Hydrogen storage, heat storage and electricity storage collaborative power fluctuation smoothing method for microgrid of electric heat hydrogen combination

Abstract

This invention discloses a method for mitigating power fluctuations in a combined electrothermal-hydrogen microgrid that integrates hydrogen storage, thermal storage, and energy storage. The method employs dynamically adjusted parameters. λ L and λ M The dual-stage low-pass filter decomposes the net fluctuating power into low, medium, and high-frequency components, which are then allocated to the hydrogen storage system (HSS), heat pump (HP), and battery energy storage system (BESS), respectively. The HSS and HP outputs undergo soft-cutoff correction based on their own and the heat storage tank's status. The BESS handles high-frequency and upstream transfer fluctuations and incorporates an adaptive dead zone and bidirectional protection mechanism: when the BESS status exceeds limits or deviates from the optimal range, feedback reduces... λ L This method forcibly transfers some fluctuations to the upstream HSS (High-Speed ​​System) or utilizes dead-zone filtering micro-actions to protect lifespan. Through full-band soft cutoff decoupling and bidirectional upstream and downstream feedback, it effectively unleashes the joint regulation potential of heterogeneous multi-energy devices.

Description

Technical Field

[0001] This invention belongs to the field of microgrid energy management and control technology, and specifically relates to a method for smoothing power fluctuations in a combined electrothermal-hydrogen microgrid that integrates hydrogen storage, thermal storage, and electricity storage. Background Technology

[0002] With the global energy structure transitioning towards cleaner and lower-carbon energy and the high proportion of distributed renewable energy being integrated, the penetration rate of renewable energy sources, such as wind and solar power, in microgrids is increasing. However, the output of such energy sources is characterized by significant randomness, intermittency, and volatility. The large and rapid changes in their power pose serious challenges to the power quality (such as voltage and frequency fluctuations), power balance, and friendly interaction with the main grid in microgrids.

[0003] In the operation and control of microgrids, effectively mitigating power fluctuations introduced by renewable energy generation is one of the core tasks to ensure the stable, reliable, and economical operation of the system. Traditional mitigation methods often employ hybrid energy storage systems composed of battery energy storage systems (BESS) or supercapacitors (SC). However, supercapacitors are expensive, and relying solely on batteries to cope with power fluctuations across the entire frequency band, especially high-frequency and large-amplitude fluctuations, would severely shorten their lifespan. In recent years, combined power-heat microgrids have introduced heat pumps (HP) and thermal storage tanks (HST) to participate in the mitigation of low-frequency or medium-frequency fluctuations. Building on this, combined power-heat-hydrogen microgrids, due to the further integration of the high energy density and long-term energy storage characteristics of hydrogen storage systems (HSS), utilize the conversion and complementarity between electrical energy, thermal energy, and hydrogen energy, and are considered an ideal form of future energy interconnection.

[0004] Existing technologies disclose a strategy for mitigating power fluctuations through the coordinated operation of a hydrogen storage system (HSS), a heat pump (HP), and a battery energy storage system (BESS). This strategy is based on frequency division control, using a unidirectional fixed filtering time constant to decompose the fluctuating power to be mitigated: the HSS responds to the low-frequency component, the heat pump responds to the mid-frequency component, and the battery handles the remaining high-frequency component. However, existing technologies, after introducing these three heterogeneous energy storage media, lack a refined three-level coordinated allocation strategy for power fluctuations across the entire frequency band (low-mid-high frequency), and the devices often operate independently.

[0005] The technical problem to be solved is: how to achieve smooth and efficient suppression of power fluctuations across the low-to-medium-to-high frequency bands in an electrothermal-hydrogen combined microgrid without increasing the cost of energy storage configuration, while also achieving dynamic mutual assistance across different levels when various heterogeneous energy storage media face extreme conditions, and fully protecting the battery life.

[0006] Although the HSS+HP+BESS synergistic strategy proposed in existing technologies has theoretically verified the feasibility of electrothermal-hydrogen synergistic fluctuation mitigation, it still faces the following challenges in practical engineering applications:

[0007] 1. Poor cross-level coordination and rigid regulation: In existing technologies, energy storage devices in different frequency bands often respond independently to the allocated fluctuation components, and the filtering and decomposition process is unidirectional. When batteries or thermal storage tanks at the mid-to-high frequency response level are constrained due to their state of charge (SOC) approaching the safety boundary, the system lacks a dynamic feedback mechanism for downstream devices to "request support" from the upstream large-capacity hydrogen storage system. This essentially severs the potential for state mutual assistance among multiple heterogeneous energy storage systems, resulting in the upstream regulation margin being unable to support the downstream extreme operating conditions, thus affecting the overall smoothing effect of the system.

[0008] 2. Poor cross-level coordination and rigid regulation: In existing technologies, energy storage devices in different frequency bands often respond independently to the allocated fluctuation components, and the filtering and decomposition process is unidirectional. When batteries or thermal storage tanks at the mid-to-high frequency response level are constrained due to their state of charge (SOC) approaching the safety boundary, the system lacks a dynamic feedback mechanism for downstream devices to "request support" from the upstream large-capacity hydrogen storage system. This essentially severs the potential for state mutual assistance among multiple heterogeneous energy storage systems, resulting in the upstream regulation margin being unable to support the downstream extreme operating conditions, thus affecting the overall smoothing effect of the system. Summary of the Invention

[0009] Purpose of the Invention: The main purpose of this invention is to overcome the problems of poor coordination among multiple devices in existing electrothermal hydrogen microgrids, control jumps, and rapid battery life degradation. This invention provides a method for efficient three-level frequency division and smoothing of LMH (low-medium-high) using a hydrogen storage system (HSS), heat pump and thermal storage tank (HP / HST), and battery energy storage system (BESS) without the need for supercapacitors. Through an innovative bidirectional feedback dynamic filtering mechanism and adaptive dead-zone control, it achieves efficient smoothing of power fluctuations across the entire frequency band while realizing state mutual support and lifespan protection for various heterogeneous energy storage media.

[0010] Technical solution:

[0011] To achieve the above objectives, this invention provides a method for mitigating power fluctuations in a combined thermal and electrical microgrid with thermal energy storage, comprising the following steps:

[0012] (1) Status Acquisition: Real-time acquisition of renewable energy fluctuation power (P) Flu ), State of charge (SOC) of hydrogen storage system HSS ), battery state of charge (SOC) BESS ), thermal state of the storage tank (SOC) HST ), outdoor temperature (T) out ), User indoor and outdoor temperatures (T) Room The key parameters of ).

[0013] (2) Reference Extraction and Two-Stage Dynamic Filtering: The reference power required by the hydrogen storage system is extracted, and the remaining net fluctuation is sent to a cascaded two-stage low-pass filter. The first-stage filter separates the fluctuation into a low-frequency component (P). L The second-stage filter separates the mid-to-high frequency components into intermediate frequency components (P) and mid-to-high frequency components; M ) and high-frequency components (P H First-stage filter time constant (λ) L According to SOC BESS and SOC HST The feedback state is dynamically adjusted to enable a mechanism for downstream applications to seek help from upstream (HSS) when downstream conditions are limited. The second-stage filter time constant (λ) M Smooth adjustments are made based on room temperature error and battery status.

[0014] Filtering time constant λ L The two-way dynamic feedback adjustment mechanism is as follows: the state of charge (SOC) of the hydrogen storage system itself is adjusted accordingly. HSS Determine the base time constant when SOC HSS The minimum value is taken when the system is in the middle safe zone, and the maximum value is taken when the system is in the extreme zones at both ends; a downstream help feedback factor is set: when the downstream SOC is detected... BESS or SOC HST When entering a preset danger zone, output a help factor less than 1; the overall time constant λ L The product of the basic time constant and the help factor is used to force a reduction in the first-stage filter time constant when the downstream equipment is under extreme pressure, thereby transferring the low- and medium-frequency fluctuations to the hydrogen storage system.

[0015] (3) Three-level initial distribution: the low-frequency component (P) L ), intermediate frequency component (P) M ), high-frequency components (P) H (4) Hydrogen storage coordinated control (low frequency): The HSS responds to the hydrogen production baseline command and low frequency fluctuations, and applies a SOC-based control. HSS The soft cutoff limit causes unprocessed low-frequency fluctuations to be transferred downstream to HP.

[0016] Hydrogen storage system HSS coordinated control: The total power command of the hydrogen storage system is determined by meeting hydrogen production requirements and adjusting according to the state of charge (SOC). BESS The linked reference power, and the allocated low-frequency component P L Composition; combined with soft-cutoff logic, when SOC HSS When the charging and discharging power is close to the upper and lower limits, the charging and discharging power is dynamically drated; and the low-frequency fluctuations that the hydrogen storage system cannot handle due to limitations are transferred to the amount P. L_transfer Distribute to heat pump system

[0017] (5) Heat pump coordinated control (medium frequency): HP responds to basic commands for maintaining thermal storage, medium frequency fluctuations, and low frequency fluctuations during HSS transfer. This is based on winter / summer modes and SOC. HST A soft cutoff limit is applied, and any unprocessed residual fluctuations are transferred to BESS.

[0018] Heat pump HP and heat storage tank HST coordinated control: The heat pump's command for smoothing fluctuations includes the allocated intermediate frequency component P. M Low-frequency fluctuations P related to hydrogen storage system transfer L_transfer The sum; the total heat pump command consists of the base power to maintain the target temperature of the heat storage tank and the corrected power to smooth out fluctuations; depending on whether the system is currently in heating or cooling mode, and based on the SOC. HST The soft cutoff logic limits and corrects the power fluctuations; and transfers the low-to-medium frequency fluctuations P that the heat pump limitation could not handle. M_transfer Distribute to the storage batteries.

[0019] (6) Battery Coordination Control (High Frequency): BESS handles high-frequency fluctuations and all remaining fluctuations transferred from upstream. Adaptive dead-zone control is introduced, with no dead-zone response only in the SOC golden range. Outside the range, dead-zone filtering is activated to extend lifespan, and finally, a soft cutoff limit is applied.

[0020] Battery BESS Coordination Control: The battery assumes the responsibility for distributing the high-frequency component P. H With the low-to-medium frequency fluctuations P of heat pump transfer M_transfer The sum; adopting an adaptive dead-time control mechanism based on SOC: when SOC BESS When within the preset golden safety range, the dead zone is set to zero to respond to all minor fluctuations; when SOC BESS When deviating from the golden range, a preset dead zone threshold is activated to filter out minor fluctuations and reduce cycle loss; finally, this is combined with SOC. BESS The soft-cutoff logic outputs the final battery execution command, which is then sent to various devices for execution.

[0021] (7) Instruction issuance: The final instructions for the three devices are issued and executed, and the thermodynamic and SOC models of each system are updated.

[0022] Beneficial effects:

[0023] Compared with existing technologies, this invention achieves the following significant technological advancements and beneficial effects through a unique system configuration (HSS+HP+HST+BESS) and an innovative collaborative control strategy (dynamic filtering coordination based on bidirectional feedback, battery adaptive dead zone, and full-equipment soft-cutoff anti-jump).

[0024] 1. Multi-timescale three-level coordinated frequency division: The fluctuation is creatively divided into three frequency bands: low, medium and high, which are respectively handled by hydrogen storage (slow / large capacity), heat pump / thermal storage (medium speed / thermal inertia) and battery (fast / high frequency), realizing fine smoothing of the entire frequency band without supercapacitors.

[0025] 2. Unique Two-Way Help Feedback Mechanism: The first-stage filter breaks through the limitations of traditional one-way decomposition. When the battery or thermal storage tank's State of Charge (SOC) faces the risk of exceeding its limit, it actively outputs a "help factor" to reduce λ. L This forces large-capacity upstream hydrogen storage systems to absorb more broadband fluctuations in order to avoid system collapse.

[0026] 3. Eliminate the soft cutoff logic of abrupt transitions: The SOC constraints of all devices (including HSS, HP / HST, BESS) adopt a continuous linear "soft cutoff" derating logic instead of the traditional hard threshold cutoff, which greatly improves the smoothness of the microgrid power command.

[0027] 4. Battery Adaptive Dead Zone Life Extension: To address the cycle life reduction caused by high-frequency minute movements of the battery, a dynamic adaptive control system is designed with no dead zone in the SOC golden range and activated dead zone in the non-golden range, achieving a perfect balance between the smoothing effect and battery life. Attached Figure Description

[0028] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. It should be understood that the drawings are only schematic and are not drawn to scale.

[0029] Figure 1 This is the logic flow diagram of the two-stage dynamic filtering and three-stage power allocation and transfer coordinated control of the present invention. Detailed Implementation

[0030] This invention provides a method for mitigating power fluctuations in a combined hydrogen storage, thermal storage, and electricity storage microgrid. The method includes: (1) a system state parameter acquisition step: the controller acquires the current operating state parameters and environmental variables of the microgrid system in real time at a preset control cycle (e.g., 1 minute). Specifically, this includes: the net fluctuating power P at the renewable energy grid connection point. Flu_total The battery's current state of charge (SOC) BESS Current State of Charge (SOC) of the thermal storage tank HST The current state of charge (SOC) of the hydrogen storage system HSS Outdoor ambient temperature T out User indoor temperature T Room and the user's current basic hydrogen load P H2_load .

[0031] (2) Benchmark subtraction and two-stage dynamic filtering decomposition steps:

[0032] (a) Baseline power deduction for hydrogen storage: Set the baseline operating target power P of the hydrogen storage system (HSS). target_base and combined with SOC BESS Implement intelligent credit limit reduction. Calculate the credit limit reduction factor D. factor When SOC BESS When ≥0.6, D factor =1.0; when SOC BESS When ≤0.4, D factor =0; when it is between 0.4 and 0.6, perform linear interpolation calculation. Determine the current hydrogen production reference power P. HSS_Base =P target_base × D factor And calculate the net fluctuation power used for subsequent filtering decomposition, such as Figure 1 As shown, the power of the fluctuation to be smoothed (P) is obtained. Flu (This is obtained by subtracting the HSS reference power from the net fluctuation).

[0033] (b) Dynamic low-pass filter LPF1 (L / MH separation): such as Figure 1 As shown, the power fluctuations to be smoothed enter the first-stage low-pass filter (LPF1) (which includes a time constant λ). L First-stage filter time constant (λ) L The calculation employs bidirectional feedback logic for dynamic computation, which is performed by... Figure 1 λ on the left L The two-way dynamic adjustment module is complete:

[0034] Basic intention calculation: This module receives the feedback signal SOC. HSS (Basic) SOC HSS The basic time constant is obtained by V-shaped curve interpolation when SOC HSS It takes the minimum value when in the middle safe region (rated point) and the maximum value when at the extreme edges; Downstream help feedback factor: This module monitors and receives the downstream signal SOC in real time through the dashed line. BESS (Seeking help) and SOC HST (Seeking help). Taking a storage battery as an example, when the SOC... BESS When the system is in the safe zone [0.3, 0.8], the feedback factor is 1.0; when it enters the preset danger zone, the linear transition output is less than the minimum emergency response factor of 1. The feedback factor for the thermal storage tank is similar.

[0035] Integrated decision-making and clamping: Integrated time constant λ L The product of the base time constant and the smallest of the two is used to force a reduction in the first-stage filter time constant when downstream equipment is under extreme pressure, thus transferring more low- and medium-frequency fluctuations to the hydrogen storage system. To prevent frequency overlap, λ is... LThe absolute lower limit clamp is located at λ M_max +1.0. After the calculation is completed, the first-order inertial filter formula P is discretized. L (t)= (1-λ L )P L (t-1)+ (λ L )P flu_for_filter (t) Extract low-frequency components, such as Figure 1 As shown in the flow direction, the input is decomposed into low-frequency components (P). L ) and mid-to-high frequency components (P MH ).

[0036] (c) Dynamic low-pass filter LPF2 (M / H separation): such as Figure 1 As shown, the mid-to-high frequency components enter the second-stage low-pass filter (LPF2) (which includes a time constant λ). M The second-stage filter time constant λ M Depend on Figure 1 λ on the right M The smoothing adjustment module performs the adjustment, and this module receives three dashed feedback signals: T Room (room temperature deviation), SOC BESS and SOC HST Among them, SOC BESS The factor uses PCHIP smoothing interpolation, taking the peak value near the middle value and the trough value at both ends; SOC HST The factor uses linear interpolation, increasing linearly from 0.9 to 1.2 with increasing thermal state; the temperature error factor T is calculated. Room The absolute value of the deviation from the set comfort range; the larger the deviation, the more linearly this factor increases from 1.0 to over 1.5. λ is calculated by multiplying the three smoothing factors together. M Then, using the same first-order digital filtering formula, such as Figure 1 As shown in the flow direction, the mid-to-high frequency components (P) MH Decomposed into intermediate frequency components (P) M ) and high-frequency components (P H ).

[0037] (3) Initial task allocation steps: assign the low-frequency component P L P, as the initial command reference value for the hydrogen storage system L_consume_ref The intermediate frequency component P M P, as the initial command reference value for the heat pump system M_consume_ref , will high frequency component P H P, the initial command reference value for the battery H_consume_ref .

[0038] (4) Coordinated control steps for hydrogen storage system (HSS) (low frequency): such as Figure 1As shown in the lower left corner of the Hydrogen Storage System Coordination and Control Layer (HSS), P HSS_Base With P L_consume_ref Superimposed as the general command for hydrogen storage P HSS_cmd Right now Figure 1 The superimposed hydrogen production baseline logic is used. After applying physical limit constraints, a non-jumping soft cutoff protection logic is introduced. Figure 1 The soft-cutoff SOC limiting includes preset charging and discharging warning zones. If charging is required and a warning is triggered, it is based on formula D. HSS = (SOC max - SOC HSS ) / (SOC max -SOC warn_charge Calculate the reduction factor by multiplying the original instruction by D. HSS Amplification and compression are applied; the same applies to discharge. Finally, the actual absorbed power P is calculated. HSS_consume_actual And the low-frequency transfer quantity P that could not be processed due to limitations L_transfer = P HSS_cmd -P HSS_consume_actual Issued to the heat pump system (corresponding) Figure 1 The middle arrow points to the horizontal solid line arrow of the heat pump and the transfer of low-frequency fluctuations P. L_transfer (5) Coordinated control steps for heat pump (HP) and thermal storage tank (HST) (medium frequency): such as Figure 1 As shown in the lower middle heat pump coordination control layer (HP / HST), the total fluctuating response requirement of the heat pump is P. HP_consume_ref_total = P M + P L_transfer Execute the following based on the system's current cooling / heating mode:

[0039] Heating mode: such as Figure 1 As shown in the superimposed basic thermal power, the basic power P HP_base Controlled by feedforward (user heat demand / COP) and feedback (storage tank temperature difference × K). p Composed of ( ). Utilizing the current SOC HST Calculate the soft cutoff correction factor αHST when attempting to further increase power and SOC HST When ≥0.85, αHST linearly decreases to 0.1; as Figure 1 As shown in the winter / summer mode soft cutoff limiting, the actual power for smoothing fluctuations is P. HP_flu = P HP_consume_ref_total × αHST. General instruction P HP_cmd =P HP_base + P HP_flu .

[0040] Cooling mode: Base power P HP_base = |Q demand| / EER, the fluctuation response coefficient α remains at 1.0, and the response is directly superimposed.

[0041] like Figure 1 The middle arrow points to the horizontal solid line arrow of the battery and the transfer of low-frequency fluctuations P. M_transfers As shown, after applying physical power limits, the actual fluctuation amount smoothed by the heat pump is calculated, and the unprocessed residual amount is denoted as P. M_transfer This information is then transmitted to the battery control layer.

[0042] (6) Battery Escape Control Procedure (Frequency Frequency): (e.g., ...) Figure 1 As shown in the lower right corner of the Battery Coordination and Control Layer (BESS), the total battery response requirement is P. BESS_consume_ref_total = P H + P M_transfer .like Figure 1 As shown in the adaptive dead-time judgment, the adaptive dead-time control mechanism is executed: the current SOC is determined. BESS Is it within the preset golden health range? If within the range, the equivalent dead zone is set to 0 to fully absorb all minor fluctuations; if outside the range, the basic dead zone threshold is restored. When the absolute value of demand is less than this dead zone, the instruction is directly set to zero, thereby filtering out high-frequency, worthless micro-movements to protect the lifespan. Figure 1 As shown in the soft cutoff SOC limiting, a similar soft cutoff derating logic as HSS is then executed to obtain the final battery output power command P. BESS .

[0043] (7) Control command issuance and system status update steps: The final P HSS P HP_cmd P BESS The data is transmitted to each device's converter / frequency converter for execution via communication. The next state is updated based on the Euler integral method and the law of conservation of energy: the battery and hydrogen storage SOC are updated according to charge / discharge power and efficiency; thermodynamic models are used to calculate heat loss from the walls, heat pump heating / cooling input, and the heat loss Q from the storage tank to the environment. loss_HST Update indoor temperature and storage tank water temperature, and calculate the latest SOC. HST ,like Figure 1 As shown by the dotted feedback loop at the bottom, the latest SOC states at the bottom layer are fed back to the top layer through the dotted lines and enter the next control cycle.

Claims

1. A method for mitigating power fluctuations in a combined electrothermal-hydrogen microgrid integrating hydrogen storage, thermal storage, and electricity storage, characterized in that, The method includes state acquisition: real-time acquisition of renewable energy fluctuation power in the combined electric-thermal-hydrogen microgrid. P Flu State of charge of hydrogen storage system SOCIETY HSS Battery state of charge SOCIETY BESS Thermal status of the heat storage tank SOCIETY HST Outdoor temperature T out User indoor temperature T Room And hydrogen load.

2. The method according to claim 1, characterized in that, Includes dynamic frequency division and power decomposition: a two-stage dynamic low-pass filter is used to decompose fluctuating power. P Flu Decomposed into low-frequency components P L Intermediate frequency components P M and high frequency components P H ; The first-stage low-pass filter decomposes the net fluctuating power after deducting the hydrogen storage reference power into low-frequency and mid-to-high-frequency components, and its filtering time constant is... λ L according to SOCIETY HSS 、SOC BESS and SOCIETY HST Perform two-way dynamic feedback adjustments; The second-stage low-pass filter decomposes the mid-to-high frequency components into mid-frequency and high-frequency components, and its filtering time constant is... λ M according to SOCIETY BESS 、SOC HST and T Room The error is dynamically and smoothly adjusted.

3. The method according to claim 2, characterized in that, The filter time constant λ L The two-way dynamic feedback adjustment mechanism is as follows: the state of the hydrogen storage system itself... SOCIETY HSS Determine the fundamental time constant when SOCIETY HSS The value is minimized when the area is in the middle safe zone and maximized when the area is in the extreme zones at both ends; a downstream help feedback factor is set: when a downstream help feedback factor is detected... SOCIETY BESS or SOCIETY HST When entering a preset danger zone, output a help factor less than 1; combined with the time constant. λ L The product of the basic time constant and the help factor is used to force a reduction in the first-stage filter time constant when the downstream equipment is under extreme pressure, thereby transferring the low- and medium-frequency fluctuations to the hydrogen storage system.

4. The method according to claim 3, characterized in that, Including preliminary task allocation: assigning low-frequency components P L Initially allocated to the hydrogen storage system HSS, the medium-frequency component P M Initially allocated to the HP heat pump system, high-frequency components P H Initially allocated to the BESS battery.

5. The method according to claim 4, characterized in that, This includes the coordinated control of the hydrogen storage system (HSS): the total power command of the hydrogen storage system is determined by meeting hydrogen production requirements and adapting accordingly. SOCIETY BESS Linked reference power, and allocated low-frequency components P L Composition; combination Soft cutoff logic, when SOCIETY HSS Dynamically reduce the charging and discharging power when the power is close to the upper or lower limits; Transfer of low-frequency fluctuations that hydrogen storage systems are unable to handle P L_transfer Issued to the heat pump system.

6. The method according to claim 5, characterized in that, This includes coordinated control of the heat pump (HP) and the heat storage tank (HST): the heat pump's commands for smoothing out fluctuations include a distributed mid-frequency component. P M Low-frequency fluctuations in hydrogen storage system transfer P L_transfer The sum; the total heat pump command consists of the base power to maintain the target temperature of the heat storage tank and the corrected power to smooth out fluctuations; based on whether the system is currently in heating or cooling mode, and according to... SOCIETY HST The soft-cutoff logic limits and corrects the power fluctuations; and transfers the low-to-medium frequency fluctuations that the heat pump cannot handle. P M_transfer Distribute to the storage batteries.

7. The method according to claim 6, characterized in that, Includes battery BESS coordination control: the battery handles the distribution of high-frequency components. P H Mid-to-low frequency fluctuations related to heat pump transfer P M_transfer The sum; adopting an adaptive dead-time control mechanism based on SOC: when SOCIETY BESS When within the preset golden safety range, the dead zone is set to zero to respond to all minor fluctuations; when SOCIETY BESS When deviating from the golden range, a preset dead zone threshold is activated to filter out minor fluctuations and reduce cycle loss; finally, combined with SOCIETY BESS The soft-cutoff logic outputs the final battery execution command, which is then sent to various devices for execution.

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