Efficient thermoelectric decoupling method and system combined with supercritical CO2 circulation

Abstract

The invention discloses an efficient thermoelectric decoupling method and system combined with supercritical CO2 circulation, relates to the field of energy power systems, and aims at solving the problems that a traditional steam circulation system is low in load energy efficiency, insufficient in thermoelectric decoupling flexibility and large in energy loss. The system comprises a steam cycle unit, a supercritical CO2 cycle unit, a collaborative heat exchange unit and an intelligent control unit, and the core of the method is that a sensor is arranged to collect multi-dimensional parameters, the multi-dimensional parameters are preprocessed through a 3-sigma criterion, and a collaborative reference coefficient of the system is calculated to quantify dual-cycle suitability; distinguishing working conditions based on a load fluctuation coefficient, and predicting the load in future 2 hours by combining machine learning; the supercritical CO2 cycle power generation load proportion is calculated according to the working conditions, the rotating speed of a compressor and the opening degree of a regulating valve are adjusted, and the ejection coefficient of an ejector and heat pump power are calculated through synchronous coupling; and through the energy efficiency deviation correction parameter, the daily update reference coefficient adapts to long-term change. And the method is suitable for the scenes of thermal power generation, central heating and the like.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of energy power systems, in particular to a high-efficiency heat-electricity decoupling method and system combined with a supercritical CO2 cycle, which is applied to thermal power plants, central heating stations and industrial waste heat utilization scenarios. BACKGROUND

[0002] In the energy security system of industrial production and urban heating, the cogeneration system occupies a core position due to its dual functions of power generation and heat supply. The heat-electricity decoupling technology with steam cycle as the core is widely used due to its maturity. However, with the dynamicization of energy demand and the improvement of energy saving and emission reduction requirements, the inherent defects of this traditional technology have become increasingly prominent, becoming a key bottleneck restricting efficient energy utilization.

[0003] The energy efficiency cliff drop under low load condition is the primary pain point. The thermodynamic design of the traditional steam cycle system is highly adapted to the rated load, and the efficiency in the steam turbine is strongly positively correlated with the steam inlet parameter. In the scenarios of night-time low electricity demand, seasonal alternating heat load reduction, etc., to match the low load demand, the boiler needs to reduce the combustion intensity, resulting in a decrease in the main steam pressure from the rated value and a decrease in the temperature. In winter night, the heat load is reduced by half, which not only increases the operating cost, but also aggravates carbon emissions. The lack of flexibility of heat-electricity decoupling leads to imbalance between supply and demand. The traditional system is constrained by "heat determines electricity" and "electricity determines heat", and the heat and electricity load adjustment is mutually restricted. A sharp reduction in heat load will reduce the steam extraction amount of the steam turbine, and the excess power will easily cause equipment vibration if the power generation load is forcibly reduced. When the electricity load suddenly increases, the boiler needs to prioritize the steam inlet of the steam turbine, which also leads to insufficient heating pressure. This coupling relationship makes the system unable to accurately respond to peak and valley demand, and the annual energy waste rate in areas with large load fluctuations is as high as 10%-15%. In the process of heat energy conversion and transmission, the steam cycle has a large energy loss, such as heat loss of steam in pipeline transportation, mechanical loss of steam turbine and other equipment, lack of low-grade waste heat recovery, and direct emission of low-temperature heat energy such as steam turbine exhaust condensing heat and equipment cooling water waste heat, forming secondary waste, and the total energy loss rate of the traditional system is generally 25%-30%.

[0004] Existing optimization methods are mostly local adjustments such as valve throttling and steam extraction staging, which do not touch the essential defects of the cycle architecture. Therefore, it is imperative to develop a new type of technology that can adapt to wide load fluctuations, break through the coupling constraints and reduce losses. SUMMARY

[0005] The application aims to provide a high-efficiency thermal-electric decoupling method and system combined with supercritical CO2 cycle, which dynamically determines the working condition and predicts the load through the intelligent control unit by collecting double-cycle multi-dimensional parameters and calibrating the quantitative cooperative reference coefficient, adjusts the supercritical CO2 cycle power load ratio, the ejector entrainment coefficient and the steam heat pump power for different working conditions to realize thermal-electric decoupling, and forms a closed-loop control guarantee system for efficient and stable operation through energy efficiency deviation correction parameters and daily update of reference coefficient, aiming to improve energy utilization efficiency, optimize thermal-electric decoupling process and realize efficient conversion and utilization of energy.

[0006] To achieve the above-mentioned purpose, the application provides the following technical scheme.

[0007] A high-efficiency thermal-electric decoupling method combined with supercritical CO2 cycle, characterized in that it comprises the following steps:

[0008] S1: arranging sensors to collect system initial parameters, real-time running parameters and historical and target parameters, and performing outlier rejection and calibration on the parameters;

[0009] S2: calculating the system cooperative reference coefficient based on the calibrated data, and quantifying the initial adaptability of the steam cycle and the supercritical CO2 cycle;

[0010] S3: determining the system working condition, distinguishing between high fluctuation working condition and stable working condition, and combining historical data and machine learning algorithm to predict future total load and heat load values;

[0011] S4: according to the working condition determination result, calculating the supercritical CO2 cycle power load ratio under different working conditions, and adjusting the CO2 compressor speed and the steam regulating valve opening degree according to the ratio value calculated by the predicted value;

[0012] S5: combining the supercritical CO2 cycle power load ratio, calculating the optimal entrainment coefficient of the ejector and the steam heat pump driving power, and adjusting the ejector nozzle opening degree and the steam heat pump operating parameter according to the calculation result;

[0013] S6: collecting system output data, calculating the optimal comprehensive energy efficiency and energy efficiency deviation of the system, and correcting the supercritical CO2 cycle power load ratio and the optimal entrainment coefficient of the ejector according to the calculation result.

[0014] Step S1 arranges the sensor, collects the system initial parameters, real-time operation parameters and historical and target parameters, and carries out outlier elimination and mean calibration on them, wherein the system initial parameters include collecting the rated pressure of the boiler, the rated temperature of the main steam, the air load steam consumption of the steam turbine, the initial rotating speed of the CO2 compressor, the critical pressure and temperature of the turbine start, the real-time operation parameters include collecting the total load demand, the heat load demand, the actual temperature of the main steam, the actual pressure of the sCO2 cycle, the inlet and outlet pressures of the ejector and the mass flow of the working medium at a frequency of 10 Hz, the historical and target parameter collection includes the load history data of the past 720 hours, records the rated power generation of the system, the benchmark heat load and the target temperature rise of the steam heat pump, wherein the outlier elimination adopts the 3σ criterion and the mean calibration.

[0015] Step S2 calculates the system synergy benchmark coefficient based on the calibrated data, quantifies the initial adaptability of the steam cycle and the supercritical CO2 cycle, specifically calculates the system synergy benchmark coefficient based on the calibrated data , and the formula is as follows:

[0016] ;

[0017] In the formula, represents the system synergy benchmark coefficient, represents the rated pressure of the boiler, represents the rated temperature of the main steam, represents the air load steam consumption of the steam turbine, represents the initial rotating speed of the CO2 compressor, represents the critical pressure of the supercritical CO2 turbine start, represents the critical temperature of the supercritical CO2 turbine start, represents the rated power generation of the system, represents the benchmark heat load of the system.

[0018] S3 determines the system working condition, distinguishes between high fluctuation working condition and stable working condition, and combines historical data and machine learning algorithm to predict future total load and heat load values, specifically includes calculating the load fluctuation coefficient based on the collected real-time data and the system synergy benchmark coefficient , and the formula is as follows:

[0019] ;

[0020] In the formula, represents the load fluctuation coefficient, represents the sampling point serial number, represents the total load demand of the th sampling point, represents the rated power generation of the system, represents the heat load demand of the th sampling point, Indicates the system's reference heat load. Represents the system's collaborative benchmark coefficient; when High-fluctuation operating conditions are defined as high-volatility operating conditions, while low-fluctuation conditions are defined as stable operating conditions. By combining historical data with machine learning algorithms, the load value for the next 2 hours can be predicted. , .

[0021] Step S4, based on the operating condition determination results, calculates the supercritical CO2 cycle power generation load ratio under different operating conditions, and adjusts the CO2 compressor speed and steam regulating valve opening according to the ratio value calculated from the predicted value. Specifically, for high-fluctuation operating conditions, a fast response formula is used to calculate the supercritical CO2 cycle power generation load ratio. Its formula is:

[0022] ;

[0023] For steady-state operating conditions: the proportion is calculated using the energy efficiency priority formula. Its formula is:

[0024] ;

[0025] In the formula, This indicates the proportion of supercritical CO2 cycle power generation load under highly fluctuating operating conditions. This indicates the maximum power generation capacity of the supercritical CO2 cycle. Indicates the future Total load forecast at time 10:00 This indicates the actual temperature of the main steam. This indicates the rated total power output of the system. Indicates the future The predicted heat load value at any given time. Indicates the system's reference heat load. Represents the system's collaborative benchmark coefficient. This indicates the proportion of supercritical CO2 cycle power generation load under stable operating conditions; This indicates the maximum power generation capacity of the supercritical CO2 cycle. This indicates the current total load demand of the system. Indicates the average temperature of the main steam. This indicates the current heat load demand. This represents the system's baseline heat load. The equipment is adjusted based on the supercritical CO2 cycle power generation load ratio (λ). When λ increases, the CO2 compressor speed is increased between 1500-6000 r / min to increase the supercritical CO2 cycle power generation ratio; when λ decreases, the compressor speed is reduced to decrease the supercritical CO2 cycle ratio. At low loads, adjustments are needed to ensure... .

[0026] Step S5, combining the supercritical CO2 cycle power generation load ratio, calculates the optimal ejector coefficient and steam heat pump drive power. Based on the calculation results, it adjusts the ejector nozzle opening and steam heat pump operating parameters. Specifically, it combines the ejector parameters from step S1 with those from step S4. Value, calculate the optimal ejector coefficient. Its formula is:

[0027] ;

[0028] In the formula, This represents the optimal ejection coefficient of the injector. This indicates the pressure at the injector drive inlet. This indicates the pressure at the ejector inlet. Indicates the target temperature of the steam heat pump. This indicates the mass flow rate of the low-grade working fluid at the ejector inlet. This indicates the mass flow rate of the high-energy working fluid at the injector drive inlet. This indicates the proportion of supercritical CO2 cycle power generation load;

[0029] when Increase the nozzle opening to increase the injection velocity and momentum of the driving working fluid, thereby improving the suction effect on low-grade ejector working fluid and raising the ejector flow rate ratio to a suitable level. The level; when Reduce the nozzle opening to decrease the driving propellant injection intensity and reduce the proportion of ejector flow.

[0030] Calculate the driving power of the steam heat pump Its formula is:

[0031] ;

[0032] In the formula, Indicates the driving power of the steam heat pump. This indicates the mass flow rate of the mixed working fluid output by the injector. This represents the specific heat capacity at constant pressure of the mixed working fluid. This indicates the target temperature rise of the steam heat pump. This indicates the actual pressure of the supercritical CO2 cycle. This represents the mass flow rate of the supercritical CO2 circulating working fluid. By changing the value as described above, the heat pump output working fluid is distributed, with one path supplying heat users and the other path returning to the sCO2 regenerator to recover waste heat.

[0033] Step S6 collects system output data, calculates the system's optimal comprehensive energy efficiency and energy efficiency deviation, and corrects the supercritical CO2 cycle power generation load ratio and the optimal ejector coefficient based on the calculation results. Specifically, it collects the system's output electrical energy. Thermal energy and fuel input Calculate optimal energy efficiency Its formula is:

[0034] ;

[0035] In the formula, This indicates the optimal overall energy efficiency of the system. This represents the actual electrical power output of the system. This represents the actual thermal power output of the system. Indicates the fuel thermal energy power of the input system. Indicates the system's rated power generation. This represents the system's collaborative baseline coefficient, which determines the optimal energy efficiency. The difference is calculated by comparing it with the current energy consumption. ,like The corrected value for the supercritical CO2 cycle power generation load ratio λ is λ. Specifically Based on the revised Value and energy efficiency deviation Synchronous adjustment By modifying the ejector coefficient to optimize the ejector's effect on low-grade working fluid, the heat recovery efficiency of the steam heat pump is improved, thereby making up for the energy efficiency gap and bringing the system closer to the optimal energy efficiency state.

[0036] The above method recalculates and updates the system coordination baseline coefficients daily based on the full amount of operational data collected that day. This allows subsequent energy efficiency calculations and parameter corrections to adapt to long-term changes such as equipment aging and operating condition fluctuations, maintaining the continuity of closed-loop control.

[0037] A highly efficient thermoelectric decoupling system combining a supercritical CO2 cycle includes a steam cycle unit, a supercritical CO2 cycle unit, a synergistic heat exchange unit, and an intelligent control unit. In the steam cycle unit, the main steam generated by the boiler is transported to the turbine via a steam pipeline. After driving the turbine to perform work, the steam is discharged to the condenser, and the condensate is returned to the boiler via a feedwater pump, forming a closed-loop steam cycle. In the supercritical CO2 cycle unit, CO2 is compressed by a CO2 compressor, then preheated on the low-temperature side of the regenerator, and then flows into a channel connected to the boiler to absorb high-temperature heat energy, becoming high-temperature and high-pressure CO2. This CO2 then enters the supercritical CO2 turbine to perform work, and the low-temperature and low-pressure CO2 discharged from the turbine returns to the regenerator, completing the supercritical CO2 cycle closed loop. The turbine and the supercritical CO2 turbine are both connected to a generator via a coupling to convert mechanical energy into electrical energy and input it into the power grid.

[0038] In the collaborative heat exchange unit, a branch of the boiler extraction steam pipe connects to the ejector as the drive inlet. The condenser drain pipe merges with the outlet pipe of the low-temperature section of the supercritical CO2 circulating regenerator and is then connected to the ejector inlet. The mixed working fluid discharged from the ejector enters the steam heat pump, while the branch of the outlet pipe on the low-temperature side of the supercritical CO2 circulating regenerator also provides low-temperature working fluid to the steam heat pump. The high-temperature working fluid output by the steam heat pump is supplied to the heat user on one side and returned to the inlet of the supercritical CO2 circulating regenerator on the other side. The heated working fluid returns to the front end of the CO2 compressor inlet. The heat user's return water is pumped to the low-grade working fluid inlet of the ejector for waste heat and working fluid recovery.

[0039] The intelligent control unit includes a data acquisition module and a control center optimization control module, implementing the method of any one of claims 1-8. The data acquisition module collects parameters of each pipeline and equipment through sensors such as temperature, pressure, and flow, and transmits them to the control center optimization control module. The control center then regulates the actuators such as water pumps, regulating valves, and regulating mechanisms of each unit through control lines to form a closed loop, ensuring the efficient and stable operation of the system.

[0040] This efficient thermoelectric decoupling system and method combining supercritical CO2 cycles achieves thermoelectric decoupling and energy efficiency optimization through progressive operation of multi-dimensional parameter sensing, dynamic operating condition adaptation, coordinated parameter adjustment, and full-cycle energy efficiency correction: The data acquisition module of the intelligent control unit first acquires the initial, real-time, historical, and target parameters of the steam cycle and the supercritical CO2 cycle at a frequency of 10Hz. After outlier removal and mean calibration by the 3σ criterion, the initial adaptability of the dual cycles is quantified by the system coordinated benchmark coefficient formula. This coefficient integrates the rated parameters of the equipment and the cycle start-up characteristics, laying a quantitative foundation for subsequent regulation. Next, based on real-time data, the load fluctuation coefficient is calculated to accurately distinguish between high-fluctuation and stable operating conditions. Simultaneously, machine learning models combined with historical data are used to predict the total load and heat load for the next two hours, providing a predictive basis for differentiated regulation. Subsequently, the proportion of supercritical CO2 cycle power generation load is calculated for different operating conditions. For high-fluctuation conditions, a fast-response formula prioritizes load tracking, adjusting the CO2 compressor speed within the 1500-6000 r / min range to change the proportion of supercritical CO2 cycle power generation load. For stable operating conditions, an energy efficiency priority formula focuses on energy efficiency optimization, simultaneously combining… The optimal ejector coefficient is calculated based on the values ​​and ejector parameters. The ejector flow rate is matched by adjusting the nozzle opening. The steam heat pump drive power is calculated based on the characteristics of the mixed working fluid and the supercritical CO2 pressure. The working fluid of the heat pump is dynamically allocated, with one path supplying heat to users and the other returning to the regenerator to recover waste heat. Finally, the system output electrical energy, thermal energy and fuel input data are collected to calculate the optimal comprehensive energy efficiency. If the deviation from the actual energy efficiency exceeds the preset value, it is corrected to make up for the energy efficiency gap. Furthermore, the system is updated daily based on full data to adapt to equipment aging and operating condition fluctuations, forming a closed loop to continuously ensure the efficient and stable operation of the thermoelectric decoupling.

[0041] Compared with the prior art, the beneficial effects of the present invention are:

[0042] By adopting a dual-cycle coupling design of supercritical CO2 cycle and steam cycle, the core control parameter of supercritical CO2 cycle power generation load ratio is introduced. Differentiated calculation logics with fast response and energy efficiency priority are adopted for high fluctuation and stable operating conditions, respectively. Combined with the dynamic adjustment of CO2 compressor speed and steam regulating valve, the inherent limitation of power generation relying on heat supply load in traditional cogeneration systems is broken, and independent response to power generation and heat supply demand is achieved.

[0043] A closed-loop control system covering the entire lifecycle of "parameter acquisition - benchmark quantification - adjustment and correction" is constructed. By quantifying the dual-cycle adaptability through system-coordinated benchmark coefficients and combining the optimal ejector coefficient and the driving power of the steam heat pump, the efficiency of low-grade working fluid recovery and waste heat utilization is optimized. At the same time, based on dynamic correction of energy efficiency deviations and daily updates to adapt to equipment aging and operating condition fluctuations, the overall energy efficiency improvement is more sustainable and precise compared to the existing fixed parameter control mode.

[0044] By relying on the load fluctuation coefficient, the system can accurately distinguish between high fluctuation and stable operating conditions. Combined with machine learning algorithms, it can predict the load for the next two hours, enabling parameter adjustments to adapt to changes in demand in advance. The linkage design of the ejector and steam heat pump in the heat exchange unit, as well as the dynamic distribution mechanism of the working fluid flow, further enhances the system's tolerance to load fluctuations. Compared with existing single-cycle or simple coupling systems, the system's operational stability and response speed under complex operating conditions are significantly improved. Attached Figure Description

[0045] Figure 1 This is a flowchart of an efficient thermoelectric decoupling method combining a supercritical CO2 cycle according to the present invention.

[0046] Figure 2 This is a diagram of a highly efficient thermoelectric decoupling system combining a supercritical CO2 cycle according to the present invention;

[0047] Figure 3 This is a schematic diagram of the CO2 cycle workflow of a high-efficiency thermoelectric decoupling system combining a supercritical CO2 cycle according to the present invention;

[0048] Figure 4 This is a schematic diagram of the collaborative operation of a high-efficiency thermoelectric decoupling ejector combined with a steam heat pump and a supercritical CO2 cycle according to the present invention. Detailed Implementation

[0049] The technical solutions of the present invention will now be described in detail with reference to the accompanying drawings.

[0050] like Figures 1-4 As shown, step S1 involves deploying sensors to collect initial system parameters, real-time operating parameters, and historical and target parameters, and performing outlier removal and mean calibration. The initial system parameters include the collection of boiler rated pressure, main steam rated temperature, turbine no-load steam consumption, CO2 compressor initial speed, turbine start-up critical pressure and temperature. The real-time operating parameters include the collection of total load demand, heat load demand, actual main steam temperature, actual sCO2 cycle pressure, ejector inlet and outlet pressures, and working fluid mass flow rate at a frequency of 10Hz. The historical and target parameter collection includes the load history data of the past 720 hours, recording the system rated power generation, baseline heat load, and target temperature rise of the steam heat pump. Outlier removal is performed using the 3σ criterion and mean calibration.

[0051] Step S2 calculates the system coordination reference coefficient based on the calibrated data to quantify the initial compatibility between the steam cycle and the supercritical CO2 cycle. Specifically, it calculates the system coordination reference coefficient based on the calibrated data. The formula is as follows:

[0052] ;

[0053] In the formula, Represents the system's collaborative benchmark coefficient. Indicates the boiler's rated pressure. Indicates the rated temperature of the main steam. This indicates the no-load steam consumption of the steam turbine. Indicates the initial speed of the CO2 compressor. This indicates the critical pressure for starting a supercritical CO2 turbine. This indicates the critical start-up temperature of a supercritical CO2 turbine. Indicates the system's rated power generation. This represents the system's baseline heat load.

[0054] S3 determines the system operating condition, distinguishing between high-fluctuation and stable conditions. It also combines historical data with machine learning algorithms to predict future total load and heat load values. Specifically, it calculates the load fluctuation coefficient based on collected real-time data and system coordination baseline coefficients. Its formula is:

[0055] ;

[0056] In the formula, Indicates the load fluctuation coefficient. Indicates the sampling point number. Indicates the first Total load requirement for each sampling point Indicates the system's rated power generation. Indicates the first Heat load requirements of each sampling point Indicates the system's reference heat load. Represents the system's collaborative benchmark coefficient; when High-fluctuation operating conditions are defined as high-volatility operating conditions, while low-fluctuation conditions are defined as stable operating conditions. By combining historical data with machine learning algorithms, the load value for the next 2 hours can be predicted. , .

[0057] Step S4, based on the operating condition determination results, calculates the supercritical CO2 cycle power generation load ratio under different operating conditions, and adjusts the CO2 compressor speed and steam regulating valve opening according to the ratio value calculated from the predicted value. Specifically, for high-fluctuation operating conditions, a fast response formula is used to calculate the supercritical CO2 cycle power generation load ratio. Its formula is:

[0058] ;

[0059] For steady-state operating conditions: the proportion is calculated using the energy efficiency priority formula. Its formula is:

[0060] ;

[0061] In the formula, This indicates the proportion of supercritical CO2 cycle power generation load under highly fluctuating operating conditions. This indicates the maximum power generation capacity of the supercritical CO2 cycle. Indicates the future Total load forecast at time 10:00 This indicates the actual temperature of the main steam. This indicates the rated total power output of the system. Indicates the future The predicted heat load value at any given time. Indicates the system's reference heat load. Represents the system's collaborative benchmark coefficient. This indicates the proportion of supercritical CO2 cycle power generation load under stable operating conditions; This indicates the maximum power generation capacity of the supercritical CO2 cycle. This indicates the current total load demand of the system. Indicates the average temperature of the main steam. This indicates the current heat load demand. This represents the system's baseline heat load. The equipment is adjusted based on the supercritical CO2 cycle power generation load ratio (λ). When λ increases, the CO2 compressor speed is increased between 1500-6000 r / min to increase the supercritical CO2 cycle power generation ratio; when λ decreases, the compressor speed is reduced to decrease the supercritical CO2 cycle ratio. At low loads, adjustments are needed to ensure... .

[0062] Step S5, combining the supercritical CO2 cycle power generation load ratio, calculates the optimal ejector coefficient and steam heat pump drive power. Based on the calculation results, it adjusts the ejector nozzle opening and steam heat pump operating parameters. Specifically, it combines the ejector parameters from step S1 with those from step S4. Value, calculate the optimal ejector coefficient. Its formula is:

[0063] ;

[0064] In the formula, This represents the optimal ejection coefficient of the injector. This indicates the pressure at the injector drive inlet. This indicates the pressure at the ejector inlet. Indicates the target temperature of the steam heat pump. This indicates the mass flow rate of the low-grade working fluid at the ejector inlet. This indicates the mass flow rate of the high-energy working fluid at the injector drive inlet. This indicates the proportion of supercritical CO2 cycle power generation load;

[0065] when Increase the nozzle opening to increase the injection velocity and momentum of the driving working fluid, thereby improving the suction effect on low-grade ejector working fluid and raising the ejector flow rate ratio to a suitable level. The level; when Reduce the nozzle opening to decrease the driving propellant injection intensity and reduce the proportion of ejector flow.

[0066] Calculate the driving power of the steam heat pump Its formula is:

[0067] ;

[0068] In the formula, Indicates the driving power of the steam heat pump. This indicates the mass flow rate of the mixed working fluid output by the injector. This represents the specific heat capacity at constant pressure of the mixed working fluid. This indicates the target temperature rise of the steam heat pump. This indicates the actual pressure of the supercritical CO2 cycle. This represents the mass flow rate of the supercritical CO2 circulating working fluid. By changing the value as described above, the heat pump output working fluid is distributed, with one path supplying heat users and the other path returning to the sCO2 regenerator to recover waste heat.

[0069] Step S6 collects system output data, calculates the system's optimal comprehensive energy efficiency and energy efficiency deviation, and corrects the supercritical CO2 cycle power generation load ratio and the optimal ejector coefficient based on the calculation results. Specifically, it collects the system's output electrical energy. Thermal energy and fuel input Calculate optimal energy efficiency Its formula is:

[0070] ;

[0071] In the formula, This indicates the optimal overall energy efficiency of the system. This represents the actual electrical power output of the system. This represents the actual thermal power output of the system. Indicates the fuel thermal energy power of the input system. Indicates the system's rated power generation. This represents the system's collaborative baseline coefficient, which determines the optimal energy efficiency. The difference is calculated by comparing it with the current energy consumption. ,like The corrected value for the supercritical CO2 cycle power generation load ratio λ is λ. Specifically Based on the revised Value and energy efficiency deviation Synchronous adjustment By modifying the ejector coefficient to optimize the ejector's effect on low-grade working fluid, the heat recovery efficiency of the steam heat pump is improved, thereby making up for the energy efficiency gap and bringing the system closer to the optimal energy efficiency state.

[0072] The above method recalculates and updates the system coordination baseline coefficients daily based on the full amount of operational data collected that day. This allows subsequent energy efficiency calculations and parameter corrections to adapt to long-term changes such as equipment aging and operating condition fluctuations, maintaining the continuity of closed-loop control.

[0073] A highly efficient thermoelectric decoupling system combining a supercritical CO2 cycle includes a steam cycle unit, a supercritical CO2 cycle unit, a synergistic heat exchange unit, and an intelligent control unit. In the steam cycle unit, the main steam generated by the boiler is transported to the turbine via a steam pipeline. After driving the turbine to perform work, the steam is discharged to the condenser, and the condensate is returned to the boiler via a feedwater pump, forming a closed-loop steam cycle. In the supercritical CO2 cycle unit, CO2 is compressed by a CO2 compressor, then preheated on the low-temperature side of the regenerator, and then flows into a channel connected to the boiler to absorb high-temperature heat energy, becoming high-temperature and high-pressure CO2. This CO2 then enters the supercritical CO2 turbine to perform work, and the low-temperature and low-pressure CO2 discharged from the turbine returns to the regenerator, completing the supercritical CO2 cycle closed loop. The turbine and the supercritical CO2 turbine are both connected to a generator via a coupling to convert mechanical energy into electrical energy and input it into the power grid.

[0074] In the collaborative heat exchange unit, a branch of the boiler extraction steam pipe connects to the ejector as the drive inlet. The condenser drain pipe merges with the outlet pipe of the low-temperature section of the supercritical CO2 circulating regenerator and is then connected to the ejector inlet. The mixed working fluid discharged from the ejector enters the steam heat pump, while the branch of the outlet pipe on the low-temperature side of the supercritical CO2 circulating regenerator also provides low-temperature working fluid to the steam heat pump. The high-temperature working fluid output by the steam heat pump is supplied to the heat user on one side and returned to the inlet of the supercritical CO2 circulating regenerator on the other side. The heated working fluid returns to the front end of the CO2 compressor inlet. The heat user's return water is pumped to the low-grade working fluid inlet of the ejector for waste heat and working fluid recovery.

[0075] The intelligent control unit includes a data acquisition module and a control center optimization control module, implementing the method of any one of claims 1-8. The data acquisition module collects parameters of each pipeline and equipment through sensors such as temperature, pressure, and flow, and transmits them to the control center optimization control module. The control center then regulates the actuators such as water pumps, regulating valves, and regulating mechanisms of each unit through control lines to form a closed loop, ensuring the efficient and stable operation of the system.

[0076] Example 1: This example is adapted to a 30MW cogeneration project, meeting the dynamic demands of an industrial park with a power generation load of 20-28MW and a heating load of 8-12MW. The core equipment rated parameters are as follows: boiler rated pressure 13.7MPa, main steam rated temperature 540℃, turbine rated power 25MW, condenser design pressure 0.005MPa. Supercritical CO2 circulation unit: CO2 compressor initial speed 3000r / min, turbine start-up critical pressure 7.38MPa, temperature 31℃, maximum power generation 10MW. Synergistic heat exchange unit: ejector drive inlet design pressure 1.2MPa, ejector inlet design pressure 0.1MPa, steam heat pump target temperature rise 40℃. Intelligent control unit: sensor sampling frequency 10Hz, built-in LSTM load prediction model, data update cycle 24h. Initial parameters were collected: turbine no-load steam consumption of 15 t / h, system rated power generation of 30 MW, baseline heat load of 10 MW, and supercritical CO2 circulating working fluid mass flow rate of 8 kg / s. After removing outliers in the main steam temperature using the 3σ criterion, the mean value was calibrated.

[0077] Baseline coefficient calculation: Substituting into the formula, the system collaborative baseline coefficient is calculated to be 1.82.

[0078] Load fluctuation coefficient calculation: Data from 100 consecutive sampling points was collected, and the calculated load fluctuation coefficient was 0.27. Since it is less than 0.3, it is determined to be a stable operating condition.

[0079] Load forecast: Based on historical data, the LSTM model predicts a total load of 24MW and a heat load of 10MW for the next 2 hours.

[0080] Calculation and adjustment of the proportion of supercritical CO2 cycle: Under stable operating conditions, the proportion of supercritical CO2 cycle power generation load is calculated to be 0.68; the control center adjusts the speed of CO2 compressor to 3600 r / min and simultaneously reduces the opening of steam regulating valve to 40%.

[0081] Ejector and heat pump parameter adjustment: After collecting relevant pressure and flow data, the optimal ejector coefficient was calculated to be 1.25, and the nozzle opening of the ejector was increased to 65%. The steam heat pump drive power was calculated to be 1840kW. The heat pump output working fluid was distributed in a 7:3 ratio, with 70% supplied to heat users and 30% returned to the sCO2 regenerator.

[0082] The system collects and outputs 23MW of electrical energy, 9.8MW of thermal energy, and 45MW of fuel input, and calculates the optimal comprehensive energy efficiency as 0.62. The current actual comprehensive energy efficiency of the system is 0.73, with an energy efficiency deviation of 11%. The supercritical CO2 cycle power generation load ratio is corrected to 0.74, and the optimal ejector coefficient is adjusted to 1.38.

[0083] After the day's operation ended, the system coordination benchmark coefficient was recalculated based on all the data and found to be 1.79, which was used for the next day's control.

[0084] Under stable operating conditions, the system achieves a power generation load of 23MW and a heating load of 9.8MW, with a comprehensive energy efficiency of 73%, which is 8%-10% higher than that of traditional cogeneration systems. Under high-fluctuation operating conditions, the load tracking delay is less than 2s, and the supercritical CO2 cycle power generation load accounts for 0.61% under low load conditions.

Claims

1. A high-efficiency thermoelectric decoupling method combined with a supercritical CO2 cycle, characterized in that, The method comprises the following steps: S1: arranging sensors, collecting system initial parameters, real-time operation parameters, and historical and target parameters, and performing outlier elimination and calibration on the parameters; S2: calculating system coordination reference coefficients based on the calibrated data, and quantifying the initial adaptability of the steam cycle and the supercritical CO2 cycle; S3: determining the system working condition, distinguishing between high fluctuation working conditions and stable working conditions, and predicting future total load and heat load values by combining historical data and machine learning algorithms; S4: according to the working condition determination result, distinguishing and calculating the supercritical CO2 cycle power generation load proportion under different working conditions, and adjusting the CO2 compressor speed and the steam regulating valve opening degree according to the proportion value calculated by the predicted value; S5: combining the supercritical CO2 cycle power generation load proportion, calculating the optimal injection coefficient of the ejector and the steam heat pump driving power, and adjusting the nozzle opening degree of the ejector and the operation parameters of the steam heat pump according to the calculation result; S6: collecting system output data, calculating the optimal comprehensive energy efficiency and energy efficiency deviation of the system, and correcting the supercritical CO2 cycle power generation load proportion and the optimal injection coefficient of the ejector according to the calculation result.

2. The high-efficiency thermoelectric decoupling method combined with a supercritical CO2 cycle according to claim 1, characterized in that, Step S1: Arrange sensors, collect system initial parameters, real-time operation parameters, and historical and target parameters, and perform outlier elimination and mean value calibration on the parameters. The system initial parameters include the rated pressure of the boiler, the rated temperature of the main steam, the steam turbine air consumption, the initial speed of the CO2 compressor, the critical pressure and temperature of the turbine start, and the real-time operation parameters include the total load demand, the heat load demand, the actual temperature of the main steam, the actual pressure of the sCO2 cycle, the inlet and outlet pressure of the ejector, and the mass flow rate of the working medium. The historical and target parameter collection includes the load history data of the past 720 hours, records the rated power generation power of the system, the reference heat load, and the target temperature rise of the steam heat pump, and the outlier elimination adopts the 3σ criterion and the mean value calibration.

3. The highly efficient thermoelectric decoupling method combined with supercritical CO2 cycle according to claim 1, characterized in that, Step S2 calculates the system synergy reference coefficient based on the calibrated data, quantifies the initial adaptability of the steam cycle and the supercritical CO2 cycle, specifically, calculates the system synergy reference coefficient based on the calibrated data The formula is as follows: ； In the formula, represents the system coordination reference coefficient, represents the boiler rated pressure, represents the main steam rated temperature, represents the turbine idle steam consumption, represents the CO2 compressor initial rotating speed, represents the supercritical CO2 turbine start-up critical pressure, represents the supercritical CO2 turbine start-up critical temperature, represents the system rated power generation, represents the system reference thermal load.

4. The highly efficient thermoelectric decoupling method combined with supercritical CO2 cycle according to claim 1, characterized in that, S3 determines the system working condition, distinguishes between high fluctuation working condition and stable working condition, and combines historical data and machine learning algorithm to predict future total load and heat load value, which specifically includes calculating load fluctuation coefficient based on collected real-time data and system cooperative benchmark coefficient The formula is: ； In the formula, represents the load fluctuation coefficient, represents the sampling point sequence number, represents the total load demand of the sampling point, represents the system rated power generation, represents the thermal load demand of the sampling point, represents the system reference thermal load, represents the system cooperative reference coefficient; when is a high fluctuation working condition, otherwise it is a stable working condition; Predicting future 2 hours load value in combination with historical data and machine learning algorithm 、 .

5. The highly efficient thermoelectric decoupling method combined with supercritical CO2 cycle according to claim 1, characterized in that, S4 According to the working condition judgment result, the supercritical CO2 cycle power generation load proportion under different working conditions is distinguished, and the CO2 compressor speed and the steam regulating valve opening degree are adjusted according to the proportion value calculated according to the predicted value. Specifically, the sCO2 cycle power generation load proportion is calculated by using a fast response formula under high fluctuation conditions The formula is: ； For stable working condition: the energy efficiency priority formula is used to calculate the proportion The formula is: ； In the formula, represents the supercritical CO2 cycle power generation load ratio under high fluctuation conditions, represents the maximum power generation of the supercritical CO2 cycle, represents the total load prediction value at the future time, represents the actual temperature of the main steam, represents the total power generation power rating of the system, represents the thermal load prediction value at the future time, represents the system reference thermal load, represents the system coordination reference coefficient, represents the supercritical CO2 cycle power generation load ratio under stable conditions; represents the maximum power generation of the supercritical CO2 cycle, represents the total load demand of the current system, represents the average temperature of the main steam, represents the current thermal load demand, represents the system reference thermal load; the equipment is adjusted according to the supercritical CO2 cycle power generation load ratio λ value, when λ increases, the CO2 compressor speed is increased between 1500-6000 r / min, and the sCO2 cycle power generation ratio is increased; when λ decreases, the compressor speed is decreased to decrease the sCO2 cycle ratio, and when the load is low, the is ensured by adjustment.

6. The highly efficient thermoelectric decoupling method combined with supercritical CO2 cycle according to claim 1, characterized in that, Step S5 combines the supercritical CO2 cycle power generation load ratio to calculate the optimal ejector coefficient of the ejector and the steam heat pump driving power. According to the calculation result, the nozzle opening degree of the ejector and the operation parameters of the steam heat pump are adjusted. Specifically, the ejector parameters of step S1 and the values of step S4 are combined to calculate the optimal ejector coefficient of the ejector , and the formula is: ； In the formula, represents the optimal entrainment coefficient of the ejector, represents the pressure of the drive inlet of the ejector, represents the pressure of the entrainment inlet of the ejector, represents the target temperature of the steam heat pump, represents the mass flow of the low-grade working medium at the entrainment inlet of the ejector, represents the mass flow of the high-energy working medium at the drive inlet of the ejector, represents the proportion of supercritical CO2 cycle power generation load; when Increase the nozzle opening to increase the injection velocity and momentum of the driving working fluid, thereby improving the suction effect on low-grade ejector working fluid and raising the ejector flow rate ratio to a suitable level. The level; when Reduce the nozzle opening to decrease the driving propellant injection intensity and reduce the proportion of ejector flow. Computing steam heat pump drive power The formula is: ； wherein, represents the vapor heat pump driving power, represents the ejector output mixed working medium mass flow rate, represents the specific heat capacity of the mixed working medium at constant pressure, represents the vapor heat pump target temperature rise, represents the supercritical CO2 cycle actual pressure, represents the supercritical CO2 cycle working medium mass flow rate; by changing the numerical value of the above, the heat pump output working medium is distributed, one of which supplies the heat user, and the other returns to the sCO2 regenerator to recover waste heat.

7. The highly efficient thermoelectric decoupling method combined with supercritical CO2 cycle according to claim 1, characterized in that, Step S6 collects system output data, calculates system optimal comprehensive energy efficiency and energy efficiency deviation, and corrects supercritical CO2 cycle power generation load proportion and ejector optimal entrainment coefficient according to the calculation results. Specifically, the system output electric energy , thermal energy and fuel input are collected, and the optimal energy efficiency is calculated, and the formula is: ； In the formula, represents the optimal comprehensive energy efficiency of the system, represents the actual output electric energy power of the system, represents the actual output thermal energy power of the system, represents the fuel thermal energy power input into the system, represents the rated power generation of the system, represents the system coordination reference coefficient, and the optimal energy efficiency is The difference between the current energy consumption is calculated to obtain the difference , if , the correction supercritical CO2 cycle power generation load proportion λ value is , specifically ; based on the corrected value and the energy efficiency deviation , the is adjusted synchronously, the injection coefficient is corrected to optimize the injection effect of the ejector on the low-grade working medium, improve the thermal energy recovery efficiency of the steam heat pump, and then make up the energy efficiency gap, so that the system approaches the optimal energy efficiency state.

8. The highly efficient thermoelectric decoupling method combined with supercritical CO2 cycle according to claim 1, characterized in that, The method recalculates and updates the system coordination benchmark coefficient on the basis of full quantity operation data collected on the day Make the subsequent energy efficiency calculation and parameter correction adapt to the long-term changes such as equipment aging and working condition fluctuation, and maintain the continuity of closed-loop regulation.

9. A high-efficiency thermal-electric decoupling system combined with a supercritical CO2 cycle, comprising a steam cycle unit, a supercritical CO2 cycle unit, a cooperative heat exchange unit, and an intelligent control unit. In the steam cycle unit, the main steam generated by the boiler is delivered to the steam turbine through the steam pipeline, and after the steam turbine does work, the steam is discharged to the condenser, and the condensed water is sent back to the boiler by the feed water pump to form a closed loop of the steam cycle. In the supercritical CO2 cycle unit, CO2 is compressed by the CO2 compressor, then preheated in the low-temperature side of the regenerator, and then flows into the channel connected with the boiler to absorb high-temperature heat energy, becomes high-temperature and high-pressure CO2, and then enters the supercritical CO2 turbine to do work. The low-temperature and low-pressure CO2 discharged from the turbine returns to the regenerator, completing a closed loop of the supercritical CO2 cycle. The steam turbine and the supercritical CO2 turbine are connected to the generator through the shaft coupling to convert mechanical energy into electrical energy and input into the power grid. In the synergistic heat exchange unit, the boiler extraction steam pipeline is branched to connect the ejector as the driving inlet, the condenser drainage pipeline is combined with the outlet pipeline of the low-temperature section of the supercritical CO2 circulation regenerator, and then connected to the injection inlet of the ejector. The mixed working medium discharged from the ejector enters the steam heat pump, and the outlet pipeline of the low-temperature side of the supercritical CO2 circulation regenerator is also branched to provide low-temperature working medium to the steam heat pump. The high-temperature working medium output by the steam heat pump is supplied to the heat user in one way, and is returned to the inlet of the supercritical CO2 circulation regenerator in the other way. The working medium after being warmed up returns to the front end of the inlet of the CO2 compressor. The return water of the heat user is connected to the low-grade working medium inlet of the ejector through the water pump to recover the waste heat and working medium.

10. The high-efficiency heat-electricity decoupling system combined with a supercritical CO2 cycle according to claim 9, wherein the intelligent control unit comprises a data acquisition module and a control center optimization control module, and the method according to any one of claims 1-8 is realized. The data acquisition module acquires parameters of each pipeline and device through temperature, pressure, flow and other sensors, and transmits the parameters to the control center optimization control module. The control center controls the actuators such as water pumps, regulating valves and adjusting mechanisms of each unit through control lines to form a closed loop, thereby ensuring efficient and stable operation of the system.

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