Deep peak shaving optimization methods and apparatus, electronic devices and storage media

Abstract

This disclosure presents a deep peak-shaving optimization method and apparatus, electronic equipment, and storage medium. By accurately analyzing the impact of heat extraction operations on the unit's operating status based on a thermal calculation model, it dynamically optimizes the heat extraction strategy and fully improves the energy grade utilization rate. The extracted heat energy is stored and specifically used to maintain the operating temperature of related environmental protection equipment, preventing the tail gas temperature from falling below the optimal operating range. At the same time, the heat extraction and release processes are coordinated and controlled to achieve dynamic matching of heat extraction, heat storage, and heat use. This results in improved energy grade utilization efficiency, reduced coal consumption during peak shaving, reduced emissions of pollutants such as nitrogen oxides, deepened peak shaving depth of thermal power units, reduced equipment damage accumulation, balanced environmental indicators and operating efficiency, and adaptability to new energy consumption scenarios.

Description

Technical Field

[0001] This disclosure relates to the field of thermal power generation technology, and in particular to a deep peak shaving optimization method and apparatus, electronic equipment and storage medium. Background Technology

[0002] Thermal power peak-shaving technology, as a core support for the flexibility transformation of energy systems, is widely used in grid-side renewable energy consumption scenarios. With the continuous increase in wind and solar power installed capacity, the insufficient deep peak-shaving capacity of traditional thermal power units has become a key bottleneck restricting the grid connection of clean energy. Among related technologies, a complete technical system covering molten salt material development, heat exchanger design, and system integration has been constructed through the coordinated operation of molten salt thermal storage systems and thermal power units.

[0003] In existing thermal power-molten salt thermal storage coupled systems, the fixed location of the main steam / reheat steam heat extraction leads to insufficient energy quality utilization, increased coal consumption during peak shaving, and lower flue gas temperature at the tail end than the optimal operating range, resulting in excessive nitrogen oxide emissions. These technical defects not only limit the depth of peak shaving but also lead to cumulative equipment damage and imbalances in environmental indicators, necessitating breakthroughs through multi-system integration and dynamic parameter chain simulation. Summary of the Invention

[0004] This disclosure provides a deep peak shaving optimization method, apparatus, electronic device, and storage medium.

[0005] According to a first aspect of this disclosure, a deep peak-shaving optimization method is provided, comprising:

[0006] A thermodynamic calculation model for thermal power units was established to analyze the impact of heat extraction operations on the unit's operating status. Based on the analysis results of the aforementioned thermal calculation model, the thermal energy extraction strategy is dynamically optimized. The extracted heat energy is stored in a heat storage medium and released when needed, wherein at least part of the released heat energy is used to maintain the operating temperature of the associated environmental protection equipment; The process of heat energy extraction and release is controlled in a coordinated manner.

[0007] Optionally, the dynamic optimization of the thermal energy extraction strategy based on the analysis results of the thermal calculation model includes: It integrates the calculation and analysis of the turbine axial thrust, the assessment of the thermal stress on the boiler heating surface, and the assessment of the overall energy consumption of the system.

[0008] Optionally, the dynamic optimization of the thermal energy extraction strategy based on the analysis results of the thermal calculation model includes: Based on the real-time parameters of main steam and reheat steam, the proportion of heat extracted from different locations is matched and optimized to determine the comprehensive impact on the safety and economy of the unit.

[0009] Optionally, the released heat energy can be used to heat the flue gas entering the selective catalytic reduction denitrification system in order to maintain its inlet flue gas temperature within a preset range.

[0010] Optionally, the coordinated control of the heat energy extraction and release process includes: A multi-objective optimization algorithm is adopted, with peak shaving depth, operating cost and environmental protection indicators as optimization objectives, and the solution is obtained under the condition of meeting equipment safety constraints.

[0011] Optionally, the method further includes: Based on the thermal properties of the heat storage medium, the internal structure of the heat storage tank is optimized to improve the heat storage density. When the grid load changes abruptly, the heat release rate of the thermal storage medium is rapidly adjusted to achieve frequency regulation response.

[0012] According to a second aspect of this disclosure, a deep peak-shaving optimization apparatus is provided, comprising: The analysis unit is used to establish a thermodynamic calculation model for thermal power units and to analyze the impact of heat extraction operations on the unit's operating status. An optimization unit is used to dynamically optimize the heat energy extraction strategy based on the analysis results of the thermal calculation model. A storage unit is used to store extracted heat energy in a heat storage medium and release the stored heat energy when needed, wherein the released heat energy is at least partially used to maintain the operating temperature of associated environmental protection equipment; The control unit is used to coordinate the heat extraction and release process.

[0013] Optionally, the optimization unit is further configured to: It integrates the calculation and analysis of the turbine axial thrust, the assessment of the thermal stress on the boiler heating surface, and the assessment of the overall energy consumption of the system.

[0014] Optionally, the optimization unit is further configured to: Based on the real-time parameters of main steam and reheat steam, the proportion of heat extracted from different locations is matched and optimized to determine the comprehensive impact on the safety and economy of the unit.

[0015] Optionally, the released heat energy can be used to heat the flue gas entering the selective catalytic reduction denitrification system in order to maintain its inlet flue gas temperature within a preset range.

[0016] Optionally, the control unit is further configured to: A multi-objective optimization algorithm is adopted, with peak shaving depth, operating cost and environmental protection indicators as optimization objectives, and the solution is obtained under the condition of meeting equipment safety constraints.

[0017] Optionally, the method further includes: The optimization unit is also used to optimize the internal structure of the heat storage tank based on the thermal properties parameters of the heat storage medium in order to improve the heat storage density. The regulating unit is used to quickly adjust the heat release rate of the thermal storage medium to achieve frequency regulation response when the grid load changes abruptly.

[0018] According to a third aspect of this disclosure, an electronic device is provided, comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect above.

[0019] According to a fourth aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions, wherein the computer instructions are configured to cause the computer to perform the method described in the first aspect above.

[0020] According to a fifth aspect of this disclosure, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method described in the first aspect above.

[0021] The deep peak shaving optimization method, apparatus, electronic equipment, and storage medium disclosed herein, through this application, accurately analyze the impact of heat extraction operations on the unit's operating status based on a thermal calculation model, dynamically optimize the heat energy extraction strategy, and fully improve energy grade utilization. The extracted heat energy is stored and specifically used to maintain the operating temperature of related environmental protection equipment, preventing the tail gas temperature from falling below the optimal operating range. Simultaneously, the heat energy extraction and release processes are coordinated and controlled to achieve dynamic matching of heat extraction, storage, and utilization. Therefore, it can solve the technical problems in existing thermal power and molten salt thermal storage coupling systems where fixed heat extraction locations lead to insufficient energy grade utilization, increased coal consumption during peak shaving, and excessive nitrogen oxide emissions. Furthermore, it addresses the limitations of peak shaving depth, accumulated equipment damage, and imbalances in environmental indicators. The goal is to achieve the technical effects of improving energy grade utilization efficiency, reducing coal consumption during peak shaving, reducing emissions of pollutants such as nitrogen oxides, deepening the peak shaving depth of thermal power units, mitigating accumulated equipment damage, balancing environmental indicators and operating efficiency, and adapting to new energy consumption scenarios.

[0022] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0023] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein: Figure 1 A flowchart illustrating a deep peak-shaving optimization method provided in an embodiment of this disclosure; Figure 2 This is a schematic diagram of the structure of a deep peak-shaving optimization device provided in an embodiment of the present disclosure; Figure 3 A schematic diagram of another deep peak-shaving optimization device provided in this embodiment of the present disclosure; Figure 4 A schematic block diagram of an example electronic device provided for embodiments of this disclosure. Detailed Implementation

[0024] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0025] The following description, with reference to the accompanying drawings, outlines a deep peak-shaving optimization method, apparatus, electronic device, and storage medium according to embodiments of the present disclosure.

[0026] Figure 1 This is a schematic flowchart of a deep peak-shaving optimization method provided in an embodiment of the present disclosure.

[0027] like Figure 1 As shown, the method includes the following steps: Step 101: Establish a thermal calculation model for the thermal power unit to analyze the impact of heat extraction operations on the unit's operating status. The model uses heat extraction operation as the core input condition and can systematically analyze the changes in the unit's operating status after the implementation of heat extraction operation. The unit's operating status mainly includes key indicators such as overall unit energy consumption (the total amount of various energy sources consumed by the unit per unit time), turbine axial thrust (the axial force exerted on the turbine rotor during operation), and boiler heating surface wall temperature (the temperature of the heating surfaces inside the boiler used to absorb heat). Through this thermodynamic calculation model, the impact of heat extraction operation on the above-mentioned unit operating status indicators can be clearly understood, providing basic data support for subsequent optimization of relevant operating schemes for thermal power units, ensuring that heat extraction operation meets actual needs while guaranteeing that the unit remains in a safe and stable operating state.

[0028] Step 102: Based on the analysis results of the thermal calculation model, dynamically optimize the thermal energy extraction strategy; Step 103: storing the extracted thermal energy in a heat storage medium, and releasing the stored thermal energy when needed, wherein the released thermal energy is at least partially used to maintain the operating temperature of the associated environmental protection equipment; After the dynamic optimization of the thermal energy extraction strategy is completed, the thermal energy extracted according to the optimized strategy is transferred to the heat storage medium for storage. Meanwhile, when there is a thermal energy demand in the thermal power unit or associated equipment, the thermal energy stored in the heat storage medium is released. The heat storage medium is a substance with thermal energy storage capacity, which can receive and retain the extracted thermal energy through its own physical or chemical properties, ensuring that the thermal energy is not easily lost during the storage period, maintaining a good energy storage effect, and guaranteeing the availability of the thermal energy for subsequent call-up.

[0029] In the thermal energy release phase, the released thermal energy will be reasonably distributed according to actual operation demands, and at least part of the thermal energy is used to maintain the operating temperature of the associated environmental protection equipment. The associated environmental protection equipment is equipment supporting the thermal power unit and used to realize environmental protection treatment functions, and its normal operation needs to be maintained within a specific temperature range. If the temperature deviates from this range, it may lead to a decrease in the treatment efficiency of the equipment, failure to meet the environmental protection treatment standards, and even cause equipment failures that affect the overall operation. By using part of the released thermal energy to maintain the operating temperature of the equipment, it can not only ensure that the environmental protection equipment continuously and stably exerts its environmental protection function, but also realize the efficient utilization of the extracted thermal energy, avoid thermal energy waste, and at the same time adapt to the overall operation demands of the thermal power unit, helping the unit operate stably on the premise of meeting environmental protection requirements.

[0030] Step 104: performing coordinated control on the thermal energy extraction and release processes.

[0031] Coordinated control is carried out on the thermal energy extraction process and the release process. The coordinated control refers to a control mode that coordinates the operating states of the two processes, and dynamically adjusts key parameters to make the two processes adapt to each other and synchronously respond to the demands of the thermal power unit and associated equipment. During implementation, based on the unit operation data fed back by the thermal calculation model, parameters such as the steam extraction rate and extraction temperature in the thermal energy extraction process are monitored in real time, and the heat release rate of the heat storage medium and the changes in the temperature demand of the associated environmental protection equipment during the thermal energy release process are tracked at the same time.

[0032] When the thermal calculation model shows that the unit's energy consumption is within a reasonable range and the extraction rate can be increased, the current thermal storage capacity of the thermal storage medium and the recent heat release demand of related equipment are simultaneously assessed. If the thermal storage capacity is sufficient and further heat release is required, the extraction rate is appropriately increased. If the current temperature of the related environmental protection equipment is close to the lower limit and immediate replenishment of thermal energy is needed, the heat release parameters of the release process are adjusted first, while the extraction process is adjusted accordingly to ensure the continuity of thermal energy supply. Through such coordinated control, it is possible to avoid overloading the thermal storage medium due to excessive extraction and to prevent insufficient thermal energy supply when the release demand increases. This ensures that the thermal energy extraction and release processes always meet the requirements of safe unit operation and stable operation of environmental protection equipment, achieving efficient operation of the entire thermal energy utilization system.

[0033] In some embodiments, the dynamic optimization of the thermal energy extraction strategy based on the analysis results of the thermal calculation model includes: It integrates the calculation and analysis of the turbine axial thrust, the assessment of the thermal stress on the boiler heating surface, and the assessment of the overall energy consumption of the system.

[0034] When dynamically optimizing the heat extraction strategy based on the analysis results of the thermal calculation model, it is necessary to integrate the calculation and analysis of the turbine axial thrust, the assessment of the thermal stress on the boiler heating surface, and the assessment of the overall system energy consumption. The calculation and analysis of the turbine axial thrust involves quantifying the axial force experienced by the turbine rotor under heat extraction conditions to determine whether this force is within the equipment's safe tolerance range, thus avoiding rotor wear, seal failure, and other malfunctions caused by excessive thrust. The assessment of the boiler heating surface thermal stress focuses on the stress distribution caused by temperature changes during heat extraction, identifying stress concentration areas and values ​​to prevent excessive thermal stress from causing deformation and cracking of the heating surface, which could affect the boiler's operational stability. The assessment of the overall system energy consumption requires statistical analysis of various energy consumption changes caused by heat extraction operations, accurate calculation of energy costs, and ensuring that the optimized strategy meets economic requirements.

[0035] By organically integrating these three assessment components, a comprehensive understanding of the combined impact of heat extraction operations on the safety status of core unit components and system operating costs can be achieved. Based on this, key parameters such as the location, proportion, and rate of heat extraction can be adjusted in a targeted manner. This ensures that the dynamically optimized heat extraction strategy not only meets the heat acquisition requirements but also takes into account the safety protection of unit components and the economic efficiency of system operation, thereby further improving the overall operational reliability and efficiency of the thermal power unit coupled with the heat storage system.

[0036] In some embodiments, the dynamic optimization of the thermal energy extraction strategy based on the analysis results of the thermal calculation model includes: Based on the real-time parameters of main steam and reheat steam, the proportion of heat extracted from different locations is matched and optimized to determine the comprehensive impact on the safety and economy of the unit.

[0037] When dynamically optimizing the thermal energy extraction strategy based on the analysis results of the thermal calculation model, it is necessary to match and optimize the proportion of heat extracted from different positions according to the real-time parameters of main steam and reheat steam, so as to determine the comprehensive influence law of said proportion on the safety and economy of the unit. The real-time parameters of main steam and reheat steam include key operating data such as temperature, pressure, and flow rate, which directly reflect the energy state of the steam and the current thermal condition of the unit, and are the core basis for optimizing the heat extraction proportion.

[0038] Different heat extraction positions correspond to different thermal nodes such as the main steam pipeline and reheat steam pipeline of the thermal power unit. The steam energy level and parameter stability of each node are different, and the corresponding heat extraction cost and the degree of influence on unit operation are also different. During the optimization process, it is necessary to capture the parameter fluctuations of main steam and reheat steam in real time, dynamically adjust the heat extraction proportion of each heat extraction position, simulate the operating state of the unit under different proportion combinations through the thermal calculation model, focus on analyzing the influence of said proportion on safety indicators such as unit energy consumption, steam turbine axial thrust, and boiler heating surface wall temperature, and calculate the corresponding economic indicators such as energy consumption cost and operation efficiency, so as to summarize the comprehensive influence law between different heat extraction proportions and the safety and economy of the unit, ensuring that the optimized thermal energy extraction strategy is not only adapted to real-time steam parameters, but also achieves the balance between safe unit operation and economic benefits.

[0039] In some embodiments, the released thermal energy is used to heat the flue gas entering the selective catalytic reduction denitration system, so as to maintain the flue gas temperature at the inlet thereof within a preset range.

[0040] The released thermal energy is used to heat the flue gas entering the selective catalytic reduction denitration system, so as to maintain the flue gas temperature at the inlet of said system within a preset range. The selective catalytic reduction denitration system is the core environmental protection equipment supporting the thermal power unit, which removes nitrogen oxides in the flue gas through catalytic reaction to achieve pollutant emission reduction. The denitration efficiency of said system is closely related to the inlet flue gas temperature. If the flue gas temperature is lower than the minimum temperature required for the reaction, the catalyst activity will decrease significantly, the denitration effect will be greatly reduced, and the environmental protection emission requirements cannot be met; if the flue gas temperature is too high, it may lead to accelerated catalyst aging and increase equipment maintenance costs.

[0041] The preset range is the optimal flue gas temperature interval determined according to the catalyst performance, denitration efficiency target and equipment safe operation requirements. The released thermal energy performs heat exchange with the flue gas entering said system through a reasonable heat transfer path, compensates the flue gas temperature loss in real time, and ensures that the temperature of the flue gas when entering the system is stably within the preset range. This method not only realizes the efficient utilization of stored thermal energy, but also ensures that the selective catalytic reduction denitration system continuously and stably exerts the denitration function, so that the thermal power unit can meet the environmental protection emission standards under different operating conditions such as deep peak regulation, and is adapted to the overall operation rhythm of the unit, taking into account both environmental protection benefits and operation stability.

[0042] In some embodiments, the coordinated control of the heat energy extraction and release process includes: A multi-objective optimization algorithm is adopted, with peak shaving depth, operating cost and environmental protection indicators as optimization objectives, and the solution is obtained under the condition of meeting equipment safety constraints.

[0043] When coordinating the control of the heat energy extraction and release process, a multi-objective optimization algorithm is adopted, with peak-shaving depth, operating cost, and environmental indicators as optimization objectives, and the solution is obtained under the condition of meeting equipment safety constraints. The multi-objective optimization algorithm is a computational method that can simultaneously coordinate multiple interrelated or conflicting optimization directions to seek a comprehensive optimal solution, and is suitable for optimizing control parameters of complex thermal systems. Peak-shaving depth refers to the ability of thermal power units to adjust output power according to grid load demand, directly affecting the stability and flexibility of grid operation; operating cost encompasses various expenses such as energy loss during heat energy extraction, maintenance of thermal storage media, and equipment operating losses, and is a core indicator for measuring system economics; environmental indicators mainly include key parameters that must meet environmental requirements, such as the denitrification efficiency of the selective catalytic reduction denitrification system and pollutant emission concentrations.

[0044] Equipment safety constraints refer to the requirement that parameters such as turbine axial thrust, boiler heating surface wall temperature, and heat storage medium operating temperature must be strictly maintained within the safety thresholds designed for the equipment to prevent equipment damage or malfunctions due to parameter exceeding limits. By using multi-objective optimization algorithms to quantitatively model and solve these objectives and constraints, optimal control parameters such as heat extraction rate, release timing, and heat extraction ratio can be output. This ensures that the heat extraction and release process meets the grid peak-shaving requirements, controls operating costs, meets environmental protection standards, and simultaneously guarantees the safe and stable operation of the equipment, achieving a dynamic balance of multiple objectives and improving the overall system operating efficiency.

[0045] In some embodiments, the method further includes: Based on the thermal properties of the heat storage medium, the internal structure of the heat storage tank is optimized to improve the heat storage density. When the grid load changes abruptly, the heat release rate of the thermal storage medium is rapidly adjusted to achieve frequency regulation response.

[0046] The thermophysical properties of the thermal storage medium, including specific heat capacity, thermal conductivity, phase change temperature, and thermal stability, are key characteristics that directly affect thermal energy storage efficiency and capacity. These parameters provide the core design basis for optimizing the internal structure of the thermal storage tank. Optimization of the internal structure of the thermal storage tank can be achieved by rationally designing internal flow guiding components to optimize the medium flow path, or by adopting a layered storage structure to reduce thermal mixing losses. Ultimately, this increases the thermal storage density, i.e., the total amount of thermal energy that can be stored per unit volume of the thermal storage tank, thereby improving the space utilization and energy storage capacity of the thermal storage system.

[0047] Sudden grid load change refers to a situation where the power consumption load in the power grid increases or decreases significantly within a short period. In this case, thermal power units need to quickly adjust their output power to maintain grid frequency stability. By rapidly adjusting the heat release rate of the heat storage medium, part of the energy can be supplemented or absorbed in a timely manner, assisting the units to quickly respond to frequency regulation demands, shortening the frequency regulation response time, and improving the stability and reliability of grid operation. These two supplementary contents further improve the functions of the entire thermal energy utilization system, not only enhancing the efficiency of the heat storage link, but also strengthening the system's adaptability to grid load changes, making the method more practical and flexible in practical applications.

[0048] Corresponding to the foregoing deep peak regulation optimization method, the present invention further proposes a deep peak regulation optimization apparatus. Since the apparatus embodiment of the present invention corresponds to the foregoing method embodiment, details not disclosed in the apparatus embodiment may be referred to the foregoing method embodiment, and will not be elaborated in the present invention.

[0049] Figure 2 is a schematic structural diagram of a deep peak regulation optimization apparatus provided by an embodiment of the present disclosure, as shown in Figure 2 the figure, includes: an analysis unit 21, configured to establish a thermal calculation model of the thermal power unit, and analyze the influence of the heat extraction operation on the operating state of the unit; an optimization unit 22, configured to dynamically optimize the thermal energy extraction strategy based on the analysis result of the thermal calculation model; a storage unit 23, configured to store the extracted thermal energy in a heat storage medium, and release the stored thermal energy when needed, where the released thermal energy is at least partially used to maintain the operating temperature of associated environmental protection equipment; a control unit 24, configured to perform coordinated control over the thermal energy extraction and release processes.

[0050] Further, in a possible implementation manner of the embodiment of the present disclosure, the optimization unit 22 is further configured to: integrate the calculation and analysis of the axial thrust of the steam turbine, the evaluation of the thermal stress on the heating surface of the boiler, and the evaluation of the overall energy consumption of the system.

[0051] Further, in a possible implementation manner of the embodiment of the present disclosure, the optimization unit 22 is further configured to: match and optimize the proportion of heat extracted from different positions according to the real-time parameters of the main steam and reheat steam, so as to determine the comprehensive influence rule on the safety and economy of the unit.

[0052] Further, in a possible implementation manner of the embodiment of the present disclosure, the released thermal energy is used to heat the flue gas entering the selective catalytic reduction denitration system, so as to maintain the flue gas temperature at its inlet within a preset range.

[0053] Furthermore, in one possible implementation of this disclosure embodiment, the control unit 24 is further configured to: A multi-objective optimization algorithm is adopted, with peak shaving depth, operating cost and environmental protection indicators as optimization objectives, and the solution is obtained under the condition of meeting equipment safety constraints.

[0054] Furthermore, in one possible implementation of the embodiments of this disclosure, such as Figure 3 As shown, the method further includes: The optimization unit 22 is also used to optimize the internal structure of the heat storage tank based on the thermal properties parameters of the heat storage medium in order to improve the heat storage density. The regulating unit 25 is used to quickly adjust the heat release rate of the thermal storage medium to achieve frequency regulation response when the grid load changes suddenly.

[0055] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of the embodiments of this disclosure, and the principle is the same. Therefore, the embodiments of this disclosure are not limited thereto.

[0056] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0057] Figure 4 A schematic block diagram of an example electronic device 400 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0058] like Figure 4 As shown, device 400 includes a computing unit 401, which can perform various appropriate actions and processes based on a computer program stored in ROM (Read-Only Memory) 402 or a computer program loaded from storage unit 408 into RAM (Random Access Memory) 403. RAM 403 may also store various programs and data required for the operation of device 400. The computing unit 401, ROM 402, and RAM 403 are interconnected via bus 404. I / O (Input / Output) interface 405 is also connected to bus 404.

[0059] Multiple components in device 400 are connected to I / O interface 405, including: input unit 406, such as keyboard, mouse, etc.; output unit 407, such as various types of monitors, speakers, etc.; storage unit 408, such as disk, optical disk, etc.; and communication unit 409, such as network card, modem, wireless transceiver, etc. Communication unit 409 allows device 400 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0060] The computing unit 401 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, CPUs (Central Processing Units), GPUs (Graphics Processing Units), various special-purpose AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, DSPs (Digital Signal Processors), and any suitable processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as deep peak shaving optimization methods. For example, in some embodiments, the deep peak shaving optimization method may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by the computing unit 401, one or more steps of the methods described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to perform the aforementioned deep peaking optimization method by any other suitable means (e.g., by means of firmware).

[0061] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application-Specific Standard Products), SOCs (System-on-Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0062] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0063] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, RAM, ROM, EPROM (Electrically Programmable Read-Only Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0064] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0065] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include LANs (Local Area Networks), WANs (Wide Area Networks), the Internet, and blockchain networks.

[0066] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service system that addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0067] It's important to note that artificial intelligence (AI) is the study of enabling computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). It encompasses both hardware and software technologies. AI hardware technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily include computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graph technologies.

[0068] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0069] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A deep peak-shaving optimization method, characterized in that, include: A thermodynamic calculation model for thermal power units was established to analyze the impact of heat extraction operations on the unit's operating status. Based on the analysis results of the aforementioned thermal calculation model, the thermal energy extraction strategy is dynamically optimized. The extracted heat energy is stored in a heat storage medium and released when needed, wherein at least part of the released heat energy is used to maintain the operating temperature of the associated environmental protection equipment; The process of heat energy extraction and release is controlled in a coordinated manner.

2. The method according to claim 1, characterized in that, The dynamic optimization of the thermal energy extraction strategy based on the analysis results of the aforementioned thermal calculation model includes: It integrates the calculation and analysis of the turbine axial thrust, the assessment of the thermal stress on the boiler heating surface, and the assessment of the overall energy consumption of the system.

3. The method according to claim 1, characterized in that, The dynamic optimization of the thermal energy extraction strategy based on the analysis results of the aforementioned thermal calculation model includes: Based on the real-time parameters of main steam and reheat steam, the proportion of heat extracted from different locations is matched and optimized to determine the comprehensive impact on the safety and economy of the unit.

4. The method according to claim 1, characterized in that, The released heat energy is used to heat the flue gas entering the selective catalytic reduction denitrification system in order to maintain its inlet flue gas temperature within a preset range.

5. The method according to claim 1, characterized in that, The coordinated control of the heat energy extraction and release process includes: A multi-objective optimization algorithm is adopted, with peak shaving depth, operating cost and environmental protection indicators as optimization objectives, and the solution is obtained under the condition of meeting equipment safety constraints.

6. The method according to claim 1, characterized in that, The method further includes: Based on the thermal properties of the heat storage medium, the internal structure of the heat storage tank is optimized to improve the heat storage density. When the grid load changes abruptly, the heat release rate of the thermal storage medium is rapidly adjusted to achieve frequency regulation response.

7. A deep peak-shaving optimization method, characterized in that, include: The analysis unit is used to establish a thermodynamic calculation model for thermal power units and to analyze the impact of heat extraction operations on the unit's operating status. An optimization unit is used to dynamically optimize the heat energy extraction strategy based on the analysis results of the thermal calculation model. A storage unit is used to store extracted heat energy in a heat storage medium and release the stored heat energy when needed, wherein the released heat energy is at least partially used to maintain the operating temperature of associated environmental protection equipment; The control unit is used to coordinate the heat extraction and release process.

8. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method according to any one of claims 1-6.

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