Peak shaving life loss coordination control system and method for molten salt-coal coupling system

Abstract

This disclosure provides a coordinated control system and method for peak-shaving lifespan loss in a molten salt-coal-power coupled system, belonging to the field of energy technology and power system technology. The system includes a coal-fired power generation unit, a molten salt thermal storage unit, a coupling interface, and a system coordination controller. The controller has a built-in state prediction and lifespan management module for executing a lifespan loss coordinated control algorithm based on state prediction. The method includes: acquiring grid peak-shaving commands and real-time operating parameters; predicting the lifespan loss rate under different strategies using a preset key component lifespan loss model; solving for the optimal coordinated control strategy using the minimum peak-shaving command tracking deviation, the minimum operating cost, and the minimum lifespan loss increment as multi-objective optimization functions; and dynamically allocating power output and storage / release power commands. This disclosure achieves coordinated optimization of peak-shaving performance, economy, and equipment lifespan, improving the safety margin of key equipment and the long-term operational reliability of the system through proactive prediction and dynamic protection.

Description

Technical Field

[0001] The embodiments disclosed herein belong to the field of energy technology and power system technology, specifically relating to a coordinated control system and method for peak shaving life loss of molten salt-coal-electricity coupling system. Background Technology

[0002] With the strategic goal of "carbon peaking and carbon neutrality," the transformation of the energy structure towards clean and low-carbon energy has been accelerated, leading to a surge in installed capacity of new energy sources and a rapid increase in the proportion of renewable energy generation such as wind and solar power. These energy sources are intermittent, volatile, and uncertain, posing a significant challenge to the stable operation of the power grid. To balance the power fluctuations of wind and solar power and maintain grid frequency stability, a large number of flexible peak-shaving power sources are needed to provide power during peak load periods and reduce power during off-peak periods. Currently, coal-fired power remains the mainstay of electricity supply and the primary peak-shaving power source. Frequent load changes greatly exacerbate low-cycle fatigue damage, while creep damage to high-temperature components continues. The interaction between these two factors severely shortens the design life of the units, leading to soaring maintenance costs and increased safety hazards.

[0003] Traditional control strategies have significant limitations. For example, storing heat at night and releasing it during the day does not take into account the real-time fluctuations of grid peak-shaving commands and cannot respond to changes in the unit's own state. Most optimization control research focuses on maximizing peak-shaving benefits or minimizing coal consumption, treating the equipment as a "black box" and ignoring its internal dynamic stress and lifespan loss. Summary of the Invention

[0004] The embodiments disclosed herein aim to at least solve one of the technical problems existing in the prior art, and provide a coordinated control system and method for peak shaving life loss of molten salt-coal-electricity coupling system.

[0005] One aspect of this disclosure provides a coordinated control system for peak-shaving lifespan loss in a molten salt-coal-power coupled system, the system comprising: A coal-fired power generation unit includes a boiler, a steam turbine, and a generator; The molten salt thermal energy storage unit includes a molten salt storage tank, a molten salt heater, a molten salt-feedwater heat exchanger, and related piping and valves; The coupling interface is used for the molten salt heater to extract heat from the steam system or flue gas system of the boiler to heat and store molten salt, and for the molten salt-feed water heat exchanger to use the stored molten salt heat to heat the boiler feedwater or generate auxiliary steam. The system coordination controller has its signal input terminal connected to the power grid dispatch center to receive power grid peak-shaving commands, and its signal output terminals connected to both the coal-fired power generation unit and the molten salt thermal storage unit; wherein... The system coordination controller has a built-in state prediction and lifetime management module, which is configured to execute a lifetime loss coordination control algorithm based on state prediction.

[0006] Furthermore, the state prediction and lifetime management module includes: The load forecasting submodule is used to predict the power grid peak-shaving demand curve within a future time window based on historical data and real-time power grid information. The equipment status prediction submodule is used to predict the temperature and stress field distribution of key components within a future time window based on real-time operating data of the coal-fired power generation unit and the molten salt thermal storage unit, through a pre-established thermodynamic-stress model. The life loss calculation submodule is used to calculate the cumulative life loss of critical components based on the predicted stress field distribution.

[0007] Furthermore, the key components include one or more of the following: boiler drum, high-temperature superheater, turbine rotor, and main steam pipe.

[0008] Furthermore, the life loss calculation submodule is used to calculate the low-cycle fatigue life loss fraction according to the Manson-Coffin equation.

[0009] Another aspect of this disclosure provides a method for coordinated control of peak-shaving lifetime loss in a molten salt-coal-power coupled system, based on the aforementioned coordinated control system for peak-shaving lifetime loss in a molten salt-coal-power coupled system, the method comprising: Obtain current real-time power grid peak-shaving instructions and power grid peak-shaving demand within future time windows; Obtain real-time operating status parameters of molten salt thermal storage unit and coal-fired power generation unit; Based on the real-time operating status parameters, the future lifespan loss rate of key components is predicted under different control strategies through a preset key component lifespan loss model. The optimal coordinated control strategy is solved by taking the minimum tracking deviation of the total peak shaving command, the minimum system operating cost, and the minimum increase in total lifetime loss as the multi-objective optimization function. According to the optimal coordination control strategy, the output command of the coal-fired power generation unit and the storage / release power command of the molten salt thermal storage unit are dynamically allocated.

[0010] Furthermore, the critical component life loss model calculates the fatigue life loss fraction for each stress cycle based on the Manson-Coffin equation, as shown in the following formula:

[0011]

[0012] In the formula, This represents the fatigue life loss fraction for a single stress cycle. This refers to the number of material failure cycles under stress cycling amplitude and mean temperature. For the total strain range, The fatigue strength coefficient, For Young's modulus, The fatigue strength index, The fatigue ductility coefficient, It is the fatigue ductility index.

[0013] Furthermore, the multi-objective optimization function is shown in the following equation:

[0014] In the formula, This represents the total power demand of the power grid. This represents the total output power of the system. To optimize the total coal consumption cost within the cycle, To optimize the total lifespan loss increment of key components within the cycle, , , These are the weighting coefficients.

[0015] Furthermore, the weighting coefficients are dynamically adjusted based on the urgency of power grid peak shaving and the health status of the equipment.

[0016] Furthermore, the solution for the optimal coordinated control strategy employs a model predictive control framework, specifically including: In each control cycle, the current system state is used as the initial condition; Within the prediction time domain, the multi-objective optimization function is solved in a rolling manner to obtain the optimal operation sequence for the coal-fired power generation unit and the molten salt thermal storage unit; The first element of the operation sequence is sent to each unit as the actual control command at the current moment.

[0017] Furthermore, the dynamic allocation includes a lifetime protection mode: When the predicted rate of life loss exceeds a preset safety threshold, the system coordination controller prioritizes instructing the molten salt thermal storage unit to handle the power change and limits the load change rate of the coal-fired power generation unit.

[0018] This disclosure discloses a coordinated control system and method for peak shaving lifespan loss in a molten salt-coal-power coupled system. By physically integrating the molten salt thermal storage unit and the coal-fired power generation unit and managing them uniformly by a system coordination controller with a built-in state prediction and lifespan management module, it breaks through the fundamental problem of the original system operating independently and unable to coordinate optimization, laying the hardware foundation for simultaneously achieving peak shaving and lifespan protection. By quantifying the lifespan loss of key components into objective indicators that can be calculated in real time, it provides direct input variables for optimized control, making "extending equipment lifespan" a precisely executable optimization objective. By using the minimum tracking deviation of the total peak shaving command, the minimum system operating cost, and the minimum increment of total lifespan loss as multi-objective optimization functions, it enables the three conflicting objectives of peak shaving performance, economy, and equipment lifespan to be coordinated and solved within a unified framework. Ultimately, it achieves comprehensive optimization of the system in terms of safety, economy, and efficiency. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating a method for coordinated control of peak-shaving lifespan loss in a molten salt-coal-power coupling system according to an embodiment of this disclosure. Detailed Implementation

[0020] The technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. Based on the embodiments of this disclosure, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this disclosure.

[0021] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this disclosure.

[0022] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0023] It should be understood that although the terms first, second, third, etc., may be used in this disclosure to describe various components, these components should not be limited by these terms. These terms are used to distinguish one component from another. Therefore, the first component discussed below may be referred to as the second component without departing from the teachings of this disclosure. As used in this disclosure, the term "and / or" includes all combinations of any one and more of the associated listed items.

[0024] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of exemplary embodiments, and the modules or processes in the drawings are not necessarily necessary for implementing this disclosure, and therefore cannot be used to limit the scope of protection of this disclosure.

[0025] One embodiment of this disclosure provides a molten salt-coal-power coupled system peak-shaving lifetime loss coordinated control system, comprising: a coal-fired power generation unit, including a boiler, a steam turbine, and a generator; a molten salt thermal storage unit, including a molten salt storage tank, a molten salt heater, a molten salt-feedwater heat exchanger, and related pipelines and valves; a coupling interface for the molten salt heater to extract heat from the boiler's steam system or flue gas system to heat and store molten salt, and for the molten salt-feedwater heat exchanger to use the stored molten salt heat to heat boiler feedwater or generate auxiliary steam; and a system coordination controller, whose signal input terminal is connected to the power grid dispatch center for receiving power grid peak-shaving commands, and whose signal output terminal is connected to the coal-fired power generation unit and the molten salt thermal storage unit respectively; wherein, the system coordination controller has a built-in state prediction and lifetime management module, which is configured to execute a lifetime loss coordinated control algorithm based on state prediction.

[0026] Specifically, the molten salt thermal storage unit is physically integrated with the traditional coal-fired power generation unit through a coupling interface, and managed uniformly by an intelligent system coordinating controller. This solves the fundamental problem of the original system operating independently and being unable to coordinate and optimize, laying the hardware foundation for simultaneously achieving peak shaving and lifespan protection effects.

[0027] For example, the state prediction and lifetime management module includes: The load forecasting submodule is used to predict the peak-shaving demand curve of the power grid within a specific future time window based on historical data and real-time power grid information. The equipment status prediction submodule is used to predict the temperature and stress field distribution of key components within a future time window based on real-time operating data of the coal-fired power generation unit and the molten salt thermal storage unit, through a pre-established thermodynamic-stress model. The life loss calculation submodule, connected to the equipment condition prediction submodule, is used to calculate the cumulative life loss (low-cycle fatigue life loss fraction) of key components based on the predicted stress field distribution using the Manson-Coffin equation. It is the intelligent core of the controller.

[0028] The key components include one or more of the boiler drum, high-temperature superheater, turbine rotor, and main steam piping, thus focusing on the most expensive, critical, and vulnerable parts of the system. This allows investment and computational resources to be used effectively, ensuring that the proposed method solves the most practical and pressing engineering problems and preventing a decline in control effectiveness due to target generalization.

[0029] By introducing three sub-modules—load forecasting, equipment condition forecasting, and lifespan loss calculation—the control decision-making process has been elevated from the traditional "current state-based" approach to a more advanced "future forecast-based" stage. This enables the system to proactively adjust its strategies, preventing equipment from experiencing excessive stress, thus achieving a leap from "passive response" to "active protection."

[0030] like Figure 1 As shown, another embodiment of this disclosure provides a method for coordinated control of peak-shaving lifetime loss in a molten salt-coal-power coupled system, based on the coordinated control system for peak-shaving lifetime loss in a molten salt-coal-power coupled system described in the previous embodiment, comprising: Step S1: Obtain the current real-time peak-shaving instructions of the power grid and the peak-shaving demand of the power grid within the future time window.

[0031] Step S2: Obtain the real-time operating status parameters of the molten salt thermal storage unit and the coal-fired power generation unit.

[0032] Step S3: Based on the real-time operating status parameters, predict the future life loss rate of key components under different control strategies using a preset key component life loss model.

[0033] Specifically, for the boiler drum or main steam pipeline, the low-cycle fatigue life loss of key components is calculated using the following formula:

[0034] in, This represents the fatigue life loss fraction for a single stress cycle. For this stress cycle amplitude and average temperature The number of material failure cycles is given by the Manson-Coffin equation:

[0035] in, For the total strain range, the predicted temperature difference is obtained through a thermodynamic-stress model. Calculated; This is the fatigue strength coefficient; Young's modulus; The fatigue strength index; It is the fatigue ductility coefficient; The fatigue ductility index. The total lifespan loss of a critical component within one control cycle. Loss fraction for all identified stress cycles The sum of these factors transforms lifespan loss from a vague, qualitative concept into an objective indicator that can be quantified in real time and calculated precisely. By introducing the mature fatigue life theory model of the Manson-Coffin equation, the assessment of equipment damage is grounded in solid physics, resulting in scientific, accurate, and reliable results. This quantitative assessment provides direct and calculable input variables for subsequent optimized control, making "extending equipment lifespan" no longer an empty slogan, but an optimization goal that can be integrated into the controller algorithm and executed precisely.

[0036] Step S4: Solve for the optimal coordinated control strategy by taking the minimum tracking deviation of the total peak shaving command, the minimum system operating cost, and the minimum increment of total lifetime loss as the multi-objective optimization function.

[0037] Specifically, the mathematical expression of the multi-objective optimization function is as follows:

[0038] in, This represents the total power demand of the power grid. This represents the total output power of the system. To optimize the total coal consumption cost within the cycle; To optimize the total lifespan loss increment of key components within the cycle; , , As weighting coefficients, they can be dynamically adjusted based on the urgency of power grid peak shaving and equipment health status. This provides a flexible and adjustable trade-off mechanism by specifying and mathematically representing the objectives of coordinated control. , , System operators can dynamically adjust the focus of control strategies based on actual conditions. For example, when the power grid is extremely unstable, the emphasis can be increased. To ensure priority tracking of instructions; to improve [the effectiveness of] equipment before maintenance or when it is severely aged. Prioritizing the protection of equipment lifespan, this design makes the control strategy highly engineering-practical and adaptable, capable of handling diverse real-world operating scenarios.

[0039] The optimal coordinated control strategy is solved using a model predictive control framework, which includes: in each control cycle, the current system state is used as the initial condition; in the prediction time domain, a multi-objective optimization function is solved continuously to obtain the optimal operation sequence of the coal-fired power generation unit and the molten salt thermal storage unit; the first element of the operation sequence is used as the actual control command at the current moment and issued to each unit, providing a specific technical path to achieve the above complex optimization.

[0040] Step S5: According to the optimal coordination control strategy, dynamically allocate the output command of the coal-fired power generation unit and the heat storage / release power command of the molten salt thermal storage unit.

[0041] Specifically, the dynamic allocation strategy includes a lifespan protection mode. When the predicted lifespan loss rate exceeds a preset safety threshold, the coordinating controller prioritizes instructing the molten salt thermal storage unit to bear more drastic power changes, limiting the load change rate of the coal-fired power generation unit to a moderate range. This provides a specific protective measure under extreme or dangerous operating conditions. It explicitly uses the rapid response characteristics of the molten salt thermal storage system as a "buffer" or "sacrificial pool" to protect the more valuable and vulnerable main coal-fired power equipment. When the system predicts excessively rapid lifespan loss, it proactively allows the molten salt system to bear the majority of the power surge, thereby stabilizing the operating state of the coal-fired power unit within a "safe zone." This embodies the coordination principle of "letting the right equipment do the right thing," greatly improving the safety margin and long-term operational reliability of critical main equipment.

[0042] By integrating the three originally conflicting objectives of tracking power grid commands, reducing operating costs, and suppressing lifespan loss into a unified multi-objective optimization framework for coordinated solution, the system's operation is ensured to find a dynamic optimal balance among the three, ultimately achieving comprehensive optimization in terms of safety, economy, and efficiency.

[0043] It is understood that the above embodiments are merely exemplary embodiments used to illustrate the principles of this disclosure, and this disclosure is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and substance of this disclosure, and these modifications and improvements are also considered to be within the scope of protection of this disclosure.

Claims

1. A coordinated control system for peak-shaving lifespan loss in a molten salt-coal-electricity coupling system, characterized in that, The system includes: A coal-fired power generation unit includes a boiler, a steam turbine, and a generator; The molten salt thermal energy storage unit includes a molten salt storage tank, a molten salt heater, a molten salt-feedwater heat exchanger, and related piping and valves; The coupling interface is used for the molten salt heater to extract heat from the steam system or flue gas system of the boiler to heat and store molten salt, and for the molten salt-feed water heat exchanger to use the stored molten salt heat to heat the boiler feedwater or generate auxiliary steam. The system coordination controller has its signal input terminal connected to the power grid dispatch center to receive power grid peak-shaving commands, and its signal output terminals connected to both the coal-fired power generation unit and the molten salt thermal storage unit; wherein... The system coordination controller has a built-in state prediction and lifetime management module, which is configured to execute a lifetime loss coordination control algorithm based on state prediction.

2. The molten salt-coal-electricity coupling system peak-shaving lifespan loss coordinated control system according to claim 1, characterized in that, The state prediction and lifetime management module includes: The load forecasting submodule is used to predict the power grid peak-shaving demand curve within a future time window based on historical data and real-time power grid information. The equipment status prediction submodule is used to predict the temperature and stress field distribution of key components within a future time window based on real-time operating data of the coal-fired power generation unit and the molten salt thermal storage unit, through a pre-established thermodynamic-stress model. The life loss calculation submodule is used to calculate the cumulative life loss of critical components based on the predicted stress field distribution.

3. The molten salt-coal-electricity coupling system peak-shaving lifespan loss coordinated control system according to claim 2, characterized in that, The key components include one or more of the following: boiler drum, high-temperature superheater, turbine rotor, and main steam pipe.

4. The molten salt-coal-electricity coupling system peak-shaving lifespan loss coordinated control system according to claim 2, characterized in that, The lifetime loss calculation submodule is used to calculate the low-cycle fatigue lifetime loss fraction according to the Manson-Coffin equation.

5. A method for coordinated control of peak-shaving lifetime loss in a molten salt-coal-power coupled system, based on the coordinated control system for peak-shaving lifetime loss in a molten salt-coal-power coupled system according to any one of claims 1 to 4, characterized in that, The method includes: Obtain current real-time power grid peak-shaving instructions and power grid peak-shaving demand within future time windows; Obtain real-time operating status parameters of molten salt thermal storage unit and coal-fired power generation unit; Based on the real-time operating status parameters, the future lifespan loss rate of key components is predicted under different control strategies through a preset key component lifespan loss model. The optimal coordinated control strategy is solved by taking the minimum tracking deviation of the total peak shaving command, the minimum system operating cost, and the minimum increase in total lifetime loss as the multi-objective optimization function. According to the optimal coordination control strategy, the output command of the coal-fired power generation unit and the storage / release power command of the molten salt thermal storage unit are dynamically allocated.

6. The method for coordinated control of peak-shaving lifespan loss in a molten salt-coal-electricity coupling system according to claim 5, characterized in that, The critical component life loss model calculates the fatigue life loss fraction for each stress cycle based on the Manson-Coffin equation, as shown in the following formula: In the formula, This represents the fatigue life loss fraction for a single stress cycle. This refers to the number of material failure cycles under stress cycling amplitude and mean temperature. For the total strain range, The fatigue strength coefficient, For Young's modulus, The fatigue strength index. The fatigue ductility coefficient, It is the fatigue ductility index.

7. The method for coordinated control of peak-shaving lifespan loss in a molten salt-coal-electricity coupling system according to claim 5, characterized in that, The multi-objective optimization function is shown in the following equation: In the formula, This represents the total power demand of the power grid. This represents the total output power of the system. To optimize the total coal consumption cost within the cycle, To optimize the total lifespan loss increment of key components within the cycle, , , These are the weighting coefficients.

8. The method for coordinated control of peak-shaving lifespan loss in a molten salt-coal-electricity coupling system according to claim 7, characterized in that, The weighting coefficients are dynamically adjusted based on the urgency of power grid peak shaving and the health status of equipment.

9. The method for coordinated control of peak-shaving lifespan loss in a molten salt-coal-electricity coupling system according to claim 5, characterized in that, The solution for the optimal coordinated control strategy employs a model predictive control framework, specifically including: In each control cycle, the current system state is used as the initial condition; Within the prediction time domain, the multi-objective optimization function is solved in a rolling manner to obtain the optimal operation sequence for the coal-fired power generation unit and the molten salt thermal storage unit; The first element of the operation sequence is sent to each unit as the actual control command at the current moment.

10. The method for coordinated control of peak-shaving lifespan loss in a molten salt-coal-electricity coupling system according to claim 5, characterized in that, The dynamic allocation includes a lifetime protection mode: When the predicted rate of life loss exceeds a preset safety threshold, the system coordination controller prioritizes instructing the molten salt thermal storage unit to handle the power change and limits the load change rate of the coal-fired power generation unit.

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