Electric power resource regulation and control method and system based on inland river port flexible traffic

Abstract

The invention discloses an electric power resource regulation and control method and system based on inland river port flexible traffic. The method comprises the following steps: respectively constructing a port traffic logistics whole-process scheduling optimization model and a port traffic flow-multi-energy flow collaborative scheduling optimization model; in combination with the port traffic logistics whole-process scheduling optimization model and the port traffic flow-multi-energy flow collaborative scheduling optimization model, the port traffic logistics whole process is analyzed, the energy coupling relation between an energy system and traffic logistics in the whole process is extracted, and a port traffic logistics-power resource whole-process collaborative scheduling model is established; and through the harbor district traffic logistics-power resource whole-process collaborative scheduling model, obtaining the optimal benefit of energy flow and traffic logistics overall scheduling, and determining a final energy flow and traffic logistics scheduling plan. According to the invention, co-scheduling of the energy flow and the traffic logistics is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of resource regulation, and particularly to a method and system for regulating electric power resources based on flexible traffic in inland ports. Background Art

[0002] Flexible traffic mainly refers to traffic and logistics tasks that can be regulated and scheduled, meeting the adjustability in terms of time and space. The time adjustability is reflected in optimizing the ship berthing time arrangement to change the total demand curve of the onshore power load of the port; most of the loading and unloading operations in the port are usually total quantity constraints. For example, the quay cranes at the terminal only need to complete the loading and unloading of goods before the latest departure time of the ship, and there is a certain tolerance for processing delays; the energy consumption can be reduced by optimizing the charging and discharging time and power of transport vehicles; by adjusting the charging and discharging scheme, the load transfer and reduction of refrigerated containers under peak load can be achieved. The space adjustability is mainly reflected in that the choice of the berth position of the arriving ship, the choice of the yard position of the loading and unloading equipment, the choice of the charging pile position of the transport vehicle, and the choice of the charging plug position of the refrigeration device will all affect the spatial distribution of the load at each node of the port energy network. When a large number of energy loads of the logistics system are connected disorderly, it may cause problems such as uneven port load distribution, line congestion, and poor power supply quality. The space adjustability of the energy consumption of the logistics system can achieve load balance and supply-demand balance between the nodes of the energy network, improve the energy flow distribution in the port area, and optimize the location and parameter planning of the port energy network, the location selection and capacity planning of the charging stations.

[0003] Currently, a small number of domestic and foreign studies on the collaborative scheduling of port power and traffic mainly come from the field of logistics and transportation, and are carried out for highly electrified ports, including: energy management methods such as using electric-driven quay cranes in cooperation with energy storage operation, intermittent power supply operation of refrigerated containers, and optimization of charging and discharging of automatically guided container trucks to reduce port energy consumption. Some scholars have also carried out research on ship-port energy collaborative scheduling considering berth allocation, the operation flexibility of onshore power and refrigerated containers based on the development trend of port integrated energy. However, most of the above studies are carried out for single or a few links in the logistics operation process, such as the berth allocation when the yard crane, onshore power, and ship enter the port, etc., without comprehensively considering the energy consumption characteristics of the joint scheduling of equipment in the whole logistics process, nor considering the energy system.

[0004] Current research on the energy side usually conducts planning research from the perspective of meeting the demand of multiple loads such as power, gas, and heat supply, mainly considering optimization objectives such as economy and environmental protection. There are mainly two common methods.

[0005] The first is a port hybrid energy storage model that separately establishes models for the stored energy and operating costs of hydrogen energy storage, natural gas energy storage, electrochemical energy storage, and cold storage equipment, a port handling equipment model, and a port refrigerated container system model; by constructing an objective function and constraint conditions, an initial value of the optimal scheduling scheme for the port hybrid energy storage is proposed; based on the port hybrid energy storage model and the initial value of the optimal scheduling scheme, a two-stage robust optimization operation model is established and solved through a column constraint generation algorithm to obtain the final optimal scheduling scheme, making full use of the electro-thermal comprehensive effect and response characteristics of various energy storage devices, using the two-stage robust optimization method, fully considering the volatility and uncertainty of renewable energy output, and under the condition of ensuring real-time source-load balance in the actual operation process, mitigating the volatility of renewable energy device output to the greatest extent and achieving the lowest operating cost and carbon emissions.

[0006] The second is a multi-port shore power energy router system and its design method, which obtains the energy supply of the port energy system, predicts the shore power load of the ship and the cooling, heating, and power loads of the port energy system; under different usage conditions of the ship for shore power, according to the relationship between the energy supply and load in the port energy system, different operation scenarios of the multi-port shore power energy router are constructed; the operation indicators of the multi-port shore power energy router under different operation scenarios are obtained, and a hierarchical architecture of the shore power energy scheduling system is constructed; according to the hierarchical architecture of the shore power energy scheduling, the component layer, communication layer, and information layer of the model are mapped into the shore power energy scheduling system in a bottom-up order; according to the uncertainty of the ship's use of shore power, a hierarchical and recursive architecture of the shore power energy scheduling is established to solve the energy management and distribution problems of the multi-port shore power energy router.

[0007] The above methods focus on the optimization of the port energy system, or the modeling of the transportation side is too idealized, without considering the variability of the actual working conditions of the logistics transportation and without taking into account the impact of the logistics system on the energy system.

[0008] At the same time, there are few studies that consider both the transportation and logistics side and the energy side, and most of them solve for a certain part or link in the logistics-energy system, lacking an overall solution method for the entire logistics-transportation process. Therefore, the present invention designs a method for regulating electric power resources for flexible transportation in inland river ports based on an energy flow-transportation and logistics double-flow collaborative scheduling optimization model. Summary of the Invention

[0009] To solve the above technical problems, the present invention proposes a method and system for regulating electric power resources based on flexible transportation in inland river ports to improve the efficiency of port resource management and maximize the utilization of renewable energy resources.

[0010] On the one hand, to achieve the above object, the present invention provides a method for regulating electric power resources based on flexible transportation in inland river ports, including:

[0011] Construct an optimization model for the whole process of port traffic logistics scheduling based on the flow shop scheduling theory, and construct a port traffic flow - multi - energy flow collaborative scheduling optimization model based on the relationship between traffic flow and energy;

[0012] Combined with the optimization model for the whole process of port traffic logistics scheduling and the port traffic flow - multi - energy flow collaborative scheduling optimization model, analyze the whole process of port traffic logistics, extract the energy coupling relationship between the energy system and traffic logistics in the whole process, construct a traffic flow - power resource interconnection framework through the energy coupling relationship, and establish a whole - process collaborative scheduling model for port area traffic logistics - power resources based on the traffic flow - power resource interconnection framework and the flow shop scheduling theory;

[0013] Solve the whole - process collaborative scheduling model for port area traffic logistics - power resources by the alternating direction multiplier method to determine the final energy flow and traffic logistics scheduling plan.

[0014] Preferably, set the scheduling objective function of the optimization model for the whole process of port traffic logistics scheduling, including:

[0015] Take the scheduling objective function of the shore - power SPS berth as minimizing the average in - port time of all ships, and use it as the scheduling objective of the shore - power berth. At the same time, take the lowest total scheduling cost of multi - power - consuming equipment in traffic logistics as the objective for the scheduling and allocation of various equipment, which is the joint scheduling objective of multi - power - consuming equipment, that is, the scheduling objective function of the optimization model for the whole process of port traffic logistics scheduling.

[0016] Preferably, the constraint conditions of the optimization model for the whole process of port traffic logistics scheduling include logistics equipment scheduling constraints and logistics equipment operation constraints. Among them, the logistics equipment scheduling constraints mean that the scheduling of logistics equipment needs to meet the single - equipment scheduling constraints and the joint scheduling constraints between equipment; the logistics equipment operation constraints mean that the operation of logistics equipment needs to meet the working efficiency, power, and capacity constraints of each equipment.

[0017] Preferably, the constraint conditions of the optimization model for the whole process of port traffic logistics scheduling also include ship berthing constraints. The ship berthing constraints adopt the continuous berth allocation method, regard the port shoreline as a continuous whole, allocate berths according to the arrival time sequence of each ship and the ship length, and provide shore - power services for each ship by the shore - power within the berth range.

[0018] Preferably, construct the port traffic flow - multi - energy flow collaborative scheduling optimization model based on the relationship between traffic flow and energy, including:

[0019] Establish a coupling model of port multi - energy flows, combine the output models of each energy equipment, and introduce a scheduling factor to represent the proportion of the input power of the power grid, natural gas network, and internal heat network allocated to the multi - energy coupling conversion equipment, and establish the port traffic flow - multi - energy flow collaborative scheduling optimization model.

[0020] Preferably, the objective function of the port traffic flow - multi - energy flow collaborative scheduling optimization model is as follows: Considering the combined effects of the demand response incentives and pollution reduction and carbon emission reduction incentives of the power department, the total subsidy revenue is maximized as the multi - source incentive objective of the scheduling response, and the operating cost is minimized as the objective function of the port traffic flow - multi - energy flow collaborative scheduling optimization model.

[0021] Preferably, the constraint conditions of the port traffic flow - multi - energy flow collaborative scheduling optimization model include the energy supply - demand balance constraint. The energy system scheduling in each period needs to meet the power balance constraints of electricity, heat, cold energy, and natural gas, including: The power generation needs to meet the total electricity demand of the infrastructure and transportation logistics; the heat and cold production power needs to meet the heat and cold energy demands of the port infrastructure.

[0022] Preferably, solving the port traffic flow - multi - energy flow collaborative scheduling optimization model by the alternating direction method of multipliers includes:

[0023] Drawing on the theory in the field of flow - shop scheduling, a port traffic logistics scheduling process based on the principle of flexible flow - line shop scheduling is established. According to the given arrival and departure times of each ship, ship length, and container task volume indicators, the ship logistics work is divided into operation stages and time windows. Taking the average in - port time of the ship and the total cost of energy system scheduling as the optimization objectives, the optimal start order of logistics work, as well as the best scheduling plan for berths and equipment at each stage, are solved, and the improved non - dominated sorting genetic algorithm with double comparison sorting is used to solve the proposed port traffic logistics optimization scheduling problem.

[0024] Preferably, determining the final energy flow and traffic logistics scheduling plan includes:

[0025] S1. The traffic logistics formulates a scheduling plan for the whole process of logistics according to its own scheduling objectives and constraints, and sends the corresponding electricity - using plan to the energy system; then the energy system evaluates the electricity demand of the logistics, combines its own benefits, formulates an energy flow scheduling plan, and transmits the power supply plan to the traffic logistics.

[0026] S2. The traffic logistics comprehensively considers the available electricity and its own benefits, adjusts the logistics scheduling plan, and sends the electricity demand to the energy system again.

[0027] Repeat S1 - S2 until the overall scheduling benefits of the energy flow and the traffic logistics are optimal, and the final energy flow and traffic logistics scheduling plan is determined.

[0028] On the other hand, to achieve the above - mentioned purpose, the present invention also provides a power resource regulation system based on the flexible traffic of inland ports, including:

[0029] Model construction unit: It is used to construct an overall scheduling optimization model for the whole process of port traffic logistics according to the flow shop scheduling theory, and construct a collaborative scheduling optimization model for port traffic flow - multi - energy flow based on the relationship between traffic flow and energy;

[0030] Collaborative scheduling processing unit: It is used to combine the overall scheduling optimization model for the whole process of port traffic logistics and the collaborative scheduling optimization model for port traffic flow - multi - energy flow, analyze the whole process of port traffic logistics, extract the energy coupling relationship between the energy system and traffic logistics in the whole process, construct a traffic flow - power resource interconnection framework through the energy coupling relationship, and establish an overall collaborative scheduling model for port area traffic logistics - power resources based on the traffic flow - power resource interconnection framework and the flow shop scheduling theory;

[0031] Scheduling plan determination unit: It is used to solve the overall collaborative scheduling model for port area traffic logistics - power resources by the alternating direction multiplier method and determine the final energy flow and traffic logistics scheduling plan.

[0032] The present invention also provides a computer device, including a memory, a processor, and a computer program stored on the memory. The processor executes the computer program to implement the steps of the power resource regulation method based on the flexible traffic of inland ports.

[0033] The present invention also provides a computer - readable storage medium, on which a computer program / instructions are stored. When the computer program / instructions are executed by a processor, the steps of the power resource regulation method based on the flexible traffic of inland ports are implemented.

[0034] Compared with the prior art, the present invention has the following advantages and technical effects:

[0035] In the construction of the traffic logistics scheduling optimization model, the present invention constructs an overall scheduling optimization model for the whole process of port traffic logistics, proposes an objective function of the optimization model with the goal of minimizing the ship's stay time in port and the total scheduling cost, and comprehensively considers constraints such as berthing, operation of logistics equipment, and scheduling. In terms of multi - energy flow scheduling, the multi - energy flow coupling model based on the energy hub incorporates the objective function of multi - source incentives, with the goal of maximizing the total subsidy income and the lowest operating cost, and sets multiple constraints such as energy supply - demand balance, energy network supply, and equipment operation.

[0036] The present invention proposes a solution method for the collaborative scheduling optimization model of port traffic flow - multi - energy flow, abstracts the whole - process scheduling problem of logistics into a multi - stage operation scheduling problem of an assembly line, and combines a distributed optimization algorithm to achieve the collaborative scheduling of the energy flow and traffic logistics double - flow. Information exchange and scheduling management between different systems are realized in a distributed environment based on partial information consensus, providing innovative technical support for the efficient collaborative utilization of port logistics and energy resources.

[0037] The collaborative scheduling optimization method of the present invention provides a systematic technical framework and model for the multi-energy flow management of ports, significantly improving the resource utilization rate and scheduling efficiency of port traffic logistics. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The drawings constituting a part of this application are used to provide a further understanding of this application. The schematic embodiments of this application and their descriptions are used to explain this application and do not constitute an improper limitation of this application. In the drawings:

[0039] Figure 1 It is a schematic diagram of the overall process collaborative scheduling model architecture of port traffic logistics - power resources in the embodiment of the present invention;

[0040] Figure 2 It is a schematic diagram of the flow shop scheduling process in the embodiment of the present invention;

[0041] Figure 3 It is a flowchart for solving the collaborative scheduling optimization model of port traffic flow - multi-energy flow in the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] It should be noted that, without conflict, the embodiments in this application and the features in the embodiments can be combined with each other. The following will refer to the drawings and combine the embodiments to detail this application.

[0043] It should be noted that the steps shown in the flowchart of the drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0044] The present invention proposes a method for regulating power resources based on flexible traffic in inland ports, including:

[0045] Construct an overall process scheduling optimization model for port traffic logistics according to the flow shop scheduling theory, and construct a collaborative scheduling optimization model of port traffic flow - multi-energy flow based on the relationship between traffic flow and energy;

[0046] Combined with the overall process scheduling optimization model of port traffic logistics and the collaborative scheduling optimization model of port traffic flow - multi-energy flow, analyze the overall process of port traffic logistics, extract the energy coupling relationship between the energy system and traffic logistics in the overall process, construct a traffic flow - power resource interconnection framework through the energy coupling relationship, and establish an overall process collaborative scheduling model of port traffic logistics - power resources based on the traffic flow - power resource interconnection framework and the flow shop scheduling theory;

[0047] The whole - process collaborative scheduling model of port area traffic logistics - power resources is solved by the alternating direction multiplier method to determine the final energy flow and traffic logistics scheduling plan.

[0048] In view of the fact that most existing studies only consider the traffic logistics side or the energy side, and there is less research on the logistics - energy coupling problem, this embodiment proposes a whole - process collaborative scheduling model of port area traffic logistics - power resources to explore the economic operation potential of their collaborative optimization. The improved non - dominated genetic algorithm is used to solve the traffic flow, and the alternating direction multiplier method based on partial information consensus is used to solve the two - flow collaborative optimization model, providing innovative technical support for the efficient collaborative utilization of port logistics and energy resources.

[0049] Furthermore, according to the flow - shop scheduling theory, a whole - process scheduling optimization model of port traffic logistics is constructed, including:

[0050] Set the total power demand of traffic logistics at time t as the sum of the powers of various logistics equipment in this period. Among them, the relevant logistics equipment comprehensively considers facilities such as shore power, electrically - driven quay cranes, gantry cranes, automated guided container trucks, and refrigerated containers:

[0051]

[0052] In the formula, represents the total power demand of logistics entities at time t, respectively represent the powers of shore power, electrically - driven quay cranes, gantry cranes, automated guided containers, and refrigerated containers at time t.

[0053]

[0054] In the formula, represents the 0 - 1 state variable of the j - th shore power supplying power to the i - th ship at time t. If it supplies power, it is 1, otherwise it is 0. is the 0 - 1 variable of the berthing state of the i - th ship. If it berths and connects to shore power, it is 1, otherwise it is 0. is the power demand of the i - th ship in the t - time period. Similarly, are respectively the state variables of electrically - driven quay cranes, gantry cranes, refrigerated containers, automated guided container trucks, and refrigerated containers, and the powers of the k - th electrically - driven quay crane, gantry crane, automated guided container, and refrigerated container in the t - time period.

[0055] Furthermore, set the scheduling objective function of the whole - process scheduling optimization model of port traffic logistics, including:

[0056] The scheduling objective function of the shore power SPS berth is to minimize the average stay time of all ships in the port, which is used as the scheduling objective of the shore power berth. At the same time, the scheduling of various equipment in the traffic logistics is carried out with the goal of minimizing the total scheduling cost of multi-electricity-consuming equipment, which is used as the joint scheduling objective of multi-electricity-consuming equipment, that is, the scheduling objective function of the whole-process scheduling optimization model of the port traffic logistics.

[0057] The constraint conditions of the whole-process scheduling optimization model of the port traffic logistics include logistics equipment scheduling constraints and logistics equipment operation constraints. Among them, the logistics equipment scheduling constraints mean that the scheduling of logistics equipment needs to meet the single-equipment scheduling constraints and the joint scheduling constraints between equipment; the logistics equipment operation constraints mean that the operation of logistics equipment needs to meet the working efficiency, power, and capacity constraints of each equipment.

[0058] The constraint conditions of the whole-process scheduling optimization model of the port traffic logistics also include ship berthing constraints. The ship berthing constraints adopt the continuous berth allocation method, regarding the port shoreline as a continuous whole, and allocating berths according to the arrival time sequence of each ship and the ship length. The shore power within the berth range provides shore power services for each ship.

[0059] Specifically, establish the scheduling objective function of the port traffic logistics. Among them, to ensure that each ship completes loading and unloading and departs smoothly before the planned latest departure time, the scheduling objective function of the SPS berth is to minimize the average stay time of all ships in the port, which is used as the scheduling objective of the shore power berth. At the same time, the scheduling of various equipment in the traffic logistics is carried out with the goal of minimizing the total scheduling cost of multi-electricity-consuming equipment, which is used as the joint scheduling objective of multi-electricity-consuming equipment.

[0060] Finally, set the scheduling constraint conditions of the whole-process scheduling optimization model of the port traffic logistics.

[0061] Among them, for the ship berthing constraints, the continuous berth allocation method widely used in the port is adopted, regarding the port shoreline as a continuous whole, and allocating berths according to the arrival time sequence of each ship and the ship length. The shore power within the berth range provides shore power services for each ship. Assuming that the water depth of each berth meets the berthing requirements of all ships, the following constraints are made on the ship berthing time and berthing position: Ships can only berth after they arrive; The actual departure time of the ship cannot be later than the planned latest departure time; The berthing positions of all ships cannot exceed the range of the port coastline; There cannot be any conflicts in the berthing positions and berthing times of any two ships. Specifically:

[0062] t ber,i ≥t ar r,i (7);

[0063] t ber,i +t SPS,i ≤t dep,i (8);

[0064] l 0,i +l i ≤L(9);

[0065] t ber,i +t SPS,i ≤t ber,q +M(1 - h i,q )(10);

[0066] z i,q +z q,i +h i,q +h q,i ≥1(11);

[0067] l 0,i +l i ≤l q +M(1 - z i,q )(12);

[0068] Wherein, t dep,i 、t ber,i 、t arr,i 、t SPS,i respectively represent the planned latest departure, berthing, arrival and shore power connection times of ship i; l 0,i and l i respectively represent the starting position of the berth of ship i and the ship length (including the berthing safety distance between ships); l q is the length of ship q; L is the shoreline length; h i,q 、h q,i represent the 0 - 1 state variables of the berthing times of any two ships. If ship i berths before ship q, the value is 1, otherwise it is 0; z i,q 、z q,i represent the 0 - 1 state variables of the berthing positions of any two ships. If ship i berths on the left - hand shoreline of ship q, the value is 1, otherwise it is 0; M is an infinite constant. t ber,q is the berthing time of ship q.

[0069] For the logistics equipment scheduling constraints: The scheduling of logistics equipment needs to meet the single - equipment scheduling constraints and the joint scheduling constraints between equipment, including: Each equipment can only serve one ship in each time period; In each time period, the operating quantity of various equipment cannot exceed its total quantity; The number of electric - driven quay cranes serving each ship is limited by the total number of electric - driven quay cranes that can be allocated to the ship; Assuming that the loading and unloading tasks of each ship can be evenly distributed to the electric - driven quay cranes, the duration of a ship occupying the shore power at the berth is the sum of the loading and unloading preparation duration and the time used for loading and unloading all containers. Specifically:

[0070]

[0071] Wherein, rQC,i,min and r QC,i,max respectively represent the upper and lower limits of the number of QCs available for the loading and unloading operations of vessel i. is the state variable of the k-th QC serving the i-th vessel within the t time period, r QC is the number of QCs serving vessels, k is the k-th QC, and T L is the total time period, r C,i represents the number of containers to be loaded and unloaded on the i-th vessel, is the stacking efficiency of the k-th QC within the t time period.

[0072] For the operating constraints of logistics equipment: The operation of logistics equipment needs to meet the constraints of the working efficiency, power, capacity, etc. of each equipment, including: The loading and unloading efficiency of a single electric-driven quay crane, the stacking efficiency of a starter, and the container transportation efficiency of an automated guided container truck in each time period are all subject to upper and lower limit constraints; The power supply of each shore power is subject to upper and lower limit constraints; The charging power and state of charge of each automated guided container truck are subject to upper and lower limit constraints, and the state of charge of each automated guided container truck at the end of the scheduling period needs to be the same as that at the start of the scheduling; The refrigeration power of each refrigerated container and the change in the temperature inside the container are also subject to upper and lower limit constraints. Based on the above analysis, mathematical expressions for various constraints can be established, specifically as follows:

[0073]

[0074]

[0075] In the formula, n QC,k,max and n AGV,m,max and n GC,n,max respectively represent the maximum operating efficiencies of a single electric-driven quay crane, an automated guided container, and a gantry crane; and respectively represent the upper and lower limits of the power supply of the j-th shore power; respectively represent the minimum and maximum charging powers of the j-th automated guided container. and respectively represent the operating efficiencies of the gc and the automated guided container within the t time period, is the power supply of the j-th shore power, is the charging power of the m-th automated guided container.

[0076] Furthermore, a port traffic flow - multi-energy flow collaborative scheduling optimization model is constructed based on traffic flow and energy relationships, including:

[0077] Build a coupling model for the multi - energy flow in the port, combine the output models of each energy device, and introduce a scheduling factor to represent the proportion of the input power of the power grid, natural gas network, and internal heat network allocated to the multi - energy coupling conversion device, and establish the collaborative scheduling optimization model for the port traffic flow - multi - energy flow.

[0078] The objective function of the collaborative scheduling optimization model for the port traffic flow - multi - energy flow is: Considering the combined effect of the demand response incentive and the pollution reduction and carbon emission reduction incentive in the power sector, taking the maximization of the total subsidy revenue as the multi - source incentive target for scheduling response, and taking the minimization of the operating cost as the objective function of the collaborative scheduling optimization model for the port traffic flow - multi - energy flow.

[0079] The constraint conditions of the collaborative scheduling optimization model for the port traffic flow - multi - energy flow include the energy supply - demand balance constraint. The energy system scheduling in each time period needs to meet the power balance constraints of electricity, heat, cold energy, and natural gas, including: The power generation needs to meet the total electricity demand of the infrastructure and transportation and logistics; The heat and cold production power needs to meet the heat and cold energy demands of the port infrastructure.

[0080] Specifically, build a collaborative scheduling optimization model for the port traffic flow - multi - energy flow, combine the output models of each energy device, and introduce a scheduling factor to represent the proportion of the input power of the power grid, natural gas network, and internal heat network allocated to the multi - energy coupling conversion device, and establish the collaborative scheduling optimization model for the port traffic flow - multi - energy flow.

[0081] Next, establish the scheduling objective function of the collaborative scheduling optimization model for the port traffic flow - multi - energy flow. Among them, considering the combined effect of the demand response incentive and the pollution reduction and carbon emission reduction incentive in the power sector, taking the maximization of the total subsidy revenue as the multi - source incentive target for scheduling response. Taking the minimization of the operating cost as the scheduling objective for the multi - energy flow.

[0082] Finally, set the constraint conditions of the collaborative scheduling optimization model for the port traffic flow - multi - energy flow. Among them, for the energy supply - demand balance constraint, the energy system scheduling in each time period needs to meet the power balance constraints of electricity, heat, cold energy, and natural gas, including: The power generation needs to meet the total electricity demand of the port office and other infrastructure and transportation and logistics; The heat and cold production power needs to meet the heat and cold energy demands of the port infrastructure. For the energy network supply constraint, the energy system scheduling is subject to the upper and lower limits of the energy supply from the external power grid and natural gas network. For the energy device operation constraint, the operation of each energy device needs to meet the output constraint conditions. In addition, the gas turbine needs to meet the ramp - up and ramp - down constraints. The energy of the energy storage device needs to meet the capacity constraint, and the energy at the end of the scheduling should be the same as that at the start of the scheduling.

[0083] Furthermore, based on the traffic flow - power resource interconnection framework and the flow - shop scheduling theory, establish a whole - process collaborative scheduling model for the port area transportation and logistics - power resources, including:

[0084] Analyze the entire process of port traffic logistics, refine the energy coupling relationship between the energy system and traffic logistics in the whole process, and establish a whole-process collaborative scheduling model for port traffic logistics - power resources.

[0085] Next, considering a multi-source incentive model that combines the demand response incentives of the power grid power department and the pollution reduction and carbon emission reduction incentives of the environmental department, with the goal of maximizing the overall scheduling benefits of port energy flow and logistics, overall consider the scheduling objectives and constraints of energy flow and traffic logistics, and based on the energy coupling relationship in the whole process of both, establish a whole-process collaborative scheduling model for port traffic logistics - power resources. During the scheduling decision-making process, traffic logistics formulates a whole-process scheduling plan for logistics according to its own scheduling objectives and constraints, and sends the corresponding power consumption plan to the energy system; then the energy system evaluates the power consumption demand of logistics, combines its own benefits, formulates an energy flow scheduling plan, and transmits the power supply plan to traffic logistics; after that, traffic logistics comprehensively considers the available power and its own benefits, adjusts the logistics scheduling plan, and sends the power demand to the energy system again. This process repeats until the overall scheduling benefits of energy flow and traffic logistics are optimal, and the final energy flow and traffic logistics scheduling plans are determined. The energy flow - traffic logistics dual-stream collaborative scheduling framework is as Figure 1 shown.

[0086] Furthermore, the solution to the port traffic flow - multi-energy flow collaborative scheduling optimization model by the alternating direction method of multipliers includes:

[0087] Drawing on the theory in the field of flow shop scheduling, establish a port traffic logistics scheduling process based on the principle of flexible flow shop scheduling. According to the given arrival and departure times of each ship, ship length, and container task volume indicators, divide the ship logistics work into operation stages and time windows. Taking the average in-port time of the ship and the total scheduling cost of the energy system as the optimization objectives, solve the optimal start sequence of the logistics work, as well as the best scheduling plans for berths and equipment at each stage, and solve the proposed port traffic logistics optimization scheduling problem by an improved non-dominated sorting genetic algorithm with double comparison sorting.

[0088] Specifically, based on the flow shop scheduling theory (such as Figure 2) Solve the whole-process collaborative scheduling model for port area traffic logistics - power resources. The arrival and departure times of ships and berthing times, the quantity of containers to be loaded and unloaded, and the allocation and working status of various logistics equipment are all discrete events. The port container logistics scheduling problem is a complex discrete optimization problem, and the number of feasible solutions will increase exponentially with the increase of the scheduling scale. To reduce the computational complexity, in this embodiment, based on the continuity characteristics of processes such as ship berthing, container loading and unloading, transportation, and stacking, the whole-process logistics scheduling problem is abstracted into a pipeline multi-stage job scheduling problem, and the theory in the field of flow shop scheduling is used for reference to establish a port traffic logistics scheduling process based on the flexible flow shop scheduling principle. Following this process, according to the given indicators such as the planned arrival and departure times of each ship, ship length, and container task volume, the ship logistics work is divided into operation stages and time windows, and the optimal start sequence of logistics work and the best scheduling plan for berths and equipment at each stage are solved with the average in-port time of ships and the total cost of energy system scheduling as the optimization objectives.

[0089] Furthermore, determine the final energy flow and traffic logistics scheduling plan, including:

[0090] S1. The traffic logistics formulates a whole-process logistics scheduling plan according to its own scheduling objectives and constraints, and sends the corresponding power consumption plan to the energy system; subsequently, the energy system evaluates the power consumption demand of logistics, combines its own benefits, formulates an energy flow scheduling plan, and transmits the power supply plan to the traffic logistics;

[0091] S2. The traffic logistics comprehensively considers the available power and its own benefits, adjusts the logistics scheduling plan, and sends the power demand to the energy system again;

[0092] Repeat S1 - S2 until the overall scheduling benefits of the energy flow and the traffic logistics are optimal, and determine the final energy flow and traffic logistics scheduling plan.

[0093] Specifically, considering the superiority of non-dominated sorting and crowding distance comparison sorting in individual ranking and excellent individual selection, an improved non-dominated sorting genetic algorithm with double comparison sorting is proposed to solve the proposed port traffic logistics optimization scheduling problem. The initial parent population and the new parent population used for each iteration are both obtained through non-dominated sorting and crowding distance comparison sorting to reduce the influence of randomly generated initial parent populations on the subsequent iteration convergence. Based on non-dominated sorting and crowding distance comparison sorting, the tournament method is used to select the parent population suitable for reproduction and enter the iteration. During the iteration process, the elite strategy is applied to perform non-dominated and crowding distance comparison sorting on the combined population of offspring and parents again, and the optimal individuals are selected to form a new population as the parent population for the next iteration. Until the maximum number of iterations is satisfied, all non-inferior solutions are obtained.

[0094] Next, the alternating direction multiplier method is used to solve the whole-process collaborative scheduling model of port traffic logistics - power resources. According to the supply-demand relationship of electricity, heat, and cooling energy in the port, electricity, heat, and cooling coupling variables are introduced to represent the coupling relationship between energy output and the total energy demand of the port. Based on relevant constraints, the Lagrangian relaxation method is used to increase the consistency of each convergence objective function, and the augmented Lagrangian function of the two-stream collaborative scheduling optimization problem is represented. During the solution process, the coupling variables and Lagrange multipliers are used to solve the function in each iteration. According to the latest coupling variables obtained by iteration, the Lagrange multipliers are updated. When the coupling variables and consensus variables are close enough, the iteration stops. Subsequently, the energy system shares the coupling variable information with traffic logistics to determine the final energy flow and logistics scheduling plan. The whole-process energy system and traffic logistics only need to exchange coupling variable data, avoiding the problem of information privacy between the two parties. The complete solution process of the whole-process collaborative scheduling optimization problem of port energy flow - traffic logistics is as Figure 3 shown.

[0095] This embodiment also provides a power resource regulation system based on the flexible traffic of inland ports, including:

[0096] Model construction unit: used to construct the whole-process scheduling optimization model of port traffic logistics according to the flow shop scheduling theory, and construct the port traffic flow - multi-energy flow collaborative scheduling optimization model based on the traffic flow and energy relationship;

[0097] Collaborative scheduling processing unit: used to combine the whole-process scheduling optimization model of port traffic logistics and the port traffic flow - multi-energy flow collaborative scheduling optimization model, analyze the whole process of port traffic logistics, extract the energy coupling relationship between the energy system and traffic logistics in the whole process, construct a traffic flow - power resource interconnection framework through the energy coupling relationship, and establish a whole-process collaborative scheduling model of port traffic logistics - power resources based on the traffic flow - power resource interconnection framework and the flow shop scheduling theory;

[0098] Scheduling plan determination unit: used to solve the whole-process collaborative scheduling model of port traffic logistics - power resources by the alternating direction multiplier method to determine the final energy flow and traffic logistics scheduling plan. This embodiment has studied in detail the power demand characteristics of traffic logistics processes such as port berths, loading and unloading, transfer, and yards, as well as the power supply characteristics of external power grids, renewable energy sources such as photovoltaic and wind power, and power generation equipment such as gas turbines, constructed the energy coupling relationship and interconnection architecture, and solved the problem that it is difficult to model the two-way coupling between the traffic logistics system and the energy system.

[0099] This embodiment also provides a computer device, including a memory, a processor, and a computer program stored on the memory, and the processor executes the computer program to implement the steps of a power resource regulation method based on the flexible traffic of inland ports.

[0100] This embodiment also provides a computer-readable storage medium, on which a computer program / instructions are stored. When the computer program / instructions are executed by a processor, the steps of a power resource regulation method based on flexible inland port traffic are implemented.

[0101] The above are only the preferred specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present application should be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for regulating power resources based on inland port flexible transportation, characterized in that: include: According to the flow shop scheduling theory, a port transportation logistics whole process scheduling optimization model is constructed, and based on the relationship between traffic flow and energy, a port traffic flow-multi-energy flow collaborative scheduling optimization model is constructed; Combined with the port traffic and logistics full process scheduling optimization model and the port traffic flow-multi-energy flow collaborative scheduling optimization model, the port traffic and logistics full process is analyzed, the energy coupling relationship between the energy system and traffic and logistics in the whole process is extracted, and the traffic flow-power resource interconnection framework is constructed through the energy coupling relationship. Based on the traffic flow-power resource interconnection framework and the flow workshop scheduling theory, a port area traffic and logistics-power resource full process collaborative scheduling model is established; The alternating direction multiplier method is used to solve the coordinated scheduling model of the whole process of port area transportation logistics and power resources to determine the final energy flow and transportation logistics scheduling plan.

2. The method according to claim 1, characterized in that The scheduling objective function of the whole process scheduling optimization model of port transportation logistics is set, including: The scheduling objective function of the SPS berth with shore power is to minimize the average port time of all ships, which is taken as the scheduling objective of the berth with shore power. At the same time, the transportation logistics is scheduled and allocated to various types of equipment with the goal of minimizing the total scheduling cost of multiple power equipment, which is taken as the joint scheduling objective of multiple power equipment, that is, the scheduling objective function of the whole process scheduling optimization model of port transportation logistics.

3. The method according to claim 2, characterized in that The constraint conditions of the port transportation logistics whole process scheduling optimization model include logistics equipment scheduling constraints and logistics equipment operation constraints. Among them, the logistics equipment scheduling constraints are that the scheduling of logistics equipment must satisfy the scheduling constraints of a single device and the joint scheduling constraints between equipment; the logistics equipment operation constraints are that the operation of logistics equipment must satisfy the working efficiency, power and capacity constraints of each equipment.

4. The method according to claim 3, characterized in that The constraint conditions of the port transportation and logistics whole process scheduling optimization model also include ship berthing constraints. The ship berthing constraints adopt a continuous berth allocation method, which regards the port coastline as a continuous whole, allocates berths according to the time sequence of each ship's arrival at the port and the length of the ship, and the shore power within the berth range provides shore power services for each ship.

5. The method according to claim 1, characterized in that The port traffic flow-multi-energy flow coordinated scheduling optimization model is constructed based on the relationship between traffic flow and energy, including: A coupling model of multi-energy flows in ports is established, combined with the output models of various energy equipment, and a scheduling factor is introduced to represent the proportion of input power of the power grid, natural gas network and internal heat network allocated to multi-energy coupling conversion equipment, so as to establish the port traffic flow-multi-energy flow collaborative scheduling optimization model.

6. The method according to claim 5, characterized in that The objective function of the port traffic flow-multi-energy flow collaborative scheduling optimization model is: considering the combined effects of the power sector's demand response incentives and pollution reduction and carbon reduction incentives, maximizing the total subsidy benefits is used as the scheduling response multi-source incentive target, and minimizing the operating costs is used as the objective function of the port traffic flow-multi-energy flow collaborative scheduling optimization model.

7. The method according to claim 5, characterized in that The constraints of the port traffic flow-multi-energy flow collaborative scheduling optimization model include constraints on energy supply and demand balance. The energy system scheduling in each time period must meet the power balance constraints of electricity, heat, cold energy and natural gas, including: the power generation power must meet the total power demand of infrastructure and transportation logistics; the heat and cold production power must meet the heat and cold energy demand of the port infrastructure.

8. The method according to claim 5, characterized in that Solving the port traffic flow-multi-energy flow coordinated scheduling optimization model by the alternating direction multiplier method includes: Drawing on the theories in the field of assembly line workshop scheduling, a port transportation logistics scheduling process based on the principle of flexible assembly line workshop scheduling is established. According to the given planned entry and departure time of each ship, ship length and container task volume indicators, the ship logistics work is divided into operation stages and time windows. Taking the average ship's port time and the total cost of energy system scheduling as optimization goals, the optimal start-up sequence of logistics work and the best scheduling scheme for berths and equipment at each stage are solved. The proposed port transportation logistics optimization scheduling problem is solved by an improved non-dominated sorting genetic algorithm with double comparison sorting.

9. The method according to claim 1, characterized in that: Determine the final energy flow and traffic logistics scheduling plan, including: S1. Transportation and logistics formulates a scheduling plan for the entire logistics process based on its own scheduling goals and constraints, and sends the corresponding power supply plan to the energy system; then the energy system evaluates the power demand of logistics, formulates an energy flow scheduling plan based on its own benefits, and transmits the power supply plan to transportation and logistics; S2, transportation logistics comprehensively considers the available power and its own benefits, adjusts the logistics scheduling plan, and sends the power demand to the energy system again; Repeat S1-S2 until the overall scheduling efficiency of the energy flow and the traffic logistics is optimal, and determine the final scheduling plan of the energy flow and traffic logistics.

10. An electric power resource control system based on inland port flexible transportation, characterized in that: include: Model building unit: used to build a port transportation logistics whole process scheduling optimization model based on the flow shop scheduling theory, and to build a port transportation flow-multi-energy flow collaborative scheduling optimization model based on the relationship between traffic flow and energy; Collaborative scheduling processing unit: used to combine the port transportation and logistics whole process scheduling optimization model and the port traffic flow-multi-energy flow collaborative scheduling optimization model, analyze the whole process of port transportation and logistics, extract the energy coupling relationship between energy system and transportation and logistics in the whole process, build a traffic flow-power resource interconnection framework through the energy coupling relationship, and establish a port area transportation logistics-power resource whole process collaborative scheduling model based on the traffic flow-power resource interconnection framework and the flow shop scheduling theory; The dispatching plan determination unit is used to solve the port area transportation logistics-electricity resource whole process coordinated dispatching model through the alternating direction multiplier method to determine the final energy flow and transportation logistics dispatching plan.

11. A computer device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 9.

12. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 9 are implemented.

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