WO2023160641A1 - 基于分层博弈的港船能源交通系统融合运行方法 - Google Patents

基于分层博弈的港船能源交通系统融合运行方法 Download PDF

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WO2023160641A1
WO2023160641A1 PCT/CN2023/078052 CN2023078052W WO2023160641A1 WO 2023160641 A1 WO2023160641 A1 WO 2023160641A1 CN 2023078052 W CN2023078052 W CN 2023078052W WO 2023160641 A1 WO2023160641 A1 WO 2023160641A1
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port
ship
period
energy
ships
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French (fr)
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文书礼
林安妮
朱淼
江昇
董晊兴
叶惠丽
潘春阳
徐莉婷
马建军
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Shanghai Jiao Tong University
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G06F30/27—Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/083—Shipping
    • G06Q10/08355—Routing methods
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Energy or water supply
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/26—Government or public services
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00—Details relating to CAD techniques
    • G06F2111/04—Constraint-based CAD
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00—Details relating to CAD techniques
    • G06F2111/06—Multi-objective optimisation, e.g. Pareto optimisation using simulated annealing [SA], ant colony algorithms or genetic algorithms [GA]

Definitions

  • the present invention relates to the technical field of optimized operation of port ship energy transportation fusion system, specifically, to a method for integrated operation of port ship energy transportation system based on layered game, and more specifically, to port and ship energy transportation system based on layered game theory Fusion run method.
  • the port undertakes key tasks such as logistics and transportation.
  • Ships are the most important service objects in the port energy system, and their port service management and charging and discharging optimization management are effective means to realize the overall economic efficiency of ports and ships.
  • the present invention establishes a marine energy and service transaction mechanism to realize the energy transaction and service management of the ship mobile micro-grid and the port micro-energy network.
  • the port as an energy agent, participates in the declaration and transaction of electric energy in the public power market, and formulates the energy transaction price between the port and the ship;
  • the port is based on historical ship berth service data, Formulate ship berth service prices.
  • the port energy agent formulates reasonable energy transaction prices and berth service prices to guide ships to call at the port in an orderly manner, and realize the economics of the overall operation of ports and ships through coordinated scheduling.
  • the seaport logistics-energy coupling system Analyzes the energy consumption characteristics of the seaport logistics system, combine the status of ships in the port and the characteristics of load operation, and establish a logistics-energy system coupling load model, so as to realize the coordination between the logistics system and the energy system. Aiming at the lowest operating cost, combined with various forms of energy utilization, the seaport logistics-energy coupling system is collaboratively optimized to obtain ship load operation strategies, quayside crane dispatching schemes, and the output of various energy equipment. Taking a port in Shanghai as an example, the simulation results show that the proposed method can effectively combine the port logistics system and energy system on the basis of fully considering the ship schedule, reduce operating costs and carbon emissions, and improve comprehensive energy utilization. This paper proposes a logistics-energy collaborative optimization scheduling strategy for the integrated energy system of seaports.
  • This method focuses on the economy and environmental protection of the comprehensive energy system of the port, and does not consider the energy transaction mechanism between the ship and the port.
  • the literature does not consider the dynamic response of the ship to the energy transaction price and berth service price under the port optimization decision.
  • energy-transportation integration planning method energy-transportation integration operation method
  • energy-transportation integration evaluation index system energy-transportation integration evaluation index system
  • Patent document CN113822578A (Application No.: 202111117258.6) discloses a distributed energy management method that considers the comprehensive energy system of the ship and port in cooperation. When the ship leaves the port, the energy management is performed inside the comprehensive energy system of the port; , regard the ship as a mobile power source, and use it as an additional power supply device to participate in the comprehensive energy system of the port, so as to realize the full utilization of energy.
  • the present invention solves the energy management problem based on the dynamic programming method for the centralized energy management mode during the ship's navigation, based on the distributed energy management mode of the port comprehensive energy system during the ship's navigation and the collaborative consideration of the comprehensive energy of the ship and the port during the ship's berthing
  • the system mode adopts the distributed alternating multiplier algorithm to optimize the scheduling.
  • the object of the present invention is to provide a method and system for integrated operation of the port ship energy transportation system based on layered game.
  • a layered game-based fusion operation method of a port ship energy transportation system includes:
  • Step S1 Formulate a layered game framework for the integrated operation of ports and ship energy and transportation;
  • Step S2 Based on the optimization objective function and optimization constraints of the port and the optimization objective function and optimization constraints of the ship, a layered game optimization model between the port and the ship is established;
  • Step S3 The layered game structure is based on the port and ship layered game optimization model, and the optimal fusion operation method of the port and ship energy transportation system is obtained by solving the kkt optimality conditional solution method;
  • the port and ship layered game optimization model is that the port acts as the upper-level leader to formulate and execute strategies, and the ship as the lower-level follower uses the strategy formulated by the port as a constraint to make a corresponding response, and the port updates itself according to the response made by the ship. strategy until the game equilibrium is reached.
  • P represents the energy supply equipment of the port
  • S represents the set of ships
  • s p represents the strategy set of the fixed port micro-grid
  • s s represents the strategy set of the mobile micro-grid
  • Income represents the net income realized by the ship mobile microgrid strategy set
  • F s,i is the utility function of the i-th ship; It is the charging and discharging strategy set for other ships.
  • the strategy set sp of the port fixed microgrid includes the active power output of each functional equipment, the price of electricity sold from the port to ships, and the price of electricity purchased from the port to ships.
  • the ship mobile microgrid strategy set s s represents the charging strategy and discharging strategy of the ship.
  • the energy supply equipment of the port includes a port diesel generator, a port energy storage system and a renewable energy power generation system;
  • the port diesel generators include:
  • RU n , RD n are the upper limit of the power increase and decrease range of the nth diesel generator respectively; SD n , SU n are the start-up and shutdown power change values of the nth diesel generator respectively; ⁇ n,t is the indicator variable of the start-stop state of the nth diesel engine in the period t; is the upper and lower limits of the active power output of the nth diesel engine; N is the collection of diesel generators in the port; T is the entire day-ahead scheduling operation period; is the cost of the port diesel generator in period t; Output cost coefficient for the port diesel engine; Contribute to the active power of the nth diesel engine in the port during the period t; Indicates the spinning reserve of the generating set, z n, t indicates the indicator variable for starting the generating set, and y n, t indicates the indicating variable for shutting down the generating set;
  • the port energy storage system includes:
  • ⁇ pch and ⁇ pdis are the charging and discharging efficiencies of the port energy storage equipment; Indicates the state of charge of the port energy storage in the period t; P pess,max and P pess,min are the upper and lower limits of the charging and discharging power of the port energy storage; is the initial capacity of port energy storage; T is the total dispatch period;
  • the renewable energy power generation system includes a photovoltaic power generation system and a wind power generation system, and its respective output P t PV and P t WT can be obtained using historical data based on short-term prediction of machine learning; wherein, P t PV and P t WT represent t periods respectively Photovoltaic and wind power active output.
  • step S2 adopts:
  • Step S2.1 Establish port optimization objective function
  • P t gb , P t gs are the electricity purchase and sales from the grid during the t period, respectively;
  • T is the entire day-ahead scheduling operation period;
  • T b is the berthing period of the ship;
  • ⁇ t is the optimal scheduling time interval;
  • c ps,i,t is the port service fee of the i-th ship during t period; Respectively, the cost of selling/purchasing electricity from the port to ships during the period t;
  • Step S2.2 Establish port optimization constraints
  • Port-ship energy transaction price constraints include:
  • c up and c lo are the upper and lower limits of the energy transaction price between ships in the port;
  • P t pl is the port's own load during t period
  • Step S2.3 Establishing an objective function for ship optimization
  • T is the entire day-ahead scheduling operation period;
  • T b is the berthing period of the ship;
  • ⁇ t is the optimal scheduling time interval;
  • c ps,i,t is the port service fee of the i-th ship during the t period; Respectively, the cost of selling/purchasing electricity from the port to ships during the period t; Respectively, the charge and discharge power of the i-th ship during t period;
  • Step S2.4 Establish ship optimization constraints
  • S i is the amount of cargo to be loaded and unloaded by the i-th ship
  • dl i is the rate of cargo to be loaded and unloaded by the i-th ship
  • N is the collection of diesel generators in the port.
  • step S3 adopts:
  • Step S3.1 using the Karush-Kuhn-Tucker optimality condition to transform the port and ship layered game optimization model into a single-layer mixed integer linear model;
  • Step S3.2 Then use the commercial solver to solve the final optimal energy transaction price strategy for the port.
  • a layered game-based integrated operation system for port and ship energy and transportation systems includes:
  • Module M1 Formulate a layered game framework for the integrated operation of ports and ship energy and transportation;
  • Module M2 Based on the optimization objective function and optimization constraints of the port and the optimization objective function and optimization constraints of the ship, a layered game optimization model between the port and the ship is established;
  • Module M3 The layered game architecture is based on the port and ship layered game optimization model, and the optimal fusion operation method of the port and ship energy transportation system is obtained by solving the kkt optimality conditional solution method;
  • the port and ship layered game optimization model is that the port acts as the upper-level leader to formulate and execute strategies, and the ship as the lower-level follower uses the strategy formulated by the port as a constraint to make a corresponding response, and the port updates itself according to the response made by the ship. strategy until the game equilibrium is reached.
  • G ⁇ (P ⁇ S); s p ; F p ; s s ; F s ⁇ (1)
  • P represents the energy supply equipment of the port
  • S represents the set of ships
  • s p represents the strategy set of the fixed port micro-grid
  • s s represents the strategy set of the mobile micro-grid
  • Income represents the net income realized by the ship mobile microgrid strategy set
  • F s,i is the utility function of the i-th ship; Charging and discharging strategy set for other ships;
  • the strategy set s p of the fixed port microgrid includes the active output of each functional equipment, the price of electricity sold by the port to ships, and the price of electricity purchased by ports from ships;
  • the ship mobile microgrid strategy set s s represents the charging strategy and discharging strategy of the ship;
  • the energy supply equipment of the port includes port diesel generators, port energy storage systems and renewable energy power generation systems;
  • the port diesel generators include:
  • RU n , RD n are the upper limit of the power increase and decrease range of the nth diesel generator respectively; SD n , SU n are the start-up and shutdown power change values of the nth diesel generator respectively; ⁇ n,t is the indicator variable of the start-stop state of the nth diesel engine in the period t; is the upper and lower limits of the active power output of the nth diesel engine; N is the collection of diesel generators in the port; T is the entire day-ahead scheduling operation period; is the cost of the port diesel generator in period t; Output cost coefficient for the port diesel engine; Contribute to the active power of the nth diesel engine in the port during the period t; Indicates the spinning reserve of the generating set, z n, t indicates the indicator variable for starting the generating set, and y n, t indicates the indicating variable for shutting down the generating set;
  • the port energy storage system includes:
  • ⁇ pch and ⁇ pdis are the charging and discharging efficiencies of the port energy storage equipment; Indicates the state of charge of the port energy storage in the period t; P pess,max and P pess,min are the upper and lower limits of the charging and discharging power of the port energy storage; is the initial capacity of port energy storage; T is the total dispatch period;
  • the renewable energy power generation system includes a photovoltaic power generation system and a wind power generation system, and its respective output P t PV and P t WT can be obtained using historical data based on short-term prediction of machine learning; wherein, P t PV and P t WT represent t periods respectively Photovoltaic and wind power active output.
  • P t gb , P t gs are the electricity purchase and sales from the grid during the t period, respectively;
  • T is the entire day-ahead scheduling operation period;
  • T b is the berthing period of the ship;
  • ⁇ t is the optimal scheduling time interval;
  • c ps, i , t is the port service charge of the i-th ship during t period; Respectively, the cost of selling/purchasing electricity from the port to ships during the period t;
  • Port-ship energy transaction price constraints include:
  • c up and c lo are the upper and lower limits of the energy transaction price between ships in the port;
  • T is the entire day-ahead scheduling operation period;
  • T b is the berthing period of the ship;
  • ⁇ t is the optimal scheduling time interval;
  • c ps,i,t is the port service fee of the i-th ship during the t period; Respectively, the cost of selling/purchasing electricity from the port to ships during the period t; Respectively, the charge and discharge power of the i-th ship during t period;
  • S i is the amount of cargo to be loaded and unloaded by the i-th ship
  • dl i is the speed of cargo to be loaded and unloaded by the i-th ship
  • N is the collection of diesel generators in the port
  • the module M3 uses:
  • Module M3.1 Using the Karush-Kuhn-Tucker optimality condition to transform the hierarchical game optimization model of ports and ships into a single-layer mixed integer linear model;
  • Module M3.2 Then use the commercial solver to solve the final optimal energy transaction price strategy for the port.
  • Figure 1 is a flow chart of the integrated operation method of the port ship energy transportation system based on hierarchical game.
  • Figure 2 shows the electricity purchased by the port from the grid.
  • Figure 3 shows the optimal pricing strategy for port and ship energy transactions.
  • the invention aims to solve the overall operation economy of the port and ship energy transportation system.
  • the purpose of the present invention is to provide a port-ship energy transportation system fusion operation method based on layered game, in order to improve the overall operation economy of the port micro-energy system and the ship mobile micro-energy system, and guide the orderly docking of ships to receive Berth services and energy transactions.
  • the present invention has the following characteristics.
  • a layered game model for the integrated operation of port and ship energy transportation is proposed, taking into account the response of energy transactions and berth service strategies to energy prices and berth service prices after ships call at the port, it can increase port revenue, reduce ship operating costs, and improve overall operation Economical, to achieve a win-win situation for the main body of the port and the main body of the ship.
  • the hierarchical game model is transformed into a mixed integer linear programming problem, and the optimal pricing decision for port energy transactions is solved.
  • the present invention proposes a layered game model for integrated operation of energy and transportation between ports and ships.
  • Ports play the roles of guides and setters of energy transactions and service prices, and ships play the role of followers of energy and service transactions.
  • the overall economics of the port-ship operation can be effectively improved through coordinated scheduling, and a win-win situation for the port and ship entities can be achieved.
  • a layered game-based integrated operation method for port and ship energy and transportation systems includes:
  • Step S1 Formulate a layered game framework for the integrated operation of ports and ship energy and transportation;
  • the port plays the role of the upper-level leader, and prioritizes the energy transaction price between the port and the ship.
  • the ship plays the role of the lower-level follower, passively accepting the energy transaction price information released by the upper-level leader, but the charging and discharging of the ship Strategies will in turn affect the ultimate benefits of top leaders.
  • the step S1 is specifically adopted:
  • the port In order to maximize the benefits of all game participants, the port should not only consider its own interests when setting the energy transaction price, but also consider the dynamic response behavior of the ship, that is, there are interests between the port and the ship. game.
  • P represents the energy supply equipment of the port, including: port diesel generators, port energy storage systems, and renewable energy power generation systems
  • S represents a collection of ships
  • s p represents the strategy set of port fixed microgrids, including: Output, the price of electricity sold from ports to ships, and the price of electricity purchased from ports to ships.
  • s s represents the ship's mobile microgrid strategy set, which represents the ship's charging strategy and discharge strategy
  • F p represents the net income realized by the strategy set based on the port fixed microgrid
  • F s represents the net income realized by the ship's mobile microgrid strategy set
  • the port diesel generator includes:
  • RU n , RD n are the upper limit of the power increase and decrease range of the nth diesel generator respectively; SD n , SU n are the start-up and shutdown power change values of the nth diesel generator respectively; ⁇ n,t is the indicator variable of the start-stop state of the nth diesel engine in the period t; is the upper and lower limits of the active power output of the nth diesel engine; N is the collection of diesel generators in the port; T is the entire day-ahead scheduling operation period; is the cost of the port diesel generator in period t; Output cost coefficient for the port diesel engine; Contribute to the active power of the nth diesel engine in the port during the period t; Indicates the spinning reserve of the generating set, z n, t indicates the indicator variable for starting the generating set, and y n, t indicates the indicating variable for shutting down the generating set;
  • the port energy storage system includes:
  • ⁇ pch and ⁇ pdis are the charging and discharging efficiencies of the port energy storage equipment; Indicates the state of charge of the port energy storage in the period t; P pess,max and P pess,min are the upper and lower limits of the charging and discharging power of the port energy storage; is the initial capacity of port energy storage; T is the total dispatch period;
  • the renewable energy power generation system includes a photovoltaic power generation system and a wind power generation system, and its respective output P t PV and P t WT can be obtained using historical data based on short-term prediction of machine learning; wherein, P t PV and P t WT represent t periods respectively Photovoltaic and wind power active output.
  • the port optimizes its own operation strategy by setting the energy transaction price between the port and the ship, and realizes the maximum net profit F p ; the ship according to the energy transaction price set by the port, the mobile micro-grid of the ship participates in the energy management of the port-ship integrated operation through dynamic response, and arranges itself reasonably Purchasing energy and selling energy strategy to realize maximum self-profit F s .
  • F s,i is the utility function of the i-th ship; It is the charging and discharging strategy set for other ships.
  • Step S2 Based on the optimization objective function and optimization constraints of the port and the optimization objective function and optimization constraints of the ship, a layered game optimization model between the port and the ship is established;
  • Described step S2 specifically adopts:
  • Step S2.1 As the leader of offshore energy transactions and service prices, the port optimizes its operation with the goal of maximizing net income.
  • the net income includes income from energy sales to ships calling at the port, income from providing berth services to The electricity purchase cost of the upper-level public grid and the fuel cost of its own energy supply equipment.
  • P t gb , P t gs are the electricity purchase and sales from the grid during the t period, respectively;
  • T is the entire day-ahead scheduling operation period;
  • T b is the berthing period of the ship;
  • ⁇ t is the optimal scheduling time interval;
  • c ps, i , t is the port service charge of the i-th ship during t period; Respectively, the cost of selling/purchasing electricity from the port to ships during the period t;
  • Step S2.2 Establish port optimization constraints
  • Port-ship energy transaction price constraints include:
  • c up and c lo are the upper and lower limits of the energy transaction price between ships in the port;
  • P t pl is the port's own load during t period
  • Step S2.3 The port formulates the price for providing energy trading and berth services to the ship.
  • the ship decides the strategy of energy consumption and receiving berth service according to the set price, and maximizes its own income.
  • the objective function can be expressed as:
  • T is the entire day-ahead scheduling operation period;
  • T b is the berthing period of the ship;
  • ⁇ t is the optimal scheduling time interval;
  • c ps,i,t is the port service fee of the i-th ship during the t period; Respectively, the cost of selling/purchasing electricity from the port to ships during the period t; Respectively, the charge and discharge power of the i-th ship during t period;
  • Step S2.4 Establish ship optimization constraints
  • S i is the amount of cargo to be loaded and unloaded by the i-th ship
  • dl i is the rate of cargo to be loaded and unloaded by the i-th ship
  • N is the collection of diesel generators in the port.
  • Step S3 The layered game structure is based on the port and ship layered game optimization model, and the optimal fusion operation method of the port and ship energy transportation system is obtained by solving the kkt optimality conditional solution method;
  • the port-ship layered game model is a two-level programming problem, wherein the charging and discharging complementary constraints of the lower model Constraint relaxation can be performed to convert the underlying model from a non-convex to a linear programming model; through the Karush-Kuhn-Tucker optimality condition, the bilevel programming problem can be converted into a single-level mixed integer linear programming problem, and then the high-efficiency commercial solution can be used Finally, the optimal energy transaction price strategy of the port is obtained.
  • Step S3.1 using the Karush-Kuhn-Tucker optimality condition to transform the port and ship layered game optimization model into a single-layer mixed integer linear model;
  • Step S3.2 Then use the commercial solver to solve the final optimal energy transaction price strategy for the port.
  • the hierarchical master-slave game can be regarded as a special kind of non-zero-sum non-cooperative game.
  • Participant 1 plays a leading role, formulates and implements personal strategies; participant 2 takes the strategies of participant 1 as constraints and makes rational responses.
  • Player 1 considers the rational response of player 2, and then rationally chooses its own strategy. In the end, the two reach a game equilibrium, and neither party can obtain higher returns by changing its own strategy.
  • the port-ship layered game optimization model is a port-ship layered game: the port plays the role of the leader and setter of upper-level energy transactions and service prices, and the ship plays the role of follower of lower-level energy and service transactions.
  • the port as the leader of the upper layer, formulates and implements strategies, and the ship, as the follower of the lower layer, takes the strategy formulated by the port as a constraint and makes a corresponding response.
  • the port updates its own strategy according to the response of the ship until the game equilibrium is reached.
  • a layered game-based integrated operation system for port and ship energy and transportation systems includes:
  • Module M1 Formulate a layered game framework for the integrated operation of ports and ship energy and transportation;
  • the port plays the role of the upper-level leader, and prioritizes the energy transaction price between the port and the ship.
  • the ship plays the role of the lower-level follower, passively accepting the energy transaction price information released by the upper-level leader, but the charging and discharging of the ship Strategies will in turn affect the ultimate benefits of top leaders.
  • the specific use of the module M1 is: in order to maximize the benefits of all game participants, the port should not only consider its own interests when setting the energy transaction price, but also consider the dynamic response behavior of the ship, that is, there are interests between the port and the ship. game.
  • P represents the energy supply equipment of the port, including: port diesel generators, port energy storage systems, and renewable energy power generation systems
  • S represents a collection of ships
  • s p represents the strategy set of port fixed microgrids, including: Output, the price of electricity sold from ports to ships, and the price of electricity purchased from ports to ships.
  • s s represents the ship's mobile microgrid strategy set, which represents the ship's charging strategy and discharge strategy
  • F p represents the net income realized by the strategy set based on the port fixed microgrid
  • F s represents the net income realized by the ship's mobile microgrid strategy set
  • the port diesel generator includes:
  • RU n , RD n are the upper limit of the power increase and decrease range of the nth diesel generator respectively; SD n , SU n are the start-up and shutdown power change values of the nth diesel generator respectively; ⁇ n,t is the indicator variable of the start-stop state of the nth diesel engine in the period t; is the upper and lower limits of the active power output of the nth diesel engine; N is the collection of diesel generators in the port; T is the entire day-ahead scheduling operation period; is the cost of the port diesel generator in period t; Output cost coefficient for the port diesel engine; Contribute to the active power of the nth diesel engine in the port during the period t; Indicates the spinning reserve of the generating set, z n, t indicates the indicator variable for starting the generating set, and y n, t indicates the indicating variable for shutting down the generating set;
  • the port energy storage system includes:
  • ⁇ pch and ⁇ pdis are the charging and discharging efficiencies of the port energy storage equipment; Indicates the state of charge of the port energy storage in the period t; P pess,max and P pess,min are the upper and lower limits of the charging and discharging power of the port energy storage; is the initial capacity of port energy storage; T is the total dispatch period;
  • the renewable energy power generation system includes a photovoltaic power generation system and a wind power generation system, and its respective output P t PV and P t WT can be obtained using historical data based on short-term prediction of machine learning; wherein, P t PV and P t WT represent t periods respectively Photovoltaic and wind power active output.
  • the port optimizes its own operation strategy by setting the energy transaction price between the port and the ship, and realizes the maximum net profit F p ; the ship according to the energy transaction price set by the port, the mobile micro-grid of the ship participates in the energy management of the port-ship integrated operation through dynamic response, and arranges itself reasonably Purchasing energy and selling energy strategy to realize maximum self-profit F s .
  • F s,i is the utility function of the i-th ship; It is the charging and discharging strategy set for other ships.
  • Module M2 Based on the optimization objective function and optimization constraints of the port and the optimization objective function and optimization constraints of the ship, a layered game optimization model between the port and the ship is established;
  • the module M2 specifically adopts:
  • Module M2.1 As a leader in offshore energy transactions and service prices, the port optimizes its operation with the goal of maximizing net income.
  • the net income includes income from energy sales to ships calling at the port, income from providing berth services to The electricity purchase cost of the upper-level public grid and the fuel cost of its own energy supply equipment.
  • P t gb , P t gs are the electricity purchase and sales from the grid during the t period, respectively;
  • T is the entire day-ahead scheduling operation period;
  • T b is the berthing period of the ship;
  • ⁇ t is the optimal scheduling time interval;
  • c ps,i,t is the port service fee of the i-th ship during t period; Respectively, the cost of selling/purchasing electricity from the port to ships during the period t;
  • Port-ship energy transaction price constraints include:
  • c up and c lo are the upper and lower limits of the energy transaction price between ships in the port;
  • P t pl is the port's own load during t period
  • Module M2.3 The port formulates prices for energy transactions and berth services provided to ships. According to the set prices, ships make decisions on energy consumption and receive berth service strategies to maximize their own benefits.
  • the objective function can be expressed as:
  • T is the entire day-ahead scheduling operation period;
  • T b is the berthing period of the ship;
  • ⁇ t is the optimal scheduling time interval;
  • c ps,i,t is the port service fee of the i-th ship during the t period; Respectively, the cost of selling/purchasing electricity from the port to ships during the period t; Respectively, the charge and discharge power of the i-th ship during t period;
  • S i is the amount of cargo to be loaded and unloaded by the i-th ship
  • dl i is the rate of cargo to be loaded and unloaded by the i-th ship
  • N is the collection of diesel generators in the port.
  • Module M3 The layered game architecture is based on the port and ship layered game optimization model, and the optimal fusion operation method of the port and ship energy transportation system is obtained by solving the kkt optimality conditional solution method;
  • the module M3 specifically uses: the port-ship layered game model, which belongs to a two-level programming problem, wherein the charging and discharging complementary constraints of the lower model Constraint relaxation can be performed to convert the underlying model from a non-convex to a linear programming model; through the Karush-Kuhn-Tucker optimality condition, the bilevel programming problem can be converted into a single-level mixed integer linear programming problem, and then the high-efficiency commercial solution can be used Finally, the optimal energy transaction price strategy of the port is obtained.
  • Module M3.1 Using the Karush-Kuhn-Tucker optimality condition to transform the hierarchical game optimization model of ports and ships into a single-layer mixed integer linear model;
  • Module M3.2 Then use the commercial solver to solve the final optimal energy transaction price strategy for the port.
  • the hierarchical master-slave game can be regarded as a special kind of non-zero-sum non-cooperative game.
  • Participant 1 plays a leading role, formulates and implements personal strategies; participant 2 takes the strategies of participant 1 as constraints and makes rational responses.
  • Player 1 considers the rational response of player 2, and then rationally chooses its own strategy. In the end, the two reach a game equilibrium, and neither party can obtain higher returns by changing its own strategy.
  • the port-ship layered game optimization model is a port-ship layered game: the port plays the role of the leader and setter of upper-level energy transactions and service prices, and the ship plays the role of follower of lower-level energy and service transactions.
  • the port as the leader of the upper layer, formulates and implements strategies, and the ship, as the follower of the lower layer, takes the strategy formulated by the port as a constraint and makes a corresponding response.
  • the port updates its own strategy according to the response of the ship until the game equilibrium is reached.
  • Embodiment 2 is a preferred example of embodiment 1
  • the energy storage capacity of the port is 24MWh, and the charging and discharging efficiency is 85%.
  • this example illustrates that based on the layered game model, the port-ship energy transportation fusion system realizes the optimal decision-making of energy transaction prices between ports and ships and the orderly guidance for ships to participate in energy transactions at ports. Effectively improve the overall operating economy.
  • the system, device and each module thereof provided by the present invention can be completely programmed by logically programming the method steps.
  • the same program is implemented in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, and embedded microcontrollers, among others. Therefore, the system, device and each module provided by the present invention can be regarded as a hardware component, and the modules included in it for realizing various programs can also be regarded as the structure in the hardware component; A module for realizing various functions can be regarded as either a software program realizing a method or a structure within a hardware component.
  • the present invention has the following beneficial effects:
  • the present invention establishes a marine energy transaction and service transaction mechanism to simultaneously realize energy transaction and service management of the ship mobile micro-grid and the port micro-energy network.
  • the present invention establishes a port-ship layered game model, and the port micro-energy network can effectively realize the overall operation economy by setting prices to guide the ship's port service and energy transactions;
  • the present invention uses the Karush-Kuhn-Tucker condition to convert the hierarchical master-slave game model into a mixed integer linear programming problem, and obtains the optimal pricing decision of port energy;
  • the present invention establishes a layered game model for integrated operation of port and ship energy transportation, and solves the energy transaction and service management problems of ship mobile microgrid and port microenergy network. Taking into account the response of the energy trading strategy between ships to energy prices after the ship is at the port, it can increase the port's revenue, reduce the operating cost of the ship's port call, improve the overall operating economy, and achieve a win-win situation for the main body of the port and the main body of the ship.

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Abstract

本发明提供了一种基于分层博弈的港船能源交通系统融合运行方法及系统，包括：步骤S1：制定港口与船舶能源交通融合运行的分层博弈架构；步骤S2：基于港口的优化目标函数和优化约束条件以及船舶的优化目标函数和优化约束条件建立港口与船舶分层博弈优化模型；步骤S3：分层博弈架构基于港口与船舶分层博弈优化模型，通过kkt最优性条件求解方法求解得到港口与船舶能源交通系统最优融合运行方法；所述港口与船舶分层博弈优化模型是港口作为上层的引导者制定策略并执行，船舶作为下层跟随者以港口制定的策略作为约束，做出相应的反应，港口根据船舶做出的反应更新自身策略，直至达到博弈均衡。

Description

[根据细则26改正 20.04.2023]基于分层博弈的港船能源交通系统融合运行方法及系统 技术领域
本发明涉及港口船舶能源交通融合系统优化运行技术领域，具体地，涉及基于分层博弈的港船能源交通系统融合运行方法，更为具体地，涉及基于分层博弈理论的港口与船舶能源交通系统融合运行方法。
 背景技术
港口作为链接海洋与陆地的重要枢纽，承担着物流交通运输等关键任务。而船舶是港口能源系统中最为重要的服务对象，其靠港服务管理及充放电优化管理是实现港口与船舶整体运行经济性的有效手段。
为了鼓励船舶与港口能源间进行能源交互，本发明建立了海上能源与服务交易机制，以实现船舶移动微电网与港口微能源网的能源交易与服务管理。在能源市场交易模型中，港口作为能源代理商参与公共电力市场的电能申报与交易，并制定港口与船舶间的日前能源交易价格；在海上泊位服务交易模型中，港口基于历史船舶泊位服务数据，制定船舶泊位服务价格。基于分层主从博弈模型，港口能源代理商制定出合理的能源交易价格和泊位服务价格引导船舶有序靠港，通过协调调度实现港口与船舶整体运行的经济性。
中国电机工程学报1-12[2021-12-22]黄逸文,黄文焘,卫卫,邰能灵,李然的大型海港综合能源系统物流-能量协同优化调度方法，为实现港口节能减排和能效提升，提出一种海港综合能源系统物流-能量协同优化调度方法，充分挖掘物流系统与能源系统结合的经济优化潜力。从物流系统运行特性出发，分析岸桥调度对船舶在港状态影响，建立港船物流协同调度模型。分析海港物流系统用能特点，结合船舶在港状态和负荷运行特性，建立物流-能源系统耦合负荷模型，以此实现物流系统与能源系统间的协同。以运行成本最低为目标，结合多种能源利用形式，对海港物流-能源耦合系统协同优化，得到船舶负荷运行策略和岸桥调度方案，以及各能源设备出力。以上海某港口为算例，仿真结果表明所提方法在充分考虑船舶行程安排的基础上，能够有效结合港口物流系统与能源系统，降低运行成本和碳排放量，提高能源综合利用率。该文献提出了一种海港综合能源系统物流-能量协同优化调度策略。该方法着眼于港口综合能源系统的经济性和环保性，未考虑船舶与港口间的能源交易机制，此外该文献也未考虑港口优化决策下船舶针对能源交易价格及泊位服务价格的动态响应。
中国电机工程学报:1-20[2021-12-22].方斯顿,赵常宏,丁肇豪,张沈习,廖瑞金.面向碳中和的港口综合能源系统(二)：能源-交通融合中的柔性资源与关键技术[J/OL]，港口综合能源系统是交通-能源融合发展的标志。作为论文的第二部分，本文首先从能源侧与交通侧分析港口能源-交通融合中的柔性资源，并提出这些柔性资源的建模方法。然后基于当前陆地综合能源系统的研究，本文展望了港口综合能源系统的能流建模方法。最后结合当前研究现状，提出能源-交通融合规划方法、能源-交通融合运行方法，能源-交通融合评估指标体系三个未来关键技术。该文献综述了港口与船舶融合系统的关键技术，未涉及具体技术方案，也未考虑港船间的能源交易机制。
F.D.Kanellos,"Multiagent-System-Based Operation Scheduling of Large Ports’Power Systems With Emissions Limitation,"in IEEE Systems Journal,vol.13,no.2,pp.1831-1840,June 2019,doi:10.1109/JSYST.2018.2850970.该文献针对大型港口优化运行提出了基于多代理系统的方法，着眼于港口自身的经济性与环境友好性，未考虑到港船间的能源交易策略优化。
专利文献CN113822578A(申请号：202111117258.6)公开了一种协同考虑船港综合能源系统的分布式能源管理方法，当船舶离港期间，港口综合能源系统内部进行能量管理；当船舶进岸靠港停留期间，将船舶视为移动电源，将其作为额外的供电设备参与至港口综合能源系统中，从而实现能源的充分利用。本发明针对船舶航行期间的集中式能量管理模式基于动态规划方法对其能量管理问题进行求解，基于船舶航行期间港口综合能源系统的分布式能量管理模式和船舶靠港期间协同考虑船舶与港口综合能源系统模式则采用分布式交替乘子算法对其进行优化调度。
发明内容
针对现有技术中的缺陷，本发明的目的是提供一种基于分层博弈的港船能源交通系统融合运行方法及系统。
根据本发明的实施例提供的一种基于分层博弈的港船能源交通系统融合运行方法，包括：
步骤S1：制定港口与船舶能源交通融合运行的分层博弈架构；
步骤S2：基于港口的优化目标函数和优化约束条件以及船舶的优化目标函数和优化约束条件建立港口与船舶分层博弈优化模型；
步骤S3：分层博弈架构基于港口与船舶分层博弈优化模型，通过kkt最优性条件求解方法求解得到港口与船舶能源交通系统最优融合运行方法；
所述港口与船舶分层博弈优化模型是港口作为上层的引导者制定策略并执行，船舶作为下层跟随者以港口制定的策略作为约束，做出相应的反应，港口根据船舶做出的反应更新自身策略，直至达到博弈均衡。
进一步地，所述步骤S1采用：G＝{(P∪S)；sp；Fp；ss；Fs}  (1)
其中，P表示港口的供能设备；S表示船舶集合；sp表示港口固定式微电网的策略集；ss表示船舶移动式微电网策略集；Fp表示基于港口固定式微电网的策略集实现的净收益；Fs表示船舶移动式微电网策略集实现的净收益；
当博弈达到均衡时，效用函数应满足：
其中，Fs,i为第i艘船舶的效用函数；为其它船舶的充放电策略集。
进一步地，所述港口固定式微电网的策略集sp包括各功能设备有功出力、港口向船舶售电价格以及港口向船舶购电价格。
进一步地，所述船舶移动式微电网策略集ss表示船舶的充电策略和放电策略。
进一步地，所述港口的供能设备包括港口柴油发电机、港口储能系统以及可再生能源发电系统；
所述港口柴油发电机包括：
其中，RUn、RDn分别为第n台柴油发电机的功率升高和降低范围上限；SDn、SUn分别为第n台柴油发电机的启动和关停功率变化值；γn,t为第n台柴油机在t时段的启停状态指示变量；为第n台柴油机有功出力上下限；N为港口柴油发电机集合；T为整个日前调度运行时段；为t时段港口柴油发电机成本；为港口柴油机出力成本系数；为港口第n台柴油机t时段有功出力；表示发电机组的旋转备用，zn,t表示发电机组启动指示变量，yn,t表示发电机组关停指示变量；
所述港口储能系统包括：
其中，为储能荷电状态上限；ηpch，ηpdis分别为港口储能设备充放电效率；表示t时段港口储能的荷电状态；Ppess,max、Ppess,min为港口储能充放电功率上下限；为港口储能初始容量；T为总调度时段；
所述可再生能源发电系统包括光伏发电系统和风力发电系统，其各自出力Pt PV和Pt WT可以利用历史数据基于机器学习短期预测得到；其中，Pt PV和Pt WT分别表示t时段光伏和风电有功出力。
进一步地，所述步骤S2采用：
步骤S2.1：建立港口优化目标函数；
其中，分别为t时段港口从电网购电和售电价格；Pt gb，Pt gs分别为t时段从电网购电量和售电量；T为整个日前调度运行时段；Tb为船舶靠港停泊时段；△t为优化调度时间间隔；cps,i,t为第i艘船t时段靠港服务费；分别为t时段港口向船舶售电/购电费用；分别为第i艘船t时段充放电功率；表示第i艘船t时段的服务费，I表示参与港船互动的在港船舶集合；
步骤S2.2：建立港口优化约束条件；
港口-船舶能源交易价格约束包括：
其中，cup，clo为港船间能源交易价格上下限；
功率平衡约束：
其中，Pt pl为t时段港口自身负荷；
步骤S2.3：建立船舶优化目标函数；
其中，T为整个日前调度运行时段；Tb为船舶靠港停泊时段；△t为优化调度时间间隔；cps,i,t为第i艘船t时段靠港服务费；分别为t时段港口向船舶售电/购电费用；分别为第i艘船t时段充放电功率；
步骤S2.4：建立船舶优化约束条件；
全电力船储能相关约束采用：
其中，Tb为船舶靠港停泊时段；△t为优化调度时间间隔；I为计划到港船舶集合；分别为第i艘船t时段船载储能的充放电功率；分别为第i艘船t时段船载储能的充放电功率上限值；为第i艘船t时段船载储能的荷电能量；ηsch，ηsdis分别为船载储能的充放电效率；分别为第i艘船t时段充放电功率；
物流相关约束采用：
假定港口各调度时段对在港船舶的装卸速率基本一致，则
其中，Si为第i艘船需装卸货物量，dli第i艘船需装卸货物速率；N为港口柴油发电机集合。
进一步地，所述步骤S3采用：
步骤S3.1：利用Karush-Kuhn-Tucker最优性条件将港口与船舶分层博弈优化模型转化为单层混合整数线性模型；
步骤S3.2：再利用商业求解器求解最终得到港口最优能源交易价格策略。
根据本发明提供的一种基于分层博弈的港船能源交通系统融合运行系统，包括：
模块M1：制定港口与船舶能源交通融合运行的分层博弈架构；
模块M2：基于港口的优化目标函数和优化约束条件以及船舶的优化目标函数和优化约束条件建立港口与船舶分层博弈优化模型；
模块M3：分层博弈架构基于港口与船舶分层博弈优化模型，通过kkt最优性条件求解方法求解得到港口与船舶能源交通系统最优融合运行方法；
所述港口与船舶分层博弈优化模型是港口作为上层的引导者制定策略并执行，船舶作为下层跟随者以港口制定的策略作为约束，做出相应的反应，港口根据船舶做出的反应更新自身策略，直至达到博弈均衡。
进一步地，在所述模块M1中：G＝{(P∪S)；sp；Fp；ss；Fs}  (1)
其中，P表示港口的供能设备；S表示船舶集合；sp表示港口固定式微电网的策略集；ss表示船舶移动式微电网策略集；Fp表示基于港口固定式微电网的策略集实现的净收益；Fs表示船舶移动式微电网策略集实现的净收益；
当博弈达到均衡时，效用函数应满足：
其中，Fs,i为第i艘船舶的效用函数；为其它船舶的充放电策略集；
所述港口固定式微电网的策略集sp包括各功能设备有功出力、港口向船舶售电价格以及港口向船舶购电价格；
所述船舶移动式微电网策略集ss表示船舶的充电策略和放电策略；
所述港口的供能设备包括港口柴油发电机、港口储能系统以及可再生能源发电系统；
所述港口柴油发电机包括：
其中，RUn、RDn分别为第n台柴油发电机的功率升高和降低范围上限；SDn、SUn分别为第n台柴油发电机的启动和关停功率变化值；γn,t为第n台柴油机在t时段的启停状态指示变量；为第n台柴油机有功出力上下限；N为港口柴油发电机集合；T为整个日前调度运行时段；为t时段港口柴油发电机成本；为港口柴油机出力成本系数；为港口第n台柴油机t时段有功出力；表示发电机组的旋转备用，zn,t表示发电机组启动指示变量，yn,t表示发电机组关停指示变量；
所述港口储能系统包括：
其中，为储能荷电状态上限；ηpch，ηpdis分别为港口储能设备充放电效率；表示t时段港口储能的荷电状态；Ppess,max、Ppess,min为港口储能充放电功率上下限；为港口储能初始容量；T为总调度时段；
所述可再生能源发电系统包括光伏发电系统和风力发电系统，其各自出力Pt PV和Pt WT可以利用历史数据基于机器学习短期预测得到；其中，Pt PV和Pt WT分别表示t时段光伏和风电有功出力。
进一步地，在所述模块M2中：
模块M2.1：建立港口优化目标函数；
其中，分别为t时段港口从电网购电和售电价格；Pt gb，Pt gs分别为t时段从电网购电量和售电量；T为整个日前调度运行时段；Tb为船舶靠港停泊时段；△t为优化调度时间间隔；cps, i , t为第i艘船t时段靠港服务费；分别为t时段港口向船舶售电/购电费用；分别为第i艘船t时段充放电功率；表示第i艘船t时段的服务费，I表示参与港船互动的在港船舶集合；
模块M2.2：建立港口优化约束条件；
港口-船舶能源交易价格约束包括：
其中，cup，clo为港船间能源交易价格上下限；
功率平衡约束：
其中，为t时段港口自身负荷；
模块M2.3：建立船舶优化目标函数；
其中，T为整个日前调度运行时段；Tb为船舶靠港停泊时段；△t为优化调度时间间隔；cps,i,t为第i艘船t时段靠港服务费；分别为t时段港口向船舶售电/购电费用；分别为第i艘船t时段充放电功率；
模块M2.4：建立船舶优化约束条件；
全电力船储能相关约束采用：
其中，Tb为船舶靠港停泊时段；△t为优化调度时间间隔；I为计划到港船舶集合；分别为第i艘船t时段船载储能的充放电功率；分别为第i艘船t时段船载储能的充放电功率上限值；为第i艘船t时段船载储能的荷电能量；ηsch，ηsdis分别为船载储能的充放电效率；分别为第i艘船t时段充放电功率；
物流相关约束采用：
假定港口各调度时段对在港船舶的装卸速率基本一致，则
其中，Si为第i艘船需装卸货物量，dli第i艘船需装卸货物速率；N为港口柴油发电机集合；
所述模块M3采用：
模块M3.1：利用Karush-Kuhn-Tucker最优性条件将港口与船舶分层博弈优化模型转化为单层混合整数线性模型；
模块M3.2：再利用商业求解器求解最终得到港口最优能源交易价格策略。
 附图说明
通过阅读参照以下附图对非限制性实施例所作的详细描述，本发明的其它特征、目的和优点将会变得更明显：
图1为基于分层博弈的港船能源交通系统融合运行方法流程图。
图2为港口从电网购电量。
图3为港船能源交易最优定价策略。
 具体实施方式
下面结合具体实施例对本发明进行详细说明。以下实施例将有助于本领域的技术人员进一步理解本发明，但不以任何形式限制本发明。应当指出的是，对本领域的普通技术人员来说，在不脱离本发明构思的前提下，还可以做出若干变化和改进。这些都属于本发明的保护范围。
本发明旨在解决港口与船舶能源交通系统的整体运行经济性。为此，本发明的目的在于提供一种基于分层博弈的港-船能源交通系统融合运行方法，以期提高港口微能源系统与船舶移动微能源系统整体运行经济性，引导船舶有序靠港接受泊位服务及能源交易。本发明具有以下特点。
建立海上日前能源交易和服务机制，将港口作为能源交易及服务价格的引导者和制定者；船舶作为跟随者，根据港口制定的能源交易价格，决策是否参与港船间能源交易。
提出了港口与船舶能源交通融合运行的分层博弈模型，计及船舶靠港后能源交易及泊位服务策略对能源价格与泊位服务价格的响应，能够提高港口收益，降低船舶运行成本，改善整体运行经济性，实现港口主体与船舶主体的双赢。
考虑了船舶移动式微电网向港口固定式微电网反向送电(Ship to Port,S2P)交易行为，能够高效调动船舶参与港船能源交易的积极性。
利用Karush-Kuhn-Tucker最优性条件将分层博弈模型转换为混合整数线性规划问题，求解得到港口能源交易的最优定价决策。
本发明提出了港口与船舶能源交通融合运行的分层博弈模型，港口扮演能源交易及服务价格的引导者和制定者的角色，船舶扮演能源与服务交易的跟随者的角色。计及船舶靠港后能源交易及泊位服务策略对能源价格与泊位服务价格的响应，通过协同调度有效提升港口-船舶整体运行经济性，实现港口主体与船舶主体的双赢。
实施例1
根据本发明提供的一种基于分层博弈的港船能源交通系统融合运行方法，包括：
步骤S1：制定港口与船舶能源交通融合运行的分层博弈架构；
在该分层博弈模型中，港口扮演上层领导者角色，优先制定港船间的能源交易价格，船舶扮演下层跟随者角色，被动地接受上层领导者发布的能源交易价格信息，但船舶的充放电策略会反过来影响上层领导者的最终收益。
所述步骤S1具体采用：为了使得所有博弈参与者自身效益最大化，港口在制定能源交易价格时，不能只考虑自身的利益，还需要考虑船舶的动态响应行为，即港口和船舶之间存在利益博弈。港船间的分层主从博弈可描述为：G＝{(P∪S)；sp；Fp；ss；Fs}  (1)
其中，P表示港口的供能设备，包括：港口柴油发电机、港口储能系统以及可再生能源发电系统；S表示船舶集合；sp表示港口固定式微电网的策略集，包括：各功能设备有功出力、港口向船舶售电价格以及港口向船舶购电价格。；ss表示船舶移动式微电网策略集表示船舶的充电策略和放电策略；Fp表示基于港口固定式微电网的策略集实现的净收益；Fs表示船舶移动式微电网策略集实现的净收益；
其中，所述港口柴油发电机包括：
其中，RUn、RDn分别为第n台柴油发电机的功率升高和降低范围上限；SDn、SUn分别为第n台柴油发电机的启动和关停功率变化值；γn,t为第n台柴油机在t时段的启停状态指示变量；为第n台柴油机有功出力上下限；N为港口柴油发电机集合；T为整个日前调度运行时段；为t时段港口柴油发电机成本；为港口柴油机出力成本系数；为港口第n台柴油机t时段有功出力；表示发电机组的旋转备用，zn,t表示发电机组启动指示变量，yn,t表示发电机组关停指示变量；
其中，所述港口储能系统包括：
其中，为储能荷电状态上限；ηpch，ηpdis分别为港口储能设备充放电效率；表示t时段港口储能的荷电状态；Ppess,max、Ppess,min为港口储能充放电功率上下限；为港口储能初始容量；T为总调度时段；
所述可再生能源发电系统包括光伏发电系统和风力发电系统，其各自出力Pt PV和Pt WT可以利用历史数据基于机器学习短期预测得到；其中，Pt PV和Pt WT分别表示t时段光伏和风电有功出力。
港口通过制定港船间能源交易价格，优化自身运行策略，实现净收益Fp最大；船舶根据港口制定的能源交易价格，船舶移动式微电网通过动态响应参与港-船融合运行能量管理，合理安排自身购能售能策略，实现自身收益Fs最大。
当博弈达到均衡时，此时港口和船舶任何一方都无法单方面改变自身策略来获得更高的收益，效用函数应满足：
其中，Fs,i为第i艘船舶的效用函数；为其它船舶的充放电策略集。
步骤S2：基于港口的优化目标函数和优化约束条件以及船舶的优化目标函数和优化约束条件建立港口与船舶分层博弈优化模型；
所述步骤S2具体采用：
步骤S2.1：港口作为海上能源交易及服务价格的领导者，以净收益最大为优化运行目标，其净收益包括向靠港船舶售能的收入、向靠港船舶提供泊位服务的收入、向上级公共电网购电成本和自身供能设备燃料成本。建立港口优化目标函数；
其中，分别为t时段港口从电网购电和售电价格；Pt gb，Pt gs分别为t时段从电网购电量和售电量；T为整个日前调度运行时段；Tb为船舶靠港停泊时段；△t为优化调度时间间隔；cps, i , t为第i艘船t时段靠港服务费；分别为t时段港口向船舶售电/购电费用；分别为第i艘船t时段充放电功率；表示第i艘船t时段的服务费，I表示参与港船互动的在港船舶集合；
步骤S2.2：建立港口优化约束条件；
港口-船舶能源交易价格约束包括：
其中，cup，clo为港船间能源交易价格上下限；
功率平衡约束：
其中，Pt pl为t时段港口自身负荷；
步骤S2.3：港口制定向船舶提供能源交易及泊位服务的价格，船舶根据制定的价格，决策用能及接受泊位服务的策略，最大化自身收益，其目标函数可以表示为：
其中，T为整个日前调度运行时段；Tb为船舶靠港停泊时段；△t为优化调度时间间隔；cps,i,t为第i艘船t时段靠港服务费；分别为t时段港口向船舶售电/购电费用；分别为第i艘船t时段充放电功率；
步骤S2.4：建立船舶优化约束条件；
全电力船储能相关约束采用：
其中，Tb为船舶靠港停泊时段；△t为优化调度时间间隔；I为计划到港船舶集合；分别为第i艘船t时段船载储能的充放电功率；分别为第i艘船t时段船载储能的充放电功率上限值；为第i艘船t时段船载储能的荷电能量；ηsch，ηsdis分别为船载储能的充放电效率；分别为第i艘船t时段充放电功率；
物流相关约束采用：
假定港口各调度时段对在港船舶的装卸速率基本一致，则
其中，Si为第i艘船需装卸货物量，dli第i艘船需装卸货物速率；N为港口柴油发电机集合。
步骤S3：分层博弈架构基于港口与船舶分层博弈优化模型，通过kkt最优性条件求解方法求解得到港口与船舶能源交通系统最优融合运行方法；
所述步骤S3具体采用：所述的港口-船舶分层博弈模型，属于双层规划问题，其中下层模型的充放电互补约束可进行约束松弛，从而将下层模型由非凸转化为线性规划模型；通过Karush-Kuhn-Tucker最优性条件将双层规划问题转换为单层混合整数线性规划问题，再利用高效率的商业求解器求解，最终得到港口最优能源交易价格策略。
步骤S3.1：利用Karush-Kuhn-Tucker最优性条件将港口与船舶分层博弈优化模型转化为单层混合整数线性模型；
步骤S3.2：再利用商业求解器求解最终得到港口最优能源交易价格策略。
所述分层博弈框架：分层主从博弈可以看作一类特殊的非零和非合作博弈。参与者1起领导作用，制定个人策略并执行；参与者2以参与者1的策略为约束，做出理性反应。参与者1考虑到参与者2的理性反应，再理性地选择自身策略。最终二者达到博弈均衡，任何一方都无法通过改变自身策略获得更高收益。
所述港口与船舶分层博弈优化模型是港口与船舶分层博弈：港口扮演上层能源交易及服务价格的引导者和制定者的角色，船舶扮演下层能源与服务交易的跟随者的角色。港口作为上层的引导者制定策略并执行，船舶作为下层跟随者以港口制定的策略作为约束，做出相应的反应，港口根据船舶做出的反应更新自身策略，直至达到博弈均衡。
根据本发明提供的一种基于分层博弈的港船能源交通系统融合运行系统，包括：
模块M1：制定港口与船舶能源交通融合运行的分层博弈架构；
在该分层博弈模型中，港口扮演上层领导者角色，优先制定港船间的能源交易价格，船舶扮演下层跟随者角色，被动地接受上层领导者发布的能源交易价格信息，但船舶的充放电策略会反过来影响上层领导者的最终收益。
所述模块M1具体采用：为了使得所有博弈参与者自身效益最大化，港口在制定能源交易价格时，不能只考虑自身的利益，还需要考虑船舶的动态响应行为，即港口和船舶之间存在利益博弈。港船间的分层主从博弈可描述为：G＝{(P∪S)；sp；Fp；ss；Fs}  (1)
其中，P表示港口的供能设备，包括：港口柴油发电机、港口储能系统以及可再生能源发电系统；S表示船舶集合；sp表示港口固定式微电网的策略集，包括：各功能设备有功出力、港口向船舶售电价格以及港口向船舶购电价格。；ss表示船舶移动式微电网策略集表示船舶的充电策略和放电策略；Fp表示基于港口固定式微电网的策略集实现的净收益；Fs表示船舶移动式微电网策略集实现的净收益；
其中，所述港口柴油发电机包括：
其中，RUn、RDn分别为第n台柴油发电机的功率升高和降低范围上限；SDn、SUn分别为第n台柴油发电机的启动和关停功率变化值；γn,t为第n台柴油机在t时段的启停状态指示变量；为第n台柴油机有功出力上下限；N为港口柴油发电机集合；T为整个日前调度运行时段；为t时段港口柴油发电机成本；为港口柴油机出力成本系数；为港口第n台柴油机t时段有功出力；表示发电机组的旋转备用，zn,t表示发电机组启动指示变量，yn,t表示发电机组关停指示变量；
其中，所述港口储能系统包括：
其中，为储能荷电状态上限；ηpch，ηpdis分别为港口储能设备充放电效率；表示t时段港口储能的荷电状态；Ppess,max、Ppess,min为港口储能充放电功率上下限；为港口储能初始容量；T为总调度时段；
所述可再生能源发电系统包括光伏发电系统和风力发电系统，其各自出力Pt PV和Pt WT可以利用历史数据基于机器学习短期预测得到；其中，Pt PV和Pt WT分别表示t时段光伏和风电有功出力。
港口通过制定港船间能源交易价格，优化自身运行策略，实现净收益Fp最大；船舶根据港口制定的能源交易价格，船舶移动式微电网通过动态响应参与港-船融合运行能量管理，合理安排自身购能售能策略，实现自身收益Fs最大。
当博弈达到均衡时，此时港口和船舶任何一方都无法单方面改变自身策略来获得更高的收益，效用函数应满足：
其中，Fs,i为第i艘船舶的效用函数；为其它船舶的充放电策略集。
模块M2：基于港口的优化目标函数和优化约束条件以及船舶的优化目标函数和优化约束条件建立港口与船舶分层博弈优化模型；
所述模块M2具体采用：
模块M2.1：港口作为海上能源交易及服务价格的领导者，以净收益最大为优化运行目标，其净收益包括向靠港船舶售能的收入、向靠港船舶提供泊位服务的收入、向上级公共电网购电成本和自身供能设备燃料成本。建立港口优化目标函数；
其中，分别为t时段港口从电网购电和售电价格；Pt gb，Pt gs分别为t时段从电网购电量和售电量；T为整个日前调度运行时段；Tb为船舶靠港停泊时段；△t为优化调度时间间隔；cps,i,t为第i艘船t时段靠港服务费；分别为t时段港口向船舶售电/购电费用；分别为第i艘船t时段充放电功率；表示第i艘船t时段的服务费，I表示参与港船互动的在港船舶集合；
模块M2.2：建立港口优化约束条件；
港口-船舶能源交易价格约束包括：
其中，cup，clo为港船间能源交易价格上下限；
功率平衡约束：
其中，Pt pl为t时段港口自身负荷；
模块M2.3：港口制定向船舶提供能源交易及泊位服务的价格，船舶根据制定的价格，决策用能及接受泊位服务的策略，最大化自身收益，其目标函数可以表示为：
其中，T为整个日前调度运行时段；Tb为船舶靠港停泊时段；△t为优化调度时间间隔；cps,i,t为第i艘船t时段靠港服务费；分别为t时段港口向船舶售电/购电费用；分别为第i艘船t时段充放电功率；
模块M2.4：建立船舶优化约束条件；
全电力船储能相关约束采用：
其中，Tb为船舶靠港停泊时段；△t为优化调度时间间隔；I为计划到港船舶集合；分别为第i艘船t时段船载储能的充放电功率；分别为第i艘船t时段船载储能的充放电功率上限值；为第i艘船t时段船载储能的荷电能量；ηsch，ηsdis分别为船载储能的充放电效率；分别为第i艘船t时段充放电功率；
物流相关约束采用：
假定港口各调度时段对在港船舶的装卸速率基本一致，则
其中，Si为第i艘船需装卸货物量，dli第i艘船需装卸货物速率；N为港口柴油发电机集合。
模块M3：分层博弈架构基于港口与船舶分层博弈优化模型，通过kkt最优性条件求解方法求解得到港口与船舶能源交通系统最优融合运行方法；
所述模块M3具体采用：所述的港口-船舶分层博弈模型，属于双层规划问题，其中下层模型的充放电互补约束可进行约束松弛，从而将下层模型由非凸转化为线性规划模型；通过Karush-Kuhn-Tucker最优性条件将双层规划问题转换为单层混合整数线性规划问题，再利用高效率的商业求解器求解，最终得到港口最优能源交易价格策略。
模块M3.1：利用Karush-Kuhn-Tucker最优性条件将港口与船舶分层博弈优化模型转化为单层混合整数线性模型；
模块M3.2：再利用商业求解器求解最终得到港口最优能源交易价格策略。
所述分层博弈框架：分层主从博弈可以看作一类特殊的非零和非合作博弈。参与者1起领导作用，制定个人策略并执行；参与者2以参与者1的策略为约束，做出理性反应。参与者1考虑到参与者2的理性反应，再理性地选择自身策略。最终二者达到博弈均衡，任何一方都无法通过改变自身策略获得更高收益。
所述港口与船舶分层博弈优化模型是港口与船舶分层博弈：港口扮演上层能源交易及服务价格的引导者和制定者的角色，船舶扮演下层能源与服务交易的跟随者的角色。港口作为上层的引导者制定策略并执行，船舶作为下层跟随者以港口制定的策略作为约束，做出相应的反应，港口根据船舶做出的反应更新自身策略，直至达到博弈均衡。
实施例2
实施例2是实施例1的优选例
考虑15条不同装载货物量的全电力船舶抵达港口，参与港口船舶间的能源交易，港口储能容量为24MWh，充放电效率均为85％。
参照图1至图3所示，通过本实例说明，基于分层博弈模型，港口-船舶能源交通融合系统实现了港船间能源交易价格的优化决策及船舶靠港参与能源交易的有序引导，有效提升了整体运行经济性。
本领域技术人员知道，除了以纯计算机可读程序代码方式实现本发明提供的系统、装置及其各个模块以外，完全可以通过将方法步骤进行逻辑编程来使得本发明提供的系统、装置及其各个模块以逻辑门、开关、专用集成电路、可编程逻辑控制器以及嵌入式微控制器等的形式来实现相同程序。所以，本发明提供的系统、装置及其各个模块可以被认为是一种硬件部件，而对其内包括的用于实现各种程序的模块也可以视为硬件部件内的结构；也可以将用于实现各种功能的模块视为既可以是实现方法的软件程序又可以是硬件部件内的结构。
与现有技术相比，本发明具有如下的有益效果：
1、本发明建立了海上能源交易与服务交易机制，以同时实现船舶移动微电网和港口微能源网的能源交易与服务管理。
2、本发明建立港口-船舶分层博弈模型，港口微能源网通过制定价格引导船舶靠港服务与能源交易，能够有效实现整体运行经济性；
3、考虑了船舶移动式微电网向港口固定式微电网反向送电(Ship to Port,S2P)交易行为，能够高效调动船舶参与港船能源交易的积极性；
4、本发明利用Karush-Kuhn-Tucker条件将分层主从博弈模型转换为混合整数线性规划问题，求解得到港口能源最优定价决策；
5、本发明建立了港口与船舶能源交通融合运行的分层博弈模型，解决了船舶移动微电网与港口微能源网的能源交易与服务管理问题。计及船舶靠港后港船间的能源交易策略对能源价格的响应，能够提高港口收益，同时降低船舶靠港运行成本，改善整体运行经济性，实现港口主体与船舶主体的双赢。
以上对本发明的具体实施例进行了描述。需要理解的是，本发明并不局限于上述特定实施方式，本领域技术人员可以在权利要求的范围内做出各种变化或修改，这并不影响本发明的实质内容。在不冲突的情况下，本申请的实施例和实施例中的特征可以任意相互组合。

Claims (10)

  1. 一种基于分层博弈的港船能源交通系统融合运行方法，其特征在于，包括：
    步骤S1：制定港口与船舶能源交通融合运行的分层博弈架构；
    步骤S2：基于港口的优化目标函数和优化约束条件以及船舶的优化目标函数和优化约束条件建立港口与船舶分层博弈优化模型；
    步骤S3：分层博弈架构基于港口与船舶分层博弈优化模型，通过kkt最优性条件求解方法求解得到港口与船舶能源交通系统最优融合运行方法；
    所述港口与船舶分层博弈优化模型是港口作为上层的引导者制定策略并执行，船舶作为下层跟随者以港口制定的策略作为约束，做出相应的反应，港口根据船舶做出的反应更新自身策略，直至达到博弈均衡。
  2. 根据权利要求1所述的基于分层博弈的港船能源交通系统融合运行方法，其特征在于，所述步骤S1采用：
    G＝{(P∪S)；sp；Fp；ss；Fs}  (1)
    其中，P表示港口的供能设备；S表示船舶集合；sp表示港口固定式微电网的策略集；ss表示船舶移动式微电网策略集；Fp表示基于港口固定式微电网的策略集实现的净收益；Fs表示船舶移动式微电网策略集实现的净收益；
    当博弈达到均衡时，效用函数应满足：

    其中，Fs,i为第i艘船舶的效用函数；为其它船舶的充放电策略集。
  3. 根据权利要求2所述的基于分层博弈的港船能源交通系统融合运行方法，其特征在于，所述港口固定式微电网的策略集sp包括各功能设备有功出力、港口向船舶售电价格以及港口向船舶购电价格。
  4. 根据权利要求2所述的基于分层博弈的港船能源交通系统融合运行方法，其特征在于，所述船舶移动式微电网策略集ss表示船舶的充电策略和放电策略。
  5. 根据权利要求2所述的基于分层博弈的港船能源交通系统融合运行方法，其特征在于，所述港口的供能设备包括港口柴油发电机、港口储能系统以及可再生能源发电系统；
    所述港口柴油发电机包括：


    其中，RUn、RDn分别为第n台柴油发电机的功率升高和降低范围上限；SDn、SUn分别为第n台柴油发电机的启动和关停功率变化值；γn,t为第n台柴油机在t时段的启停状态指示变量；为第n台柴油机有功出力上下限；N为港口柴油发电机集合；T为整个日前调度运行时段；为t时段港口柴油发电机成本；为港口柴油机出力成本系数；为港口第n台柴油机t时段有功出力；表示发电机组的旋转备用，zn,t表示发电机组启动指示变量，yn,t表示发电机组关停指示变量；
    所述港口储能系统包括：


    其中，为储能荷电状态上限；ηpch，ηpdis分别为港口储能设备充放电效率；表示t时段港口储能的荷电状态；Ppess,max、Ppess，min为港口储能充放电功率上下限；为港口储能初始容量；T为总调度时段；
    所述可再生能源发电系统包括光伏发电系统和风力发电系统，其各自出力Pt PV和Pt WT可以利用历史数据基于机器学习短期预测得到；其中，Pt PV和Pt WT分别表示t时段光伏和风电有功出力。
  6. 根据权利要求1所述的基于分层博弈的港船能源交通系统融合运行方法，其特征在于，所述步骤S2采用：
    步骤S2.1：建立港口优化目标函数；
    其中，分别为t时段港口从电网购电和售电价格；Pt gb，Pt gs分别为t时段从电网购电量和售电量；T为整个日前调度运行时段；Tb为船舶靠港停泊时段；△t为优化调度时间间隔；cps,i,t为第i艘船t时段靠港服务费；分别为t时段港口向船舶售电/购电费用；分别为第i艘船t时段充放电功率；表示第i艘船t时段的服务费，I表示参与港船互动的在港船舶集合；
    步骤S2.2：建立港口优化约束条件；
    港口-船舶能源交易价格约束包括：
    其中，cup，clo为港船间能源交易价格上下限；
    功率平衡约束：
    其中，Pt pl为t时段港口自身负荷；
    步骤S2.3：建立船舶优化目标函数；
    其中，T为整个日前调度运行时段；Tb为船舶靠港停泊时段；△t为优化调度时间间隔；cps,i,t为第i艘船t时段靠港服务费；分别为t时段港口向船舶售电/购电费用；分别为第i艘船t时段充放电功率；
    步骤S2.4：建立船舶优化约束条件；
    全电力船储能相关约束采用：

    其中，Tb为船舶靠港停泊时段；△t为优化调度时间间隔；I为计划到港船舶集合；分别为第i艘船t时段船载储能的充放电功率；分别为第i艘船t时段船载储能的充放电功率上限值；为第i艘船t时段船载储能的荷电能量；ηsch，ηsdis分别为船载储能的充放电效率；分别为第i艘船t时段充放电功率；
    物流相关约束采用：
    假定港口各调度时段对在港船舶的装卸速率基本一致，则
    其中，Si为第i艘船需装卸货物量，dli第i艘船需装卸货物速率；N为港口柴油发电机集合。
  7. 根据权利要求1所述的基于分层博弈的港船能源交通系统融合运行方法，其特征在于，所述步骤S3采用：
    步骤S3.1：利用Karush-Kuhn-Tucker最优性条件将港口与船舶分层博弈优化模型转化为单层混合整数线性模型；
    步骤S3.2：再利用商业求解器求解最终得到港口最优能源交易价格策略。
  8. 一种基于分层博弈的港船能源交通系统融合运行系统，其特征在于，包括：
    模块M1：制定港口与船舶能源交通融合运行的分层博弈架构；
    模块M2：基于港口的优化目标函数和优化约束条件以及船舶的优化目标函数和优化约束条件建立港口与船舶分层博弈优化模型；
    模块M3：分层博弈架构基于港口与船舶分层博弈优化模型，通过kkt最优性条件求解方法求解得到港口与船舶能源交通系统最优融合运行方法；
    所述港口与船舶分层博弈优化模型是港口作为上层的引导者制定策略并执行，船舶作为下层跟随者以港口制定的策略作为约束，做出相应的反应，港口根据船舶做出的反 应更新自身策略，直至达到博弈均衡。
  9. 根据权利要求8所述的基于分层博弈的港船能源交通系统融合运行系统，其特征在于，在所述模块M1中：
    G＝{(P∪S)；sp；Fp；ss；Fs}  (1)
    其中，P表示港口的供能设备；S表示船舶集合；sp表示港口固定式微电网的策略集；ss表示船舶移动式微电网策略集；Fp表示基于港口固定式微电网的策略集实现的净收益；Fs表示船舶移动式微电网策略集实现的净收益；
    当博弈达到均衡时，效用函数应满足：

    其中，Fs,i为第i艘船舶的效用函数；为其它船舶的充放电策略集；
    所述港口固定式微电网的策略集sp包括各功能设备有功出力、港口向船舶售电价格以及港口向船舶购电价格；
    所述船舶移动式微电网策略集ss表示船舶的充电策略和放电策略；
    所述港口的供能设备包括港口柴油发电机、港口储能系统以及可再生能源发电系统；
    所述港口柴油发电机包括：


    其中，RUn、RDn分别为第n台柴油发电机的功率升高和降低范围上限；SDn、SUn分别为第n台柴油发电机的启动和关停功率变化值；γn,t为第n台柴油机在t时段的启停状态指示变量；为第n台柴油机有功出力上下限；N为港口柴油发电机集合；T为整个日前调度运行时段；为t时段港口柴油发电机成本；为港口柴油机出力成本系数；为港口第n台柴油机t时段有功出力；表示发电机组的旋转备用，zn,t表示发电机组启动指示变量，yn,t表示发电机组关停指示变量；
    所述港口储能系统包括：


    其中，为储能荷电状态上限；ηpch，ηpdis分别为港口储能设备充放电效率；表示t时段港口储能的荷电状态；Ppess,max、Ppess,min为港口储能充放电功率上下限；为港口储能初始容量；T为总调度时段；
    所述可再生能源发电系统包括光伏发电系统和风力发电系统，其各自出力Pt PV和Pt WT可以利用历史数据基于机器学习短期预测得到；其中，Pt PV和Pt WT分别表示t时段光伏和风电有功出力。
  10. 根据权利要求8所述的基于分层博弈的港船能源交通系统融合运行系统，其特征在于，在所述模块M2中：
    模块M2.1：建立港口优化目标函数；
    其中，分别为t时段港口从电网购电和售电价格；Pt gb，Pt gs分别为t时段从电网购电量和售电量；T为整个日前调度运行时段；Tb为船舶靠港停泊时段；△t为优化调度时间间隔；cps,i,t为第i艘船t时段靠港服务费；分别为t时段港口向船舶售电/购电费用；分别为第i艘船t时段充放电功率；表示第i艘船t时段的服务费，I表示参与港船互动的在港船舶集合；
    模块M2.2：建立港口优化约束条件；
    港口-船舶能源交易价格约束包括：
    其中，cup，clo为港船间能源交易价格上下限；
    功率平衡约束：
    其中，为t时段港口自身负荷；
    模块M2.3：建立船舶优化目标函数；
    其中，T为整个日前调度运行时段；Tb为船舶靠港停泊时段；△t为优化调度时间间隔；cps,i,t为第i艘船t时段靠港服务费；分别为t时段港口向船舶售电/购电费用；分别为第i艘船t时段充放电功率；
    模块M2.4：建立船舶优化约束条件；
    全电力船储能相关约束采用：

    其中，Tb为船舶靠港停泊时段；△t为优化调度时间间隔；I为计划到港船舶集合；分别为第i艘船t时段船载储能的充放电功率；分别为第i艘船t时段船载储能的充放电功率上限值；为第i艘船t时段船载储能的荷电能量；ηsch，ηsdis分别为船载储能的充放电效率；分别为第i艘船t时段充放电功率；
    物流相关约束采用：
    假定港口各调度时段对在港船舶的装卸速率基本一致，则
    其中，Si为第i艘船需装卸货物量，dli第i艘船需装卸货物速率；N为港口柴油发电机集合；
    所述模块M3采用：
    模块M3.1：利用Karush-Kuhn-Tucker最优性条件将港口与船舶分层博弈优化模型转化为单层混合整数线性模型；
    模块M3.2：再利用商业求解器求解最终得到港口最优能源交易价格策略。
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