Method, device and system for controlling output power of thermal power generation system

Abstract

The invention provides a thermal power generation system output power control method, device and system. The method comprises the steps that external environment parameters and / or internal performance parameters of a thermal power generation system are / is acquired; based on the external environment parameters and / or the internal performance parameters, whether the thermal power generation system is in or is about to enter a performance reduction state is judged; when the system is in or is about to enter the performance reduction state, a first type adjusting instruction used for adjusting the flow of a working medium entering the internal refrigeration sub-loop is generated; the flow of the working medium flowing into the internal refrigeration sub-loop is actively increased according to the first type of adjusting instruction, and the working medium flowing to the inlet of the compressor in the main circulation loop is deeply cooled by utilizing the refrigeration effect enhanced by the increased working medium flow, so that the power consumption of the compressor in the main circulation loop is reduced; the reduction of the net output power of the thermal power generation system caused by external environment parameters is compensated, the reliability of output power control of the thermal power generation system is improved, and the control cost is reduced.

Description

Technical Field

[0001] This invention relates to the field of thermal engineering and automation control, and in particular to a method, apparatus and system for controlling the output power of a thermal power generation system. Background Technology

[0002] Thermal cycle power generation technology is the absolute core of the modern society's energy supply system. Its applications are wide-ranging, encompassing traditional fossil fuel power generation such as coal and gas, nuclear power generation, solar thermal power generation, and various technological routes such as the rapidly developing Organic Rankine Cycle (ORC) and supercritical carbon dioxide (sCO2) Brayton cycle. The basic physical principle of all these technologies follows the second law of thermodynamics, which utilizes a working medium (working fluid) to absorb heat from a high-temperature heat source in a closed or open cycle. Through expansion and work done in power machinery such as turbines, thermal energy is efficiently converted into mechanical energy, which ultimately drives a generator to produce electrical energy.

[0003] In the design and operation of all thermodynamic cycle systems (thermal power generation systems), a prevalent and decisive technical bottleneck affecting system performance is its strong dependence on the cold-end conditions of the cycle, typically manifested as sensitivity to ambient temperature. According to fundamental thermodynamic principles, the theoretical maximum efficiency of a thermodynamic cycle, namely the Carnot efficiency (η...), is... Carnot ), determined by the absolute temperature of its heat source (T) hot ) and absolute temperature of the cold source (T) cold The relationship between η and η is jointly determined and expressed as: η Carnot =1-T cold / T hot In actual power generation systems, the temperature of the cooling source is not a parameter that can be freely set. Instead, it depends directly or indirectly on the temperature of the ambient cooling medium at the power plant's location, the dry / wet bulb temperature of the ambient air, or the water temperature of nearby rivers, lakes, or oceans. Therefore, when the seasons change, especially during the hot summer months, the natural rise in ambient temperature, or drought leading to insufficient cooling water supply or increased water temperature, will inevitably cause the temperature of the cooling medium to rise as well.

[0004] An increase in the temperature of the cooling medium will directly lead to a deterioration in the cooling effect of the working fluid in the low-pressure side of the cycle (such as the condenser in a Rankine cycle or the cooler in a Brayton cycle). Specifically, this deterioration manifests as a forced increase in the outlet temperature of the working fluid as it flows out of the cooling equipment. To maintain normal cycle operation, the minimum cycle pressure, i.e., the inlet pressure of the compressor or feedwater pump, must also be increased accordingly to prevent the working fluid from entering an undesirable state. This increase in both the minimum cycle temperature and pressure has a double, catastrophic negative impact on the system's net output power. On the one hand, according to the turbine's working principle, an increase in the cycle back pressure (i.e., the turbine outlet pressure) will significantly reduce the effective enthalpy drop of the working fluid within the turbine, thus directly leading to a reduction in the turbine's output power. On the other hand, an increase in the compressor inlet working fluid temperature means a decrease in working fluid density and an increase in specific volume. According to compressor power consumption theory, the power consumption required to compress one unit mass of working fluid is approximately proportional to its inlet specific volume; therefore, a higher inlet temperature will lead to a sharp increase in the drive power required by the compressor. The combined effect of reduced turbine output power and dramatically increased compressor power consumption leads to a significant, sometimes precipitous, drop in the system's net output power (defined as total turbine output power minus total compressor power consumption and other plant power consumption). This phenomenon is commonly referred to in the power industry as summer output limitation or high-temperature performance degradation, and it has long been a major problem plaguing the global power generation industry.

[0005] For supercritical carbon dioxide (sCO2) cycles, considered a revolutionary next-generation thermodynamic cycle technology, the aforementioned environmental temperature sensitivity issue is particularly prominent and severe. One of the core advantages of the sCO2 cycle, which can potentially surpass the efficiency of the traditional steam Rankine cycle, lies in the fact that its main compression process is designed close to the critical point of carbon dioxide (approximately 31.04°C, 7.38 MPa). In this near-critical region, carbon dioxide, as the working fluid, exhibits extremely high density similar to a liquid, while its isothermal compressibility factor is very small. This unique combination of physical properties significantly reduces the power consumption required to compress a unit mass of sCO2. This low compression work characteristic is key to the high efficiency of the sCO2 cycle. However, this advantage also brings an extremely demanding operational requirement: the control of the main compressor inlet temperature must be extremely precise. In practical engineering design, the optimal operating temperature window of the main compressor is typically strictly controlled between 32°C and 35°C. If insufficient cooling is caused by an increase in ambient temperature, and the inlet temperature of the main compressor deviates from the optimal window by even a few degrees Celsius, the specific volume of the working fluid will increase exponentially, leading to an explosive increase in compression power consumption. Consequently, the cycle efficiency and net output power of the entire system will also deteriorate sharply.

[0006] Currently, the conventional technical means used in the power industry to cope with summer output limitations mainly include the following, but each of them has significant technical or economic drawbacks: The first method is passive derating. This approach involves allowing the power generation system's output to naturally decrease according to thermodynamic laws when ambient temperatures rise, without any additional active intervention. The advantage of this method is its simplicity and lack of additional investment. However, its cost is that power plants may fail to meet expected power generation targets during critical periods. Especially in summer, when electricity demand often reaches its annual peak, a decrease in power generation capacity not only causes significant direct economic losses (reduced electricity sales revenue) but may also pose a serious threat to the stability of the regional power grid and the security of power supply.

[0007] The second method is forced cooling. This method attempts to counteract the effects of ambient temperature by significantly increasing the operating power of the cooling system itself. For air-cooled systems, all fans in the cooling tower operate at full or overspeed; for water-cooled systems, the flow rate of the cooling water circulation pump is increased. The aim is to forcibly increase the heat exchange temperature difference or heat transfer coefficient in order to lower the working fluid temperature to the design point. However, this method consumes a large amount of plant power, the so-called parasitic power. In many practical cases, the extra power consumed for forced cooling may even exceed the increase in power generation recovered by the decrease in working fluid temperature, ultimately leading to a decrease in the system's net output power instead of an increase, resulting in a net loss and extremely poor economic efficiency.

[0008] The third approach is overcapacity design. This strategy involves designing and configuring the cooling system and related auxiliary equipment (such as cooling towers, fans, and pumps) based on the most extreme high-temperature weather conditions in local history (once-in-a-century temperatures) during the initial design and construction phases of the power plant. This means that for most of the year, including spring, autumn, winter, and non-extreme weather periods in summer, the entire massive cooling system is either idle or operating inefficiently, exceeding its capabilities. This approach undoubtedly leads to a huge waste of initial investment (CAPEX), significantly increases the levelized cost of electricity (LCOE) over the project's lifecycle, and reduces the project's overall economic competitiveness.

[0009] The fourth option is an external auxiliary cooling system. This solution involves configuring a completely independent refrigeration unit for the main power generation system, such as a large ammonia compression refrigeration system, a lithium bromide absorption refrigeration system, or a steam jet refrigeration system. When the ambient temperature rises and the main cooling system's capacity is insufficient, this auxiliary refrigeration unit is activated, and the cooling capacity it generates is specifically used for secondary cooling of the low-pressure working fluid in the main cycle. This method is technically effective, but it essentially adds an expensive, complex, and large-scale independent chemical system to the power plant. It also faces a series of problems, including high initial investment, increased operating and maintenance costs, and an increase in overall system complexity and potential failure points.

[0010] To address the above problems, the present invention provides a method, apparatus, and system for controlling the output power of a thermal power generation system, thereby solving at least one of the aforementioned problems. Summary of the Invention

[0011] In order to solve the problems existing in the prior art, this invention innovatively proposes a method, device and system for controlling the output power of a thermal power generation system. It effectively solves the problems of high cost and low reliability of output power control in thermal power generation systems caused by the prior art, effectively improves the reliability of output power control in thermal power generation systems and reduces control costs.

[0012] The first aspect of this invention provides a method for controlling the output power of a thermal power generation system, comprising: Acquire external environmental parameters and / or internal performance parameters of a thermal power generation system; wherein the thermal power generation system includes a main circulation loop and an internal refrigeration sub-loop from which a working fluid can be diverted to generate a cooling effect; Based on external environmental parameters and / or internal performance parameters, determine whether the thermal power generation system is in or about to enter a performance degradation state; when the thermal power generation system is in or about to enter a performance degradation state, generate a first type of regulation command to regulate the flow rate of the working fluid entering the internal refrigeration sub-loop; Based on the first type of regulation command, the flow rate of the working fluid flowing into the internal refrigeration sub-loop is actively increased. The enhanced refrigeration effect due to the increased flow rate is used to deeply cool the working fluid flowing to the compressor inlet in the main circulation loop, thereby reducing the power consumption of the compressor in the main circulation loop to compensate for the decrease in the net output power of the thermal power generation system caused by external environmental parameters.

[0013] A second aspect of the present invention provides a control device for the output power of a thermal power generation system, comprising: The monitoring module acquires external environmental parameters and / or internal performance parameters of the thermal power generation system; wherein the thermal power generation system includes a main circulation loop and an internal refrigeration sub-loop from which working fluid can be diverted to generate a cooling effect; The decision module determines whether the thermal power generation system is in or about to enter a performance degradation state based on external environmental parameters and / or internal performance parameters; when the thermal power generation system is in or about to enter a performance degradation state, it generates a first type of regulation command to adjust the flow rate of the working fluid entering the internal refrigeration sub-loop. The execution module actively increases the flow rate of the working fluid flowing into the internal refrigeration sub-loop according to the first type of adjustment command. By utilizing the enhanced refrigeration effect due to the increased working fluid flow, the working fluid flowing to the compressor inlet in the main circulation loop is deeply cooled, thereby reducing the power consumption of the compressor in the main circulation loop to compensate for the decrease in the net output power of the thermal power generation system caused by external environmental parameters.

[0014] A third aspect of the present invention provides a thermal power generation system, comprising: a main circulation loop, an internal refrigeration sub-loop, and a control device for the output power of the thermal power generation system as described in the second aspect of the present invention, wherein the internal refrigeration sub-loop is used to divert working fluid from the main circulation loop to generate a cooling effect.

[0015] The technical solution adopted in this invention has the following technical effects: 1. The technical solution of this invention acquires external environmental parameters and / or internal performance parameters of a thermal power generation system; determines whether the thermal power generation system is in or about to enter a performance degradation state; when the thermal power generation system is in or about to enter a performance degradation state, generates a first type of regulation command for adjusting the flow rate of the working fluid entering the internal refrigeration sub-loop; actively increases the flow rate of the working fluid flowing into the internal refrigeration sub-loop according to the first type of regulation command, and utilizes the enhanced cooling effect due to the increased flow rate of the working fluid to deeply cool the working fluid flowing to the compressor inlet in the main circulation loop, thereby reducing the power consumption of the compressor in the main circulation loop to compensate for the decrease in the net output power of the thermal power generation system caused by external environmental parameters. This changes the past single passive adaptation, derating operation or violent confrontation, high-consumption cooling mode to a new mode of active utilization and intelligent control; effectively solves the problems of high output power control cost and low reliability of thermal power generation systems caused by existing technologies, effectively improves the reliability of output power control of thermal power generation systems, and reduces control costs.

[0016] 2. In the technical solution of this invention, it is determined whether the current ambient air temperature is greater than a first preset temperature threshold. If the current ambient air temperature is greater than the first preset temperature threshold, it is determined whether the thermal power generation system is in or about to enter a performance degradation state; or, whether the current net output power of the thermal power generation system is less than a preset power threshold. If the current net output power of the thermal power generation system is less than the preset power threshold, it is determined whether the thermal power generation system is in or about to enter a performance degradation state; or, whether the current main compressor inlet temperature is greater than a second preset temperature threshold. If the current main compressor inlet temperature is greater than the second preset temperature threshold, it is determined whether the thermal power generation system is in or about to enter a performance degradation state, thus ensuring the reliability of the output power control of the thermal power generation system.

[0017] 3. In the technical solution of this invention, the current operating stage or the upcoming operating stage of the thermal power generation system is determined based on external environmental parameters and / or internal performance parameters. If the thermal power generation system is in a stable and controllable operating condition, a first regulation control command is generated according to a first regulation control strategy. If the thermal power generation system is in a complex dynamic operating condition, a second regulation control command is generated according to a second regulation control strategy. Based on a comprehensive judgment of the operating condition of the thermal power generation system, intelligent switching is performed between the two control strategies, which can organically combine the two control strategies and achieve an effective balance between control performance and computational resource consumption.

[0018] 4. The technical solution of this invention establishes a system dynamic characteristic prediction model; defines an optimization objective function that includes the expectation of future internal system performance parameters and the penalty for changes in control input; in each control cycle, based on the currently acquired external environmental parameters, internal performance parameters, and system dynamic characteristic prediction model, solves the optimization objective function that satisfies the constraints in the future prediction time domain to obtain the optimal control input sequence; calculates the second regulation control command based on the first element of the optimal control input sequence; it can determine future internal performance parameters based on system external environmental parameters, disturbance parameters, equipment state parameters, etc., enabling the thermal power generation system to cope more easily with various non-design point operating conditions, whether it is predictable seasonal temperature changes, large intraday temperature fluctuations, or sudden, unexpected abnormal situations, such as brief interruptions in cooling water supply or water quality deterioration; it can maintain the relative stability of its key performance indicators within a certain range through the automatic redistribution of internal energy flow, which greatly enhances the robustness of the entire power generation system and enables it to adapt to more variable and harsh external environments.

[0019] 5. The objective function optimized in the technical solution of this invention not only includes the expectation of future internal performance parameters of the system, but also the penalty for changes in control input. The constraints include control input constraints, control input change rate constraints, output variable constraints, safety constraints, etc., which further improves the reliability of output power control of thermal power generation system.

[0020] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the invention. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart illustrating the method in Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of the thermal power generation system in the method of Embodiment 1 of the present invention; Figure 3 This is a flowchart illustrating the dynamic adjustment method based on PID strategy in Embodiment 1 of the present invention. Figure 4 This is a performance comparison curve of the beneficial effects of the method in Embodiment 1 of the present invention. The graph intuitively shows the performance comparison between the system using the method of the present invention and the traditional system in terms of net output power as a function of ambient temperature. Figure 5 This is a flowchart illustrating the dynamic adjustment method based on model predictive control (MPC) in Embodiment 1 of the present invention. Figure 6 This is a schematic diagram of the modular structure in the device of Embodiment 2 of the present invention.

[0023] Figure 2 , Figure 6Legend: 100: Main turbine; 110: Generator; 120: High-temperature regenerator (HTR); 130: Low-temperature regenerator (LTR); 140: Main cooler; 150: Main compressor (MC); 160: Recompressor (RC); 170: Heater (heat source); 180: Diverter valve; 200: Internal refrigeration sub-loop; 210: Refrigeration expander (T2); 220: Refrigeration heat exchanger; 300: Control device; 310: Monitoring module; 320: Decision module; 330: Execution module; 340: Human-machine interaction and data storage module; 401: External ambient temperature sensor (T_amb); 402: Net output power sensor (P_net); 403: Main compressor inlet temperature sensor (T_MC_in). Detailed Implementation

[0024] To clearly illustrate the technical features of this solution, the invention will be described in detail below through specific embodiments and in conjunction with the accompanying drawings. The following disclosure provides many different embodiments or examples for implementing different structures of the invention. To simplify the disclosure of the invention, components and arrangements of specific examples are described below. Furthermore, reference numerals and / or letters may be repeated in different examples. This repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed. It should be noted that the components illustrated in the drawings are not necessarily drawn to scale. Descriptions of well-known components, processing techniques, and processes are omitted in this invention to avoid unnecessarily limiting the invention.

[0025] Example 1 like Figure 1 As shown, the present invention provides a method for controlling the output power of a thermal power generation system, comprising: S1, acquire external environmental parameters and / or internal performance parameters of the thermal power generation system; wherein, the thermal power generation system includes a main circulation loop and an internal refrigeration sub-loop from which working fluid can be diverted to generate a cooling effect; S2, based on external environmental parameters and / or internal performance parameters, determines whether the thermal power generation system is in or about to enter a performance degradation state; when the thermal power generation system is in or about to enter a performance degradation state, it generates a first type of regulation command to regulate the flow rate of the working fluid entering the internal refrigeration sub-loop. S3 actively increases the flow rate of the working fluid flowing into the internal refrigeration sub-loop according to the first type of adjustment command. By utilizing the enhanced refrigeration effect due to the increased working fluid flow rate, the working fluid flowing to the compressor inlet in the main circulation loop is deeply cooled, thereby reducing the power consumption of the compressor in the main circulation loop to compensate for the decrease in the net output power of the thermal power generation system caused by external environmental parameters.

[0026] In step S1, external environmental parameters include ambient air temperature, cooling water inlet temperature, and cooling air inlet temperature; internal performance parameters include the net output power of the thermal power generation system, and the working fluid temperature, working fluid pressure, turbine speed, and cycle efficiency at the compressor inlet in the main circulation loop. Two key parameters can be continuously monitored and acquired at a sufficiently high sampling frequency (once per second or every few hundred milliseconds) through its monitoring interface. The first type of parameter is the external environmental disturbance parameter characterizing the system's operating environment. The most crucial and direct parameter is the ambient temperature, which can be obtained by measuring the dry-bulb temperature of the ambient air or directly measuring the inlet temperature of the cooling water or cooling air before it enters the main cooler. The second type of parameter is the internal performance parameter directly or indirectly characterizing the system's current real-time operating performance. These parameters constitute a comprehensive picture of the system's health status and performance level, including the system's net output power as the final evaluation indicator, the main compressor inlet working fluid temperature as a key control variable, and other important state parameters such as the main compressor inlet working fluid pressure, the speed of the main turbine and compressor, and the cycle thermal efficiency characterizing the overall energy conversion efficiency of the system.

[0027] It should be noted that the thermal power generation system in the technical solution of this invention can be a supercritical carbon dioxide split-expansion Rankine cycle (sCO2-SERC) system, which serves as the ideal physical carrier for the technical solution of this invention. This system ingeniously combines some features of the traditional recompression Brayton cycle and Rankine cycle to form a highly efficient composite cycle system.

[0028] like Figure 2 As shown, the entire thermal power generation system physically consists mainly of a main circulation loop for power generation and a controllable internal refrigeration sub-loop. These two loops achieve close functional coupling through the splitting and merging of the working fluid at specific nodes, together forming an advanced power system capable of actively adapting to environmental changes.

[0029] Specifically, the main circulation loop, as the power core of the thermal power generation system, operates as follows: At state point 1 (e.g., temperature 650°C, pressure 20 MPa), the sCO2 working fluid flows out from heater 170, which serves as the system's heat source. This heat source can be driven by various energy forms such as solar thermal, nuclear reactor, gas turbine exhaust steam, or industrial waste heat. The high-temperature, high-pressure working fluid then enters the main turbine 100 to expand and perform work, driving the coaxially connected generator 110 to output electrical energy. After performing work, the working fluid becomes medium-temperature, medium-pressure exhaust steam (state point 2). To maximize energy recovery, this exhaust steam flows sequentially through the hot-side channels of the high-temperature regenerator 120 (HTR) and the low-temperature regenerator 130 (LTR), transferring residual heat to the working fluid to be heated on the high-pressure side, while being cooled to state point 3.

[0030] At state point 3, the working fluid flow path reaches a critical multi-way splitting node (splitter valve 180). A portion of the working fluid (splitter ratio x) is directly fed into the recompressor 160 for recompression, reaching state point 7. This recompression configuration is typical of advanced sCO2 cycles, designed to reduce the heat exchange temperature difference within the cryogenic regenerator 130, preventing phase change of the working fluid on the low-pressure side, thereby significantly improving regeneration efficiency and overall cycle efficiency. The other portion of the mainstream working fluid (splitter ratio 1-xy) continues to flow towards the cold end of the cycle, entering the main cooler 140. Here, the working fluid exchanges heat with an external cooling medium (such as cooling water or air), discharging waste heat to the environment, and is initially cooled to near ambient temperature at state point 4.

[0031] The operation of the internal refrigeration sub-loop 200 is key to achieving dynamic regulation. The internal refrigeration sub-loop 200 consists of the following components connected in series: the working fluid diverted from the main circulation loop flows sequentially through the refrigeration expander 210 and the refrigeration heat exchanger 220 before merging back into the main circulation loop; deep cooling of the working fluid in the main circulation loop is completed in the refrigeration heat exchanger 220, which cools the working fluid flowing towards the inlet of the main compressor 150 in the main circulation loop.

[0032] A diversion valve 180, precisely controlled by a control device 300, is located after state point 3 and before the main cooler 140 (at the point where the main circulation loop and the internal refrigeration sub-loop diverge). When it is determined that internal refrigeration needs to be activated, the valve 180 opens, diverting a small portion of the working fluid (diversion ratio y, state point 3) from the main flow path (main circulation loop) and introducing it into the internal refrigeration sub-loop. This working fluid first enters the refrigeration expander 210 for quasi-isentropic expansion, causing its pressure and temperature to drop sharply (e.g., from approximately 40°C to 5°C), forming a low-temperature working fluid flow with forced cooling capacity (state point 12). To recover energy, the refrigeration expander 210 can be linked to a micro-generator or compressor; alternatively, a Joule-Thomson throttle valve can be used.

[0033] The low-temperature working fluid carrying a large amount of cooling capacity (state point 12) then flows into the cold-side channel of the refrigeration heat exchanger 220. Simultaneously, a portion of the mainstream working fluid (state point 4) flowing out of the main cooler 140 is guided into the hot-side channel of the refrigeration heat exchanger 220. Inside the refrigeration heat exchanger 220, the two fluids undergo efficient heat exchange. The low-temperature refrigerant absorbs heat from the hot-side mainstream working fluid, thereby achieving a secondary deep cooling of the mainstream working fluid's temperature, reducing it from state point 4 (e.g., 38°C) to a more ideal compressor inlet temperature, state point 9 (e.g., 32°C). After completing the heat exchange, the refrigerant in the sub-loop reaches state point 13, where it merges with the mainstream working fluid (state point 4) that has undergone preliminary cooling by the main cooler, together forming the final working fluid flow entering the main compressor 150.

[0034] In the low-pressure section of the main cycle, the working fluid stream (state point 9), after deep cooling and merging, enters the main compressor 150 and is compressed to an intermediate pressure (state point 10). Subsequently, this working fluid stream mixes with another working fluid stream (state point 7) from the recompressor 160 before the cold-side inlet of the cryogenic regenerator 130, reaching state point 8. The mixed full-flow high-pressure working fluid flows sequentially through the cold side of the cryogenic regenerator 130 and the high-temperature regenerator 120, fully absorbing the waste heat of the turbine exhaust steam, preheating to state point 11, and finally returning to the heater 170, completing the entire closed thermodynamic cycle.

[0035] The core technical solution of this invention operates precisely on this physical architecture. The flow split ratio y is not a fixed value, but a key variable actively adjusted by the control device 300 according to real-time operating conditions. By precisely controlling the opening of the flow split valve 180, the system can freely allocate the flow rate of the working fluid entering the internal refrigeration sub-loop 200. When y increases, the total cooling capacity generated by the refrigeration sub-loop increases accordingly, and the secondary cooling capacity of the working fluid at the main compressor inlet also improves. This gives the system a powerful active thermal management means, enabling it to force the main compressor inlet temperature T to rise when the external ambient temperature increases and the performance of the main cooler 140 decreases, through intelligent internal energy scheduling. MC_in (i.e., the temperature at state point 9) is maintained near the preset optimal target value, thereby ensuring stable and efficient system power output.

[0036] Among them, such as Figure 3 As shown, in step S2, determining whether the thermal power generation system is in or about to enter a performance degradation state based on external environmental parameters and / or internal performance parameters specifically includes: S201, determine the current ambient air temperature (T) obtained. amb If the ambient air temperature (T_amb) is greater than the first preset temperature threshold (threshold 1), and the current ambient air temperature is greater than the first preset temperature threshold, determine whether the thermal power generation system is in or about to enter a performance degradation state; or, S202, the current net output power of the thermal power generation system (P) net If the net output power of the current thermal power generation system is less than the preset power threshold (target value), determine whether the thermal power generation system is in or about to enter a performance degradation state; or, S203, Current main compressor inlet temperature (T) MC_in If the current main compressor inlet temperature is greater than the second preset temperature threshold (threshold 3), determine whether the thermal power generation system is in or about to enter a performance degradation state.

[0037] Specifically, the acquisition of external environmental parameters and / or internal performance parameters is typically achieved through a multi-channel analog / digital input / output (I / O) module, physically connected to various sensors and transmitters distributed throughout the power generation system via standard industrial signal lines (such as 4-20mA current loops, HART protocol, or Profibus-DP fieldbus). In this embodiment, the external ambient temperature sensor 401 (T) acquires the external ambient temperature. amb The sensor can be installed at the cooling medium inlet of the main cooler 140; the net output power sensor 402 (P) acquires the net output power of the hot-spot power generation system. net This value is typically derived in real time by a calculation module, which subtracts all plant power consumption (mainly including the power consumption of the main compressor 150, re-compressor 160, and cooling system fans / pumps) from the output power of the generator 110; and obtains the main compressor inlet temperature sensor 403 (T) to acquire the main compressor inlet temperature in the main circulation loop. MC_in The temperature sensor is precisely installed Figure 2 The pipeline position at state point 9. Furthermore, to achieve more precise control and comprehensive monitoring, it is also possible to collect data such as the main compressor inlet pressure, turbine speed, pressure and temperature at key points in the system, and valve position feedback signals from the diverter valve 180.

[0038] Furthermore, in step S2, when the thermal power generation system is in or about to enter a performance degradation state, the generation of regulation commands for adjusting the flow rate of the working fluid entering the internal refrigeration sub-loop specifically includes: S211, Based on external environmental parameters and / or internal performance parameters, determine the current operating stage or the upcoming operating stage of the thermal power generation system; S212, if the thermal power generation system is in a stable and controllable operating condition, a first regulation control command is generated according to the first regulation control strategy, wherein the first regulation control strategy is a PID strategy, and the first regulation control command is the first target opening degree of the diversion valve set between the main circulation loop and the internal refrigeration sub-loop; the thermal power generation system is in a stable and controllable operating condition specifically as follows: the load change rate is less than a preset change rate threshold; and the external environmental parameters are respectively less than the corresponding preset environmental parameter thresholds; and the distance between the current operating point and the constraint boundary is less than a preset distance threshold. Specifically, based on a comprehensive assessment of the system's overall state, intelligent switching is performed between two control modes: Mode 1: Basic adjustment mode (corresponding to PID control strategy); Mode 2: Advanced Predictive Optimization Mode (corresponding to MPC control strategy); The dimensions of analysis mainly include: (1) System operation phase: Distinguish whether the system is in a steady-state operation phase with stable load (load change rate is less than the preset change rate threshold) or a dynamic transition phase with rapid load change (load change rate is greater than the preset change rate threshold) (such as start-up, shutdown, and response to grid dispatch).

[0039] (2) External disturbance characteristics: taking into account the ambient temperature T amb The current value and rate of change dT amb / dt (whether the external environmental parameters are less than the corresponding preset environmental parameter thresholds), and can even integrate weather forecast data to obtain future disturbance trends.

[0040] (3) System operating boundary margin: Real-time calculation of the distance between the current operating point and multiple key safety or performance constraints (such as the upper limit of turbine inlet temperature, the temperature difference of the regenerator, etc.).

[0041] Based on the above analysis, the built-in switching logic follows these principles: Conditions for activating the basic control mode (PID): When the system is determined to be in a stable and controllable operating condition, the controller will adopt the PID strategy. In this mode, the main task is to suppress small disturbances near a stable operating point. The PID controller, with its low computational cost and high robustness, is the most efficient choice. The conditions for determining that the system is in a stable and controllable operating condition are: the load change rate is less than a preset change rate threshold; the external environmental parameters are respectively less than their corresponding preset environmental parameter thresholds; and the distance between the current operating point and the constraint boundary is less than a preset distance threshold.

[0042] S213, if the thermal power generation system is in a complex dynamic operating condition, a second regulation control command is generated according to the second regulation control strategy, wherein the second regulation control strategy is the MPC strategy, and the second regulation control command is the second target opening degree of the diversion valve set between the main circulation loop and the internal refrigeration sub-loop; the thermal power generation system is in a stable and controllable operating condition specifically when: the load change rate is greater than the preset change rate threshold; or, the external environmental parameters are greater than the corresponding preset environmental parameter thresholds; or, the distance between the current operating point and the constraint boundary is greater than the preset distance threshold.

[0043] Conditions for activating Advanced Predictive Optimization Mode (MPC control strategy): When the system is determined to have entered a complex dynamic operating condition, it will seamlessly switch to the MPC strategy. In this mode, the system needs to proactively handle significant changes and optimize trade-offs among multiple conflicting objectives and constraints. MPC's model-based prediction and online optimization capabilities make it an essential choice to ensure a safe, smooth, and efficient transition for the system. The conditions for determining that the system has entered a complex dynamic operating condition are: the load change rate is greater than a preset change rate threshold; or, the external environmental parameters are greater than their corresponding preset environmental parameter thresholds; or, the distance between the current operating point and the constraint boundary is greater than a preset distance threshold.

[0044] In this way, the present invention organically combines the two control strategies to form an intelligent control system that can adapt to different times and places, achieving the best balance between control performance and computational resource consumption (PID consumes less computational resources, while MPC consumes more).

[0045] Specifically, such as Figure 3 As shown, generating the first regulation control command according to the first regulation control strategy specifically includes: Using the inlet temperature of the main compressor in the main circulation loop as the controlled variable and the optimal operating temperature of the main compressor in the main circulation loop as the setpoint, the calculation method for the first target opening degree is as follows: ; in, Let t be the first target opening of the diversion valve set between the main circulation loop and the internal refrigeration sub-loop at time t, e(t) be the error between the set value and the controlled variable, Kp be the proportional coefficient in the PID parameters, Ki be the integral coefficient in the PID parameters, and Kd be the derivative coefficient in the PID parameters.

[0046] During each control cycle, a composite decision logic is executed once, which organically combines the predictive nature of feedforward control with the corrective nature of feedback control.

[0047] First, a feedforward judgment is performed, which is a predictive intervention mechanism. This involves determining the currently acquired ambient temperature T. amb Is it greater than a first preset temperature threshold T? threshold_1 (Threshold 1). This threshold, which can be called the ambient temperature warning threshold, can be set to 28°C based on historical climate data and system simulation analysis of the power plant location. When T amb >T threshold_1 When the conditions are met, the system can predict that the heat dissipation capacity of the main cooler 140 is about to decrease or has already begun to decrease significantly, which is very likely to lead to a subsequent decrease in the main compressor inlet temperature T. MC_in The net output power P of the heating and thermal power generation system net The rate of decrease is therefore determined by setting an intervention trigger flag (Trigger_Flag) to 1 in advance.

[0048] Secondly, feedback judgments are performed in parallel, which is a responsive correction mechanism. Current net output power P net Is it less than its target value P? target Multiply by an allowable deviation coefficient (P) net <P target *(1 ),in, It can be set to 3%; that is, the preset power threshold is P.target *(1 Main compressor inlet temperature T MC_in Is it greater than its optimal setpoint T? setpoint Add a safety margin (T) MC_in >T setpoint +ΔT margin T setpoint It can be set to 32°C, ΔT margin It can be set to 1.5°C, that is, the second preset temperature threshold is T. setpoint +ΔT margin When the net output power P of the thermal power generation system net An unacceptable drop has begun, or the critical ambient air temperature T... MC_in When the performance starts to rise uncontrollably, the system confirms that performance degradation is happening or has already happened through real-time performance feedback, and also sets the intervention trigger flag Trigger_Flag to 1.

[0049] When Trigger_Flag is 1, the adjustment amount is calculated. A PID control algorithm is initiated to calculate the necessary adjustment to the split ratio y. In this embodiment, a classic proportional-integral-derivative (PID) controller is used. A controller is constructed based on the main compressor inlet temperature T. MC_in The controlled variable (PV) is at its optimal operating temperature T. setpoint A single-loop PID controller with a setpoint (SP). First, calculate the current error e(t) = T. setpoint T MC_in(t) Then, according to the PID algorithm formula... ; Calculate the first target opening of the flow divider valve 180. Position (t). Where Kp, Ki, and Kd are PID parameters that need to be tuned according to the dynamic characteristics of the system. Kp is the proportional coefficient in the PID parameters, Ki is the integral coefficient in the PID parameters, and Kd is the derivative coefficient in the PID parameters.

[0050] Then, based on the first target opening degree of the diverter valve 180, Valve Position (t) Perform precise adjustment. The calculated new valve position setpoint Valve Position (t) is sent to the execution module 330. The execution module 330 then adjusts the 4-20mA current signal it outputs to the actuator of the diversion valve 180, driving the valve to move to a new first target opening, thereby achieving precise adjustment of the diversion ratio y.

[0051] Preferably, cyclic and adaptive adjustment can also be performed. After entering the next control cycle, in subsequent operation, if the ambient temperature T... amb The decrease caused T amb <T threshold_1 And the system's P net and T MC_in Once all parameters return to normal, Trigger_Flag will automatically become 0. At this point, the PID controller may gradually reduce the opening of the diversion valve 180 according to the change in error (generating a second type of regulation command to reduce the flow rate of the working fluid entering the internal refrigeration sub-loop), reduce the diversion ratio y, or even completely close it (y=0) when the cooling conditions are excellent, in order to avoid unnecessary energy diversion and thus maximize the power generation efficiency of the system under favorable operating conditions.

[0052] like Figure 4 As shown, the performance comparison curves visually demonstrate the significant beneficial effects of the method described in this embodiment. Curve A represents a conventional sCO2 recompression cycle system that does not employ the control strategy of this invention. It can be seen that in low ambient temperature regions (e.g., T...),... amb At temperatures below 25°C, thermal power generation systems operate at or near their design point, enabling them to output maximum net power. However, as the ambient temperature T... amb The continuous increase in temperature caused a sharp drop in the performance of the main cooler, resulting in T... MC_in The temperature is forced to rise accordingly. Due to the drastic changes in the properties of sCO2 near the critical region, T... MC_in The increase in power consumption leads to an exponential increase in the main compressor's power consumption, ultimately reducing the system's net output power P. net A precipitous drop occurs. In contrast, curve B represents the sCO2-SERC system employing the method and apparatus described in this embodiment. In the low-temperature region, the diversion valve 180 remains closed (y=0), and its performance is completely consistent with the conventional system. When T amb As the temperature rises and exceeds a preset trigger point (e.g., 28°C), the present invention gradually increases the split ratio y based on the output of a PID algorithm or MPC control strategy. Although diverting a portion of the working fluid for cooling results in a small loss of turbine power, this active internal cooling effect significantly improves T... MC_in The system is forced to maintain, precisely, at or very close to its optimal setpoint (e.g., 32°C). The resulting significant savings in main compressor power consumption far outweigh the energy losses caused by the non-ideal efficiency of the splitter and refrigeration expander. Therefore, the net output power P of the thermal power generation system... net In high-temperature regions, it can maintain a very high level, and its curve as a function of ambient temperature becomes exceptionally flat. The area of ​​the shaded region between the two curves in the figure intuitively represents the huge power generation gain that this invention can bring during the high-temperature season.

[0053] On the other hand, the MPC strategy is an advanced process control technique in modern control theory. It uses an explicit dynamic process model to predict the behavior of the system over a period of time in the future and determines the optimal control input at the current moment by repeatedly solving a constrained optimization problem online.

[0054] like Figure 5 As shown, this illustrates the core workflow of the MPC control algorithm within a control cycle.

[0055] The first step, S501, is to perform system modeling (establish a predictive model of the system's dynamic characteristics). The cornerstone of the MPC control strategy is having a mathematical model capable of accurately predicting the system's dynamic behavior. This model needs to describe the system's key input-output relationships. For the sCO2-SERC system of this invention, a discrete-time state-space model can be established, with the following standard form: x(k+1)=A x(k)+B u(k)+E d(k) y out (k)=C x(k) Where k represents the current discrete control moment. x(k) is the thermodynamic state vector of the internal equipment of the thermal power generation system, which contains a set of key variables that can describe the internal thermodynamic state of the system. x(k) can be defined as including the metal wall temperature of each key device (such as HTR 120, LTR 130, and refrigeration heat exchanger 220), and the working fluid temperature and pressure at each key node (such as the compressor / turbine inlet and outlet). u(k) is the control input vector of the flow divider valve opening. In this invention, the most crucial control input is the flow divider ratio. d(k) is the disturbance vector of the measurable external environmental parameters. The most important disturbance is the external environmental temperature, i.e., d = [T amb ]. y out (k) is the output vector of the system's internal performance parameters, which contains the performance indicators that we are interested in and need to control or optimize, y out = [P net , T MC_inA represents the state input matrix describing the dynamic characteristics of the system; B represents the control input matrix describing the dynamic characteristics of the system; E represents the disturbance input matrix describing the dynamic characteristics of the system; and C represents the state output matrix describing the dynamic characteristics of the system. These matrices can be obtained through two main approaches: one is based on first-principles mechanistic modeling, which involves establishing detailed nonlinear differential equations for each component (heat exchanger, compressor, turbine, pipe, etc.) in the system based on the fundamental physical laws of thermodynamics, fluid mechanics, and heat transfer, and then linearizing and discretizing them around one or more typical operating points to obtain these matrices. The other approach is based on data-driven system identification, which involves applying a series of carefully designed input signals (step signals or pseudo-random binary sequence PRBS signals) with sufficient excitation frequencies to the control input u and the disturbance T on a high-fidelity system simulation platform (based on Modelica's Dymola or Aspen HYSYSDynamics) or on actual physical devices. amb Simultaneously record the system output y out The response data is then used to directly fit the matrix of the state-space model from these input-output data using identification algorithms such as N4SID and ARMA.

[0056] The second step, S502, is online optimization. At each control time k (every 30 seconds), the MPC controller (executing the MPC control strategy) performs a complex online optimization calculation in the decision module 320. This process can be further subdivided into several sub-steps. First, state estimation and disturbance measurement are performed. The actual system output y at the current time is obtained through measurement. out (k) and disturbance d(k). Since not all variables in the state vector x(k) can be directly measured, MPC usually combines a state observer, such as a Kalman filter, to provide an optimal estimate of the internal state x(k) of the current system using the known model, past control inputs, and current measurement outputs.

[0057] Secondly, the optimization problem is defined and constructed. The core of MPC is to solve a dynamic optimization problem within a finite time window in the future (called the prediction time domain Np). Its goal is to find a future control input sequence U = [u(k), u(k+1)... u(k+Nc-1)] (where Nc is the control time domain, usually less than or equal to Np) such that a predefined objective function (or cost function) J is minimized.

[0058] The predictive time domain Np refers to the total time length during which the MPC controller, using its internal model, predicts the future dynamic behavior of the system within each control cycle. Its main function is to ensure the stability and foresight of the control. A sufficiently long Np allows the controller to see the full impact of its current actions on the future state of the system, especially for systems with significant delays or non-minimum phase characteristics. In the control time domain, Nc refers to the number of independent future control actions that the MPC controller actually calculates and optimizes in each control cycle. Its main function is to balance control flexibility with computational complexity. Nc is the number of variables to be solved in the optimization problem, directly determining the computational cost of online optimization.

[0059] In this embodiment, the optimization objective function J can be designed as follows:

[0060] This objective function clearly expresses the desired control outcome. The first term is the performance tracking term, where y out_ref It is a target sequence of internal performance parameters set for the future prediction time domain (desired net power P). net Maintain at the rated value, T MC_in (Maintain at 32°C) out_pred This term uses a state-space model (system dynamics prediction model) to predict the system output sequence starting from the current state x(k) under the influence of a future control sequence u and a predicted disturbance sequence d (which can be provided by weather forecasts). The aim is to make the system's future actual performance as close as possible to the desired target. Q is a positive definite expectation weight matrix; by adjusting the size of its diagonal elements, the weights can be set for different output targets (such as P). net and T MC_in The tracking priority is determined by the input. The second term is the control cost term, where Δu is the change in the control input (i.e., u(k+i)). u(k+i-1)). This term aims to penalize overly drastic or frequent control actions to ensure smooth system operation and reduce excessive wear on the actuator (diverter valve 180). R is the control input penalty weight matrix, the magnitude of which reflects our requirements for the smoothness of control actions.

[0061] By adjusting the size of the diagonal elements in the Q matrix, you can specify which output variable's tracking accuracy you are more concerned with. For example, if you are more concerned with the net output power P... netIf the system is stable, a larger weight can be assigned to the corresponding Pnet. R is a positive definite weight matrix. The larger the value of R, the heavier the penalty for changes in control action. The controller will tend to produce smoother, less variable control outputs to avoid frequent and violent actions of actuators (such as flow dividers) and protect physical equipment. Then, various system constraints must be considered. The optimization process must be carried out under the constraints of satisfying the physical and operational safety boundaries of the system. These constraints are explicitly added to the optimization problem. Control input constraints: u min ≤ u(k+i) ≤ u max (For example, the range of the split ratio y is limited to 0 ≤ y ≤ 0.15); Constraint on the rate of change of control input: Δu min ≤ Δu(k+i) ≤ Δu max (Limiting the operating speed of the diverter valve); Output variable constraint: y out_min ≤ y out_pred (k+i) ≤ y out_max (Hard constraint T) MC_in The temperature must always be higher than the pseudocritical temperature at the corresponding pressure plus a safety margin to absolutely prevent the working fluid from entering the unstable two-phase region. Other safety constraints, such as turbine speed limits and compressor surge margins, can also be modeled and added to the constraint set. Finally, the optimization problem is solved. The optimization problems involving quadratic objective functions and linear constraints are combined into a standard quadratic programming problem. A real-time optimization solver (such as Gurobi) quickly solves this QP problem within each control cycle to obtain the optimal future control sequence U. = [u(k), u(k+1)...].

[0062] The third step, S503, is rolling time-domain execution. A key characteristic of the MPC algorithm is that it does not execute the entire calculated optimal control sequence U. It takes only the first element u(k) in the sequence and uses it as the final control element at the current time k. That is, it determines the second target opening of the diversion valve 180 according to the optimal control input element (diversion ratio) and uses the second target opening of the diversion valve 180 as the second regulation control command.

[0063] The fourth step, namely step S504, is to send the second adjustment control command to the corresponding execution module to drive the diversion valve 180 to operate.

[0064] The fifth step, S505, returns to step S502 when the next control time k+1 arrives, repeating the entire process. The MPC controller remeasures the latest state of the system and, based on this state which includes the latest feedback information, solves a completely new optimization problem starting from time k+1. This strategy of continuously rolling the optimization window forward is called rolling time-domain control. It allows the MPC to continuously use the latest feedback information to correct its control strategy, thus exhibiting strong robustness to disturbances not anticipated in the model and mismatches inherent in the model itself.

[0065] Compared to the simple threshold and PID-based control method in Example 1, the MPC strategy employed in this example has unparalleled theoretical advantages. Its forward-looking nature allows it to anticipate the impact of future disturbances (based on the Tamb variation curves provided by weather forecasts for the next few hours) and take optimal, smooth countermeasures in advance, rather than reacting after performance has already degraded. Its multivariate coordination capability enables it to simultaneously handle multiple interrelated inputs and outputs and find the optimal balance point among potential conflicts (the trade-off between maximizing power generation and minimizing valve actuation). Its ability to explicitly handle constraints fundamentally ensures that the system always operates within preset safety boundaries, greatly improving operational safety. Ultimately, provided the model is accurate, MPC can find the control action that optimizes the overall performance of the system over a future period at every moment, rather than simply correcting current errors, thereby achieving a higher level of autonomous operation and global performance optimization, further amplifying the technical advantages and economic benefits of this invention.

[0066] In step S3, when the opening of the diversion valve 180 increases and the diversion ratio y increases, more high-pressure sCO2 working fluid is introduced into the internal refrigeration sub-loop. This diverted working fluid first undergoes depressurization and expansion through a refrigeration expander 210. During this process, the temperature of the working fluid drops sharply due to the Joule-Thomson effect or by performing work, thus generating a strong refrigeration effect. The low-temperature working fluid carrying a large amount of cooling energy then flows into a specially designed refrigeration heat exchanger 220, flowing on the cold side of the refrigeration heat exchanger 220. At the same time, in the main circulation loop, the mainstream working fluid, which has been initially cooled by the main cooler 140 but is still at a relatively high temperature, is guided to flow through the hot side of the refrigeration heat exchanger 220 before entering the main compressor. Inside the refrigeration heat exchanger 220, the low-temperature working fluid from the refrigeration sub-loop performs secondary deep cooling on the mainstream working fluid, effectively absorbing its heat.

[0067] The macroscopic effect of this proactively initiated internal cooling process is as follows: Although the external main cooler 140 experiences performance degradation due to the high-temperature environment, and its outlet working fluid temperature may be far higher than the design value, after secondary deep cooling by the refrigeration heat exchanger 220, the working fluid temperature entering the main compressor 150 is forcibly pulled back to or very close to its optimal operating temperature. This significant reduction in working fluid temperature leads to a substantial increase in density and a sharp decrease in specific volume. According to the basic thermodynamic principles of compressor power consumption (ideal gas compression work is proportional to inlet temperature, while real fluid compression work is strongly correlated with inlet specific volume), this will non-linearly reduce the drive power consumption required by the main compressor. The compressor power consumption saved by this proactive intervention can effectively compensate for, and even under optimized design, exceed, the turbine work loss caused by increased ambient temperature, and the small cost incurred in driving the refrigeration sub-loop itself (i.e., the diverted working fluid not performing work on the main turbine and the potential non-ideal efficiency of the refrigeration expander). Therefore, the ultimate macroscopic result for the system as a whole is that, under hot summer or poor cooling conditions, the net output power of the entire system can be maintained at a level much higher than that of traditional uncontrolled systems, thus effectively suppressing and compensating for the problem of power output limitation in summer.

[0068] Compared with existing technologies, the method disclosed in this invention, through its innovative control concept and specific technical implementation path, can bring one or more of the following significant and practically valuable benefits: First, this invention proposes a control method for the output power of a thermal power generation system. It successfully transforms an internal refrigeration sub-loop within the system from a traditional, single-function secondary module into a key dynamic regulator that resists external environmental disturbances and ensures the stability of the core main function (power generation). Whether employing a relatively simple and easily implemented threshold and PID-based control strategy or a more complex and superior model-predictive MPC control strategy, both methods significantly improve the performance of thermal power generation systems, especially SO2 power generation systems, under high-temperature conditions. This effectively increases the annual power generation and economic benefits, and enhances the system's adaptability and operational robustness to varying environments. This invention provides a novel, economical, efficient, and widely applicable innovative solution to the long-standing technical challenge of summer output limitations in the global power industry.

[0069] Secondly, this invention significantly improves the power generation performance of the system under high-temperature conditions, which is its most direct and core value. Under conditions where the external ambient temperature rises and the performance of traditional systems declines sharply, the control strategy of this invention can actively intervene and effectively suppress the precipitous drop in net output power. Extensive system simulation analysis and preliminary experimental data show that, compared to a baseline system without any active control measures, the method of this invention can significantly reduce the attenuation of the system's net output power from the conventional 20% to 30% or more under typical summer design conditions (ambient temperature rising from the design baseline of 15°C to 35°C) to less than 5%, and even approach zero attenuation in some finely optimized system designs. This means that during the peak summer electricity demand period, when societal electricity needs are most urgent, power plants using this invention can generate 15% to 25% or even more electricity than traditional power plants, creating significant economic value.

[0070] Third, this invention can significantly improve the economic benefits of a project throughout its entire life cycle. By significantly increasing power generation during the high-temperature season, this invention directly increases the power plant's total annual power generation and corresponding electricity sales revenue. Simultaneously, because this invention provides an efficient peak-shaving method, it eliminates the need for a conservative strategy of excess margin design in configuring the cooling system during the power plant design phase, thereby effectively reducing the initial construction investment of the power plant. Furthermore, compared to forced cooling schemes, the energy utilization method of this invention is more refined and efficient, avoiding a large amount of unnecessary plant power consumption. In summary, higher revenue, lower initial investment, and lower operating costs work together to significantly reduce the levelized cost of electricity (LCOE) of the project, thereby greatly improving the project's return on investment and market competitiveness.

[0071] Fourth, this invention significantly enhances the system's operational robustness and environmental adaptability. The dynamic closed-loop and feedforward control strategy of this invention enables the power generation system to more readily cope with various off-design point operating conditions, including predictable seasonal temperature changes, large intraday temperature fluctuations, and sudden, unexpected anomalies such as brief interruptions in cooling water supply or water quality deterioration. The system can maintain the relative stability of its key performance indicators within a certain range through the automatic redistribution of internal energy flow, which greatly enhances the robustness of the entire power generation system, enabling it to adapt to more variable and harsh external environments.

[0072] Fifth, this invention achieves synergy between internal system functions and a multiplier effect on overall value. The power generation-cooling combined cycle system upon which this invention is based inherently possesses the potential value of dual-purpose functionality. Furthermore, the control method of this invention further delves into the inherent synergistic potential between power generation and cooling functions, achieving system-level efficiency gains greater than the sum of its parts (1+1>2) through flexible control strategies. In scenarios where there is an external demand for cooling, the system can output cooling normally; while in scenarios where there is no external demand for cooling but stable power generation is required, the cooling capacity of the cooling circuit is creatively internalized, serving to ensure the stability of the primary power generation function. This flexible, real-time demand-based energy management strategy greatly enhances the overall value of the system and the breadth of its application scenarios.

[0073] Sixth, the core control concept of this invention has good technical versatility and scalability. Although the supercritical carbon dioxide split-expansion Rankine cycle (sCO2-SERC) is described in detail as the best physical carrier in the specific embodiments of this invention, its core control concept—that is, using the cooling capacity generated by the internally integrated refrigeration sub-loop to compensate for the performance degradation of the main cycle due to high temperature—has considerable universality. This concept can be borrowed, transplanted, and applied to any other thermodynamic system or chemical process with a similar main functional loop + controllable internal refrigeration sub-loop topology, certain specially designed organic Rankine cycle (ORC) systems, or other energy conversion systems that require precise control of the inlet temperature of critical equipment, thus forming a widely applicable superposition protection system.

[0074] In summary, the technical solution of this invention acquires external environmental parameters and / or internal performance parameters of a thermal power generation system; determines whether the thermal power generation system is in or about to enter a performance degradation state; when the thermal power generation system is in or about to enter a performance degradation state, it generates a first type of regulation command to adjust the flow rate of the working fluid entering the internal refrigeration sub-loop; based on the first type of regulation command, it actively increases the flow rate of the working fluid flowing into the internal refrigeration sub-loop, and utilizes the enhanced cooling effect due to the increased flow rate to deeply cool the working fluid flowing to the compressor inlet in the main circulation loop, thereby reducing the power consumption of the compressor in the main circulation loop to compensate for the decrease in the net output power of the thermal power generation system caused by external environmental parameters. This changes the past single passive adaptation, derating operation or violent confrontation, high-consumption cooling mode to a new mode of active utilization and intelligent control; effectively solves the problems of high output power control cost and low reliability of thermal power generation systems caused by existing technologies, effectively improves the reliability of output power control of thermal power generation systems, and reduces control costs.

[0075] In this invention, the system determines whether the current ambient air temperature is greater than a first preset temperature threshold. If the current ambient air temperature is greater than the first preset temperature threshold, it determines whether the thermal power generation system is in or about to enter a performance degradation state. Alternatively, it determines whether the current net output power of the thermal power generation system is less than a preset power threshold. If the current net output power of the thermal power generation system is less than the preset power threshold, it determines whether the thermal power generation system is in or about to enter a performance degradation state. Or, it determines whether the current main compressor inlet temperature is greater than a second preset temperature threshold. If the current main compressor inlet temperature is greater than the second preset temperature threshold, it determines whether the thermal power generation system is in or about to enter a performance degradation state, thus ensuring the reliability of the thermal power generation system's output power control.

[0076] The technical solution of this invention determines the current operating stage or the upcoming operating stage of the thermal power generation system based on external environmental parameters and / or internal performance parameters. If the thermal power generation system is in a stable and controllable operating condition, a first regulation control command is generated according to a first regulation control strategy. If the thermal power generation system is in a complex dynamic operating condition, a second regulation control command is generated according to a second regulation control strategy. Based on a comprehensive judgment of the operating condition of the thermal power generation system, intelligent switching is performed between the two control strategies, which can organically combine the two control strategies and achieve an effective balance between control performance and computational resource consumption.

[0077] The technical solution of this invention establishes a system dynamic characteristic prediction model; defines an optimization objective function that includes the expectation of future internal system performance parameters and the penalty for changes in control input; in each control cycle, based on the currently acquired external environmental parameters, internal performance parameters, and system dynamic characteristic prediction model, solves the optimization objective function that satisfies the constraints in the future prediction time domain to obtain the optimal control input sequence; calculates the second regulation control command based on the first element of the optimal control input sequence; it can determine future internal performance parameters based on system external environmental parameters, disturbance parameters, equipment state parameters, etc., enabling the thermal power generation system to cope more easily with various non-design point operating conditions, whether it is predictable seasonal temperature changes, large intraday temperature fluctuations, or sudden, unexpected abnormal situations, such as brief interruptions in cooling water supply or water quality deterioration; it can maintain the relative stability of its key performance indicators within a certain range through the automatic redistribution of internal energy flow, which greatly enhances the robustness of the entire power generation system and enables it to adapt to more variable and harsh external environments.

[0078] The objective function optimized in this invention not only includes the expectation of future internal performance parameters of the system, but also the penalty for changes in control input. The constraints include control input constraints, control input change rate constraints, output variable constraints, and safety constraints, which further improves the reliability of output power control in thermal power generation systems.

[0079] Example 2 like Figure 6 As shown, the present invention also provides a control device for the output power of a thermal power generation system, comprising: The monitoring module 310 acquires external environmental parameters and / or internal performance parameters of the thermal power generation system; wherein the thermal power generation system includes a thermal cycle system, the thermal cycle system includes a main cycle loop and an internal refrigeration sub-loop from which working fluid can be diverted to generate a cooling effect; Decision module 320 determines whether the thermal power generation system is in or about to enter a performance degradation state based on external environmental parameters and / or internal performance parameters; when the thermal power generation system is in or about to enter a performance degradation state, it generates a first type of regulation command to regulate the flow rate of the working fluid entering the internal refrigeration sub-loop. The execution module 330 actively increases the flow rate of the working fluid flowing into the internal refrigeration sub-loop according to the first type of adjustment command. By utilizing the enhanced refrigeration effect due to the increased working fluid flow rate, the working fluid flowing to the compressor inlet in the main circulation loop is deeply cooled, thereby reducing the power consumption of the compressor in the main circulation loop to compensate for the decrease in the net output power of the thermal power generation system caused by external environmental parameters.

[0080] In engineering practice, this control device can be an industrial-grade programmable logic controller (PLC), such as the Siemens S7-1500 series, or a controller module within a distributed control system (DCS), such as Rockwell Automation's ControlLogix. Its main components include: The monitoring module 310 functions as a sensor for the control device. It is typically a multi-channel analog / digital input / output (I / O) module, physically connected to various sensors and transmitters throughout the power generation system via standard industrial signal lines (such as 4-20mA current loops, HART protocol, or Profibus-DP fieldbus). In this embodiment, the module needs to connect to and acquire at least the following key parameters: an ambient temperature sensor 401 (Tamb), which can be installed at the cooling medium inlet of the main cooler 140; a net output power sensor 402 (Pnet), which is typically calculated in real-time by a calculation module, i.e., subtracting all plant power consumption (mainly including the power consumption of the main compressor 150, re-compressor 160, and cooling system fans / pumps) from the generator 110's output power; and a main compressor inlet temperature sensor 403 (TMC_in), which is precisely installed... Figure 1The pipeline position at state point 9. Furthermore, to achieve more precise control and comprehensive monitoring, the monitoring module 310 can also collect data such as the main compressor inlet pressure, turbine speed, pressure and temperature at key points in the system, and valve position feedback signals from the diverter valve 180.

[0081] The decision module 320 functions as the brain of the control device. It is typically the central processing unit (CPU) module in the controller, responsible for running the core control algorithm of this invention. It acquires real-time data from the monitoring module 310 at extremely high frequency and performs complex calculations and judgments based on the preset control logic stored internally, ultimately generating control decisions.

[0082] The actuator module 330 functions as the control unit's actuators. It is typically an analog or digital output module. It receives control commands from the decision module 320, a value representing the target valve opening from 0-100%, and converts it into a standard drive signal, such as a 4-20mA control current, which is then sent to the pneumatic or electric actuator mounted on the diverter valve 180. This precisely controls the valve opening, thereby adjusting the diversion ratio y.

[0083] Preferably, the control device 300 may further include a human-machine interface and data storage module 340, which provides operators with a monitoring and operation interface. It typically includes a touchscreen human-machine interface (HMI) and memory or hard disk for data recording. Through the HMI, engineers can set control parameters (such as various thresholds, PID parameters, target setpoints), monitor the real-time operating status of various parts of the system, view historical data trend curves, and query and confirm alarm information.

[0084] Monitoring module 310 continuously collects T data at a relatively high fixed frequency (once per second). amb P net T MC_inThe instantaneous values ​​of a series of parameters are obtained and transmitted to the decision module 320. Within each control cycle, the decision module 320 executes the following composite judgment logic, which organically combines the predictive nature of feedforward control and the corrective nature of feedback control. The decision module 320 determines whether the thermal power generation system is in or about to enter a performance degradation state. If so, it sets an intervention trigger flag (Trigger_Flag) to 1 in advance. When Trigger_Flag is 1, the adjustment amount is calculated. The decision module 320 initiates a control algorithm (PID strategy or MPC strategy) to calculate the necessary adjustment to the flow ratio y. The decision module 320 sends the calculated target opening setpoint of the flow divider valve to the execution module 330. The execution module 330 then adjusts the 4-20mA current signal output to the actuator of the flow divider valve 180, driving the valve to the new target opening, thereby achieving precise adjustment of the flow ratio y.

[0085] This invention acquires external environmental parameters and / or internal performance parameters of a thermal power generation system; determines whether the thermal power generation system is in or about to enter a performance degradation state; when the thermal power generation system is in or about to enter a performance degradation state, it generates a first type of regulation command to adjust the flow rate of the working fluid entering the internal refrigeration sub-loop; based on the first type of regulation command, it actively increases the flow rate of the working fluid flowing into the internal refrigeration sub-loop, utilizing the enhanced cooling effect due to the increased flow rate to deeply cool the working fluid flowing to the compressor inlet in the main circulation loop, thereby reducing the power consumption of the compressor in the main circulation loop to compensate for the decrease in the net output power of the thermal power generation system caused by external environmental parameters. This changes the past single passive adaptation, derating operation, or violent confrontation, high-consumption cooling mode to a new mode of active utilization and intelligent control; effectively solves the problems of high output power control cost and low reliability of thermal power generation systems caused by existing technologies, effectively improving the reliability of output power control of thermal power generation systems and reducing control costs.

[0086] In this invention, the system determines whether the current ambient air temperature is greater than a first preset temperature threshold. If the current ambient air temperature is greater than the first preset temperature threshold, it determines whether the thermal power generation system is in or about to enter a performance degradation state. Alternatively, it determines whether the current net output power of the thermal power generation system is less than a preset power threshold. If the current net output power of the thermal power generation system is less than the preset power threshold, it determines whether the thermal power generation system is in or about to enter a performance degradation state. Or, it determines whether the current main compressor inlet temperature is greater than a second preset temperature threshold. If the current main compressor inlet temperature is greater than the second preset temperature threshold, it determines whether the thermal power generation system is in or about to enter a performance degradation state, thus ensuring the reliability of the thermal power generation system's output power control.

[0087] The technical solution of this invention determines the current operating stage or the upcoming operating stage of the thermal power generation system based on external environmental parameters and / or internal performance parameters. If the thermal power generation system is in a stable and controllable operating condition, a first regulation control command is generated according to a first regulation control strategy. If the thermal power generation system is in a complex dynamic operating condition, a second regulation control command is generated according to a second regulation control strategy. Based on a comprehensive judgment of the operating condition of the thermal power generation system, intelligent switching is performed between the two control strategies, which can organically combine the two control strategies and achieve an effective balance between control performance and computational resource consumption.

[0088] The technical solution of this invention establishes a system dynamic characteristic prediction model; defines an optimization objective function that includes the expectation of future internal system performance parameters and the penalty for changes in control input; in each control cycle, based on the currently acquired external environmental parameters, internal performance parameters, and system dynamic characteristic prediction model, solves the optimization objective function that satisfies the constraints in the future prediction time domain to obtain the optimal control input sequence; calculates the second regulation control command based on the first element of the optimal control input sequence; it can determine future internal performance parameters based on system external environmental parameters, disturbance parameters, equipment state parameters, etc., enabling the thermal power generation system to cope more easily with various non-design point operating conditions, whether it is predictable seasonal temperature changes, large intraday temperature fluctuations, or sudden, unexpected abnormal situations, such as brief interruptions in cooling water supply or water quality deterioration; it can maintain the relative stability of its key performance indicators within a certain range through the automatic redistribution of internal energy flow, which greatly enhances the robustness of the entire power generation system and enables it to adapt to more variable and harsh external environments.

[0089] The objective function optimized in this invention not only includes the expectation of future internal performance parameters of the system, but also the penalty for changes in control input. The constraints include control input constraints, control input change rate constraints, output variable constraints, and safety constraints, which further improves the reliability of output power control in thermal power generation systems.

[0090] Real-time Example 3 like Figure 2 As shown, the present invention also provides a thermal power generation system, including: a main circulation loop, an internal refrigeration sub-loop, and a control device for the output power of a thermal power generation system as shown in Embodiment 2. The internal refrigeration sub-loop is used to divert the working fluid from the main circulation loop to generate a cooling effect.

[0091] like Figure 2As shown, the entire thermal power generation system physically consists mainly of a main circulation loop for power generation and a controllable internal refrigeration sub-loop. These two loops achieve close functional coupling through the splitting and merging of the working fluid at specific nodes, together forming an advanced power system capable of actively adapting to environmental changes.

[0092] Specifically, the main circulation loop, as the power core of the thermal power generation system, operates as follows: At state point 1 (e.g., temperature 650°C, pressure 20 MPa), the sCO2 working fluid flows out from heater 170, which serves as the system's heat source. This heat source can be driven by various energy forms such as solar thermal, nuclear reactor, gas turbine exhaust steam, or industrial waste heat. The high-temperature, high-pressure working fluid then enters the main turbine 100 to expand and perform work, driving the coaxially connected generator 110 to output electrical energy. After performing work, the working fluid becomes medium-temperature, medium-pressure exhaust steam (state point 2). To maximize energy recovery, this exhaust steam flows sequentially through the hot-side channels of the high-temperature regenerator 120 (HTR) and the low-temperature regenerator 130 (LTR), transferring residual heat to the working fluid to be heated on the high-pressure side, while being cooled to state point 3.

[0093] At state point 3, the working fluid flow path reaches a critical multi-way splitting node (splitter valve 180). A portion of the working fluid (splitter ratio x) is directly fed into the recompressor 160 for recompression, reaching state point 7. This recompression configuration is typical of advanced sCO2 cycles, designed to reduce the heat exchange temperature difference within the cryogenic regenerator 130, preventing phase change of the working fluid on the low-pressure side, thereby significantly improving regeneration efficiency and overall cycle efficiency. The other portion of the mainstream working fluid (splitter ratio 1-xy) continues to flow towards the cold end of the cycle, entering the main cooler 140. Here, the working fluid exchanges heat with an external cooling medium (such as cooling water or air), discharging waste heat to the environment, and is initially cooled to near ambient temperature at state point 4.

[0094] The operation of the internal refrigeration sub-loop 200 is key to achieving dynamic regulation. The internal refrigeration sub-loop consists of the following components connected in series: the working fluid diverted from the main circulation loop flows sequentially through the refrigeration expander 210 and the refrigeration heat exchanger 220 before merging back into the main circulation loop; deep cooling of the working fluid in the main circulation loop is completed in the refrigeration heat exchanger 220, which cools the working fluid flowing towards the inlet of the main compressor 150 in the main circulation loop.

[0095] A diversion valve 180, precisely controlled by a control device 300, is located after state point 3 and before the main cooler 140 (at the point where the main circulation loop and the internal refrigeration sub-loop diverge). When it is determined that internal refrigeration needs to be activated, the valve 180 opens, diverting a small portion of the working fluid (diversion ratio y, state point 3) from the main flow path (main circulation loop) and introducing it into the internal refrigeration sub-loop. This working fluid first enters the refrigeration expander 210 for quasi-isentropic expansion, causing its pressure and temperature to drop sharply (e.g., from approximately 40°C to 5°C), forming a low-temperature working fluid flow with forced cooling capacity (state point 12). To recover energy, the refrigeration expander 210 can be linked to a micro-generator or compressor; alternatively, a Joule-Thomson throttle valve can be used.

[0096] The low-temperature working fluid carrying a large amount of cooling capacity (state point 12) then flows into the cold-side channel of the refrigeration heat exchanger 220. Simultaneously, a portion of the mainstream working fluid (state point 4) flowing out of the main cooler 140 is guided into the hot-side channel of the refrigeration heat exchanger 220. Inside the refrigeration heat exchanger 220, the two fluids undergo efficient heat exchange. The low-temperature refrigerant absorbs heat from the hot-side mainstream working fluid, thereby achieving a secondary deep cooling of the mainstream working fluid's temperature, reducing it from state point 4 (e.g., 38°C) to a more ideal compressor inlet temperature, state point 9 (e.g., 32°C). After completing the heat exchange, the refrigerant in the sub-loop reaches state point 13, where it merges with the mainstream working fluid (state point 4) that has undergone preliminary cooling by the main cooler, together forming the final working fluid flow entering the main compressor 150.

[0097] In the low-pressure section of the main cycle, the working fluid stream (state point 9), after deep cooling and merging, enters the main compressor 150 and is compressed to an intermediate pressure (state point 10). Subsequently, this working fluid stream mixes with another working fluid stream (state point 7) from the recompressor 160 before the cold-side inlet of the cryogenic regenerator 130, reaching state point 8. The mixed full-flow high-pressure working fluid flows sequentially through the cold side of the cryogenic regenerator 130 and the high-temperature regenerator 120, fully absorbing the waste heat of the turbine exhaust steam, preheating to state point 11, and finally returning to the heater 170, completing the entire closed thermodynamic cycle.

[0098] This invention acquires external environmental parameters and / or internal performance parameters of a thermal power generation system; determines whether the thermal power generation system is in or about to enter a performance degradation state; when the thermal power generation system is in or about to enter a performance degradation state, it generates a first type of regulation command to adjust the flow rate of the working fluid entering the internal refrigeration sub-loop; based on the first type of regulation command, it actively increases the flow rate of the working fluid flowing into the internal refrigeration sub-loop, utilizing the enhanced cooling effect due to the increased flow rate to deeply cool the working fluid flowing to the compressor inlet in the main circulation loop, thereby reducing the power consumption of the compressor in the main circulation loop to compensate for the decrease in the net output power of the thermal power generation system caused by external environmental parameters. This changes the past single passive adaptation, derating operation, or violent confrontation, high-consumption cooling mode to a new mode of active utilization and intelligent control; effectively solves the problems of high output power control cost and low reliability of thermal power generation systems caused by existing technologies, effectively improving the reliability of output power control of thermal power generation systems and reducing control costs.

[0099] In this invention, the system determines whether the current ambient air temperature is greater than a first preset temperature threshold. If the current ambient air temperature is greater than the first preset temperature threshold, it determines whether the thermal power generation system is in or about to enter a performance degradation state. Alternatively, it determines whether the current net output power of the thermal power generation system is less than a preset power threshold. If the current net output power of the thermal power generation system is less than the preset power threshold, it determines whether the thermal power generation system is in or about to enter a performance degradation state. Or, it determines whether the current main compressor inlet temperature is greater than a second preset temperature threshold. If the current main compressor inlet temperature is greater than the second preset temperature threshold, it determines whether the thermal power generation system is in or about to enter a performance degradation state, thus ensuring the reliability of the thermal power generation system's output power control.

[0100] The technical solution of this invention determines the current operating stage or the upcoming operating stage of the thermal power generation system based on external environmental parameters and / or internal performance parameters. If the thermal power generation system is in a stable and controllable operating condition, a first regulation control command is generated according to a first regulation control strategy. If the thermal power generation system is in a complex dynamic operating condition, a second regulation control command is generated according to a second regulation control strategy. Based on a comprehensive judgment of the operating condition of the thermal power generation system, intelligent switching is performed between the two control strategies, which can organically combine the two control strategies and achieve an effective balance between control performance and computational resource consumption.

[0101] The technical solution of this invention establishes a system dynamic characteristic prediction model; defines an optimization objective function that includes the expectation of future internal system performance parameters and the penalty for changes in control input; in each control cycle, based on the currently acquired external environmental parameters, internal performance parameters, and system dynamic characteristic prediction model, solves the optimization objective function that satisfies the constraints in the future prediction time domain to obtain the optimal control input sequence; calculates the second regulation control command based on the first element of the optimal control input sequence; it can determine future internal performance parameters based on system external environmental parameters, disturbance parameters, equipment state parameters, etc., enabling the thermal power generation system to cope more easily with various non-design point operating conditions, whether it is predictable seasonal temperature changes, large intraday temperature fluctuations, or sudden, unexpected abnormal situations, such as brief interruptions in cooling water supply or water quality deterioration; it can maintain the relative stability of its key performance indicators within a certain range through the automatic redistribution of internal energy flow, which greatly enhances the robustness of the entire power generation system and enables it to adapt to more variable and harsh external environments.

[0102] The objective function optimized in this invention not only includes the expectation of future internal performance parameters of the system, but also the penalty for changes in control input. The constraints include control input constraints, control input change rate constraints, output variable constraints, and safety constraints, which further improves the reliability of output power control in thermal power generation systems.

[0103] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method of controlling the output power of a thermal power generating system, characterized by, The method comprises the following steps: acquiring external environment parameters and / or internal performance parameters of a thermal power generation system; wherein the thermal power generation system comprises a main circulation loop and an internal refrigeration sub-loop capable of diverting working medium from the main circulation loop to generate a refrigeration effect; judging whether the thermal power generation system is in or about to enter a performance decline state based on the external environment parameters and / or the internal performance parameters; and generating a first type of adjustment instruction for adjusting the flow of working medium into the internal refrigeration sub-loop when the thermal power generation system is in or about to enter the performance decline state; actively increasing the flow of working medium into the internal refrigeration sub-loop according to the first type of adjustment instruction, and using the enhanced refrigeration effect caused by the increased flow of working medium to deeply cool the working medium flowing to the inlet of a compressor in the main circulation loop, so as to reduce the power consumption of the compressor in the main circulation loop, thereby compensating for the decline in the net output power of the thermal power generation system caused by the external environment parameters.

2. A method of controlling the output power of a thermal power generating system according to claim 1, characterized in that, The external environment parameters include ambient air temperature, cooling water inlet temperature, and cooling air inlet temperature; and the internal performance parameters include the net output power of the thermal power generation system, the working medium temperature, the working medium pressure, the turbine speed, and the circulation efficiency at the inlet of the compressor in the main circulation loop.

3. A method of controlling the output power of a thermal power generating system according to claim 2, characterized in that, The judgment of whether the thermal power generation system is in or about to enter a performance decline state based on the external environment parameters and / or the internal performance parameters specifically comprises: judging whether the current ambient air temperature is greater than a first preset temperature threshold; if the current ambient air temperature is greater than the first preset temperature threshold, judging whether the thermal power generation system is in or about to enter a performance decline state; or, judging whether the net output power of the current thermal power generation system is less than a preset power threshold; if the net output power of the current thermal power generation system is less than the preset power threshold, judging whether the thermal power generation system is in or about to enter a performance decline state; or, judging whether the current main compressor inlet temperature is greater than a second preset temperature threshold; if the current main compressor inlet temperature is greater than the second preset temperature threshold, judging whether the thermal power generation system is in or about to enter a performance decline state.

4. The method of claim 1, wherein The generation of the adjustment instruction for adjusting the flow of working medium into the internal refrigeration sub-loop when the thermal power generation system is in or about to enter a performance decline state specifically comprises: determining the current operating stage or the operating stage about to be entered of the thermal power generation system based on the external environment parameters and / or the internal performance parameters; if the thermal power generation system is in a stable controllable working condition, generating a first adjustment control instruction according to a first adjustment control strategy, wherein the first adjustment control strategy is a PID strategy, and the first adjustment control instruction is a first target opening degree of a diversion valve arranged between the main circulation loop and the internal refrigeration sub-loop; the thermal power generation system being in a stable controllable working condition specifically means that the load change rate is less than a preset change rate threshold; and the external environment parameters are respectively less than corresponding preset environment parameter thresholds; and the distance between the current working point and the constraint boundary is less than a preset distance threshold. If the thermal power generation system is in a complex dynamic working condition, a second adjustment control instruction is generated according to a second adjustment control strategy, wherein the second adjustment control strategy is an MPC strategy, and the second adjustment control instruction is a second target opening degree of a shunt valve arranged between a main circulation loop and an internal refrigeration sub-loop; the thermal power generation system is in a stable controllable working condition, specifically: a load change rate is greater than a preset change rate threshold; or, external environment parameters are respectively greater than corresponding preset environment parameter thresholds; or, a distance between a current working point and a constraint boundary is greater than a preset distance threshold.

5. A method of controlling the output power of a thermal power generating system according to claim 4, characterized in that, The first adjustment control instruction is generated according to a first adjustment control strategy, specifically including: The first target opening degree is calculated by taking the inlet temperature of the main compressor in the main circulation loop as a controlled variable and taking the optimal working temperature of the main compressor in the main circulation loop as a set value, specifically including: ； wherein, is the first target opening degree of the flow dividing valve disposed between the main circulation loop and the internal refrigeration sub-loop at time t, e(t) is the error between the set value and the controlled variable, Kp is the proportional coefficient in the PID parameter, Ki is the integral coefficient in the PID parameter, and Kd is the differential coefficient in the PID parameter.

6. A method of controlling the output power of a thermal power generating system according to claim 4, characterized in that, The second adjustment control instruction is generated according to a second adjustment control strategy, specifically including: A system dynamic characteristic prediction model is established, the system dynamic characteristic prediction model taking a working medium flow into the internal refrigeration sub-loop as a control input quantity, taking external environment parameters as disturbance quantities, and taking internal performance parameters as output quantities; An optimization objective function is defined, including an expectation of future system internal performance parameters and a punishment for a change in the control input quantity; In each control period, based on the currently acquired external environment parameters, internal performance parameters and the system dynamic characteristic prediction model, the optimization objective function that meets the constraint conditions in a future prediction time domain is solved to obtain an optimal control input sequence; The second adjustment control instruction is calculated according to a first element of the optimal control input sequence.

7. A method of controlling the output power of a thermal power generating system according to claim 6, characterized in that, The system dynamic characteristic prediction model is specifically: x(k + 1) = A x(k) + B u(k) + E d(k); y out (k)=C x(k) wherein k represents the current discrete control time; x(k) is a thermodynamic state vector of the internal equipment of the system; u(k) is a control input vector of the flow divider opening; d(k) is a disturbance vector of the external environmental parameters; y out (k) is an output vector of the internal performance parameters of the system; A is a state input matrix describing the dynamic characteristics of the system; B is a control input matrix describing the dynamic characteristics of the system; E is a disturbance input matrix describing the dynamic characteristics of the system; and C is a state output matrix describing the dynamic characteristics of the system.

8. The method for controlling the output power of a thermal power generation system according to claim 6, characterized in that, The optimization objective function is specifically: where J is the optimization objective function, y out_ref is the internal performance parameter target sequence set in the future prediction time domain, y out_pred is the predicted internal performance parameter output sequence starting from the current state x(k) under the action of the future control sequence and the disturbance sequence; Q is the expected weight matrix; Δu is the change of the control input; and R is the control input quantity penalty weight matrix. The constraint conditions include control input constraints, control input change rate constraints, output variable constraints and safety constraints.

9. A control device for the output power of a thermal power generation system, characterized in that, The method includes: A monitoring module acquires external environment parameters and / or internal performance parameters of a thermal power generation system; wherein the thermal power generation system includes a thermal circulation system, and the thermal circulation system includes a main circulation loop and an internal refrigeration sub-loop that can shunt working medium from the main circulation loop to generate a refrigeration effect; A decision-making module judges whether the thermal power generation system is in or about to enter a performance decline state based on the external environment parameters and / or the internal performance parameters; when the thermal power generation system is in or about to enter the performance decline state, a first type of adjustment instruction for adjusting the working medium flow into the internal refrigeration sub-loop is generated; An execution module actively increases the working medium flow into the internal refrigeration sub-loop according to the first type of adjustment instruction, and uses the enhanced refrigeration effect caused by the increased working medium flow to deeply cool the working medium flowing to the inlet of a compressor in the main circulation loop, thereby reducing the power consumption of the compressor in the main circulation loop to compensate for the decline in the net output power of the thermal power generation system caused by the external environment parameters.

10. A thermal power generation system, characterized by comprising: The method includes: A main circulation loop, an internal refrigeration sub-loop and a control device for the output power of a thermal power generation system as claimed in claim 9, the internal refrigeration sub-loop being used to shunt working medium from the main circulation loop to generate a refrigeration effect.

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