Ship energy storage microgrid timing event triggering control method, terminal and storage medium
By constructing a system architecture model in a shipboard DC energy storage microgrid and introducing an adaptive virtual droop resistor, and by adopting a timed event-triggered control method, the problem of communication instability in the distributed control system was solved, the balanced regulation of the state of charge was achieved, and the control efficiency and energy utilization efficiency were improved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- YANSHAN UNIV
- Filing Date
- 2026-03-06
- Publication Date
- 2026-06-05
Smart Images
Figure CN122159164A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of power system control technology, and in particular to a timed event triggering control method, terminal and storage medium for a ship energy storage microgrid. Background Technology
[0002] With the continuous improvement of ship electrification and intelligence, ship power systems are gradually evolving from traditional AC power distribution structures to DC power distribution structures. Compared with AC systems, ship DC microgrids have significant advantages such as fewer power conversion stages, flexible energy management, high system efficiency, and ease of integrating new energy sources and energy storage devices. They have become an important development direction for modern electric propulsion ships, all-electric ships, and intelligent ships. Among these, energy storage units, as a key component of ship DC microgrids, play an irreplaceable role in smoothing load fluctuations, improving system dynamic performance, and ensuring power supply security.
[0003] In real-world shipboard operating environments, DC microgrids typically exhibit distributed and modular structural characteristics, requiring coordinated operation of various energy storage units and power electronic interfaces in the absence of centralized control. Therefore, distributed control strategies, due to their excellent scalability, robustness, and fault tolerance, have gradually become a research hotspot in shipboard DC energy storage microgrid control. However, distributed control relies on communication networks to achieve information exchange between nodes. Shipboard communication networks, constrained by complex electromagnetic environments, network bandwidth, and equipment reliability, often exhibit intermittent communication characteristics such as communication interruptions, latency variations, and data packet loss. These undesirable communication conditions significantly impact the stability and control performance of the distributed control system.
[0004] To reduce communication resource consumption and improve system efficiency in unreliable communication environments, event-triggered control methods have received widespread attention in recent years. Compared with traditional periodic sampling control, event-triggered control only transmits information and updates control when the system state meets specific triggering conditions, thus effectively reducing unnecessary communication burdens and computational overhead. However, pure event-triggered mechanisms may introduce Zeno behavior risks in engineering applications, and the uncertainty of their triggering timing also increases the difficulty of system implementation. Summary of the Invention
[0005] This application provides a timing event triggering control method, terminal, and storage medium for ship energy storage microgrids to solve the problems of the inability to converge the state of charge in traditional droop control and the slow convergence time of existing controllers.
[0006] Firstly, this application provides a method for triggering and controlling timed events in a ship energy storage microgrid, including: A system architecture model of a ship DC energy storage microgrid to be regulated is constructed, and an adaptive virtual droop resistor is constructed in the system architecture model; wherein, the ship DC energy storage microgrid to be regulated includes N distributed energy storage units, where N is a positive integer greater than or equal to 1, and each distributed energy storage unit corresponds to a unique adaptive virtual droop resistor; At the event triggering time that meets the triggering conditions, the average state of charge estimation value of each distributed energy storage unit in the ship DC energy storage microgrid to be controlled is calculated respectively, and the adaptive virtual droop resistance corresponding to each distributed energy storage unit is dynamically updated within a preset fixed time using the average state of charge estimation value of each distributed energy storage unit. The updated adaptive virtual droop resistor is input into the system architecture model to achieve balanced regulation of the state of charge of each distributed energy storage power source in the ship DC energy storage microgrid to be regulated.
[0007] In a second aspect, this application provides a terminal including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method as described in the first aspect or any possible implementation thereof.
[0008] Thirdly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method as described in the first aspect or any possible implementation thereof.
[0009] This application provides a timed event-triggered control method, terminal, and storage medium for a ship energy storage microgrid. By constructing a system architecture model of the DC energy storage microgrid to be controlled on the ship and introducing an adaptive virtual droop resistor, the system can be flexibly adjusted according to the actual operating conditions and energy storage needs of the ship. Each distributed energy storage unit corresponds to a unique adaptive virtual droop resistor, enabling personalized control based on the characteristics of different energy storage units, thus enhancing the system's adaptability to complex ship environments. Furthermore, the event-triggered control method, unlike traditional continuous-time control, only performs calculations and control operations at the event trigger moment when the triggering conditions are met, significantly reducing the computational load and communication burden during the control process, lowering system energy consumption, and improving control efficiency. Then, during event triggering... The system continuously calculates the average estimated state of charge (SOC) of each distributed energy storage unit and dynamically updates the resistance value of the corresponding adaptive virtual droop resistor using this average. This dynamic adjustment method based on the actual SOC more accurately reflects the energy state of each energy storage unit, thereby achieving balanced control of the SOC of each distributed energy storage power source. This avoids overcharging or over-discharging of some energy storage units due to unbalanced SOC, extending the service life of the energy storage units. At the same time, by achieving balanced control of the SOC of each distributed energy storage unit, it avoids situations where some energy storage units cannot fully utilize energy due to overcharging or over-discharging. This allows for a more rational allocation and utilization of energy in the entire ship's energy storage microgrid, thereby improving energy efficiency and reducing the ship's operating costs. Attached Figure Description
[0010] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0011] Figure 1 This is a flowchart illustrating the implementation of the timing event triggering control method for ship energy storage microgrids provided in this application embodiment; Figure 2 This is a schematic diagram of the system architecture model provided in the embodiments of this application; Figure 3 This is a schematic diagram of the state of charge effect of each distributed energy storage unit provided in the embodiments of this application; Figure 4 This is a schematic diagram illustrating the effect of estimating the average state of charge of each distributed energy storage unit provided in the embodiments of this application; Figure 5 This is a schematic diagram of the output current of each distributed energy storage unit provided in the embodiments of this application; Figure 6This is a schematic diagram of the output voltage of each distributed energy storage unit provided in the embodiments of this application; Figure 7 This is a schematic diagram of the timing event triggering of each distributed energy storage unit based on intermittent communication provided in the embodiments of this application; Figure 8 This is a schematic diagram showing the results of each distributed energy storage unit under a fixed-time control strategy provided in the embodiments of this application; Figure 9 This is a schematic diagram showing the results of each distributed energy storage unit under a finite-time control strategy provided in the embodiments of this application; Figure 10 This is a schematic diagram of the structure of the ship energy storage microgrid timing event triggering control device provided in the embodiments of this application; Figure 11 This is a schematic diagram of the terminal provided in the embodiments of this application. Detailed Implementation
[0012] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.
[0013] To make the objectives, technical solutions, and advantages of this application clearer, the following description will be provided in conjunction with the accompanying drawings and specific embodiments.
[0014] Figure 1 The implementation flowchart of the timing event triggering control method for ship energy storage microgrids provided in the embodiments of this application is described in detail below: In step 101, a system architecture model of the ship DC energy storage microgrid to be regulated is constructed, and an adaptive virtual droop resistor is constructed in the system architecture model; wherein, the ship DC energy storage microgrid to be regulated includes N distributed energy storage units (DESUs), where N is a positive integer greater than or equal to 1, and each distributed energy storage unit corresponds to a unique adaptive virtual droop resistor.
[0015] In this embodiment, based on the system architecture of the ship DC energy storage microgrid to be regulated, a system architecture model is constructed. The modeling and derivation of core components such as distributed energy storage units, bus connection lines, and power electronic interfaces in the microgrid are completed. The mathematical relationships between the electrical parameters of each component and the changes in their state of charge are clarified. The specific model structure is referenced... Figure 2 As shown, the modeling formula can be derived as follows:
[0016] in, For the first The state-of-charge derivative of a distributed energy storage unit. For the first The state-of-charge derivative of a distributed energy storage unit. For the first Distributed energy storage unit and bus Connect the direct connection cable group. For the first Adaptive virtual droop resistance of a distributed energy storage unit For the first Distributed energy storage unit and bus Connect the direct connection cable group. For the first Adaptive virtual droop resistance of a distributed energy storage unit For the first The battery capacity of each distributed energy storage unit, For the first Battery capacity of each distributed energy storage unit.
[0017] Since the state-of-charge equilibrium condition requires that the battery capacity and equivalent line impedance of each distributed energy storage unit be equal, this is an ideal condition. Therefore, the adaptive virtual droop resistance in the above formula should be adjusted. This is to achieve state-of-charge balance among distributed energy storage units.
[0018] Therefore, in order to overcome the shortcomings of traditional droop control, this application embodiment also designs a [system / mechanism] that... Adaptive virtual droop resistance related to state of charge Each distributed energy storage unit corresponds to a uniquely designed adaptive virtual droop resistance, which is dynamically adjusted. Achieve state-of-charge balance among distributed energy storage units. Specifically: When the distributed energy storage unit discharges: if the distributed energy storage unit If the state of charge of the distributed energy storage unit is smaller compared to the state of charge of other distributed energy storage units, then the distributed energy storage unit... The discharge current of this unit is smaller than that of other distributed energy storage units, which helps to mitigate the discharge rate, i.e., distributed energy storage units Adaptive virtual droop resistance The value needs to be increased; if the distributed energy storage unit If the state of charge of the distributed energy storage unit is larger than that of other distributed energy storage units, then the distributed energy storage unit... The discharge current of the distributed energy storage unit is larger than that of other distributed energy storage units to accelerate the discharge rate. Adaptive virtual droop resistance The value should be reduced; and among distributed energy storage units with different battery capacities, the distributed energy storage unit with a larger battery capacity should release more energy, i.e., the corresponding adaptive virtual droop resistance. To reduce this, distributed energy storage units with smaller battery capacities should release less energy, i.e., the corresponding adaptive virtual droop resistance should be reduced. The size needs to be increased. However, when the distributed energy storage unit is charging, the balancing strategy is the opposite of when the distributed energy storage unit is discharging.
[0019] In this embodiment, the expression for the adaptive virtual droop resistance is:
[0020] in, For the first The adaptive virtual droop resistance corresponding to each distributed energy storage unit. The initial droop resistance, For the balance coefficient, For accuracy parameters, For acceleration parameters, These are the initial numerical parameters. For the first The state of charge (SOC) value of each distributed energy storage unit. The average state of charge of the energy storage system. For the first The output current of each distributed energy storage unit, when When the distributed energy storage unit discharges, At that time, the distributed energy storage unit is charged.
[0021] The formula for calculating the initial droop resistance is as follows:
[0022] in, For the first The initial droop coefficient of each distributed energy storage unit This represents the maximum battery capacity of the energy storage system. For the first The battery capacity of each distributed energy storage unit, Let be the relative capacity factor of the i-th distributed energy storage unit.
[0023] This application's embodiments construct a system architecture model for a ship's DC energy storage microgrid to be regulated, and introduce an adaptive virtual droop resistor. This design enables the system to be flexibly adjusted according to the ship's actual operating conditions and energy storage needs. Each distributed energy storage unit corresponds to a unique adaptive virtual droop resistor, which can achieve personalized control based on the characteristics of different energy storage units, enhancing the system's adaptability to complex ship environments.
[0024] In step 102, at the event triggering time that meets the triggering conditions, the average state of charge estimation value of each distributed energy storage unit in the DC energy storage microgrid of the ship to be regulated is calculated, and the adaptive virtual droop resistance corresponding to each distributed energy storage unit is dynamically updated within a preset fixed time using the average state of charge estimation value of each distributed energy storage unit.
[0025] In this embodiment, at the event triggering time that satisfies the preset trigger function, based on an intermittent communication timing strategy, the average estimated state of charge (SOC) of each distributed energy storage unit in the ship's DC energy storage microgrid to be regulated is calculated using the self-measured values of each distributed energy storage unit at the event triggering time and the interaction data of adjacent units. This intermittent communication timing strategy does not require continuous communication between units; information exchange only occurs when the triggering condition is met, effectively saving communication resources in the complex electromagnetic environment of the ship. Then, using the average SOC of each distributed energy storage unit, combined with a preset fixed time for system stability, the resistance value of the adaptive virtual droop resistor corresponding to each distributed energy storage unit is dynamically updated. The convergence upper limit of the preset fixed time is only related to the system parameters and is not affected by the initial system values. This allows for adaptation to the stringent estimation time requirements and rapid interference recovery needs of the ship's microgrid by adjusting the controller parameters.
[0026] In this embodiment, an event-triggered control method is adopted, which differs from traditional continuous-time control. Calculation and control operations are performed only at the moment an event triggers when the triggering conditions are met. This significantly reduces the computational load and communication burden during the control process, lowers system energy consumption, and improves control efficiency. It is particularly suitable for ship energy storage microgrid systems with limited energy resources and high real-time requirements.
[0027] The formula for calculating the preset fixed time is as follows:
[0028] in, To preset a fixed time, Laplace matrix of communication topology The second smallest eigenvalue, In order to be with the first The number of adjacent distributed energy storage units that have communication connections. It is the ratio, that is, the ratio of two positive odd numbers; , These are all control gain coefficients, which can be any positive constant.
[0029] In one possible implementation, at the event triggering time that meets the triggering conditions, the average estimated state of charge of each distributed energy storage unit in the ship DC energy storage microgrid to be regulated is calculated, which may include: For each distributed energy storage unit, the following steps are performed: Calculate the trigger function for this distributed energy storage unit; If the triggering function meets the triggering condition, then at the time the event that meets the triggering condition is triggered, the mean estimated state of charge of the distributed energy storage unit is calculated.
[0030] Optionally, for each distributed energy storage unit in the ship's DC energy storage microgrid to be regulated, the following steps are performed independently to achieve accurate calculation of the mean estimated state of charge: First, based on the real-time operating status, communication topology parameters, and preset control parameters of the distributed energy storage unit, the trigger function corresponding to the distributed energy storage unit is calculated. The trigger function characterizes the matching relationship between the distributed energy storage unit's state deviation, communication interaction error, and trigger threshold, and is the core basis for determining whether an event is triggered.
[0031] Based on the communication topology, system control parameters, and real-time operating data of the distributed energy storage unit of the ship's DC energy storage microgrid to be regulated, the trigger function of the distributed energy storage unit is calculated using the first formula:
[0032]
[0033]
[0034]
[0035]
[0036] in, For the first Distributed energy storage units in The trigger function at a specific moment, for example, for an agent. In other words, when The event is triggered when the value is greater than or equal to 0, and the agent... The control mechanism is denoted as the specific moment when the event occurs. Refresh in real time, and at the same time, the intelligent agent It can obtain its most recent measurement value and neighboring data; For the first Distributed energy storage units in Accumulated state error at any given time. For the first Each distributed energy storage unit at the event trigger time The trigger threshold, For a moment, For the first The first distributed energy storage unit The timing of this event , These are all the serial numbers of distributed energy storage units. The first adjustment coefficient, This is the second adjustment coefficient. For trigger parameters, ; The ratio, For the first Each distributed energy storage unit at the event trigger time The error in the state of charge estimation, For symbolic functions, , , All are control gain coefficients. Laplace matrix of communication topology The largest eigenvalue, Let Lyapunov's function value be the value of the system at the initial moment. ,in, , , , , To estimate the error between the mean and average state of charge of the energy storage system at time 0, In order to be in The error between the mean estimated state of charge (SOC) of the energy storage system at any given time and the average SOC. To estimate the mean state of charge of the energy storage system, For the first The error between the mean estimated state of charge (SOC) of each distributed energy storage unit and the average SOC. To estimate the error between the mean and average state of charge of an energy storage system; In order to be with the first The number of adjacent distributed energy storage units that have communication connections. , These are all elements of the communication topology Laplace matrix. For the first Each distributed energy storage unit at the event trigger time The control input, For the first Each distributed energy storage unit at the event trigger time Control input.
[0037] Then, the calculated trigger function value The trigger value is compared with a preset trigger condition. In this embodiment, the preset trigger condition is greater than or equal to 0. Therefore, if the trigger function value is... If the value is greater than or equal to 0, it is determined that the distributed energy storage unit has reached the event triggering time. At the event triggering time that meets the triggering conditions, based on the intermittent communication timing strategy, combined with the distributed energy storage unit's own state of charge measurement value and the interaction data of adjacent communication units, the estimated mean value of the distributed energy storage unit's state of charge is accurately calculated.
[0038] Specifically, at the event triggering moment when the distributed energy storage unit meets the triggering conditions, based on the intermittent communication timing strategy and the distributed communication topology characteristics of the ship DC energy storage microgrid to be regulated, the average estimated state of charge of the distributed energy storage unit is calculated using the second formula, which is:
[0039]
[0040]
[0041] in, For the first The mean estimated state of charge of each distributed energy storage unit. For the first The state of charge (SOC) value of each distributed energy storage unit. For the first Distributed energy storage units at time The control input, Let the elements of the communication topology Laplace matrix be... The distributed energy storage unit for the first Each distributed energy storage unit can transmit information, then It equals 1, otherwise Equal to 0; In order to be with the first The number of adjacent distributed energy storage units that have communication connections. , These are all the serial numbers of distributed energy storage units. For a moment, For the first Each distributed energy storage unit at the event trigger time The error in the state of charge estimation, For the first The first distributed energy storage unit The timing of this event The ratio, , , All are control gain coefficients. For symbolic functions, For the first The mean estimated state of charge of each distributed energy storage unit.
[0042] If the trigger function does not meet the trigger condition, the mean value of the state of charge estimation will not be calculated, nor will the subsequent adaptive virtual droop resistance update operation be performed, until the trigger function meets the trigger condition.
[0043] To obtain the average state of charge (SOC) estimate of this distributed energy storage unit. Then, the mean is estimated using the state of charge. Update the average state of charge of the energy storage system in the above formula for calculating the adaptive virtual droop resistance. This allows for dynamic adjustment of the droop coefficient, thereby achieving balanced charge state and precise current distribution.
[0044] The average state-of-charge estimate of the distributed energy storage unit is input into the third formula to calculate the adaptive virtual droop resistance corresponding to the distributed energy storage unit. The third formula is as follows:
[0045] in, For the first The adaptive virtual droop resistance corresponding to each distributed energy storage unit. The initial droop resistance, For the balance coefficient, For accuracy parameters, For acceleration parameters, These are the initial numerical parameters. For the first The state of charge (SOC) value of each distributed energy storage unit. For the first The mean estimated state of charge of each distributed energy storage unit. For the first The output current of each distributed energy storage unit.
[0046] In step 103, the updated adaptive virtual droop resistor is input into the system architecture model to achieve balanced regulation of the state of charge of each distributed energy storage power source in the ship DC energy storage microgrid to be regulated.
[0047] In this embodiment, the updated resistance value of each adaptive virtual droop resistor is input into the system architecture model constructed in step 101. The charging and discharging current of each distributed energy storage unit is precisely controlled by dynamically adjusting the resistance value: during discharge, the discharge current of distributed energy storage units with low state of charge (SOC) values is reduced, and the discharge current of distributed energy storage units with high SOC values is increased. During charging, the opposite control logic is executed. At the same time, the corresponding resistance value is matched according to the battery capacity difference of the distributed energy storage units, so that the distributed energy storage units with large battery capacity release / absorb more energy and the distributed energy storage units with small battery capacity release / absorb less energy. In this way, the SOC balance control of each distributed energy storage unit in the controlled ship DC energy storage microgrid is achieved, the current distribution accuracy of distributed energy storage units with different capacities is improved, and the SOC of each distributed energy storage unit is quickly converged to a consistent state.
[0048] In one possible implementation, after inputting each updated adaptive virtual droop resistor into the system architecture model, the method may further include: Run the system architecture model of the DC energy storage microgrid on the ship to be regulated, and collect the actual bus voltage during operation; Determine whether the actual bus voltage is less than the rated bus voltage; If the actual bus voltage is less than the rated bus voltage, the output voltage reference value of the first distributed energy storage unit is calculated using the rated bus voltage, the output current of the first distributed energy storage unit, and the updated adaptive virtual droop resistance of the first distributed energy storage unit. The output voltage reference value is used to compensate the bus voltage of the first distributed energy storage unit. The first distributed energy storage unit is any distributed energy storage unit in the ship DC energy storage microgrid to be regulated.
[0049] Optionally, since the adaptive virtual droop resistor has a large selection range, the bus voltage may deviate from the rated value (generally less than the rated bus voltage). This application embodiment designs the following voltage compensation strategy to compensate the bus voltage. Specifically: After updating the adaptive virtual droop resistance, all resistance parameters are imported into the system architecture model of the DC energy storage microgrid on the ship to be regulated. This drives the system architecture model to run the entire process according to the actual electrical conditions and load conditions of the ship. During model operation, a preset voltage detection module continuously collects real-time electrical parameters of the microgrid bus, obtaining the actual bus voltage at different time points during operation, thus achieving real-time monitoring of the bus voltage status. The collected actual bus voltage is compared in real-time with the system's preset rated bus voltage to determine if the actual bus voltage is less than the rated bus voltage, thereby determining whether there is an undervoltage deviation and requiring compensation control. If the determination result is that the actual bus voltage is less than the rated bus voltage, i.e., there is an undervoltage deviation, then based on the voltage compensation control logic, the rated bus voltage, the output current of the first distributed energy storage unit, and the updated adaptive virtual droop resistance corresponding to the first distributed energy storage unit are input into the fourth formula to calculate the reference value of the output voltage of the first distributed energy storage unit. The fourth formula is:
[0050]
[0051] in, For the first The output voltage reference value of each distributed energy storage unit The rated voltage of the busbar For the first The output current of each distributed energy storage unit For the first The adaptive virtual droop resistance corresponding to each distributed energy storage unit. This is the voltage compensation amount. This is the proportionality coefficient. The integral coefficient is... For integration, For the first The estimated average bus voltage of a distributed energy storage unit.
[0052] The calculated output voltage reference value serves as the core control benchmark for bus voltage compensation of the distributed energy storage unit. It is used to specifically compensate and adjust the bus voltage at the connection point of the first distributed energy storage unit, thereby correcting undervoltage deviations. The first distributed energy storage unit can be any distributed energy storage unit in the ship's DC energy storage microgrid to be controlled. This compensation logic is adaptable to bus voltage compensation scenarios for all distributed energy storage units in the microgrid.
[0053] For example, suppose the DC energy storage microgrid on the ship to be regulated includes 6 distributed energy storage units, namely , , , , and This application was verified using simulation testing, and the verification results are as follows: Figure 3 This verifies that the adaptive virtual droop resistance regulation control based on the state of charge designed in this application can effectively regulate the state of charge of each distributed energy storage unit to be consistent. Figure 4 The intermittent communication timing strategy designed in this application has been verified to converge and continuously stabilize the mean value of the state of charge estimation within a fixed time period. Figure 5 The control strategy designed in this application has been verified to improve the current distribution accuracy of distributed energy storage units with different battery capacities and achieve state of charge balance. Figure 6 The control strategy designed in this application has been verified to ensure that the bus voltage is stable and the deviation is less than 0.5%. Figure 7 The intermittent communication event triggering method proposed in this application has been verified to avoid continuous communication and significantly reduce communication energy consumption. Figure 8 and Figure 9 The intermittent communication timing strategy designed in this application has been verified. The convergence time of the system is less affected by the initial value of the system, and the convergence time of the system is faster than that of the finite time strategy. The upper limit of the convergence time is only related to the system parameters and is not related to the initial value of the system.
[0054] This application provides a timed event-triggered control method for a ship energy storage microgrid. By constructing a system architecture model of the DC energy storage microgrid to be controlled on the ship and introducing an adaptive virtual droop resistor, the system can be flexibly adjusted according to the actual operating conditions and energy storage needs of the ship. Each distributed energy storage unit corresponds to a unique adaptive virtual droop resistor, enabling personalized control based on the characteristics of different energy storage units, thus enhancing the system's adaptability to complex ship environments. Furthermore, the event-triggered control method, unlike traditional continuous-time control, only performs calculations and control operations at the event triggering time when the triggering conditions are met, significantly reducing the computational load and communication burden during the control process, lowering system energy consumption, and improving control efficiency. Then, at the event triggering time, respectively... The average state of charge (SOC) estimate of each distributed energy storage unit is calculated, and this average is used to dynamically update the resistance value of the corresponding adaptive virtual droop resistor. This dynamic adjustment method based on the actual SOC more accurately reflects the energy state of each energy storage unit, thereby achieving balanced regulation of the SOC of each distributed energy storage power source. This avoids overcharging or over-discharging of some energy storage units due to unbalanced SOC, extending the service life of the energy storage units. At the same time, by achieving balanced regulation of the SOC of each distributed energy storage unit, it avoids situations where some energy storage units cannot fully utilize energy due to overcharging or over-discharging. This allows for a more rational allocation and utilization of energy in the entire ship energy storage microgrid, thereby improving energy efficiency and reducing the ship's operating costs.
[0055] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.
[0056] The following are device embodiments of this application. For details not described in detail, please refer to the corresponding method embodiments described above.
[0057] Figure 10 A schematic diagram of the timing event triggering control device for a ship energy storage microgrid provided in an embodiment of this application is shown. For ease of explanation, only the parts related to the embodiment of this application are shown, and are described in detail below: like Figure 10 As shown, the ship energy storage microgrid timing event triggering control device 10 includes: Module 1001 is used to construct a system architecture model of the DC energy storage microgrid to be regulated on the ship, and to construct an adaptive virtual droop resistor in the system architecture model; wherein, the DC energy storage microgrid to be regulated on the ship includes N distributed energy storage units, where N is a positive integer greater than or equal to 1, and each distributed energy storage unit corresponds to a unique adaptive virtual droop resistor. The calculation module 1002 is used to calculate the average state of charge estimation of each distributed energy storage unit in the DC energy storage microgrid of the ship to be regulated at the event triggering time that meets the triggering conditions, and to dynamically update the adaptive virtual droop resistance corresponding to each distributed energy storage unit within a preset fixed time using the average state of charge estimation of each distributed energy storage unit. The control module 1003 is used to input the updated adaptive virtual droop resistor into the system architecture model to achieve balanced regulation of the state of charge of each distributed energy storage power source in the ship DC energy storage microgrid to be regulated.
[0058] This application provides a timing event-triggered control device for a ship energy storage microgrid. By constructing a system architecture model of the DC energy storage microgrid to be controlled on the ship and introducing an adaptive virtual droop resistor, the system can be flexibly adjusted according to the actual operating conditions and energy storage needs of the ship. Each distributed energy storage unit corresponds to a unique adaptive virtual droop resistor, enabling personalized control based on the characteristics of different energy storage units, thus enhancing the system's adaptability to complex ship environments. Furthermore, the event-triggered control method, unlike traditional continuous-time control, only performs calculations and control operations at the event triggering time when the triggering conditions are met, significantly reducing the computational load and communication burden during the control process, lowering system energy consumption, and improving control efficiency. Then, at the event triggering time, respectively... The average state of charge (SOC) estimate of each distributed energy storage unit is calculated, and this average is used to dynamically update the resistance value of the corresponding adaptive virtual droop resistor. This dynamic adjustment method based on the actual SOC more accurately reflects the energy state of each energy storage unit, thereby achieving balanced regulation of the SOC of each distributed energy storage power source. This avoids overcharging or over-discharging of some energy storage units due to unbalanced SOC, extending the service life of the energy storage units. At the same time, by achieving balanced regulation of the SOC of each distributed energy storage unit, it avoids situations where some energy storage units cannot fully utilize energy due to overcharging or over-discharging. This allows for a more rational allocation and utilization of energy in the entire ship energy storage microgrid, thereby improving energy efficiency and reducing the ship's operating costs.
[0059] In one possible implementation, the computation module can be used for: For each distributed energy storage unit, the following steps are performed: Calculate the trigger function for this distributed energy storage unit; If the triggering function meets the triggering condition, then at the time the event that meets the triggering condition is triggered, the mean estimated state of charge of the distributed energy storage unit is calculated.
[0060] In one possible implementation, the computation module can be used for: The trigger function of the distributed energy storage unit is calculated using the first formula, which is:
[0061]
[0062]
[0063]
[0064]
[0065] in, For the first Distributed energy storage units in The trigger function at a given time. For the first Distributed energy storage units in Accumulated state error at any given time. For the first Each distributed energy storage unit at the event trigger time The trigger threshold, For a moment, For the first The first distributed energy storage unit The timing of this event , These are all the serial numbers of distributed energy storage units. The first adjustment coefficient, This is the second adjustment coefficient. For trigger parameters, The ratio, For the first Each distributed energy storage unit at the event trigger time The error in the state of charge estimation, For symbolic functions, , , All are control gain coefficients. Laplace matrix of communication topology The largest eigenvalue, Let Lyapunov's function value be the value of the system at the initial moment. In order to be with the first The number of adjacent distributed energy storage units that have communication connections. , These are all elements of the communication topology Laplace matrix. For the first Each distributed energy storage unit at the event trigger time The control input, For the first Each distributed energy storage unit at the event trigger time Control input.
[0066] In one possible implementation, the computation module can also be used for: The mean estimated state of charge of the distributed energy storage unit is calculated using the second formula, which is:
[0067]
[0068]
[0069] in, For the first The mean estimated state of charge of each distributed energy storage unit. For the first The state of charge (SOC) value of each distributed energy storage unit. For the first Distributed energy storage units at time The control input, The elements of the communication topology Laplace matrix, In order to be with the first The number of adjacent distributed energy storage units that have communication connections. , These are all the serial numbers of distributed energy storage units. For a moment, For the first Each distributed energy storage unit at the event trigger time The error in the state of charge estimation, For the first The first distributed energy storage unit The timing of this event The ratio, , , All are control gain coefficients. For symbolic functions, For the first The mean estimated state of charge of each distributed energy storage unit.
[0070] In one possible implementation, the computation module can also be used for: For each distributed energy storage unit, the average estimated state of charge of that unit is input into the third formula to calculate the adaptive virtual droop resistance corresponding to that unit. The third formula is as follows:
[0071] in, For the first The adaptive virtual droop resistance corresponding to each distributed energy storage unit. The initial droop resistance, For the balance coefficient, For accuracy parameters, For acceleration parameters, These are the initial numerical parameters. For the first The state of charge (SOC) value of each distributed energy storage unit. For the first The mean estimated state of charge of each distributed energy storage unit. For the first The output current of each distributed energy storage unit.
[0072] In one possible implementation, the formula for calculating the preset fixed time is:
[0073] in, To preset a fixed time, Laplace matrix of communication topology The second smallest eigenvalue, In order to be with the first The number of adjacent distributed energy storage units that have communication connections. The ratio, , All of these are control gain coefficients.
[0074] In one possible implementation, the device may further include a bus voltage compensation module, which can be used for: Run the system architecture model of the DC energy storage microgrid on the ship to be regulated, and collect the actual bus voltage during operation; Determine whether the actual bus voltage is less than the rated bus voltage; If the actual bus voltage is less than the rated bus voltage, the output voltage reference value of the first distributed energy storage unit is calculated using the rated bus voltage, the output current of the first distributed energy storage unit, and the updated adaptive virtual droop resistance of the first distributed energy storage unit. The output voltage reference value is used to compensate the bus voltage of the first distributed energy storage unit. The first distributed energy storage unit is any distributed energy storage unit in the ship DC energy storage microgrid to be regulated.
[0075] In one possible implementation, the bus voltage compensation module can also be used for: The rated bus voltage, the output current of the first distributed energy storage unit, and the updated adaptive virtual droop resistance corresponding to the first distributed energy storage unit are input into the fourth formula to calculate the reference value of the output voltage of the first distributed energy storage unit. The fourth formula is as follows:
[0076]
[0077] in, For the first The output voltage reference value of each distributed energy storage unit The rated voltage of the busbar For the first The output current of each distributed energy storage unit For the first The adaptive virtual droop resistance corresponding to each distributed energy storage unit. This is the voltage compensation amount. This is the proportionality coefficient. The integral coefficient is... For integration, For the first The estimated average bus voltage of a distributed energy storage unit.
[0078] Figure 11 This is a schematic diagram of the terminal provided in an embodiment of this application. For example... Figure 11 As shown, the terminal 11 in this embodiment includes: a processor 110, a memory 111, and a computer program 112 stored in the memory 111 and executable on the processor 110. When the processor 110 executes the computer program 112, it implements the steps in the various embodiments of the ship energy storage microgrid timing event triggering control method described above, for example... Figure 1 Steps 101 to 103 are shown. Alternatively, when the processor 110 executes the computer program 112, it implements the functions of each module / unit in the above-described device embodiments, for example... Figure 10 The functions of each module are shown.
[0079] For example, the computer program 112 can be divided into one or more modules / units, which are stored in the memory 111 and executed by the processor 110 to complete this application. The one or more modules / units can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 112 in the terminal 11. For example, the computer program 112 can be divided into... Figure 10 The modules shown.
[0080] The terminal 11 can be a computing device such as a desktop computer, laptop, handheld computer, or cloud server. The terminal 11 may include, but is not limited to, a processor 110 and a memory 111. Those skilled in the art will understand that... Figure 11This is merely an example of terminal 11 and does not constitute a limitation on terminal 11. It may include more or fewer components than shown, or combine certain components, or different components. For example, the terminal may also include input / output devices, network access devices, buses, etc.
[0081] The processor 110 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.
[0082] The memory 111 can be an internal storage unit of the terminal 11, such as a hard disk or memory of the terminal 11. The memory 111 can also be an external storage device of the terminal 11, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the terminal 11. Furthermore, the memory 111 can include both internal storage units and external storage devices of the terminal 11. The memory 111 is used to store the computer program and other programs and data required by the terminal. The memory 111 can also be used to temporarily store data that has been output or will be output.
[0083] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.
[0084] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.
[0085] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0086] In the embodiments provided in this application, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling or direct coupling or communication connection may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.
[0087] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0088] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.
[0089] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above-described embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium. When executed by a processor, the computer program can implement the steps of the various ship energy storage microgrid timing event triggering control method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.
[0090] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.
Claims
1. A method for triggering control of timed events in a ship energy storage microgrid, characterized in that, include: A system architecture model of a ship DC energy storage microgrid to be regulated is constructed, and an adaptive virtual droop resistor is constructed in the system architecture model; wherein, the ship DC energy storage microgrid to be regulated includes N distributed energy storage units, where N is a positive integer greater than or equal to 1, and each distributed energy storage unit corresponds to a unique adaptive virtual droop resistor; At the event triggering time that meets the triggering conditions, the average state of charge estimation value of each distributed energy storage unit in the ship DC energy storage microgrid to be controlled is calculated respectively, and the adaptive virtual droop resistance corresponding to each distributed energy storage unit is dynamically updated within a preset fixed time using the average state of charge estimation value of each distributed energy storage unit. The updated adaptive virtual droop resistor is input into the system architecture model to achieve balanced regulation of the state of charge of each distributed energy storage power source in the ship DC energy storage microgrid to be regulated.
2. The method for triggering and controlling timed events in a ship energy storage microgrid according to claim 1, characterized in that, At the event triggering time that meets the triggering conditions, the average estimated state of charge of each distributed energy storage unit in the ship DC energy storage microgrid to be regulated is calculated, including: For each distributed energy storage unit, the following steps are performed: Calculate the trigger function for this distributed energy storage unit; If the triggering function satisfies the triggering condition, then at the time the event that satisfies the triggering condition is triggered, the mean estimated state of charge of the distributed energy storage unit is calculated.
3. The method for triggering and controlling timed events in a ship energy storage microgrid according to claim 2, characterized in that, The trigger function for calculating the distributed energy storage unit includes: The trigger function of the distributed energy storage unit is calculated using the first formula, which is: in, For the first Distributed energy storage units in The trigger function at a given time. For the first Distributed energy storage units in Accumulated state error at any given time. For the first Each distributed energy storage unit at the event trigger time The trigger threshold, For a moment, For the first The first distributed energy storage unit The timing of this event , These are all the serial numbers of distributed energy storage units. The first adjustment coefficient, This is the second adjustment coefficient. For trigger parameters, The ratio, For the first Each distributed energy storage unit at the event trigger time The error in the state of charge estimation, For symbolic functions, , , All are control gain coefficients. Laplace matrix of communication topology The largest eigenvalue, Let Lyapunov's function value be the value of the system at the initial moment. In order to be with the first The number of adjacent distributed energy storage units that have communication connections. , These are all elements of the communication topology Laplace matrix. For the first Each distributed energy storage unit at the event trigger time The control input, For the first Each distributed energy storage unit at the event trigger time Control input.
4. The method for triggering and controlling timed events in a ship energy storage microgrid according to claim 2, characterized in that, The calculation of the mean estimated state of charge of the distributed energy storage unit includes: The mean estimated state of charge of the distributed energy storage unit is calculated using the second formula, which is: in, For the first The mean estimated state of charge of each distributed energy storage unit. For the first The state of charge (SOC) value of each distributed energy storage unit. For the first Distributed energy storage units at time The control input, The elements of the communication topology Laplace matrix, In order to be with the first The number of adjacent distributed energy storage units that have communication connections. , These are all the serial numbers of distributed energy storage units. For a moment, For the first Each distributed energy storage unit at the event trigger time The error in the state of charge estimation, For the first The first distributed energy storage unit The timing of this event The ratio, , , All are control gain coefficients. For symbolic functions, For the first The mean estimated state of charge of each distributed energy storage unit.
5. The method for triggering and controlling timed events in a ship energy storage microgrid according to claim 1, characterized in that, The step of estimating the average state of charge of each distributed energy storage unit and dynamically updating the adaptive virtual droop resistance of each distributed energy storage unit within a preset fixed time period includes: For each distributed energy storage unit, the average estimated state of charge of that distributed energy storage unit is input into the third formula to calculate the adaptive virtual droop resistance corresponding to that distributed energy storage unit. The third formula is as follows: in, For the first The adaptive virtual droop resistance corresponding to each distributed energy storage unit. The initial droop resistance, For the balance coefficient, For accuracy parameters, For acceleration parameters, These are the initial numerical parameters. For the first The state of charge (SOC) value of each distributed energy storage unit. For the first The mean estimated state of charge of each distributed energy storage unit. For the first The output current of each distributed energy storage unit.
6. The method for triggering and controlling timed events in a ship energy storage microgrid according to claim 1, characterized in that, The formula for calculating the preset fixed time is: in, For the preset fixed time, Laplace matrix of communication topology The second smallest eigenvalue, In order to be with the first The number of adjacent distributed energy storage units that have communication connections. The ratio, , All of these are control gain coefficients.
7. The method for triggering and controlling timed events in a ship energy storage microgrid according to claim 1, characterized in that, After inputting each updated adaptive virtual droop resistor into the system architecture model, the method further includes: Run the system architecture model of the ship DC energy storage microgrid to be regulated, and collect the actual bus voltage during operation; Determine whether the actual bus voltage is less than the rated bus voltage; If the actual bus voltage is less than the rated bus voltage, the output voltage reference value of the first distributed energy storage unit is calculated using the rated bus voltage, the output current of the first distributed energy storage unit, and the updated adaptive virtual droop resistance corresponding to the first distributed energy storage unit. The output voltage reference value is used to compensate the bus voltage of the first distributed energy storage unit. The first distributed energy storage unit is any distributed energy storage unit in the ship DC energy storage microgrid to be regulated.
8. The method for triggering and controlling timed events in a ship energy storage microgrid according to claim 7, characterized in that, The step of calculating the output voltage reference value of the first distributed energy storage unit using the rated voltage of the bus, the output current of the first distributed energy storage unit, and the updated adaptive virtual droop resistance corresponding to the first distributed energy storage unit includes: The rated voltage of the bus, the output current of the first distributed energy storage unit, and the updated adaptive virtual droop resistance corresponding to the first distributed energy storage unit are input into the fourth formula to calculate the reference value of the output voltage of the first distributed energy storage unit. The fourth formula is as follows: in, For the first The output voltage reference value of each distributed energy storage unit The rated voltage of the busbar, For the first The output current of each distributed energy storage unit For the first The adaptive virtual droop resistance corresponding to each distributed energy storage unit. This is the voltage compensation amount. This is the proportionality coefficient. The integral coefficient is... For integration, For the first The estimated average bus voltage of a distributed energy storage unit.
9. A terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the ship energy storage microgrid timing event triggering control method as described in any one of claims 1 to 8.
10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the ship energy storage microgrid timing event triggering control method as described in any one of claims 1 to 8.