Method and system for hybrid optimization of operation of light-wind-storage-hydrogen energy system in mining area

Abstract

The invention relates to the technical field of comprehensive energy systems, and provides a hybrid optimization mining area light-wind-storage-hydrogen energy system operation method and system. The method comprises the following steps: constructing a multi-target operation optimization model with the minimum operation cost, the minimum carbon emission and the maximum renewable energy self-absorption rate based on the operation data of a light-wind-storage-hydrogen energy system in a mining area; based on the multi-target operation optimization model and a preset mining area operation rule knowledge base, determining a search space of decision variables corresponding to the output and start-stop time sequence of each device in the mining area light-wind-storage-hydrogen energy system; adopting a hybrid multi-objective optimization algorithm fusing dynamic weight adjustment and rule guidance to obtain a candidate scheme library of the output and start-stop time sequence of each device; and the optimal scheme of the output and start-stop time sequence of each device is screened out by weighting the comprehensive satisfaction and interpretability score. According to the method, accurate collaborative optimization of multiple targets such as economical efficiency, low-carbon property and reliability can be realized.

Description

Technical Field

[0001] This invention relates to the field of integrated energy system technology, and in particular to a hybrid optimized operation method and system for a solar-wind-storage-hydrogen energy system in a mining area. 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] The load in mining areas exhibits significant time-varying and pulsating characteristics: on the power side, there are impact loads caused by the start-up and shutdown of hoists, while loads such as ventilation and drainage show long-term stability but periodic fluctuations; on the heating side, in scenarios such as winter heating and daily bathing, there are obvious seasonal and intraday peak-valley differences. At the same time, some mining areas are still facing the problem of wind and solar curtailment during certain periods due to grid access capacity, transmission and distribution constraints, and time-of-use pricing mechanisms. This means that energy security, economic operation, and carbon emission reduction targets need to be synergistically optimized under more complex boundary conditions.

[0004] Several key technological bottlenecks remain in the coordinated operation of existing integrated energy systems. These systems also face systemic shortcomings in multi-objective coordinated regulation: at the system modeling level, traditional methods employ fixed objective weight strategies, which struggle to match the optimization needs of different time periods in mining areas. They also fail to adequately characterize the dynamic characteristics of key equipment and the coupling constraints of multiple energy flows, and lack effective multi-timescale coordination mechanisms. At the algorithm implementation level, existing optimization methods have a low degree of integration with the operational patterns of mining areas, exhibit poor efficiency in population initialization and constraint processing, and struggle to support high-quality decision-making in complex engineering scenarios, thus limiting their practical application value. Summary of the Invention

[0005] To address the aforementioned technical issues, this invention provides a hybrid optimized operation method and system for a solar-wind-storage-hydrogen energy system in mining areas. This system can achieve precise synergistic optimization of multiple objectives such as economy, low carbon emissions, and reliability, providing a novel technical path for the efficient, low-carbon, and reliable operation of energy systems in mining areas.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: The first aspect of the present invention provides a method for operating a hybrid optimized solar-wind-storage-hydrogen energy system in a mining area.

[0007] In one or more embodiments, a method for operating a hybrid optimized solar-wind-storage-hydrogen energy system in a mining area is provided, including: Based on the operational data of the solar-wind-storage-hydrogen energy system in the mining area, a multi-objective operation optimization model is constructed with the goals of minimizing operating costs, minimizing carbon emissions, and maximizing the self-consumption rate of renewable energy. Based on the multi-objective operation optimization model and the pre-set knowledge base of mining area operation rules, the search space of decision variables corresponding to the output and start-up / shutdown sequence of each device in the solar-wind-storage-hydrogen energy system of the mining area is determined. A hybrid multi-objective optimization algorithm that integrates dynamic weight adjustment and rule guidance is adopted. Within the search space of decision variables, the target weights are dynamically allocated by identifying the operating conditions of the mining area. At the same time, based on the mine operation rule library, the population initialization and individual repair are guided to generate the Pareto optimal solution set and obtain the candidate scheme library of output and start-up / shutdown timing of each device. Based on the pre-constructed membership functions of each objective, the membership degree of each candidate scheme on each objective is calculated, and then the comprehensive satisfaction of each candidate scheme is calculated by linear weighted summation. The interpretability score of each candidate scheme's compliance with the mining area operation rules is calculated. By weighting the comprehensive satisfaction and interpretability scores, the optimal scheme for the output and start-up / shutdown sequence of each device is selected.

[0008] As one implementation method, a target weight vector matching each mining area operating condition is pre-configured in the mining area operation rule knowledge base.

[0009] As one implementation method, during the iterative optimization process within the search space of decision variables, the operating conditions of the mining area are identified in real time based on the predicted load fluctuation rate and the proportion of renewable energy output in the current period, and the decision variable weight vector corresponding to the operating conditions is dynamically switched.

[0010] As one implementation method, in the initial stage of the hybrid multi-objective optimization algorithm that integrates dynamic weight adjustment and rule guidance, a partial initial solution is generated using the knowledge base of mining area operation rules, which together with the random solution constitutes the initial population. In the evolutionary iteration, if the new solution individuals generated by crossover and mutation violate the strong constraints in the knowledge base of mining area operation rules, a repair operation is triggered and they are adjusted to be feasible solutions.

[0011] As one implementation method, the expression for calculating the interpretability score of each candidate scheme's compliance with the mining area's operating rules is as follows:

[0012] in, This is the score for interpretability; This represents the total number of key rules in the mining area's operational rule base. For the first Rules; This is an indicator function; it is 1 if the rules are met, and 0 otherwise. These are the solutions in the Pareto optimal solution set, i.e., the candidate schemes for the output and start-stop timing of each device.

[0013] As one implementation method, the weighted comprehensive satisfaction and interpretability scores are used as the decision evaluation values; the solution with the highest decision evaluation value is selected as the optimal scheme for the output and start-up / shutdown sequence of each device. :

[0014] in, This is the decision evaluation value; The Pareto optimal solution set; These are the solutions in the Pareto optimal solution set, i.e., the candidate schemes for the output and start-stop timing of each device.

[0015] As one implementation method, the constraints in the multi-objective operational optimization model include: Strengthened constraints include mutual exclusion of battery charging and discharging, state-of-charge management to adapt to impact loads, and cyclic energy conservation to meet safety redundancy; and Key equipment constraints, including minimum start-up and shutdown times to meet the requirements of ramp rate and mine safety production; and The power grid interaction capacity is matched with the capacity of the mine substation.

[0016] A second aspect of the present invention provides a hybrid optimized operating device for a solar-wind-storage-hydrogen energy system in a mining area.

[0017] In one or more embodiments, a hybrid optimized solar-wind-storage-hydrogen energy system operating device for mining areas includes: The optimization model building module is used to construct a multi-objective operation optimization model based on the operation data of the solar-wind-storage-hydrogen energy system in the mining area, with the goals of minimizing operating costs, minimizing carbon emissions, and maximizing the self-consumption rate of renewable energy. The search space determination module is used to determine the search space of the decision variables corresponding to the output and start-up / shutdown sequence of each device in the solar-wind-storage-hydrogen energy system of the mining area, based on the multi-objective operation optimization model and the preset knowledge base of mining area operation rules. The candidate solution library generation module is used to adopt a hybrid multi-objective optimization algorithm that integrates dynamic weight adjustment and rule guidance. Within the search space of decision variables, it dynamically allocates target weights by identifying the operating conditions of the mining area. At the same time, it guides population initialization and individual repair based on the mine operation rule library to generate the Pareto optimal solution set and obtain the candidate solution library for the output and start-up / shutdown sequence of each device. The optimal solution selection module is used to calculate the membership degree of each candidate solution on each target based on the pre-constructed membership function of each target, and then calculate the comprehensive satisfaction of each candidate solution by linear weighted summation; calculate the interpretability score of each candidate solution's compliance with the mining area operation rules, and select the optimal solution for the output and start-up / shutdown sequence of each equipment by weighting the comprehensive satisfaction and interpretability score.

[0018] A third aspect of the present invention provides a computer-readable storage medium.

[0019] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the above-described method for operating a hybrid optimized solar-wind-storage-hydrogen energy system in a mining area.

[0020] A fourth aspect of the present invention provides an electronic device.

[0021] 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 above-described method for operating a hybrid optimized solar-wind-storage-hydrogen energy system in a mining area.

[0022] Compared with the prior art, the beneficial effects of the present invention are: This invention constructs a multi-objective operation optimization model that aims to minimize operating costs, carbon emissions, and the self-consumption rate of renewable energy, and utilizes a hybrid intelligent optimization algorithm that integrates dynamic weight adjustment and rule-guided optimization. The system dynamically assigns target weights to the operating conditions of the mining area. Simultaneously, it guides population initialization and individual repair based on the mine operation rule library, resulting in a candidate solution library for the output and start-up / shutdown sequence of each piece of equipment. By dynamically adapting to different time periods and optimizing target weights, and embedding mine operation rule knowledge to improve search efficiency and solution feasibility, the system determines the optimal solution for the output and start-up / shutdown sequence of each piece of equipment through weighted comprehensive satisfaction and interpretability scores. This achieves precise and coordinated optimization of multiple objectives such as economy, low carbon emissions, and reliability, providing a new technical path for the efficient, low-carbon, and reliable operation of the mining area's energy system. Attached Figure Description

[0023] 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.

[0024] Figure 1 This is a flowchart of the operation method of the hybrid optimized solar-wind-storage-hydrogen energy system in a mining area according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of a solar-wind-storage-hydrogen energy system in a mining area according to an embodiment of the present invention; Figure 3 This is a flowchart illustrating the generation of the Pareto optimal solution set using a hybrid multi-objective optimization algorithm that integrates dynamic weight adjustment and rule guidance, as described in an embodiment of the present invention. Figure 4 This is a schematic diagram of the operating device structure of the hybrid optimized mining area solar-wind-storage-hydrogen energy system 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

[0025] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0026] 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.

[0027] 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.

[0028] Figure 1 A schematic diagram of the operation method of the hybrid optimized solar-wind-storage-hydrogen energy system in the mining area according to an embodiment of the present invention is provided. Figure 2 The structure of a mining area solar-wind-storage-hydrogen energy system according to an embodiment of the present invention is presented. This system comprises a comprehensive energy system integrating photovoltaic power generation, wind power generation, batteries, an electrolyzer, a hydrogen storage tank, a fuel cell, and a hydrogen boiler. Through the synergistic effect of multiple energy flows (electricity, hydrogen, and heat) and the coordination of energy storage across multiple time scales, this system achieves an organic unity between short-term power balance and long-term energy transfer, significantly improving the system's operational flexibility and economy.

[0029] The mining area's solar-wind-storage-hydrogen energy system uses photovoltaic and wind power generation units as the main renewable energy sources; batteries provide short-term power support; electrolyzers, hydrogen storage tanks, fuel cells, and hydrogen boilers constitute a hydrogen energy cycle subsystem, achieving long-term energy storage and efficient conversion; the power grid serves as a backup power source; and electrical and thermal loads act as energy consumption terminals. All units interact with each other via a common AC bus, forming a complete "source-grid-load-storage" collaborative operation architecture.

[0030] according to Figure 1 The hybrid optimized operation method of the solar-wind-storage-hydrogen energy system in the mining area in this embodiment may include the following steps S101 to S104.

[0031] The specific implementation process of steps S101 to S104 is as follows: Step S101: Based on the operation data of the solar-wind-storage-hydrogen energy system in the mining area, construct a multi-objective operation optimization model with the goals of minimizing operating costs, minimizing carbon emissions, and maximizing the self-consumption rate of renewable energy.

[0032] The operational data of the solar-wind-storage-hydrogen energy system in this mining area includes, but is not limited to, typical daily wind speed, irradiance, ambient temperature, electrical and thermal load, time-of-use electricity price, and equipment parameters. Time-series alignment and missing data imputation are performed in 24-hour and 30-minute increments to construct a dataset that can be directly used for optimization calculations.

[0033] A unified mechanistic model is established, encompassing photovoltaic (PV) power generation, wind power generation (WT), battery-assisted energy storage (BESS), electrolyzer (EL), hydrogen storage tank (HT), fuel cell (FC), hydrogen boiler (HB) (with optional thermal storage), and the power grid and electrical / thermal loads. This model characterizes the input-output relationships and coupling of the three energy links: electricity, hydrogen, and heat. In mining applications, batteries are used not only for short-term power balancing and peak shaving but also for providing instantaneous power buffering against impact loads such as hoists. The hydrogen production and storage system, composed of electrolyzers and hydrogen storage tanks, prioritizes capacity planning and operational strategies to address potential long-term grid constraints or failures in mines, ensuring a continuous energy supply. Fuel cells and hydrogen boilers serve as core backup energy sources to guarantee the electrical and thermal loads required for continuous mine production.

[0034] Photovoltaic and wind power outputs are represented using linear models and piecewise functions, respectively. The mine's photovoltaic-wind-storage-hydrogen energy system must meet real-time power balance requirements. The power supply consists of photovoltaic, wind power, fuel cells, battery discharge, and purchased electricity, with an upper limit on the curtailment rate set based on the mine's power grid conditions. The hydrogen system follows the law of mass conservation; the hydrogen storage state is jointly determined by the hydrogen flow rate in the electrolysis and power generation / heating stages, and its capacity and flow rate are subject to strict safety limits. On the thermal side, waste heat from fuel cells is utilized first, with any shortfall supplemented by a hydrogen boiler.

[0035] It should be noted here that the constraints in the multi-objective operational optimization model include: Strengthened constraints include mutual exclusion of battery charging and discharging, state-of-charge management to adapt to impact loads, and cyclic energy conservation to meet safety redundancy; and Key equipment constraints, including minimum start-up and shutdown times to meet the requirements of ramp rate and mine safety production; and The power grid interaction capacity is matched with the capacity of the mine substation.

[0036] Based on the aforementioned unified mechanism model and operational boundary, a three-objective operational optimization model is constructed to minimize operating costs, carbon emissions, and the self-consumption rate of renewable energy, reflecting the essential trade-off between economic efficiency, low carbon emissions, and energy consumption in mining scenarios. The economic objective considers time-of-use electricity purchase and sale costs, equipment operation and maintenance costs, and revenue from optional hydrogen sales; the environmental objective considers the carbon emission factor on the electricity purchase side; and the energy consumption objective is characterized by the self-consumption rate, which is transformed into an equivalent form through mathematical transformation within a unified minimization framework.

[0037] The daily operating cost target is:

[0038] in The cost of interacting with the power grid is in yuan. The total cost of operation and maintenance for all equipment is [amount in yuan]. Revenue from hydrogen sales is expressed in yuan; if the remaining hydrogen is sold externally, it is expressed as... ,in The value is the hydrogen valence, expressed in yuan / kg; , This is the hydrogen sales rate, kg / h; this value can be initially set to 0. This is the running step size.

[0039] The system's carbon emissions are:

[0040] in This represents the system's total daily carbon emissions, expressed in kgCO2. The carbon emission factor kgCO2 / kWh for grid electricity represents the carbon emissions generated by consuming 1 kWh of grid electricity.

[0041] The self-consumption rate of renewable energy is:

[0042] in The renewable energy absorption rate is %; the numerator is the total amount of renewable energy electricity consumed by local loads, electrolyzers, and batteries, in kWh; the denominator is the total renewable energy power generation, in kWh; and T is the total operating time of the solar-wind-storage-hydrogen energy system in the mining area. This is the running step size.

[0043] Step S102: Based on the multi-objective operation optimization model and the preset mine operation rule knowledge base, determine the search space of the decision variables corresponding to the output and start-up / shutdown sequence of each device in the mine's solar-wind-storage-hydrogen energy system.

[0044] Specifically, the knowledge base of mining area operation rules is pre-configured with various mining area operation conditions (such as shock load periods). Abundant Scenery Period The target weight vector that matches (etc.) .

[0045] Step S103: A hybrid multi-objective optimization algorithm that integrates dynamic weight adjustment and rule guidance is adopted. Within the search space of decision variables, the target weights are dynamically allocated by identifying the operating conditions of the mining area. At the same time, based on the mine operation rule library, the population initialization and individual repair are guided to generate the Pareto optimal solution set and obtain the candidate scheme library of output and start-up / shutdown timing of each device.

[0046] like Figure 3 As shown, in the initial stage of the hybrid multi-objective optimization algorithm that integrates dynamic weight adjustment and rule guidance, a partial initial solution is generated using the knowledge base of mining area operation rules, which together with the random solution constitutes the initial population. In the evolutionary iteration, if the new solution individuals generated by crossover and mutation violate the strong constraints in the knowledge base of mining area operation rules, a repair operation is triggered and they are adjusted to be feasible solutions.

[0047] During the iterative optimization process within the search space of decision variables, the load volatility predicted for the current time period is used as a basis. and the proportion of renewable energy output To identify the operating conditions of the mining area in real time And dynamically switch to the decision variable weight vector for the corresponding working condition. .

[0048] During the algorithm initialization phase, a number of high-quality initial solutions are generated using a rule base, which, together with random solutions, constitute the initial population. This improves the starting point for the search. The rule base includes rules such as "before an impact load occurs, the battery state of charge should meet..." "and other logical rules. In the evolutionary iteration, if crossover and mutation produce new solution individuals..." Violation of strong constraints in the rule base This will trigger a repair operation. This allows us to adjust the solution to a feasible one, thereby significantly reducing invalid searches and ensuring that the optimization process always focuses on the engineering-feasible solution space.

[0049] The hybrid multi-objective optimization algorithm, which integrates dynamic weight adjustment and rule-guided optimization, adopts a three-stage sequential architecture of "rule pre-screening → improved MOEA / D global optimization → local fine-grained search," and its process is as follows: Phase 1: Based on the rule knowledge base, perform rapid logical filtering on the complete decision variable space to eliminate obviously infeasible or uneconomical regions, resulting in a reduced, high-quality search space Ω'.

[0050] The second stage involves running the improved MOEA / D algorithm, which integrates the aforementioned dynamic weight adjustment and rule-guided repair mechanisms, within the space Ω'. This algorithm performs global exploration and co-evolution, ultimately outputting a uniformly distributed Pareto approximate solution set. .

[0051] Phase Three: [Regarding] Each nondominated solution in In its defined neighborhood A fine-grained local search is performed within the solution to further improve its accuracy, ultimately yielding a high-quality Pareto optimal solution set. .

[0052] Step S104: Based on the pre-constructed membership functions of each target, calculate the membership degree of each candidate scheme on each target, and then calculate the comprehensive satisfaction of each candidate scheme by linear weighted summation; calculate the interpretability score of each candidate scheme's compliance with the mining area operation rules, and select the optimal scheme for the output and start-up / shutdown sequence of each equipment by weighted comprehensive satisfaction and interpretability score.

[0053] To obtain the Pareto optimal solution set Subsequently, to select the unique best feasible solution, this invention proposes an enhanced fuzzy decision-making method. This method achieves scientific decision-making by introducing a flexible preference interval and a quantitative evaluation of the interpretability of the solution.

[0054] For the three objectives of this invention, the membership functions of their elastic preference intervals are constructed as follows: 1) Economic objective: To minimize daily operating costs. As low as possible;

[0055] in, = ; This represents the minimum daily operating cost. This represents the maximum daily operating cost. This represents the membership degree of economic objectives.

[0056] 2) Environmental goals: To minimize daily carbon emissions. As low as possible;

[0057] in, = ; This represents the minimum daily carbon emissions. This represents the maximum daily carbon emissions. This refers to the degree of membership in environmental protection goals.

[0058] 3) Energy consumption target: To maximize the self-consumption rate of renewable energy. As high as possible;

[0059] in, = ; This represents the minimum self-consumption rate of renewable energy. This represents the maximum value of the renewable energy self-consumption rate; This represents the membership degree of energy consumption targets.

[0060] After obtaining the membership degree of each solution to each objective, the overall satisfaction is calculated by linear weighted summation. :

[0061] in, These are the weight coefficients for each objective, and they satisfy... .

[0062] The expression for calculating the interpretability score of each candidate scheme's compliance with the mining area's operational rules is as follows:

[0063] in, This is the score for interpretability; This represents the total number of key rules in the mining area's operational rule base. For the first Rules; This is an indicator function; it is 1 if the rules are met, and 0 otherwise. These are the solutions in the Pareto optimal solution set, i.e., candidate schemes for the output and start-stop timing of each device. The more rules that are met, the better. The closer the value is to 1, the stronger the interpretability and feasibility of the solution.

[0064] Each solution is calculated by weighting the overall satisfaction score and the interpretability score. Final decision evaluation value :

[0065] in, ∈[0,1] is an adjustable parameter used to balance the preference between optimal performance and solution interpretability.

[0066] The weighted overall satisfaction and interpretability scores are used as the decision evaluation values; the solution with the highest decision evaluation value is selected as the optimal solution for the output and start-up / shutdown sequence of each device. :

[0067] in, This is the decision evaluation value; The Pareto optimal solution set; These are the solutions in the Pareto optimal solution set, i.e., the candidate schemes for the output and start-stop timing of each device.

[0068] The hybrid optimized operation of the solar-wind-storage-hydrogen energy system in mining areas provided by this invention establishes a unified mechanism model that fits the impact load and high reliability requirements of mines. Combined with targeted hybrid intelligent optimization strategies, it can automatically generate multi-energy collaborative scheduling schemes under given operating conditions, clarify the optimal output and start-up / shutdown sequence of each device, and provide directly applicable decision support for the refined operation of mining area energy systems.

[0069] In the optimization analysis, based on the time-varying and pulsating characteristics of the mine load, a hierarchical collaborative strategy of source-storage-load-hydrogen is implemented. During periods of abundant renewable energy, surplus electricity is rationally allocated between battery charging and electrolysis hydrogen production; when renewable energy is insufficient or facing shock loads, batteries are given priority to provide short-term power support, and fuel cells are linked to supplementary power generation. On the heat load side, the coordinated supply of waste heat from fuel cells, hydrogen boilers, and thermal storage devices is achieved to realize the cross-period balance and efficient utilization of electrical and thermal energy.

[0070] At the solution and decision-making level, this invention employs a hybrid optimization algorithm that integrates dynamic weight adjustment and rule-guided optimization. It adaptively adjusts the target weights by identifying operational conditions in real time and incorporates mine operation knowledge to improve search efficiency and the engineering feasibility of the solution, thereby consistently obtaining a high-quality Pareto optimal solution set. Furthermore, by introducing a fuzzy decision-making method that incorporates multi-attribute preferences and scheme interpretability evaluation, it automatically selects the best scheduling scheme from the solution set that boasts superior overall performance and aligns with mine operation experience, forming a complete technical closed loop from accurate modeling and efficient optimization to scientific decision-making.

[0071] Using a mine as a case study, data with 24-hour and 30-minute resolutions were used for verification. The results showed that the daily operating cost of the system was reduced by about 26.4%, carbon emissions decreased by about 22.6%, and the self-consumption rate of renewable energy increased from about 15.1% to about 85.5%, which fully verified the effectiveness and engineering applicability of the proposed strategy.

[0072] like Figure 4 As shown, the hybrid optimized mining area solar-wind-storage-hydrogen energy system operation device provided in this embodiment of the invention can be implemented in software. The hybrid optimized mining area solar-wind-storage-hydrogen energy system operation device includes the following software modules: optimization model construction module 401, search space determination module 402, candidate solution library generation module 403, and optimal solution screening module 404.

[0073] The following is a description of the functions of each software module in the hybrid optimized mining area solar-wind-storage-hydrogen energy system operating device: The optimization model construction module 401 is used to construct a multi-objective operation optimization model based on the operation data of the solar-wind-storage-hydrogen energy system in the mining area, with the goal of minimizing operating costs, minimizing carbon emissions, and maximizing the self-consumption rate of renewable energy. The search space determination module 402 is used to determine the search space of the decision variables corresponding to the output and start-up / stop sequence of each device in the solar-wind-storage-hydrogen energy system of the mining area based on the multi-objective operation optimization model and the preset knowledge base of mining area operation rules. The candidate solution library generation module 403 is used to adopt a hybrid multi-objective optimization algorithm that integrates dynamic weight adjustment and rule guidance. Within the search space of decision variables, it dynamically allocates target weights by identifying the operating conditions of the mining area. At the same time, it guides population initialization and individual repair based on the mine operation rule library to generate the Pareto optimal solution set and obtain the candidate solution library for the output and start-up / stop sequence of each device. The optimal solution screening module 404 is used to calculate the membership degree of each candidate solution on each target based on the pre-constructed membership function of each target, and then calculate the comprehensive satisfaction of each candidate solution by linear weighted summation; calculate the interpretability score of each candidate solution's compliance with the mining area operation rules, and screen out the optimal solution for the output and start-up / shutdown sequence of each equipment by weighted comprehensive satisfaction and interpretability score.

[0074] It should be noted that each module in the hybrid optimized mining area solar-wind-storage-hydrogen energy system operation device of the present invention corresponds one-to-one with each step in the hybrid optimized mining area solar-wind-storage-hydrogen energy system operation method in the above embodiments, and their specific implementation processes are the same, so they will not be repeated here.

[0075] 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.

[0076] 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 hybrid optimized mining area solar-wind-storage-hydrogen energy system operating device are coupled together via 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.

[0077] The user interface 503 may include a monitor, keyboard, mouse, trackball, click wheel, buttons, touchpad, or touch screen.

[0078] 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.

[0079] In some embodiments, the hybrid optimized solar-wind-storage-hydrogen energy system operation device for mining areas provided in this invention can be implemented using a combination of hardware and software. For example, the hybrid optimized solar-wind-storage-hydrogen energy system operation device for mining areas provided in this invention can be a processor in the form of a hardware decoding processor, which is programmed to execute the hybrid optimized solar-wind-storage-hydrogen energy system operation method for mining areas provided in this invention. For example, the processor in the form of a 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.

[0080] 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.

[0081] As an example of the hardware implementation of the hybrid optimized mining area solar-wind-storage-hydrogen energy system operation device 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 hybrid optimized mining area solar-wind-storage-hydrogen energy system operation method provided in this embodiment of the invention.

[0082] The memory 502 in this embodiment of the invention is used to store various types of data to support the operation of the hybrid optimized solar-wind-storage-hydrogen energy system operating device in the mining area, 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 a hybrid optimized mining area solar-wind-storage-hydrogen energy system operating device, such as executable instructions, and the program for implementing the hybrid optimized mining area solar-wind-storage-hydrogen energy system operation method of the embodiments of the present invention may be included in the executable instructions.

[0083] 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.

[0084] 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 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0085] 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 operating a hybrid optimized solar-wind-storage-hydrogen energy system in a mining area, characterized in that, include: Based on the operational data of the solar-wind-storage-hydrogen energy system in the mining area, a multi-objective operation optimization model is constructed with the goals of minimizing operating costs, minimizing carbon emissions, and maximizing the self-consumption rate of renewable energy. Based on the multi-objective operation optimization model and the pre-set knowledge base of mining area operation rules, the search space of decision variables corresponding to the output and start-up / shutdown sequence of each device in the solar-wind-storage-hydrogen energy system of the mining area is determined. A hybrid multi-objective optimization algorithm that integrates dynamic weight adjustment and rule guidance is adopted. Within the search space of decision variables, the target weights are dynamically allocated by identifying the operating conditions of the mining area. At the same time, based on the mine operation rule library, the population initialization and individual repair are guided to generate the Pareto optimal solution set and obtain the candidate scheme library of output and start-up / shutdown timing of each device. Based on the pre-constructed membership functions of each objective, the membership degree of each candidate solution on each objective is calculated, and then the overall satisfaction of each candidate solution is calculated by linear weighted summation. Calculate the interpretability score of each candidate scheme's compliance with the mine's operating rules. By weighting and combining the satisfaction and interpretability scores, select the optimal scheme for the output and start-up / shutdown sequence of each piece of equipment.

2. The method for operating a hybrid optimized solar-wind-storage-hydrogen energy system in a mining area as described in claim 1, characterized in that, The knowledge base of mining area operation rules is pre-configured with target weight vectors that match each mining area operation condition.

3. The method for operating a hybrid optimized solar-wind-storage-hydrogen energy system in a mining area as described in claim 2, characterized in that, During the iterative optimization process within the search space of decision variables, the operating conditions of the mining area are identified in real time based on the predicted load fluctuation rate and the proportion of renewable energy output in the current period, and the decision variable weight vectors are dynamically switched to the corresponding operating conditions.

4. The method for operating a hybrid optimized solar-wind-storage-hydrogen energy system in a mining area as described in claim 1, characterized in that, In the initial stage of the hybrid multi-objective optimization algorithm that integrates dynamic weight adjustment and rule guidance, a partial initial solution is generated using the knowledge base of mining area operation rules, which together with the random solution constitutes the initial population. During the evolutionary iteration, if the new solution individuals generated by crossover and mutation violate the strong constraints in the knowledge base of mining area operation rules, a repair operation is triggered and they are adjusted to be feasible solutions.

5. The method for operating a hybrid optimized solar-wind-storage-hydrogen energy system in a mining area as described in claim 1, characterized in that, The expression for calculating the interpretability score of each candidate scheme's compliance with the mining area's operational rules is as follows: in, This is the score for interpretability; This represents the total number of key rules in the mining area's operational rule base. For the first Rules; This is an indicator function; it is 1 if the rules are met, and 0 otherwise. These are the solutions in the Pareto optimal solution set, i.e., the candidate schemes for the output and start-stop timing of each device.

6. The method for operating a hybrid optimized solar-wind-storage-hydrogen energy system in a mining area as described in claim 1, characterized in that, The weighted overall satisfaction and interpretability scores are used as the decision evaluation values; the solution with the highest decision evaluation value is selected as the optimal solution for the output and start-up / shutdown sequence of each device. : in, This is the decision evaluation value; The Pareto optimal solution set; These are the solutions in the Pareto optimal solution set, i.e., the candidate schemes for the output and start-stop timing of each device.

7. The method for operating a hybrid optimized solar-wind-storage-hydrogen energy system in a mining area as described in claim 1, characterized in that, The constraints in the multi-objective operational optimization model include: Strengthened constraints include mutual exclusion of battery charging and discharging, state-of-charge management to adapt to impact loads, and cyclic energy conservation to meet safety redundancy; and Key equipment constraints, including minimum start-up and shutdown times to meet the requirements of ramp rate and mine safety production; and The power grid interaction capacity is matched with the capacity of the mine substation.

8. A hybrid optimized solar-wind-storage-hydrogen energy system operation device for mining areas, characterized in that, The method for operating a hybrid optimized solar-wind-storage-hydrogen energy system in a mining area, based on any one of claims 1-7, includes: The optimization model building module is used to construct a multi-objective operation optimization model based on the operation data of the solar-wind-storage-hydrogen energy system in the mining area, with the goals of minimizing operating costs, minimizing carbon emissions, and maximizing the self-consumption rate of renewable energy. The search space determination module is used to determine the search space of the decision variables corresponding to the output and start-up / shutdown sequence of each device in the solar-wind-storage-hydrogen energy system of the mining area, based on the multi-objective operation optimization model and the preset knowledge base of mining area operation rules. The candidate solution library generation module is used to adopt a hybrid multi-objective optimization algorithm that integrates dynamic weight adjustment and rule guidance. Within the search space of decision variables, it dynamically allocates target weights by identifying the operating conditions of the mining area. At the same time, it guides population initialization and individual repair based on the mine operation rule library to generate the Pareto optimal solution set and obtain the candidate solution library for the output and start-up / shutdown sequence of each device. The optimal solution selection module is used to calculate the membership degree of each candidate solution on each target based on the pre-constructed membership function of each target, and then calculate the comprehensive satisfaction of each candidate solution by linear weighted summation; calculate the interpretability score of each candidate solution's compliance with the mining area operation rules, and select the optimal solution for the output and start-up / shutdown sequence of each equipment by weighting the comprehensive satisfaction and interpretability score.

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 method for operating a hybrid optimized solar-wind-storage-hydrogen energy system in a mining area 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 method for operating a hybrid optimized solar-wind-storage-hydrogen energy system in a mining area as described in any one of claims 1-7.

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