 node system is used as a case study for analysis. The system structure diagram is as follows: Figure 2 As shown, node 1 is the thermal power node, representing the input port of traditional energy; node 2 is the intermediate aggregation node, representing the core load coupling point of the park's power system; photovoltaic and wind power are connected to nodes 3 and 6 respectively; the steel industrial park is powered through node 4; and node 5 is the backup aggregation node, representing the load support node connected to both thermal power and photovoltaic power. Assuming a unit construction cost of 1 million yuan / km and an economic service life of 20 years, and considering that equipment such as water electrolysis for hydrogen production, hydrogen-blended gas turbines, and hydrogen storage tanks generally have a service life of 20 years, this embodiment uses a 20-year planning period for the planning and configuration of the transmission lines and the steel industrial park.

[0128] Three scenarios are set up: Scenario 1 is the independent planning of the power transmission network without considering the flexible response of demand-side resources; Scenario 2 is the grid-load coordination planning that considers the flexible response of the steel industrial park, but does not consider the low-carbon transformation of the steel industrial park under the "dual carbon" target; Scenario 3 adds the low-carbon transformation of the park's energy and production systems on the basis of Scenario 2, which is the model proposed in this invention.

[0129] The planning results for each scenario are shown in Table 1. In Table 1, (1-4)*1 represents the creation of a new line from node 1 to node 4, and so on for the others.

[0130] Table 1 Route planning results for each scenario

[0131]

[0132] The planning costs for each scenario are shown in Table 2.

[0133] Table 2 Planning cost results for each scenario

[0134]

[0135] By comparing the planning results of Scenario 1 and Scenario 2, the significance of considering demand-side resources in the planning process can be verified. By considering the participation of demand-side resources in demand response, the curtailment of wind and solar power can be reduced, while simultaneously lowering the cost of line expansion.

[0136] By comparing the planning results of scenarios 2 and 3, the significance of considering the low-carbon transformation of the park in the planning of this embodiment can be verified. Although the low-carbon transformation of the park increases the initial investment and construction costs, it will greatly improve the park's ability to respond to demand, further reduce the amount of power wasted by the system, and reduce the need for line expansion.

[0137] Example 3, an embodiment of the present invention, provides a low-carbon steel industrial park grid load planning system, including an energy flow path analysis module, a production process modeling module, an energy equipment operation modeling module, a transmission line expansion planning module, and a collaborative optimization planning module.

[0138] The energy flow path analysis module is used to analyze the flow paths of various types of energy between different equipment in the steel industrial park, forming an energy network structure.

[0139] The production process modeling module is used to establish process models based on the energy network structure and considering the constraints of the steel production process, and to obtain energy load demand information.

[0140] The energy equipment operation modeling module is used to construct an operation model of the park's energy equipment based on load-side demand and analyze the technical operation characteristics of energy.

[0141] The transmission line expansion planning module is used to construct transmission line expansion planning schemes based on energy and transmission characteristics and using an improved heuristic stepwise expansion method.

[0142] The collaborative optimization planning module is used to collaboratively optimize energy operation characteristics and expansion plans to form a grid-load coordination planning scheme that is coordinated with the time sequence operation of steel production.

[0143] This embodiment also provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements a personnel positioning safety management visualization analysis system as proposed in the above embodiment.

[0144] This embodiment also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements a personnel positioning safety management visualization analysis system as proposed in the above embodiment.

[0145] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0146] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0147] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0148] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0149] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for low-carbon steel iron yard network load planning, characterized in that, The method comprises the following steps: constructing an analysis model (100) to analyze a low-carbon comprehensive energy flow path in a steel industrial park to obtain an energy network structure (101); based on the energy network structure (101), considering the constraints in the steel production process, constructing a steel production process model (200) to obtain load side demand information of energy equipment; based on the load side demand information of energy equipment, constructing an operation model (300) of energy equipment in the steel park to analyze the technical operation characteristics of energy; considering the characteristics (Q) of the power transmission line, constructing a power transmission line expansion planning method (400) based on an improved heuristic step-by-step expansion method; coordinately optimizing the technical operation characteristics of energy and the power transmission line expansion planning method to obtain a power grid expansion planning and steel production timing operation simulation coordinated planning method (500); analyzing the technical operation characteristics of energy includes constructing an operation model (300) of energy equipment in the steel park, combining with the load side demand information, dynamically analyzing the energy supply and demand changes to obtain the time series characteristics results of energy supply and demand and energy storage; coordinately optimizing the technical operation characteristics of energy and the power transmission line expansion planning method includes, based on the technical operation characteristics of energy and the power transmission line expansion planning method, combining with the energy timing law of steel production, constructing a network-load coordination optimization model of the steel industrial park to determine a network-load coordination optimization scheduling scheme under the constraints of energy supply and demand balance and power grid expansion economy; constructing a steel production process model (200) includes, based on the hydrogen injection process of blast furnace and the short process steelmaking process of electric arc furnace, constructing a functional relationship between energy and energy consumption to calculate the energy demand information (201) of equipment in the steel industrial park; analyzing the technical operation characteristics of energy includes, based on the load side demand information of energy equipment, constructing an operation model (300) of energy equipment in the steel park, analyzing the technical operation characteristics of the whole process of energy consumption, and analyzing the supply and demand changes in the energy regulation process to form the energy supply, demand and storage change results in time series; coordinately optimizing the technical operation characteristics of energy and the power transmission line expansion planning method includes coupling the technical operation characteristics of energy equipment with the power transmission line expansion planning scheme obtained based on the improved heuristic step-by-step expansion method, combining with the energy timing law of steel production, constructing a network-load coordination optimization model of the steel industrial park to determine a network-load coordination optimization scheduling scheme under the constraints of energy supply and demand balance and power grid expansion economy.

2. The low carbon steel iron yard network load planning method of claim 1, wherein: The constructing an analysis model (100) includes introducing energy conversion equipment and energy-using equipment, identifying the energy interaction relationship between hydrogen conversion equipment and energy-using equipment in the steel industrial park, analyzing the flow path of energy in the park, and determining the network structure of low-carbon comprehensive energy.

3. The low carbon steel iron yard network load planning method of claim 2, wherein: The hydrogen injection process of blast furnace includes constraining the production rate of hydrogen metallurgy process; the short process steelmaking process of electric arc furnace includes calculating the power of electric arc furnace and constraining the power adjustment amount of electric arc furnace.

4. The low carbon steel iron yard network load planning method of claim 3, wherein: The construction of the power transmission line expansion planning method (400) based on the improved heuristic step-by-step expansion method includes establishing an economic evaluation mechanism in the power transmission line expansion process based on the energy network structure (101) and the technical operation characteristics of energy, iteratively optimizing the power transmission line, calculating the economic indicators of the power transmission line in the set of power transmission lines to be expanded in each iteration, adding a power transmission line that meets the preset economic conditions to the power transmission network, and stopping the iteration if the newly added power transmission line cannot reduce the cost.

5. A low-carbon steel and iron park network load planning system, adopting the low-carbon steel and iron park network load planning method according to any one of claims 1-4, characterized in that: The energy flow path analysis module, the production process modeling module, the energy equipment operation modeling module, the power transmission line expansion planning module, and the collaborative optimization planning module are included. The energy flow path analysis module is used to analyze the flow paths of various types of energy between different devices in the steel industrial park, forming an energy network structure (101). The production process modeling module is used to establish a process model based on the energy network structure and consider the constraints of the steel production process to obtain energy load side demand information. The energy equipment operation modeling module is used to construct a park energy equipment operation model according to the load side demand and analyze the technical operation characteristics of energy. The power transmission line expansion planning module is used to construct a power transmission line expansion planning scheme based on energy and power transmission characteristics using an improved heuristic step-by-step expansion method. The collaborative optimization planning module is used to collaboratively optimize the energy operation characteristics and the expansion scheme to form a network-load coordination planning scheme that is coordinated with the timing operation of steel production. 6.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-5 when the computer program is executed by the processor. The processor executes the computer program to implement the steps of the low-carbon steel and iron park network-load planning method of any one of claims 1-4.

7. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the low-carbon steel and iron park network-load planning method of any one of claims 1-4.

Images