Electric heat coordination method and system of solid oxide fuel cell heat and power cogeneration system

Abstract

The invention discloses an electricity and heat coordination method and system of a solid oxide fuel cell heat and power cogeneration system. The method comprises the following steps: acquiring a system operation parameter set (an electric load, a heat load, an electric pile temperature, a tail gas temperature and a fuel flow) in real time; determining a thermoelectric coordination control target value including a target power generation efficiency interval and a target heat supply temperature interval based on the parameter set; a fuel supply and air flow adjusting instruction is generated; executing the instruction to dynamically match the output power of the system with the electric load demand, dynamically match the output temperature of the waste heat recovery system with the thermal load demand, and generate a real-time heat-to-power ratio; when the stack temperature exceeds a preset safety threshold value, the fuel flow is preferentially reduced to a temperature return safety interval, and the air flow is synchronously compensated according to a stoichiometric ratio; and dynamically correcting the boundary value of the target power generation efficiency interval based on the real-time heat-to-electricity ratio, so that the real-time heat-to-electricity ratio of the system is always in the preset optimal efficiency interval. According to the invention, dynamic decoupling control and continuous efficiency optimization of the electric heating load are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of solid oxide fuel cells, and in particular to an electric and thermal coordination method and system for a solid oxide fuel cell combined heat and power system. Background Art

[0002] Solid oxide fuel cells (SOFCs), as third-generation high-temperature fuel cell technology, have become a core technology in the distributed energy sector due to their wide fuel adaptability, high energy conversion efficiency, and ability to directly utilize industrial by-product hydrogen. Their high-temperature operation (800-1000°C) not only increases electrochemical reaction rates but also enables cascaded thermal energy utilization through waste heat recovery systems, enabling the construction of green energy microgrids in scenarios such as industrial parks and data centers.

[0003] At present, the control strategy of SOFC cogeneration system mainly revolves around the stability of the stack and the matching of thermoelectric output. Traditional methods mostly use PID (proportional-integral-differential) control to achieve basic regulation of fuel flow and air flow, and maintain system operation by presetting fixed parameters. In recent years, some studies have introduced advanced algorithms such as Model Predictive Control (MPC) and fractional-order sliding mode variable structure control to optimize dynamic response characteristics by establishing thermoelectric coupling models. For example, the steady-state optimal operating range is obtained through the hierarchical dimension reduction graph traversal method, or the TS fuzzy model constrained generalized predictive control is used to achieve the coordination of power tracking and temperature constraints. In addition, for the design of waste heat recovery system, some technologies improve the thermal energy utilization rate by optimizing the structure of the exhaust gas heat exchanger, such as adding a heat recovery water tank in the air pipeline or using an annular high-temperature heat pipe to balance the temperature gradient of the stack.

[0004] However, existing technologies still face challenges on multiple dimensions. First, the thermoelectric coupling characteristics of the SOFC system lead to a lag in dynamic response. When the electrical load or thermal load suddenly changes, it is difficult for traditional control methods to quickly adjust the fuel supply and air ratio, which can easily cause output power fluctuations or the waste heat recovery temperature to deviate from the requirements. Secondly, there are safety hazards in the temperature control of the fuel cell stack under high-temperature operating conditions. Factors such as steam flow fluctuations and changes in fuel composition may cause abnormal burner temperature, which in turn leads to the risk of overheating of the fuel cell stack. However, existing protection mechanisms mostly rely on passive adjustment triggered by thresholds and lack active prediction and dynamic compensation capabilities. Furthermore, the optimization of the thermal-electric ratio has not yet formed a closed-loop control system. Existing strategies are mostly based on setting target ranges based on static efficiency curves, and cannot be dynamically corrected in real time according to changes in operating conditions, resulting in a decrease in the overall efficiency of the system during long-term operation. In addition, the synergy between the waste heat recovery system and the operation of the fuel cell stack is insufficient, and the thermal energy of the high-temperature exhaust gas is not fully converted into usable heat load, further limiting the improvement of the overall energy efficiency of the system. Summary of the Invention

[0005] In view of this, an embodiment of the present invention provides a method and system for coordinating heat and electricity in a solid oxide fuel cell combined heat and power system to solve the above technical problems.

[0006] To achieve the above objectives, in a first aspect, a method for coordinating heat and electricity in a solid oxide fuel cell combined heat and power system is provided, which comprises the following steps:

[0007] S1. Acquiring in real time an operating parameter set of the solid oxide fuel cell (SOFC) combined heat and power system, wherein the operating parameter set includes an electric load demand value, a heat load demand value, a stack temperature, an exhaust gas temperature, and a fuel flow rate;

[0008] S2. Determining a heat and power coordinated control target value based on the operating parameter set, wherein the heat and power coordinated control target value includes a target power generation efficiency range and a target heating temperature range;

[0009] S3. generating a fuel supply adjustment instruction and an air flow adjustment instruction according to the heat and power coordinated control target value;

[0010] S4. Executing the fuel supply adjustment instruction and the air flow adjustment instruction to dynamically match the output power of the SOFC cogeneration system with the electric load demand value, and simultaneously dynamically matching the output temperature of a waste heat recovery system integrated in the SOFC cogeneration system with the heat load demand value, and generating a real-time heat-to-power ratio;

[0011] S5. Real-time monitoring of the stack temperature. When the stack temperature exceeds a preset safety threshold, triggering an over-temperature protection strategy, the over-temperature protection strategy includes preferentially reducing the fuel flow rate until the stack temperature returns to a safe operating range, and simultaneously compensating the air flow rate according to a stoichiometric ratio based on the fuel flow rate;

[0012] S6. Based on the real-time heat-to-electricity ratio, dynamically correct the boundary value of the target power generation efficiency range so that the real-time heat-to-electricity ratio of the SOFC cogeneration system is always within a preset optimal efficiency range, where the preset optimal efficiency range is a subset of the target power generation efficiency range.

[0013] In a second aspect, a heat and electricity coordination system for a solid oxide fuel cell combined heat and power system is provided, comprising:

[0014] a parameter acquisition module for acquiring in real time an operating parameter set of the solid oxide fuel cell cogeneration system, the operating parameter set including an electric load demand value, a thermal load demand value, a stack temperature, an exhaust gas temperature, and a fuel flow rate;

[0015] a target determination module, configured to determine a heat and power coordinated control target value based on the operating parameter set, wherein the heat and power coordinated control target value includes a target power generation efficiency range and a target heating temperature range;

[0016] An instruction generation module, configured to generate a fuel supply adjustment instruction and an air flow adjustment instruction according to the heat and power coordinated control target value;

[0017] an instruction execution module, configured to execute the fuel supply adjustment instruction and the air flow adjustment instruction, so as to dynamically match the output power of the cogeneration system with the electric load demand value, and simultaneously dynamically match the output temperature of a waste heat recovery system integrated in the cogeneration system with the heat load demand value, and generate a real-time heat-to-power ratio;

[0018] an over-temperature protection module, configured to monitor the stack temperature in real time and trigger an over-temperature protection strategy when the stack temperature exceeds a preset safety threshold. The over-temperature protection strategy includes preferentially reducing the fuel flow rate until the stack temperature returns to a safe operating range, and simultaneously compensating the air flow rate according to a stoichiometric ratio based on the fuel flow rate;

[0019] A dynamic optimization module is used to dynamically correct the boundary value of the target power generation efficiency range based on the real-time heat-to-electricity ratio, so that the real-time heat-to-electricity ratio of the cogeneration system is always within a preset optimal efficiency range, and the preset optimal efficiency range is a subset of the target power generation efficiency range.

[0020] According to a third aspect, an electronic device is provided, comprising:

[0021] one or more processors;

[0022] a storage device for storing one or more programs,

[0023] When the one or more programs are executed by the one or more processors, the one or more processors implement the heat and electricity coordination method for a solid oxide fuel cell cogeneration system as described in the first aspect.

[0024] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the method for coordinating heat and electricity of a solid oxide fuel cell cogeneration system as described in the first aspect is implemented.

[0025] The above technical solution has the following beneficial technical effects:

[0026] The present invention collects multi-dimensional operating parameters such as the stack temperature, exhaust gas temperature, and fuel flow in real time, and dynamically determines the thermoelectric coordinated control target in combination with the electrical load and thermal load requirements, thereby achieving coordinated regulation of fuel supply and air flow, so that the system output power and waste heat recovery temperature can quickly respond to load changes and maintain a stable matching state. The overtemperature protection strategy prioritizes adjusting the fuel flow and compensating the air flow according to the stoichiometric ratio when the stack temperature is abnormal, which not only effectively controls the stack temperature to return to a safe range, but also maintains the stability of the system operation through combustion efficiency. Based on the dynamic correction mechanism of the boundary value of the target power generation efficiency interval of the real-time thermoelectric ratio, a closed-loop optimization control system is formed to ensure that the system continues to operate in the preset optimal efficiency range under different working conditions, thereby improving the thermoelectric dynamic response capability, operational safety and long-term comprehensive energy efficiency of the solid oxide fuel cell cogeneration system. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The accompanying drawings are provided for a better understanding of the present invention and are not intended to limit the present invention.

[0028] Figure 1 This is a flow chart of a method for coordinating heat and electricity in a solid oxide fuel cell combined heat and power system according to an embodiment of the present invention;

[0029] Figure 2 is a specific flow chart of step S1 of an embodiment of the present invention;

[0030] Figure 3 is a specific flow chart of step S2 of an embodiment of the present invention;

[0031] Figure 4 is a specific flow chart of step S3 of an embodiment of the present invention;

[0032] Figure 5 is a specific flow chart of step S4 of an embodiment of the present invention;

[0033] Figure 6 is a specific flow chart of step S5 of an embodiment of the present invention;

[0034] Figure 7 is a specific flow chart of step S6 of an embodiment of the present invention;

[0035] Figure 8 This is a functional block diagram of a heat and power coordination system of a solid oxide fuel cell combined heat and power system according to an embodiment of the present invention;

[0036] Figure 9 Schematic diagram of the structure of a computer system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0037] The following description of exemplary embodiments of the present invention is made in conjunction with the accompanying drawings, in which various details of the embodiments of the present invention are included to facilitate understanding. These details should be considered as merely exemplary. Therefore, it should be appreciated by those skilled in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0038] like Figure 1 As shown, a method for coordinating heat and electricity in a solid oxide fuel cell combined heat and power system comprises the following steps:

[0039] S1. Acquiring in real time an operating parameter set of the solid oxide fuel cell (SOFC) combined heat and power system, wherein the operating parameter set includes an electric load demand value, a heat load demand value, a stack temperature, an exhaust gas temperature, and a fuel flow rate;

[0040] Specifically, operating parameters are collected in real time through sensors placed at key nodes of the system. The electric load demand value is obtained through real-time feedback from smart meters on the grid or user-terminal electrical equipment; the thermal load demand value is calculated using the return water temperature sensor and flow sensor of the heating pipe network combined with the parameters of the user's end-of-line cooling equipment; the stack temperature is monitored in real time by a K-type thermocouple temperature measuring device installed at the inlet and outlet of the anode / cathode flow channel of the SOFC stack, with an accuracy of ±1°C; the exhaust gas temperature is collected by an infrared thermometer at the exhaust gas outlet of the stack; and the fuel flow rate is measured in real time by a Coriolis mass flowmeter at the anode fuel inlet, with an accuracy of ±0.5% FS. All sensor signals are transmitted to the system controller via 4-20mA analog or Modbus RTU (Remote Terminal Unit) digital signals, and the sampling period is set to 500ms.

[0041] S2. Determining a heat and power coordinated control target value based on the operating parameter set, wherein the heat and power coordinated control target value includes a target power generation efficiency range and a target heating temperature range;

[0042] Specifically, the system controller has a built-in thermoelectric coupling control algorithm based on the mechanism model. First, according to the current stack temperature T stack (Unit: °C), exhaust gas temperature T exh (Unit: °C) and fuel flow rate m fuel (Unit: g / s), through the formula η elec =f(T stack ,m fuel ,λ) to calculate the current power generation efficiency, where λ is the air stoichiometric ratio. The target power generation efficiency range [η min ,η max ] According to the efficiency characteristic curve provided by the stack manufacturer, combined with the current power load demand Pelec_req (Unit: kW) is determined dynamically, for example, when P elec_req When the rated power is 60%-80%, the target range is set to [55%, 65%]. heat_min ,T heat_max ] According to the thermal model of the plate heat exchanger of the waste heat recovery system, combined with the heat load demand Q heat_req (Unit: kW) and exhaust gas temperature T exh Calculations ensure that the outlet water temperature meets the user's heating or domestic hot water needs (e.g. 60-80°C).

[0043] S3. generating a fuel supply adjustment instruction and an air flow adjustment instruction according to the heat and power coordinated control target value;

[0044] Specifically, the controller adopts the model predictive control (MPC) algorithm, with the midpoint value η of the target power generation efficiency interval target and the target heating temperature midpoint value T heat_target To control the target, a multivariable prediction model including the electrochemical reaction kinetics of the fuel cell stack and the thermodynamics of waste heat recovery is established. The fuel flow correction value Δm is solved by rolling optimization. fuel and air flow correction Δm air The air flow rate is calculated based on the fuel composition (e.g., 90% hydrogen and 10% methane) using a stoichiometric ratio. For example, the stoichiometric ratio for a complete reaction is 2 for hydrogen and 2.5 for methane. The resulting fuel supply control command drives the pneumatic proportional valve via a 4-20mA signal, while the air flow control command drives the frequency converter of the centrifugal air pump, with control accuracies of ±1% and ±2% of the rated flow rate, respectively.

[0045] S4. Executing the fuel supply adjustment instruction and the air flow adjustment instruction to dynamically match the output power of the SOFC cogeneration system with the electric load demand value, and simultaneously dynamically matching the output temperature of a waste heat recovery system integrated in the SOFC cogeneration system with the heat load demand value, and generating a real-time heat-to-power ratio;

[0046] Specifically, after receiving the adjustment command, the actuator completes the adjustment of the fuel valve opening and the air pump speed within 500ms. elec The voltage and current sensors at the output of the battery stack are used to calculate in real time (P elec =U×I), heat supply Q heat Through the waste heat recovery system outlet / return water temperature difference ΔT, water flow m water and specific heat capacity c calculation (Q heat =c×m water ×ΔT). The real-time thermal power ratio Rt is defined as the ratio of heat supply to electric power (R th =Qheat / P elec ), which is updated once a second by the data acquisition module and transmitted to the controller for dynamic analysis.

[0047] S5. Real-time monitoring of the stack temperature. When the stack temperature exceeds a preset safety threshold, triggering an over-temperature protection strategy, the over-temperature protection strategy includes preferentially reducing the fuel flow rate until the stack temperature returns to a safe operating range, and simultaneously compensating the air flow rate according to a stoichiometric ratio based on the fuel flow rate;

[0048] Specifically, the preset safety threshold is obtained by calculating the thermodynamic transfer function according to the upper limit of the target heating temperature range; the safe operating range is [preset safety threshold - ΔT, preset safety threshold + ΔT], where ΔT is the maximum temperature fluctuation value allowed by the SOFC cogeneration system.

[0049] Specifically, step 5 includes Figure 1 Step 5a, step 5b, step 5c and step 5d in the above. The stack temperature safety threshold is preset to [750℃, 850℃] (determined according to the temperature resistance characteristics of the stack material). When T stack When the temperature exceeds 850℃, the controller immediately triggers the over-temperature protection: first, the fuel flow rate is reduced at a rate of 10% / s until T stack Falling back to below 850℃, at the same time, according to the real-time value of fuel flow m fuel_new , calculate the required air flow m according to the stoichiometric ratio λ=2.0 (hydrogen working condition) air_new =λ×m fuel_new ×M air / M fuel (M is the molar mass), where M air / M fuel It is the molar mass ratio of air to fuel. The air flow is adjusted by a fast-response solenoid valve to ensure that the combustion efficiency remains above the target value and avoid incomplete combustion caused by reduced fuel volume.

[0050] S6. Based on the real-time heat-to-electricity ratio, dynamically correct the boundary value of the target power generation efficiency range so that the real-time heat-to-electricity ratio of the SOFC cogeneration system is always within a preset optimal efficiency range, where the preset optimal efficiency range is a subset of the target power generation efficiency range.

[0051] Specifically, step 6 includes Figure 1 The preset optimal efficiency interval is an inner subset of the target power generation efficiency interval. For example, when the target interval is [55%, 65%], the optimal interval is set to [58%, 62%]. The controller monitors the thermal power ratio R in real time. th , when three consecutive sampling cycles (1.5s) Rth When the target power generation efficiency range deviates from the theoretical ratio range corresponding to the optimal interval, the fuzzy logic algorithm is used to adjust the target power generation efficiency range boundary value. For example, if the actual R th If the ratio is higher than the upper limit of the optimal interval, it means that the power generation efficiency is low and the lower limit of the target interval needs to be increased by 1%. On the contrary, if R th If the ratio is lower than the lower limit, the upper limit of the target range is reduced by 1%. Through cycle-by-cycle fine-tuning (each adjustment range ≤ 2%), the system is always operated in a narrow range with optimal thermoelectric conversion efficiency.

[0052] The advantages of the above-mentioned electric and thermal coordination method for the solid oxide fuel cell cogeneration system are: this method obtains key operating parameters such as electric load demand value, thermal load demand value, and stack temperature in real time, accurately determines the thermal and electric coordination control target value, and combines the model predictive control algorithm to generate fuel supply and air flow adjustment instructions, thereby realizing dynamic matching of system output power with electric load demand, and waste heat recovery system output temperature with thermal load demand, effectively improving the comprehensive energy utilization rate; at the same time, the overtemperature protection strategy can intervene in time when the stack temperature is abnormal, and ensure safe and stable operation of the system by adjusting the fuel and air flow; the mechanism of dynamically correcting the boundary value of the target power generation efficiency range based on the real-time thermal-electric ratio can enable the system to operate continuously in the optimal efficiency range. Compared with traditional control methods, it further reduces energy consumption and improves the economy and reliability of the cogeneration system.

[0053] like Figure 2 As shown, step S1 specifically includes the following steps:

[0054] S11. The electric load demand value is collected in real time via a smart meter connected to the power output terminal of the SOFC cogeneration system. Specifically, in step S11, a 0.5S-class smart meter is installed at the power output terminal (AC 380V bus) of the SOFC cogeneration system and connected to the central controller via an RS485 interface. The meter collects three-phase voltage, current, and power factor in real time to calculate the electric load demand value. The data refresh rate is 100ms / time, which complies with the GB / T17215.321-2021 electric energy measurement standard. The central controller obtains the electric load data via the Modbus-TCP protocol for subsequent control decisions.

[0055] S12. The heat load demand value is obtained in real time through the heat network monitoring system connected to the heat supply pipe network of the waste heat recovery system. Specifically, in the heat load acquisition of step S12, a temperature and pressure integrated sensor is installed in the heat supply pipe network (DN200 main pipe) of the waste heat recovery system and connected to the SCADA (Supervisory Control And Data Acquisition) heat network monitoring system. The system collects water supply temperature, return water temperature and flow data in real time, calculates the heat load demand value according to the thermodynamic formula Q = cmΔt, and transmits the data to the central controller via the OPC UA protocol with a sampling interval of 500ms. In the formula, c is the specific heat capacity of the medium, m is the mass of the medium, and Δt is the temperature change.

[0056] S13. Measure the stack temperature using multiple thermocouples distributed on the anode and cathode surfaces of the stack. Specifically, in step S13, three K-type armored thermocouples (with a measurement accuracy of ±0.75%) are placed on each of the anode and cathode surfaces of the stack, using a distributed installation with equal spacing (50 mm spacing). The thermocouple signals are converted to a standard 4-20 mA signal via a temperature transmitter and connected to the analog input module of the central controller via shielded twisted-pair cables, enabling full-field monitoring of the stack temperature.

[0057] S14. Obtain the exhaust gas temperature using an infrared temperature sensor installed in the exhaust heat exchanger outlet pipe. Specifically, in step S14, the exhaust gas temperature monitoring is performed by installing an infrared temperature sensor at the flange interface of the exhaust heat exchanger outlet pipe (150 mm diameter). The infrared temperature sensor has a measurement wavelength range of 8-14 μm and a response time of ≤80 ms. The sensor transmits data to the central controller via the 4-20 mA HART (Highway Addressable Remote Transducer) protocol. The sensor is installed 1.5 pipe diameters from the heat exchanger outlet to ensure adequate mixing of the flue gas, achieving a measurement accuracy of ±1°C.

[0058] S15. Real-time monitoring of the fuel flow rate is performed using a flow meter installed in the fuel supply pipeline. Specifically, in step S15, a Coriolis mass flowmeter is installed in a straight section (10D in front and 5D in the rear) of the fuel supply pipeline (316L stainless steel, DN50). The flowmeter directly measures the fuel mass flow rate (in kg / h) and has a pressure rating of PN40. The data is transmitted in real time to a central controller via a Profibus-DP bus with a sampling frequency of 50 Hz.

[0059] The electric load demand value at the power output end is directly collected through smart meters to ensure that the acquired electric load data is real-time and accurate, directly reflecting the actual power supply demand of the system; the heat network monitoring system is used to connect to the heating pipeline network to achieve dynamic tracking of the heat load demand value, effectively integrate the full-link data of the heating end, and improve the systematicness and reliability of heat load monitoring; distributed thermocouples are arranged on the cathode and anode surfaces of the fuel cell body, and multi-point temperature measurement covers the key areas of the fuel cell, avoiding single-point temperature measurement blind spots, improving the comprehensiveness and accuracy of fuel cell temperature monitoring, and providing a reliable basis for thermal runaway warning; the exhaust gas temperature collection point is set at the outlet pipe of the exhaust gas heat exchanger. The temperature parameter at this location is directly related to the actual energy efficiency of the waste heat recovery system, ensuring the targeted control of the heating temperature; the fuel flow metering device is integrated into the fuel supply pipeline to achieve in-situ real-time monitoring of the fuel input, providing accurate basic data for subsequent fuel supply adjustment. The above multi-dimensional and regional parameter collection scheme has built a full-factor monitoring system covering electricity, heat, fuel, and temperature.

[0060] like Figure 3 As shown, step S2 specifically includes: S21, determining a basic efficiency reference value based on the ratio of the electric load demand value to the rated capacity of the SOFC cogeneration system; S22, based on the ratio of the heat load demand value to the maximum heating capacity of the waste heat recovery system, superimposing a temperature compensation coefficient on the basic efficiency reference value to generate a compensated efficiency value; S23, determining the target power generation efficiency range based on the compensated efficiency value, and determining the target heating temperature range in combination with the heat network return water temperature and the preset heating temperature difference.

[0061] Specifically, in step S21, the system controller collects the electric load demand value P in real time. elec_req , and transfer the rated power generation capacity P of the SOFC cogeneration system rated , the degree of matching of the electric load demand is determined by calculating the ratio of the two. According to the efficiency characteristics of the stack at different load rates, the matching degree is divided into three intervals: when the electric load demand is less than 50% of the rated capacity (i.e. low load condition), the basic efficiency benchmark value takes the optimal efficiency of the stack in the low load area of ​​50%; when the load rate is between 50% and 90% (medium load condition), the benchmark value starts at 55% and increases linearly in proportion to the load rate exceeding 50%, ensuring that the efficiency increases reasonably with the load; when the load rate reaches 90% and above (high load condition), the benchmark value takes the stable efficiency value of 60% under the rated load. The above matching rules are pre-stored in the controller's stack efficiency database, which contains efficiency mapping relationships under different fuel compositions (such as pure hydrogen, hydrogen-methane mixture) and operating temperatures (750-850°C).

[0062] Specifically, in step S22, the controller synchronously obtains the heat load demand value Q heat_req and the maximum heating capacity Q of the waste heat recovery systemheat_max (Based on the design exhaust temperature of 600°C and the rated fuel flow calibration), by calculating the matching degree of the heat load demand, a segmented strategy is used to generate the temperature compensation coefficient: when the heat load is lower than 30% of the maximum heating capacity (low heat load), no efficiency compensation is required; when the load rate is between 30% and 80% (medium heat load), the compensation coefficient increases linearly with the load rate to ensure that the heating capacity matches the demand; when the load rate reaches 80% and above (high heat load), the compensation amplitude is limited to avoid excessive sacrifice of power generation efficiency. Finally, the compensation coefficient is superimposed on the basic efficiency benchmark value to generate the compensated efficiency value as the central adjustment benchmark for the target power generation efficiency range. At the same time, the return water temperature T is collected in real time through the temperature sensor of the heat network return water pipe. return , providing basic parameters for heating temperature range calculation.

[0063] Specifically, in step S23, the target power generation efficiency range is centered on the compensated efficiency value, and a fluctuation boundary of ±5% is set in combination with the efficiency stability of the fuel stack under ±10% fluctuation of the fuel flow rate to form an adjustment range that includes efficiency robustness. The target heating temperature range is determined based on the preset heating temperature difference of the user-end heat dissipation form (such as floor heating, radiator) and the real-time return water temperature. While meeting the water supply temperature accuracy requirements, an adjustment margin is reserved for fluctuations in heat exchanger efficiency and changes in environmental factors. For example, when the preset heating temperature difference is 20°C and the return water temperature is 50°C, the target heating temperature range is 65-75°C, ensuring that the outlet water temperature is stable at 70°C±5°C.

[0064] The calculation formula for the above-mentioned electric load demand matching degree is as follows:

[0065]

[0066] Among them, K elec is the degree of matching of electric load demand, dimensionless; P elec_req is the real-time electric load demand value, in kW; P rated is the rated power generation capacity of the SOFC system, in kW.

[0067] The calculation formula for the above heat load demand matching degree is as follows:

[0068]

[0069] Among them, K heat is the heat load demand matching degree, dimensionless, Q heat_req is the real-time heat load demand value, in kW; Q heat_max The maximum heating capacity of the waste heat recovery system is in kW. This value is calibrated based on the design operating conditions.

[0070] The boundary formula of the above target power generation efficiency interval is as follows:

[0071] η min =η comp -5%;

[0072] η max =η comp +5%;

[0073] Among them, η min is the lower limit of target power generation efficiency, percentage; η max is the upper limit of target power generation efficiency, percentage; η comp It is the efficiency value after compensation, which is obtained by superimposing the basic efficiency reference value and the temperature compensation coefficient, in percentage.

[0074] The boundary formula of the target heating temperature range is as follows:

[0075] T heat_min =T return +ΔT set -5℃;

[0076] T heat_max =T return +ΔT set +5℃;

[0077] Among them, T heat_min is the lower limit of the target heating temperature, in °C; T heat_max is the upper limit of the target heating temperature, in °C; T return is the return water temperature of the heating network, in °C; ΔT set It is the preset heating temperature difference, in °C (determined by the user's heat dissipation form).

[0078] like Figure 4 As shown, the generation of the fuel supply adjustment instruction in step S3 includes:

[0079] S31. Calculating the theoretical maximum value of the fuel flow rate using the upper limit of the target power generation efficiency range as a constraint condition;

[0080] S32, using the rate of change of the stack temperature as a feedback variable, dynamically adjusting the theoretical maximum value of the fuel flow rate using a proportional-integral control algorithm to generate a corrected upper limit value of the fuel flow rate;

[0081] S33: Output the corrected fuel flow upper limit as the fuel supply adjustment instruction.

[0082] The generation of the air flow adjustment instruction in step S3 includes:

[0083] S34, calculating a theoretical stoichiometric ratio value according to the fuel flow value in the fuel supply adjustment instruction;

[0084] S35. Based on the deviation between the exhaust gas temperature and the target heating temperature range, the theoretical value of the stoichiometric ratio is corrected to generate an optimized stoichiometric ratio;

[0085] S36: Convert the optimized stoichiometric ratio into a fan speed control signal, and generate the air flow adjustment instruction based on the fan speed control signal.

[0086] Specifically, in the process of generating the fuel supply adjustment instruction in step S3, the specific implementation is as follows: first, S31 is executed, and the upper limit value η of the target power generation efficiency range is set. e_max As a constraint condition, the power generation efficiency formula η based on the solid oxide fuel cell e =P e / (Q f × LHV)(where P e is the output power of the stack, Q f is the fuel flow rate, LHV is the lower heating value of the fuel), combined with the current power load demand value P e demand , calculate the theoretical maximum fuel flow rate Q f_max =P e_demand / (η e_max × LHV), which reflects the minimum fuel flow required to meet the electrical load at the highest target power generation efficiency. Then, S32 is executed, and the stack temperature change rate dT / dt is used as the feedback variable, and the proportional integral (PI) control algorithm is used to dynamically adjust the theoretical maximum value of the fuel flow: the PI controller input is the measured value of the stack temperature T stack and the safety threshold interval [T min ,T max ] deviation rate and change rate, output correction coefficient ΔK f =K p (dT / dt)+K i ·∫(T stack -T set )dt(where K p is the proportionality coefficient, K i is the integral coefficient, T set is the target operating temperature of the stack), through ΔK f Q f_max Correction is performed to obtain the corrected fuel flow upper limit value Q f_upper =Q f_max ×(1+ΔK f ), this correction process can suppress the trend of abnormal increase or decrease in the temperature of the battery stack. Finally, S33 is executed to set Q f_upper Output to the fuel supply system as a fuel supply adjustment command, which is also limited by the fuel flow safety upper limit Q f_safe_max , that is, the actual output value is Qf_upper With Q f_safe_max The smaller value in ensures the safety of the adjustment process.

[0087] Specifically, in the process of generating the air flow adjustment instruction in step S3, the specific implementation is as follows: first, S34 is executed, and the fuel flow value Q in the fuel supply adjustment instruction is calculated. f_cmd , calculate the theoretical value of the stoichiometric ratio λ based on the fuel chemical reaction formula sto =Q air_sto / Q f_cmd (where Q air_sto The theoretical air flow rate required for complete fuel reaction) is determined by the fuel composition (such as the ratio of hydrogen and methane) and the chemical reaction equation. For example, for pure hydrogen fuel, λ sto =0.5(2H2+O2→2H2O). Then execute S35 to collect the exhaust gas temperature T exhaust And calculate its difference with the target heating temperature range [T heat_min ,T heat_max ] the central value T heat_set Deviation ΔT=T exhaust -T heat_set , a proportional control algorithm with limiting is used to correct λsto: when ΔT>0, it means that the exhaust temperature is higher than the target range, and the air flow needs to be increased to reduce the combustion temperature. The correction amount Δλ=K p_heat ·ΔT(K p_heat is the heating temperature adjustment coefficient), generating the optimized stoichiometric ratio λ opt =λ sto +Δλ, and λ opt Not less than the minimum safe stoichiometric ratio λ safe_min (avoid oxygen-deficient combustion); when ΔT≤0, λ opt =λ sto Finally, S36 is executed, and according to the fan characteristic curve n=k fan ·λ opt (n is the fan speed, k fan is the speed-to-stoichiometric ratio conversion coefficient, determined by the fan factory characteristic test), and λ opt Converted into fan speed control signal, combined with the fan safety speed range [n min ,n max ] Generates an air flow control instruction, which controls the air flow Q by adjusting the opening of the air fan inverter. air =k q ·n(k q Precise control of the fan flow coefficient ensures that the exhaust temperature dynamically matches the heat load demand while maintaining efficient combustion.

[0088] The embodiment of the present invention achieves precise control of electric-thermal coupling under multi-dimensional constraints through the coordinated generation strategy of fuel supply adjustment instructions and air flow adjustment instructions, resulting in the following beneficial technical effects: In fuel supply adjustment, the theoretical maximum value of the fuel flow is dynamically defined based on the target power generation efficiency upper limit, ensuring that the system operates within the high power generation efficiency range. Furthermore, by introducing the proportional-integral control algorithm with the stack temperature change rate as the feedback variable, abnormal temperature fluctuations are suppressed in real time. Compared with traditional fixed efficiency threshold control, this reduces the risk of stack temperature overheating and avoids the heat output lag caused by relying solely on electrical load to adjust the fuel flow. In air flow adjustment, the theoretical stoichiometric ratio of the fuel flow is combined with dynamic correction of exhaust temperature deviation to form a "fuel-air-temperature" closed-loop control link, improving the exhaust temperature adjustment response speed and significantly reducing the fluctuation range of the heating temperature. By optimizing the stoichiometric ratio, the risk of oxygen-deficient combustion is effectively avoided, maintaining a high level of combustion efficiency. Through the synergistic effect of the two, the system's real-time heat-to-electricity ratio automatically converges to the preset optimal efficiency range, improving both power generation efficiency and waste heat recovery efficiency compared to the existing technology, while achieving the simultaneous optimization of the stack temperature safety margin and heating quality.

[0089] like Figure 5 As shown, step S4 includes the following steps:

[0090] S41, executing the fuel supply adjustment instruction, and controlling the fuel flow rate through a closed loop so that the actual power generation power of the SOFC cogeneration system dynamically tracks the electric load demand value;

[0091] S42, executing the air flow adjustment instruction to control the exhaust gas thermal power by adjusting the air supply so that the output temperature of the waste heat recovery system dynamically matches the heat load demand value;

[0092] S43. Calculate and output the real-time thermal-to-electricity ratio based on the actual generated power and the exhaust gas thermal power.

[0093] Specifically, S41 dynamic tracking control of power generation includes: collecting the voltage V of the stack in real time through the voltage sensor and current sensor at the output end of the stack. stack With the output current I stack , calculate the actual power generation P elec =V stack I stack , and compare it with the electric load demand value P demand Input to the proportional-integral-derivative (PID) controller to generate the fuel flow correction signal ΔQ f The correction signal is consistent with the fuel flow rate upper limit value Q output in step S3. f_upperAfter superposition, the fuel supply valve (such as a proportional solenoid valve or a metering pump) is driven by a servo driver to form a closed-loop control loop for fuel flow. The control period is set to 50ms to ensure that the actual generated power tracks the electrical load demand with a steady-state error of less than ±2%, and the response time does not exceed 100ms.

[0094] Specifically, the S42 exhaust gas thermal power and heating temperature control specifically includes: the air flow adjustment instruction controls the air fan speed through the variable frequency drive, thereby adjusting the air flow Q entering the fuel cell stack air . Exhaust gas heat power P heat The exhaust gas mass flow rate Q exh Calculated with the change in exhaust enthalpy, where Q exh Measured by ultrasonic flow meter, enthalpy value is based on exhaust gas temperature sensor T exh and air inlet temperature T air_in The output temperature T of the waste heat recovery system output The temperature sensor on the secondary side of the plate heat exchanger monitors the temperature in real time and compares it with the target heating temperature range. The fuzzy PID controller fine-tunes the air flow control instruction to form a temperature-flow double closed-loop control so that T output Dynamically match heat load demand with an accuracy of ±1°C while controlling exhaust gas temperature fluctuations within the target range.

[0095] Specifically, S43 real-time heat-to-electricity ratio calculation and output specifically includes: actual power generation power P elec Directly use the calculated value in S41, exhaust gas thermal power P heat Calculation based on the law of conservation of energy: P heat =Q exh c p ·(T exh -T air_in ), where c p is the constant pressure specific heat capacity of the tail gas (dynamically corrected by the online gas analyzer data based on the real-time gas composition). Real-time thermoelectric ratio TER = P elec / P heat It is generated by real-time calculation by an embedded control unit (such as a DSP or PLC) and output to the system main controller via the Modbus communication protocol. It serves as a key parameter for the dynamic correction of the boundary value of the target power generation efficiency range in step S6. The update frequency is 20 Hz, ensuring that the calculation accuracy of the thermal-electric ratio is better than ±0.5%.

[0096] This technical solution achieves deep coupling and adaptive regulation of electric and thermal output through the coordinated design of dynamic power tracking, precise control of exhaust thermal power, and real-time heat-to-electricity ratio calculation. On the power generation side, a closed-loop control mechanism based on fuel supply instructions enables actual power generation to quickly respond to load fluctuations and maintain stable tracking, effectively avoiding the power overshoot and lag problems common in traditional open-loop control and improving power supply reliability. On the heat supply side, through the linkage control of air flow regulation and exhaust thermal power, a direct regulation link between "air supply, combustion reaction, and waste heat recovery" is established, ensuring that the output temperature of the waste heat recovery system matches the heat load demand in real time, avoiding the limitation of traditional combined heat and power systems where heat output depends on passive adjustment of the stack power. The calculation and output of the real-time heat-to-electricity ratio provides a key feedback parameter for optimizing the overall system efficiency, transforming the electric and thermal coupling relationship from passive response to active optimization. This not only ensures the dynamic balance of electric and thermal output, but also provides data support for subsequent efficiency range correction. Ultimately, the system achieves efficient and stable operation under variable load conditions, improving the engineering practicality and economic efficiency of solid oxide fuel cell combined heat and power systems.

[0097] like Figure 6 As shown, step S5 specifically includes the following steps:

[0098] S51, obtaining the temperature of the fuel cell stack in real time through distributed temperature sensors;

[0099] Specifically, a distributed array of K-type thermocouple temperature sensors is deployed at key locations in the SOFC stack (such as the anode inlet, cathode outlet, and between cell layers). The sampling frequency is 10 Hz, and the measured values ​​from each sensor are transmitted to the PLC controller via the CAN bus. The system applies Kalman filtering to the temperature values ​​at each measurement point to eliminate measurement noise. The temperature field gradient is also calculated, and the highest temperature value in the stack is used as the basis for overtemperature detection.

[0100] S52, when the temperature of the battery stack exceeds the preset safety threshold, entering an over-temperature protection state;

[0101] Specifically, when the temperature at any measuring point exceeds a preset safety threshold (e.g., 850°C), the PLC controller immediately activates the over-temperature protection interrupt routine, triggering the audible and visual alarm system and switching the system control mode from "thermal and electrical coordination mode" to "temperature priority mode." At this point, the system automatically blocks conventional control instructions and enters the preset protection control logic.

[0102] S53, performing the following fuel flow rate staged regulation in the over-temperature protection state: in the first stage, controlling the fuel regulating valve to reduce the fuel flow rate at a constant rate; in the second stage, monitoring the rate of decrease of the stack temperature in real time, and when the rate of decrease enters a preset stable range, switching to a proportional-integral control mode based on the stack temperature deviation;

[0103] Specifically, in the first stage, the PLC (Programmable Logic Controller) controls the fuel regulating valve through the servo driver to reduce the fuel flow at a constant rate of 0.5L / min, and starts the timer T1 at the same time. This stage lasts until the temperature drop rate of the fuel cell stack reaches 0.2℃ / s, or the fuel flow rate drops to 60% of the rated value. In the second stage, when the temperature drop rate enters the preset stable range (0.1~0.3℃ / s), the system switches to PI control mode. The controller takes the deviation between the fuel cell stack temperature and the midpoint value of the safety range (for example, 800℃) as input, and calculates the fuel flow correction amount through the PI algorithm. The proportional coefficient K p =0.05L / (min·℃), integral coefficient K i =0.001L / (min·℃·s), achieving fine adjustment of fuel flow.

[0104] S54, calculating a real-time air compensation amount based on the current fuel flow rate and the preset stoichiometric ratio;

[0105] Specifically, according to the current fuel flow Q f Calculate the theoretical air demand Q based on the stoichiometric ratio λ = 2.5 (1.5 times the theoretical value of the methane reforming reaction safety margin) a =Q f ×λ×ρ f / ρ a (ρ f , ρ a Considering the change of air specific heat capacity at high temperature, the temperature correction coefficient α=1+0.0005×(T stack -750), the final air compensation amount Q comp =Q a ×α.

[0106] S55, adjusting the air flow rate to the real-time air compensation amount through an independently controlled air supply device;

[0107] Specifically, the PLC adjusts the output frequency of the air supply fan inverter through an independent PID controller, and the PID parameter is set to K p =0.5Hz / (m 3 / h), T i =10s, T d = 2s. Air flow is monitored in real time by a vortex flowmeter, forming a closed-loop control with a response time of less than 500ms, ensuring that air flow quickly tracks the calculated value and maintains stable combustion efficiency.

[0108] S56 , continuously monitoring the temperature of the fuel cell stack, and exiting the over-temperature protection state when the temperature of the fuel cell stack remains stable within the safe operating range for a preset duration.

[0109] Specifically, when the temperature of all measuring points in the fuel cell stack remains within the safe range (700-850°C) for 10 consecutive minutes, the system automatically exits the over-temperature protection state. During the exit process, the fuel flow rate returns to the normal control value at a rate of 0.3L / min, and the air flow rate is adjusted synchronously to prevent temperature rebound. The data of the entire over-temperature protection process (temperature change curve, fuel / air flow adjustment record) is automatically stored in the system log and kept for 10 years.

[0110] This technical solution establishes a three-dimensional temperature protection system for the fuel cell stack through a hierarchical, multi-dimensional over-temperature protection control strategy. Its advantages are as follows: a distributed temperature sensor array enables real-time monitoring of the entire stack temperature field, avoiding blind spots in single-point measurement and improving the accuracy and reliability of over-temperature warnings. The fuel flow rate adjustment mechanism combines rapid response with precise control. In the first stage, constant rate regulation ensures immediate intervention in the event of over-temperature. In the second stage, proportional-integral control based on temperature deviation enables dynamic adaptation of the cooling process, effectively balancing cooling speed and control accuracy, and avoiding temperature overshoot or regulation lag in traditional single-control modes. The coordinated design of real-time air compensation calculation and independent air supply control dynamically adjusts the air supply according to the stoichiometric ratio while reducing the fuel flow rate, ensuring that combustion efficiency remains within a reasonable range while avoiding secondary safety risks caused by imbalance in the air-fuel ratio. A protection state exit mechanism based on temperature stability ensures that the system resumes normal control after continuous and stable operation within the safety threshold, preventing frequent switching of protection strategies and temperature rebound, improving the safety and operational robustness of the solid oxide fuel cell stack under abnormal operating conditions, and providing technical support for the long-term reliable operation of the system.

[0111] like Figure 7 As shown, step S6 may specifically include the following steps:

[0112] S61, calculating the deviation between the real-time thermal-to-electricity ratio and the median of the preset optimal efficiency range;

[0113] Specifically, in step S61, when calculating the deviation between the real-time thermoelectric ratio and the median of the preset optimal efficiency interval, the real-time thermoelectric ratio data output by step S43 is first obtained. The preset optimal efficiency interval has a minimum value and a maximum value, and the median of the interval is obtained by calculating the average of the two. The real-time thermoelectric ratio is compared with the median, and the absolute value of the difference between the two is calculated to obtain the absolute deviation. In order to more conveniently evaluate the degree of deviation and eliminate the influence of the data dimension, the absolute deviation is divided by the width of the preset optimal efficiency interval (i.e., the difference between the maximum and minimum values) to obtain the normalized deviation. This series of calculation processes is executed in real time by the system's embedded control unit at a frequency of 20Hz, and the real-time thermoelectric ratio data is obtained from the thermoelectric ratio calculation module through the Modbus protocol to ensure the real-time and accuracy of the calculation.

[0114] S62: When the deviation exceeds a first threshold, adjusting the lower limit of the target power generation efficiency range by a preset step size, wherein the first threshold is less than half the width of the preset optimal efficiency range;

[0115] Specifically, in step S62, when the calculated normalized deviation exceeds the first threshold, the adjustment operation of the lower limit of the target power generation efficiency range will be triggered. The first threshold is set to be less than half of the preset optimal efficiency range width, for example, it can be set to 0.25. The adjustment direction depends on the relative size relationship between the real-time heat-to-electricity ratio and the median of the preset optimal efficiency range: if the real-time heat-to-electricity ratio is greater than the median, it means that the current operating state of the system tends to produce heat. At this time, the step size is reduced according to the preset lower limit, for example, 0.5%, and the lower limit value of the target power generation efficiency range is reduced; if the real-time heat-to-electricity ratio is less than the median, the step size is increased according to the preset upper limit, also 0.5%, and the lower limit value is increased. After the adjustment is completed, the new lower limit value needs to be verified to ensure that it is not lower than the safe lower limit of power generation efficiency, for example, 40%, so as to ensure the feasibility of the adjustment process in actual engineering applications.

[0116] S63: When the deviation exceeds a second threshold, adjusting the upper limit of the target power generation efficiency range according to a preset step size, wherein the second threshold is greater than the first threshold and less than the width of the preset optimal efficiency range;

[0117] Specifically, in step S63, when the normalized deviation exceeds the second threshold, the adjustment mechanism for the upper limit of the target power generation efficiency range will be activated. The second threshold is set to be greater than the first threshold and less than the width of the preset optimal efficiency range, for example, 0.75. The adjustment strategy is determined based on the deviation of the real-time heat-to-electricity ratio from the boundary of the preset optimal efficiency range: if the real-time heat-to-electricity ratio is greater than the maximum value of the preset optimal efficiency range, it indicates that the system heat production ratio is too high. At this time, the upper limit value of the target power generation efficiency range is reduced by the step size according to the preset upper limit, for example, 1%. If the real-time heat-to-electricity ratio is less than the minimum value of the preset optimal efficiency range, it indicates that the power generation ratio is too high. In this case, the upper limit value is increased by the step size according to the preset upper limit, that is, 1%. After the adjustment, it is necessary to ensure that the new upper limit value does not exceed the stack efficiency limit value, for example, 65%, and to ensure that the preset optimal efficiency range is always a subset of the adjusted target range.

[0118] S64: when the number of consecutive adjustments reaches a preset limit and the real-time heat-to-electricity ratio still cannot enter the preset optimal efficiency range, resetting the heat-to-electricity coordinated control target value to an initial calibration value;

[0119] Specifically, in step S64, the system sets a continuous adjustment counter. Whenever the adjustment operation in step S62 or S63 is performed, the counter value is increased by 1. When the counter value reaches the preset limit, for example 10 times, and the real-time thermal-electric ratio still does not enter the preset optimal efficiency range, the system will trigger the control target value reset program. The reset process includes reading the initial calibration target power generation efficiency range determined by the full-load operating condition test before the system leaves the factory from the EEPROM (Electrically Erasable Programmable read only memory). The initial range contains the optimal range and leaves a 10% safety margin. At the same time, the adjustment counter is cleared and a reset alarm signal is sent to the monitoring interface to remind the operation and maintenance personnel to check whether there are abnormal external load fluctuations or sensor failures, so as to prevent the control parameters from drifting due to long-term abnormal operating conditions.

[0120] S65 . Generate a new thermal-electricity coordinated control target value based on the adjusted target power generation efficiency range, and maintain the preset optimal efficiency range as a subset of the adjusted target power generation efficiency range.

[0121] Specifically, in step S65, after the target power generation efficiency range is adjusted, whether through normal adjustment or reset operation, the control unit will redefine the preset optimal efficiency range. Specifically, based on the lower and upper limits of the adjusted target power generation efficiency range, the minimum and maximum values ​​of the preset optimal efficiency range are determined through a specific calculation. The calculation formula is: the minimum value of the preset optimal efficiency range = the new lower limit + (new upper limit - new lower limit) × 0.3, and the maximum value of the preset optimal efficiency range = the new upper limit - (new upper limit - new lower limit) × 0.3. This ensures that the preset optimal efficiency range is always located near the center axis of the target range and its width is 60% of the target range. The newly generated thermal power coordinated control target value is synchronously transmitted to the fuel supply and air flow control module via the CAN bus, and the efficiency range display content on the human-machine interface is updated at the same time, realizing adaptive iteration of the system efficiency optimization strategy.

[0122] The normalized deviation D is used to quantify the degree of deviation between the real-time thermal power ratio and the median of the preset optimal efficiency range. The calculation formula is: D = |RM| / W. R represents the real-time thermal power ratio, that is, the ratio of the actual power generation of the system to the thermal power of the exhaust gas; M is the median of the preset optimal efficiency range, and the minimum value O of the range is passed. min With the maximum value O max The calculation is as follows: M=(O min +O max ) / 2. This value reflects the center position of the optimal efficiency range; W represents the width of the preset optimal efficiency range, that is: W=0 max -O min W is used to normalize the deviation to eliminate the dimension effect and make the deviation degrees in different intervals comparable.

[0123] The optimal efficiency interval redefinition formula is used to redefine the boundaries of the preset optimal efficiency interval after the target power generation efficiency interval is adjusted. The specific formula is: min_new =E low +0.3*(E high -E low ), O max_new =E high -0.3*(E high -E low ). Among them, E low and E high are the lower and upper limits of the adjusted target power generation efficiency range, representing the power generation efficiency constraint range of the current system operation; min_new and O max_newThe minimum and maximum values ​​of the newly generated preset optimal efficiency range are based on the target range. This formula ensures that the optimal range is always located near the center axis of the target range (accounting for 60% of the target range width), preserving the core range for efficiency optimization while providing a reasonable adjustment margin for system operation.

[0124] This embodiment is based on the deviation analysis between the real-time heat-to-electricity ratio and the preset optimal efficiency range, which realizes the accurate quantitative evaluation of the system's electric and thermal output characteristics, so that the target power generation efficiency range can be dynamically corrected according to the actual operating conditions, effectively solving the problem of efficiency optimization lag in traditional fixed-range control; the hierarchical adjustment strategy (the first threshold triggers the lower limit adjustment, and the second threshold triggers the upper limit adjustment) forms a progressive control logic from shallow to deep, which not only ensures fine adjustment under small deviations, but also can respond quickly to large deviations, thereby improving the system's adaptability to complex load fluctuations; the continuous adjustment within the preset limits and the initial value reset mechanism build a dual protection system, while avoiding excessive drift of control parameters, ensuring that the system always operates in a safe and efficient range; by maintaining the preset optimal efficiency range as a subset of the target range, a reasonable adjustment margin is provided for the operating parameters while retaining the core efficiency optimization range, and ultimately achieving a coordinated improvement in power generation efficiency and waste heat recovery efficiency.

[0125] like Figure 8 As shown, a heat and electricity coordination system of a solid oxide fuel cell combined heat and power system comprises:

[0126] a parameter acquisition module for acquiring in real time an operating parameter set of the solid oxide fuel cell cogeneration system, the operating parameter set including an electric load demand value, a thermal load demand value, a stack temperature, an exhaust gas temperature, and a fuel flow rate;

[0127] a target determination module, configured to determine a heat and power coordinated control target value based on the operating parameter set, wherein the heat and power coordinated control target value includes a target power generation efficiency range and a target heating temperature range;

[0128] An instruction generation module, configured to generate a fuel supply adjustment instruction and an air flow adjustment instruction according to the heat and power coordinated control target value;

[0129] an instruction execution module, configured to execute the fuel supply adjustment instruction and the air flow adjustment instruction, so as to dynamically match the output power of the cogeneration system with the electric load demand value, and simultaneously dynamically match the output temperature of a waste heat recovery system integrated in the cogeneration system with the heat load demand value, and generate a real-time heat-to-power ratio;

[0130] an over-temperature protection module, configured to monitor the stack temperature in real time and trigger an over-temperature protection strategy when the stack temperature exceeds a preset safety threshold. The over-temperature protection strategy includes preferentially reducing the fuel flow rate until the stack temperature returns to a safe operating range, and simultaneously compensating the air flow rate according to a stoichiometric ratio based on the fuel flow rate;

[0131] A dynamic optimization module is used to dynamically correct the boundary value of the target power generation efficiency range based on the real-time heat-to-electricity ratio, so that the real-time heat-to-electricity ratio of the cogeneration system is always within a preset optimal efficiency range, and the preset optimal efficiency range is a subset of the target power generation efficiency range.

[0132] In some embodiments, the parameter acquisition module includes:

[0133] An electric power parameter acquisition unit, configured to acquire electric load demand values ​​in real time via a smart meter connected to an electric power output terminal of the cogeneration system;

[0134] A heat load acquisition unit is used to obtain the heat load demand value in real time through a heat network monitoring system connected to the heat supply network of the waste heat recovery system;

[0135] A stack temperature monitoring unit is used to measure the stack temperature through a plurality of thermocouples distributed on the anode and cathode surfaces of the stack body;

[0136] The exhaust gas temperature monitoring unit is used to obtain the exhaust gas temperature through an infrared temperature sensor installed in the exhaust gas heat exchanger outlet pipe;

[0137] The fuel flow monitoring unit is used to monitor the fuel flow in real time through a flow metering device arranged in the fuel supply pipeline.

[0138] In some embodiments, the target determination module includes:

[0139] a basic efficiency calculation unit, configured to determine a basic efficiency reference value according to a ratio of the electric load demand value to the rated capacity of the cogeneration system;

[0140] a temperature compensation calculation unit, configured to add a temperature compensation coefficient to the basic efficiency reference value based on a ratio of the heat load demand value to the maximum heating capacity of the waste heat recovery system to generate a compensated efficiency value;

[0141] The target interval generating unit is configured to determine the target power generation efficiency interval according to the compensated efficiency value, and determine the target heating temperature interval in combination with the return water temperature of the heating network and a preset heating temperature difference.

[0142] In some embodiments, the fuel supply adjustment instruction generation unit of the instruction generation module includes:

[0143] A theoretical calculation subunit, configured to calculate a theoretical maximum value of the fuel flow rate using the upper limit of the target power generation efficiency range as a constraint condition;

[0144] a dynamic correction subunit, configured to dynamically adjust the theoretical maximum value of the fuel flow rate using a proportional-integral control algorithm with the rate of change of the fuel stack temperature as a feedback variable, thereby generating a corrected upper limit value of the fuel flow rate;

[0145] The instruction output subunit is used to output the corrected fuel flow upper limit value as the fuel supply adjustment instruction.

[0146] In some embodiments, the air flow adjustment instruction generation unit of the instruction generation module includes:

[0147] a stoichiometric ratio calculation subunit, configured to calculate a theoretical stoichiometric ratio value according to the fuel flow value in the fuel supply adjustment instruction;

[0148] a temperature deviation correction subunit, configured to correct the theoretical value of the stoichiometric ratio based on a deviation between the exhaust gas temperature and the target heating temperature range to generate an optimized stoichiometric ratio;

[0149] The speed control conversion subunit is used to convert the optimized stoichiometric ratio into a fan speed control signal and generate the air flow adjustment instruction based on the signal.

[0150] In some embodiments, the instruction execution module includes:

[0151] a fuel closed-loop control unit, configured to execute the fuel supply adjustment instruction and control the fuel flow rate in a closed-loop manner so that the actual power generation power of the cogeneration system dynamically tracks the electric load demand value;

[0152] an air flow regulating unit, configured to execute the air flow regulating instruction, control the exhaust gas thermal power by adjusting the air supply, and dynamically match the output temperature of the waste heat recovery system with the heat load demand value;

[0153] The thermoelectric ratio calculation unit is used to calculate and output the real-time thermoelectric ratio based on the actual power generation power and the exhaust gas thermal power.

[0154] In some embodiments, the over-temperature protection module includes:

[0155] A temperature monitoring unit, configured to obtain the temperature of the fuel cell stack in real time through distributed temperature sensors;

[0156] An over-temperature trigger unit, configured to trigger an over-temperature protection state when the temperature of the battery stack exceeds the preset safety threshold;

[0157] A fuel staged regulation unit is configured to, in the over-temperature protection state, perform the following: in the first stage, control the fuel regulating valve to reduce the fuel flow at a constant rate; in the second stage, when the temperature drop rate enters a preset stable range, switch to a proportional-integral control mode based on the temperature deviation;

[0158] An air compensation calculation unit, used to calculate a real-time air compensation amount based on a current fuel flow rate and a preset stoichiometric ratio;

[0159] an air supply control unit, configured to adjust the air flow rate to the real-time air compensation amount through an independently controlled air supply device;

[0160] The stable exit unit is used to continuously monitor the temperature of the fuel cell stack and exit the over-temperature protection state when the temperature remains stable within the safe operating range for a preset duration.

[0161] In some embodiments, the dynamic optimization module includes:

[0162] a deviation calculation unit, configured to calculate a deviation between the real-time thermal-to-electricity ratio and a median of the preset optimal efficiency range;

[0163] a lower limit adjustment unit, configured to adjust the lower limit of the target power generation efficiency range according to a preset step size when the deviation exceeds a first threshold, wherein the first threshold is less than half the width of the preset optimal efficiency range;

[0164] an upper limit adjustment unit, configured to adjust the upper limit of the target power generation efficiency range according to a preset step size when the deviation exceeds a second threshold, wherein the second threshold is greater than the first threshold and less than the width of the preset optimal efficiency range;

[0165] a control resetting unit, configured to reset the heat-power coordinated control target value to an initial calibration value when the number of consecutive adjustments reaches a preset limit and still fails to make the real-time heat-to-electricity ratio enter the preset optimal efficiency range;

[0166] The target updating unit is configured to generate a new heat and power coordinated control target value based on the adjusted target power generation efficiency interval, and maintain the preset optimal efficiency interval as a subset of the adjusted target interval.

[0167] In some embodiments, the preset safety threshold is obtained by calculating the thermodynamic transfer function based on the upper limit value of the target heating temperature range; the safe operating range is [preset safety threshold - ΔT, preset safety threshold + ΔT], where ΔT is the maximum temperature fluctuation value allowed by the cogeneration system.

[0168] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0169] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any one of the above-mentioned methods for coordinating heat and electricity in a solid oxide fuel cell cogeneration system.

[0170] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor, it can implement the steps of the above-mentioned various method embodiments. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc. Of course, there are other ways of readable storage media, such as quantum memory, graphene memory, etc. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practices in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practices, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0171] The present invention also provides an electronic device. The electronic device in an embodiment of the present invention includes: one or more processors; and a storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the power-heat coordination method for a solid oxide fuel cell cogeneration system provided by the present invention.

[0172] Reference below Figure 9 , which shows a schematic structural diagram of a computer system 800 of an electronic device suitable for implementing an embodiment of the present invention. Figure 9 The electronic device shown is only an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0173] like Figure 9 As shown, the computer system 900 includes a central processing unit (CPU) 901, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 902 or a program loaded from a storage unit 908 into a random access memory (RAM) 903. Various programs and data required for the operation of the computer system 900 are also stored in the RAM 903. The CPU 901, the ROM 902, and the RAM 903 are connected to each other via a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0174] The following components are connected to the I / O interface 905: an input section 906 including a keyboard, a mouse, and the like; an output section 907 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 908 including a hard disk and the like; and a communication section 909 including a network interface card such as a LAN card or a modem. The communication section 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to the I / O interface 905 as needed. A removable medium 911, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 910 as needed, so that computer programs read therefrom can be installed in the storage section 908 as needed.

[0175] In particular, according to embodiments disclosed herein, the processes described in the main step diagrams above can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for executing the methods shown in the main step diagrams. In the above embodiments, the computer program can be downloaded and installed from a network via the communication section 909 and / or installed from removable media 911. When the computer program is executed by the central processing unit 901, the above-described functions defined in the system of the present invention are performed.

[0176] It should be noted that the computer-readable medium described in the present invention may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device, or component. In the present invention, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wireline, optical cable, RF, or any suitable combination thereof.

[0177] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the above-mentioned module, program segment, or a part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0178] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A method for coordinating heat and electricity in a solid oxide fuel cell combined heat and power system, characterized in that: The following steps are involved: S1. Acquiring in real time an operating parameter set of the solid oxide fuel cell (SOFC) combined heat and power system, wherein the operating parameter set includes an electric load demand value, a heat load demand value, a stack temperature, an exhaust gas temperature, and a fuel flow rate; S2. Determining a heat and power coordinated control target value based on the operating parameter set, wherein the heat and power coordinated control target value includes a target power generation efficiency range and a target heating temperature range; S3. generating a fuel supply adjustment instruction and an air flow adjustment instruction according to the heat and power coordinated control target value; S4. Executing the fuel supply adjustment instruction and the air flow adjustment instruction to dynamically match the output power of the SOFC cogeneration system with the electric load demand value, and simultaneously dynamically matching the output temperature of a waste heat recovery system integrated in the SOFC cogeneration system with the heat load demand value, and generating a real-time heat-to-power ratio; S5. Real-time monitoring of the stack temperature. When the stack temperature exceeds a preset safety threshold, triggering an over-temperature protection strategy, the over-temperature protection strategy includes preferentially reducing the fuel flow rate until the stack temperature returns to a safe operating range, and simultaneously compensating the air flow rate according to a stoichiometric ratio based on the fuel flow rate; S6. Based on the real-time heat-to-electricity ratio, dynamically correct the boundary value of the target power generation efficiency range so that the real-time heat-to-electricity ratio of the SOFC cogeneration system is always within a preset optimal efficiency range, where the preset optimal efficiency range is a subset of the target power generation efficiency range.

2. The electric heating coordination method according to claim 1, characterized in that: Step S1 specifically includes: S11, collecting the electric load demand value in real time through a smart meter connected to the power output end of the SOFC cogeneration system; S12, obtaining the heat load demand value in real time through a heat network monitoring system connected to the heat supply pipe network of the waste heat recovery system; S13, measuring the temperature of the fuel cell stack by using a plurality of thermocouples distributedly arranged on the anode side and cathode side surfaces of the fuel cell stack body; S14, obtaining the exhaust gas temperature by using an infrared temperature sensor provided at an outlet pipe of the exhaust gas heat exchanger; S15. Monitor the fuel flow in real time through a flow metering device provided in the fuel supply pipeline.

3. The electric heating coordination method according to claim 1 or 2, characterized in that: Step S2 specifically includes: S21. Determine a basic efficiency reference value according to a ratio of the electric load demand value to the rated capacity of the SOFC cogeneration system; S22. Based on the ratio of the heat load demand value to the maximum heating capacity of the waste heat recovery system, a temperature compensation coefficient is added to the basic efficiency reference value to generate a compensated efficiency value; S23. Determine the target power generation efficiency range according to the compensated efficiency value, and determine the target heating temperature range in combination with the return water temperature of the heating network and a preset heating temperature difference.

4. The electric heating coordination method according to claim 3, characterized in that: The generation of the fuel supply adjustment instruction in step S3 includes: S31. Calculating the theoretical maximum value of the fuel flow rate using the upper limit of the target power generation efficiency range as a constraint condition; S32, using the rate of change of the stack temperature as a feedback variable, dynamically adjusting the theoretical maximum value of the fuel flow rate using a proportional-integral control algorithm to generate a corrected upper limit value of the fuel flow rate; S33: Output the corrected fuel flow upper limit as the fuel supply adjustment instruction.

5. The electric heating coordination method according to claim 4, characterized in that: The generation of the air flow adjustment instruction in step S3 includes: S34, calculating a theoretical stoichiometric ratio value according to the fuel flow value in the fuel supply adjustment instruction; S35. Based on the deviation between the exhaust gas temperature and the target heating temperature range, the theoretical value of the stoichiometric ratio is corrected to generate an optimized stoichiometric ratio; S36: Convert the optimized stoichiometric ratio into a fan speed control signal, and generate the air flow adjustment instruction based on the fan speed control signal.

6. The electric heating coordination method according to claim 1, characterized in that: Step S4 specifically includes: S41, executing the fuel supply adjustment instruction, and controlling the fuel flow rate through a closed loop so that the actual power generation power of the SOFC cogeneration system dynamically tracks the electric load demand value; S42, executing the air flow adjustment instruction to control the exhaust gas thermal power by adjusting the air supply so that the output temperature of the waste heat recovery system dynamically matches the heat load demand value; S43. Calculate and output the real-time thermal-to-electricity ratio based on the actual generated power and the exhaust gas thermal power.

7. The electric heating coordination method according to claim 1, characterized in that: Step S5 specifically includes: S51, obtaining the temperature of the fuel cell stack in real time through distributed temperature sensors; S52, when the temperature of the battery stack exceeds the preset safety threshold, entering an over-temperature protection state; S53, performing the following fuel flow rate staged regulation in the over-temperature protection state: in the first stage, controlling the fuel regulating valve to reduce the fuel flow rate at a constant rate; in the second stage, monitoring the rate of decrease of the stack temperature in real time, and when the rate of decrease enters a preset stable range, switching to a proportional-integral control mode based on the stack temperature deviation; S54, calculating a real-time air compensation amount based on the current fuel flow rate and the preset stoichiometric ratio; S55, adjusting the air flow rate to the real-time air compensation amount through an independently controlled air supply device; S56 , continuously monitoring the temperature of the fuel cell stack, and exiting the over-temperature protection state when the temperature of the fuel cell stack remains stable within the safe operating range for a preset duration.

8. The electric heating coordination method according to claim 1, characterized in that: Step S6 specifically includes: S61, calculating the deviation between the real-time thermal-to-electricity ratio and the median of the preset optimal efficiency range; S62: When the deviation exceeds a first threshold, adjusting the lower limit of the target power generation efficiency range by a preset step size, wherein the first threshold is less than half the width of the preset optimal efficiency range; S63: When the deviation exceeds a second threshold, adjusting the upper limit of the target power generation efficiency range according to a preset step size, wherein the second threshold is greater than the first threshold and less than the width of the preset optimal efficiency range; S64: when the number of consecutive adjustments reaches a preset limit and the real-time heat-to-electricity ratio still cannot enter the preset optimal efficiency range, resetting the heat-to-electricity coordinated control target value to an initial calibration value; S65 . Generate a new thermal-electricity coordinated control target value based on the adjusted target power generation efficiency range, and maintain the preset optimal efficiency range as a subset of the adjusted target power generation efficiency range.

9. The electric heating coordination method according to claim 1, characterized in that: The preset safety threshold is obtained by calculating the thermodynamic transfer function based on the upper limit of the target heating temperature range; the safe operating range is [preset safety threshold - ΔT, preset safety threshold + ΔT], where ΔT is the maximum temperature fluctuation value allowed by the SOFC cogeneration system.

10. An electric heat coordination system for a solid oxide fuel cell combined heat and power system, characterized in that: include: a parameter acquisition module for acquiring in real time an operating parameter set of the solid oxide fuel cell cogeneration system, the operating parameter set including an electric load demand value, a thermal load demand value, a stack temperature, an exhaust gas temperature, and a fuel flow rate; a target determination module, configured to determine a heat and power coordinated control target value based on the operating parameter set, wherein the heat and power coordinated control target value includes a target power generation efficiency range and a target heating temperature range; An instruction generation module, configured to generate a fuel supply adjustment instruction and an air flow adjustment instruction according to the heat and power coordinated control target value; an instruction execution module, configured to execute the fuel supply adjustment instruction and the air flow adjustment instruction, so as to dynamically match the output power of the cogeneration system with the electric load demand value, and simultaneously dynamically match the output temperature of a waste heat recovery system integrated in the cogeneration system with the heat load demand value, and generate a real-time heat-to-power ratio; an over-temperature protection module, configured to monitor the stack temperature in real time and trigger an over-temperature protection strategy when the stack temperature exceeds a preset safety threshold. The over-temperature protection strategy includes preferentially reducing the fuel flow rate until the stack temperature returns to a safe operating range, and simultaneously compensating the air flow rate according to a stoichiometric ratio based on the fuel flow rate; A dynamic optimization module is used to dynamically correct the boundary value of the target power generation efficiency range based on the real-time heat-to-electricity ratio, so that the real-time heat-to-electricity ratio of the cogeneration system is always within a preset optimal efficiency range, and the preset optimal efficiency range is a subset of the target power generation efficiency range.

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