A method and system for collaborative enhancement of port microgrid and ship energy system

Abstract

The present disclosure relates to the technical field of multi-energy coordinated scheduling of microgrids, and discloses a method and system for enhancing the coordination between a port microgrid and a ship energy system. The specific implementation scheme is as follows: based on the ship automatic identification system data, the measured extreme weather data and the port power system status, the real-time requested power supply of the port under extreme weather conditions and the actual power supply of the ship's reverse power supply are predicted; based on the real-time requested power supply and the actual power supply, the minimum operating cost and resilience coordination index of the port are calculated to determine the power purchase price; based on the power purchase price and the ship's maximum profit objective function, the agreed power supply of the ship's reverse power supply is determined; based on the real-time requested power supply and the agreed power supply, the real-time power supply of the port's power generation equipment is determined. The present disclosure can improve the robustness of the coordination strategy.

Description

Technical Field

[0001] The present disclosure relates to the technical field of microgrid multi-energy coordinated scheduling, and in particular to a method and system for enhancing the coordination between a port microgrid and a ship energy system. Background Art

[0002] Ports are a highly concentrated industry with high load consumption. Meanwhile, the contradiction between economic development and environmental protection is becoming increasingly prominent. Building and developing green ports has become a common consensus within the port industry. The accelerating and intensifying nature of extreme weather events has fundamentally altered the operational risk profile of global offshore energy infrastructure, posing unprecedented synergistic threats to port microgrids and ship power systems.

[0003] Related technologies fail to reconcile the dichotomy between millisecond-level dynamic response of ships and hourly-level port planning, leading to the failure of critical energy reciprocity during extreme weather. Furthermore, ship power management ignores the intermittent nature of port renewable energy, while port microgrids fail to account for fluctuations in ship hydrodynamic loads. Summary of the Invention

[0004] In order to solve the above technical problems, the present disclosure provides a method for collaboratively enhancing a port microgrid and a ship energy system, comprising the following steps:

[0005] Based on the ship automatic identification system data, the measured extreme weather data and the port power system status, the real-time requested power supply of the port under extreme weather conditions and the actual power supply of the ship's reverse power supply are predicted; based on the real-time requested power supply and the actual power supply, the minimum operating cost and resilience coordination index of the port are calculated to determine the power purchase price; based on the power purchase price and the ship's maximum profit objective function, the agreed power supply for the ship's reverse power supply is determined; based on the real-time requested power supply and the agreed power supply, the real-time power supply of the port's power generation equipment is determined.

[0006] Furthermore, the method of predicting the real-time requested power supply of the port and the actual power supply of the ship's reverse power supply under extreme weather conditions based on the ship automatic identification system data, the measured extreme weather data and the port power system status includes:

[0007] Determine a physical information digital twin fusion model; input ship automatic identification system data, measured extreme weather data and port power system status into the physical information digital twin fusion model to obtain the real-time requested power supply of the port under extreme weather conditions and the actual power supply of the ship's reverse power supply.

[0008] Furthermore, determining the physical information digital twin fusion model includes:

[0009] According to extreme weather data, the adaptive fusion parameters of fluid dynamics and long-short-term memory artificial neural network are determined respectively, and the sum of the adaptive fusion parameters of the fluid dynamics and the adaptive fusion parameters of the long-short-term memory artificial neural network is 1; the observation operator is determined according to the fluid dynamics and the long-short-term memory artificial neural network and their respective corresponding adaptive fusion parameters; according to the observation operator, the fluid dynamics and the long-short-term memory artificial neural network, a data-physics fusion model is constructed; historical data is obtained, the data-physics fusion model is trained, and a physical information digital twin fusion model is obtained.

[0010] Furthermore, the acquisition of historical data, training of the data-physics fusion model, and obtaining of the physical information digital twin fusion model include:

[0011] The historical data of different time scales are fused; the long-short-term memory artificial neural network is trained based on the fused historical data to obtain a long-short-term memory ship trajectory prediction model, and the fluid dynamics is trained based on the fused historical data to obtain a ship wave force offset prediction model; according to the observation operator, the long-short-term memory ship trajectory prediction model and the ship wave force offset prediction model are fused to obtain a physical information digital twin fusion model.

[0012] Furthermore, the obtaining of historical data includes:

[0013] After removing abnormal data from the acquired historical data of the ship automatic identification system, extreme weather historical data, port power system status historical data, and power grid status historical data, they are aligned based on timestamps to obtain historical data.

[0014] Furthermore, the calculating of the minimum operating cost and resilience coordination index of the port and determining the power purchase price based on the real-time requested power supply and the actual power supply includes:

[0015] The expenditure on purchasing electricity from the ship is calculated based on the real-time requested power supply; the minimum operating cost of the port is determined based on the fuel cost of the diesel generator of the energy storage system, the cost of using the energy storage system equipment and the expenditure; based on the actual power supply, the support ratio of the ship to the reverse power supply of the key loads of the port is determined; the resilience coordination index is calculated based on the support ratio, the power supply speed of the ship in response to the port and the frequency deviation of the power grid; the purchase price of the electricity purchased by the port from the ship is determined based on the minimum operating cost and the resilience coordination index.

[0016] Furthermore, determining the agreed power supply amount of the ship's reverse power supply based on the power purchase price and the ship's maximum profit objective function includes:

[0017] Obtain an hourly reverse power supply plan for the ship, and minimize the deviation between the ship's real-time power supply and the port's real-time requested power supply based on the power supply plan; determine the voltage at the common coupling point between the ship and the port; obtain the ship's own state, and calculate the ship's maximum profit objective function based on the power purchase price, with the minimization of the deviation, the common coupling point voltage, and the ship's own state as constraints, to determine the agreed power supply for the ship's reverse power supply.

[0018] Furthermore, after determining the real-time power supply of the port power generation equipment according to the real-time requested power supply and the agreed power supply, the method further includes:

[0019] Obtain a first instantaneous frequency of the real-time power supply and a second instantaneous frequency of the protocol power supply; calculate a frequency deviation between the first instantaneous frequency and the second instantaneous frequency; and when the frequency deviation is greater than a set threshold, redetermine the protocol power supply based on the frequency deviation.

[0020] According to another aspect of the present disclosure, a system for collaboratively enhancing a port microgrid and a ship energy system is provided, the system comprising:

[0021] The prediction module is used to predict the real-time requested power supply of the port and the actual power supply of the ship's reverse power supply under extreme weather conditions based on the ship's automatic identification system data, the measured extreme weather data and the port's power system status; the determination module is used to calculate the port's minimum operating cost and resilience coordination index and determine the power purchase price based on the real-time requested power supply and the actual power supply; determine the agreed power supply of the ship's reverse power supply based on the power purchase price and the ship's maximum profit objective function; and determine the real-time power supply of the port's power generation equipment based on the real-time requested power supply and the agreed power supply.

[0022] Furthermore, the prediction module is used to:

[0023] Determine a physical information digital twin fusion model; input ship automatic identification system data, measured extreme weather data and port power system status into the physical information digital twin fusion model to obtain the real-time requested power supply of the port under extreme weather conditions and the actual power supply of the ship's reverse power supply.

[0024] The embodiments of the present disclosure have the following technical effects:

[0025] The method for collaborative enhancement of the port microgrid and the ship energy system provided by the present disclosure predicts the real-time requested power supply of the port and the actual power supply of the ship's reverse power supply under extreme weather conditions through the data of the ship's automatic identification system, the measured extreme weather data and the status of the port power system, which can improve the prediction accuracy of the real-time requested power supply and the actual power supply of the ship's reverse power supply under extreme weather scenarios. Secondly, by calculating the minimum operating cost and resilience coordination index of the port based on the real-time requested power supply and the actual power supply, and determining the power purchase price, the resilience coordination index combined with the minimum operating cost can quantify the 22% improvement in the recovery speed of the port ship energy system under extreme weather conditions. Furthermore, based on the power purchase price and the maximum profit objective function of the ship, the agreed power supply of the ship's reverse power supply is determined, and based on the real-time requested power supply and the agreed power supply, the real-time power supply of the port power generation equipment is controlled to realize a closed-loop strategy of prediction, game, agreement and control, thereby achieving the goal of enhanced coordination between the port and ship energy systems, shortening the power outage time of the port under the influence of extreme weather, and improving the robustness of the coordination strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0027] Figure 1 This is a flow chart of a method for collaboratively enhancing a port microgrid and a ship energy system provided by an embodiment of the present invention;

[0028] Figure 2 This is an evolution trajectory diagram of the coordinated enhancement of the port microgrid and the ship energy system provided by an embodiment of the present invention;

[0029] Figure 3 A structural schematic diagram of a port microgrid and ship energy system collaborative enhancement system provided by an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0030] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention are described clearly and completely below. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are considered to be within the scope of the present invention.

[0031] Ports are a highly concentrated industry with high load consumption. Meanwhile, the contradiction between economic development and environmental protection is becoming increasingly prominent. Building and developing green ports has become a common consensus within the port industry. The accelerating and intensifying nature of extreme weather events has fundamentally altered the operational risk profile of global offshore energy infrastructure, posing unprecedented synergistic threats to port microgrids and ship power systems.

[0032] Among them, traditional resilience strategies developed for isolated land microgrids or ocean-going ships are seriously inadequate when applied to port-ship coupled ecosystems. Significant progress in the resilience of isolated systems has instead exacerbated the coordination challenges of port-ship interfaces.

[0033] Based on this, this application proposes a method and system for collaboratively enhancing port microgrids and ship energy systems. By using ship automatic identification system data, measured extreme weather data, and the port power system status, the method predicts the port's real-time requested power supply and the actual amount of reverse power supplied by the ship during extreme weather conditions. Based on the real-time requested power supply and the actual amount of reverse power supplied by the ship, a power purchase game between the port and the ship is established, maximizing the interests of both the port and the ship. This method achieves the goal of enhanced coordination between the port and ship energy systems, shortens port power outages under extreme weather conditions, and improves the robustness of the coordination strategy.

[0034] Figure 1 This is a flow chart of the method for collaboratively enhancing the port microgrid and ship energy system provided by an embodiment of the present invention. Figure 1 , including the following steps:

[0035] In step S11, the real-time requested power supply of the port under extreme weather conditions and the actual power supply of the ship's reverse power supply are predicted based on the ship automatic identification system data, the measured extreme weather data and the port power system status.

[0036] In this disclosure, Automatic Identification System (AIS) data includes information such as a ship's automatically exchanged position, speed, heading, and name. Measured extreme weather data includes 24-hour extreme weather data, such as 24-hour typhoon path and wind speed data. Port power system status may include parameters such as voltage amplitude, load curve, and remaining power.

[0037] Furthermore, during extreme weather, ships can supply power to ports. This allows prediction of the port's real-time power supply requirements and the actual power supply provided by ships in return during extreme weather conditions based on current ship automatic identification system data, measured extreme weather data, and the port's power system status. In this disclosure, this information can also be used to predict the locations of potential port and ship faults and port load fluctuations during extreme weather conditions.

[0038] The reverse power supply of the ship is the power supply forecasted by the ship to the port, which can also be understood as the predetermined ideal reverse power supply of the ship to the port when extreme weather occurs.

[0039] In step S12, the minimum operating cost and resilience coordination index of the port are calculated based on the real-time requested power supply and the actual power supply, and the power purchase price is determined.

[0040] In the disclosed embodiment, based on the predicted locations of possible faults and load fluctuations under extreme weather conditions, and taking into account a comprehensive range of factors including the future charge and discharge curves of the port energy storage system, the startup of the standby units, the real-time requested and actual power supply of the port, and the deactivation of non-critical loads, the objective function of the minimum operating cost and its resilience coordination index are calculated, thereby determining the purchase price of electricity from the ships.

[0041] The resilience coordination index can be understood as a measure of the coordination ability of ports and ships in extreme weather conditions. A higher value indicates a stronger system resilience. The resilience coordination index is expressed as follows:

[0042]

[0043] Where, represents the resilience coordination index, Indicates the energy transmitted in emergency situations, represents the total critical load demand of the port during period k, Indicates the control instruction synchronization delay, Indicates the duration of extreme weather conditions, Absolute value of frequency deviation, η , ξ , ζ Both represent calibration factors.

[0044] In step S13, the agreed power supply amount of the ship's reverse power supply is determined according to the power purchase price and the ship's maximum profit objective function.

[0045] In this disclosure, the ship's maximum revenue objective function is calculated based on the port's published electricity purchase price, combined with the ship's remaining power limit, the ship's equipment status, and the port-ship coupling point voltage. This determines the agreed amount of power supplied for the ship's reverse power supply. Specifically, the amount of power supplied by the ship to the port is determined based on the current port's published electricity purchase price.

[0046] In step S14, the real-time power supply of the port power generation equipment is determined according to the real-time requested power supply and the agreed power supply.

[0047] In the embodiment of the present disclosure, the real-time power supply provided by the port power generation equipment is updated in real time according to the agreed power supply of the ship and the real-time power supply requested by the port.

[0048] Among them, if the real-time power supply provided by the port's power generation equipment is insufficient, non-critical loads can be disabled to reduce power usage.

[0049] Furthermore, a first instantaneous frequency of the real-time power supply and a second instantaneous frequency of the protocol power supply may be obtained, and a frequency deviation between the first instantaneous frequency and the second instantaneous frequency may be calculated. When the frequency deviation is greater than a set threshold, the protocol power supply is re-determined based on the frequency deviation.

[0050] The frequency deviation is expressed as follows:

[0051]

[0052] Where, represents the frequency deviation at time t, represents the frequency synchronization error at time t, represents the real-time frequency of the port power grid at time t, represents the real-time frequency of the ship's reverse power supply at time t, represents the proportional gain, represents the integral gain, represents the differential gain, Indicates the frequency synchronization error at the current moment.

[0053] The method for collaborative enhancement of the port microgrid and the ship energy system provided by the present disclosure predicts the real-time requested power supply of the port and the actual power supply of the ship's reverse power supply under extreme weather conditions through the data of the ship's automatic identification system, the measured extreme weather data and the status of the port power system, which can improve the prediction accuracy of the real-time requested power supply and the actual power supply of the ship's reverse power supply under extreme weather scenarios. Secondly, by calculating the minimum operating cost and resilience coordination index of the port based on the real-time requested power supply and the actual power supply, and determining the power purchase price, the resilience coordination index combined with the minimum operating cost can quantify the 22% improvement in the recovery speed of the port ship energy system under extreme weather conditions. Furthermore, based on the power purchase price and the maximum profit objective function of the ship, the agreed power supply of the ship's reverse power supply is determined, and based on the real-time requested power supply and the agreed power supply, the real-time power supply of the port power generation equipment is controlled to realize a closed-loop strategy of prediction, game, agreement and control, thereby achieving the goal of enhanced coordination between the port and ship energy systems, shortening the power outage time of the port under the influence of extreme weather, and improving the robustness of the coordination strategy.

[0054] In this disclosure, the port and ship power coupling system is represented by the following formula:

[0055]

[0056] Where, represents the state of the port and ship power coupling system at time t, represents the system state vector at time t, represents the port control input power at time t, Indicates the port control input power, represents the ship control input power at time t, Indicates the ship control input power, represents the disturbance caused by the weather at time t.

[0057] Among them, the function f It is used to describe the differential changes of the system status, port control input power, ship control input power and weather-induced disturbances in the port and ship power coupling system at time t.

[0058] In the embodiment of the present disclosure, a physical information digital twin fusion model can be determined in advance, so that the ship automatic identification system data, the measured extreme weather data and the port power system status are input into the physical information digital twin fusion model to obtain the real-time requested power supply of the port under extreme weather conditions and the actual power supply of the ship's reverse power supply.

[0059] Furthermore, adaptive fusion parameters for the fluid dynamics and long-short-term memory artificial neural networks can be determined based on extreme weather data, with the sum of the adaptive fusion parameters for the fluid dynamics and the long-short-term memory artificial neural networks being 1. An observation operator is determined based on the fluid dynamics and long-short-term memory artificial neural networks and their corresponding adaptive fusion parameters. A data-physics fusion model is constructed based on the observation operator, the fluid dynamics, and the long-short-term memory artificial neural network. Historical data is acquired, and the data-physics fusion model is trained to produce a physical information digital twin fusion model.

[0060] For example, the adaptive fusion parameter for fluid dynamics in extreme weather conditions can be 0.7, and the adaptive fusion parameter for the long short-term memory artificial neural network can be 0.3. Generally, the adaptive fusion parameter for fluid dynamics in extreme weather conditions can be 0.3, and the adaptive fusion parameter for the long short-term memory artificial neural network can be 0.7.

[0061] The expression of the observation operator is as follows:

[0062]

[0063] Where, represents the observation operator, represents the adaptive fusion parameter of fluid dynamics, represents a physical simulation of fluid dynamics, Represents environmental parameters, Indicates the status of the ship. represents the data-driven long short-term memory artificial neural network, Indicates the ship automatic identification system data, Indicates the status of the port power system, Denotes the predicted target variable.

[0064] In this disclosure, the resulting physical-information digital twin fusion model can be tested using hardware-in-the-loop testing. For example, the physical-information digital twin fusion model can be tested by simulating a 300% load step change during a typhoon eye passage and synchronous fault recovery under a 2.5Hz frequency deviation.

[0065] Furthermore, historical data from different time scales can be fused and a long-short-term memory artificial neural network trained based on the fused historical data to obtain a long-short-term memory ship trajectory prediction model. The fluid dynamics model can then be trained based on the fused historical data to obtain a ship wave force offset prediction model. Based on the observation operator, the long-short-term memory ship trajectory prediction model and the ship wave force offset prediction model are fused to obtain a physical information digital twin fusion model.

[0066] Among them, the historical data of different time scales are integrated to obtain heterogeneous data streams. The expression is as follows:

[0067]

[0068] Where, Contains ship position / speed from Automatic Identification System, For ECMWF weather ensemble, is the phasor measurement unit data, Indicates the port equipment status.

[0069] The expression of the physical information digital twin fusion model is as follows:

[0070]

[0071] represents the fluid mechanics model, represents power system simulation, represents the prediction of the neural network based on the observed operator trajectory, Represents meteorological data, Indicates ship dynamic information. Represents the tensor fusion of multimodal data, V represents the ship speed, W represents the wave height, Represents the physical-data fusion digital twin model, x Represents input data, t Indicates time, θ Represents the phase angle.

[0072] In the disclosed embodiment, it is also necessary to remove abnormal data from the acquired historical data of the ship automatic identification system, extreme weather historical data, port power system status historical data, and power grid status historical data, and align them based on timestamps to obtain historical data.

[0073] In the present disclosure, data for a certain region for one year may be selected as historical data.

[0074] In the embodiment of the present disclosure, the minimum operating cost and resilience coordination index of the port are calculated based on the real-time requested power supply and the actual power supply, and the implementation method for determining the power purchase price is as follows.

[0075] The cost of purchasing electricity from ships is calculated based on the real-time power supply requests. The port's minimum operating cost is determined based on the energy storage system's diesel generator fuel costs, the energy storage system equipment costs, and the cost of the power supply. The proportion of reverse power provided by ships to critical port loads is determined based on the actual power supply. The resilience coordination index is calculated based on the support ratio, the speed at which ships respond to the port's power supply requests, and the grid frequency deviation. The minimum operating cost and the resilience coordination index are used to determine the price at which the port can purchase electricity from ships.

[0076] In this embodiment, the minimum sum of the minimum operating cost and the resilience coordination index can be solved, that is, the port control input (such as energy storage scheduling, diesel engine start and stop, etc.) is optimized to determine the price of electricity purchased by the port from the ship. The expression for minimizing the supply and demand imbalance and voltage deviation is as follows:

[0077]

[0078] Where, represents the minimization of port control input, Indicates that the time step is 24 hours, represents the port operating cost, is a resilience synergy indicator, α , β is the weight coefficient, represents the toughness target value,

[0079] In the embodiment of the present disclosure, the following implementation method will provide a detailed description of determining the agreed power supply amount of the ship's reverse power supply based on the power purchase price and the maximum profit objective function of the ship.

[0080] Obtain the ship's hourly reverse power supply plan, and minimize the deviation between the ship's real-time power supply and the port's real-time requested power supply based on the power supply plan; determine the voltage at the common coupling point between the ship and the port; obtain the ship's own status, and use the minimization of the deviation, the common coupling point voltage, and the ship's own status as constraints. According to the power purchase price, calculate the ship's maximum profit objective function and determine the agreed power supply for the ship's reverse power supply.

[0081] The voltage at the common coupling point is stabilized at 1.0 pu to prevent voltage collapse and cascading failures.

[0082] The expression constrained by minimizing the deviation, the voltage at the common coupling point, and the ship's own state is as follows:

[0083]

[0084] Where, represents minimizing the supply-demand imbalance and voltage deviation, Indicates that the time step is 60 seconds, represents the actual power supply of the ship during period m, represents the requested power supply of the port in period m, is the voltage at the point of common coupling, γ and δ Represents the penalty weight.

[0085] For example, the port publishes the electricity purchase price to the ship and purchases electricity from the ship. Then the ship feeds back the amount of power it can provide to the port based on multiple factors, thus conducting multiple games. Figure 2 This is the evolution trajectory diagram of the coordinated enhancement of the port microgrid and the ship energy system provided by the embodiment of the present invention. Figure 2 , showing convergence to a stable Nash equilibrium within 45 iterations under a storm scenario, compared to 82 iterations required by conventional methods. The collaborative resilience index peaked at 0.78 during coordinated ship-port power transfer. These optimizations fundamentally altered the fault propagation dynamics: PMU data confirmed that under coordinated control, voltage deviation propagation delay increased from a baseline of 8–12 minutes to 18–22 minutes, a critical buffer for enabling corrective actions.

[0086] Based on Figure 1 The same principle as shown in the method, Figure 3 FIG. 1 shows a schematic diagram of a structure of a port microgrid and a ship energy system collaborative enhancement system provided by an embodiment of the present disclosure, as shown in FIG. Figure 3 As shown, the port microgrid and ship energy system collaborative enhancement system 300 may include:

[0087] The prediction module 301 is used to predict the real-time requested power supply of the port and the actual power supply of the ship's reverse power supply under extreme weather conditions based on the ship's automatic identification system data, the measured extreme weather data and the port's power system status; the determination module 302 is used to calculate the port's minimum operating cost and resilience coordination index and determine the power purchase price based on the real-time requested power supply and the actual power supply; determine the agreed power supply of the ship's reverse power supply based on the power purchase price and the ship's maximum profit objective function; and determine the real-time power supply of the port's power generation equipment based on the real-time requested power supply and the agreed power supply.

[0088] In the present disclosure, the prediction module 301 is used to determine the physical information digital twin fusion model; the ship automatic identification system data, the measured extreme weather data and the port power system status are input into the physical information digital twin fusion model to obtain the real-time requested power supply of the port under extreme weather and the actual power supply of the ship's reverse power supply.

[0089] In the present disclosure, the determination module 302 is used to determine the adaptive fusion parameters of fluid dynamics and long-short-term memory artificial neural networks respectively based on extreme weather data, and the sum of the adaptive fusion parameters of the fluid dynamics and the adaptive fusion parameters of the long-short-term memory artificial neural network is 1; determine the observation operator based on the fluid dynamics and the long-short-term memory artificial neural network and their respective corresponding adaptive fusion parameters; construct a data-physics fusion model based on the observation operator, the fluid dynamics and the long-short-term memory artificial neural network; obtain historical data, train the data-physics fusion model, and obtain a physical information digital twin fusion model.

[0090] In the present disclosure, the determination module 302 is used to fuse the historical data of different time scales; train the long-short-term memory artificial neural network based on the fused historical data to obtain a long-short-term memory ship trajectory prediction model, and train the fluid dynamics based on the fused historical data to obtain a ship wave force offset prediction model; according to the observation operator, fuse the long-short-term memory ship trajectory prediction model and the ship wave force offset prediction model to obtain a physical information digital twin fusion model.

[0091] In the present disclosure, the determination module 302 is used to eliminate abnormal data from the acquired historical data of the ship automatic identification system, extreme weather historical data, port power system status historical data and power grid status historical data, and align them based on timestamps to obtain historical data.

[0092] In the present disclosure, the determination module 302 is used to calculate the expenditure cost of purchasing electricity from the ship based on the real-time requested power supply; determine the minimum operating cost of the port based on the fuel cost of the diesel generator of the energy storage system, the cost of using the energy storage system equipment and the expenditure cost; determine the support ratio of the ship to the reverse power supply of the key loads of the port based on the actual power supply; calculate the resilience coordination index based on the support ratio, the power supply speed of the ship in response to the port and the grid frequency deviation; determine the purchase price of electricity for the port from the ship based on the minimum operating cost and the resilience coordination index.

[0093] In the present disclosure, the determination module 302 is used to obtain the power supply plan for the ship's hourly reverse power supply, and minimize the deviation between the ship's real-time power supply and the port's real-time requested power supply according to the power supply plan; determine the voltage of the common coupling point between the ship and the port; obtain the ship's own state, and use the minimization of the deviation, the common coupling point voltage and the ship's own state as constraints, calculate the ship's maximum profit objective function according to the power purchase price, and determine the agreed power supply for the ship's reverse power supply.

[0094] In the present disclosure, the determination module 302 is used to obtain the first instantaneous frequency of the real-time power supply and the second instantaneous frequency of the protocol power supply; calculate the frequency deviation between the first instantaneous frequency and the second instantaneous frequency; when the frequency deviation is greater than a set threshold, re-determine the protocol power supply based on the frequency deviation.

[0095] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. A method for collaboratively enhancing port microgrid and ship energy system, characterized in that: The method comprises: Based on the ship automatic identification system data, measured extreme weather data and the port power system status, the real-time requested power supply of the port and the actual power supply of the ship reverse power supply under extreme weather conditions are predicted; Calculating the minimum operating cost and resilience coordination index of the port based on the real-time requested power supply and the actual power supply, and determining the power purchase price; the resilience coordination index is used to quantify the coordination ability of the port and ships in extreme weather conditions; Determining the agreed power supply amount for the ship's reverse power supply based on the power purchase price and the ship's maximum profit objective function; Determining the real-time power supply of the port power generation equipment according to the real-time requested power supply and the agreed power supply; The calculating the minimum operating cost and resilience coordination index of the port and determining the power purchase price based on the real-time requested power supply and the actual power supply includes: Calculating the cost of purchasing electricity from the ship based on the real-time requested power supply; Determine the minimum operating cost of the port based on the fuel cost of the energy storage system diesel generator, the cost of using the energy storage system equipment, and the aforementioned expenditures; Based on the actual power supply, determining the proportion of reverse power supply provided by the ship to the key loads in the port; Calculating the resilience coordination index based on the support ratio, the speed at which the ship responds to the power supply of the port, and the grid frequency deviation; determining, based on the minimum operating cost and the resilience coordination index, a price at which the port purchases electricity from the ship; The expression of the resilience coordination index is as follows: ； Where, represents the resilience coordination index, Indicates the energy transmitted in emergency situations, represents the total critical load demand of the port during period k, Indicates the control instruction synchronization delay, Indicates the duration of extreme weather conditions, Absolute value of frequency deviation, η , ξ , ζ Both represent calibration factors.

2. The method for collaboratively enhancing the port microgrid and ship energy system according to claim 1 is characterized in that: The method of predicting the real-time requested power supply of the port and the actual power supply of the ship's reverse power supply under extreme weather conditions based on the ship's automatic identification system data, the measured extreme weather data, and the port's power system status includes: Determine the physical information digital twin fusion model; The ship automatic identification system data, measured extreme weather data and port power system status are input into the physical information digital twin fusion model to obtain the real-time requested power supply of the port under extreme weather conditions and the actual power supply of the ship's reverse power supply.

3. The method for collaboratively enhancing the port microgrid and ship energy system according to claim 2, characterized in that: Determining the physical information digital twin fusion model includes: Determining adaptive fusion parameters of fluid dynamics and long short-term memory artificial neural network respectively according to extreme weather data, wherein the sum of the adaptive fusion parameters of fluid dynamics and the adaptive fusion parameters of the long short-term memory artificial neural network is 1; Determining an observation operator based on the fluid dynamics and the long short-term memory artificial neural network and their respective corresponding adaptive fusion parameters; constructing a data-physics fusion model based on the observation operator, the fluid dynamics, and the long-short-term memory artificial neural network; Acquire historical data, train the data-physics fusion model, and obtain a physical information digital twin fusion model.

4. The method for collaboratively enhancing the port microgrid and ship energy system according to claim 3 is characterized in that: The acquiring of historical data, training of the data-physics fusion model, and obtaining of the physical-information digital twin fusion model include: fusing the historical data at different time scales; Training the long-short-term memory artificial neural network based on the fused historical data to obtain a long-short-term memory ship trajectory prediction model, and training the fluid dynamics based on the fused historical data to obtain a ship wave force offset prediction model; According to the observation operator, the long-short-term memory ship trajectory prediction model and the ship wave force offset prediction model are fused to obtain a physical information digital twin fusion model.

5. The method for collaboratively enhancing the port microgrid and ship energy system according to claim 3 is characterized in that: The obtaining of historical data includes: After removing abnormal data from the acquired historical data of the ship automatic identification system, extreme weather historical data, port power system status historical data, and power grid status historical data, they are aligned based on timestamps to obtain historical data.

6. The method for collaboratively enhancing port microgrid and ship energy system according to claim 1, characterized in that: The determining of the agreed power supply amount of the ship reverse power supply according to the power purchase price and the maximum profit objective function of the ship includes: Obtaining an hourly reverse power supply plan for the ship, and minimizing the deviation between the real-time power supply of the ship and the real-time power supply requested by the port according to the power supply plan; Determine the voltage at the point of common coupling between the ship and the port; The ship's own state is obtained, and the maximum profit objective function of the ship is calculated based on the power purchase price, with the minimization of the deviation, the common coupling point voltage and the ship's own state as constraints, to determine the agreed power supply amount of the ship's reverse power supply.

7. The method for collaboratively enhancing port microgrid and ship energy system according to claim 1, characterized in that: After determining the real-time power supply of the port power generation equipment according to the real-time requested power supply and the agreed power supply, the method further includes: Acquire a first instantaneous frequency of the real-time power supply and a second instantaneous frequency of the protocol power supply; Calculating a frequency deviation between the first instantaneous frequency and the second instantaneous frequency; When the frequency deviation is greater than a set threshold, the agreed power supply amount is re-determined based on the frequency deviation.

8. A port microgrid and ship energy system collaborative enhancement system, characterized in that: The system adopts the method for collaboratively enhancing the port microgrid and the ship energy system according to any one of claims 1 to 7, and the system includes: The prediction module is used to predict the real-time requested power supply of the port and the actual power supply of the ship's reverse power supply under extreme weather conditions based on the ship's automatic identification system data, measured extreme weather data, and the port's power system status; A determination module is used to calculate the minimum operating cost and resilience coordination index of the port based on the real-time requested power supply and the actual power supply, and determine the power purchase price; determine the agreed power supply for the ship's reverse power supply based on the power purchase price and the ship's maximum profit objective function; and determine the real-time power supply of the port's power generation equipment based on the real-time requested power supply and the agreed power supply.

9. The port microgrid and ship energy system collaborative enhancement system according to claim 8 is characterized in that: The prediction module is used to: Determine the physical information digital twin fusion model; The ship automatic identification system data, measured extreme weather data and port power system status are input into the physical information digital twin fusion model to obtain the real-time requested power supply of the port under extreme weather conditions and the actual power supply of the ship's reverse power supply.

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