A direct current micro-grid multi-energy storage equalization control method and device based on residual available energy

Abstract

The application provides a DC micro-grid multi-energy storage equalization control method and device based on residual available energy, relates to the technical field of DC micro-grid operation control, and comprises the following steps: S1, collecting the operation state information of the DC micro-grid in real time; S2, calculating the residual available energy of each energy storage unit; S3, generating a dynamic RAE reference value based on a communication network and an adaptive consistency algorithm; S4, calculating a normalized RAE deviation; S5, correcting the droop coefficient according to the RAE deviation to realize adaptive distribution of the power of the multi-energy storage branch; S6, introducing bus voltage compensation control to correct the bus voltage deviation caused by the droop control; S7, generating a battery-side current reference value through a voltage outer loop; S8, realizing the fast execution of a bidirectional DC / DC converter by adopting model predictive current control; and S9, judging the system operation state and cyclically updating the control instruction. The method can realize the residual available energy equalization of the multi-energy storage unit, the DC bus voltage recovery and the fast tracking of the energy storage branch current.

Description

Technical Field

[0001] This application relates to the field of DC microgrid operation control technology, and more specifically, to a method and device for multi-energy storage balancing control of DC microgrids based on remaining available energy. Background Technology

[0002] In DC microgrids containing distributed power sources such as photovoltaic power generation, multiple battery energy storage systems are typically configured to mitigate the randomness and volatility of renewable energy output. The rational distribution of power among energy storage units and the stability of the bus voltage are key issues in DC microgrids. Among the many control methods for microgrids, droop control is widely used in DC microgrid control due to its advantages such as plug-and-play functionality, no communication link required, and high redundancy. However, the droop coefficient of traditional droop control is usually fixed, and each energy storage unit is charged and discharged according to a fixed ratio. Some batteries may prematurely exit operation due to overcharging or over-discharging, significantly reducing battery utilization.

[0003] To address the aforementioned issues, existing technologies have proposed an improved droop control method based on State of Charge (SOC). This method establishes a relationship between droop control and the SOC of the energy storage units, making the droop coefficient related to SOC. By controlling the output current balance, it achieves SOC equilibrium among the energy storage units. However, while the aforementioned SOC-based balancing control method can achieve a certain degree of power distribution, SOC balancing, and bus voltage stability, it still suffers from the following problems: 1. State of Charge (SOC) only reflects the ratio of the battery's current remaining capacity to its rated capacity, and cannot fully reflect the actual usable energy of different energy storage units. When the rated capacity, battery health status, or internal resistance characteristics of multiple energy storage units are inconsistent, even if the SOC of each energy storage unit is the same, the actual energy that can be released or absorbed may differ. Therefore, using SOC alone as a balancing indicator may misjudge the true energy state among multiple energy storage units.

[0004] 2. Existing SOC balancing control methods typically assume that all energy storage units have the same capacity, similar aging levels, or minimal differences in battery parameters. In actual engineering, multiple energy storage units may gradually develop inconsistencies in capacity and internal resistance due to differences in manufacturing, operating temperature, cycle count, and aging levels. In this situation, if a single SOC index is still used for balancing control, the SOC curves may converge, but the actual energy utilization may not be balanced, making it difficult to guarantee the energy state balance and lifespan coordination of multiple energy storage units during long-term operation.

[0005] 3. Some existing equalization control methods rely on a centralized controller to calculate the global average SOC or a unified reference value. While this approach is simple to implement, it requires centralized collection of status information from all energy storage units, with a central controller generating control commands. If the central controller or communication link fails, the system's equalization control performance will significantly degrade. Furthermore, as the number of energy storage units increases, the communication load and computational burden also rise with centralized control, hindering the expansion and distributed operation of multi-energy storage systems.

[0006] 4. Traditional droop control essentially achieves power distribution by introducing virtual impedance, which can easily cause the DC bus voltage to deviate from the rated value. Under conditions such as sudden load changes or photovoltaic output fluctuations, if the underlying current control still adopts the traditional PI inner loop, the tracking speed of the energy storage branch current to the power distribution command is limited, which may affect the dynamic response performance of the system and the recovery speed of the bus voltage. Summary of the Invention

[0007] The embodiments of this application provide a method and device for multi-energy storage balance control of DC microgrid based on residual available energy. This method uses residual available energy (RAE) as the balance index, generates distributed RAE reference values ​​through an adaptive consensus algorithm, and combines dynamic droop correction, distributed voltage compensation and model predictive current control to achieve energy state balance of multiple energy storage units, bus voltage recovery and fast current tracking.

[0008] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.

[0009] According to a first aspect of the embodiments of this application, a multi-energy storage balancing control method for a DC microgrid based on remaining available energy is provided, comprising: Real-time acquisition of DC microgrid operating status information, including energy storage unit state of charge, rated voltage, rated capacity, energy storage unit output current, energy storage unit output voltage, converter output current, local sampling bus voltage, and bidirectional DC / DC converter output current limit value; Calculate the remaining usable energy of each energy storage unit; Based on the remaining available energy of the energy storage unit itself and the remaining available energy of adjacent energy storage units, an adaptive algorithm is used to generate a dynamic reference value of remaining available energy. The normalized remaining available energy deviation of the energy storage unit is calculated based on the dynamic remaining available energy reference value; The droop coefficient is corrected based on the normalized remaining available energy deviation, and power allocation is controlled based on the corrected droop coefficient. A bus voltage compensation mechanism is introduced to correct the bus voltage deviation caused by droop control. Based on the bus voltage deviation, a battery-side current reference value is generated using a voltage outer loop controller; Based on the battery-side current reference value, a finite set model is used to predict the current generation control command; Determine the operating status of the DC microgrid and cyclically update the control commands.

[0010] In some embodiments of this application, based on the foregoing scheme, calculating the remaining usable energy of each energy storage unit includes: Calculate the first... based on the current charging and discharging direction of the energy storage unit. The remaining usable energy of each energy storage unit : ; in, For the first The current on the battery side of each energy storage unit is specified, and the discharge time of the battery to the DC bus is also specified. ; For the first The state of charge of each energy storage unit; Indicates the minimum state of charge. Indicates the maximum state of charge; Indicates the first The rated total energy of each energy storage unit.

[0011] In some embodiments of this application, based on the foregoing scheme, the step of generating a dynamic remaining available energy reference value using an adaptive algorithm based on the remaining available energy of the energy storage unit itself and the remaining available energy of adjacent energy storage units includes: Each energy storage unit communicates with adjacent energy storage units to exchange local reference status information of remaining available energy. Each energy storage unit updates its dynamic remaining available energy reference value based on the remaining available energy reference state information of adjacent energy storage units and its own remaining available energy, using an adaptive consistency adjustment rule.

[0012] In some embodiments of this application, based on the foregoing scheme, the calculation formula for the normalized remaining available energy deviation is as follows: ; in, For the first Normalized residual available energy deviation of the energy storage unit group; For the first The remaining usable energy of each energy storage unit; This is a reference value for the dynamic remaining available energy. This represents the smallest positive number that prevents the denominator from being zero.

[0013] In some embodiments of this application, based on the foregoing scheme, the step of correcting the droop coefficient according to the normalized remaining available energy deviation includes: Combining the current dead zone debouncing logic within the actual operating range, and considering the remaining available energy deviation, the first... Dynamic droop coefficient of each energy storage unit for: ; in, Indicates the base sag coefficient. This represents the adjustment weight of the arctangent function. For the converter output current, This indicates the set dead zone current threshold.

[0014] In some embodiments of this application, based on the foregoing scheme, the power allocation control based on the modified droop coefficient includes: When the remaining usable energy of a certain energy storage unit is higher than its dynamic remaining usable energy reference value, the droop coefficient of the certain energy storage unit is reduced or the power sharing capacity of the certain energy storage unit is increased, so that the energy storage unit can bear more discharge power in the discharge state or bear more charging absorption power in the charging state. When the remaining usable energy of a certain energy storage unit is lower than its dynamic remaining usable energy reference value, the droop coefficient of the certain energy storage unit is increased or the power sharing capacity of the certain energy storage unit is reduced, so that the energy storage unit reduces the discharge power in the discharge state or reduces the charging absorption power in the charging state.

[0015] In some embodiments of this application, based on the foregoing scheme, the introduction of a bus voltage compensation mechanism to correct the bus voltage deviation caused by droop control includes: The energy storage unit collects the bus voltage through the local controller and exchanges voltage observation information with adjacent energy storage units to obtain the compensation amount for voltage recovery. The compensation amount and the dynamic droop voltage drop term are applied together to the local reference voltage to generate the corrected voltage reference value for the energy storage unit.

[0016] In some embodiments of this application, based on the foregoing scheme, generating a battery-side current reference value using a voltage outer loop controller based on the bus voltage deviation includes: The corrected voltage reference value is compared with the actual sampled bus voltage to obtain the voltage error; The voltage error is then input into the outer voltage loop controller, which generates a corresponding battery-side current reference value based on the voltage error.

[0017] In some embodiments of this application, based on the foregoing scheme, the step of predicting the current generation control command using a finite set model based on the battery-side current reference value includes: The controller uses a finite set model to predict the current value at the next moment or after multiple steps under different switching states based on the current battery-side current reference value, battery terminal voltage, DC bus voltage and filter inductor parameters, and calculates the error between the predicted current and the reference current. Then, the switching state with the smallest error is selected as the optimal control output to drive the bidirectional DC / DC converter, enabling the energy storage branch current to quickly track the reference value.

[0018] According to a second aspect of the embodiments of this application, a multi-energy storage balancing control device for a DC microgrid based on remaining available energy is provided, comprising: The data acquisition unit is used to collect real-time operating status information of the DC microgrid, including the state of charge, rated voltage, rated capacity, output current, output voltage, converter output current, local sampling bus voltage, and output current limit value of the bidirectional DC / DC converter of the energy storage unit. The first computing unit is used to calculate the remaining available energy of each energy storage unit; The first generation unit is used to generate a dynamic reference value of remaining available energy based on the remaining available energy of the energy storage unit itself and the remaining available energy of adjacent energy storage units using an adaptive algorithm. The second calculation unit is used to calculate the normalized remaining available energy deviation of the energy storage unit based on the dynamic remaining available energy reference value; The first correction unit is used to correct the droop coefficient according to the normalized remaining available energy deviation, and to control the power distribution based on the corrected droop coefficient. The second correction unit is used to introduce a bus voltage compensation mechanism to correct the bus voltage deviation caused by droop control. The second generation unit is used to generate a battery-side current reference value based on the bus voltage deviation using a voltage outer loop controller. The prediction unit is used to predict the current generation control command based on the battery-side current reference value using a finite set model. The cyclic update unit is used to determine the operating status of the DC microgrid and cyclically update the control commands.

[0019] The technical solution of this application has the following beneficial effects: 1. Improve the accuracy of state balancing of multiple energy storage units.

[0020] This invention uses Remaining Available Energy (RAE) as a balancing index for multiple energy storage units. Compared with balancing methods based solely on State of Charge (SOC), this invention can further reflect the differences in actual available energy caused by differences in rated capacity, SOC operating boundary, and aging state among different energy storage units. This avoids the problem of inconsistent actual energy states even when SOC is the same, thereby improving the accuracy of multi-energy storage state balancing judgment.

[0021] 2. Improve the rationality of power distribution under heterogeneous energy storage conditions.

[0022] This invention dynamically adjusts the droop coefficient based on the deviation of the remaining usable energy of each energy storage unit, thus relating the charging and discharging power allocation of the energy storage units to their actual energy state. Therefore, when energy storage units have inconsistent capacities, different initial SOCs, or different degrees of aging, in the discharge state, energy storage units with higher remaining releaseable energy undertake more discharge power; in the charging state, energy storage units with larger remaining absorbable energy space undertake more charging power, thereby improving the rationality of power allocation among multiple energy storage units.

[0023] 3. Improve distributed load balancing control capabilities and system scalability.

[0024] This invention employs a dynamic RAE reference generation method based on neighboring node communication. Each energy storage unit does not need to rely on a centralized controller to calculate the global average SOC or a unified reference value; it can obtain its local RAE reference value simply through information exchange with neighboring nodes. Therefore, it can reduce the dependence on a single centralized controller and global communication link, and improve the system's distributed operation capability, fault tolerance, and scalability.

[0025] 4. Reduce control jitter during dynamic droop adjustment.

[0026] This invention introduces dead zone protection for energy storage branch current and droop coefficient limiting protection during the dynamic droop coefficient correction process. When the energy storage branch current is near zero power exchange, dynamic droop correction can be paused or the base droop coefficient can be maintained, thereby reducing droop coefficient fluctuations caused by frequent switching of charging and discharging states. At the same time, limiting protection prevents the droop coefficient from being too large or too small, improving the stability of the control process and engineering feasibility. 5. Reduce DC bus voltage deviation.

[0027] This invention employs a distributed uniform voltage observer combined with PI voltage compensation to compensate for the bus voltage deviation caused by traditional droop control while maintaining power coordination among multiple energy storage units. This allows the DC bus voltage to recover to near its rated value, thereby improving the stability of the DC bus voltage and the operational quality of the DC microgrid.

[0028] 6. Improve the system's dynamic response capability.

[0029] This invention employs a current model predictive control method at the bottom layer of the energy storage bidirectional DC / DC converter. Based on the current reference value, battery voltage, bus voltage, and real-time current state, it predicts the current change under different candidate switching states and selects the switching state with the smaller current tracking error as the control output. This is beneficial to improving the tracking speed of the energy storage branch current to the reference value and the dynamic response performance under load disturbance and photovoltaic fluctuation conditions.

[0030] 7. It is easy to implement on existing DC microgrid hardware structures.

[0031] This invention does not require changes to the basic hardware structure of a DC microgrid and can be implemented on existing photovoltaic power generation units, DC buses, multiple energy storage parallel units, and bidirectional DC / DC converter control frameworks. The method mainly achieves energy balancing across multiple energy storage units, bus voltage compensation, and rapid tracking of the underlying current through improved control algorithms, demonstrating good engineering applicability.

[0032] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0033] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings: Figure 1 A schematic diagram of a DC microgrid system according to an embodiment of this application is shown; Figure 2 A flowchart illustrating a multi-energy storage balancing control method for a DC microgrid based on remaining available energy, according to an embodiment of this application, is shown. Figure 3 A block diagram of a DC microgrid multi-energy storage equalization control device based on remaining available energy, according to one embodiment of this application, is shown. Figure 4 A block diagram of an electronic device according to one embodiment of this application is shown; Figure 5 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown. Detailed Implementation

[0034] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this application more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art.

[0035] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0036] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0037] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0038] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such uses of these terms can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described.

[0039] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0040] The following detailed description of some embodiments of this application will be provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0041] To address the shortcomings of existing multi-energy storage equalization control methods for DC microgrids, this application provides a multi-energy storage equalization control method for DC microgrids based on remaining available energy, specifically solving the following technical problems: 1. Solves the problem that traditional fixed droop control cannot dynamically allocate power according to the actual energy state of the energy storage unit.

[0042] Existing traditional droop control typically uses a fixed droop coefficient, with each energy storage unit participating in charging and discharging according to a fixed ratio. This makes it difficult to dynamically adjust the output based on the real-time energy status of different energy storage units, which can easily lead to some energy storage units being overcharged, over-discharged, or prematurely shutting down.

[0043] 2. To address the problem that it is difficult to accurately characterize the actual usable energy of an energy storage unit when using only SOC as a balance indicator.

[0044] Existing SOC-based equalization control methods mainly allocate power based on the proportion of remaining battery capacity. However, when there are differences in rated capacity, aging degree, or available energy boundary among energy storage units, the same SOC does not represent the same actual release or absorption energy space, which can easily lead to inaccurate equalization judgment.

[0045] 3. Addressing the challenge of achieving true energy balance in heterogeneous energy storage units with inconsistent capacities. In scenarios involving multiple energy storage units operating in parallel, inconsistencies in capacity, internal resistance, and available energy may arise due to differences in manufacturing processes, operating temperatures, cycle counts, and aging levels. Existing SOC balancing methods may result in SOC curves converging but actual available energy remaining uneven, making it difficult to guarantee energy state coordination across multiple energy storage units during long-term operation.

[0046] 4. Solve the problem that centralized equilibrium control relies heavily on global information and the central controller.

[0047] Some existing equalization control methods require centralized collection of status information from all energy storage units, with the central controller calculating the global average SOC or a unified reference value. When the central controller or critical communication links fail, the system's equalization control performance will significantly degrade. Furthermore, as the number of energy storage units increases, the communication pressure and computational burden of centralized control methods also increase, hindering system scalability.

[0048] 5. Solve the problem of DC bus voltage deviation caused by traditional droop control.

[0049] Traditional droop control achieves power distribution by introducing virtual impedance, which can easily cause the DC bus voltage to deviate from its rated value, affecting the power quality and operational stability of the DC microgrid. Therefore, it is necessary to consider both energy storage unit power distribution and bus voltage recovery during the equalization control process.

[0050] 6. Solve the problem of insufficient current response speed of energy storage branches when there are sudden load changes or fluctuations in photovoltaic output.

[0051] Under conditions of photovoltaic power fluctuations or sudden load changes, energy storage units need to respond quickly to power shortages or surpluses. The limited dynamic response speed of the traditional PI current inner loop may result in the energy storage branch current not tracking the reference command quickly enough, thus affecting the system's transient performance and bus voltage stability.

[0052] This application provides a multi-energy storage balancing control method for DC microgrids based on remaining available energy, applicable to DC microgrid systems containing multiple energy storage units, bidirectional DC / DC converters, DC buses, loads, and hierarchical controllers. The multiple energy storage units are connected in parallel to the DC bus via corresponding bidirectional DC / DC converters. Each energy storage branch is equipped with voltage, current, and state-of-charge acquisition modules. The control system includes an upper-level remaining available energy balancing control layer, a middle-level bus voltage compensation control layer, and a lower-level model-predicted current control layer. This method calculates the remaining available energy of each energy storage unit in real time, constructs a consistent reference update mechanism based on a communication network, and incorporates the remaining available energy deviation into droop control and voltage compensation control, thereby achieving energy balancing, bus voltage stability, and coordinated distribution of branch currents during the charging and discharging processes of multiple energy storage units.

[0053] For example, see Figure 1 The diagram shows a schematic representation of a DC microgrid system according to an embodiment of this application.

[0054] like Figure 1 The diagram illustrates the connections between photovoltaic (PV) power generation units, PV-side DC / DC converters, DC buses, load units, and parallel energy storage units. Each energy storage unit is connected to the DC bus via a bidirectional DC / DC converter, and its charging and discharging are controlled by a corresponding controller. Typically, in a DC microgrid, if the connected load exceeds the PV output, multiple energy storage units will discharge to fill the power deficit in the system; if the load is less than the PV output, the energy storage units will charge to absorb the system's power surplus.

[0055] See Figure 2 The diagram shows a flowchart of a multi-energy storage balancing control method for a DC microgrid based on remaining available energy, according to an embodiment of this application.

[0056] like Figure 2As shown, a method for balancing multiple energy storage in a DC microgrid based on remaining available energy is demonstrated, specifically including steps S100 to S900.

[0057] refer to Figure 2 Step S100: Real-time acquisition of DC microgrid operating status information, including the state of charge, rated voltage, rated capacity, energy storage unit output current, energy storage unit output voltage, converter output current, local sampling bus voltage, and output current limit value of bidirectional DC / DC converter.

[0058] It should be noted that in practical applications, this data acquisition step S100 is performed during the operation of the DC microgrid system.

[0059] Continue to refer to Figure 2 Step S200: Calculate the remaining available energy of each energy storage unit.

[0060] In some feasible embodiments, based on the foregoing scheme, the calculation of the remaining available energy of each energy storage unit includes: Calculate the first... based on the current charging and discharging direction of the energy storage unit. The remaining usable energy of each energy storage unit : ; in, For the first The current on the battery side of each energy storage unit is specified, and the discharge time of the battery to the DC bus is also specified. ; For the first The state of charge of each energy storage unit; Indicates the minimum state of charge. Indicates the maximum state of charge. Indicates the first The rated total energy of each energy storage unit.

[0061] Here is an example of how to calculate remaining available energy: Let the first The current state of charge of each energy storage unit is Rated voltage is Rated capacity is The minimum and maximum permissible states of charge are respectively and , No. Each energy storage unit outputs current .in, This indicates that the energy storage unit is in a discharging state. The rated total energy of the energy storage unit is defined. for: ; in, The unit can be Wh. Based on the current charging and discharging direction of the energy storage unit, the first... The remaining usable energy of each energy storage unit The calculation is as follows: ; When the energy storage unit is in a discharging state, This indicates the energy that the energy storage unit can still release relative to the minimum permissible state of charge; when the energy storage unit is in the charging state, This indicates the energy space that the energy storage unit can still absorb relative to its maximum permissible state of charge. This feature differs from existing methods that only use the SOC ratio as a balancing basis, and can reflect the actual usable energy differences between energy storage units of different capacities.

[0062] Continue to refer to Figure 2 In step S300, based on the remaining available energy of the energy storage unit itself and the remaining available energy of adjacent energy storage units, an adaptive algorithm is used to generate a dynamic remaining available energy reference value.

[0063] In some feasible embodiments, based on the aforementioned scheme, the step of generating a dynamic remaining available energy reference value using an adaptive algorithm based on the remaining available energy of the energy storage unit itself and the remaining available energy of adjacent energy storage units includes: Each energy storage unit communicates with adjacent energy storage units to exchange local reference status information of remaining available energy. Each energy storage unit updates its dynamic remaining available energy reference value based on the remaining available energy reference state information of adjacent energy storage units and its own remaining available energy, using an adaptive consistency adjustment rule.

[0064] It should be noted that, in this embodiment, during the initial control cycle, it can be set that ( = ), The dynamic remaining available energy reference value is used to ensure that each energy storage unit uses its own initial RAE state as the starting point for consistency iteration. In subsequent control cycles, when the RAE reference state difference between adjacent energy storage units is large, the consistency adjustment intensity is increased to accelerate reference value convergence; when the difference is small, the adjustment intensity is decreased to reduce steady-state fluctuations. The current cycle update obtains... It can be stored and used for deviation calculation in the next control cycle.

[0065] Here is an example of how to generate a dynamic reference value for remaining available energy: To generate RAE reference estimates for each energy storage unit in a distributed communication topology, this invention designs a discrete dynamic consistency observer with a local RAE tracking correction term. Defined as the... The energy storage unit in the first The local RAE reference state variables at each sampling time are set with the following initial conditions: = ; This initialization method allows each energy storage unit to use its current RAE state as the starting point for consistency iteration, thereby avoiding dependence on a centralized global average value.

[0066] Let the discrete sampling period of the consensus algorithm be... The local tracking gain is , No. The set of adjacent nodes of each energy storage unit is Then the update law for its local reference state variable is:

[0067] To enable the consistency adjustment strength to adaptively change with the differences in RAE reference states between nodes, and to avoid excessive adjustment through upper and lower bound constraints on the gain, this example constructs a nonlinear adaptive coupling gain based on local consistency error. The local consistency error of an energy storage unit is defined as:

[0068] The adaptive consistency gain is defined as:

[0069] In the formula: and These are the steady-state and transient gain limits, respectively. This is the sensitivity coefficient. This adaptive mechanism causes the system to diverge in local states. When the gain is large, it rapidly increases to accelerate convergence, and automatically drops back to a low gain to suppress steady-state fluctuations when the divergence narrows.

[0070] After the above iterations, the first Each energy storage unit obtains its local dynamic RAE reference value:

[0071] This step does not rely on centralized global average calculation, but only on the information exchange between neighboring nodes to generate distributed RAE reference values.

[0072] Continue to refer to Figure 2 Step S400: Calculate the normalized remaining available energy deviation of the energy storage unit based on the dynamic remaining available energy reference value.

[0073] In some feasible embodiments, based on the aforementioned scheme, the formula for calculating the normalized remaining available energy deviation is as follows: ; in, For the first Normalized residual available energy deviation of the energy storage unit group; For the first The remaining usable energy of each energy storage unit; This is a reference value for the dynamic remaining available energy. This represents the smallest positive number that prevents the denominator from being zero.

[0074] Continue to refer to Figure 2 In step S500, the droop coefficient is corrected according to the normalized remaining available energy deviation, and the power distribution is controlled based on the corrected droop coefficient.

[0075] In some feasible embodiments, based on the foregoing scheme, the step of correcting the droop coefficient according to the normalized remaining available energy deviation includes: Combining the current dead zone debouncing logic within the actual operating range, and considering the remaining available energy deviation, the first... Dynamic droop coefficient of each energy storage unit for: ; in, Indicates the base sag coefficient. This represents the adjustment weight of the arctangent function. For the converter output current, This indicates the set dead zone current threshold.

[0076] Here is an example of a correction for the droop factor: Obtaining dynamic RAE reference values Afterwards, according to the first The deviation between the current RAE of an energy storage unit and its reference value affects the base sag factor. Real-time corrections are performed. To ensure consistent control sensitivity across different energy bases, the normalized RAE deviation is defined as:

[0077] In the formula, To prevent extremely small positive numbers with a denominator of zero.

[0078] Combining the current dead zone debouncing logic within the actual operating range, the first Dynamic droop coefficient of each energy storage unit Designed as follows:

[0079] In the formula: The adjustment weights for the arctangent function; The dead zone current threshold is set to prevent the energy storage unit from experiencing sag coefficient fluctuations near the zero power exchange point due to frequent switching of charging and discharging modes.

[0080] When the energy storage branch current is within the dead zone, dynamic droop adjustment is temporarily suppressed, let:

[0081] This current dead zone design can reduce the droop coefficient fluctuation of the energy storage unit near the zero power exchange point caused by frequent switching of charging and discharging modes.

[0082] To further improve the stability and engineering feasibility of the control process, the modified droop coefficient is limited for protection.

[0083] in, and These are the lower and upper limits of the dynamic droop coefficient, respectively.

[0084] In this way, energy storage units with higher remaining usable energy or larger energy absorption space can undertake more power regulation tasks under corresponding operating conditions, while energy storage units with lower remaining usable energy or smaller absorption space undertake fewer power regulation tasks, thereby achieving energy state balance among multiple energy storage units.

[0085] In some feasible embodiments, based on the foregoing scheme, the power allocation control based on the modified droop coefficient includes: When the remaining usable energy of a certain energy storage unit is higher than its dynamic remaining usable energy reference value, the droop coefficient of the certain energy storage unit is reduced or the power sharing capacity of the certain energy storage unit is increased, so that the energy storage unit can bear more discharge power in the discharge state or bear more charging absorption power in the charging state. When the remaining usable energy of a certain energy storage unit is lower than its dynamic remaining usable energy reference value, the droop coefficient of the certain energy storage unit is increased or the power sharing capacity of the certain energy storage unit is reduced, so that the energy storage unit reduces the discharge power in the discharge state or reduces the charging absorption power in the charging state.

[0086] It should be noted that, in this embodiment, the power distribution controlled by the modified droop coefficient can ensure that the power distribution matches the actual remaining available energy state of each energy storage unit, regardless of whether the system is in a charging or discharging state, thereby achieving energy balance among multiple energy storage units.

[0087] Continue to refer to Figure 2 In step S600, a bus voltage compensation mechanism is introduced to correct the bus voltage deviation caused by droop control.

[0088] In some feasible embodiments, based on the aforementioned scheme, the introduction of a bus voltage compensation mechanism to correct the bus voltage deviation caused by droop control includes: The energy storage unit collects the bus voltage through the local controller and exchanges voltage observation information with adjacent energy storage units to obtain the compensation amount for voltage recovery. The compensation amount and the dynamic droop voltage drop term are applied together to the local reference voltage to generate the corrected voltage reference value for the energy storage unit.

[0089] Understandably, this step is used to address the issue of DC bus voltage deviating from its rated value due to droop control.

[0090] Here is an example of correcting bus voltage deviation: To reduce voltage deviation caused by droop control and avoid the dependence of centralized voltage compensation on global information, this example designs a distributed voltage compensator based on a multi-agent consensus algorithm. The compensator consists of a consensus voltage observer and a PI recovery controller. To obtain the global average voltage, nodes... Relying on communication networks to exchange information with neighboring nodes, its dynamic consistency observation equation is designed as follows:

[0091] In the formula: For nodes The average voltage observation status; For local sampling bus voltage; and These are the local tracking gain and the uniform coupling gain, respectively. It is the set of adjacent nodes; These are the adjacency matrix elements of the communication topology. The above iterative convergence is obtained... Then, compare it with the bus rated reference voltage. The difference is calculated and sent to the PI controller to generate a voltage compensation command. :

[0092] In the formula, and This is a PI control parameter. The compensation amount... This voltage is ultimately superimposed on the droop control reference voltage, thereby reducing the system static voltage drop and restoring the DC bus voltage to near its rated value.

[0093] Continue to refer to Figure 2 In step S700, based on the bus voltage deviation, a battery-side current reference value is generated using a voltage outer loop controller.

[0094] In some feasible embodiments, based on the foregoing scheme, the step of generating a battery-side current reference value using a voltage outer loop controller based on the bus voltage deviation includes: The corrected voltage reference value is compared with the actual sampled bus voltage to obtain the voltage error; The voltage error is then input into the outer voltage loop controller, which generates a corresponding battery-side current reference value based on the voltage error.

[0095] Understandably, this battery-side current reference value reflects the power regulation requirements resulting from the combined action of upper-level RAE equalization control and middle-level voltage compensation control, providing input commands for the current control of the lower-level bidirectional DC / DC converter.

[0096] As an example, the following provides an example of generating a battery-side current reference value using voltage outer loop control: To achieve rapid execution of power allocation commands from multiple energy storage units in a DC microgrid and to mitigate bus voltage deviation caused by traditional droop control, this example incorporates an outer voltage loop and an inner current model prediction loop in the bidirectional DC / DC converter corresponding to each energy storage unit. The outer voltage loop generates a battery current reference value based on the compensated bus voltage error, while the inner current model prediction loop replaces the traditional PI inner current loop, enabling rapid tracking of the energy storage branch current to the reference value.

[0097] The outer voltage loop integrates the dynamic droop coefficient generated by RAE equalization control with the distributed consistency voltage compensation, and converts it into the current reference command required by the underlying current predictive control. (Regarding the first...) Each energy storage unit has an initial rated DC reference voltage. First, the consistency voltage compensation is applied. Correction, followed by the introduction of the first Group converter output current With dynamic droop coefficient The voltage drop feedback generates the corrected reference voltage command for this unit. :

[0098] To reduce the static voltage deviation caused by droop control and improve bus voltage stability, Compared with the actual sampled value of the local DC bus voltage The difference is fed into the PI voltage regulator. The battery-side current reference command is output from the outer voltage loop. for:

[0099] In the formula, and These are the proportional and integral coefficients of the voltage outer loop, respectively. Through this voltage outer loop, the change in the dynamic droop coefficient caused by RAE deviation can further affect the current reference value, thereby aligning the actual power output of the energy storage unit with its remaining available energy state.

[0100] Continue to refer to Figure 2 In step S800, based on the battery-side current reference value, a finite set model is used to predict the current generation control command.

[0101] In some feasible embodiments, based on the foregoing scheme, the step of predicting the current generation control command using a finite set model based on the battery-side current reference value includes: The controller uses a finite set model to predict the current value at the next moment or after multiple steps under different switching states based on the current battery-side current reference value, battery terminal voltage, DC bus voltage and filter inductor parameters, and calculates the error between the predicted current and the reference current. Then, the switching state with the smallest error is selected as the optimal control output to drive the bidirectional DC / DC converter, enabling the energy storage branch current to quickly track the reference value.

[0102] As an example, the following provides an example of using a current model to predict the inner loop design: Obtaining battery current reference value Subsequently, this example employs finite set current model predictive control to select the switching state of the bidirectional DC / DC converter. This method predicts the current changes under different candidate switching states based on the current battery-side current, battery terminal voltage, DC bus voltage, and current reference value, and selects the switching state that minimizes the current tracking error as the control output.

[0103] Let the candidate switching states of the bidirectional DC / DC converter be According to Kirchhoff's voltage law, the continuous-time dynamic differential equation for the inductor current is:

[0104] In the formula: L is the converter filter inductance; This refers to the battery terminal voltage. This is the equivalent voltage applied to the other end of the inductor for the operation of the switching transistor. Considering the converter topology, when... hour, ;when hour, ( For the first Local bus voltage at the access point of each energy storage unit.

[0105] To facilitate digital controller implementation, the above model is discretized using the forward Euler method. Let the control period be... In the candidate switch state The one-step prediction model for the battery branch current is as follows:

[0106] In a preferred embodiment, a three-step prediction method is adopted to improve the predictive power of the control. Because the control period is short, it can be approximated within the same prediction period. and If we keep it unchanged, then we have:

[0107]

[0108] For each candidate switch state, construct a current tracking error evaluation function:

[0109] Within one control cycle, the microprocessor traverses the candidate state set. Substitute the values ​​into the extended model to calculate the corresponding three-step predicted current. The algorithm calculates the value of the cost function g. The optimization logic selects the switching state with the minimum cost function g as the optimal control vector for the next moment, and uses it as the gate control signal for the bidirectional DC / DC converter switch, or converts it through the drive circuit and applies it to the corresponding switching device.

[0110] By coordinating the voltage outer loop and the model-predicted current inner loop, the dynamic power allocation command generated by the RAE equalization control can be further transformed into rapid dynamic adjustment of the battery-side current of the energy storage unit, thereby achieving coordinated control for equalizing the remaining available energy of multiple energy storage units, restoring the bus voltage, and rapidly tracking the energy storage current.

[0111] Continue to refer to Figure 2 Step S900: Determine the operating status of the DC microgrid and cyclically update the control commands.

[0112] It should be noted that, in this embodiment, within each control cycle, the controller determines whether the RAE deviation, DC bus voltage deviation, and energy storage branch current of each energy storage unit meet the preset requirements. If the RAE deviation of each energy storage unit is within the allowable range, and the bus voltage and branch current both meet the safety constraints, the current control state is maintained; if any indicator does not meet the requirements, the system returns to the status acquisition step S100, recalculates the RAE, updates the RAE reference value, corrects the droop coefficient, and generates a new control command.

[0113] Through the above-mentioned cyclic control, the present invention can achieve the balancing of remaining available energy of multiple energy storage units, the recovery of DC bus voltage, and the rapid tracking of energy storage branch current under operating conditions such as load disturbance, photovoltaic power output fluctuation, and inconsistent energy storage unit status.

[0114] The following describes an embodiment of the apparatus described in this application, which can be used to execute a multi-energy storage balancing control method for DC microgrids based on remaining available energy, as described in the above embodiments of this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in the above applications.

[0115] Reference Figure 3 As shown, a DC microgrid multi-energy storage balancing control device 300 based on surplus available energy according to an embodiment of this application includes: The acquisition unit 301 is used to acquire real-time operating status information of the DC microgrid, including the state of charge, rated voltage, rated capacity, output current, output voltage, converter output current, local sampling bus voltage, and output current limit value of the bidirectional DC / DC converter of the energy storage unit. The first calculation unit 302 is used to calculate the remaining available energy of each energy storage unit; The first generation unit 303 is used to generate a dynamic remaining available energy reference value based on the remaining available energy of the energy storage unit itself and the remaining available energy of adjacent energy storage units using an adaptive algorithm. The second calculation unit 304 is used to calculate the normalized remaining available energy deviation of the energy storage unit based on the dynamic remaining available energy reference value. The first correction unit 305 is used to correct the droop coefficient according to the normalized remaining available energy deviation, and control the power distribution based on the corrected droop coefficient. The second correction unit 306 is used to introduce a bus voltage compensation mechanism to correct the bus voltage deviation caused by droop control. The second generation unit 307 is used to generate a battery-side current reference value based on the bus voltage deviation using a voltage outer loop controller. Prediction unit 308 is used to predict current generation control commands based on the battery-side current reference value using a finite set model; The cyclic update unit 309 is used to determine the operating status of the DC microgrid and cyclically update the control commands.

[0116] like Figure 4As shown, this application embodiment also provides an electronic device 400, including a memory 410, a processor 420, and a computer program 411 stored in the memory 410 and executable on the processor. When the processor 420 executes the computer program 411, it implements the steps of the above-mentioned DC microgrid multi-energy storage equalization control method based on remaining available energy.

[0117] Since the electronic device described in this embodiment is the device used to implement a DC microgrid multi-energy storage equalization control device based on the remaining available energy in the embodiments of this application, those skilled in the art can understand the specific implementation method and various variations of the electronic device in this embodiment based on the method described in the embodiments of this application. Therefore, how the electronic device implements the method in the embodiments of this application will not be described in detail here. Any device used by those skilled in the art to implement the method in the embodiments of this application falls within the scope of protection of this application.

[0118] In practice, when the computer program 411 is executed by the processor, it can implement any of the embodiments corresponding to the first aspect.

[0119] Figure 5 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown.

[0120] It should be noted that, Figure 5 The computer system 500 of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0121] like Figure 5 As shown, the computer system 500 includes a Central Processing Unit (CPU) 501, which can perform various appropriate actions and processes based on programs stored in Read-Only Memory (ROM) 502 or programs loaded from storage portion 508 into Random Access Memory (RAM) 503, such as performing the methods described in the above embodiments. The RAM 503 also stores various programs and data required for system operation. The CPU 501, ROM 502, and RAM 503 are interconnected via a bus 504. An Input / Output (I / O) interface 505 is also connected to the bus 504.

[0122] The following components are connected to I / O interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to I / O interface 505 as needed. Removable media 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 510 as needed so that computer programs read from them can be installed into storage section 508 as needed.

[0123] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is executed by central processing unit (CPU) 501, it performs various functions defined in the system of this application.

[0124] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such transmitted data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0125] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0126] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0127] In another aspect, this application also provides a computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the multi-energy storage balancing control method for DC microgrids based on remaining available energy described in the above embodiments.

[0128] In another aspect, this application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiments; or it may exist independently and not assembled into the electronic device. The computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to implement the multi-energy storage balancing control method for DC microgrids based on remaining available energy described in the above embodiments.

[0129] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0130] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, touch terminal, or network device, etc.) to execute the methods according to the embodiments of this application.

[0131] Other embodiments of this application will readily conceive of by those skilled in the art upon consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. It should be understood that this application is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A multi-energy storage equalization control method for DC microgrids based on surplus available energy, characterized in that, include: Real-time acquisition of DC microgrid operating status information, including energy storage unit state of charge, rated voltage, rated capacity, energy storage unit output current, energy storage unit output voltage, converter output current, local sampling bus voltage, and bidirectional DC / DC converter output current limit value; Calculate the remaining usable energy of each energy storage unit; Based on the remaining available energy of the energy storage unit itself and the remaining available energy of adjacent energy storage units, an adaptive algorithm is used to generate a dynamic reference value of remaining available energy. The normalized remaining available energy deviation of the energy storage unit is calculated based on the dynamic remaining available energy reference value; The droop coefficient is corrected based on the normalized remaining available energy deviation, and power allocation is controlled based on the corrected droop coefficient. A bus voltage compensation mechanism is introduced to correct the bus voltage deviation caused by droop control. Based on the bus voltage deviation, a battery-side current reference value is generated using a voltage outer loop controller; Based on the battery-side current reference value, a finite set model is used to predict the current generation control command; Determine the operating status of the DC microgrid and cyclically update the control commands; Wherein, the step of correcting the droop coefficient based on the normalized remaining available energy deviation includes: Combining the current dead zone debouncing logic within the actual operating range, and considering the remaining available energy deviation, the first... Dynamic droop coefficient of each energy storage unit for: ； in, Indicates the base sag coefficient. This represents the adjustment weight of the arctangent function. For the converter output current, This indicates the set dead zone current threshold. For the first The normalized remaining available energy deviation of the energy storage unit group.

2. The method according to claim 1, characterized in that, The calculation of the remaining available energy of each energy storage unit includes: Calculate the first... based on the current charging and discharging direction of the energy storage unit. The remaining usable energy of each energy storage unit : ； in, For the first The current on the battery side of each energy storage unit is specified, and the discharge time of the battery to the DC bus is also specified. ; For the first The state of charge of each energy storage unit; Indicates the minimum state of charge. Indicates the maximum state of charge. Indicates the first The rated total energy of each energy storage unit.

3. The method according to claim 1, characterized in that, The dynamic remaining available energy reference value is generated using an adaptive algorithm based on the remaining available energy of the energy storage unit itself and the remaining available energy of adjacent energy storage units, including: Each energy storage unit communicates with adjacent energy storage units to exchange local reference status information of remaining available energy. Each energy storage unit updates its dynamic remaining available energy reference value based on the remaining available energy reference state information of adjacent energy storage units and its own remaining available energy, using an adaptive consistency adjustment rule.

4. The method according to claim 1, characterized in that, The formula for calculating the normalized remaining available energy deviation is as follows: ； in, For the first Normalized residual available energy deviation of the energy storage unit group; For the first The remaining usable energy of each energy storage unit; This is a reference value for the dynamic remaining available energy. This represents the smallest positive number that prevents the denominator from being zero.

5. The method according to claim 1, characterized in that, The power allocation control based on the modified droop coefficient includes: When the remaining usable energy of a certain energy storage unit is higher than its dynamic remaining usable energy reference value, the droop coefficient of the certain energy storage unit is reduced or the power sharing capacity of the certain energy storage unit is increased, so that the energy storage unit can bear more discharge power in the discharge state or bear more charging absorption power in the charging state. When the remaining usable energy of a certain energy storage unit is lower than its dynamic remaining usable energy reference value, the droop coefficient of the certain energy storage unit is increased or the power sharing capacity of the certain energy storage unit is reduced, so that the energy storage unit reduces the discharge power in the discharge state or reduces the charging absorption power in the charging state.

6. The method according to claim 1, characterized in that, The introduced bus voltage compensation mechanism corrects the bus voltage deviation caused by droop control, including: The energy storage unit collects the bus voltage through the local controller and exchanges voltage observation information with adjacent energy storage units to obtain the compensation amount for voltage recovery. The compensation amount and the dynamic droop voltage drop term are applied together to the local reference voltage to generate the corrected voltage reference value for the energy storage unit.

7. The method according to claim 6, characterized in that, The step of generating a battery-side current reference value based on the bus voltage deviation using a voltage outer loop controller includes: The corrected voltage reference value is compared with the actual sampled bus voltage to obtain the voltage error; The voltage error is then input into the outer voltage loop controller, which generates a corresponding battery-side current reference value based on the voltage error.

8. The method according to claim 1, characterized in that, The current generation control command predicted using a finite set model based on the battery-side current reference value includes: The controller uses a finite set model to predict the current value at the next moment or after multiple steps under different switching states based on the current battery-side current reference value, battery terminal voltage, DC bus voltage and filter inductor parameters, and calculates the error between the predicted current and the reference current. Then, the switching state with the smallest error is selected as the optimal control output to drive the bidirectional DC / DC converter, enabling the energy storage branch current to quickly track the reference value.

9. A DC microgrid multi-energy storage balancing control device based on surplus available energy, applied to the method as described in any one of claims 1-8, characterized in that, include: The data acquisition unit is used to collect real-time operating status information of the DC microgrid, including the state of charge, rated voltage, rated capacity, output current, output voltage, converter output current, local sampling bus voltage, and output current limit value of the bidirectional DC / DC converter of the energy storage unit. The first computing unit is used to calculate the remaining available energy of each energy storage unit; The first generation unit is used to generate a dynamic reference value of remaining available energy based on the remaining available energy of the energy storage unit itself and the remaining available energy of adjacent energy storage units using an adaptive algorithm. The second calculation unit is used to calculate the normalized remaining available energy deviation of the energy storage unit based on the dynamic remaining available energy reference value; The first correction unit is used to correct the droop coefficient according to the normalized remaining available energy deviation, and to control the power distribution based on the corrected droop coefficient. The second correction unit is used to introduce a bus voltage compensation mechanism to correct the bus voltage deviation caused by droop control. The second generation unit is used to generate a battery-side current reference value based on the bus voltage deviation using a voltage outer loop controller. The prediction unit is used to predict the current generation control command based on the battery-side current reference value using a finite set model. The cyclic update unit is used to determine the operating status of the DC microgrid and cyclically update the control commands.

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