A thermal power plant coupling heat storage peak shaving method and system and storage medium

Abstract

This invention belongs to the field of coal-fired power generation technology, and relates to a method, system, and storage medium for coupled thermal storage peak shaving in coal-fired power plants. It includes: establishing a dynamic prediction model for the coal-fired unit, which describes the energy balance and dynamic response characteristics between boiler heat load, turbine power generation, and the charging and discharging heat power of the thermal storage system; obtaining the current operating state parameters of the coal-fired unit and the future time-domain grid load prediction command; solving for the optimal control sequence in the future prediction time domain based on the operating state parameters, grid load prediction command, a preset optimization objective function, and preset constraints; and controlling the boiler fuel quantity, turbine valves, and the charging and discharging heat power of the thermal storage system based on the optimal control sequence. This invention achieves thermal-electric decoupling and power synergistic optimization of coal-fired units under deep peak shaving conditions, significantly improving the load response speed and peak shaving depth of the unit while ensuring the safe operation of the boiler and turbine.

Description

Technical Field

[0001] This invention belongs to the field of coal-fired power generation technology, and relates to a method, system and storage medium for peak shaving coupled with thermal storage in thermal power plants. Background Technology

[0002] With the continuous increase in the installed capacity of new energy sources such as wind power and photovoltaics, the inherent intermittency and volatility of their output power have brought significant challenges to the safe and stable operation of the power grid. In order to ensure the reliability of power supply, the functional positioning of coal-fired power plants is gradually shifting from traditional base load power sources to regulating power sources, which requires the units to have deeper peak-shaving capabilities and faster load response speeds.

[0003] However, the deep peak-shaving capacity of large-capacity coal-fired power units is constrained by rigid limitations such as the minimum stable combustion load of the boiler, making implementation difficult. During off-peak electricity demand at night, when grid demand falls below the boiler's stable combustion limit, the unit cannot further reduce its output, resulting in energy waste. For example, with current technology, many units still maintain their minimum technical output at around 50% of their rated load, making it difficult to adapt to even lower grid demand during off-peak periods. Furthermore, for combined heat and power (CHP) units, maintaining stable external heat supply during operation further compresses the grid's peak-shaving margin due to the "heat-driven power generation" operating mode. Simultaneously, frequent deep load reduction and increase operations exacerbate the thermal stress on the boiler and turbine, adversely affecting equipment lifespan.

[0004] To address the aforementioned issues, the industry has begun exploring the coupling of large-scale thermal storage devices with coal-fired power units, aiming to store excess energy during low-load periods and release heat to assist power generation during high-load periods. Molten salt thermal storage systems, due to their high safety, large storage capacity, long service life, and relatively low cost, have become a viable technical solution. They are suitable for the flexible retrofitting of thermal power units and can achieve large-scale energy storage and release. During periods of low grid load, surplus electricity or excess steam from the unit can be used to heat the molten salt, storing the heat in storage tanks. During periods of high grid load, the heat stored in the molten salt is released to generate steam to drive power generation or supply industrial heat loads, essentially equipping the coal-fired unit with a highly efficient thermal battery. This type of molten salt thermal storage coupling technology can effectively improve the frequency regulation and peak-shaving performance of coal-fired power units and ensure the stability of industrial steam supply under low-load conditions.

[0005] However, there is still a lack of mature and effective methods for optimizing and controlling molten salt thermal storage systems. A key challenge facing current technologies is how to achieve dynamic and smooth switching between thermal storage and heat release conditions while ensuring stable boiler combustion and safe operation, and how to achieve optimal power allocation between the unit and the thermal storage system, thereby fully tapping the potential of the thermal storage unit in peak shaving. Summary of the Invention

[0006] To address the problems in the prior art, this invention provides a method, system, and storage medium for coupled thermal storage peak shaving in thermal power plants. It realizes thermal-electric decoupling and power synergistic optimization of coal-fired units under deep peak shaving conditions, and significantly improves the load response speed and peak shaving depth of the units while ensuring the safe operation of the boiler and turbine.

[0007] To achieve the above objectives, the present invention employs the following technical solution: In a first aspect, the present invention provides a method for peak shaving of thermal power plants coupled with thermal storage, comprising the following steps: A dynamic prediction model for a coal-fired power unit is established. The dynamic prediction model is used to describe the energy balance relationship and dynamic response characteristics between boiler heat load, turbine power generation and thermal storage system charge and release power. Obtain current operating status parameters of coal-fired power units and future time-domain power grid load forecasting commands; Based on the operating status parameters, the power grid load forecasting command, the preset optimization objective function, and the preset constraints, the optimal control sequence in the future forecast time domain is solved. The control commands at the first preset moment in the optimal control sequence control the boiler's fuel quantity, turbine valves, and the charging and discharging power of the thermal storage system.

[0008] Preferably, the expression of the dynamic prediction model is:

[0009] In the formula, This is the state transition matrix; for The state vector at any given time, wherein the state vector includes at least the power generation, heat storage, steam flow rate, and boiler heat load; The input matrix; for The control vector at any given time includes at least the fuel quantity, turbine valve opening, and thermal storage system charging / discharging power. Here is the perturbation matrix; for The disturbance vector at any given time, wherein the disturbance vector includes at least the grid load command.

[0010] Preferably, the expression for the optimization objective function is:

[0011] In the formula, To optimize the objective function value; To predict the length of the time domain; Power generation capacity; For power grid load instructions; Fuel quantity; This refers to the heating power; This refers to the heat release power; To control the rate of change of quantity; , , and All are weighting coefficients.

[0012] Preferably, the constraints include thermal storage system constraints, and the expressions for the thermal storage system constraints include: Power constraints:

[0013]

[0014] In the formula, This is the maximum charging power; This represents the maximum heat release power. Thermal storage constraints:

[0015] In the formula, Minimum heat storage; For current heat storage; To maximize heat storage; When the thermal storage system is a thermocline thermal storage tank, the expression for the constraints of the thermal storage system also includes temperature constraints, and the expression for the temperature constraints is:

[0016] In the formula, Minimum allowable temperature; for The height inside the thermocline storage tank at any time Temperature distribution of the medium at that location; This is the maximum permissible temperature of the medium.

[0017] Preferably, the constraints also include boiler operation constraints and turbine operation constraints; The expressions for the boiler operating constraints include:

[0018]

[0019] In the formula, This is the minimum stable combustion load for the boiler; Real-time heat load of the boiler; This is the boiler's maximum continuous output load; This refers to the boiler load change rate; This refers to the maximum allowable rate of change of load for the boiler. The expressions for the turbine operating constraints include:

[0020]

[0021] In the formula, The rate of change of power generation; This refers to the maximum allowable rate of increase or decrease in load for the steam turbine. This represents the minimum steam inlet flow rate for the steam turbine. This refers to the real-time steam intake of the steam turbine. This represents the maximum steam intake of the steam turbine.

[0022] Preferably, the thermal storage system achieves thermoelectric decoupling of the coal-fired unit by adjusting the charging and discharging heat power. The power balance relationship after thermoelectric decoupling is expressed as follows:

[0023] In the formula, Power generation capacity; For heat load; ( ) represents the power generation function under heating conditions; The thermoelectric decoupling regulation provided for the thermal storage system.

[0024] Preferably, when the thermal storage system participates in thermoelectric decoupling, the expression for the heat load balance relationship is:

[0025] In the formula, The heat load required by the boiler; The required heat load on the user side; This refers to the heat release power; This refers to the heating power.

[0026] Preferably, the control command based on the first preset moment in the optimal control sequence controls the boiler's fuel quantity, turbine valves, and the charging and discharging heat power of the thermal storage system, including: The control command at the first preset time is decomposed into a fuel quantity setpoint, a turbine control valve opening command, a thermal storage system charging valve opening command, or a heat release valve opening command. The fuel quantity setpoint is sent to the boiler fuel control actuator, the turbine regulating valve opening command is sent to the turbine control actuator, and the heat charging valve opening command or heat releasing valve opening command is sent to the valve actuator of the thermal storage system. Each of the aforementioned actuators operates synchronously according to the received instructions, thereby achieving coordinated regulation of the unit's power generation and the thermal storage system's heat charging and discharging power.

[0027] Secondly, the present invention provides a thermal power plant coupled with thermal storage peak-shaving system, comprising: Model building module: used to establish a dynamic prediction model for coal-fired power units. The dynamic prediction model is used to describe the energy balance relationship and dynamic response characteristics between boiler heat load, turbine power generation and thermal storage system charge and release power. Data acquisition module: used to acquire the current operating status parameters of the coal-fired power unit and the future time domain power grid load forecasting instructions; Optimization solution module: used to solve for the optimal control sequence in the future prediction time domain based on the operating state parameters, the power grid load prediction command, the preset optimization objective function, and the preset constraints; Instruction execution module: used to control the boiler's fuel quantity, turbine valves, and the charging and discharging power of the thermal storage system based on the control instruction at the first preset moment in the optimal control sequence.

[0028] Thirdly, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of a thermal power plant coupled with thermal storage for peak shaving.

[0029] Compared with the prior art, the present invention has the following beneficial effects: By establishing a unified dynamic prediction model describing the energy balance and dynamic response characteristics among the boiler, turbine, and thermal storage system, a precise mathematical foundation is provided for the coordinated control of complex thermal systems. Furthermore, by combining real-time operating conditions with future grid load commands, and using preset optimization objective functions and constraints to continuously solve for the optimal control sequence, feedforward prediction and rolling optimization of future operating conditions are achieved, effectively overcoming the lag and blindness of traditional control methods. Finally, by executing the control command at the first moment, the fuel quantity, turbine valves, and thermal storage charging and discharging power are synchronously adjusted, transforming multi-device collaboration into a rigid synchronous action mechanism. This not only ensures the strict satisfaction of hard constraints such as the boiler's minimum stable combustion boundary and the turbine's safe load change rate, but also fully leverages the rapid energy buffering capacity of the thermal storage system, significantly improving the deep peak-shaving amplitude and load response speed of coal-fired units. Simultaneously, during dynamic adjustment, the drastic fluctuations in boiler combustion intensity are smoothed out, realizing a fundamental shift in coal-fired power plants from passively adapting to the grid to actively optimizing operation. Attached Figure Description

[0030] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0032] The present invention will now be described in detail with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other.

[0033] The following detailed description is exemplary and intended to provide further detailed explanation of the invention. Unless otherwise specified, all technical terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. The terminology used in this invention is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention.

[0034] The first objective of this invention is to provide a method for peak shaving in thermal power plants coupled with thermal storage, such as... Figure 1 As shown, it includes the following steps: A dynamic prediction model for a coal-fired power unit is established. The dynamic prediction model is used to describe the energy balance relationship and dynamic response characteristics between boiler heat load, turbine power generation and thermal storage system charge and release power. Obtain current operating status parameters of coal-fired power units and future time-domain power grid load forecasting commands; Based on the operating status parameters, the power grid load forecasting command, the preset optimization objective function, and the preset constraints, the optimal control sequence in the future forecast time domain is solved. The control commands at the first preset moment in the optimal control sequence control the boiler's fuel quantity, turbine valves, and the charging and discharging power of the thermal storage system.

[0035] This method constructs a unified dynamic prediction model encompassing the boiler, turbine, and thermal storage system. It accurately describes the distribution and conversion of heat released from fuel combustion among boiler thermal storage, steam power generation, and molten salt thermal storage media, as well as the dynamic response characteristics of each component under changing operating conditions. At the beginning of each control cycle, real-time operating parameters of the unit are collected, including main steam pressure and temperature, turbine regulating stage pressure, power generation, temperature distribution within the molten salt tank, and heat storage. Combined with future grid load forecast commands in the future time domain, the optimal control sequence that meets load tracking accuracy requirements and minimizes overall operating costs is calculated by solving a pre-set multi-objective optimization function and physical constraints within the prediction time domain. Finally, the control command for the first moment is sent to the actuators to precisely adjust the boiler fuel input, turbine valve opening, and the opening of the thermal storage system's charging and releasing valves, thereby achieving coordinated and optimized operation of the coal-fired power generation unit and the large-scale thermal storage system. This invention can fully leverage the rapid response and energy buffering capabilities of molten salt thermal storage units while ensuring the minimum stable combustion boundary of the boiler and the safe load change rate of the turbine. This significantly improves the deep peak shaving range and load response speed of the unit. At the same time, it effectively reduces the unit coal consumption for power generation and reduces thermal fatigue damage to key high-temperature components by smoothing out the drastic fluctuations in boiler combustion intensity. Ultimately, it enables the safe, efficient, and flexible operation of coal-fired units in a grid environment with a high proportion of new energy sources.

[0036] For example, the expression of the dynamic prediction model is:

[0037] In the formula, This is the state transition matrix; for The state vector at any given time, wherein the state vector includes at least the power generation, heat storage, steam flow rate, and boiler heat load; The input matrix; for The control vector at any given time includes at least the fuel quantity, turbine valve opening, and thermal storage system charging / discharging power. Here is the perturbation matrix; for The disturbance vector at any given time, wherein the disturbance vector includes at least the grid load command.

[0038] This dynamic prediction model accurately depicts the dynamic evolution of system state variables (such as power generation, heat storage, steam flow, and boiler heat load) under the combined action of control vectors (such as fuel quantity, turbine valve opening, and heat storage system charging and discharging power) and disturbance vectors (such as grid load commands) through state transition matrix A, input matrix B, and disturbance matrix D, thereby realizing the ability to quantitatively predict future system behavior.

[0039] For example, the expression for the optimization objective function is:

[0040] In the formula, To optimize the objective function value; To predict the length of the time domain; Power generation capacity; For power grid load instructions; Fuel quantity; This refers to the heating power; This refers to the heat release power; To control the rate of change of quantity; , , and All are weighting coefficients.

[0041] This function quantifies multi-dimensional control objectives into a single scalar indicator through weighted summation. The first term quantifies the tracking accuracy of power generation to grid dispatch commands, ensuring timely and accurate unit response to meet system frequency regulation requirements. The second term directly characterizes operational economy through the square of fuel consumption and encourages low-energy operation. The third term suppresses ineffective circulation and frequent switching in the thermal storage system by using the difference in charging and discharging heat power, avoiding unnecessary energy losses due to multiple heat exchanges during charging and discharging. The fourth term limits the range and rate of equipment operation by penalizing the rate of change of control variables, preventing wear on actuators or large fluctuations in thermal parameters caused by drastic command fluctuations. This is achieved through the reasonable configuration of weighting coefficients. to This method can dynamically balance the inherent conflicts between tracking performance, economic indicators, thermal storage efficiency, and equipment lifespan under different operating scenarios. For example, under deep peak-shaving conditions, the weights of tracking and thermal storage terms can be appropriately strengthened to ensure grid security and energy throughput capacity, while during stable operation, fuel consumption and control smoothing terms can be emphasized to achieve energy conservation and consumption reduction. This optimization function upgrades the traditional single-command tracking control mode into an intelligent decision-making process with optimal comprehensive benefits. It enables autonomous trade-offs when facing complex constraints and disturbances, ensuring the unit's ability to execute external commands while also taking into account the safe and economical operation of internal equipment. Ultimately, it enhances the flexibility of coal-fired power plants while minimizing resource consumption and maximizing equipment lifespan.

[0042] For example, the constraints include thermal storage system constraints, and the expressions for the thermal storage system constraints include: Power constraints:

[0043]

[0044] In the formula, This is the maximum charging power; The maximum heat release power is used to ensure that the thermal storage system does not exceed the physical load-bearing limits of the heat exchanger, circulating pump and related pipelines during actual operation, thereby avoiding equipment damage or a sudden drop in efficiency due to excessive flow or excessive heat exchange intensity.

[0045] Thermal storage constraints:

[0046] In the formula, Minimum heat storage; For current heat storage; To maximize heat storage capacity; the heat storage capacity constraint not only prevents the heat storage medium from solidifying due to excessive heat release or exceeding the tank capacity due to excessive heat charge, but also reserves the necessary buffer space for continuous adjustment of the system.

[0047] When the thermal storage system is a thermocline thermal storage tank, the expression for the constraints of the thermal storage system also includes temperature constraints, and the expression for the temperature constraints is:

[0048] In the formula, Minimum allowable temperature; for The height inside the thermocline storage tank at any time Temperature distribution of the medium at that location; The maximum allowable temperature of the medium; temperature constraints not only focus on the overall temperature level of the medium inside the tank, but also characterize the temperature stratification along the height of the tank, ensuring that the inclined temperature layer is always controlled within a reasonable thickness and position range, preventing the mixing of hot and cold fluids from being aggravated due to excessive temperature gradient or the inclined temperature layer touching the top or bottom of the tank, thereby damaging the heat storage efficiency and heat release quality.

[0049] The inclined temperature layer thermal storage tank exhibits temperature stratification, with the medium temperature distributed along the height of the tank and dynamically changing over time. The expression for this dynamic change process is as follows:

[0050] In the formula, The thermal diffusivity; This refers to the molten salt flow rate; For height The temperature of the molten salt at that location; Heating power per unit height; The heat dissipation power per unit height; Density of molten salt; This refers to the specific heat capacity of molten salt. This is the cross-sectional area of ​​the tank.

[0051] This expression reveals the dynamic characteristics of the thermocline storage tank from a physical perspective: where the heat diffusivity term... The thermal conductivity effect caused by temperature difference inside the molten salt was characterized, and the convection term was also described. This reflects the heat migration caused by the flow of molten salt during the charging and discharging process, while the source term This represents the direct impact of the heat power injected or extracted by the heat exchanger per unit height on the local temperature. Through the above expression, this invention can simulate the temperature profile evolution of the thermocline under charging, releasing, and static conditions in real time, accurately predicting the future trends of key state parameters such as thermocline thickness, location, and temperature gradient. It upgrades the traditional thermal storage tank, which is only treated as a capacity constraint, into a dynamic element with refined internal characteristics. This allows the controller to formulate more precise charging and releasing strategies based on a deep understanding of the thermocline's behavior. For example, during continuous charging, it can actively control the flow rate to maintain the integrity of the thermocline, avoiding excessive mixing of hot and cold fluids due to high flow rates, which would reduce thermal storage efficiency. Or, after long periods of static storage, it can maintain temperature stratification through fine-tuning the circulation to prevent natural convection from damaging the thermocline structure. This achieves proactive management and optimized utilization of the thermocline's dynamics.

[0052] For example, the constraints also include boiler operation constraints and turbine operation constraints; The expressions for the boiler operating constraints include:

[0053]

[0054] In the formula, This is the minimum stable combustion load for the boiler; Real-time heat load of the boiler; This is the boiler's maximum continuous output load; This refers to the boiler load change rate; This refers to the maximum allowable rate of change of load for the boiler. Among them, boiler operation constraints are set by setting the real-time heat load of the boiler. It must be within the minimum stable combustion load. With maximum continuous output load This directly avoids the risks of unstable combustion and flameout that coal-fired boilers may face under low-load conditions, as well as the safety issues of pressure-bearing components during overload operation; simultaneously, by monitoring the boiler load change rate... Apply restrictions This effectively suppresses drastic adjustments in fuel quantity and air supply, avoiding potential hazards such as large fluctuations in steam pressure, thermal stress concentration on the heating surface, and uncontrolled combustion caused by sudden changes in heat load.

[0055] The expressions for the turbine operating constraints include:

[0056]

[0057] In the formula, The rate of change of power generation; This refers to the maximum allowable rate of increase or decrease in load for the steam turbine. This represents the minimum steam inlet flow rate for the steam turbine. This refers to the real-time steam intake of the steam turbine. This represents the maximum steam intake of the steam turbine.

[0058] Steam turbine operating constraints are based on the safety of rotating equipment and the continuity of thermodynamic cycles. On the one hand, they limit the rate of change of power generation. Not exceeding the maximum allowable load increase / decrease rate of the steam turbine To prevent accelerated fatigue damage to critical components such as blades and rotors due to excessive thermal stress and centrifugal force changes, and on the other hand, to monitor the real-time steam intake of the turbine. Set minimum steam intake With maximum steam flow This ensures that the last-stage blades are always protected by sufficient cooling steam flow, while avoiding vibration and efficiency degradation caused by exceeding the flow capacity limit.

[0059] For example, the thermal storage system achieves thermoelectric decoupling of the coal-fired unit by adjusting the charging and discharging heat power. The power balance relationship after thermoelectric decoupling is expressed as follows:

[0060] In the formula, Power generation capacity; For heat load; ( ) represents the power generation function under heating conditions; The thermoelectric decoupling regulation provided for the thermal storage system.

[0061] Among them, the function This represents the inherent operating characteristics of traditional combined heat and power (CHP) units, namely, a strong coupling constraint between power generation and heating load. The unit must maintain a certain power output to meet heating demand, and conversely, changes in heating load will forcibly restrict the adjustment range of power generation load; while The introduction of this term signifies the degree of freedom created by the thermal storage system through the active adjustment of charging and discharging heat power. It breaks the original rigid coupling relationship, allowing the power generation capacity to be independently adjusted by the thermal storage unit absorbing redundant heat or supplementing insufficient heat energy without changing the total boiler heat load or heating capacity. This invention can be achieved through reasonable allocation... The value is sufficient to meet heating demand. At the same time, increase power generation It can flexibly track power grid dispatch instructions.

[0062] In practical applications, under conditions of deep peak shaving, when the power grid requires the generating units to significantly reduce their load but the heating load cannot be reduced synchronously, the controller can instruct the thermal storage system to... Firstly, it absorbs excess heat in a positive manner, preventing the boiler from being forced into an unstable combustion zone. Secondly, during peak grid demand, the thermal storage system absorbs excess heat in a negative manner. Releasing heat to supplement the steam source enables the power generation to rise rapidly even when the boiler response is slow, significantly improving frequency regulation performance.

[0063] For example, when the thermal storage system participates in thermoelectric decoupling, the expression for the heat load balance relationship is:

[0064] In the formula, The heat load required by the boiler; The required heat load on the user side; This refers to the heat release power; This refers to the heating power.

[0065] in, This represents the immediate heating demand required by external users. In traditional combined heat and power (CHP) units, this demand must be generated and directly supplied by the boiler in real time, resulting in a rigid coupling between boiler output and user load. However, by introducing the thermal storage system, the charging power... and heat dissipation power This invention constructs a time-shifting channel for heat: when the charging power is positive, it indicates that part of the heat generated by the boiler is transferred to the heat storage tank for temporary storage, at which time the actual heat load provided by the boiler is... The heat load is higher than the user's demand. When the heat release power is positive, it means that the heat stored in the heat storage tank is released to supplement the supply. At this time, the heat load required by the boiler can be lower than the user's demand. This invention extends the heat relationship that originally had to be balanced in real time to an optimization problem that can be redistributed in the time dimension. This allows the setting of the boiler heat load to no longer passively follow the instantaneous changes in user demand, but to be actively planned according to the overall operating economy of the unit and the grid regulation requirements.

[0066] In practical applications, when user heat load fluctuates frequently, the buffering capacity of the thermal storage system can be used to smooth out drastic changes in boiler load, enabling the boiler to maintain efficient and stable combustion for extended periods, avoiding efficiency losses and emissions degradation caused by frequent fuel quantity adjustments. Secondly, when the power grid requires the unit to participate in deep peak shaving, even if the user heat load remains high, it can be controlled via commands. This method stores excess heat from the boiler, satisfying users' heating needs while allowing for flexible reduction of power generation load.

[0067] For example, the control command based on the first preset moment in the optimal control sequence controls the boiler's fuel quantity, turbine valves, and the charging and discharging heat power of the thermal storage system, including: The control command at the first preset time is decomposed into a fuel quantity setpoint, a turbine control valve opening command, a thermal storage system charging valve opening command, or a heat release valve opening command. The fuel quantity setpoint is sent to the boiler fuel control actuator, the turbine regulating valve opening command is sent to the turbine control actuator, and the heat charging valve opening command or heat releasing valve opening command is sent to the valve actuator of the thermal storage system. Each of the aforementioned actuators operates synchronously according to the received instructions, thereby achieving coordinated regulation of the unit's power generation and the thermal storage system's heat charging and discharging power.

[0068] The synchronous and coordinated execution mechanism ensures that the generation of boiler-side heat load, the conversion and utilization of steam on the turbine side, and the absorption or replenishment of heat on the thermal storage side are coordinated and consistent on the same time segment. This achieves coordinated adjustment of power generation and thermal storage charging and releasing power on a millisecond time scale, avoiding the problems of thermodynamic parameter mismatch and energy waste caused by command transmission delays or asynchronous execution in traditional hierarchical control. Secondly, this synchronous action mechanism enables the thermal storage system to cooperate with the dynamic response of the boiler and turbine in a feedforward manner. For example, when the unit needs to rapidly increase the load, the immediate opening of the heat release valve can be synchronized with the gradual increase of fuel, and the heat released by the thermal storage can instantly replenish the steam shortage and make up for the output gap during the boiler delay period. Conversely, during the load reduction process, the timely opening of the charging valve can simultaneously absorb the redundant heat that the boiler cannot reduce in time, preventing steam pressure from exceeding limits or safety valve tripping. This invention not only ensures a smooth transition when the unit switches between different operating modes, but also maximizes the buffering and supporting role of the thermal storage system during each load adjustment process, ultimately achieving safe and stable operation of the coal-fired unit under deep peak shaving conditions and continuous improvement of overall energy efficiency.

[0069] A second objective of this invention is to provide a thermal power plant coupled with thermal storage for peak shaving, comprising: Model building module: used to establish a dynamic prediction model for coal-fired power units. The dynamic prediction model is used to describe the energy balance relationship and dynamic response characteristics between boiler heat load, turbine power generation and thermal storage system charge and release power. Data acquisition module: used to acquire the current operating status parameters of the coal-fired power unit and the future time domain power grid load forecasting instructions; Optimization solution module: used to solve for the optimal control sequence in the future prediction time domain based on the operating state parameters, the power grid load prediction command, the preset optimization objective function, and the preset constraints; Instruction execution module: used to control the boiler's fuel quantity, turbine valves, and the charging and discharging power of the thermal storage system based on the control instruction at the first preset moment in the optimal control sequence.

[0070] The model building module establishes a dynamic prediction model that accurately depicts the energy coupling relationship and dynamic response characteristics between the boiler, turbine, and thermal storage system, providing a reliable mathematical foundation for subsequent optimized control. The data acquisition module acquires real-time unit operating status and grid load forecast information, ensuring that the control system always makes decisions based on the latest data. The optimization solution module solves the optimal control sequence in the prediction time domain based on preset multi-objective functions and safety constraints, transforming the complex thermo-electric decoupling coordination problem into a quantifiable and computable mathematical optimization problem. The command execution module decomposes the optimal control command and synchronously sends it to the actuators of the fuel, valves, and thermal storage system, ensuring that the theoretical optimization results can be accurately transformed into coordinated adjustment actions in actual operation. This invention can autonomously balance multiple objectives such as power generation efficiency, thermal storage loss, and equipment lifespan while meeting grid load commands, enabling the unit to maintain safe and stable operation under deep peak shaving conditions and achieve smooth transition of thermal parameters during rapid load changes. Ultimately, it significantly improves the flexible adjustment performance and market competitiveness of coal-fired power plants without increasing the installed power generation capacity.

[0071] In one embodiment of the present invention, a computer device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions from the computer storage medium to achieve a corresponding method flow or corresponding function. The processor described in this embodiment of the present invention can be used in the operation of a thermal power plant coupled with thermal storage peak shaving method.

[0072] This invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the thermal power plant coupled thermal storage peak-shaving method in the above embodiments.

[0073] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0074] 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, and 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 illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0075] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1The function specified in one or more boxes.

[0076] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0077] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for peak shaving in a thermal power plant coupled with thermal storage, characterized in that, Includes the following steps: A dynamic prediction model for a coal-fired power unit is established. The dynamic prediction model is used to describe the energy balance relationship and dynamic response characteristics between boiler heat load, turbine power generation and thermal storage system charge and release power. Obtain current operating status parameters of coal-fired power units and future time-domain power grid load forecasting commands; Based on the operating status parameters, the power grid load forecasting command, the preset optimization objective function, and the preset constraints, the optimal control sequence in the future forecast time domain is solved. The control commands at the first preset moment in the optimal control sequence control the boiler's fuel quantity, turbine valves, and the charging and discharging power of the thermal storage system.

2. The method for peak shaving of a thermal power plant coupled with thermal storage according to claim 1, characterized in that, The expression for the dynamic prediction model is: In the formula, This is the state transition matrix; for The state vector at any given time, wherein the state vector includes at least the power generation, heat storage, steam flow rate, and boiler heat load; The input matrix; for The control vector at any given time includes at least the fuel quantity, turbine valve opening, and thermal storage system charging / discharging power. Here is the perturbation matrix; for The disturbance vector at any given time, wherein the disturbance vector includes at least the grid load command.

3. The method for peak shaving in a thermal power plant coupled with thermal storage according to claim 1, characterized in that, The expression for the optimization objective function is: In the formula, To optimize the objective function value; To predict the length of the time domain; Power generation capacity; For power grid load instructions; Fuel quantity; This refers to the heating power; This refers to the heat release power; To control the rate of change of quantity; , , and All are weighting coefficients.

4. The method for peak shaving in a thermal power plant coupled with thermal storage according to claim 1, characterized in that, The constraints include thermal storage system constraints, and the expressions for the thermal storage system constraints include: Power constraints: In the formula, This is the maximum charging power; This represents the maximum heat release power. Thermal storage constraints: In the formula, Minimum heat storage; For current heat storage; To maximize heat storage; When the thermal storage system is a thermocline thermal storage tank, the expression for the constraints of the thermal storage system also includes temperature constraints, and the expression for the temperature constraints is: In the formula, Minimum allowable temperature; for The height inside the thermocline storage tank at any time Temperature distribution of the medium at that location; This is the maximum permissible temperature of the medium.

5. The method for peak shaving in a thermal power plant coupled with thermal storage according to claim 1, characterized in that, The constraints also include boiler operation constraints and turbine operation constraints; The expressions for the boiler operating constraints include: In the formula, This is the minimum stable combustion load for the boiler; Real-time heat load of the boiler; This is the boiler's maximum continuous output load; This refers to the boiler load change rate; This refers to the maximum allowable rate of change of load for the boiler. The expressions for the turbine operating constraints include: In the formula, The rate of change of power generation; This refers to the maximum allowable rate of increase or decrease in load for the steam turbine. This represents the minimum steam inlet flow rate for the steam turbine. This refers to the real-time steam intake of the steam turbine. This represents the maximum steam intake of the steam turbine.

6. The method for peak shaving of a thermal power plant coupled with thermal storage according to claim 1, characterized in that, The thermal storage system achieves thermoelectric decoupling of the coal-fired unit by adjusting the charging and discharging heat power. The power balance relationship after thermoelectric decoupling is expressed as follows: In the formula, Power generation capacity; For heat load; ( ) represents the power generation function under heating conditions; The thermoelectric decoupling regulation provided for the thermal storage system.

7. A method for peak shaving in a thermal power plant coupled with thermal storage according to claim 6, characterized in that, When the thermal storage system participates in thermoelectric decoupling, the expression for the heat load balance relationship is: In the formula, The heat load required by the boiler; The required heat load on the user side; This refers to the heat release power; This refers to the heating power.

8. The method for peak shaving in a thermal power plant coupled with thermal storage according to claim 1, characterized in that, The control command based on the first preset time in the optimal control sequence controls the boiler's fuel quantity, turbine valves, and the charging and discharging power of the thermal storage system, including: The control command at the first preset time is decomposed into a fuel quantity setpoint, a turbine control valve opening command, a thermal storage system charging valve opening command, or a heat release valve opening command. The fuel quantity setpoint is sent to the boiler fuel control actuator, the turbine regulating valve opening command is sent to the turbine control actuator, and the heat charging valve opening command or heat releasing valve opening command is sent to the valve actuator of the thermal storage system. Each of the aforementioned actuators operates synchronously according to the received instructions, thereby achieving coordinated regulation of the unit's power generation and the thermal storage system's heat charging and discharging power.

9. A thermal power plant coupled with thermal storage for peak shaving, characterized in that, include: Model building module: used to establish a dynamic prediction model for coal-fired power units. The dynamic prediction model is used to describe the energy balance relationship and dynamic response characteristics between boiler heat load, turbine power generation and thermal storage system charge and release power. Data acquisition module: used to acquire the current operating status parameters of the coal-fired power unit and the future time domain power grid load forecasting instructions; Optimization solution module: used to solve for the optimal control sequence in the future prediction time domain based on the operating state parameters, the power grid load prediction command, the preset optimization objective function, and the preset constraints; Instruction execution module: used to control the boiler's fuel quantity, turbine valves, and the charging and discharging power of the thermal storage system based on the control instruction at the first preset moment in the optimal control sequence.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1-8.

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