Power supply control method for mobile safety intelligent electric cooking guarantee cabin energy storage system

Abstract

The invention discloses a power supply control method for an energy storage system of a mobile safety intelligent electric cooking guarantee cabin, and the method comprises the steps: building a voltage-frequency-power control model which comprises the charge state of the energy storage system, the dynamic constraint of a fuel cell and the load demand in a micro-grid environment; in the primary frequency modulation stage, dynamic droop control combined with the state of charge of the battery is adopted to quickly correct the frequency; in the secondary frequency modulation stage, the fuel cell is used for correcting the power, and the storage battery is kept in the safety margin; superposing the frequency deviation detected in real time to a voltage reference value of the energy storage system to realize cooperative adjustment of frequency and voltage; when power shortage is detected, key load voltage is guaranteed preferentially, power compensation is carried out by reducing non-key load voltage and calling energy storage allowance, and stability of the micro-grid is recovered quickly. According to the method, the overall working efficiency of the system is improved, the mismatching risk caused by purely depending on fixed parameters is avoided, and the running robustness and safety of the micro-grid are enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of microgrid power supply and regulation, and in particular to a power supply control method for a mobile safe intelligent electric cooking support cabin energy storage system. Background Art

[0002] With the increasing popularity of distributed generation technology and energy storage units in microgrids, how to achieve effective management of power supply quality and system stability has become one of the current research focuses. The loads in a microgrid environment are usually diverse and random, and the intermittent nature of renewable energy and the dynamic characteristics of new energy modules such as fuel cells will cause significant fluctuations in frequency and voltage; however, traditional methods often only consider single energy storage or simple droop control strategies, and lack more sophisticated processing of dynamic constraints such as the startup characteristics of fuel cells and the charge state of energy storage units. As a result, when load mutations or power shortages occur, it is impossible to effectively maintain the dual stability of system frequency and voltage in a short period of time.

[0003] Although existing related technologies have made certain explorations in the combination of primary frequency regulation and secondary frequency regulation, they have ignored the special protection needs of core loads in microgrid environments, as well as the deep integration of complementary operations of energy storage systems and fuel cells. For example, in primary frequency regulation, if the battery SoC status monitoring is insufficient, excessive discharge or waste of energy storage space due to excessive SoC may occur easily. In secondary frequency regulation, if the fuel cell response delay and power upper limit are not fully considered, frequency regulation lag or insufficient regulation margin may occur easily. At the same time, many technical solutions only focus on frequency or only focus on voltage, lack a comprehensive study of the coupling effect between the two, and are difficult to cope with the dual disturbances caused by drastic changes in load power. When the power shortage is large, if the load is not graded or moderate sacrifices are not made on the voltage side, the working safety of the critical load and the overall stability of the system will be greatly reduced.

[0004] The existing mobile safe intelligent electric cooking support cabin energy storage system technology generally has the problems of insufficient coordinated regulation, load guarantee defects and difficulty in balancing the response delay of fuel cells. In view of the above shortcomings, the present invention proposes a power supply control method that integrates the charge state of the energy storage system, the dynamic constraints of the fuel cell and the load demand in a microgrid environment. By improving the voltage-frequency-power (VFC) control model and linking multi-stage frequency modulation and voltage regulation, the system's safety and peak load response capabilities in emergency situations can be effectively improved. Summary of the invention

[0005] The purpose of this section is to summarize some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the abstract of the specification and the title of the invention of this application to avoid blurring the purpose of this section, the abstract of the specification and the title of the invention, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0006] In view of the above existing problems, the present invention is proposed.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions: in a microgrid environment, an improved voltage-frequency-power control model including the state of charge of the energy storage system, the dynamic constraints of the fuel cell and the load demand is established;

[0008] In the primary frequency modulation stage, dynamic droop control combined with the battery state of charge is used to quickly correct the frequency;

[0009] In the secondary frequency regulation stage, the fuel cell correction power is used to further stabilize the frequency and maintain the battery at a safety margin;

[0010] The frequency deviation detected in real time is superimposed on the voltage reference value of the energy storage system to achieve coordinated regulation of frequency and voltage;

[0011] When a power shortage is detected, priority is given to ensuring the voltage of critical loads, and power compensation is performed by reducing the voltage of non-critical loads and calling on the energy storage margin to quickly restore the stability of the microgrid.

[0012] As a preferred solution of the power supply control method for the mobile safe intelligent electric cooking support cabin energy storage system described in the present invention, the improved voltage-frequency-power control model including the charge state of the energy storage system, the dynamic constraints of the fuel cell and the load demand is established, and various calculation relationship formulas about load power, energy storage SoC, fuel cell constraints, power deviation and frequency deviation are combined and written into the energy management system of the microgrid centralized controller or the cooking support cabin, and various safety thresholds or correction coefficients are integrated into the control model so as to be automatically called when frequency or voltage regulation is performed subsequently.

[0013] As a preferred scheme of the power supply control method for the mobile safe intelligent electric cooking support cabin energy storage system described in the present invention, the model outputs the key information of the frequency deviation estimate at the current moment, the load sensitivity parameter to the voltage frequency, the upper and lower limits of the battery available power, and the upper and lower limits of the fuel cell available power, so as to facilitate real-time calling and decision-making in subsequent steps.

[0014] As a preferred solution of the power supply control method for the mobile safe intelligent electric cooking support cabin energy storage system of the present invention, a rapid correction is performed in the primary frequency modulation stage, including:

[0015] The controller calculates Δf(t) at the current moment by monitoring the electrical parameters of the microgrid;

[0016] If Δf(t) is close to 0, it means the frequency is relatively stable;

[0017] If Δf(t) is positive and exceeds the threshold, it means that the system frequency is higher than the reference value, and it is necessary to reduce the system power output or increase the load absorption;

[0018] According to the real-time state of charge SoC(t) of the battery, dynamic adjustment is performed to obtain the time-varying dynamic droop coefficient K ′ d (t), and then obtain the battery charge / discharge reference power P bat ;

[0019] immediately sending the power reference value to a bidirectional converter of a battery energy storage system;

[0020] The bidirectional converter performs corresponding charging / discharging operations according to the power reference value and internal current and voltage detection.

[0021] As a preferred solution of the power supply control method for the mobile safe intelligent electric cooking support cabin energy storage system described in the present invention, it includes:

[0022] When Δf(t)<0, the system frequency is too low and Δf(t) is negative, then P bat (t) is a negative number multiplied by K ′ d , the result is positive, indicating that the battery needs to discharge to the system;

[0023] When Δf(t)>0, the system frequency is too high, Δf(t) is a positive value, then P bat (t) is a negative value, which means that the battery is allowed to reduce discharge or switch to charging to prevent the frequency from continuing to increase.

[0024] As a preferred solution of the power supply control method for the mobile safe intelligent electric cooking support cabin energy storage system of the present invention, the power is corrected by using a fuel cell in the secondary frequency modulation stage, including:

[0025] The controller calculates the corrected power ΔP that the fuel cell needs to compensate based on the current microgrid operation status. FC (t);

[0026] The correction power is added to the original set power of the fuel cell. Maximum output power Compare:

[0027]

[0028] Will The command is sent to the fuel cell controller to actually change the output power of the fuel cell;

[0029] By increasing or decreasing the fuel cell output power, the system frequency Δf(t) is brought closer to 0.

[0030] As a preferred solution of the power supply control method for the mobile safe intelligent electric cooking support cabin energy storage system of the present invention, it also includes:

[0031] The system continuously monitors the real-time state of charge SoC(t) of the battery and compares it with the minimum value of the real-time state of charge SoC of the battery min 、Battery real-time state of charge maximum value SoC max Comparison:

[0032] SoC min ≤SoC(t)≤SoC max

[0033] When SoC(t) remains in the safe range and Δf(t) returns to the smaller deviation zone, it means that the secondary frequency regulation target has been achieved;

[0034] If SoC(t) is too low or too high again in the subsequent process, calculate ΔP again FC (t) be amended.

[0035] Beneficial effects of the present invention:

[0036] 1. Through the establishment of this model, the microgrid controller can accurately analyze the actual needs of the system according to different operating states, further provide a basis for multi-stage frequency regulation and power distribution, and ensure that the management of various energy storage resources and fuel cells is more targeted and real-time. It not only improves the overall work efficiency of the system, but also avoids the mismatch risk caused by relying solely on fixed parameters at the source, and enhances the robustness and safety of microgrid operation;

[0037] 2. Combining the frequency deviation control strategy with the actual remaining capacity (SoC) state of the battery, the droop coefficient can be adaptively adjusted according to different intervals of the SoC. When the frequency deviation is caused by a sudden load change or fluctuation in renewable energy, the battery can quickly and reasonably output power (or absorb excess power) for initial stabilization, which can not only alleviate the problem of frequency overshoot or undershoot in a short time, but also avoid excessive discharge or deep charging of the battery due to fixed droop, and maintain the initial frequency balance of the microgrid more efficiently and safely.

[0038] 3. After the initial compensation of the battery, the fuel cell takes over part or all of the frequency regulation work, further suppressing the residual frequency fluctuations, avoiding the life loss of the battery due to long-term high-power regulation, and taking into account the response delay and power limit of the fuel cell. This not only enables the microgrid to achieve a deeper level of frequency stability, but also maintains the battery at a reasonable SoC level, prolonging the life of the energy storage components and stabilizing the overall operation quality;

[0039] 4. By slightly adjusting the voltage, the energy fluctuations in the microgrid can be further dispersed or absorbed, so that the frequency and voltage parameters can be coordinated and controlled, and the voltage and frequency of the microgrid can be stabilized under complex load scenarios;

[0040] 5. In the event of sudden power shortage, the core power demand is guaranteed to operate stably. At the same time, the total load is reduced by reducing the voltage of non-critical loads, and the rapid supply of energy storage units is used to quickly fill the power gap and improve the system's power supply reliability and emergency response capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0042] Figure 1 It is a flow chart of a power supply control method for a mobile safe intelligent electric cooking support cabin energy storage system shown in the present invention. DETAILED DESCRIPTION

[0043] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, but not all of the embodiments.

[0044] Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without making any creative work should fall within the scope of protection of the present invention.

[0045] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0046] According to an embodiment of the present invention, Figure 1The flowchart shown is a power supply control method for a mobile safe intelligent electric cooking support cabin energy storage system, which specifically includes the following steps:

[0047] S1. In a microgrid environment, an improved voltage-frequency-power (VFC) control model is established that includes the state of charge of the energy storage system, the dynamic constraints of the fuel cell, and the load requirements. Among them, the following points need to be explained in this step:

[0048] The system obtains the microgrid bus voltage, microgrid real-time frequency, current load power, and the operating status and ambient temperature of the energy storage system and fuel cell through the monitoring and communication module within a millisecond to second cycle;

[0049] In the embodiment of the present invention, the VFC control model is intended to characterize the dynamic correspondence between load, voltage, and frequency, and on this basis, consider the state of charge of the energy storage system and the dynamic constraints of the fuel cell, so as to more accurately perform primary frequency modulation, secondary frequency modulation, and voltage adjustment operations in subsequent steps S2 to S5;

[0050] As an example, based on the real-time data provided by the battery management system (BMS), the energy storage system state of charge SoC(t) is calculated and recorded to obtain SoC min With SoC max , to determine the safe available range, determine whether the battery is currently at the saturated charge value or the minimum discharge value. If it is close to the boundary, it is necessary to add a correction factor (such as quadratic penalty or power reduction factor) to the model to prevent overcharging or over-discharging;

[0051] As an example, read the maximum sustainable output power of the fuel cell at the current ambient temperature provided by the fuel cell controller or detection unit If the fuel cell is in the startup preparation stage, record its Δt FC time (for example, it will take 3 seconds or 5 seconds to reach full power output) so that its response delay can be considered in the power balance equation; if the fuel cell temperature, exhaust treatment or other information shows that the fuel cell needs to be derated, appropriate corrections can be made value;

[0052] As an example, the load demand P load (t) is the sum of the power requirements of all electrical equipment in the cooking support cabin at time t. The influence coefficient of voltage and frequency on load power is: When the voltage decreases or the frequency shifts, the power of some loads will change dynamically (especially inductive or resistive loads);

[0053] As an example, other operating parameters of the microgrid environment include microgrid bus voltage, microgrid frequency, and reference frequency (e.g., 50 Hz or 60 Hz, depending on regional standards);

[0054] In an optional embodiment, according to different load types (resistive, inductive, variable frequency equipment) and real-time detection values ​​U(t), f(t), the function P is executed in the control system. load (t) = f(U(t), f(t));

[0055] If the load is complex, f(·) can be piecewise linearized in the controller, such as:

[0056]

[0057] Among them, k 1 , k 2 is a constant estimated or experimentally calibrated based on load characteristics. This function f(·) is used to describe the change in load power demand caused by the change in voltage U(t) and frequency f(t) at time t;

[0058] After determining the available energy storage power P bat (t) and available fuel cell power P FC (t), calculate whether the total power supply of the system meets P load (t) demand;

[0059] Calculate the system power difference:

[0060] ΔP(t)=P bat (t)+P FC (t)-P load (t)

[0061] Input ΔP(t) into the function g(·) (a nonlinear or piecewise linear function that reflects the corresponding relationship between frequency offset and power imbalance based on the principle of small signal linearization and droop control) to obtain the estimated value of system frequency deviation:

[0062] Δf(t)=g(ΔP(t))

[0063] If Δf(t) is a negative value, it means that the microgrid operating frequency is lower than the reference frequency. If it is a positive value, it means that the frequency is higher, the load demand is smaller, or the supply is relatively abundant;

[0064] ΔP(t) represents the imbalance between the total power supply and demand of the microgrid at time t, which includes the difference between the output power of the energy storage system, the output power of the fuel cell and the load demand;

[0065] It should also be noted that the following constraints need to be incorporated when establishing the above two core functions:

[0066] When SoC(t) approaches the lower limit, the discharge requirement for the battery should be reduced to avoid over-discharge. When SoC(t) approaches the upper limit, the charging power should be limited.

[0067] When a short-term power shock occurs, since the fuel cell usually takes a certain amount of time to rise from the standby or low-power state to the maximum power output state, the impact of this time delay on ΔP(t) needs to be considered in the model;

[0068] If the fuel cell temperature exceeds a certain value, the maximum output power must be reduced. Carry out derating;

[0069] Furthermore, the above-mentioned various calculation relationships between load power, energy storage SoC, fuel cell constraints, power deviation and frequency deviation are combined and written into the energy management system of the microgrid centralized controller or the cooking support cabin, and various safety thresholds or correction coefficients are integrated into the model to ensure automatic call when frequency modulation or voltage regulation is performed subsequently. After step S1 is completed, the model outputs (or updates) the estimated value of the frequency deviation Δf(t) at the current moment, the sensitivity parameters of the load to the voltage frequency, the upper and lower limits of the available power of the battery, and the upper and lower limits of the available power of the fuel cell, which are key information for real-time call and decision-making in subsequent steps S2 to S5.

[0070] Preferably, this step obtains various operating parameters in a microgrid environment and incorporates data such as the state of charge of the energy storage system, the dynamic constraints of the fuel cell and the load demand into an improved voltage-frequency-power (VFC) control model, thereby providing an accurate, complete and adaptive operating basis for subsequent primary frequency modulation, secondary frequency modulation, coordinated frequency and voltage regulation and power shortage compensation, so that the method of the present invention has higher controllability and reliability in the mobile safe intelligent electric cooking support cabin energy storage system.

[0071] S2. In the primary frequency modulation stage, the frequency is quickly corrected by using dynamic droop control combined with the battery charge state. The following points need to be explained in this step:

[0072] In an optional implementation, the system is confirmed to enter a frequency modulation stage (i.e., a "fast frequency correction" stage) through the following real-time monitoring and logical judgment:

[0073] If |Δf(t)|>Δf occurs according to the model calculation or monitoring results of step S1 threshold , indicating that the real-time frequency deviation of the current microgrid exceeds the acceptable range (Δf threshold is a threshold value of 1% to 2% less than the rated frequency), then a frequency modulation stage is immediately triggered;

[0074] If the system detects P load (t) If there is a sharp rise or fall in a short period of time, it will also be determined that the frequency fluctuation risk of the microgrid has increased, and thus the primary frequency regulation process will be entered for rapid compensation;

[0075] At the same time, confirm that SoC(t) is greater than SoC min And it is within the safe discharge range, which means that the battery can provide sufficient power support for frequency correction in a short time. If SoC(t) is too low, it is necessary to further determine whether the fuel cell can be called or the subsequent frequency regulation stage can be entered;

[0076] If SoC(t) is too high, the battery can increase the charging power when the frequency overshoots to avoid excessive increase in system frequency;

[0077] As long as any of the above trigger conditions is met (such as |Δf(t)| exceeds the threshold and SoC(t) is within the available range), the system enters the primary frequency modulation stage;

[0078] Furthermore, the frequency is quickly corrected by using dynamic droop control combined with the battery state of charge, which specifically includes the following steps:

[0079] The controller calculates Δf(t) at the current moment by monitoring the electrical parameters of the microgrid (voltage, current, frequency);

[0080] If Δf(t) is close to 0, it means the frequency is relatively stable;

[0081] If Δf(t) is positive and exceeds the threshold, it means that the system frequency is higher than the reference value, and it is necessary to reduce the system power output or increase the load absorption;

[0082] Dynamic adjustment is performed according to the real-time state of charge SoC(t) of the battery, and the droop coefficient is recorded as:

[0083] K ′ d (t) = K d × SoC (t)

[0084] Among them, w SoC (t) is a weight coefficient defined based on the remaining capacity of the battery, for example:

[0085]

[0086] When SoC(t) is high, w SoC (t) Reduce to avoid excessive discharge of the battery or repeated high current charging and discharging;

[0087] When SoC(t) approaches the lower limit, w SoC (t) increases. To avoid severe undervoltage, it is necessary to more actively deliver power to the system to support the frequency.

[0088] After the above correction, the time-varying dynamic droop coefficient K is obtained. ′ d(t), enabling the system to adaptively adjust the discharge / charge power within different SoC intervals;

[0089] In the primary frequency modulation stage, the battery discharge (or charging) reference power P bat It can be given by the following formula:

[0090] P bat (t) = K ′ d (t)×Δf(t)

[0091] When Δf(t)<0 (system frequency is too low), Δf(t) is negative, then P bat (t) is a negative number multiplied by K ′ d , the result is positive, indicating that the battery needs to discharge to the system;

[0092] When Δf(t)>0 (system frequency is too high), Δf(t) is positive, then P bat (t) becomes negative, indicating that the battery is allowed to reduce discharge or switch to charging (absorbing excess energy) to prevent the frequency from continuing to increase;

[0093] When the controller gets P bat (t), immediately sending the power reference value to the bidirectional converter of the battery energy storage system;

[0094] The converter performs corresponding charging / discharging operations according to the reference value and internal current and voltage detection;

[0095] In the sampling period of milliseconds to seconds, the control system continuously monitors Δf(t) and synchronously updates K ′ d (t) and P bat (t) calculation;

[0096] When Δf(t) returns to |Δf(t)|≤Δf threshold If the safety range is reached, the main control tasks of the frequency modulation stage can be considered to be preliminarily completed.

[0097] It should be noted that through the dynamic droop control of the primary frequency modulation, the system can restore the frequency that is significantly deviated from the benchmark to a relatively stable level in a short period of time. At the same time, due to the combination of SoC real-time information, excessive use of the battery can be effectively avoided. After the primary frequency modulation is completed, if the frequency still has a slight deviation for a long period of time, or the SoC of the battery is significantly reduced, it will enter the secondary frequency modulation stage (step S3) and use resources such as fuel cells to perform more precise frequency compensation and battery charge regulation.

[0098] Preferably, through the implementation of this step, the battery can provide charge / discharge power in milliseconds to seconds, effectively resist sudden load changes or large frequency fluctuations, consider the SoC state, and avoid excessive charge / discharge.

[0099] S3: In the secondary frequency modulation stage, the fuel cell is used to correct the power to further stabilize the frequency and maintain the battery at a safety margin. The following points need to be explained in this step:

[0100] After the frequency is quickly corrected in step S2 (primary frequency modulation), the following two situations may occur to trigger the secondary frequency modulation:

[0101] If after the first frequency modulation is completed, Δf(t) is still greater than the set second frequency modulation trigger threshold (for example, |Δf(t)|>Δf hreshold_2 , and is greater than a certain proportion of the primary frequency modulation threshold), indicating that the system frequency cannot be brought back to the ideal range only through the rapid frequency modulation of the battery. At this time, the power correction of the fuel cell is needed to further stabilize the frequency;

[0102] When SoC(t) gradually approaches SoC min If the SoC(t) is too high and the frequency deviation still exists, it is necessary to "make room" for the battery to avoid overcharging or over-discharging. At this time, the battery can be kept within a safety margin and the frequency can be further supported by calling the fuel cell correction power in the secondary frequency modulation stage.

[0103] As long as any of the above trigger conditions is met (for example: Δf(t) is not in the ideal range or SoC(t) declines / increases significantly), the system will enter secondary frequency modulation;

[0104] Furthermore, the fuel cell power correction is used to further stabilize the frequency and maintain the battery at a safety margin, which specifically includes the following steps:

[0105] Based on the maximum output power of the fuel cell at the current ambient temperature and working state, the time constant required for the fuel cell to go from idle to full power or from low power to high power, and the data of temperature protection or derating operation constraints, the controller determines whether the fuel cell is in a startable or full power output state; if the fuel cell is still in a low temperature state or pause mode, it needs to wait for Δt FC time;

[0106] When it is confirmed that the secondary frequency modulation has been entered, the controller calculates the correction power ΔP that the fuel cell needs to compensate according to the current operation status of the microgrid. FC (t), expressed as:

[0107] ΔP FC (t) = h(Δf(t),SoC(t))

[0108] Among them, h(·) is used to comprehensively evaluate the frequency deviation of the microgrid and the remaining capacity of the battery:

[0109] If Δf(t) is negative and SoC(t) is below a certain safety level (close to SoC min ), then ΔP FC (t) A larger positive value indicates that the fuel cell power output needs to be increased as soon as possible to reduce the battery discharge pressure;

[0110] If Δf(t) is positive but the battery SoC(t) is close to the upper limit, the fuel cell needs to be kept at a lower output or even idle so that the battery has room to charge, preventing the frequency from increasing excessively or the battery from overcharging;

[0111] If Δf(t) is still large or highly volatile, in order to prevent the battery from continuing to discharge / charge violently during the primary frequency modulation, ΔP FC (t) also increases accordingly;

[0112] In order to obtain ΔP FC (t) needs to be added to the original set power of the fuel cell. Maximum output power Compare:

[0113]

[0114] If ΔP FC (t) is very large and cannot exceed The safe output limit of the fuel cell represented;

[0115] If temperature or other protection mechanisms require derating, update appropriately A smaller value ensures that the fuel cell operates within a safe range;

[0116] After this step is completed, The command is sent to the fuel cell controller to actually change the output power of the fuel cell;

[0117] By increasing or decreasing the output power of the fuel cell, the system frequency Δf(t) can be brought closer to 0. Compared with primary frequency regulation that relies solely on batteries, secondary frequency regulation can maintain the frequency within the target range in a more stable manner over a longer time scale.

[0118] As the fuel cell takes over part of the power burden, SoC(t) is alleviated and no longer over-discharged or over-charged;

[0119] The system continuously monitors the SoC(t) and communicates with the SoC min ,SoC max Comparison: SoC min≤SoC(t)≤SoC max ;

[0120] When SoC(t) remains in the safe range and Δf(t) returns to the smaller deviation zone, it means that the secondary frequency regulation target (both stabilizing the frequency and maintaining the battery safety margin) has been achieved;

[0121] If SoC(t) is too low or too high again in the subsequent process, calculate ΔP again FC (t) amend them;

[0122] In the secondary frequency modulation stage, the controller continuously updates Δf(t), SoC(t), and ΔP in a cycle of seconds or tens of seconds. FC (t) and Parameters are set to ensure the smoothness and safety of the entire regulation process. If the frequency and SoC are maintained within the ideal range, the secondary frequency regulation is gradually terminated to prevent the fuel cell from operating at high power for a long time or frequently adding or reducing power.

[0123] Preferably, secondary frequency modulation can stabilize the frequency of the microgrid at a higher power and longer time scale, which helps maintain the battery safety margin and avoid excessive discharge or rapid charging caused by primary frequency modulation. When combined with subsequent voltage regulation (step S4) or power shortage compensation (step S5), the overall operating efficiency and power safety of the system are further optimized.

[0124] S4, superimposing the frequency deviation detected in real time to the voltage reference value of the energy storage system to achieve coordinated regulation of frequency and voltage. Among them, what needs to be explained in this step is:

[0125] A proportional factor α is set to characterize the relationship between the frequency deviation and the voltage adjustment amount, and the adjustment of the voltage reference value required at the current time t is obtained through the formula ΔU(t)=α×Δf(t);

[0126] Add ΔU(t) to the original voltage reference value U ref (t), forming a new voltage reference:

[0127]

[0128] Among them, U ref (t) is the original voltage setting value (the conventional voltage reference value without considering the frequency deviation), and ΔU(t) is the additional correction amount made in this step according to Δf(t);

[0129] The above superposition operation is mainly implemented in the voltage control link of the energy storage system (such as a battery or a fuel cell converter), for example:

[0130] In the converter internal control algorithm, there is U ref(t) is the control target. At this time, we only need to add the frequency deviation channel and adjust U according to ΔU(t). ref (t) Make dynamic corrections;

[0131] If Δf(t)<0 (indicating that the system frequency is low), ΔU(t) may be negative, then Lower than the original setting value;

[0132] If Δf(t)>0, then May be moderately promoted;

[0133] The converter receives After that, the output voltage is adjusted in a very short closed-loop cycle (millisecond level);

[0134] When the voltage is lowered, the instantaneous power demand of the load will decrease (especially for resistive or inductive loads), thus indirectly assisting in supporting the frequency.

[0135] When the voltage is raised, if the system is in a state of surplus power, energy storage or other devices can absorb a certain amount of energy to avoid frequency overshoot;

[0136] Furthermore, continue to monitor the changing trends of Δf(t) and U(t);

[0137] If the microgrid frequency Δf(t) is observed to be close to 0 or fluctuates within a small range in a short period of time, and the voltage U(t) also remains near the rated value (or within an acceptable range), it means that the coordinated regulation has achieved the expected effect through the "frequency-voltage superposition" strategy;

[0138] If Δf(t) continues to deviate and the voltage cannot meet the load requirement, it may enter the subsequent steps (such as S5 power shortage compensation or load side management) for deeper control.

[0139] Preferably, coupling optimization of frequency regulation and voltage regulation is achieved, which greatly improves the system's responsiveness to load fluctuations or changes in the external environment. Under the condition of limited energy storage capacity and limited fuel cell power, through small adjustments on the voltage side, the frequency stability can be smoothly maintained without significantly reducing the load power supply quality, providing more flexible scheduling space for subsequent power shortage processing (step S5) or other power supply guarantee strategies in emergency situations.

[0140] S5: When power shortage is detected, the voltage of critical loads is prioritized, and power compensation is performed by reducing the voltage of non-critical loads and calling the energy storage margin to quickly restore the stability of the microgrid. Among them, the following points need to be explained in this step:

[0141] Calculate the sum of the total available power supply at the current moment (including fuel cell output power, battery discharge power and renewable energy power generation power), denoted as P avail (t);

[0142] If P load (t)>P avail (t), indicating that the load demand exceeds the available power supply capacity, resulting in a power shortage ΔP short (t) = P load (t)-P avail (t);

[0143] When ΔP short (t) When the set threshold is exceeded (e.g., 5% to 10% of the rated power), the trigger condition for power shortage processing is met;

[0144] If the frequency modulation action in S2 or S3 fails to cover the power shortage in time, or SoC(t) is close to SoC min The system cannot continue to discharge in large quantities, and needs to enter stricter load voltage management;

[0145] As long as any of the above trigger conditions is met (actually mostly parallel judgments), the system enters the power shortage processing mode;

[0146] In the cooking support cabin, some critical loads (such as electric cooking equipment, safety monitoring and command systems) have higher voltage requirements or more stringent operation continuity requirements. The system has classified critical loads and non-critical loads in the planning stage, and the controller saves a list of critical loads; the voltage reference value on the critical load side (such as ) is fixed at the rated level or slightly above the minimum safety limit to prevent critical loads from shutting down or failing to work properly when the voltage drops sharply, thereby ensuring the core functions of the cooking support cabin;

[0147] A coefficient β is set to convert the power shortage ΔP short (t) converted into a quantitative standard for voltage reduction;

[0148] The following relationship can be used:

[0149]

[0150] Among them, β can be selected according to the rated voltage range, load characteristics and safety regulations of the microgrid, ΔP short The larger (t) is, the greater the voltage reduction will be;

[0151] To avoid excessive voltage reduction on non-critical loads that affects service life or basic functions, set the minimum allowable voltage , to ensure that it is not so low that it cannot maintain the basic operation of the equipment;

[0153] If the calculated value Lower than , then limit it to ;

[0155] In some load categories (such as resistive and inductive loads), voltage drops usually reduce real-time power consumption. If the reduction is sufficient, ΔP short (t) can be relieved rapidly;

[0156] If the battery still has residual discharge capacity (SoC(t) greater than SoC min and can be further discharged), or the fuel cell still has output power that can be increased, the system can use it to compensate for ΔP short (t);

[0157] Calculate the dispatchable remaining power:

[0158] P remain =min(P bat_remain ,P FC_remain )

[0159] Among them, P bat_remain Indicates the upper limit of the power that the battery can continue to discharge within a safe range, P FC_remain ) represents the power that can be further increased within the temperature and start-up constraints of the fuel cell;

[0160] If ΔP short (t)≤P remain , then it can be fully compensated at one time to achieve microgrid balance;

[0161] Otherwise, there is still a surplus power shortage, and non-critical loads need to be further decompressed;

[0162] In a cycle of seconds or several seconds, the controller monitors the current power supply and ΔP short (t) changes;

[0163] The output status of SoC(t) and fuel cell is updated at the same time. If the compensation is completed and the voltage tends to be stable, the non-critical load voltage can be gradually restored to the original set value to ensure that the system as a whole returns to normal operation mode;

[0164] When the voltage of critical loads is guaranteed and the voltage of non-critical loads is lowered, the actual power demand of the system should decrease accordingly. Combined with the power compensation of energy storage or fuel cells, the supply and demand balance in the microgrid can be restored in a relatively short time.

[0165] At this time, the microgrid frequency Δf(t) and total voltage U(t) can be further monitored to see whether they return to the safe range;

[0166] If ΔP short (t) is continuously alleviated, the system will gradually adjust the non-critical load voltage back to To minimize the impact on user experience;

[0167] If the power shortage is still serious, the voltage reduction state is maintained until SoC(t) has sufficient margin or the fuel cell state allows the output to continue to increase.

[0168] It should also be noted that through the implementation of the method of the present invention, even if there is a large power shortage, the core equipment of the cooking support cabin can continue to be powered on, thereby improving system reliability. Only the voltage of non-critical loads is reduced, and there is no need to forcibly cut off the power supply, thereby reducing the impact on user use. After calling on the remaining power of the energy storage or fuel cell, the voltage and frequency can be restored to stability in a very short time, thereby achieving efficient and safe emergency control.

[0169] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A power supply control method for a mobile safe intelligent electric cooking support cabin energy storage system, characterized in that: include: In a microgrid environment, an improved voltage-frequency-power control model is established that includes the state of charge of the energy storage system, the dynamic constraints of the fuel cell, and the load demand. In the primary frequency modulation stage, dynamic droop control combined with the battery state of charge is used to quickly correct the frequency; In the secondary frequency regulation stage, the fuel cell correction power is used to further stabilize the frequency and maintain the battery at a safety margin; The frequency deviation detected in real time is superimposed on the voltage reference value of the energy storage system to achieve coordinated regulation of frequency and voltage; When a power shortage is detected, priority is given to ensuring the voltage of critical loads, and power compensation is performed by reducing the voltage of non-critical loads and calling on the energy storage margin to quickly restore the stability of the microgrid.

2. The power supply control method for the mobile safe intelligent electric cooking support cabin energy storage system according to claim 1 is characterized in that: The improved voltage-frequency-power control model including the state of charge of the energy storage system, the dynamic constraints of the fuel cell and the load demand is established, and various calculation relationships between load power, energy storage SoC, fuel cell constraints, power deviation and frequency deviation are combined and written into the energy management system of the microgrid centralized controller or the cooking support cabin, and various safety thresholds or correction coefficients are integrated into the control model so as to be automatically called when frequency or voltage regulation is performed subsequently.

3. The power supply control method for the mobile safe intelligent electric cooking support cabin energy storage system according to claim 2 is characterized in that: The model outputs the current frequency deviation estimate, load sensitivity parameters to voltage frequency, upper and lower limits of battery available power, and upper and lower limits of fuel cell available power, so as to facilitate real-time invocation and decision-making in subsequent steps.

4. The power supply control method for the mobile safe intelligent electric cooking support cabin energy storage system according to claim 1 is characterized in that: Rapid correction in one FM stage, including: The controller calculates Δf(t) at the current moment by monitoring the electrical parameters of the microgrid; If Δf(t) is close to 0, it means the frequency is relatively stable; If Δf(t) is positive and exceeds the threshold, it means that the system frequency is higher than the reference value, and it is necessary to reduce the system power output or increase the load absorption; According to the real-time state of charge SoC(t) of the battery, dynamic adjustment is performed to obtain the time-varying dynamic droop coefficient K ′ d (t), and then obtain the battery charge / discharge reference power P bat ; immediately sending the power reference value to a bidirectional converter of a battery energy storage system; The bidirectional converter performs corresponding charging / discharging operations according to the power reference value and internal current and voltage detection.

5. The power supply control method for the mobile safe intelligent electric cooking support cabin energy storage system according to claim 4 is characterized in that: include: When Δf(t)<0, the system frequency is too low and Δf(t) is negative, then P bat (t) is a negative number multiplied by K ′ d , the result is positive, indicating that the battery needs to discharge to the system; When Δf(t)>0, the system frequency is too high, Δf(t) is a positive value, then P bat (t) is a negative value, which means that the battery is allowed to reduce discharge or switch to charging to prevent the frequency from continuing to increase.

6. The power supply control method for the mobile safe intelligent electric cooking support cabin energy storage system according to claim 1 is characterized in that: Fuel cells are used to correct power in the secondary frequency regulation stage, including: The controller calculates the corrected power ΔP that the fuel cell needs to compensate based on the current microgrid operation status. FC (t); The correction power is added to the original set power of the fuel cell. Maximum output power Compare: Will The command is sent to the fuel cell controller to actually change the output power of the fuel cell; By increasing or decreasing the fuel cell output power, the system frequency Δf(t) is brought closer to 0.

7. The power supply control method for the mobile safe intelligent electric cooking support cabin energy storage system according to claim 6 is characterized in that: Also includes: The system continuously monitors the real-time state of charge SoC(t) of the battery and compares it with the minimum value of the real-time state of charge SoC of the battery min 、Battery real-time state of charge maximum value SoC max Comparison: SoC min ≤SoC(t)≤SoC max When SoC(t) remains in the safe range and Δf(t) returns to the smaller deviation zone, it means that the secondary frequency regulation target has been achieved; If SoC(t) is too low or too high again in the subsequent process, calculate ΔP again FC (t) be amended.

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