A method and related device for port micro-grid carbon emission reduction accounting

Abstract

The application provides a kind of polymeric regulation and control method for port micro-grid carbon emission reduction accounting and related equipment, target port micro-grid is analyzed, and the mathematical model of each flexible electrical resource is constructed;Determine the logistics operation process arrangement of target port micro-grid based on the mathematical model of each flexible electrical resource, establish the logistics whole-process scheduling model according to the logistics operation process arrangement;According to the logistics whole-process scheduling model, photovoltaic power generation law and energy storage configuration, minimize the target port micro-grid power operation cost and total carbon emission as the goal, construct optimization function and constraint condition, solve the optimization function based on constraint condition, obtain the flexible electrical resource aggregation control result for accounting the total carbon emission of target port micro-grid;Solve the problem that traditional port micro-grid freight flow is difficult to coordinate and dispatch with electrical resource, promote the reasonable allocation of port power resource, while reducing the carbon emission of port micro-grid.

Description

Technical Field

[0001] This invention relates to the field of flexible electrical resource regulation technology, and in particular to a method and related equipment for aggregated regulation of carbon emission reduction accounting in port microgrids. Background Technology

[0002] As a crucial hub in the integrated waterway transportation system, ports play a vital role in promoting basin economic development, optimizing industrial layout, and facilitating opening-up. With the advancement of green port policies, port microgrids are undergoing a comprehensive electrification transformation, with the proportion of flexible energy resources such as electric loading and unloading equipment, electric transport vehicles, distributed renewable energy power generation facilities, and electrochemical energy storage continuously increasing. This transformation improves energy efficiency while reducing carbon emission intensity in port operations. Accurately quantifying the carbon reduction benefits of renewable energy consumption and load regulation will become a key support for ports to participate in the carbon market and achieve environmental premiums. Port microgrids can be viewed as intelligent microgrids with significant control potential within the transportation system. The synergistic optimization of their various flexible resources can not only smooth grid fluctuations but also form low-carbon dispatch strategies based on real-time carbon accounting, contributing to the clean transformation of the regional power grid. Therefore, systematically exploring the adjustable potential of port flexible electrical resources and implementing aggregated regulation is of great significance for building a "port-grid synergy" regional energy system and improving the flexibility, economy, and environmental friendliness of port operations.

[0003] Port microgrids contain diverse flexible electrical resources, including port machinery, temperature-controlled loads, electric heavy trucks, and electrochemical energy storage, each with varying power supply and demand characteristics. Port machinery primarily includes quay cranes, yard cranes, and conveyor belts. Some studies consider the speed regulation capabilities of these machines in their modeling; however, speed control is typically not implemented in current port microgrids. Therefore, some studies treat them as baseload loads, but neither considers their actual operational portability. Temperature-controlled loads, including cold boxes and air conditioners, possess flexible temperature regulation capabilities and generalized energy storage characteristics (i.e., storing cold or hot energy), making them high-quality flexible load resources. Electric heavy trucks, as a type of electric vehicle, are currently studied primarily in residential, commercial, and highway environments, but their operational patterns in ports are unique, with significant differences in scheduling and power demand compared to everyday scenarios. Therefore, port electrical loads exhibit significant differences in characteristics and operating modes, while existing research often focuses on modeling single load types, lacking sufficient consideration for the interaction and aggregation of multiple flexible load types.

[0004] Furthermore, research on the coupled regulation of port logistics and energy is still incomplete. Ports encompass various logistics links, including berth allocation, port machinery scheduling, and electric heavy truck transfer scheduling, all of which are interconnected. With the full electrification of large-scale port logistics equipment, the strong coupling characteristics of logistics and energy are becoming increasingly prominent, leading to a significantly higher complexity in regulation compared to conventional energy systems. Existing research mainly focuses on energy management methods such as electric-driven quay cranes combined with energy storage operation, flexible operation of shore power and refrigerated containers, optimization of container truck charging and discharging, and day-ahead scheduling of hybrid energy storage considering port traffic-energy coupling, in order to reduce port energy consumption and improve port energy utilization efficiency. However, most of the aforementioned research on the coupled regulation of port logistics and energy simplifies the modeling of the logistics side or only solves for a single or a few logistics links, with few studies on the collaborative optimization of the entire logistics process with multiple types of flexible electrical resources. Summary of the Invention

[0005] This invention provides a method and related equipment for aggregated control of carbon emission reduction accounting in port microgrids. Its purpose is to solve the problem that traditional port microgrid freight processes are difficult to coordinate and schedule with electrical resources, promote the rational allocation of port power resources, reduce carbon emissions from port microgrids, and accurately calculate carbon emissions.

[0006] To achieve the above objectives, the present invention provides a method for aggregated control of carbon emission reduction accounting in port microgrids, comprising: Step 1: Analyze the target port microgrid to determine its flexible electrical resources; Step 2: Analyze the adjustable modes of each flexible electrical resource based on its working method, and construct a mathematical model for each flexible electrical resource. Step 3: Determine the logistics operation process arrangement of the target port microgrid based on the mathematical model of each flexible electrical resource, and establish a full-process logistics scheduling model according to the logistics operation process arrangement; Step 4: Based on the logistics whole-process scheduling model, photovoltaic power generation patterns and energy storage configuration, with the goal of minimizing the power operation cost and overall carbon emissions of the target port microgrid, construct an optimization function and constraints. Solve the optimization function based on the constraints to obtain the flexible electrical resource aggregation and control results used to calculate the overall carbon emissions of the target port microgrid.

[0007] Furthermore, the flexible electrical resources of the target port microgrid include: Port machinery is used to transfer cargo from arriving ships to the port storage yard. Electric heavy trucks are used to transport goods from port yards to warehouses; Temperature control loads include air conditioners used to regulate indoor temperatures in port work and living areas, and cold storage containers used to regulate warehouse temperatures. Energy storage devices are used to store photovoltaic power generation.

[0008] Furthermore, the mathematical model for Hong Kong-made machinery is as follows: ; in, Indicates the person in charge of the vessel The rated power of the port machinery used for the work tasks. Indicates a ship The workload assigned to port machinery in freight operations. This indicates the freight efficiency of port machinery. This indicates the electricity consumption for freight transport before the adjustment of port machinery load. This indicates the electricity consumption for freight transport after the adjustment of the port's machinery load.

[0009] Furthermore, the mathematical model for electric heavy-duty trucks includes: The mathematical model for the number of electric heavy trucks in cargo transshipment tasks is as follows: ; in, Indicates completion of the ship The number of electric heavy-duty trucks required for freight transport tasks. Indicates a ship Total freight volume This indicates the transport capacity of the electric heavy-duty truck. Indicates a ship The arrival time of the port, Indicates a ship Departure time; The mathematical model for the working time of an electric heavy-duty truck in completing a cargo transfer task is as follows: ; in, This indicates the working time required for the electric heavy-duty truck to complete the cargo transfer task. This indicates the transportation efficiency of electric heavy-duty trucks. This indicates the additional time lost by electric heavy-duty trucks during transportation operations. The mathematical model for the charging power of electric heavy-duty trucks is as follows: ; in, This indicates the charging power of the electric heavy-duty truck. Indicates that electric heavy trucks are in Charging power at any time This indicates the total number of electric heavy-duty trucks in the port.

[0010] Furthermore, the mathematical model for temperature-controlled loads includes: The power model for air conditioning is as follows: ; in, Indicates air conditioner exist Electric power at any given moment Indicates air conditioner Rated power, Indicates air conditioner Threshold temperature dead zone express Air conditioning The set temperature, express Air conditioning The indoor temperature of the room Indicates the simulation time step; The power model for a cold box is as follows: ; in, Indicates cold box exist Electric power at any given moment Indicates cold box Rated power, Indicates cold box Threshold temperature dead zone express Time Cold Box The set temperature, express Time Cold Box The internal temperature.

[0011] Furthermore, the mathematical model for energy storage devices is as follows: ; in, express The amount of electricity stored in the energy storage device at any time. This indicates the charging efficiency of the energy storage device. This indicates the discharge efficiency of the energy storage device. This indicates the charging power of the energy storage device. This indicates the discharge efficiency of the energy storage device.

[0012] Furthermore, step 3 includes: Based on the ship's arrival and departure timetable, a ship logistics information vector is formed; Based on logistics information vectors, a ship berth usage plan and a logistics operation process arrangement for the target port microgrid are formulated. The logistics operation process arrangement for the target port microgrid includes the specific usage arrangements for port machinery and electric heavy trucks. Based on the logistics operation process of the target port microgrid, a mission spatiotemporal arrangement information matrix for ships is generated; A full-process logistics scheduling model is constructed based on the ship's mission time and space arrangement information matrix.

[0013] Furthermore, based on the logistics operation process of the target port microgrid, a mission spatiotemporal scheduling information matrix for ships is generated, including: Based on the arrival and departure times of ships and the total cargo volume of ships, berth planning results are formulated, including berth duration and berth location. The freight planning results of the gantry crane in the gantry machinery were determined by using a mathematical model of the gantry machinery. Based on the freight planning results of the quay cranes, the allocation ratio coefficients of the yard cranes and conveyor belts of the port machinery, the freight planning results of the yard cranes and conveyor belts are allocated. The freight planning results for electric heavy trucks are determined based on the mathematical model of the number of electric heavy trucks in the freight transfer task and the mathematical model of the working time for electric heavy trucks to complete the freight transfer task. Based on the berth planning results of ships, the freight planning results of gantry cranes, the freight planning results of yard cranes and conveyors, and the freight planning results of electric heavy trucks, a mission spatiotemporal arrangement information matrix for ships is generated.

[0014] Furthermore, the mission spatiotemporal arrangement information matrix for ships is as follows: ; in, The matrix represents the spatiotemporal arrangement information of the tasks. Indicates that it includes ships A vector of berth occupancy time and location planning information. A vector representing the freight planning results of the quay crane. A vector representing the freight planning results of the yard crane. A vector representing the freight planning results of the conveyor belt. This represents a vector representing the freight planning results for electric heavy-duty trucks.

[0015] Furthermore, the logistics end-to-end scheduling model is as follows: ; in, This represents the working time vector of the overall logistics process after scheduling. Indicates the ships after dispatch The working time vector of each link in the logistics process.

[0016] Furthermore, the optimization function is: ; in, Indicates the target value. This indicates the price based on maximum demand or capacity. This indicates the maximum net power supply from the port's power grid within the reporting month. express Net power supply of the port power grid at any time This indicates the average net power supplied by the port's power grid during the day. express Time-of-use electricity pricing on the power grid Indicates the simulation time step. Represents the carbon emission weighting coefficient. express The carbon emission factor of the power grid at any time.

[0017] The constraint on the number of electric heavy trucks is expressed as: ; ; in, express Shike Electric Heavy Truck Does it undertake ships? The state variables of freight transportation work This indicates the number of electric heavy-duty trucks. This indicates the total number of electric heavy-duty trucks in the port. The constraints on the charge requirements and charging power of electric heavy-duty trucks are expressed as follows: ; ; ; in, Indicates electric heavy truck exist The charge level at which the machine is ready to start operation. Indicates electric heavy truck The minimum charge, Indicates electric heavy truck Energy consumption per unit of time during operation Indicates electric heavy truck Working time for completing cargo transfer tasks. Indicates electric heavy truck The charging power, Indicates electric heavy truck Maximum charging power, Indicates electric heavy truck The state of charge, Indicates electric heavy truck Maximum charge; The expression for the temperature constraint of the air conditioner in a temperature-controlled load is: ; in, This indicates the upper limit of the air conditioner temperature. express Air conditioning The indoor temperature of the room Indicates the lower limit of the air conditioner temperature; The expression for the temperature constraint of the cold box in a temperature-controlled load is: ; in, This indicates the upper limit of the cold box temperature. express The internal temperature of the cold box is constantly monitored. Indicates the lower limit of the cold box temperature; The constraints on the charging and discharging capacity and power of energy storage devices are expressed as follows: ; ; ; ; in, This indicates the lower limit of energy storage capacity of the energy storage device. This indicates the amount of electricity that the energy storage device can store. This indicates the upper limit of energy storage capacity of the energy storage device. This indicates the maximum charging power of the energy storage device. , These represent the charging and discharging power of the energy storage device, respectively. This indicates the maximum discharge power of the energy storage device.

[0018] The present invention also provides a converged control device for carbon emission reduction accounting in port microgrids, comprising: The analysis module is used to analyze the target port microgrid and determine the flexible electrical resources of the target port microgrid; The module is constructed by analyzing the adjustable modes of each flexible electrical resource based on its working method and constructing a mathematical model for each flexible electrical resource. The determination module is used to determine the logistics operation process arrangement of the target port microgrid based on the mathematical model of each flexible electrical resource, and to establish a full-process logistics scheduling model based on the logistics operation process arrangement; The solution module, based on the logistics full-process scheduling model, photovoltaic power generation patterns, and energy storage configuration, aims to minimize the power operation cost and overall carbon emissions of the target port microgrid. It constructs an optimization function and constraints, solves the optimization function based on the constraints, and obtains the flexible electrical resource aggregation and control results used to calculate the overall carbon emissions of the target port microgrid.

[0019] The present invention also provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements a converged control method for carbon emission reduction accounting in a port microgrid.

[0020] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements a method for aggregated control of carbon emission reduction accounting in port microgrids.

[0021] The above-described solution of the present invention has the following beneficial effects: This invention analyzes a target port microgrid to determine its flexible electrical resources; it analyzes the adjustable modes of each flexible electrical resource based on their operating methods and constructs mathematical models for each resource; based on these mathematical models, it determines the logistics operation process of the target port microgrid and establishes a full-process logistics scheduling model; based on the full-process logistics scheduling model, photovoltaic power generation patterns, and energy storage configuration, it constructs an optimization function and constraints to minimize the power operating cost and overall carbon emissions of the target port microgrid; and it solves the optimization function based on the constraints to obtain the aggregated control results of flexible electrical resources used to calculate the overall carbon emissions of the target port microgrid. This invention differs from existing technologies. In contrast, this invention, based on a logistics full-process scheduling model, photovoltaic power generation patterns, and energy storage configuration, aims to minimize the power operation cost and overall carbon emissions of the target port microgrid. It constructs an optimization function and constraints, solves the optimization function based on the constraints, and obtains flexible electrical resource aggregation and control results for calculating the overall carbon emissions of the target port microgrid. This fully taps the adjustable potential of port electrical resources, achieving coordinated control of related equipment and other source, load, and storage resources in each freight stage while meeting the requirements of port microgrid logistics operations. It solves the problem of traditional port microgrid freight processes being difficult to coordinate with electrical resources, promotes the rational allocation of port power resources, reduces overall port carbon emissions, and accurately calculates the overall carbon emissions.

[0022] Other beneficial effects of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0023] Figure 1This is a flowchart illustrating an embodiment of the present invention; Figure 2 This is a typical daily outdoor temperature curve diagram in an embodiment of the present invention; Figure 3 This is a schematic diagram of the load translation of each quay crane in the port in an embodiment of the present invention; Figure 4 This is a diagram showing the overall load power curve of the port machinery in an embodiment of the present invention; Figure 5 This is a comparison chart of port load before and after optimization in an embodiment of the present invention; Figure 6 This is a schematic diagram of the aggregated control device for carbon emission reduction accounting in a port microgrid, according to an embodiment of the present invention. Figure 7 This is a schematic diagram of the structure of the terminal device in an embodiment of the present invention. Detailed Implementation

[0024] To make the technical problems, solutions, and advantages of this invention clearer, a detailed description will be provided below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0025] In the description of this invention, it should be noted that the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0026] Furthermore, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0027] This invention addresses existing problems by providing a method for aggregated control and related equipment for carbon emission reduction accounting in port microgrids.

[0028] like Figure 1 As shown, an embodiment of the present invention provides a method for aggregated control of carbon emission reduction accounting in port microgrids, comprising: Step 1: Analyze the target port microgrid to determine its flexible electrical resources; Step 2: Analyze the adjustable modes of each flexible electrical resource based on its working method, and construct a mathematical model for each flexible electrical resource. Step 3: Determine the logistics operation process arrangement of the target port microgrid based on the mathematical model of each flexible electrical resource, and establish a full-process logistics scheduling model according to the logistics operation process arrangement; Step 4: Based on the logistics whole-process scheduling model, photovoltaic power generation patterns and energy storage configuration, with the goal of minimizing the power operation cost and overall carbon emissions of the target port microgrid, construct an optimization function and constraints. Solve the optimization function based on the constraints to obtain the flexible electrical resource aggregation and control results used to calculate the overall carbon emissions of the target port microgrid.

[0029] Because the operating time of port machinery in the target port microgrid can be shifted, the charging time and operating time of electric heavy trucks can be adjusted, the charging and discharging time and amount of energy storage devices can be adjusted, and the power of temperature-controlled loads can be regulated by changing the set temperature, such as pre-storing cold or heat, the flexible electrical resources of the target port microgrid include: Port machinery is used to transfer cargo from arriving ships to the port yard. Port machinery includes three categories: quay cranes, yard cranes, and conveyor belts. Electric heavy-duty trucks are used to transport goods from port yards to warehouses. The electric heavy-duty trucks use on-board batteries to provide the electrical energy required for transportation and connect to charging piles to charge the on-board batteries after arriving at the charging station. Temperature-controlled loads include air conditioners used to regulate indoor temperatures in port work and living areas, and cold boxes used to regulate warehouse temperatures. Temperature-controlled loads have cold and heat storage capabilities, i.e., they have generalized energy storage characteristics. Within an acceptable range, by changing their set temperature, their overall power level can be regulated over a certain period of time. For example, a lower cold box temperature can be set during periods of low electricity load to store cold energy, at which time their average power is higher; while a higher cold box temperature can be set during periods of high load to release some cold energy, at which time their average power level is lower. Energy storage devices are used to store photovoltaic power generation. Lithium-ion batteries are used as energy storage batteries. They can not only store excess photovoltaic power generation during the day for use at night or on cloudy days, but also adjust their charging and discharging status according to changes in electricity prices and port load power consumption plans.

[0030] Specifically, the derivation process of the mathematical model for the port machinery is as follows: Under the premise of meeting cargo loading and unloading needs, the operating time of different port machinery can be adjusted through logistics scheduling. The cargo transfer task of the ship is completed by the port machinery, and its operating time can be expressed by the following formula: ; During a single work task, the port machinery only consumes electrical power during its working hours. The time characteristic of the port machinery's electrical power consumption can be expressed as: ; Since the overall cargo loading and unloading workload remains unchanged, and the overall required working time remains unchanged, only the start and end times of the port machinery are changed. Therefore, it is modeled as a transferable load, and the mathematical model of the port machinery is as follows: ; in, This indicates the operating time of the port machinery. Indicates a ship The arrival time of the port, Indicates a ship After entering, the port machinery The delay time before execution begins, expressed in minutes. Always responsible for the ship Port machinery for work tasks The power consumption, expressed in kW. Indicates the person in charge of the vessel The rated power of the port machinery used for the work tasks, expressed in kW. Indicates a ship The workload allocated to port machinery in freight operations, expressed in tons (t). This indicates the freight efficiency of port machinery, expressed in units of / (t / min). This indicates the electricity consumption for freight transport before the adjustment of port machinery load. This indicates the electricity consumption for freight transport after adjustments to the port's machinery load, expressed in units of / kW. h.

[0031] It should be noted that in actual scheduling, the principle of its relocation is to minimize the use of port machinery during peak port electricity consumption periods while ensuring that loading and unloading work can be completed within the time limit for ships to berth.

[0032] Specifically, the derivation process of the mathematical model for electric heavy-duty trucks includes: The model for the change in the electric power of a charging heavy-duty truck during the charging process is established as follows: ; in, , These represent the electric heavy-duty trucks during the charging process. exist Battery charge at time 1 and the previous time, in units of / kW h, Indicates charging efficiency. This indicates the simulation calculation time step, in units of / min; In cargo transshipment tasks, the number of electric heavy-duty trucks needs to be allocated based on the ship's cargo workload and berthing time to complete the cargo transport task. The mathematical model for the number of electric heavy-duty trucks is as follows: ; in, Indicates completion of the ship The number of electric heavy-duty trucks required for freight transport tasks. Indicates a ship Total freight volume This indicates the transport capacity of electric heavy-duty trucks, expressed in units of / (t / min). Indicates a ship The arrival time of the port, Indicates a ship Departure time; The mathematical model for the working time of an electric heavy-duty truck in completing a cargo transfer task is as follows: ; in, This indicates the working time required for the electric heavy-duty truck to complete the cargo transfer task. The transport efficiency of electric heavy trucks is expressed in units of / (t / min). This indicates the additional time lost by electric heavy-duty trucks during transportation operations. The mathematical model for the charging power of electric heavy-duty trucks is as follows: ; in, This indicates the charging power of the electric heavy-duty truck. Indicates that electric heavy trucks are in Charging power at any time This indicates the total number of electric heavy-duty trucks in the port.

[0033] Specifically, the temperature control load at ports mainly consists of air conditioning and refrigerant containers. The mathematical model for the temperature control load includes: The derivation process of the air conditioner power model is as follows: Since the port's working and living areas contain several rooms of varying sizes, when the air conditioners are turned on, the compressors generate cooling or heating, causing the indoor temperature to decrease or increase accordingly. Simultaneously, due to the temperature difference between the indoor and outdoor areas, continuous heat exchange occurs, resulting in energy dissipation. Therefore, a first-order linear dynamic model of the room's indoor temperature is constructed as follows: ; Considering a fixed-frequency air conditioner, the compressor has two operating modes: on and off. Taking cooling mode as an example, when the indoor temperature is above the upper limit, the air conditioner compressor starts cooling; when the indoor temperature is below the lower limit, the air conditioner compressor stops running. To prevent frequent start-stop cycles, the air conditioner has a threshold temperature dead zone. Therefore, the air conditioner power model is as follows: ; in, Indicates air conditioner exist Electric power at any given moment Indicates air conditioner Rated power, Indicates air conditioner Threshold temperature dead zone express Air conditioning The set temperature, express Air conditioning The indoor temperature of the room Indicates the time step of the simulation calculation. The outdoor temperature at any given time is expressed in °C. Indicates air conditioner The equivalent thermal resistance of the room, expressed in °C / kW. Indicates air conditioner The heat capacity of the room, expressed in kJ / ℃. Indicates air conditioner The energy efficiency ratio of the air conditioner When in cooling mode, Take the negative sign, and the air conditioner When in heating mode, Take the positive sign; The derivation process of the cold box power model is as follows: The working principle of a cold box load is similar to that of an air conditioning load; the temperature of the cold box is regulated by switching the compressor on and off. Since the cold box is responsible for storing goods requiring cold chain transportation, the impact of the amount of goods stored inside must be considered when calculating the temperature variation pattern. The calculation expression is as follows: ; Since the power control method for cold boxes is similar to that for air conditioners, the power model for cold boxes is as follows: ; in, Indicates cold box exist The electrical power at any given time, when the refrigeration compressor stops working. =0, Indicates cold box Rated power, Indicates cold box Threshold temperature dead zone express Time Cold Box The set temperature, express Time Cold Box The internal temperature Indicates cold box External surface area, in units of / m 2 , Indicates cold box The heat transfer coefficient, in units of (W / ), Indicates cold box The weight of the goods inside is expressed in kg. Indicates cold box Specific heat capacity, in units of / (kJ / kg) K), Indicates cold box The energy efficiency ratio.

[0034] Specifically, when constructing the mathematical model for energy storage devices, privacy factors such as charging and discharging power and efficiency need to be considered. Therefore, its mathematical model is as follows: ; in, express The amount of electricity stored in the energy storage device at any time. This indicates the charging efficiency of the energy storage device. This indicates the discharge efficiency of the energy storage device. This indicates the charging power of the energy storage device. This indicates the discharge efficiency of the energy storage device.

[0035] Specifically, step 3 includes: Based on the ship's arrival and departure timetable, a ship logistics information vector is formed; Based on logistics information vectors, a ship berth usage plan and a logistics operation process arrangement for the target port microgrid are formulated. The logistics operation process arrangement for the target port microgrid includes the specific usage arrangements for port machinery and electric heavy trucks. Based on the logistics operation process of the target port microgrid, a mission spatiotemporal arrangement information matrix for ships is generated; A full-process logistics scheduling model is constructed based on the ship's mission time and space arrangement information matrix.

[0036] In this embodiment of the invention, before ships enter the port, they need to provide ship information to the port dispatch center in advance. By compiling the ship information for the day, a ship arrival and departure timetable for the port microgrid is constructed. The port microgrid ship arrival and departure timetable summarizes information such as port ship cargo handling workload, berthing time, and cargo nature. Based on the information in this table, the daily allocation of ship berths and subsequent logistics and cargo arrangements can be planned as a whole. Therefore, based on the ship arrival and departure timetable, the ship logistics information vector is formed as follows: ; in, Indicates a ship The allocation ratio of yard cranes / conveyor belts required for cargo transshipment arrangements is based on the arriving vessels. The composition of the goods determines the quantity of goods that need to be transported by cranes and conveyor belts.

[0037] Specifically, based on the logistics operation process of the target port microgrid, a mission spatiotemporal scheduling information matrix for ships is generated, including: Based on the arrival and departure times of ships and their total cargo volume, berth planning results are formulated, including berth duration. berth location , ; The freight planning results of the gantry crane in the gantry crane were determined by using a mathematical model of the gantry crane. The freight planning results of the gantry crane include working hours. Number of shore bridges , ; Based on the freight planning results of the quay cranes and the allocation ratio coefficients of the yard cranes and conveyors in the port machinery, the freight planning results for the yard cranes and conveyors are allocated. The freight planning results for the yard cranes include working hours. Number of bridges , The freight planning results for the conveyor belt include working hours. and the number of conveyor belts , ; Based on mathematical models of the number of electric heavy-duty trucks in cargo transfer tasks and the working time of electric heavy-duty trucks in completing cargo transfer tasks, the freight planning results for electric heavy-duty trucks are determined. These results include working hours. and the number of electric heavy trucks , ; Based on the berth planning results of ships, the freight planning results of gantry cranes, the freight planning results of yard cranes and conveyors, and the freight planning results of electric heavy trucks, a task spatiotemporal arrangement information matrix for ships is generated, which is as follows: ; in, A matrix representing the spatiotemporal scheduling information of a ship's missions. Indicates that it includes ships A vector of berth occupancy time and location planning information. A vector representing the freight planning results of the quay crane. A vector representing the freight planning results of the yard crane. A vector representing the freight planning results of the conveyor belt. This represents a vector representing the freight planning results for electric heavy-duty trucks.

[0038] Specifically, the process of constructing a full-process logistics scheduling model based on the ship's mission spatiotemporal arrangement information matrix is ​​as follows: Based on the adaptable nature of port machinery and electric heavy-duty truck operation times, within the planned freight transport timeframes for quay cranes, yard cranes, conveyor belts, and electric heavy-duty trucks, the specific working times for each logistics link can be scheduled. Since there are successor relationships between different links in a ship's freight transport task, therefore, for ships... The working time vectors for each logistics link after logistics scheduling can be constructed, and the expression is: ; in, ; In the formula, Ships The moment when quay cranes, yard cranes, conveyor belts, and electric heavy trucks begin operation in freight transport tasks. 、 、 、 Ships after logistics scheduling The scheduling and waiting time of quay cranes, yard cranes, conveyor belts, and electric heavy trucks after the completion of the previous logistics link in a freight task, expressed in minutes ( / min). The time from when the quay crane begins unloading cargo from the ship to when the yard crane can begin transferring cargo to the port, measured in minutes. The time from when the quay crane starts unloading cargo from the ship to when the conveyor belt can begin transferring the cargo to the port, measured in minutes. This refers to the time from the start of cargo transfer at the yard crane until the electric heavy truck can begin transfer operations, expressed in minutes ( / min). The time from the start of cargo transfer on the conveyor belt until the electric heavy truck can begin transfer operations, expressed in minutes. Specifically, after performing the above logistics scheduling process on all ships, the resulting end-to-end logistics scheduling model is as follows: ; in, This represents the working time vector of the overall logistics process after scheduling. Indicates the ships after dispatch The working time vector of each link in the logistics process.

[0039] It should be noted that for ships, the quay crane freight transport task must be completed before the ship's departure time; therefore, constraints need to be placed on the start time of the quay crane's work. ; Meanwhile, freight operations need to be completed within a certain time limit, while ensuring that the preservation requirements of cold chain transportation and the logistics and freight operations of subsequent arriving ships are not affected. Therefore, it is necessary to restrict the start time of electric heavy trucks: ; in, This indicates the time limit parameter for freight operations.

[0040] Specifically, the aggregation control method for carbon emission reduction accounting of port microgrids provided in this invention aims to reduce the overall energy cost of port microgrids and improve the economic efficiency of port operations. Therefore, based on the two-part electricity price of the target area, and with the goal of minimizing the total power operation cost of the target port microgrid, an optimization function and constraints are constructed, wherein: The optimized function is: ; in, Indicates the target value. This indicates the price based on maximum demand or capacity. This indicates the maximum net power supply from the port's power grid within the reporting month. express Net power supply of the port power grid at any time This indicates the average net power supplied by the port's power grid during the day. express Time-of-use electricity pricing on the power grid Indicates the simulation time step. Represents the carbon emission weighting coefficient. express The carbon emission factor of the power grid at any time.

[0041] The constraints include: Due to the fact that for each ship Requirements for the working hours of electric heavy trucks required for freight transport There are enough electric heavy-duty trucks available to handle freight transport, and The total number of electric heavy-duty trucks involved in freight transportation at any given time must not exceed the upper limit. Therefore, a constraint needs to be placed on the number of electric heavy-duty trucks, expressed as: ; ; in, express Shike Electric Heavy Truck Does it undertake ships? The state variables of freight transportation work, and the acceptance process. If not accepted , This indicates the number of electric heavy-duty trucks. This indicates the total number of electric heavy-duty trucks in the port. The constraints on the charge requirements and charging power of electric heavy-duty trucks are expressed as follows: ; ; ; in, Indicates electric heavy truck exist The charge level at which the machine is ready to start operation. Indicates electric heavy truck The minimum charge, Indicates electric heavy truck Energy consumption per unit of time during operation Indicates electric heavy truck Working time for completing cargo transfer tasks. Indicates electric heavy truck The charging power, Indicates electric heavy truck Maximum charging power, Indicates electric heavy truck The state of charge, Indicates electric heavy truck Maximum charge; The expression for constraining the temperature of the air conditioner in a temperature-controlled load is as follows: ; in, This indicates the upper limit of the air conditioner temperature. express Air conditioning The indoor temperature of the room Indicates the lower limit of the air conditioner temperature; The temperature of the cold box in the temperature-controlled load is constrained by the following expression: ; in, This indicates the upper limit of the cold box temperature. express The internal temperature of the cold box is constantly monitored. Indicates the lower limit of the cold box temperature; The charging and discharging capacity and power of the energy storage device are constrained by the following expression: ; ; ; Because energy storage devices must ensure that they cannot be charged and discharged simultaneously, therefore: ; in, This indicates the lower limit of energy storage capacity of the energy storage device. This indicates the amount of electricity that the energy storage device can store. This indicates the upper limit of energy storage capacity of the energy storage device. This indicates the maximum charging power of the energy storage device. , These represent the charging and discharging power of the energy storage device, respectively. This indicates the maximum discharge power of the energy storage device.

[0042] This invention uses typical port summer day vessel operation plans, port charging facility configurations, and meteorological monitoring data to simulate and analyze the proposed aggregated optimization control method. To ensure the reliability and practicality of the data, the data on port machinery (quay cranes, yard cranes, conveyor belts), electric transport vehicle charging needs, and energy consumption characteristics of temperature control equipment (air conditioning and refrigerated containers) were obtained from on-site investigations and surveys of multiple ports. The two-part electricity pricing policy of the province where a specific port is located was adopted, as shown in Table 1 below: Table 1 Two-part electricity pricing table

[0043] The simulation was conducted on a typical day in June in the province where the port is located, with the simulation period from 00:00 to 24:00. The outdoor temperature curve for this typical day is shown below. Figure 2 As shown, the port's land area is 180,000 m². 2 The voltage level of the connected transformer is 35kV, the transformer capacity of the distribution area is 20MW, and a total of 9 berths of 1,000 tons are arranged.

[0044] The port's cargo handling equipment is equipped with charging facilities for 9 quay cranes, 12 yard cranes, 4 conveyor belts, and 20 electric heavy-duty trucks. Among the port's cargo handling equipment, the rated operating power of the quay cranes is 248.9 kW, the rated power of the yard cranes is 157.5 kW, and the operating power of the conveyor belts is 181.2 kW. The port's daily vessel arrival and departure timetable is shown in Table 2 below. Table 2. Port Daytime Vessel Arrival and Departure Schedule

[0045] This invention embodiment aggregates and regulates the flexible electrical resources of the target port microgrid, that is, effectively regulates the load and storage resources such as port machinery, electric heavy trucks, refrigerated containers, air conditioners, and energy storage within the port. Taking quay cranes as an example, the scheduling results of port machinery are explained. The load shifting diagram of each quay crane within the port is shown below. Figure 3 As shown, the overall load-power curve of the port machinery is as follows: Figure 4 As shown, from Figure 4 It can be seen that after the optimized scheduling, the peak power of port machinery during the peak load operation periods of 8:00-9:00 and 14:00-15:00 has been reduced from the original 2200kW and 2500kW to 1800kW and 2000kW respectively, with the maximum reduction reaching 500kW, which is about 20%.

[0046] The calculation results of the port's monthly power operating cost and the net load variance of the power grid before and after the optimized scheduling are shown in Table 3: Table 3. Port optimization scheduling effects and carbon emissions under different scenarios

[0047] As shown in Table 3, without energy storage, the optimized port power operating cost for the month decreased by RMB 195,100 (approximately 8.36%), while the net load peak-to-valley difference of the grid supply decreased, and the load fluctuation variance decreased by 42.04%. With energy storage, the optimized port power operating cost for the month decreased by RMB 241,600 (approximately 10.36%), and the load fluctuation variance decreased by 73.18%. Figure 5 It can be seen that, after optimized scheduling, some of the load during the original peak electricity consumption periods of 8:00-9:00 and 13:00-19:00 can be transferred to the off-peak period. For example, the period from 11:00 to 13:00 is the peak period for photovoltaic power generation at the port, and it is also the off-peak period with low time-of-use electricity prices. After optimized scheduling, the operating load at 11:00 am increased from about 2,500 kW to more than 3,500 kW, with significant results.

[0048] It is evident that this aggregated regulation and optimization method can shift electricity load from peak to off-peak periods. Under the proposed strategy, various energy devices in the port can operate in a coordinated manner, reducing port power operating costs while decreasing net load variance, thus contributing to peak shaving and valley filling in the regional power grid. Furthermore, configuring energy storage in the scenario further reduces power operating costs compared to the scenario without energy storage, significantly improving the reduction effect on load fluctuation variance.

[0049] The calculation expression for total carbon emissions in this embodiment of the invention is as follows: ; in, Indicates total carbon emissions. express Net power supply of the port power grid at any time Indicates the simulation time step. express The carbon emission factor of the power grid at any time.

[0050] This invention analyzes a target port microgrid to determine its flexible electrical resources; analyzes the adjustable modes of each flexible electrical resource based on its operating mode, and constructs a mathematical model for each flexible electrical resource; determines the logistics operation process arrangement of the target port microgrid based on the mathematical model of each flexible electrical resource, and establishes a logistics full-process scheduling model based on the logistics operation process arrangement; based on the logistics full-process scheduling model, photovoltaic power generation patterns, and energy storage configuration, with the goal of minimizing the power operating cost and overall carbon emissions of the target port microgrid, constructs an optimization function and constraints, solves the optimization function based on the constraints, and obtains the aggregated control result of flexible electrical resources used to calculate the overall carbon emissions of the target port microgrid; compared with existing technologies... In contrast, this invention, based on a logistics full-process scheduling model, photovoltaic power generation patterns, and energy storage configuration, aims to minimize the operating costs and overall carbon emissions of the target port microgrid. It constructs an optimization function and constraints, solves the optimization function based on the constraints, and obtains flexible electrical resource aggregation and control results for calculating the overall carbon emissions of the target port microgrid. This fully taps the adjustable potential of port electrical resources, achieving coordinated control of related equipment and other source, load, and storage resources in each freight stage while meeting the requirements of port microgrid logistics operations. It solves the problem of traditional port microgrid freight processes being difficult to coordinate with electrical resources, promotes the rational allocation of port power resources, reduces overall port carbon emissions, and accurately calculates the overall carbon emissions.

[0051] Corresponding to the aggregated control method for carbon emission reduction accounting of port microgrids described in the above embodiments, such as Figure 6 As shown, the present invention also provides a converged control device 100 for carbon emission reduction accounting in port microgrids. This inland waterway flexible electrical resource converged control device 100 includes: Analysis module 101 is used to analyze the target port microgrid and determine the flexible electrical resources of the target port microgrid; Module 102 is constructed to analyze the adjustable modes of each flexible electrical resource based on its working method and to construct a mathematical model for each flexible electrical resource. The determination module 103 is used to determine the logistics operation process arrangement of the target port microgrid based on the mathematical model of each flexible electrical resource, and to establish a full-process logistics scheduling model according to the logistics operation process arrangement. The solution module 104, based on the logistics whole-process scheduling model, photovoltaic power generation patterns and energy storage configuration, constructs an optimization function and constraints with the goal of minimizing the power operation cost and overall carbon emissions of the target port microgrid. Based on the constraints, the optimization function is solved to obtain the flexible electrical resource aggregation and control results used to calculate the overall carbon emissions of the target port microgrid.

[0052] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0053] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0054] This invention also provides a terminal device, such as... Figure 7 As shown, the terminal device D10 of this embodiment includes: at least one processor D100 ( Figure 7 The diagram shows only one processor, a memory D101, and a computer program D102 stored in the memory D101 and executable on the at least one processor D100. When the processor D100 executes the computer program D102, it implements the above-described aggregated control method for carbon emission reduction accounting of port microgrids.

[0055] The terminal device D10 can be a desktop computer, laptop, handheld computer, server, server cluster, or cloud server, etc. This terminal device may include, but is not limited to, a processor D100 and a memory D101. Those skilled in the art will understand that... Figure 7 This is merely an example of terminal device D10 and does not constitute a limitation on terminal device D10. It may include more or fewer components than shown in the figure, or combine certain components, or different components, such as input / output devices, network access devices, etc.

[0056] The processor D100 can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0057] In some embodiments, the memory D101 may be an internal storage unit of the terminal device D10, such as a hard disk or memory of the terminal device D10. In other embodiments, the memory D101 may be an external storage device of the terminal device D10, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the terminal device D10. Furthermore, the memory D101 may include both internal and external storage units of the terminal device D10. The memory D101 is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory D101 can also be used to temporarily store data that has been output or will be output.

[0058] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0059] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0060] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements a converged control method for carbon emission reduction accounting in a port microgrid.

[0061] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying the computer program code to a building device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0062] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for aggregated control of carbon emission reduction accounting in port microgrids, characterized in that, include: Step 1: Analyze the target port microgrid to determine the flexible electrical resources of the target port microgrid; Step 2: Analyze the adjustable modes of each flexible electrical resource based on its working method, and construct a mathematical model for each flexible electrical resource. Step 3: Determine the logistics operation process arrangement of the target port microgrid based on the mathematical model of each flexible electrical resource, and establish a full-process logistics scheduling model according to the logistics operation process arrangement; Step 4: Based on the logistics full-process scheduling model, photovoltaic power generation patterns, and energy storage configuration, with the goal of minimizing the power operation cost and overall carbon emissions of the target port microgrid, construct an optimization function and constraints. Solve the optimization function based on the constraints to obtain the flexible electrical resource aggregation and control results used to calculate the overall carbon emissions of the target port microgrid.

2. The aggregation control method for carbon emission reduction accounting in port microgrids according to claim 1, characterized in that, The flexible electrical resources of the target port microgrid include: Port machinery is used to transfer cargo from arriving ships to the port storage yard. Electric heavy trucks are used to transport goods from port yards to warehouses; Temperature control loads include air conditioners used to regulate indoor temperatures in port work and living areas, and cold storage containers used to regulate warehouse temperatures. Energy storage devices are used to store photovoltaic power generation.

3. The aggregation control method for carbon emission reduction accounting in port microgrids according to claim 2 is characterized in that, The mathematical model of the port machinery is as follows: ； in, Indicates the person in charge of the vessel The rated power of the port machinery used for the work tasks. Indicates a ship The workload assigned to port machinery in freight operations. This indicates the freight efficiency of port machinery. Indicates the vessels before the adjustment of port machinery load. Electricity consumption for freight transport tasks Indicates the adjustment of the load on the ship's working machinery. Electricity consumption for freight transport tasks.

4. The aggregation control method for carbon emission reduction accounting in port microgrids according to claim 2, characterized in that, The mathematical model of the electric heavy-duty truck includes: The mathematical model for the number of electric heavy trucks in cargo transshipment tasks is as follows: ； in, Indicates completion of the ship The number of electric heavy-duty trucks required for freight transport tasks. Indicates a ship Total freight volume This indicates the transport capacity of the electric heavy-duty truck. Indicates a ship The arrival time of the port, Indicates a ship Departure time; The mathematical model for the working time of the electric heavy truck in completing the cargo transfer task is as follows: ； in, This indicates the working time required for the electric heavy-duty truck to complete the cargo transfer task. This indicates the transportation efficiency of electric heavy-duty trucks. This indicates the additional time lost by electric heavy-duty trucks during transportation operations. The mathematical model for the charging power of the electric heavy-duty truck is: ； in, This indicates the charging power of the electric heavy-duty truck. Indicates that electric heavy trucks are in Charging power at any time This indicates the total number of electric heavy-duty trucks in the port.

5. The aggregation control method for carbon emission reduction accounting in port microgrids according to claim 2, characterized in that, The mathematical model for the temperature-controlled load includes: The power model for air conditioning is as follows: ； in, Indicates air conditioner exist Electric power at any given moment Indicates air conditioner Rated power, Indicates air conditioner Threshold temperature dead zone express Air conditioning The set temperature, express Air conditioning The indoor temperature of the room Indicates the simulation time step; The power model for a cold box is as follows: ； in, Indicates cold box exist Electric power at any given moment Indicates cold box Rated power, Indicates cold box Threshold temperature dead zone express Time Cold Box The set temperature, express Time Cold Box The internal temperature.

6. The aggregation control method for carbon emission reduction accounting in port microgrids according to claim 2, characterized in that, The mathematical model of the energy storage device is as follows: ； in, express The amount of electricity stored in the energy storage device at any time. This indicates the charging efficiency of the energy storage device. This indicates the discharge efficiency of the energy storage device. This indicates the charging power of the energy storage device. This indicates the discharge efficiency of the energy storage device.

7. The aggregation control method for carbon emission reduction accounting in port microgrids according to claim 2, characterized in that, Step 3 includes: Based on the ship's arrival and departure timetable, a ship logistics information vector is formed; Based on the logistics information vector, a ship berth usage plan and a logistics operation process arrangement for the target port microgrid are formulated. The logistics operation process arrangement for the target port microgrid includes the specific usage arrangements for the port machinery and the electric heavy truck. Based on the logistics operation process arrangement of the target port microgrid, a mission spatiotemporal arrangement information matrix for ships is generated; A full-process logistics scheduling model is constructed based on the ship's mission time and space arrangement information matrix.

8. The aggregation control method for carbon emission reduction accounting in port microgrids according to claim 7, characterized in that, Based on the logistics operation process of the target port microgrid, a ship mission spatiotemporal scheduling information matrix is ​​generated, including: Based on the arrival and departure times of ships and the total cargo volume of ships, berth planning results are formulated, including berth duration and berth location. The freight planning results of the gantry crane in the gantry machinery are determined by the mathematical model of the gantry machinery. Based on the freight planning results of the quay cranes, the allocation ratio coefficients of the quay cranes and conveyor belts of the port machinery, the freight planning results of the quay cranes and conveyor belts are allocated. The freight planning results of the electric heavy trucks are determined based on the mathematical model of the number of electric heavy trucks in the cargo transfer task and the mathematical model of the working time of the electric heavy trucks to complete the cargo transfer task. Based on the berth planning results of the ship, the freight planning results of the gantry crane, the freight planning results of the yard crane and conveyor belt, and the freight planning results of the electric heavy truck, a mission spatiotemporal arrangement information matrix of the ship is generated.

9. The aggregation control method for carbon emission reduction accounting in port microgrids according to claim 8, characterized in that, The mission spatiotemporal scheduling information matrix for ships is as follows: ； in, The matrix represents the spatiotemporal arrangement information of the tasks. Indicates that it includes ships A vector of berth occupancy time and location planning information. A vector representing the freight planning results of the quay crane. A vector representing the freight planning results of the yard crane. A vector representing the freight planning results of the conveyor belt. This represents a vector representing the freight planning results for electric heavy-duty trucks.

10. The aggregation control method for carbon emission reduction accounting in port microgrids according to claim 8, characterized in that, The logistics end-to-end scheduling model is as follows: ； in, This represents the working time vector of the overall logistics process after scheduling. Indicates the ships after dispatch The working time vector of each link in the logistics process.

11. The aggregation control method for carbon emission reduction accounting in port microgrids according to claim 1, characterized in that, The optimization function is: ； in, Indicates the target value. This indicates the price based on maximum demand or capacity. This indicates the maximum net power supply from the port's power grid within the reporting month. express Net power supply of the port power grid at any time This indicates the average net power supplied by the port's power grid during the day. express Time-of-use electricity pricing on the power grid Indicates the simulation time step. Represents the carbon emission weighting coefficient. express The carbon emission factor of the power grid at any time.

12. The aggregation control method for carbon emission reduction accounting in port microgrids according to claim 1, characterized in that, The constraints include: The constraint on the number of electric heavy trucks is expressed as: ； ； in, express Shike Electric Heavy Truck Does it undertake ships? The state variables of freight transportation work This indicates the number of electric heavy-duty trucks. This indicates the total number of electric heavy-duty trucks in the port. The constraints on the charge requirements and charging power of electric heavy-duty trucks are expressed as follows: ； ； ； in, Indicates electric heavy truck exist The charge level at which the machine is ready to start operation. Indicates electric heavy truck The minimum charge, Indicates electric heavy truck Energy consumption per unit of time during operation Indicates electric heavy truck Working time for completing cargo transfer tasks. Indicates electric heavy truck The charging power, Indicates electric heavy truck Maximum charging power, Indicates electric heavy truck The state of charge, Indicates electric heavy truck Maximum charge; The expression for the temperature constraint of the air conditioner in a temperature-controlled load is: ； in, This indicates the upper limit of the air conditioner temperature. express Air conditioning The indoor temperature of the room Indicates the lower limit of the air conditioner temperature; The expression for the temperature constraint of the cold box in a temperature-controlled load is: ； in, This indicates the upper limit of the cold box temperature. express The internal temperature of the cold box is constantly monitored. Indicates the lower limit of the cold box temperature; The constraints on the charging and discharging capacity and power of energy storage devices are expressed as follows: ； ； ； ； in, This indicates the lower limit of energy storage capacity of the energy storage device. This indicates the amount of electricity that the energy storage device can store. This indicates the upper limit of energy storage capacity of the energy storage device. This indicates the maximum charging power of the energy storage device. , These represent the charging and discharging power of the energy storage device, respectively. This indicates the maximum discharge power of the energy storage device.

13. A converged control device for carbon emission reduction accounting in port microgrids, characterized in that, include: The analysis module is used to analyze the target port microgrid and determine the flexible electrical resources of the target port microgrid; The module is constructed by analyzing the adjustable modes of each flexible electrical resource based on its working method and constructing a mathematical model for each flexible electrical resource. The determination module is used to determine the logistics operation process arrangement of the target port microgrid based on the mathematical model of each flexible electrical resource, and to establish a full-process logistics scheduling model according to the logistics operation process arrangement; The solution module, based on the logistics full-process scheduling model, photovoltaic power generation patterns, and energy storage configuration, constructs an optimization function and constraints with the objective of minimizing the power operation cost and overall carbon emissions of the target port microgrid. Based on the constraints, the optimization function is solved to obtain the flexible electrical resource aggregation and control results used to calculate the overall carbon emissions of the target port microgrid.

14. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the aggregated control method for carbon emission reduction accounting of port microgrids as described in any one of claims 1 to 12.

15. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the aggregated control method for carbon emission reduction accounting of port microgrids as described in any one of claims 1 to 12.

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