Wind-solar-water-hydrogen multi-energy flow collaborative regulation system based on sponge watershed

Abstract

The application discloses a wind-solar-water-hydro multi-energy flow collaborative regulation system based on a sponge watershed. The system comprises an acquisition module, a mapping module, a setting module, a generation module, a delivery module and a control module. Through millisecond-level time sequence synchronization and data alignment, the application accurately captures the real-time correlation of hydrological dynamic changes, energy output and load demand, meets the hydrological safety requirements such as watershed flood control and drainage, ecological base flow guarantee, and guarantees the collaborative optimization regulation of wind-solar-water-hydro multi-energy flow, effectively suppresses the random fluctuation of new energy output, and improves the new energy consumption efficiency and energy supply and demand matching accuracy.

Description

Technical Field

[0001] This invention belongs to the field of multi-energy flow coordinated regulation, specifically involving a wind, solar, water, and hydrogen multi-energy flow coordinated regulation system based on sponge basins. Background Technology

[0002] With the advancement of the "dual carbon" goals, the penetration rate of new energy in my country has exceeded 30%, and the need for coordinated development of watershed-level energy and water resources management is becoming increasingly urgent.

[0003] Among them, the sponge watershed refers to a watershed management model that optimizes the watershed hydrological cycle through comprehensive measures of "infiltration, retention, storage, purification, utilization, and drainage" and can achieve a rainwater regulation and utilization rate of over 60%; the wind-solar-hydro-hydrogen multi-energy flow system is a comprehensive energy system that uses wind energy, solar energy, and hydropower as primary energy sources and hydrogen energy as an energy storage carrier to mitigate the intermittency and volatility of new energy sources.

[0004] Patent application No. 202410691031.X discloses a method for multi-energy coordination and grid regulation in zero-carbon agricultural and pastoral parks that considers power flow reversal. This application aims to address the problem that "in zero-carbon agricultural and pastoral parks, renewable energy systems are widely used, but these energy systems are volatile and uncertain, posing challenges to the stable operation of the power grid. At the same time, with the continuous increase in renewable energy power generation, the phenomenon of power flow reversal is becoming increasingly prominent. Power flow reversal refers to the phenomenon of power flowing from low voltage levels to high voltage levels due to reasons such as excess renewable energy power generation or load changes. This may not only affect the voltage stability and power quality of the power grid, but may also damage power grid equipment and even cause safety accidents."

[0005] However, in the scenario of coordinated regulation of wind, solar, water and hydrogen energy flows in sponge watersheds, there is currently no effective millisecond-level linkage regulation mechanism between the hydrological dynamics of sponge watersheds and the multi-energy flows of wind, solar, water and hydrogen. This makes it impossible to accurately match hydrological processes (such as fluctuations in the water storage and drainage of the sponge body) with changes in energy output, resulting in wind and solar curtailment rates in some watersheds far exceeding the target values, insufficient water resource utilization, and low overall system efficiency and stability.

[0006] To this end, this invention proposes a multi-energy flow coordinated regulation system based on sponge basins, encompassing wind, solar, water, and hydrogen flows. Summary of the Invention

[0007] The purpose of this invention is to provide a multi-energy flow coordinated regulation system based on sponge basins, encompassing wind, solar, water, and hydrogen flows.

[0008] This invention is achieved through the following technical solution: The system described in this invention includes the following modules: The data acquisition module is used to synchronously acquire real-time parameters of hydrological processes and real-time operating status data of various energy units such as wind, solar, water and hydrogen within the sponge watershed, and to perform data alignment and interpolation to complete missing values. The mapping module is used to construct a millisecond-level linkage and correlation mapping that follows the dynamic process of hydrology and the output of multiple energy units based on the collected hydrological parameters and energy operation data. The setting module is used to set the constraints and adjustable boundary ranges of multi-energy flow coordinated regulation based on the requirements of sponge watershed hydrological regulation and the operating characteristics of multi-energy units. The generation module is used to apply linkage mapping, control constraints and boundaries to generate millisecond-level collaborative control strategies for wind, solar, water and hydrogen multi-energy flow that are adapted to hydrological dynamics. The distribution module is used to break down the generated coordinated control strategy into independent execution instructions corresponding to the hydrological control unit and each energy unit, and to distribute them synchronously to the corresponding execution units. The control module is used to perform millisecond-level timing matching and control of the control actions of the hydrological control unit and various energy units such as wind, solar, water and hydrogen, and to constrain the execution timing and synchronization accuracy of the control actions of each unit. The acquisition module is interactively connected to the mapping module via a wireless network. The mapping module is interactively connected to the setting module via a wireless network. The setting module is interactively connected to the generation module and the distribution module via a wireless network. The distribution module is interactively connected to the generation module via a wireless network. The generation module and the distribution module are interactively connected to the control module via a wireless network.

[0009] The acquisition module of this invention includes the following: The system collects real-time hydrological parameters such as water level, runoff, adjustable water volume, soil moisture content, and infiltration rate within the sponge watershed. The acquisition module also collects real-time operational status data of each unit in the entire chain of wind power, photovoltaic power, hydropower, hydrogen production-hydrogen storage-hydrogen power generation, including output power, operating efficiency, adjustable capacity, and start / stop status. Add a uniform millisecond-level timestamp to all collected parameters and data, and perform time-series alignment and missing value interpolation based on the timestamps.

[0010] Furthermore, the missing value interpolation and completion method described in this invention completes the missing value completion through the proximity time similarity interpolation method based on the hydrological-energy coupling characteristics. The proximity time similarity interpolation method is based on the effective data within a preset time period before and after the time when the missing value is located, extracts the coupling characteristic similarity of hydrological and energy parameters, selects effective data points whose similarity meets a preset threshold (the preset threshold is comprehensively calibrated by the requirements of hydrological and energy parameter acquisition accuracy, data time sequence stability and missing value completion reliability) for weighted interpolation, and completes the single-dimensional missing value completion. If it is a multi-dimensional synchronous missing value, cross-completion is performed based on the established hydrological-energy parameter correlation relationship.

[0011] The mapping module of this invention constructs a millisecond-level linkage mapping between hydrological dynamic processes and the output of multiple energy units, that is, it constructs a hydrological-energy parameter correlation relationship that follows the function: ; In the formula: t represents the current real-time moment, in milliseconds; Let be the hydrological state vector at time t; Let t be the output / power consumption vector of the adjustable energy unit at time t; This is for the real-time power consumption of the hydrogen production unit; The hydrological-energy linkage coefficient matrix is ​​calibrated based on the characteristics of watershed regulation and hydropower units. The energy supply and demand matching coefficient matrix is ​​calibrated by combining the ramp rate and response characteristics of multiple energy units; Let t be the real-time total power load within the watershed at time t; Let t be the real-time total output of wind power and photovoltaic power. The , , The expression is: ; In the formula: Real-time water level at the core water storage nodes of the basin; Real-time transit runoff volume in the watershed; The real-time adjustable water storage volume of the basin; Provide real-time power output for the hydroelectric unit; This represents the real-time power consumption of the hydrogen production unit; T indicates the transpose symbol. , Provides real-time power output for wind and solar power units; The linkage mapping is used to characterize the real-time driving relationship between dynamic changes in hydrological conditions and the output of adjustable energy units, as well as the real-time correction relationship between energy supply and demand gaps and the output of adjustable energy units.

[0012] The constraints of the multi-energy flow coordinated regulation described in the setting module of this invention include hydrological security constraints, energy operation constraints, and supply and demand balance constraints; The adjustable boundary range is the maximum allowable adjustment range of the adjustable actions of each hydrological control unit and each energy unit, determined based on the above constraints.

[0013] Furthermore, the hydrological safety constraints described in this invention include preset range constraints on water levels at water storage nodes in the basin, minimum threshold constraints on ecological base flow, and upper limit constraints on flood control and drainage flow. Energy operation constraints include upper and lower limits of output for each energy unit, unit ramp-up rate constraints, operating efficiency range constraints for hydrogen production units, and upper and lower limits of capacity constraints for hydrogen storage units. Supply and demand balance constraints include real-time balance constraints between the power generation output and power load of the entire system and the power consumption of hydrogen production.

[0014] The generation module of this invention generates a millisecond-level collaborative regulation strategy for wind, solar, hydro, and hydrogen multi-energy flow adapted to hydrological dynamics, which follows the following optimization objective function: ; In the formula: The target value for optimizing the control strategy; This is the starting point of the control strategy; The preset control period for the control strategy; For integration time; for Hydrological state vector at any given time; The preset hydrological state target time series curve; To adjust the smoothness weighting coefficient; for The output / power consumption vector of the energy unit is adjustable in real time; It is the 2-norm of the vector; The Based on the equipment type, preset maximum allowable ramp rate, and preset annual allowable adjustment times corresponding to the equipment design life of each adjustable energy unit, it is used to balance the tracking accuracy of hydrological control with the adjustment smoothness requirements of the energy unit. It characterizes the fluctuation of the adjustment rate of the output / power consumption of the adjustable energy unit. The smaller the value, the smoother the adjustment action of the energy unit. Among them, the optimization objective function simultaneously satisfies all the constraints set by the module operation, and the generated collaborative control strategy is the output timing curve of each adjustable unit that minimizes the optimization objective value.

[0015] During the operation phase of the distribution module described in this invention, the output timing curve corresponding to the coordinated control strategy is decomposed into independent execution instructions for each hydrological control unit and each energy unit within each millisecond-level control step. A corresponding execution time window and priority label are added to each independent execution instruction. Based on a preset low-latency transmission channel, all execution instructions with time windows are synchronously distributed to the corresponding execution units, ensuring that the end-to-end delay of instruction transmission does not exceed a preset threshold (the preset threshold is comprehensively calibrated by the system's millisecond-level control requirements, the inherent response delay of each execution unit, the performance of the low-latency transmission channel, and the synchronization accuracy requirements of hydrological-energy coordinated control).

[0016] The control module of this invention is based on a unified clock source and performs millisecond-level timing calibration on the execution actions of each execution unit to ensure that the execution synchronization error of the control actions of each unit does not exceed a preset threshold (the preset threshold is comprehensively calibrated by the timing accuracy of the unified clock source, the millisecond-level control step size of the system, the synchronization accuracy requirements of hydrological-energy coordinated control, and the inherent action response delay of each execution unit). It also collects the action execution feedback data of each execution unit in real time, compares it with the target value of the corresponding execution instruction, issues correction instructions in real time to units whose execution deviation exceeds the preset threshold, and simultaneously identifies abnormal actions that exceed the adjustable boundary range during the execution process and immediately triggers an emergency lockout instruction. The correction instruction includes the target adjustment amount, execution time window, and deviation compensation coefficient of the corresponding unit within the current millisecond-level control step size; The emergency lockout command includes an action lockout identifier, a unit current operating status maintenance command, and an abnormal signal upload command. After the lockout is triggered, the abnormal information is pushed to the system master control terminal simultaneously until the master control terminal issues an unlocking command or the abnormality is cleared. Each unit continues to maintain the safe operating state at the time of lockout.

[0017] Furthermore, the formula for calculating the deviation compensation coefficient of the present invention is as follows: ; In the formula: This is the real-time deviation compensation coefficient for the corresponding execution unit; The preset maximum compensation coefficient is determined by comprehensively considering the rated ramp rate of each execution unit, the system's millisecond-level control step size, the over-adjustment suppression safety requirements, and the inherent response characteristics of the equipment. It is used to suppress over-adjustment oscillations. t represents the current real-time moment in milliseconds. The real-time execution deviation value of the execution unit at time t is equal to the difference between the unit's current actual output / action value and the target value of the corresponding execution command. R is the real-time rate of change of the execution deviation at time t; R is the rated ramp rate of the execution unit, which is pre-calibrated based on the characteristics of the unit equipment and the field operation data, and the unit is power / millisecond or action amount / millisecond. The system is preset with a millisecond-level adjustment step size to meet the requirements. ≥ ; This is the inherent response delay of the execution unit, pre-calibrated from the unit's action response characteristics, and is expressed in milliseconds. The preset positive real number for zero-bias protection; The target adjustment amount is the inverse product of the deviation compensation coefficient and the real-time execution deviation value, that is, the target adjustment amount is .

[0018] Compared with the prior art, the present invention has the following beneficial effects: 1. In this invention, the system accurately captures the real-time correlation between hydrological dynamics and energy output and load demand through millisecond-level time synchronization and data alignment. While meeting the hydrological safety requirements such as flood control and drainage and ecological base flow protection in the basin, it ensures the coordinated and optimized regulation of multiple energy flows including wind, solar, hydro, and hydrogen, effectively smoothing out random fluctuations in new energy output and improving the efficiency of new energy consumption and the accuracy of energy supply and demand matching. At the same time, it reduces the losses caused by frequent start-ups and shutdowns and large adjustments of equipment through smooth adjustment strategies, extends the service life of equipment, and ensures the synchronization and operational safety of the entire system's regulation actions through time control, deviation correction, and anomaly lock-up mechanisms.

[0019] 2. The mapping module of this invention constructs a millisecond-level linkage and correlation mapping that follows the dynamic process of hydrology and the output of multiple energy units. It captures the real-time dynamic change relationship between the hydrological state of the sponge watershed and the output of adjustable energy units in a differential form. Based on the characteristics of watershed regulation and hydropower units, it calibrates the hydrology-energy linkage coefficient matrix. Combined with the climbing and response characteristics of multiple energy units, it calibrates the energy supply and demand matching coefficient matrix. On the one hand, it accurately characterizes the driving effect of the dynamic change of hydrological state on the output of adjustable energy units. On the other hand, it realizes the real-time correction of the output of adjustable energy units through the power difference between energy load and wind, solar and hydrogen production. In this way, it constructs a millisecond-level linkage and correlation between hydrology and multiple energy units, so that the dynamic coupling relationship between the two has quantifiable calculation conditions. , , The formula set clearly defines the core components of the hydrological state vector of the sponge watershed, the output / power consumption vector of adjustable energy units, and the total output of wind and solar power. It focuses the hydrological state on three key indicators: water level at the storage node, transit runoff, and volume of adjustable water bodies. It identifies the adjustable energy units as two core adjustable objects: hydropower output and hydrogen production power consumption. The total output of wind and solar power directly integrates the real-time output of wind and solar power. It achieves standardized and dimensional representation of core parameters through vector transposition and direct summation, providing clear and unified parameter support for millisecond-level calculations of hydrological-energy linkage.

[0020] 3. The objective function of the generation module of this invention achieves comprehensive optimization of hydrological control and energy regulation through integral calculation within the control cycle. It quantifies the deviation between the actual hydrological state and the preset target time series curve through 2-normative quantification, and introduces a smoothness weight coefficient. This coefficient is calibrated in combination with the energy equipment type, the maximum allowable ramp rate, and the annual number of regulation corresponding to the design life. This balances the tracking accuracy of hydrological control in sponge watersheds with the smoothness requirements of energy unit regulation, and incorporates the fluctuation of the energy unit output regulation rate into the optimization scope. This ensures that the optimization objective not only meets the safety requirements of hydrological control in sponge watersheds, but also takes into account the operational stability and service life of energy equipment, thereby solving for the optimal adjustable unit output time series curve under given constraints.

[0021] 4. The deviation compensation coefficient calculation formula of the control module of this invention avoids the problem of over-compensation oscillation by using upper and lower limit extreme value constraints. It calculates the basic compensation value by combining the rated ramp rate of the execution unit, the preset control step size of the system and the inherent response delay of the unit. At the same time, it incorporates the real-time execution deviation value and the deviation change rate, and adds a positive real number to prevent zero bias to avoid calculation abnormalities. In this way, the compensation coefficient adapted to the current execution state of the unit is dynamically calculated. Then, the correction target adjustment amount is determined by the inverse product of the compensation coefficient and the real-time execution deviation value. It can accurately adjust the compensation degree according to the millisecond-level operation feedback of each execution unit, adapt to the response characteristics of different devices, effectively suppress the expansion of execution deviation, and ensure the real-time and accurate correction of the control execution action. Attached Figure Description

[0022] Figure 1 A schematic diagram of the structure of a multi-energy flow coordinated regulation system based on sponge basins, including wind, solar, water, and hydrogen. Detailed Implementation

[0023] The technical solution of the present invention will be further described in detail below through specific embodiments.

[0024] Example 1 This embodiment features a multi-energy flow coordinated regulation system based on sponge basins, including wind, solar, water, and hydrogen flows. Figure 1 As shown, it includes: The data acquisition module is used to synchronously acquire real-time parameters of hydrological processes and real-time operating status data of various energy units such as wind, solar, water, and hydrogen within the sponge watershed. During the data acquisition module's operation phase, synchronous acquisition and alignment of hydrological parameters and energy data are performed. The data acquisition module collects real-time hydrological parameters such as water level, runoff, adjustable water volume, soil moisture content, and infiltration rate within the sponge watershed. The data acquisition module also collects real-time operational status data of each unit in the entire chain of wind power, photovoltaic power, hydropower, hydrogen production-hydrogen storage-hydrogen power generation, including output power, operating efficiency, adjustable capacity, and start / stop status. The acquisition module adds a uniform millisecond-level timestamp to all acquired parameters and data, and performs time-series alignment and missing value interpolation based on the timestamps; Among them, missing value interpolation and completion is completed by the neighboring time similarity interpolation method based on the hydrological-energy coupling characteristics. The neighboring time similarity interpolation method is based on the effective data within a preset time period before and after the time of the missing value, extracts the coupling characteristic similarity of hydrological and energy parameters, selects effective data points whose similarity meets the preset threshold (the preset threshold is comprehensively calibrated by the requirements of hydrological and energy parameter acquisition accuracy, data time sequence stability and missing value completion reliability) for weighted interpolation, and completes the single-dimensional missing value completion. If it is a multi-dimensional synchronous missing value, cross-completion is performed based on the established hydrological-energy parameter correlation relationship.

[0025] The mapping module is used to construct a millisecond-level linkage and correlation mapping between hydrological dynamic processes and the output of multiple energy units (i.e., hydrological-energy parameter correlation) based on the collected hydrological parameters and energy operation data.

[0026] The mapping module constructs a millisecond-level linkage mapping between the hydrological dynamic process and the output of multiple energy units, which follows the following rules: ; In the formula: t represents the current real-time moment, in milliseconds; Let be the hydrological state vector at time t; Let t be the output / power consumption vector of the adjustable energy unit at time t; This is for the real-time power consumption of the hydrogen production unit; The hydrological-energy linkage coefficient matrix is ​​calibrated based on the characteristics of watershed regulation and hydropower units. The energy supply and demand matching coefficient matrix is ​​calibrated by combining the ramp rate and response characteristics of multiple energy units; Let t be the real-time total power load within the watershed at time t; Let t be the real-time total output of wind power and photovoltaic power. , , The expression is: ; In the formula: Real-time water level at the core water storage nodes of the basin; Real-time transit runoff volume in the watershed; The real-time adjustable water storage volume of the basin; Provide real-time power output for the hydroelectric unit; This represents the real-time power consumption of the hydrogen production unit; T indicates the transpose symbol. , It provides real-time power output to wind and solar power units.

[0027] The linkage mapping is used to characterize the real-time driving relationship between dynamic changes in hydrological conditions and the output of adjustable energy units, as well as the real-time correction relationship between energy supply and demand gaps and the output of adjustable energy units.

[0028] The setting module is used to set the constraints and adjustable boundary ranges for multi-energy flow coordinated regulation based on the hydrological regulation requirements of sponge watersheds and the operating characteristics of multi-energy units.

[0029] The constraints set by the module for multi-energy flow coordinated regulation include hydrological security constraints, energy operation constraints, and supply and demand balance constraints. The adjustable boundary range is the maximum allowable adjustment range of the adjustable actions of each hydrological control unit and each energy unit, determined based on the above constraints.

[0030] Among them, the hydrological safety constraints set by the setting module include the preset range constraints of the water level of the water storage nodes in the basin, the minimum threshold constraints of the ecological base flow, and the upper limit constraints of the flood control and drainage flow. Energy operation constraints include upper and lower limits of output for each energy unit, unit ramp-up rate constraints, operating efficiency range constraints for hydrogen production units, and upper and lower limits of capacity constraints for hydrogen storage units. Supply and demand balance constraints include real-time balance constraints between the power generation output and power load of the entire system and the power consumption of hydrogen production.

[0031] The generation module is used to apply linkage mapping, control constraints and boundaries to generate millisecond-level collaborative control strategies for wind, solar, water and hydrogen multi-energy flow that are adapted to hydrological dynamics.

[0032] The generation module generates a millisecond-level collaborative regulation strategy for wind, solar, hydro, and hydrogen multi-energy flow adapted to hydrological dynamics, following the optimization objective function: ; In the formula: The target value for optimizing the control strategy; This is the starting point of the control strategy; The preset control period for the control strategy; For integration time; for Hydrological state vector at any given time; The preset hydrological state target time series curve; To adjust the smoothness weighting coefficient; for The output / power consumption vector of the energy unit is adjustable in real time; It is the 2-norm of the vector; Based on the equipment type, preset maximum allowable ramp rate, and preset annual allowable adjustment times corresponding to the equipment design life of each adjustable energy unit, it is used to balance the tracking accuracy of hydrological control with the adjustment smoothness requirements of the energy unit. It characterizes the fluctuation of the adjustment rate of the output / power consumption of the adjustable energy unit. The smaller the value, the smoother the adjustment action of the energy unit.

[0033] Among them, the optimization objective function simultaneously satisfies all the constraints set by the module operation, and the generated collaborative control strategy is the output timing curve of each adjustable unit that minimizes the optimization objective value.

[0034] The distribution module is used to break down the generated coordinated control strategy into independent execution instructions corresponding to the hydrological control unit and each energy unit, and to distribute them synchronously to the corresponding execution units.

[0035] During the module operation phase, the output timing curves corresponding to the coordinated control strategy are decomposed into independent execution instructions for each hydrological control unit and each energy unit within each millisecond-level control step. Each independent execution instruction is given a corresponding execution time window and priority label. Based on the preset low-latency transmission channel, all execution instructions with time windows are synchronously sent to the corresponding execution units, ensuring that the end-to-end delay of instruction transmission does not exceed the preset threshold (the preset threshold is comprehensively calibrated by the system's millisecond-level control requirements, the inherent response delay of each execution unit, the performance of the low-latency transmission channel, and the synchronization accuracy requirements of hydrological-energy coordinated control).

[0036] The control module is used to perform millisecond-level timing matching and control of the control actions of the hydrological control unit and various energy units such as wind, solar, water and hydrogen, and to constrain the execution timing and synchronization accuracy of the control actions of each unit.

[0037] The control module, based on a unified clock source, performs millisecond-level timing calibration on the execution actions of each execution unit to ensure that the synchronization error of the control actions of each unit does not exceed a preset threshold (the preset threshold is comprehensively calibrated by the timing accuracy of the unified clock source, the millisecond-level control step size of the system, the synchronization accuracy requirements of hydrological-energy coordinated control, and the inherent action response delay of each execution unit). It also collects the action execution feedback data of each execution unit in real time, compares it with the target value of the corresponding execution command, and issues correction commands in real time to units whose execution deviation exceeds the preset threshold. Simultaneously, it identifies abnormal actions that exceed the adjustable boundary range during the execution process and immediately triggers an emergency lockout command.

[0038] Among them, the correction instruction includes the target adjustment amount, execution time window and deviation compensation coefficient of the corresponding unit within the current millisecond-level control step; the emergency lock instruction includes the action lock indicator, the unit current running status maintenance instruction and the abnormal signal upload instruction. After the lock is triggered, the abnormal information is pushed to the system master control terminal simultaneously until the master control terminal issues the unlock instruction or the abnormality is cleared. Each unit continues to maintain the safe operating state when locked.

[0039] The formula for calculating the deviation compensation coefficient is: ; In the formula: This is the real-time deviation compensation coefficient for the corresponding execution unit; The preset maximum compensation coefficient is determined by comprehensively considering the rated ramp rate of each execution unit, the system's millisecond-level control step size, the over-adjustment suppression safety requirements, and the inherent response characteristics of the equipment. It is used to suppress over-adjustment oscillations. t represents the current real-time moment in milliseconds. The real-time execution deviation value of the execution unit at time t is equal to the difference between the unit's current actual output / action value and the target value of the corresponding execution command. R is the real-time rate of change of the execution deviation at time t; R is the rated ramp rate of the execution unit, which is pre-calibrated based on the characteristics of the unit equipment and the field operation data, and the unit is power / millisecond or action amount / millisecond. The system is preset with a millisecond-level adjustment step size to meet the requirements. ≥ ; This is the inherent response delay of the execution unit, pre-calibrated from the unit's action response characteristics, and is expressed in milliseconds. The preset positive real number for zero-bias protection; The target adjustment amount is the inverse product of the deviation compensation coefficient and the real-time execution deviation value, that is, the target adjustment amount is .

[0040] The data acquisition module is connected to the mapping module via a wireless network. The mapping module is connected to the setting module via a wireless network. The setting module is connected to the generation module and the distribution module via a wireless network. The distribution module is connected to the generation module via a wireless network. The generation module and the distribution module are connected to the control module via a wireless network.

[0041] Based on the system in the above embodiments, an application example of the system is shown: A pilot sponge watershed project in a hilly area covers a total area of ​​118 square kilometers. It includes a 20MW wind farm, a 30MW centralized photovoltaic power station, a 15MW run-of-river hydropower station, and a 2MW integrated hydrogen production-storage-hydrogen turbine energy unit. It is also equipped with a core regulating reservoir, distributed permeable sponge facilities, and drainage gates and other hydrological control units. This region experiences frequent short-duration heavy rainfall during the rainy season, and has long faced challenges in flood control and drainage, difficulties in integrating wind and solar energy, and insufficient coordination between hydropower and hydrological control. This application demonstrates the actual control process for this watershed in responding to short-duration heavy rainfall during the flood season.

[0042] After the regulation was initiated, the system's data acquisition module simultaneously collected data across the entire watershed, acquiring real-time hydrological parameters such as water levels at key regulation nodes, transit runoff, adjustable water volume, soil moisture content, and rainwater infiltration rate. Simultaneously, it collected real-time operational data from each unit across the entire hydrogen production-storage-hydrogen power generation chain, including power output, operating efficiency, adjustable capacity, and equipment start-up / shutdown status. During the acquisition process, a unified millisecond-level timestamp was added to all data. Based on these timestamps, time-series alignment of multi-source data was achieved. For single-dimensional data gaps during acquisition, nearest-time similarity interpolation was used for completion. For multi-dimensional data synchronization gaps caused by short-term signal interruptions, cross-completion was performed based on the established hydrological-energy parameter correlation, ensuring data integrity and temporal consistency throughout the process.

[0043] Based on aligned hydrological and energy operation data, the mapping module constructs a millisecond-level linkage mapping between hydrological dynamics and the output of multiple energy units. This mapping can synchronously characterize the real-time driving relationship between dynamic changes in hydrological conditions and the output of adjustable energy units, as well as the real-time correction relationship between the energy supply and demand gap in the basin and the output of adjustable energy units. During this heavy rainfall event, the cumulative rainfall in the upper reaches of the basin reached 42 mm within one hour, and the water level at the core regulation and storage node rose by 0.8 m compared to the baseline value. Through this linkage mapping, the system directly obtained the target values ​​for adjusting the output of hydropower and hydrogen production units to match the dynamic changes in hydrological conditions.

[0044] The configuration module, combining the hydrological regulation requirements of the sponge watershed with the actual operational characteristics of multiple energy units, completed the setting of constraints and adjustable boundary ranges for multi-energy flow coordinated regulation. Among these, the hydrological safety constraints clearly stipulate that the water level at the watershed's regulation and storage nodes must be controlled within the range of 32.0m to 36.0m, and the watershed's ecological baseflow must not be lower than 2.5m. The maximum flow rate for flood control and drainage shall not exceed 120. The energy operation constraints clearly define the upper and lower limits of output for each energy unit, the maximum ramp rate of the unit, the operating efficiency range of the hydrogen production unit, and the upper and lower limits of capacity for the hydrogen storage unit. The supply and demand balance constraints clearly define the real-time balance requirements between the system's real-time power generation output and the basin's electricity load and hydrogen production power consumption. Based on the above constraints, the system synchronously determines the maximum allowable adjustment range of the adjustable actions of each hydrological control unit and energy unit.

[0045] Based on the established linkage mapping, control constraints, and adjustable boundary range, the generation module generated a millisecond-level coordinated control strategy for wind, solar, hydro, and hydrogen multi-energy flow adapted to the current hydrological dynamics. This strategy aims to achieve optimal hydrological state tracking accuracy and the highest smoothness of energy unit adjustment actions. The final generated control strategy ensures that the water level at the storage nodes smoothly returns to the target range, while minimizing the adjustment frequency and action fluctuations of each energy unit, thus reducing equipment wear and tear.

[0046] The distribution module breaks down the generated collaborative control strategy into independent execution instructions for each hydrological control unit and each energy unit within each millisecond-level control step. It adds a corresponding execution time window and priority label to each instruction, with the control instructions for hydrological drainage gates and core storage facilities set as the highest priority. Then, through a preset low-latency transmission channel, all execution instructions with time windows are synchronously distributed to the corresponding execution units, and the end-to-end latency of the entire instruction transmission is controlled within 10ms.

[0047] The control module, based on a unified high-precision clock source, performs millisecond-level timing matching and control of the adjustment actions of all execution units, keeping the synchronization error of each unit's adjustment actions within 5ms. Simultaneously, it collects real-time feedback data from each execution unit's actions and compares it with the target value of the corresponding command. For hydropower units whose execution deviation exceeds a preset threshold, it issues real-time correction commands with deviation compensation to bring the output deviation back within the allowable range. During the control process, if the system detects that the adjustment action of a drainage sluice gate exceeds the preset adjustable boundary range, it immediately triggers an emergency lockout command, controlling the sluice gate to maintain its current safe operating state, and simultaneously pushes the abnormal information to the system's main control terminal until the abnormality is resolved and normal control resumes.

[0048] During this application, the system successfully kept the water level of the core water storage nodes in the basin within a safe range throughout the entire process, without any watershed flooding or flood control risks, and the ecological base flow of the basin met the requirements throughout the process; at the same time, it achieved a wind and solar new energy consumption rate of 98.7%, a hydrogen production unit operating efficiency of more than 68%, and controlled the energy supply and demand balance deviation of the entire system within 0.5%.

[0049] Although the present invention has been described in detail above with general descriptions, specific embodiments, and experiments, modifications or improvements can be made to it, which will be obvious to those skilled in the art. Therefore, all such modifications or improvements made without departing from the spirit of the present invention fall within the scope of protection claimed by the present invention.

Claims

1. A multi-energy flow coordinated regulation system based on sponge basins, characterized in that, Includes the following modules: The data acquisition module is used to synchronously acquire real-time parameters of hydrological processes and real-time operating status data of various energy units such as wind, solar, water and hydrogen within the sponge watershed, and to perform data alignment and interpolation to complete missing values. The mapping module is used to construct a millisecond-level linkage and correlation mapping that follows the dynamic process of hydrology and the output of multiple energy units based on the collected hydrological parameters and energy operation data. The setting module is used to set the constraints and adjustable boundary ranges of multi-energy flow coordinated regulation based on the requirements of sponge watershed hydrological regulation and the operating characteristics of multi-energy units. The generation module is used to apply linkage mapping, control constraints and boundaries to generate millisecond-level collaborative control strategies for wind, solar, water and hydrogen multi-energy flow that are adapted to hydrological dynamics. The distribution module is used to break down the generated coordinated control strategy into independent execution instructions corresponding to the hydrological control unit and each energy unit, and to distribute them synchronously to the corresponding execution units. The control module is used to perform millisecond-level timing matching and control of the control actions of the hydrological control unit and various energy units such as wind, solar, water and hydrogen, and to constrain the execution timing and synchronization accuracy of the control actions of each unit. The acquisition module is interactively connected to the mapping module via a wireless network. The mapping module is interactively connected to the setting module via a wireless network. The setting module is interactively connected to the generation module and the distribution module via a wireless network. The distribution module is interactively connected to the generation module via a wireless network. The generation module and the distribution module are interactively connected to the control module via a wireless network.

2. The wind-solar-hydro-hydrogen multi-energy flow coordinated regulation system based on sponge basins according to claim 1, characterized in that, The data acquisition module includes the following: Collect real-time hydrological parameters such as water level, runoff, adjustable water volume, soil moisture content, and infiltration rate within the sponge watershed; collect real-time operational status data of each unit in the entire chain of wind power, photovoltaic power, hydropower, hydrogen production-hydrogen storage-hydrogen power generation, including output power, operating efficiency, adjustable capacity, and start / stop status. Add a uniform millisecond-level timestamp to all collected parameters and data, and perform time-series alignment and missing value interpolation based on the timestamps.

3. The wind-solar-hydro-hydrogen multi-energy flow coordinated regulation system based on sponge basins according to claim 2, characterized in that, The missing value interpolation and completion is accomplished by the nearest-time similarity interpolation method based on the hydrological-energy coupling characteristics. The nearest-time similarity interpolation method is based on the effective data within a preset time period before and after the time of the missing value, extracts the coupling characteristic similarity of hydrological and energy parameters, selects effective data points with similarity that meet a preset threshold for weighted interpolation, and completes the completion of single-dimensional missing values. If it is a multi-dimensional synchronous missing value, cross-completion is performed based on the established hydrological-energy parameter correlation relationship. The preset threshold is determined by comprehensively considering the accuracy of hydrological and energy parameter acquisition, the stability of data time sequence, and the reliability of missing value completion.

4. The wind-solar-hydro-hydrogen multi-energy flow coordinated regulation system based on sponge basins according to claim 1, characterized in that, The mapping module describes the construction of a millisecond-level linkage mapping between hydrological dynamic processes and the output of multiple energy units, that is, the construction of a hydrological-energy parameter correlation relationship, which follows the function: ； In the formula: t represents the current real-time moment, in milliseconds; Let be the hydrological state vector at time t; Let t be the output / power consumption vector of the adjustable energy unit at time t; This is for the real-time power consumption of the hydrogen production unit; The hydrological-energy linkage coefficient matrix is ​​calibrated based on the characteristics of watershed regulation and hydropower units. The energy supply and demand matching coefficient matrix is ​​calibrated by combining the ramp rate and response characteristics of multiple energy units; Let t be the real-time total power load within the watershed at time t; Let t be the real-time total output of wind power and photovoltaic power. The , , The expression is: ； In the formula: Real-time water level at the core water storage nodes of the basin; Real-time transit runoff volume in the watershed; The real-time adjustable water storage volume of the basin; Provide real-time power output for the hydroelectric unit; This represents the real-time power consumption of the hydrogen production unit; T indicates the transpose symbol. , Provides real-time power output for wind and solar power units; The linkage mapping is used to characterize the real-time driving relationship between dynamic changes in hydrological conditions and the output of adjustable energy units, as well as the real-time correction relationship between energy supply and demand gaps and the output of adjustable energy units.

5. The wind-solar-hydro-hydrogen multi-energy flow coordinated regulation system based on sponge basins according to claim 1, characterized in that, The constraints for the multi-energy flow coordinated regulation described in the setting module include hydrological security constraints, energy operation constraints, and supply and demand balance constraints; The adjustable boundary range is the maximum allowable adjustment range of the adjustable actions of each hydrological control unit and each energy unit, determined based on the above constraints.

6. The wind-solar-hydro-hydrogen multi-energy flow coordinated regulation system based on sponge basins according to claim 5, characterized in that, The hydrological safety constraints include preset range constraints on water levels at water storage nodes in the basin, minimum threshold constraints on ecological base flow, and upper limit constraints on flood control and drainage flow. Energy operation constraints include upper and lower limits of output for each energy unit, unit ramp-up rate constraints, operating efficiency range constraints for hydrogen production units, and upper and lower limits of capacity constraints for hydrogen storage units. Supply and demand balance constraints include real-time balance constraints between the power generation output and power load of the entire system and the power consumption of hydrogen production.

7. The wind-solar-hydro-hydrogen multi-energy flow coordinated regulation system based on sponge basins according to claim 1, characterized in that, The generation module generates a millisecond-level collaborative regulation strategy for wind, solar, hydro, and hydrogen multi-energy flow adapted to hydrological dynamics, which follows the following optimization objective function: ； In the formula: The target value for optimizing the control strategy; This is the starting point of the control strategy; The preset control period for the control strategy; For integration time; for Hydrological state vector at any given time; The preset hydrological state target time series curve; To adjust the smoothness weighting coefficient; for The output / power consumption vector of the energy unit is adjustable in real time; It is the 2-norm of the vector; The The calibration is based on the equipment type of each adjustable energy unit, the preset maximum allowable ramp rate, and the preset annual allowable number of adjustments corresponding to the equipment design life; It characterizes the fluctuation of the adjustment rate of the output / power consumption of the adjustable energy unit. The smaller the value, the smoother the adjustment action of the energy unit. Among them, the optimization objective function simultaneously satisfies all the constraints set by the module operation, and the generated collaborative control strategy is the output timing curve of each adjustable unit that minimizes the optimization objective value.

8. The wind-solar-hydro-hydrogen multi-energy flow coordinated regulation system based on sponge basins according to claim 1, characterized in that, During the operation phase of the distribution module, the output timing curve corresponding to the coordinated control strategy is decomposed into independent execution instructions for each hydrological control unit and each energy unit within each millisecond-level control step. A corresponding execution time window and priority label are added to each independent execution instruction. Based on the preset low-latency transmission channel, all execution instructions with time windows are synchronously distributed to the corresponding execution units, so that the end-to-end delay of instruction transmission does not exceed the preset threshold. The preset threshold is determined by comprehensively considering the system's millisecond-level control requirements, the inherent response latency of each execution unit, the performance of the low-latency transmission channel, and the synchronization accuracy requirements of hydrological-energy coordinated control.

9. The wind-solar-hydro-hydrogen multi-energy flow coordinated regulation system based on sponge basins according to claim 1, characterized in that, The control module, based on a unified clock source, performs millisecond-level timing calibration on the execution actions of each execution unit to ensure that the synchronization error of the control actions of each unit does not exceed a preset threshold. It also collects the action execution feedback data of each execution unit in real time, compares it with the target value of the corresponding execution instruction, and issues correction instructions in real time to units whose execution deviation exceeds the preset threshold. Simultaneously, it identifies abnormal actions that exceed the adjustable boundary range during execution and immediately triggers an emergency lockout instruction. The preset threshold is comprehensively calibrated by the timing accuracy of the unified clock source, the millisecond-level control step size of the system, the synchronization accuracy requirements of hydrological-energy coordinated control, and the inherent action response delay of each execution unit. The correction instruction includes the target adjustment amount, execution time window, and deviation compensation coefficient of the corresponding unit within the current millisecond-level control step size; The emergency lockout command includes an action lockout identifier, a unit current operating status maintenance command, and an abnormal signal upload command. After the lockout is triggered, the abnormal information is pushed to the system master control terminal simultaneously until the master control terminal issues an unlocking command or the abnormality is cleared. Each unit continues to maintain the safe operating state at the time of lockout.

10. The wind-solar-hydro-hydrogen multi-energy flow coordinated regulation system based on sponge basins according to claim 9, characterized in that, The formula for calculating the deviation compensation coefficient is as follows: ； In the formula: This is the real-time deviation compensation coefficient for the corresponding execution unit; The preset maximum compensation coefficient is determined by comprehensively calibrating the rated ramp rate of each execution unit, the system's millisecond-level control step size, the over-adjustment suppression safety requirements, and the inherent response characteristics of the equipment. t represents the current real-time moment, in milliseconds; The real-time execution deviation value of the execution unit at time t is equal to the difference between the unit's current actual output / action value and the target value of the corresponding execution command. R is the real-time rate of change of the execution deviation at time t; R is the rated ramp rate of the execution unit, which is pre-calibrated based on the characteristics of the unit equipment and the field operation data, and the unit is power / millisecond or action amount / millisecond. The system is preset with a millisecond-level adjustment step size to meet the requirements. ≥ ; This is the inherent response delay of the execution unit, pre-calibrated from the unit's action response characteristics, and is expressed in milliseconds. The preset positive real number for zero-bias protection; The target adjustment amount is the inverse product of the deviation compensation coefficient and the real-time execution deviation value, that is, the target adjustment amount is .

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