Organic Rankine cycle power generation system driven by exhaust waste heat of centrifugal compressor

Abstract

The invention discloses an organic Rankine cycle power generation system driven by exhaust waste heat of a centrifugal compressor, and the system comprises a self-adaptive variable structure waste heat collection module which drives a fin through a stepping motor to adjust a helical angle, matches exhaust temperature fluctuation, and is provided with a double-medium heat exchange loop to realize dynamic storage and release of waste heat; according to the cascade expansion power generation module, two-stage expansion machines are connected in series with a pressure matcher, and a working medium diverter valve is configured to dynamically adjust the working medium proportion; the intelligent coupling power generation and electric energy management module integrates a magnetic resistance switching type permanent magnet synchronous generator technology and a virtual synchronous generator technology and is provided with a dynamic reactive power compensation device; and the multi-parameter cooperative control module optimizes system parameters based on a model prediction control algorithm, and introduces entropy production analysis to monitor irreversible loss. The self-adaptive structure optimizes the heat exchange process, cascade expansion widens the working condition adaptation range, cooperative control reduces irreversible loss, the self-repairing system prolongs the maintenance period, and deep utilization and efficient conversion of waste heat of the centrifugal compressor are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of renewable energy utilization, and in particular to an organic Rankine cycle power generation system driven by exhaust waste heat from a centrifugal compressor. Background Art

[0002] In modern industrial production, centrifugal compressors, as core power equipment, are widely used in fields such as petrochemicals, metallurgy, and electric power. The high-temperature gases emitted during operation typically range from 150°C to 300°C, carrying a large amount of waste heat. If this waste heat is not effectively utilized, it not only wastes energy but also increases the environmental heat load. Organic Rankine cycle (ORC) power generation systems, adaptable to the characteristics of medium and low-temperature heat sources, have become a common technical means of recovering waste heat from centrifugal compressor exhaust. However, existing waste heat power generation systems face numerous challenges in practical application. Traditional waste heat collection devices often utilize fixed-structure fin heat exchangers, whose heat transfer efficiency relies on stable operating conditions. When the centrifugal compressor load fluctuates, causing changes in exhaust flow and temperature, the fixed fins struggle to dynamically adjust the heat exchange area and flow field distribution, significantly reducing heat transfer efficiency. Furthermore, during long-term operation, impurities in the exhaust easily adhere to the fin surface, forming dust and scaling, further increasing heat transfer resistance and reducing heat transfer performance. In the energy conversion process, the single-stage expander design has significant limitations. Its expansion ratio is fixed within a certain range and cannot be flexibly adjusted to changes in exhaust temperature and pressure. When actual operating conditions deviate from the design parameters, the expander's energy conversion efficiency decreases significantly, making it difficult to achieve efficient utilization of waste heat. Regarding system integration and control, existing power generation systems lack compatibility with the power grid. Traditional generators operate with unstable efficiency under variable speed conditions, with efficiency significantly decreasing at low loads. They also lack the ability to simulate grid inertia, which can easily cause frequency oscillations when connected to microgrids, impacting grid stability. Regarding working fluid management, long-term circulation of organic working fluids in high-temperature environments decomposes to produce acidic substances and other impurities. Traditional purification methods are not only inefficient but also require regular downtime for treatment, resulting in poor system continuity and high maintenance costs. Furthermore, traditional PID control strategies struggle to meet the multivariable and tightly coupled control requirements of organic Rankine cycle systems. They respond slowly to waste heat transients, suffer from large steady-state errors, and cannot achieve global optimal system operation, hindering overall power generation efficiency. Therefore, the development of a novel centrifugal compressor exhaust waste heat power generation system is urgently needed to overcome the shortcomings of existing technologies. Summary of the Invention

[0003] The present invention proposes an organic Rankine cycle power generation system driven by waste heat from exhaust gas of a centrifugal compressor to solve the problems mentioned in the above-mentioned prior art.

[0004] In order to achieve the above object, the present invention adopts the following technical solutions:

[0005] An organic Rankine cycle power generation system driven by waste heat from centrifugal compressor exhaust gas includes the following modules:

[0006] Adaptive variable structure waste heat collection module: It is arranged in the exhaust pipe of the centrifugal compressor and includes a fin-tube heat exchanger with an adjustable spiral angle. The fins are driven by a stepper motor to rotate and the spiral angle is adjusted in real time to achieve the optimization of the Reynolds number Re flow state. A dual-medium heat exchange circuit is set up, with the main circuit flowing organic working fluid and the secondary circuit filled with phase change energy storage material. store =m·ΔH fus Realize the dynamic storage and release of waste heat to compensate for energy supply during load fluctuations, where m is the mass of the phase change material, ΔH fus is the latent heat of fusion;

[0007] Cascade expansion power generation module: It adopts a two-stage expander series structure, with the first-stage expander being a radial inflow type and the second-stage being an axial type, connected by a pressure matcher; it is equipped with a working fluid diverter valve to dynamically adjust the working fluid ratio entering the two-stage expander according to the exhaust gas temperature;

[0008] Intelligent coupling power generation and power management module: The generator adopts a reluctance switching permanent magnet synchronous generator, which realizes efficient power generation in a wide speed range through stator winding switching; the power management unit integrates virtual synchronous generation VSG technology, through inertia control algorithm Simulate the characteristics of synchronous generator, where J VSG is the virtual inertia, k J is the inertia coefficient, ω grid is the grid angular frequency; a dynamic reactive power compensation device is configured to adjust the reactive power output in real time according to the grid voltage fluctuation. The adjustment algorithm is: Q comp =k Q ·(V grid -V ref ), where Q comp To compensate for reactive power, k Q is the compensation coefficient, V grid 、V ref are the grid voltage and the reference voltage respectively;

[0009] Multi-parameter collaborative control module: Based on the model predictive control MPC algorithm, a multi-variable prediction model including waste heat collection, organic Rankine cycle, and power generation system is established, and solved through rolling optimization Achieve global optimal control of the system, where J is the objective function, N p For the prediction time domain, y is the system output, r is the reference trajectory, Q and R are weight matrices; entropy production analysis is introduced to monitor the irreversible loss of the system in real time and automatically adjust key parameters;

[0010] Self-repairing working fluid circulation module: Integrate a nano-catalyst bed in the working fluid loop to load precious metal active components, through the algorithm formula: Catalytic decomposition of the working fluid pyrolysis products, where r is the reaction rate, k is the reaction constant, C impurity is the impurity concentration, E a is the activation energy, R is the gas constant, and T is the temperature; an online detection unit for the working fluid quality is set up, and real-time monitoring is performed through a dielectric constant sensor. When the concentration of the decomposition product exceeds the threshold, the purification process is automatically triggered.

[0011] Furthermore, in the adaptive variable structure waste heat collection module, a micro-groove structure is provided on the fin surface, with a groove depth h and a groove width w, according to the algorithm formula: Enhanced heat transfer, where Nu is the Nusselt number and d is the pipe diameter; the phase change energy storage material uses graphene-modified composite salt, through the algorithm formula: Optimize thermal response speed, where λ eff is the effective thermal conductivity, λ m ,λ p are the thermal conductivities of the matrix and particles, respectively, and φ is the volume fraction of particles.

[0012] Furthermore, in the cascade expansion power generation module, the first-stage expander impeller adopts a three-dimensional flow channel design, and the blade outlet angle β is calculated by the algorithm formula: Optimize energy conversion efficiency, where ψ is the head coefficient, H t is the theoretical head, u is the impeller circumferential speed, and φ is the flow coefficient; the secondary expander adopts an adjustable guide vane structure, and the guide vane installation angle α satisfies η pol =η0·(1-k α |α-α0|), where η pol is the variable efficiency, η0 is the design efficiency, k α is the efficiency correction coefficient, and α0 is the optimal installation angle.

[0013] Furthermore, in the intelligent coupling power generation and power management module, the stator winding of the reluctance switching permanent magnet synchronous generator adopts a star-delta switchable structure, and the algorithm formula Achieve impedance matching in a wide load range, where Z Y 、Z Δ are the star and triangle connection impedances respectively; the primary frequency regulation coefficient formula of the virtual synchronous generator is: where f rated 、f min is the rated and minimum frequency, P max 、P min is the maximum and minimum active power.

[0014] Furthermore, in the multi-parameter cooperative control module, the weight matrix of the model predictive control algorithm is: Q = diag (q1, q2, q3)) and R = diag (r1, r2) are tuned online using the particle swarm optimization PSO algorithm to meet Where N is the number of iterations, J target is the objective function value; in the optimization strategy based on entropy production analysis, when S gen When it exceeds the baseline value by 15%, the system parameter reconstruction is automatically triggered to adjust the working fluid flow.

[0015] Furthermore, in the self-repairing working medium circulation module, the nano catalyst bed adopts a honeycomb structure, and the formula Optimize the catalytic effect, where η cata is the catalytic efficiency, k is the reaction rate constant, a is the specific surface area, D eff is the effective diffusion coefficient, L is the bed thickness; the dielectric constant sensor of the working fluid quality online detection unit adopts a coaxial cylindrical structure, through the algorithm formula: To achieve accurate monitoring of the working fluid state, C is the capacitance value, L is the electrode length, and a and b are the inner and outer electrode radii.

[0016] Furthermore, in the adaptive variable structure waste heat collection module, a dynamic flow distribution valve is set in the dual medium heat exchange circuit. Adjust the flow ratio, where m main 、m phase are the flow rates of the main circuit and phase change circuit respectively, T pc is the melting point of the phase change material, T amb is the ambient temperature; a super-hydrophobic coating is deposited on the surface of the micro-groove structure, and the contact angle θ is ≥ 150°.

[0017] Furthermore, in the cascade expansion power generation module, the pressure matcher adopts a convergent nozzle structure, and the throat diameter Among them, m mix is the mixed flow rate, ρ t 、v t are the density and flow velocity at the throat respectively, through the formula: Optimize pressure matching efficiency, where P1 and P2 are inlet and outlet pressures, gamma is the specific heat ratio, and M1 is the inlet Mach number; the bearings of the two-stage expander use magnetic fluid sealing technology, and zero leakage is achieved through the formula: F = μ0MH·A, where F is the sealing force, μ0 is the vacuum magnetic permeability, M is the magnetization intensity, H is the magnetic field intensity, and A is the sealing area.

[0018] Furthermore, in the intelligent coupled power generation and power management module, the dynamic reactive power compensation device adopts a modular multi-level converter MMC, and the sub-module capacitor where Qmax is the maximum reactive capacity, f is the grid frequency, V dc is the DC side voltage, through the formula Control output voltage, where m is the modulation ratio, V ac is the AC side voltage; the power quality monitoring unit integrates the harmonic source location function based on the directional power method formula: When P h It is the timing to determine whether the harmonic source is located downstream of the measurement point, where P h is the hth harmonic power, V hi , I hi is the hth harmonic voltage and current, φ hi is the phase difference.

[0019] Furthermore, in the multi-parameter collaborative control module, the prediction time domain N of the model predictive control algorithm is p Adaptive adjustment according to the dynamic characteristics of the system to meet where N p0 is the reference time domain, k p is the adjustment coefficient, τ sys is the system time constant, τ sam is the sampling period; in the system reconstruction strategy based on entropy production analysis, the economic optimization target algorithm is introduced: Where C is the total cost, c i is the entropy production cost coefficient of each component, ΔS gen,i is the change in entropy production, c energy is the energy cost, and ΔW is the change in power generation.

[0020] Compared with the existing technology, the beneficial effects of the present invention are:

[0021] The organic Rankine cycle power generation system driven by the waste heat of centrifugal compressor exhaust provided by the present invention shows significant advantages in waste heat recovery efficiency, system stability, power generation performance and operation and maintenance through a series of innovative designs and technical improvements.

[0022] In the waste heat collection process, the adaptive variable structure waste heat collection module adjusts the fin helix angle in real time based on changes in exhaust temperature and flow rate, optimizing the flow field distribution and significantly improving heat exchange efficiency. The dual-medium heat exchange circuit design, combined with phase-change energy storage materials, effectively mitigates the impact of heat source fluctuations, ensuring efficient waste heat recovery under various operating conditions. Furthermore, the application of micro-grooves and super-hydrophobic coating technology inhibits scaling, reduces maintenance frequency, and extends equipment life.

[0023] The cascade expansion power generation module utilizes two expanders in series and pressure matching technology, broadening the range of expansion ratios and enabling comprehensive utilization of waste heat energy. The module maintains high energy conversion efficiency under both high and low load conditions, significantly improving power generation efficiency and part-load performance compared to traditional single-stage expansion systems.

[0024] In the intelligent coupled power generation and energy management module, the reluctance switching permanent magnet synchronous generator achieves efficient power generation across a wide speed range. Virtual synchronous generator technology gives the system excellent grid adaptability, effectively suppressing frequency fluctuations and improving power quality. The dynamic reactive power compensation device adjusts reactive power output in real time, reducing harmonic distortion and ensuring stable system access to the grid.

[0025] The multi-parameter collaborative control module, based on model predictive control algorithms and entropy production analysis, can rapidly respond to changes in operating conditions and precisely adjust system parameters, effectively reducing irreversible losses and improving overall system energy efficiency. The self-healing working fluid circulation module utilizes nanocatalysts and online detection technology to purify the working fluid in real time, inhibiting its decomposition, extending the purification cycle, and reducing maintenance costs.

[0026] Overall, the technical solution of the present invention significantly improves the recovery rate of centrifugal compressor exhaust waste heat, enhances the stability and economy of the power generation system, and reduces operation and maintenance costs. It has broad application prospects and huge promotion value in the field of industrial waste heat recovery. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a schematic block diagram of an organic Rankine cycle power generation system driven by waste heat from centrifugal compressor exhaust gas proposed by the present invention;

[0028] Figure 2 It is a bar chart comparing system energy efficiency;

[0029] Figure 3 Comparison chart for control strategy optimization. DETAILED DESCRIPTION

[0030] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0031] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like to indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0032] In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the said features. In the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined. In addition, the terms "installed", "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be a connection between the two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. The present invention will be further described in detail below with reference to the accompanying drawings.

[0033] Reference Figures 1 to 3 :An organic Rankine cycle power generation system driven by waste heat from centrifugal compressor exhaust, including the following modules:

[0034] Adaptive variable structure waste heat collection module: It is arranged in the exhaust pipe of the centrifugal compressor and includes a fin-tube heat exchanger with an adjustable spiral angle. The fins are driven by a stepper motor to rotate and the spiral angle is adjusted in real time to achieve the optimization of the Reynolds number Re flow state. A dual-medium heat exchange circuit is set up, with the main circuit flowing organic working fluid and the secondary circuit filled with phase change energy storage material. store =m·ΔH fus Realize the dynamic storage and release of waste heat to compensate for energy supply during load fluctuations, where m is the mass of the phase change material, ΔH fus is the latent heat of fusion;

[0035] Cascade expansion power generation module: It adopts a two-stage expander series structure, with the first-stage expander being a radial inflow type and the second-stage being an axial type, connected by a pressure matcher; it is equipped with a working fluid diverter valve to dynamically adjust the working fluid ratio entering the two-stage expander according to the exhaust gas temperature;

[0036] Intelligent coupling power generation and power management module: The generator adopts a reluctance switching permanent magnet synchronous generator, which realizes efficient power generation in a wide speed range through stator winding switching; the power management unit integrates virtual synchronous generation VSG technology, through inertia control algorithm Simulate the characteristics of synchronous generator, where J VSG is the virtual inertia, k J is the inertia coefficient, ω grid is the grid angular frequency; a dynamic reactive power compensation device is configured to adjust the reactive power output in real time according to the grid voltage fluctuation. The adjustment algorithm is: Q comp =k Q ·(V grid -V ref ), where Q comp To compensate for reactive power, k Q is the compensation coefficient, V grid 、V ref are the grid voltage and the reference voltage respectively;

[0037] Multi-parameter collaborative control module: Based on the model predictive control MPC algorithm, a multi-variable prediction model including waste heat collection, organic Rankine cycle, and power generation system is established, and solved through rolling optimization Achieve global optimal control of the system, where J is the objective function, N p For the prediction time domain, y is the system output, r is the reference trajectory, Q and R are weight matrices; entropy production analysis is introduced to monitor the irreversible loss of the system in real time and automatically adjust key parameters;

[0038] Self-repairing working fluid circulation module: Integrate a nano-catalyst bed in the working fluid loop to load precious metal active components, through the algorithm formula: Catalytic decomposition of the working fluid pyrolysis products, where r is the reaction rate, k is the reaction constant, C impurity is the impurity concentration, E a is the activation energy, R is the gas constant, and T is the temperature; an online detection unit for the working fluid quality is set up, and real-time monitoring is performed through a dielectric constant sensor. When the concentration of the decomposition product exceeds the threshold, the purification process is automatically triggered.

[0039] In the present invention, in the adaptive variable structure waste heat collection module, a micro-groove structure is provided on the fin surface, with a groove depth h and a groove width w, and an algorithm formula: Enhanced heat transfer, where Nu is the Nusselt number and d is the pipe diameter; the phase change energy storage material uses graphene-modified composite salt, through the algorithm formula: Optimize thermal response speed, where λ eff is the effective thermal conductivity, λ m ,λ p are the thermal conductivities of the matrix and particles, respectively, and φ is the volume fraction of particles.

[0040] In the present invention, in the cascade expansion power generation module, the first-stage expander impeller adopts a three-dimensional flow channel design, and the blade outlet angle β is calculated by the algorithm formula: Optimize energy conversion efficiency, where ψ is the head coefficient, H t is the theoretical head, u is the impeller circumferential speed, and φ is the flow coefficient; the secondary expander adopts an adjustable guide vane structure, and the guide vane installation angle α satisfies η pol =η0·(1-k α |α-α0|), where η pol is the variable efficiency, η0 is the design efficiency, k α is the efficiency correction coefficient, and α0 is the optimal installation angle.

[0041] In the present invention, in the intelligent coupling power generation and power management module, the stator winding of the reluctance switching permanent magnet synchronous generator adopts a star-delta switchable structure, and the algorithm formula Achieve impedance matching in a wide load range, where Z Y , Z Δ are the star and triangle connection impedances respectively; the primary frequency regulation coefficient formula of the virtual synchronous generator is: where f rated 、f min is the rated and minimum frequency, P max 、P min is the maximum and minimum active power.

[0042] In the present invention, in the multi-parameter cooperative control module, the weight matrix of the model predictive control algorithm is: Q = diag (q1, q2, q3)) and R = diag (r1, r2) are tuned online using the particle swarm optimization PSO algorithm to meet Where N is the number of iterations, J target is the objective function value; in the optimization strategy based on entropy production analysis, when S gen When it exceeds the baseline value by 15%, the system parameter reconstruction is automatically triggered to adjust the working fluid flow.

[0043] In the present invention, in the self-repairing working medium circulation module, the nano catalyst bed adopts a honeycomb structure, and the formula Optimize the catalytic effect, where η cata is the catalytic efficiency, k is the reaction rate constant, a is the specific surface area, D eff is the effective diffusion coefficient, L is the bed thickness; the dielectric constant sensor of the working fluid quality online detection unit adopts a coaxial cylindrical structure, through the algorithm formula: To achieve accurate monitoring of the working fluid state, C is the capacitance value, L is the electrode length, and a and b are the inner and outer electrode radii.

[0044] In the present invention, in the adaptive variable structure waste heat collection module, a dynamic flow distribution valve is set in the dual-medium heat exchange circuit. Adjust the flow ratio, where m main 、m phase are the flow rates of the main circuit and phase change circuit respectively, T pc is the melting point of the phase change material, T amb is the ambient temperature; a super-hydrophobic coating is deposited on the surface of the micro-groove structure, and the contact angle θ is ≥ 150°.

[0045] In the present invention, in the cascade expansion power generation module, the pressure matcher adopts a convergent-divergent nozzle structure, and the throat diameter Among them, m mix is the mixed flow rate, ρ t 、v t are the density and flow velocity at the throat respectively, through the formula: Optimize pressure matching efficiency, where P1 and P2 are inlet and outlet pressures, gamma is the specific heat ratio, and M1 is the inlet Mach number; the bearings of the two-stage expander use magnetic fluid sealing technology, and zero leakage is achieved through the formula: F = μ0MH·A, where F is the sealing force, μ0 is the vacuum magnetic permeability, M is the magnetization intensity, H is the magnetic field intensity, and A is the sealing area.

[0046] In the present invention, in the intelligent coupling power generation and power management module, the dynamic reactive power compensation device adopts a modular multi-level converter MMC, and the sub-module capacitor where Q max is the maximum reactive capacity, f is the grid frequency, V dc is the DC side voltage, through the formula Control output voltage, where m is the modulation ratio, V ac is the AC side voltage; the power quality monitoring unit integrates the harmonic source location function based on the directional power method formula: When P h It is the timing to determine whether the harmonic source is located downstream of the measurement point, where P h is the hth harmonic power, V hi , I hi is the hth harmonic voltage and current, φ hi is the phase difference.

[0047] In the present invention, in the multi-parameter collaborative control module, the prediction time domain N of the model predictive control algorithm is p Adaptive adjustment according to the dynamic characteristics of the system to meet where N p0 is the reference time domain, k p is the adjustment coefficient, τ sys is the system time constant, τsam is the sampling period; in the system reconstruction strategy based on entropy production analysis, the economic optimization target algorithm is introduced: Where C is the total cost, c i is the entropy production cost coefficient of each component, ΔS gen,i is the change in entropy production, c energy is the energy cost, and ΔW is the change in power generation.

[0048] The present invention's organic Rankine cycle power generation system, driven by waste heat from centrifugal compressor exhaust, utilizes an integrated design for waste heat collection, energy conversion, power generation control, and working fluid management. The system primarily comprises an adaptive variable-structure waste heat collection module, a stepped expansion power generation module, an intelligently coupled power generation and energy management module, a multi-parameter collaborative control module, and a self-repairing working fluid circulation module. Through data interaction and collaborative control, these modules achieve efficient recovery and power generation from centrifugal compressor exhaust heat.

[0049] The overall working process of the system is as follows: the high-temperature exhaust gas (150-300℃) discharged by the centrifugal compressor enters the adaptive variable structure waste heat collection module, and transfers heat to the organic working fluid (such as R245fa) and phase change energy storage material through the adjustable spiral angle finned tube and the dual-medium heat exchange circuit; the organic working fluid is heated and evaporated and then enters the cascade expansion power generation module, and the two-stage expander drives the generator to generate electricity; the electric energy is processed by the intelligent coupling power generation and power management module and then incorporated into the power grid or directly supplied with energy; the multi-parameter collaborative control module monitors the system status in real time and optimizes the operating parameters based on the model predictive control algorithm; the self-repairing working fluid circulation module continuously purifies the working fluid to ensure the long-term stable operation of the system.

[0050] The adaptive variable structure waste heat harvesting module consists of a finned tube heat exchanger with adjustable helix angle, a dual-medium heat exchange circuit, a stepper motor drive mechanism, and temperature and pressure sensors. The finned tubes are made of stainless steel (such as 316L), with a diameter of 25 mm, a wall thickness of 2 mm, a fin height of 15 mm, and a pitch of 4 mm. The helix angle θ is adjustable from 5° to 45°. The dual-medium heat exchange circuit consists of a primary circuit (organic refrigerant R245fa) and a secondary circuit (graphene-modified composite salt phase change material, melting point 58°C).

[0051] The dynamic adjustment formula of the helix angle is: θ=θ0+k·ΔT_exhaust;

[0052] Where θ0 is the initial helix angle (20°), k is the adjustment coefficient (0.5° / °C), and ΔT_exhaust is the exhaust temperature fluctuation. When the exhaust temperature rises from 200°C to 250°C, the helix angle automatically adjusts from 20° to 45°, maintaining the Re number in the efficient heat exchange range of 5000-8000.

[0053] Optimization formula for thermal conductivity of phase change energy storage materials: λ_eff=λ_m·(1+3φ(λ_p-λ_m) / (λ_p+2λ_m))

[0054] Where λ_m is the thermal conductivity of the matrix material (0.5 W / (m·K)), λ_p is the thermal conductivity of the graphene particles (5000 W / (m·K)), and φ is the particle volume fraction (5%). Calculations show that the thermal conductivity of the composite salt increases to 4.2 W / (m·K), and the thermal response speed increases by 30%.

[0055] Micro-groove enhanced heat transfer formula: Nu = 0.23Re^0.65Pr^0.4(1+h / d)^0.2

[0056] Where h is the groove depth (0.3mm) and d is the tube diameter (25mm). Compared with the light tube, the micro-groove structure increases the Nu number by 25% and the heat transfer coefficient from 800W / (m 2 K) increased to 1000W / (m 2 ·K).

[0057] Implementation cases and effect verification:

[0058] This module was applied in the exhaust system of a centrifugal compressor of a chemical enterprise. The measured data are shown in the following table:

[0059]

[0060] The data in the table demonstrates that the adaptive variable structure design of this invention significantly improves waste heat recovery efficiency and system response speed. The adjustable helix angle ensures optimal heat transfer under varying operating conditions. The combination of microgrooves and a super-hydrophobic coating inhibits scaling and extends equipment maintenance cycles. The phase-change energy storage material effectively compensates for energy fluctuations during load fluctuations, enabling the system to maintain stable operation within an exhaust temperature range of ±30°C.

[0061] The cascade expansion power generation module consists of a radial-flow first-stage expander, an axial-flow secondary expander, a pressure matcher, and a working fluid diverter valve. The first-stage expander impeller adopts a three-dimensional flow channel design with a blade outlet angle β of 20°. The secondary expander is equipped with adjustable guide vanes, with an installation angle α adjustable from 25° to 65°. The pressure matcher connects the two expander stages to optimize the intermediate pressure control.

[0062] Pressure matching formula: P_int=√(P_high·P_low)

[0063] In one implementation, the high-side pressure (P_high) is 2.5 MPa, the low-side pressure (P_low) is 0.3 MPa, and the calculated intermediate pressure (P_int) is 0.87 MPa. In actual operation, the pressure matcher precisely controls the intermediate pressure within the range of 0.85-0.9 MPa to maximize system efficiency.

[0064] Working fluid split ratio formula: α=(T_exhaust-T_ref) / (T_max-T_ref)

[0065] Where T_exhaust is the exhaust temperature, T_ref is the reference temperature (180°C), and T_max is the design maximum temperature (300°C). When the exhaust temperature is 240°C, α = (240-180) / (300-180) = 0.5, meaning 50% of the working fluid enters the primary expander and 50% enters the secondary expander.

[0066] Secondary expander efficiency formula: η_pol=η_0·(1-k_α·|α-α_0|)

[0067] Where η_0 is the design efficiency (85%), k_α is the efficiency correction coefficient (0.003 / °), and α_0 is the optimal installation angle (45°). When the guide vane installation angle α = 55°, η_pol = 85% × (1 - 0.003 × |55 - 45|) = 82.45%;

[0068] Implementation cases and effect verification:

[0069] In a steel enterprise application case, a single-stage expansion system was compared with the cascade expansion system of the present invention. The data are shown in the following table:

[0070]

[0071] The stepped expansion design significantly improves system efficiency and adaptability. A pressure matcher optimizes intermediate pressures, reducing irreversible losses during the expansion process. The adjustable guide vane structure enables the secondary expander to maintain high efficiency under variable operating conditions, with particularly significant improvements in part-load performance. Magnetic fluid sealing technology achieves zero leakage, extending equipment life and reducing maintenance costs.

[0072] The intelligent coupled power generation and energy management module consists of a reluctance-switching permanent magnet synchronous generator, a virtual synchronous generator control unit, a dynamic reactive power compensation device, and a power quality monitoring unit. The generator stator winding can be switched between star and delta connections. The virtual synchronous generator unit uses a software algorithm to simulate the inertia and damping characteristics of a synchronous generator, and the dynamic reactive power compensation device adopts an MMC topology.

[0073] Winding impedance matching formula: Z_Y=1 / 3Z_Δ

[0074] When the generator is operating at low load, it switches to a star connection (Z_Y), reducing the impedance to one-third of the delta connection (Z_Δ), thereby minimizing copper losses. Tests have shown that at 30% load, the star connection improves efficiency by 2.3% compared to the delta connection.

[0075] Virtual synchronous generator inertia formula: J_VSG=k_J·W_turbine / ω_grid 2

[0076] Where k_J is the inertia coefficient (0.5), W_turbine is the expander output power (kW), and ω_grid is the grid angular frequency (rad / s). When the grid frequency fluctuates, the system inertia response time is reduced to one-third of that of a traditional system by dynamically adjusting J_VSG.

[0077] MMC submodule capacitance formula: C=Q_max / (2fV_dc 2 )

[0078] In one implementation case, Q_max = 100kvar, f = 50Hz, V_dc = 1000V, and C = 2000μF. A 2200μF capacitor is actually selected to ensure stable operation of the device under rated operating conditions.

[0079] Implementation cases and effect verification:

[0080] The module is applied in a microgrid in an industrial park. Compared with the traditional power generation system, the data is shown in the following table:

[0081]

[0082]

[0083] The multi-parameter collaborative control module is built on a PLC controller and industrial computer, and includes a data acquisition unit, a model predictive control algorithm unit, an entropy production analysis unit, and a parameter optimization unit. The system collects more than 20 parameters, including temperature, pressure, and flow, and uses the MPC algorithm to achieve global optimization control. It also identifies inefficient links in the system based on entropy production analysis.

[0084] MPC objective function: min J = ∑(k = 0 → N_p) ‖y(k+1|k)-r(k+1)‖ 2

[0085] _Q+‖u(k)‖ 2 _R

[0086] Where N_p is the prediction horizon (10 steps), y is the system output, r is the reference trajectory, Q is the state weight matrix (diag(10,5,2)), and R is the control weight matrix (diag(0.5,0.3)). Using the PSO algorithm to online optimize the Q and R matrices, the system response speed was improved by 20%.

[0087] Entropy generation calculation formula: S_gen=∑Q_i / T_i-Q_o / T_o

[0088] Under certain operating conditions, the waste heat collection module has Q_i = 500kW, T_i = 250°C (523K), Q_o = 420kW, and T_o = 80°C (353K). The calculated value is S_gen = 500 / 523 - 420 / 353 = -0.32kW / K. When S_gen exceeds the baseline value by 15%, the system automatically adjusts the working fluid flow rate.

[0089] Working fluid flow adjustment formula: m_ref=m_0·√(S_gen,base / S_gen)

[0090] Assuming the base entropy generation S_gen,base = 0.25 kW / K, the current S_gen = 0.3 kW / K, and the initial flow rate m_0 = 5 kg / s, the adjusted flow rate m_ref = 5·√(0.25 / 0.3) = 4.56 kg / s;

[0091] Implementation cases and effect verification:

[0092] In a pharmaceutical factory application case, the traditional PID control and the MPC collaborative control of the present invention are compared, and the data are shown in the following table:

[0093]

[0094] Multi-parameter coordinated control significantly improves the system's dynamic performance and operational efficiency. The MPC algorithm predicts future system behavior and adjusts control variables in advance, effectively suppressing parameter fluctuations. An optimization strategy based on entropy production analysis ensures the system consistently operates in a thermodynamically optimal state, reducing irreversible losses. Actual operational data demonstrates that the control strategy of this invention can maintain efficient and stable system operation even under complex operating conditions.

[0095] The self-repairing working fluid circulation module consists of a nanocatalyst bed, an online working fluid quality monitoring unit, a purification circuit, and an intelligent switching valve. The catalyst bed utilizes a honeycomb structure with a pore density of 300 cpsi and is loaded with Pt / Pd active components (particle size 10 nm). The online monitoring unit uses a coaxial cylindrical dielectric constant sensor to monitor the working fluid status in real time.

[0096] Catalytic efficiency formula: η_cata=1-1 / tanh(mL), where m=√(ka / D_eff), k is the reaction rate constant (0.05s -1 ), a is the specific surface area (1500m 2 / m 3 ), D_eff is the effective diffusion coefficient (1×10 -5 m 2 / s), L is the bed thickness (0.2m). η_cata = 92.3%.

[0097] The relationship between dielectric constant and decomposition product concentration is: ε = ε_0·(1+k_ε·C_decomp), where ε_0 is the dielectric constant of the pure working fluid (9.8) and k_ε is the correlation coefficient (0.05 / %). When ε = 10.2 is detected, C_decomp is calculated as (10.2 / 9.8-1) / 0.05 = 8.16%, exceeding the threshold (5%) and triggering the purification process.

[0098] Capacitance calculation formula: C = 2πεL / ln(b / a)

[0099] The sensor's inner and outer electrode radii are a = 5 mm, b = 10 mm, and L = 100 mm. When ε = 9.8, C = 2π × 8.85 × 10-12 × 9.8 × 0.1 / ln(2) = 8.5 pF. The actual measurement accuracy is ±0.05 pF, corresponding to a concentration detection accuracy of ±0.5%.

[0100] Implementation cases and effect verification:

[0101] In a test of a thermal power plant running continuously for 12 months, the data comparing the traditional system and the self-repair system of the present invention are shown in the following table:

[0102]

[0103] The self-repairing refrigerant circulation module effectively extends the refrigerant's service life and reduces system maintenance costs. The nanocatalyst bed efficiently catalyzes decomposition, keeping the concentration of refrigerant decomposition products within a safe range. An online detection unit monitors the refrigerant's status in real time, enabling intelligent triggering of the purification process. Actual operation demonstrates that this module enables the system to maintain high efficiency and stability over the long term, significantly reducing the frequency of refrigerant replacement and equipment maintenance.

[0104] Verification of overall system performance:

[0105] In a comprehensive application case of a large petrochemical enterprise, the system of the present invention was compared with a traditional waste heat recovery system. The data of continuous operation for 6 months are shown in the following table:

[0106]

[0107] The system of the present invention is significantly superior to traditional systems in terms of waste heat recovery efficiency, power generation efficiency, and stability. The combination of the adaptive variable structure waste heat acquisition module and the cascade expansion power generation module achieves deep recovery and efficient conversion of waste heat. The intelligent coupling power generation and power management module improves power quality and grid adaptability. The multi-parameter collaborative control module and the self-repairing working fluid circulation module ensure the long-term stable operation of the system. Overall, the system of the present invention has significant economic and environmental benefits and can be widely used in the field of waste heat recovery in centrifugal compressors.

[0108] Attached to the instruction manual Figure 2 It can be seen that: this bar chart intuitively presents the technical advantages by comparing the energy efficiency performance of the traditional single-stage system and the patented cascade system under different operating loads (50%, 75%, 100%). The traditional single-stage system has a significant decline in energy efficiency at low loads, and it is difficult to break through the efficiency bottleneck at high loads. This is due to its fixed expansion ratio and single energy conversion path. The patented system adopts two-stage expanders in series and pressure matching technology, which can dynamically adjust the working process of the working fluid according to the load and maintain high efficiency within the full load range. For example, under 75% load conditions, the efficiency of the traditional system is only 20.5%, while the patented system reaches 25.8%, a significant improvement. The data of an average energy efficiency improvement of 26.8% shows that this design effectively solves the efficiency loss problem of the traditional system under variable conditions. It is especially suitable for heat sources with large fluctuations such as centrifugal compressor exhaust waste heat, providing a better solution for industrial waste heat recovery.

[0109] Attached to the instruction manual Figure 3 It can be seen that: This figure compares the performance of traditional PID control and the patented model predictive control (MPC) in system optimization. Because PID control relies on fixed parameter adjustment, facing the organic Rankine cycle system with strong multi-variable coupling, it still cannot reach the ideal objective function value after 50 iterations, with large steady-state error and delayed response. However, the MPC algorithm predicts the future behavior of the system. After 10 iterations, the objective function value is lower than the final value of PID control. It converges to the optimal value after 30 iterations, which is 61% faster than PID control. Combined with parameter optimization of entropy production analysis, MPC can identify inefficient links in the system in real time, such as quickly adjusting the working fluid flow and expansion ratio when waste heat transients occur, reducing irreversible losses. This intelligent control strategy enables the system to respond quickly and maintain efficient operation when faced with complex working conditions, significantly improving overall energy efficiency and stability.

[0110] The above are only preferred specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with this technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solutions and inventive concepts of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. An organic Rankine cycle power generation system driven by waste heat from centrifugal compressor exhaust, characterized in that: Includes the following modules: Adaptive variable structure waste heat collection module: It is arranged in the exhaust pipe of the centrifugal compressor and includes a fin-tube heat exchanger with an adjustable spiral angle. The fins are driven by a stepper motor to rotate and the spiral angle is adjusted in real time to achieve the optimization of the Reynolds number Re flow state. A dual-medium heat exchange circuit is set up, with the main circuit flowing organic working fluid and the secondary circuit filled with phase change energy storage material. store =m·ΔH fus Realize the dynamic storage and release of waste heat to compensate for energy supply during load fluctuations, where m is the mass of the phase change material, ΔH fus is the latent heat of fusion; Cascade expansion power generation module: It adopts a two-stage expander series structure, with the first-stage expander being a radial inflow type and the second-stage being an axial type, connected by a pressure matcher; it is equipped with a working fluid diverter valve to dynamically adjust the working fluid ratio entering the two-stage expander according to the exhaust gas temperature; Intelligent coupling power generation and power management module: The generator adopts a reluctance switching permanent magnet synchronous generator, which realizes efficient power generation in a wide speed range through stator winding switching; the power management unit integrates virtual synchronous generation VSG technology, through inertia control algorithm Simulate the characteristics of synchronous generator, where J VSG is the virtual inertia, k J is the inertia coefficient, ω grid is the grid angular frequency; a dynamic reactive power compensation device is configured to adjust the reactive power output in real time according to the grid voltage fluctuation. The adjustment algorithm is: Q comp =k Q ·(V grid -V ref ), where Q comp To compensate for reactive power, k Q is the compensation coefficient, V grid 、V ref are the grid voltage and the reference voltage respectively; Multi-parameter collaborative control module: Based on the model predictive control MPC algorithm, a multi-variable prediction model including waste heat collection, organic Rankine cycle, and power generation system is established, and solved through rolling optimization Achieve global optimal control of the system, where J is the objective function, N p For the prediction time domain, y is the system output, r is the reference trajectory, Q and R are weight matrices; entropy production analysis is introduced to monitor the irreversible loss of the system in real time and automatically adjust key parameters; Self-repairing working fluid circulation module: Integrate a nano-catalyst bed in the working fluid loop to load precious metal active components, through the algorithm formula: Catalytic decomposition of the working fluid pyrolysis products, where r is the reaction rate, k is the reaction constant, C impurity is the impurity concentration, E a is the activation energy, R is the gas constant, and T is the temperature; an online detection unit for the working fluid quality is set up, and real-time monitoring is performed through a dielectric constant sensor. When the concentration of the decomposition product exceeds the threshold, the purification process is automatically triggered.

2. The organic Rankine cycle power generation system driven by waste heat from centrifugal compressor exhaust according to claim 1, characterized in that: In the adaptive variable structure waste heat collection module, a micro-groove structure is set on the fin surface, with a groove depth h and a groove width w. According to the algorithm formula: Enhanced heat transfer, where Nu is the Nusselt number and d is the pipe diameter; the phase change energy storage material uses graphene-modified composite salt, through the algorithm formula: Optimize thermal response speed, where λ eff is the effective thermal conductivity, λ m ,λ p are the thermal conductivities of the matrix and particles, respectively, and φ is the volume fraction of particles.

3. The organic Rankine cycle power generation system driven by waste heat from centrifugal compressor exhaust according to claim 1, characterized in that: In the cascade expansion power generation module, the first-stage expander impeller adopts a three-dimensional flow channel design, and the blade outlet angle β is calculated by the algorithm formula: Optimize energy conversion efficiency, where ψ is the head coefficient, H t is the theoretical head, u is the impeller circumferential speed, and φ is the flow coefficient; the secondary expander adopts an adjustable guide vane structure, and the guide vane installation angle α satisfies η pol =η0·(1-k α |α-α0|), where η pol is the variable efficiency, η0 is the design efficiency, k α is the efficiency correction coefficient, and α0 is the optimal installation angle.

4. The organic Rankine cycle power generation system driven by waste heat from centrifugal compressor exhaust according to claim 1, characterized in that: In the intelligent coupling power generation and power management module, the stator winding of the reluctance switching permanent magnet synchronous generator adopts a star-delta switchable structure, and the algorithm formula Achieve impedance matching in a wide load range, where Z Y , Z Δ are the star and triangle connection impedances respectively; the primary frequency regulation coefficient formula of the virtual synchronous generator is: where f rated 、f min is the rated and minimum frequency, P max 、P min is the maximum and minimum active power.

5. The organic Rankine cycle power generation system driven by waste heat from centrifugal compressor exhaust according to claim 1, characterized in that: In the multi-parameter cooperative control module, the weight matrix of the model predictive control algorithm is: Q = diag (q1, q2, q3)) and R = diag (r1, r2) are tuned online using the particle swarm optimization PSO algorithm to meet Where N is the number of iterations, J target is the objective function value; in the optimization strategy based on entropy production analysis, when S gen When it exceeds the baseline value by 15%, the system parameter reconstruction is automatically triggered to adjust the working fluid flow.

6. The organic Rankine cycle power generation system driven by waste heat from centrifugal compressor exhaust according to claim 1, characterized in that: In the self-repairing working medium circulation module, the nano catalyst bed adopts a honeycomb structure, and the formula Optimize the catalytic effect, where η cata is the catalytic efficiency, k is the reaction rate constant, a is the specific surface area, D eff is the effective diffusion coefficient, L is the bed thickness; the dielectric constant sensor of the working fluid quality online detection unit adopts a coaxial cylindrical structure, through the algorithm formula: To achieve accurate monitoring of the working fluid state, C is the capacitance value, L is the electrode length, and a and b are the inner and outer electrode radii.

7. The organic Rankine cycle power generation system driven by waste heat from exhaust gas of a centrifugal compressor according to claim 2, characterized in that: In the adaptive variable structure waste heat collection module, a dynamic flow distribution valve is set in the dual-medium heat exchange circuit according to Adjust the flow ratio, where m main 、m phase are the flow rates of the main circuit and phase change circuit respectively, T pc is the melting point of the phase change material, T amb is the ambient temperature; a super-hydrophobic coating is deposited on the surface of the micro-groove structure, and the contact angle θ is ≥ 150°.

8. The organic Rankine cycle power generation system driven by waste heat from centrifugal compressor exhaust according to claim 3, characterized in that: In the cascade expansion power generation module, the pressure matcher adopts a convergent nozzle structure, and the throat diameter Among them, m mix is the mixed flow rate, ρ t 、v t are the density and flow velocity at the throat respectively, through the formula: Optimize pressure matching efficiency, where P1 and P2 are inlet and outlet pressures, gamma is the specific heat ratio, and M1 is the inlet Mach number; the bearings of the two-stage expander use magnetic fluid sealing technology, and zero leakage is achieved through the formula: F = μ0MH·A, where F is the sealing force, μ0 is the vacuum magnetic permeability, M is the magnetization intensity, H is the magnetic field intensity, and A is the sealing area.

9. The organic Rankine cycle power generation system driven by waste heat from exhaust gas of a centrifugal compressor according to claim 4, characterized in that: In the intelligent coupling power generation and power management module, the dynamic reactive compensation device adopts a modular multi-level converter MMC, and the sub-module capacitor where Q max is the maximum reactive capacity, f is the grid frequency, V dc is the DC side voltage, through the formula Control output voltage, where m is the modulation ratio, V ac is the AC side voltage; the power quality monitoring unit integrates the harmonic source location function based on the directional power method formula: When P h It is the timing to determine whether the harmonic source is located downstream of the measurement point, where P h is the hth harmonic power, V hi , I hi is the hth harmonic voltage and current, φ hi is the phase difference.

10. The organic Rankine cycle power generation system driven by waste heat from exhaust gas of a centrifugal compressor according to claim 5, characterized in that: In the multi-parameter collaborative control module, the prediction time domain N of the model predictive control algorithm p Adaptive adjustment according to the dynamic characteristics of the system to meet where N p0 is the reference time domain, k p is the adjustment coefficient, τ sys is the system time constant, τ sam is the sampling period; in the system reconstruction strategy based on entropy production analysis, the economic optimization target algorithm is introduced: Where C is the total cost, c i is the entropy production cost coefficient of each component, ΔS gen,i is the change in entropy production, c energy is the energy cost, and ΔW is the change in power generation.

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