Ship energy sharing management method based on multi-mode adaptive droop control

Abstract

The invention discloses a ship energy sharing management method based on multi-mode adaptive droop control. The ship energy sharing management method comprises the following steps: acquiring shipborne micro-grid data; connecting a plurality of electric ships in parallel with a direct-current micro-grid, and constructing a direct-current micro-grid cluster by using the obtained shipborne micro-grid data; and performing multi-mode adaptive droop control on the constructed DC micro-grid cluster, and coordinating a power control strategy of the whole DC micro-grid cluster. And establishing a small-signal analysis model for the direct-current micro-grid cluster to judge the stability of the system. According to the ship energy sharing management method, decentralized power sharing of a micro-grid cluster based on a plurality of electric ship parallel DC micro-grids is realized through multi-mode adaptive droop control, and a power control strategy of the whole micro-grid cluster is coordinated, so that the micro-grids can operate independently and can also provide power support mutually.

Description

Technical Field

[0001] The present invention relates to the technical field of ship shore power management, and in particular to a ship energy sharing management method based on multi-mode adaptive droop control. Background Art

[0002] In the prior art, the use of electric ships has solved the problems of polluting gases and noise generated during ship berthing. In the current construction of the shore power system in the inland river basin, for ports in the Yangtze River Basin, especially small-scale ports in the inland river, a comprehensive supporting shore power facility has not been built yet. Some ports in remote areas are far from power stations, and huge costs are required to build charging facilities for electric ships. To overcome these problems, the on-board microgrid systems of multiple electric ships can be combined with the on-shore charging infrastructure to form a small-port microgrid. The charging and discharging of electric ships are carried out according to the state of charge (SOC) of the battery packs of multiple electric ship battery energy storage systems sharing power.

[0003] In the prior art, the installed capacity of renewable energy and distributed power sources in the port will continue to expand, and the scale of all-electric ships will increase steadily. Due to the access of a large number of distributed power sources, their characteristics of dispersion, instability, and intermittency make the energy input of the port power grid unable to be smooth, quantitative, and continuous. The traditional optimization control strategy of the port power grid is difficult to continue, the power supply reliability of the port is affected, and the renewable energy curtailment rate remains high, which is not conducive to the overall operation economy optimization of the port power grid.

[0004] 1) Uncertain environment: When a power ship sails, the working conditions change frequently and the meteorological conditions are complex. Both its power generation side and demand side show strong randomness and uncertainty. For example, the uncertainty of renewable energy power generation, the uncertainty of shipboard living load, the uncertainty of the system propulsion power affected by the navigation resistance, etc. If the day-ahead scheduling plan is followed, there may be a deviation from the optimal scheduling decision, or even a situation where the system operation constraints cannot be met. These uncertainty factors include changes in the additional resistance of the ship caused by wind and waves, load fluctuations, speed loss, fluctuations in the output power of renewable energy, and random outages of power equipment. If the impact of the above uncertainties on the operation of power ships is not fully explored, it may cause waste of resources, economic losses, and additional emissions and pollution, and even affect the stability and reliability of the system operation.

[0005] 2) Multi-energy coupling: The coupling of multiple energies and the coordinated optimization of the power system - transportation system make the energy supply and scheduling management of the port more challenging. The dynamic access of large-scale ships to the shore power makes the system highly uncertain on both the source and load sides, affecting the stable operation of the system. The renewable energy power generation, the charging and discharging of energy storage devices, the heterogeneous energy conversion, the logistics operation scheduling, and the ship shore power access are associated and coupled. The uncertainty propagates interactively along the energy flow direction in the system, exacerbating the impact on the stable operation of the system. Summary of the Invention

[0006] The present invention provides a ship energy sharing management method based on multi-mode adaptive droop control, which realizes decentralized power sharing of a microgrid cluster based on multiple parallel DC microgrids of electric ships through multi-mode adaptive droop control, coordinates the power control strategies of the entire microgrid cluster, and enables the microgrids to operate independently or provide power support for each other.

[0007] The technical solution adopted by the present invention is as follows:

[0008] The ship energy sharing management method based on multi-mode adaptive droop control includes the following steps:

[0009] Step 1: Obtain on-board microgrid data and sort and divide the data of electric ships.

[0010] Step 2: Parallel multiple DC microgrids of electric ships and construct a mobile port DC microgrid cluster by using the on-board microgrid data obtained in Step 1.

[0011] Step 3: Adopt multi-mode adaptive droop control for the mobile port DC microgrid cluster constructed in Step 2 to coordinate the power control strategies of the entire DC microgrid cluster; enable the microgrids to operate independently or provide power support for each other. In addition, the mobile port DC microgrid cluster can also be interconnected with the main grid, participate in the power market and provide backup power.

[0012] Step 4: On the basis of Step 3, build a small-signal analysis model for the mobile port DC microgrid cluster to determine the system stability.

[0013] In the above Step 1, before the implementation of the management method, it is necessary to process the on-board microgrid data to ensure the quality and availability of the data and improve the accuracy of analysis, including the following:

[0014] 1) Confirm the types of connected electric ships: The connected electric ships are divided into fuel ships, electric ships with power sharing, and electric ships without power sharing.

[0015] 2) Estimation of the state of charge of energy storage:

[0016] The online estimation methods of SOC can generally be divided into Coulomb counting method, model-driven method and data-driven method. Among them, the most commonly used method is the Coulomb counting method, which uses the integral of the measured current and time to obtain SOC, is an open-loop estimation method, simple to measure and suitable for wireless communication.

[0017]

[0018] In formula (1), SOC j(t) represents the calculated value of the battery SOC; SOC i (0) represents the SOC value at the initial state of the battery; C is the unit of battery capacity: Ah; V0, I in respectively represent the DC bus voltage and the battery output current; I L represents the current output from the shipborne microgrid to the DC bus; T represents the time variable.

[0019] In step 2, the distributed power source, electric ship, energy storage device, load, etc. are combined in parallel by using a common DC bus; at the same time, the DC bus voltage of the mobile port DC microgrid cluster is stepped down and transmitted to the energy storage battery of the electric ship through a bidirectional DC / DC device; a buck converter is connected between the DC bus and the energy storage battery;

[0020] In step 2, the mathematical model expression of the buck converter is as follows:

[0021]

[0022] In the above formula, i L represents the inductor current; V g represents the input voltage, V o represents the output voltage, D represents the duty cycle; C, L, R SR and R L respectively represent the capacitor, inductor, parasitic resistance of the buck converter, and the load connected to the output terminal.

[0023] The overall transfer function of the double-loop control of the buck converter can be expressed by the following equation:

[0024]

[0025] In step 3, a multi-mode adaptive droop control method is used to achieve decentralized power sharing of the mobile port DC microgrid cluster based on multiple shipborne microgrids. Coordinate the power control strategy of the entire DC microgrid cluster so that the microgrids can operate independently or provide power support to each other.

[0026] The multi-mode adaptive droop control method realizes decentralized power sharing among different shipborne microgrids; at the SOC at the lowest or highest threshold, the V-I droop control is adopted, which helps to improve the stability margin of the system; on the contrary, when the SOC is lower than the lowest threshold or higher than the highest threshold, the I-V droop mode is adopted to enhance the transient response.

[0027] In order to achieve resource balance and effectively utilize resources, the SOC change function is set as the droop value. Specifically as follows:

[0028] V o =U dc -Io R D

[0029] Among them, R D is the droop resistance;

[0030] The charging current is expressed as follows:

[0031] I ref =(V dc - V o ) / R c

[0032]

[0033] The discharging current is expressed as follows:

[0034] I ref =(V dc - V o ) / R d

[0035]

[0036] The shipboard microgrid will reasonably share energy according to the energy storage SOC. To extend the service life of the battery, it is necessary to achieve energy balance and optimal power distribution. The power distribution among shipboard microgrids (SMGs) is divided into three modes according to the state SOC of the battery pack. These modes include:

[0037] ①. Current control charging mode: 0 ≤ SOC j < SOC min ;

[0038] ②. V-I droop control mode: SOC min ≤ SOC j < SOC max ;

[0039] ③. Current control discharging mode: SOC max ≤ SOC j < 100;

[0040] Among them, SOC j represents the state of charge of the battery, SOC min represents the threshold of the minimum state of charge of the set battery, and SOC max represents the threshold of the maximum state of charge of the battery.

[0041] In step 4, analyze the influence of the PI controller of the power compensation link introduced by the multi-mode adaptive droop control on the small-signal stability of the DC microgrid cluster, specifically as follows:

[0042] Analyze the stability performance of a mobile port DC microgrid cluster system with multi-mode adaptive droop control after experiencing small disturbances through eigenvalue root locus analysis;

[0043] For the DC / DC converter i with improved droop control, select the state variables of the buck converter as x i (t) = [Δv Ci , Δi Li , Δi oi , Δg ui , Δg ii , Δg di T , Δv Ci represents the small-signal variable of the capacitor voltage at the output of the converter of micro-source i; Δi Li represents the small-signal variable of the inductor current at the output of the converter of micro-source i; Δi oi represents the small-signal variable of the output current at the output of the converter of micro-source i; Δg ui represents the transfer function variable of the voltage PI controller of micro-source i, Δg ii represents the transfer function variable of the current PI controller of micro-source i, Δg di represents the working value of the compensation link PI controller of micro-source i; T represents the state variable;

[0044] Similarly, for micro-source j (distributed power sources in the port microgrid, such as electric ships or energy storage devices, etc.), there is x j (t) = [Δv Cj , Δi Lj , Δi oj , Δg uj , Δg ij , Δg dj T , Δv Cj represents the small-signal variable of the output voltage of micro-source j; Δi Lj represents the small-signal variable of the inductor current at the output of the converter of micro-source j; Δi oj represents the small-signal variable of the output current at the output of the converter of micro-source j; Δg uj represents the transfer function variable of the voltage PI controller of micro-source j; Δg ij represents the transfer function variable of the current PI controller of micro-source j; Δg dj represents the working value of the compensation link PI controller of micro-source j; In addition, take Δv eq and Δi eq as the load-side state variables x s (t) = [Δv eq , Δi eq T , Δv eq represents the small-signal variable of the capacitor voltage at the output of the converter of the constant power load side, Δi​​​eq represents the small-signal variable of the output current of the constant-power load side converter; thus, the state variables of the entire microgrid system can be denoted as x(t) = [x i (t), x j (t), x s (t)] T , where x(t) is a 14th-order column vector.

[0045] The islanded DC microgrid is simplified to an equivalent model including multiple DC / DC converters with improved droop control, line impedance, resistive loads, and equivalent constant-power loads; as Figure 6 shown;

[0046]

[0047] In the above formula, i eq represents the output current of the load side DC converter, C eq represents the equivalent capacitance of the load side DC converter, v eq represents the output voltage of the load side DC converter, i CPL represents the constant-power load current, P CPL represents the equivalent constant-power load power, v bus represents the DC bus voltage, R eq represents the equivalent line resistance, L eq represents the equivalent line inductance, i ok represents the output current of the kth micro-source, and k represents the kth micro-source;

[0048] Perform a Taylor expansion of i CPL (v eq ) at the steady-state value V eq in the first equation of Equation (6):

[0049]

[0050] In the above formula, i CPL (v eq ) represents the constant-power load current when v eq is a variable, i CPL (V eq ) represents the constant-power load current at the steady-state value Veq, V eq represents the steady-state value Veq, represents a higher-order infinitesimal;

[0051] where O is the remainder term. Ignoring this remainder term, we can then obtain:

[0052]

[0053] In the above formula, △i CPL represents the small-signal quantity of the load side current.

[0054] Furthermore, from Equation (5) and Equation (7), v is obtained. eq The state equation of:

[0055]

[0056] In the above equation, △v eq represents the small-signal quantity of the output voltage of the DC converter on the constant-power load side, and △i eq represents the small-signal quantity of the output current of the DC converter on the constant-power load side.

[0057] In order to derive the state equation of i oi where i oi represents the output current of the micro-source i; first, the small-signal quantity v of the bus voltage is derived bus , and according to Equation (5), it is obtained:

[0058] △v bus = R Re (△i oi + △i oj - △i eq )(9);

[0059] In the above equation, △v bus represents the small-signal quantity of the bus voltage, R Re represents the equivalent line constant resistive load, △i oi represents the small-signal quantity of the output current of the micro-source i, and △i oj represents the small-signal quantity of the output current of the micro-source j.

[0060] By combining Equation (5) and Equation (9), the state equation of i eq can be obtained:

[0061]

[0062] In the above equation, R eq represents the equivalent line resistance;

[0063] According to the above state equations, the characteristic matrix A can be obtained. The characteristic matrix A is a 14th-order square matrix. Therefore, the small-signal model of this islanded DC microgrid can be obtained as:

[0064]

[0065] In the above equation, represents the small-signal model of the microgrid, x(t) represents the state vector, B is the input matrix, and u(t) = [Δv si , Δv sj T , Δv si represents the state variable of the voltage at the outlet of the micro-source i, Δv​sj Represents the state variable of the micro-source j output voltage.

[0066] A ship energy sharing management method based on multi-mode adaptive droop control according to the present invention has the following technical effects:

[0067] 1) In step 2 of the present invention, through the parallel DC microgrid, the system capacity can be flexibly adjusted to adapt to the power demands of ports of different scales. Newly added ships can be seamlessly connected without reconstructing the existing system. At the same time, when a fault occurs in the microgrid of a certain ship, other ships can quickly fill the power gap to maintain the operation stability of the microgrid.

[0068] 2) In step 3 of the present invention, power sharing among ships is achieved through droop control, avoiding overloading or circulating current problems. At the same time, it supports power interaction with the main grid. According to the real-time state of the ship microgrid (such as SOC, power generation capacity), the droop coefficient is dynamically adjusted to achieve optimal power distribution. During the mode switching (grid-connected / off-grid / cluster) process, the droop control smoothly transitions to avoid voltage / current shocks and ensure the safety of equipment.

[0069] 3) In step 4 of the present invention, by modeling and analyzing the dynamic response of the system under disturbances (such as load mutation, ship access / exit), key parameters (such as control gain, line impedance) that may cause oscillation or instability are identified. Avoiding collapse accidents caused by improper control parameters during actual operation.

[0070] 4) The ship energy sharing management method of the present invention adopts a communication-free control scheme for the port microgrid with multi-mode adaptive droop control, avoiding overcharging or over-discharging of the battery to extend the battery life, and achieving SOC balance in the charging and discharging modes. These modes include constant voltage charging mode, V-I droop mode, and variable current charging mode. In case of emergency, these interconnected SMGs can supply power to the port through battery packs and photovoltaic (PV). The proposed scheme has certain development potential for future autonomous ships and shore power construction or remote ports. Brief Description of the Drawings

[0071] The present invention will be further described below in conjunction with the drawings and examples;

[0072] Figure 1 Is a flowchart of a ship energy sharing management method based on multi-mode adaptive droop control.

[0073] Figure 2 Is a structure diagram of the DC bus microgrid.

[0074] Figure 3 Is a structure diagram of multi-mode adaptive droop control.

[0075] Figure 4 Is a diagram of the small-signal analysis result.

[0076] Figure 5 It is a multi-mode verification result diagram.

[0077] Figure 6 It is a schematic diagram of the equivalent model of the DC microgrid. Specific implementation method

[0078] A ship energy sharing management method based on multi-mode adaptive droop control includes the following steps:

[0079] Step 1: Obtain the data of the on-board microgrid and sort and divide the data of the electric ship.

[0080] Step 2: Connect multiple electric ships in parallel to the DC microgrid, and use the on-board microgrid data obtained in Step 1 to construct a mobile port DC microgrid cluster.

[0081] Step 3: Apply multi-mode adaptive droop control to the mobile port DC microgrid cluster constructed in Step 2 to coordinate the power control strategy of the entire DC microgrid cluster; enable the microgrid to operate independently or provide power support to each other. In addition, the mobile port DC microgrid cluster can also be interconnected with the main grid, participate in the power market and provide backup power.

[0082] Step Search: On the basis of Step 3, build a small-signal analysis model for the mobile port DC microgrid cluster to determine the system stability.

[0083] Figure 2 It is a structure diagram of the DC bus microgrid.

[0084] The distributed power source, electric ship, energy storage device and load are connected in parallel by using a common DC bus; at the same time, the DC bus voltage of the mobile port DC microgrid cluster is stepped down and transmitted to the energy storage battery of the electric ship through a bidirectional DC / DC device; a buck converter is connected between the DC bus and the energy storage battery.

[0085] The mathematical model expression of the Buck converter is as follows:

[0086]

[0087]

[0088] Among them, V g is the input voltage, V o is the output voltage, D is the duty cycle, C, L, R SR and R L respectively represent the capacitance, inductance, parasitic resistance of the converter and the load connected to the output end.

[0089] The overall transfer function of the double-loop control of the Buck converter can be expressed by the following equation:

[0090]

[0091] Figure 3 It is the structure diagram of multi-mode adaptive droop control.

[0092] The decentralized power sharing of the mobile port DC microgrid cluster based on multiple shipboard microgrids is realized through the multi-mode adaptive droop control method. The power control strategy of the entire DC microgrid cluster is coordinated so that the microgrids can operate independently or provide power support to each other.

[0093] The multi-mode droop control method realizes decentralized power sharing among different shipboard microgrids. Adopting V-I droop control at the lowest or highest threshold of SOC helps to improve the stability margin of the system. On the contrary, the I-V droop mode works when SOC is lower than the lowest threshold or higher than the highest threshold to enhance the transient response. To achieve resource balance and effectively utilize resources, the SOC variation function is set as the droop value. The shipboard microgrid will reasonably share energy according to the energy storage SOC. To extend the service life of the battery, energy balance and optimal power distribution need to be achieved. The power distribution among each ship microgrid (SMG) is divided into three modes according to the state (SOC) of the battery pack. As Figure 3 shown, these modes include: current control charging mode (0 ≤ SOC j < SOC min ), voltage-current droop control mode (SOC min ≤ SOC j < SOC max ), and current control discharge mode (SOC max ≤ SOC j < 100).

[0094] Mode 1: Shipboard microgrid power control charging mode:

[0095] In each shipboard microgrid (SMG), the state (SOC) of the battery represents the availability of energy. If the SOC of a certain microgrid is lower than the minimum threshold, i.e., SOC j < SOC min , it indicates that the resources of this shipboard microgrid are insufficient. Therefore, the charging station of this shipboard microgrid will start to draw energy from the DC bus to charge the energy storage battery. In the current control mode, the shipboard microgrid will absorb power according to the reference value calculated by formula (5). The PI controller of the internal loop will generate the duty cycle, and the battery will start charging until the minimum threshold is reached.

[0096]

[0097] Among them, I ratis the rated output current.

[0098] Mode 2: Shipboard microgrid voltage and current droop control:

[0099] The distributed control V-I algorithm based on the battery SOC is as Figure 3 shown. The DC bus voltage (VB) indicates whether one or more shipboard microgrids are resource-rich or resource-scarce. If VB is higher than the reference value (Vo), it indicates that one or more shipboard microgrids are resource-rich; while if VB is lower than the reference value (Vo), it indicates that one or more shipboard microgrids are resource-scarce. When the SOC of the battery packs in different shipboard microgrids is between the minimum set value and the maximum set value, i.e., SOCmin <= SOCj < SOCmax, it indicates that the shipboard microgrid is self-sufficient in resources and power will not be shared. Such charge and discharge droop values can be expressed by Equation (7) and Equation (9) respectively. In addition, if a newly docked ship is connected to the DC bus and needs power, all shipboard microgrids will share power according to their resource availability, and the shipboard microgrid with a higher SOC will share more power.

[0100] Charging:

[0101] I ref = K c (V ref - V o ) (6)

[0102]

[0103] Discharging:

[0104] I ref = K d (V ref - V o ) (8)

[0105]

[0106] Mode 3: Shipboard microgrid current control discharge mode:

[0107] When the SOC of the battery in the shipboard microgrid exceeds the set maximum limit, i.e., SOCj >= SOCmax, it indicates that the shipboard microgrid has sufficient resources and is capable of sharing power for resource-scarce shipboard microgrids. This situation occurs when the battery pack of a certain shipboard microgrid is already fully charged and there is no load demand. Therefore, to meet the mobile energy storage shore power system, this shipboard microgrid will share power with nearby shipboard microgrids according to the reference value shown in Equation (10).

[0108]

[0109] Figure 4It is a small-signal analysis result graph. Figure 4 Perform small-signal analysis on the control system of Mode 2 of the multi-mode adaptive droop control. The SOC of SMG1 increases from 31% to 55%, and the SOC of SMG2 increases from 58% to 79%. Figure 4 When the battery pack shown is charged, i.e., the SOC increases, the eigenvalues in the s-plane start to move towards the left half-plane, indicating an enhanced stability of the system.

[0110] Figure 5 It is a multi-mode verification result graph. Set the energy storage state SOC of SMG1 to be dynamically adjusted from 22% to 88%, and the charge states of other on-board microgrids are SMG2 = 49.8%, SMG3 = 64.7%, SMG4 = 78.6%, where SOC min = 30%, SOC max = 80% to verify the feasibility of the multi-mode adaptive control scheme. It can be seen from the experimental results that when SMG1 is in Mode 1, the charging current gradually decreases to achieve dynamic current regulation. When SMG1 is in Mode 2, all ships are self-sufficient and do not share power. When SMG1 is in Mode 3, SMG1 discharges, and it can be seen that the larger the SOC, the larger the discharge current, and the more resources there are, the larger the shared power, completing the energy balance among the on-board microgrids.

[0111] The ship energy sharing management method based on multi-mode adaptive droop control proposed by the present invention has construction significance in remote or small ports in inland river basins, effectively avoids overcharging or over-discharging of electric ships, prolongs the service life of the battery, and realizes the SOC balance of each ship in the port microgrid.

Claims

1. Ship energy sharing management method based on multi-mode adaptive droop control, characterized in that It includes the following steps: Step 1: Obtain the data of the shipboard microgrid; Step 2: Parallelize multiple electric ships to a DC microgrid, and use the shipboard microgrid data obtained in Step 1 to construct a DC microgrid cluster; Step 3: Apply multi-mode adaptive droop control to the DC microgrid cluster constructed in Step 2 to coordinate the power control strategy of the entire DC microgrid cluster.

2. The ship energy sharing management method based on multi-mode adaptive droop control according to claim 1, characterized in that: Step 4: On the basis of Step 3, build a small-signal analysis model for the DC microgrid cluster to determine the system stability.

3. The method for ship energy sharing management based on multi-mode adaptive droop control according to claim 1, characterized in that: In the said Step 1, it includes processing the shipboard microgrid data, specifically as follows: 1) Confirm the types of connected electric ships: The connected electric ships are divided into fuel ships, electric ships with power sharing, and electric ships without power sharing; 2) Estimate the state of charge (SOC) of the energy storage; Adopt the Coulomb counting method, and use the integral of the measured current and time to obtain the SOC; In Equation (1), SOC j (t) represents the calculated value of the battery SOC; SOC i (0) represents the SOC value of the battery under the initial state; C is the battery capacity; V0, I in respectively represent the DC bus voltage and the battery output current; I L represents the current output from the shipboard microgrid to the DC bus; T represents the time variable.

4. The method for ship energy sharing management based on multi-mode adaptive droop control according to claim 1, wherein: In the said Step 2, a common DC bus is used to parallelly combine distributed power sources, electric ships, energy storage devices and loads together; at the same time, the DC bus voltage of the DC microgrid cluster is stepped down and transmitted to the energy storage battery of the electric ship through a bidirectional DC / DC device; a buck converter is connected between the DC bus and the energy storage battery; The mathematical model expression of the buck converter is as follows: In the above formula, i L represents the inductor current; V g represents the input voltage, V o represents the output voltage, D represents the duty cycle; C, L, R SR and R L respectively represent the capacitor, inductor, parasitic resistance of the buck converter, and the load connected to the output terminal; The overall transfer function of the double-loop control of the buck converter is expressed as the following equation:

5. The method for ship energy sharing management based on multi-mode adaptive droop control according to claim 1, wherein: In the said Step 3, through the multi-mode adaptive droop control method, decentralized power sharing is realized among different shipboard microgrids; when the SOC is at the lowest or highest threshold, V-I droop control is adopted, which helps to improve the stability margin of the system; on the contrary, when the SOC is lower than the lowest threshold or higher than the highest threshold, the I-V droop mode is adopted to enhance the transient response.

6. The method for managing ship energy sharing based on multi-mode adaptive droop control according to claim 5, characterized in that: In order to achieve resource balance and effectively utilize resources, the SOC change function is set as the droop value; specifically as follows: V o = U dc - I o R D wherein, R D is a drooping resistor; The charging current is expressed as follows: I ref = (V dc - V o ) / R c The discharging current is expressed as follows: I ref = (V dc - V o ) / R d 7. The ship energy sharing management method based on multi-mode adaptive droop control according to claim 6, characterized in that: The shipboard microgrid will reasonably share energy according to the SOC of the energy storage; in order to extend the service life of the battery, it is necessary to achieve energy balance and optimal power distribution; The power distribution among each shipboard microgrid is divided into three modes according to the state SOC of the battery pack; these modes include: ①. Current control charging mode: 0 ≤ SOC j <SOC min ; ②. V-I droop control mode: SOC min ≤ SOC j < SOC max ; ③. Current-controlled discharge mode: SOC max ≤SOC j <100; Among them, SOC j represents the state of charge of the battery, and SOC min represents the minimum state of charge threshold of the set battery, and SOC max represents the maximum state of charge threshold of the battery.

8. The method for ship energy sharing management based on multi-mode adaptive droop control according to claim 2, wherein: In the said Step 4, analyze the influence of the PI controller of the power compensation link introduced by the multi-mode adaptive droop control on the small-signal stability of the DC microgrid cluster, specifically including: For the DC / DC converter i adopting improved droop control, the state variables of the buck converter are selected as x i (t) = [Δv Ci , Δi Li , Δi oi , Δg ui , Δg ii , Δg di T , Δv Ci represents the small-signal variable of the capacitor voltage at the output of the converter of the micro-source i; Δi Li represents the small-signal variable of the inductor current at the output of the converter of the micro-source i; Δi oi represents the small-signal variable of the output current at the output of the converter of the micro-source i; Δg ui represents the transfer function variable of the voltage PI controller of the micro-source i, Δg ii represents the transfer function variable of the current PI controller of the micro-source i, Δg di represents the working value of the compensation-link PI controller of the micro-source i; T represents the state variable;​ For micro-source j, there is x j (t) = [Δv Cj , Δi Lj , Δi oj , Δg uj , Δg ij , Δg dj T , Δv Cj represents the small-signal variable of the voltage at the outlet of micro-source j; Δi Lj represents the small-signal variable of the inductor current at the outlet of the converter of micro-source j; Δi oj represents the small-signal variable of the output current at the outlet of the converter of micro-source j; Δg uj represents the transfer function variable of the voltage PI controller of micro-source j; Δg ij represents the transfer function variable of the current PI controller of micro-source j; Δg dj represents the working value of the PI controller of the compensation link of micro-source j; In addition, Δv eq and Δi eq are used as the state variables x s (t) = [Δv eq , Δi eq T , Δv eq represents the small-signal variable of the capacitor voltage at the outlet of the converter on the constant power load side, and Δi eq represents the small-signal variable of the current at the outlet of the converter on the constant power load side; Therefore, the state variables of the entire microgrid system can be recorded as x(t) = [x i (t), x j (t), x s (t)] T , and x(t) is a 14th-order column vector.​​ 9. The method for managing ship energy sharing based on multi-mode adaptive droop control according to claim 8, characterized in that: Simplify the islanded DC microgrid into an equivalent model including multiple DC / DC converters using improved droop control, line impedance, resistive load and equivalent constant power load; In the above formula, i eq represents the output current of the load-side DC converter, C eq represents the equivalent capacitance of the load-side DC converter, v eq represents the output voltage of the load-side DC converter, i CPL represents the constant power load current, P CPL represents the equivalent constant power load power, v bus represents the DC bus voltage, R eq represents the equivalent line resistance, L eq represents the equivalent line inductance, i ok represents the output current of the k-th micro-source, and k represents k micro-sources; Substitute \(i\) in the first equation of Equation (6) CPL (v eq ) and perform a Taylor expansion at the steady-state value \(V\) eq : In the above formula, i CPL (v eq ) represents the constant power load current at the time of the v eq variable, and i CPL (V eq ) represents the constant power load current at the time of the steady-state value Veq, where V eq represents the steady-state value Veq, and represents an infinitesimal of higher order; Among them, O is the remainder term, and this remainder term is ignored, and then we get: In the above formula, △i CPL represents the small-signal quantity of the load-side current; Furthermore, the state equation of v is obtained from Equation (5) and Equation (7): eq ​ In the above formula, △v eq represents the small-signal quantity of the output voltage of the DC converter on the constant-power load side, and △i eq represents the small-signal quantity of the output current of the DC converter on the constant-power load side; To derive the state equation of i oi , where i oi represents the output current of the micro-source i; First, derive the small-signal quantity v of the bus voltage bus , obtained according to Equation (5): △v bus = R Re (△i oi + △i oj - △i eq )(9); In the above formula, △v bus represents the small signal quantity of the bus voltage, R Re represents the equivalent line constant resistance load, △i oi represents the small signal quantity of the output current of micro-source i, △i oj represents the small signal quantity of the output current of micro-source j; Combining Equation (5) and Equation (9) can obtain the eq state equation of i: In the above formula, R eq represents the equivalent circuit resistance.

10. The method for ship energy sharing management based on multi-mode adaptive droop control according to claim 9, wherein: According to each state equation, the characteristic matrix A can be obtained, and this characteristic matrix A is a 14th-order square matrix; therefore, the small-signal model of this islanded DC microgrid can be obtained as: In the above formula, represents the small-signal model of the microgrid, x(t) represents the state vector, B is the input matrix, and u(t) = [Δv si , Δv sj T , Δv si represents the state variable of the outlet voltage of micro-source i, and Δv sj represents the state variable of the outlet voltage of micro-source j.​

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