Evaluation method for energy efficiency of oxirane-sCO2 energy storage power generation under variable working condition efficiency

Abstract

The invention discloses an oxirane-sCO2 energy storage power generation energy efficiency evaluation method under variable working condition efficiency. The method comprises the following steps: S1, collecting system operation key parameters through a high-precision sensor group, and calculating the credibility of any key parameter; s2, calculating load fluctuation intensity I < negative > and waste heat pulse frequency f < residual > of the ethylene oxide reaction kettle; s3, dynamically coordinating the guide vane opening and the real-time rotating speed of the supercritical CO2 turbine, and matching with the intermittent grade of the ethylene oxide reaction kettle; s4, weight coefficients of different types of losses are calculated, and the total loss of the energy storage power generation system is calculated according to the weight coefficients of the different types of losses; s5, calculating the relative deviation delta X of any constraint index according to the effective key parameters; and S6, formulating an emergency response mechanism, and immediately triggering the emergency response mechanism when the energy storage power generation system has an abnormal working condition. Accurate expression, grading adaptation and the like of the energy efficiency of the energy storage power generation system can be achieved, and the energy efficiency of the system is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of ethylene oxide production and new energy storage power generation, and particularly relates to a method for evaluating the energy efficiency of ethylene oxide-sCO2 energy storage power generation under variable working conditions and low efficiency. BACKGROUND

[0002] At present, with the promotion of the double carbon target, the coupling technology of industrial waste heat recovery and new energy storage power generation has become one of the core directions of energy saving and consumption reduction in the chemical industry. Among them, the medium-high temperature waste heat of 200-400℃ is generated in the preparation process of ethylene oxide, which accounts for 40%-50% of the total energy consumption of ethylene oxide production, and has very high recycling value. The supercritical CO2 (sCO2) energy storage power generation system has the advantages of adapting to this temperature range and high energy storage density, and becomes the preferred technical path for recycling this type of waste heat.

[0003] However, the preparation of ethylene oxide has a fixed running cycle, and the load fluctuation range is 30%-100% of the rated load. The waste heat output is intermittent in a pulse mode. The existing technology has several key problems in the energy efficiency evaluation of this scene, for example: quantitative evaluation is missing, and fluctuation characteristics cannot be accurately captured; single adaptation strategy, significant system coupling deviation; no hierarchical control, energy efficiency fluctuates sharply; low load adaptation failure, continuous power supply is blocked; targeted optimization is missing, and measures are blind and inefficient, which makes it difficult to meet the actual application requirements. SUMMARY

[0004] To solve the above problems, the purpose of the present application is to provide a method for evaluating the energy efficiency of ethylene oxide-sCO2 energy storage power generation under variable working conditions and low efficiency, which can realize the accurate expression and hierarchical adaptation of the energy efficiency of the energy storage power generation system, and improve the energy efficiency of the system.

[0005] The following technical solutions are realized: A method for evaluating the energy efficiency of ethylene oxide-sCO2 energy storage power generation under variable working conditions and low efficiency, the method comprising the following steps: S1, collecting system operation key parameters through a high-precision sensor group in the energy storage power generation system, and calculating the credibility of any key parameter collected according to a data validity verification formula, and transmitting the effective key parameters to a data acquisition and calculation core; S2, the data acquisition and calculation core calculates the load fluctuation intensity I 负 and the waste heat pulse frequency f 余 of the ethylene oxide reactor according to the collected key parameters, and calculates the energy efficiency of the energy storage power generation system according to the load fluctuation intensity I 负 and the waste heat pulse frequency f 余Determine the intermittence level of the ethylene oxide reactor; S3, dynamically coordinate the guide vane opening and real-time speed of the supercritical CO2 turbine according to the guide vane opening and speed adaptation formula, and determine the running level of the supercritical CO2 turbine according to the value of the real-time speed, and match it with the intermittence level of the ethylene oxide reactor; S4, the data acquisition and calculation core calculates the weight coefficients of different types of exergy losses according to the acquired effective key parameters, and calculates the total exergy loss E of the energy storage and power generation system according to the weight coefficients of different types of exergy losses ex,l ; S5, calculate the relative deviation ΔX of any constraint index according to the acquired effective key parameters, when the relative deviation ΔX of any constraint index exceeds the set threshold value, the energy storage and power generation system immediately starts the protection mechanism; S6, develop an emergency response mechanism, when the energy storage and power generation system appears abnormal working condition, immediately trigger the emergency response mechanism, calculate the parameter feedback correction coefficient K of the current abnormal working condition according to the feedback correction formula 修 , and feed back the parameter feedback correction coefficient K 修 to step S1. The method of the present application can significantly improve the intermittence adaptation precision, turbine variable condition stability and energy efficiency, and exergy loss calculation precision and other beneficial effects.

[0006] Preferably, in step S1, the high-precision sensor group acquires parameters according to the set sampling frequency, and when the proportion of effective parameters in the acquired key parameters is less than the set percentage, the invalid parameters trigger sensor self-checking. Through the setting of the high-precision sensor group, accurate and reliable data source can be provided for subsequent calculation.

[0007] Preferably, in step S1, the data validity verification formula is: , R 信 is the data reliability coefficient of any parameter, x 实 is the real-time acquisition value of any parameter, x 均 is the sliding average value of any parameter within a specified time, and x 阈 is the rated threshold value of any parameter. The acquired key parameters are verified for effectiveness in order to provide accurate and reliable data source for subsequent calculation.

[0008] Preferably, in step S2, the load fluctuation intensity I 负 is calculated by the formula: , and the waste heat pulse frequency f 余 is calculated by the formula: f 余 =N / T, wherein T is the running period of the ethylene oxide reactor, τ is the time variable, S 负 (τ) is the load of the ethylene oxide reactor at time τ, and N is the number of times that the waste heat power fluctuation exceeds the set range within T. The load fluctuation intensity I 负 and the waste heat pulse frequency f 余, which can realize accurate and adaptive matching of heat source fluctuation.

[0009] Preferably, in step S3, the guide vane opening degree and the rotation speed adaptation formula is: α = e*n+u, α is the turbine guide vane opening degree, e is the guide vane opening degree and the rotation speed adaptation coefficient, n is the real-time rotation speed of the turbine, and u is the basic guide vane opening degree compensation value. Through dynamic coordination of the turbine guide vane opening degree and the rotation speed, the intermittent level can be matched, and stable operation of the turbine under variable conditions can be realized.

[0010] Preferably, in steps S2 and S3, the ethylene oxide reactor intermittent level includes level I, level II, level III and level IV, and the supercritical CO2 turbine operation level includes level A, level B, level C and level D, wherein level I corresponds to level A, level II corresponds to level B, level III corresponds to level C, and level IV corresponds to level D. By matching the real-time rotation speed of the turbine with the ethylene oxide reactor intermittent level, the influence of load fluctuation on system energy efficiency can be effectively reduced.

[0011] Preferably, in step S4, the weight coefficient calculation formula of different types of 㶲 loss is: i =q+r*n-d*S 负 , and the total 㶲 loss E ex,l of the system is calculated by the formula: , wherein w i is the weight coefficient of any type of 㶲 loss, i=1, 2, 3 or 4, respectively representing four types of 㶲 loss, q is the basic weight value, r is the turbine rotation speed influence coefficient, d is the ethylene oxide reactor load influence coefficient, S 负 is the ethylene oxide reactor load, E ex,li is the basic value of any type of 㶲 loss, and k 耦合 is the coupling correction term of any type of 㶲 loss. By calculating the weight coefficient of different types of 㶲 loss, the system invalid loss can be reduced and the energy efficiency can be improved.

[0012] Preferably, in step S5, the relative deviation ΔX of any constraint index is calculated by: ΔX=|X 实 -X 阈 | / X 阈 ×100%, wherein X 实 is the real-time value of any constraint index, and X 阈 is the safety threshold value of any constraint index. By monitoring the constraint index, equipment damage caused by over-threshold operation can be further avoided.

[0013] Preferably, in step S6, the feedback correction formula is: the parameter feedback correction coefficient K 修 =1+0.02*ΔE ex,l , wherein ΔE ex,lThe system total relative change rate of loss is set, and through setting an emergency response mechanism, continuous optimization can be realized, abnormal conditions can be coped with, and continuous operation of the system can be ensured.

[0014] Preferably, the components of the energy storage power generation system include an ethylene oxide reactor, a waste heat buffer tank, a waste heat delivery pump, a waste heat distribution valve group, a hot water storage boiler, a CO2 thermocline storage tank, a low-pressure sCO2 storage tank, an sCO2 booster pump, a cooperative heat exchange machine, a supercritical CO2 turbine, a high-pressure sCO2 storage tank, an expander generator, a regenerative heat exchanger, a tube-shell cooler, a comprehensive intelligent calculation control group, a circulating water cooler, a circulating water pump and a hot water lithium bromide refrigeration subsystem. Through the structural components of the energy storage power generation system, an ethylene oxide-sCO2 energy storage power generation energy efficiency evaluation method under variable working condition and high efficiency can be realized.

[0015] Compared with the prior art, the present application has the following beneficial effects: The technical scheme of the present application quantifies the severity and frequency of heat source fluctuations into calculable load fluctuation intensity and waste heat pulse frequency, which can realize accurate and adaptive matching of heat source fluctuations; the real-time speed of the turbine is matched with the intermittency level of the ethylene oxide reactor, which can effectively reduce the influence of load fluctuation on system energy efficiency and realize stable operation of the turbine under variable working conditions; accurate calculation of loss distribution can reduce system invalid loss and improve energy efficiency; at the same time, the energy storage power generation system has strong flexible adaptation capability, without the need for large-scale modification of hardware equipment, only the adjustment of intermittent index threshold and turbine grading parameters is needed, which can adapt to different ethylene oxide production cycles and turbine specifications, thereby adapting to the industrial waste heat energy storage power generation demand of different scales in the chemical and energy industries; and for abnormal working conditions such as sudden change of intermittency level and equipment failure, the system emergency response time is less than 1 second, through rapid switching of operation level and locking of core parameters, the system can maintain continuous and stable operation. BRIEF DESCRIPTION OF DRAWINGS

[0016] Fig. 1 The flowchart of the ethylene oxide-sCO2 energy storage power generation energy efficiency evaluation method under variable working condition and high efficiency is shown in the figure. Fig. 2 The structural schematic diagram of the energy storage power generation system is shown in the figure. The components of the energy storage power generation system include an ethylene oxide reactor 1, a waste heat buffer tank 2, a waste heat delivery pump 3, a waste heat distribution valve group 4, a CO2 thermocline storage tank 5, a low-pressure sCO2 storage tank 6, an sCO2 booster pump 7, a cooperative heat exchange machine 8, a supercritical CO2 turbine 9, a high-pressure sCO2 storage tank 10, an expander generator 11, a regenerative heat exchanger 12, a tube-shell cooler 13, a comprehensive intelligent calculation control group 14, a circulating water cooler 15, a circulating water pump 16, a hot water lithium bromide refrigeration subsystem 17 and a hot water storage boiler 18. DETAILED DESCRIPTION

[0017] The technical solutions in the embodiments of the present application will be described in detail below. Figs. 1-2 The technical solutions in the embodiments of the present application will be described in detail below.

[0018] As Fig. 1 shown in the flowchart of the method for evaluating the energy efficiency of the ethylene oxide-sCO2 energy storage power generation system under variable working conditions, first, the high-precision sensor group collects the key parameters of the system operation and calculates the reliability of any key parameter; then, the load fluctuation intensity I 负 and the waste heat pulse frequency f 余 of the ethylene oxide reactor are calculated; then, the guide vane opening and real-time speed of the supercritical CO2 turbine are dynamically coordinated and matched with the intermittency level of the ethylene oxide reactor; then, the weight coefficients of different types of energy loss are calculated, and the total energy loss of the energy storage power generation system is calculated according to the weight coefficients of different types of energy loss; at the same time, the relative deviation ΔX of any constraint index is calculated according to the effective key parameters; finally, an emergency response mechanism is developed, which is triggered immediately when the energy storage power generation system appears abnormal working conditions, so that the method can realize precise expression and hierarchical adaptation of the energy efficiency of the energy storage power generation system, and improve the system energy efficiency.

[0019] The method specifically includes the following steps: S1, collecting the key parameters of the system operation by the high-precision sensor group in the energy storage power generation system, and calculating the reliability of any key parameter according to the data validity verification formula, and transmitting the effective key parameters to the data acquisition and calculation core.

[0020] Among them, the collected key parameters include: real-time load of the ethylene oxide reactor, instantaneous flow of the waste heat medium, temperature of the waste heat medium, mass flow of sCO2 working medium, inlet pressure of the supercritical CO2 turbine, inlet temperature of the supercritical CO2 turbine, outlet pressure of the supercritical CO2 turbine, outlet temperature of the supercritical CO2 turbine, temperature of the waste heat buffer tank, pressure of the high-pressure sCO2 storage tank, and pressure of the low-pressure sCO2 storage tank.

[0021] In this embodiment, in step S1, the high-precision sensor group collects each parameter according to the set sampling frequency, and when the proportion of effective parameters in the collected key parameters is less than the set percentage, the invalid parameters trigger the sensor self-checking, so that through the setting of the high-precision sensor group, accurate and reliable data source can be provided for subsequent calculation.

[0022] In this embodiment, in step S1, the data validity verification formula is: , R 信 is the data reliability coefficient of any parameter, x 实 is the real-time collection value of any parameter, x 均Sliding average value of any parameter within a specified time, x 阈 Threshold value of any parameter; wherein, R 信 is in the range of [0.8-1.0], and when R 信 is greater than or equal to 0.9, it indicates that the current collected key parameter is valid, thereby verifying the validity of the collected key parameter so as to provide accurate and reliable data source for subsequent calculation.

[0023] S2, the data acquisition and calculation core calculates the load fluctuation intensity I 负 and the waste heat pulse frequency f 余 of the ethylene oxide reactor according to the collected key parameters, and determines the intermittency level of the ethylene oxide reactor according to the load fluctuation intensity I 负 and the waste heat pulse frequency f 余 .

[0024] In this embodiment, in step S2, the load fluctuation intensity I 负 is calculated by the following formula: , and the waste heat pulse frequency f 余 is calculated by the following formula: f 余 =N / T, wherein T is the operation period of the ethylene oxide reactor, τ is a time variable, S 负 (τ) is the load of the ethylene oxide reactor at time τ, and N is the number of times that the waste heat power fluctuation exceeds the set range within a period T; wherein, in a complete operation period, the average value I 负 of the absolute value of the load change rate of the ethylene oxide reactor is greater, indicating that the load change of the ethylene oxide reactor is more intense; at the same time, in the period T, the value of f 余 is higher, indicating that the waste heat output of the ethylene oxide reactor is unstable, and the energy storage and power generation system needs to adjust the operation state more frequently. The method of the present application quantifies the intensity and frequency of the heat source fluctuation into the calculable load fluctuation intensity and waste heat pulse frequency, which can realize accurate and adaptive matching of the heat source fluctuation.

[0025] S3, dynamically coordinating the guide vane opening and the real-time speed of the supercritical CO2 turbine according to the guide vane opening and speed adaptation formula, and determining the operation level of the supercritical CO2 turbine according to the value of the real-time speed, and matching the intermittency level of the ethylene oxide reactor.

[0026] In this embodiment, in step S3, the guide vane opening and speed adaptation formula is: α=e*n+u, wherein α is the guide vane opening of the turbine, e is the adaptation coefficient of the guide vane opening and the speed, n is the real-time speed of the turbine, and u is the basic guide vane opening compensation value; wherein the turbine speed switching time t 切 ≤|n 终 -n 初 | / 500, n 终n is the target operating speed of the turbine. 初 The speed is the current operating speed of the turbine, and 500 is the maximum speed adjustment rate. This can prevent sudden speed changes from causing excessive vibration. By dynamically coordinating the turbine guide vane opening and speed, stable operation of the turbine under varying operating conditions can be achieved.

[0027] In this embodiment, in steps S2 and S3, the intermittent operation levels of the ethylene oxide reactor include Level I, Level II, Level III, and Level IV, and the operating levels of the supercritical CO2 turbine include Level A, Level B, Level C, and Level D. Level I corresponds to Level A, Level II to Level B, Level III to Level C, and Level IV to Level D. Level A corresponds to a turbine speed range of 15,000-18,000 r / min, Level B to 10,000-15,000 r / min, Level C to 5,000-10,000 r / min, and Level D to 3,000-5,000 r / min. By matching the real-time turbine speed with the intermittent operation level of the ethylene oxide reactor, the impact of load fluctuations on system energy efficiency can be effectively reduced.

[0028] S4. Data Acquisition and Calculation Core: Based on the acquired effective key parameters, the weighting coefficients for different types of losses are calculated, and the total loss E of the energy storage power generation system is calculated based on these weighting coefficients. ex,l .

[0029] In this embodiment, in step S4, the formula for calculating the weighting coefficients for different types of loss is: w i =q+r*nd*S 负 Total system loss E ex,l The calculation formula is: , where w i For any type of loss, i = 1, 2, 3, or 4, representing the four loss types respectively; q is the basic weight value; r is the turbine speed influence coefficient; d is the ethylene oxide reactor load influence coefficient; S 负 For the ethylene oxide reactor load, E ex,li k is the base value for loss of any type. 耦合 This is a coupling correction term for any type of loss; where i=1 represents flow friction loss, i=2 represents mechanical friction loss, i=3 represents coupling matching loss, and i=4 represents heat dissipation leakage loss. When the ratio of any type of loss to the total system loss exceeds a set threshold, it indicates that the current type of loss is the main source of loss under the current operating condition, and corresponding optimization operations will be triggered. By calculating the weight coefficients of different types of losses, the ineffective losses of the system can be reduced in a targeted manner, and energy efficiency can be improved.

[0030] S5. Calculate the relative deviation ΔX of any constraint index based on the collected valid key parameters. When the relative deviation ΔX of any constraint index exceeds the set threshold, the energy storage power generation system immediately activates the protection mechanism.

[0031] Specifically, in step S5, the relative deviation ΔX of any constraint index is calculated as follows: ΔX = |X 实 -X 阈 | / X 阈 ×100%, where X 实 Let X be the real-time value of any constraint index. 阈 The safety threshold is set for any constraint index; the core constraint indexes include the temperature of the waste heat buffer tank, the vibration amplitude of the turbine, and the turbine efficiency. For example, when the turbine efficiency is lower than the threshold, the sCO2 parameter is adapted first. By monitoring the constraint indexes, this invention can further avoid equipment damage caused by operating beyond the threshold.

[0032] S6. Establish an emergency response mechanism. When the energy storage power generation system experiences abnormal operating conditions, the emergency response mechanism should be triggered immediately, and the parameter feedback correction coefficient K for the current abnormal operating condition should be calculated according to the feedback correction formula. 修 And feed back the parameter correction coefficient K 修 Feedback is sent to step S1.

[0033] The feedback correction formula is: parameter feedback correction coefficient K 修 =1+0.02*ΔE ex,l , where ΔE ex,l This represents the relative change rate of the total system loss. Abnormal operating conditions include sudden changes in turbine operating level, turbine failure, and system algorithm anomalies. When a sudden change in turbine operating level occurs, the turbine will switch to level D within a short time and activate the backup electric pump. When a turbine failure occurs, the CO2 flow rate will be adjusted for adaptation. When the system algorithm malfunctions, a simplified loss calculation formula will be switched. By setting up an emergency response mechanism, continuous optimization can be achieved to cope with abnormal operating conditions and ensure continuous system operation.

[0034] like Fig. 2 The diagram shows a schematic of an energy storage power generation system. The system comprises an ethylene oxide reactor, a waste heat buffer tank, a waste heat transfer pump, a waste heat distribution valve group, a hot water thermal storage boiler, a CO2 inclined temperature layer storage tank, a low-pressure sCO2 storage tank, a sCO2 booster pump, a synergistic heat exchanger, a supercritical CO2 turbine, a high-pressure sCO2 storage tank, an expander generator, a regenerative heat exchanger, a shell-and-tube cooler, an integrated intelligent computing control group, a circulating water cooler, a circulating water pump, and a hot water lithium bromide refrigeration subsystem. By understanding the structural components of this energy storage power generation system, an energy efficiency evaluation method for ethylene oxide-sCO2 energy storage power generation under varying operating conditions can be implemented, thereby improving system energy efficiency.

[0035] Specifically, the ethylene oxide reactor is used to output waste heat; the waste heat buffer tank is used to store, buffer and stabilize the waste heat; the waste heat delivery pump is used to drive the circulation of the waste heat medium; the waste heat distribution valve group is used to adjust the flow direction of the waste heat; the hot water storage boiler is used to store the waste heat output by the chemical reactor; the CO2 thermocline storage tank is used to store CO2 of different densities; the low-pressure sCO2 storage tank is used to store low-pressure sCO2; the sCO2 booster pump is used to pressurize the low-pressure sCO2; the cooperative heat exchanger is used to adapt to different heat exchange media; the supercritical CO2 turbine is used to take sCO2 as the working medium, convert the fluid energy of sCO2 into mechanical energy, and use the generated mechanical energy to generate electricity in the generator; the high-pressure sCO2 storage tank is used to store high-pressure sCO2; the expander generator is coaxially connected with the supercritical CO2 turbine and is used to drive the generator to generate electricity; the regenerative heat exchanger is used to recover the waste heat of the CO2 gas at the turbine outlet and heat the low-pressure sCO2; the tube-shell cooler is used to further cool the sCO2; the comprehensive intelligent calculation control group includes a high-precision sensor group, a data acquisition and calculation core, and an energy efficiency evaluation and optimization server, wherein the energy efficiency evaluation and optimization server is used to output adaptive scheduling and optimization signals; the circulating water cooler is used to cool the CO2 gas at the outlet of the supercritical CO2 turbine to a temperature corresponding to the current season; the circulating water pump is used to drive the circulating water to flow between the circulating water cooler and the hot water lithium bromide refrigeration subsystem; the hot water lithium bromide refrigeration subsystem includes a lithium bromide refrigeration system for refrigeration by lithium bromide, a cold tank for storing the cold energy generated by the lithium bromide refrigeration system, and a cooling heat exchanger for transferring the cold energy generated by the lithium bromide refrigeration system to the circulating water.

[0036] To sum up, the present application can realize precise and adaptive matching of heat source fluctuation by quantifying the severity and frequency of heat source fluctuation into calculable load fluctuation intensity and waste heat pulse frequency; can effectively reduce the influence of load fluctuation on system energy efficiency by matching the real-time speed of the turbine with the intermittency level of the ethylene oxide reactor, and realize stable operation of the turbine under variable conditions; can reduce system invalid loss and improve energy efficiency by accurately calculating the loss distribution; at the same time, the energy storage and power generation system has strong flexible adaptation ability, without the need for large-scale hardware equipment modification, only by adjusting the intermittency index threshold and turbine grading parameters, it can adapt to different ethylene oxide production cycles and turbine specifications, thereby adapting to the industrial waste heat energy storage and power generation needs of different scales in the chemical and energy industries; and for abnormal working conditions such as intermittency level mutation and equipment failure, the system emergency response time is less than 1 second, through strategies such as rapid switching of operation levels and locking of core parameters, the system can maintain continuous and stable operation, which has significant progress.

[0037] The above examples only illustrate the technical idea of the present application, and cannot be used to limit the protection scope of the present application. Any modification made according to the technical idea of the present application on the basis of the technical scheme falls within the protection scope of the present application.

Claims

1. A variable working condition and efficiency evaluation method for an ethylene oxide-sCO2 energy storage and power generation system, characterized in that, The method comprises the following steps: S1, collecting system operation key parameters through high-precision sensor groups in the energy storage power generation system, and calculating the credibility of any key parameters collected according to a data validity verification formula, and transmitting the effective key parameters to a data collection and calculation core; S2, the data acquisition and calculation core calculates the load fluctuation intensity I of the ethylene oxide reactor according to the key parameters collected 负 and the waste heat pulse frequency f 余 , and determines the intermittent level of the ethylene oxide reactor according to the load fluctuation intensity I 负 and the waste heat pulse frequency f 余 ; S3, dynamically coordinating the guide vane opening degree and the real-time rotating speed of the supercritical CO2 turbine according to a guide vane opening degree and rotating speed adaptation formula, and determining the operation level of the supercritical CO2 turbine according to the value of the real-time rotating speed, and matching the intermittent level of the ethylene oxide reaction kettle at the same time; S4, the data acquisition and calculation core calculates the weight coefficients of different types of energy loss according to the effective key parameters collected, and calculates the total energy loss E of the energy storage power generation system according to the weight coefficients of different types of energy loss ex,l ; S5, calculating the relative deviation ΔX of any constraint index according to the collected effective key parameters, and when the relative deviation ΔX of any constraint index exceeds the set threshold value, the energy storage power generation system immediately starts the protection mechanism; S6, form an emergency response mechanism, when the abnormal working condition of the energy storage power generation system appears, trigger the emergency response mechanism immediately, calculate the parameter feedback correction coefficient K of the current abnormal working condition according to the feedback correction formula 修 And feed back the parameter feedback correction coefficient K 修 To step S1.

2. The method according to claim 1, wherein the method is an evaluation method of the efficiency of the power generation using the stored energy of the ethylene oxide-sCO2 under the variable working conditions, characterized in that, In step S1, the high-precision sensor group collects parameters according to the set sampling frequency, and when the proportion of effective parameters in the collected key parameters is lower than the set percentage, the invalid parameters trigger sensor self-checking.

3. The method according to claim 1, wherein the method is an evaluation method of the efficiency of the power generation using the stored energy of the ethylene oxide-sCO2 under the variable working conditions, characterized in that, In step S1, the data validity verification formula is: , R 信 is the data reliability coefficient of an arbitrary parameter, x 实 is the real-time collection value of an arbitrary parameter, x 均 is the sliding average value of an arbitrary parameter within a specified time, x 阈 is the rated threshold value of an arbitrary parameter.

4. The method according to claim 1, wherein the method is an evaluation method of the efficiency of the power generation using the stored energy of the ethylene oxide-sCO2 under the variable working conditions, characterized in that, In step S2, the load fluctuation intensity I 负 The calculation formula is: , the waste heat pulse frequency f 余 The calculation formula is: f 余 =N / T, wherein T is the operating period of the ethylene oxide reactor, τ is a time variable, S 负 (S(τ)) is the load of the ethylene oxide reactor at time τ, and N is the number of times that the waste heat power fluctuation exceeds the set range within the surrounding T.

5. The method according to claim 1, wherein the method is an evaluation method of the efficiency of the power generation using the stored energy of the ethylene oxide-sCO2 under the variable working conditions, characterized in that, In step S3, the guide vane opening degree and rotating speed adaptation formula is: α = e * n + u, α is the turbine guide vane opening degree, e is the guide vane opening degree and rotating speed adaptation coefficient, n is the real-time rotating speed of the turbine, and u is the basic guide vane opening degree compensation value.

6. The method according to claim 1, wherein the method is an evaluation method of the efficiency of the power generation using the stored energy of the ethylene oxide-sCO2 under the variable working conditions, characterized in that, In steps S2 and S3, the intermittent level of the ethylene oxide reaction kettle includes level I, level II, level III and level IV, and the operation level of the supercritical CO2 turbine includes level A, level B, level C and level D, wherein level I corresponds to level A, level II corresponds to level B, level III corresponds to level C, and level IV corresponds to level D.

7. The method according to claim 1, wherein the method is an evaluation method of the efficiency of the power generation of the variable working condition-η-ethane-sCO2 energy storage, characterized in that, The weight coefficient calculation formula of different types of energy loss in step S4 is: i =q+r*n-d*S 负 , the system total energy loss E ex,l is calculated by the formula: , wherein w i is the weight coefficient of any type of energy loss, i=1, 2, 3 or 4, respectively representing four types of energy loss, q is a basic weight value, r is a turbine speed influence coefficient, d is an ethylene oxide reactor load influence coefficient, S 负 is the ethylene oxide reactor load, E ex,li is the basic value of any type of energy loss, k 耦合 is the coupling correction term of any type of energy loss.

8. The method according to claim 1, wherein the method is an evaluation method of the efficiency of the power generation of the variable working condition-η-ethane-sCO2 energy storage, characterized in that, In step S5, the relative deviation ΔX of the arbitrary constraint index is calculated as follows: ΔX = |X 实 - X 阈 | / X 阈 × 100%, where X 实 is the real-time value of the arbitrary constraint index, and X 阈 is the safety threshold value of the arbitrary constraint index.

9. The method according to claim 1, wherein the method is an evaluation method of the efficiency of the power generation of the variable working condition-η-ethane-sCO2 energy storage, characterized in that, In step S6, the feedback correction formula is: parameter feedback correction coefficient K 修 = 1 + 0.02 * ΔE ex,l , wherein ΔE ex,l is the relative change rate of total system loss.

10. The method of claim 1, wherein the method is a method of evaluating the efficiency of an oxyethylene-sCO2 energy storage and power generation system under variable operating conditions, characterized by, The components of the energy storage power generation system include an ethylene oxide reaction kettle, a waste heat buffer tank, a waste heat delivery pump, a waste heat distribution valve group, a hot water storage boiler, a CO2 thermocline storage tank, a low-pressure sCO2 storage tank, an sCO2 booster pump, a collaborative heat exchanger, a supercritical CO2 turbine, a high-pressure sCO2 storage tank, an expander generator, a regenerative heat exchanger, a tube-shell cooler, a comprehensive intelligent calculation control group, a circulating water cooler, a circulating water pump and a hot water lithium bromide refrigeration subsystem.

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