CN-121998174-A - Port comprehensive energy coordination optimization method and system based on multiple constraints

CN121998174ACN 121998174 ACN121998174 ACN 121998174ACN-121998174-A

Abstract

The invention provides a port comprehensive energy coordination optimization method and system based on multiple constraints, the method comprises the steps of obtaining ship arrival data, building a port comprehensive energy coordination optimization model based on the ship arrival data, enabling an objective function of the model to comprise carbon emission generated by fuel consumption, carbon emission generated by main network electricity purchasing quantity, total fuel cost, main network electricity purchasing cost, energy power supply unit start-stop cost and punishment cost after a dispatching period is finished, utilizing ship and berthing station distribution, loading and unloading subsystem shore bridge distribution, electric collector card operation logic, constructing constraint conditions of an objective function by ship electricity, cold and heat loads, ship units and load demand balance, calling Gurobi a solver to solve the objective function to obtain a port comprehensive energy coordination optimization strategy, and executing port comprehensive energy coordination according to the port comprehensive energy coordination optimization strategy. The port resource utilization efficiency can be improved, and the port resource utilization method is more green and can be operated continuously.

Inventors

DONG ZHENGCHENG
WANG YU
TIAN MENG
GUO LINHAI
Shi Fangqi
LIU XIN

Assignees

武汉理工大学

Dates

Publication Date: 20260508
Application Date: 20260108

Claims (9)

1. The port comprehensive energy coordination optimization method based on multiple constraints is characterized by comprising the following steps of: The method comprises the steps of 1, obtaining ship arrival data, and establishing a port comprehensive energy coordination optimization model based on the ship arrival data, wherein an objective function of the port comprehensive energy coordination optimization model comprises carbon emission generated by fuel consumption, carbon emission generated by main network electricity purchasing quantity, total fuel cost, main network electricity purchasing cost, energy power supply unit start-stop cost and punishment cost of unloaded goods after a dispatching cycle is finished; Step 2, calling Gurobi a solver to solve the objective function to obtain a port comprehensive energy coordination optimization strategy for the port comprehensive energy coordination optimization model constructed in the step 1, wherein constraint conditions participate in solving; And 3, executing port comprehensive energy coordination according to the port comprehensive energy coordination optimization strategy.
2. The port comprehensive energy coordination optimization method based on multiple constraints according to claim 1, wherein the calculation formula of the objective function of the port comprehensive energy coordination optimization model is: (1) Wherein, min z is an objective function, d is a fuel emission coefficient; fuel consumed for the PGU; e is the cost coefficient of the power carbon energy consumption; to consume fuel costs; The electricity purchasing cost is the main network; The start-stop cost of the energy supply unit is set; The method comprises the steps of determining a punishment cost coefficient for the unloaded goods after the dispatching cycle is finished, wherein T represents the moment, and T represents the dispatching cycle.
3. The port comprehensive energy coordination optimization method based on multiple constraints according to claim 1, wherein constraints constructed by ship berthing scheduling ensure that each ship can berth orderly, and specific constraints comprise: (2) wherein, the formula (2) represents the consistency relation constraint between the ship berthing state and berthing allocation decision; a variable 0-1, indicating whether or not the vessel k is moored; A variable of 0-1 is used for indicating whether the ship k occupies the berthing station at the moment T of the berthing station B; (3) wherein equation (3) represents a berth service constraint; The variable is 0-1, which indicates whether the ship k occupies the berthing station at the time T of the berthing station B, wherein N is the number of ships, B is the number of berths, and T indicates a scheduling period; (4) Wherein equation (4) represents allocation constraints on the berths in the scheduling period; The variable is 0-1, which indicates whether the ship k starts berthing at the moment T of the berthing station B, N is the number of ships, B is the number of berths, T indicates a scheduling period; (5) wherein equation (5) represents a continuity constraint of the berthing state; a variable of 0-1 indicates whether the ship k occupies the berthing station at the time t of the berthing station b; A variable of 0-1, which indicates whether the ship k starts berthing at the moment t of the berthing station b; A variable of 0-1 indicates whether the ship k finishes berthing at the moment T of the berthing station B, wherein N is the number of ships, B is the number of berths, and T is a scheduling period; (6) Wherein, the formula (6) shows that the berthing time of the ship is not earlier than the actual arrival time; a variable of 0-1 indicates whether the ship k starts berthing at the moment t of berthing station B, wherein N is the number of ships, B is the number of berths, and a k is the moment of expected berthing of the ship k; (7) Wherein, formula (7) represents the total amount constraint of the port serviceable ship; The total number of berthing stations is the total number of berthing stations; A variable of 0-1, which indicates whether the ship k is moored at the moment T, wherein T indicates a scheduling period, and N is the number of ships; (8) wherein, formula (8) represents a ship unloading constraint, the total demand of which must be jointly satisfied by the completed part and the unfinished part; Crane _rate is the loading and unloading efficiency of a single crane shore bridge at each moment; a variable 0-1, indicating whether or not the vessel k is moored at time t; the cargo transferring capacity of the ship k which is not completed at the end of the current time domain; the cargo transportation demand for the ship k; T represents a scheduling period; (9) (10) (11) Wherein equations (9) - (11) represent vessel k berthing time continuity constraints; A variable 0-1, which indicates whether the ship k starts berthing at the time t; a variable 0-1, indicating whether or not the vessel k is moored at time t; a variable of 0-1 indicates whether the ship k finishes berthing at the moment T, wherein N is the number of the ships, and T is a scheduling period; (12) Wherein, formula (12) represents a ship arrival operation constraint; A variable of 0-1 indicates whether the ship k is berthed at the time t, N is the number of the ships, and a k is the time when the ship k is expected to berth; (13) (14) wherein, formulas (13) - (14) represent single berth and single ship constraints, and have mutual exclusivity; a variable of 0-1 indicates whether the ship k occupies the berthing station at the time t of the berthing station b; the variable is 0-1, which indicates whether the berthing station B is occupied at the time T, wherein B is the number of berths, T is the scheduling period, and N is the number of ships.
4. The port comprehensive energy coordination optimization method based on multiple constraints according to claim 1, wherein the constraints constructed by port shore bridge operation scheduling are orderly distributed to ships for loading and unloading tasks according to actual conditions of shore bridge and ship berthing operations, and specific constraint conditions comprise: (15) wherein equation (15) represents a product linearization constraint; The number of loading and unloading subsystems allocated to the ship k at the moment t of the berthing station b; the number of loading and unloading subsystems is used for the ship k at the time t, wherein M is the total number of electric collecting cards; a variable of 0-1 is used for indicating whether a ship k occupies a berthing station at a moment T of the berthing station B, wherein N is the number of ships, B is the number of berths, and T is a scheduling period; (16) wherein equation (16) represents the vessel crane allocation consistency constraint; The number of loading and unloading subsystems allocated to the ship k at the moment t of the berthing station b; The number of loading and unloading subsystems is used for the ship k at the time T, wherein N is the number of ships, T is the scheduling period, and B is the number of berths; (17) wherein, the formula (17) represents that the crane is forbidden to be allocated when the ship is not berthed; using the number of handling subsystems for vessel k at time t; an upper limit for the number of the total assembly and disassembly subsystems; A variable of 0-1, which indicates whether the ship k is berthed, N is the number of the ships, and T is a scheduling period; (18) wherein, the formula (18) represents the closed loop constraint of the number of cranes; the number of loading and unloading subsystems used at time t for the berthing station b; The number of loading and unloading subsystems allocated to the ship k at the moment T of the berthing station B is the number of berths, the number T is the scheduling period, and the number N is the number of ships; (19) (20) (21) (22) (23) Equation (19) - (23) represent crane continuous distribution constraint, equation (19) represents crane total capacity constraint, equation (20) represents initial berth crane initialization, i.e. the forefront berth starts from crane number 0, equation (21) represents berth continuity constraint, i.e. the crane start number of berth b+1 is close to the end of berth b, equation (22) represents occupation-only-capable constraint, i.e. berth-only-capable-of-distributing quay crane operation, equation (23) represents continuous block non-boundary crossing constraint, i.e. the quay crane called by berth does not exceed the upper limit number; (24) Wherein equation (24) represents an indication constraint; the number of the berth is 0-1, which indicates whether the berthing station B is occupied at the time T, h b,t is the number of the initial quay at the time T of the berthing station B, B is the number of berths, and T is the scheduling period.
5. The port comprehensive energy coordination optimization method based on multiple constraints according to claim 1, wherein constraints constructed by utilizing electric collector card operation logic reasonably distribute requirements of electric collector cards for carrying out container transportation to a yard according to ship loading and unloading tasks and quay bridge operation conditions, and specific constraint conditions comprise: (25) wherein, the formula (25) represents the constraint of the working state of the electric collector card; A variable of 0-1 indicates whether the electric collector card m is in an operating state at a time t; The variable is 0-1, which indicates whether the electric set card M is in a charging state at the time T; (26) wherein, formula (26) represents an electric power collector card state of charge constraint; the residual electric quantity of the electric collector card m at the time t is represented; A variable of 0-1, which indicates whether the electric collector card m is in a charging state at a time t; A variable of 0-1 indicates whether the electric collector card m is in an operating state at a time t; Representing the power consumption efficiency of operation per unit time; Representing the charging power per unit time; Representing the total capacity of the battery; T is a scheduling period, M is the total number of electric collection cards; (27) (28) (29) (30) (31) (32) wherein formulas (27) - (32) represent electric header card operational logic constraints; the residual electric quantity of the electric collector card m at the time t is represented; Is a charge threshold; Is a discharge threshold; a variable 0-1, indicating whether or not it should be charged; A variable of 0-1, indicating whether or not discharge should be performed; A variable of 0-1 indicates whether the electric collector card m is in an operating state at a time t; A variable of 0-1, which indicates whether the electric collector card m is in a charging state at a time t according to And Value setting of (2) And ; Is the total capacity of the battery; (33) wherein, the formula (33) represents the matching constraint of the loading and unloading speed of the shore bridge and the transferring speed of the electric collector card; Y k,c,t is a variable of 0-1, which indicates whether the ship k uses a crane c at time t; The transport rate for each electric header; The variable is 0-1, which indicates whether the electric collecting card M is in an operating state at the moment T, wherein T is a scheduling period, N is the number of ships, C is the number of the total assembly and disassembly subsystems, and M is the total number of the electric collecting cards; (34) wherein, formula (34) represents adding a quay bridge total loading and unloading power constraint; the total electric power consumption of the shore bridge system at the moment t; The unit power consumption of each loading and unloading subsystem is represented by Y k,c,t which is a variable of 0-1 and indicates whether a crane C is used by a ship k at the time T, wherein T is a scheduling period, C is the number of the total loading and unloading subsystems, and N is the number of the ships; (35) wherein, formula (35) represents adding an electric header card total charge power constraint; The total charging power of all the electric collector cards at the time t is calculated; A variable of 0-1, which indicates whether the electric collector card m is in a charging state at a time t; the power supply system is characterized in that the power supply system is charged in unit time, T is a scheduling period, and M is the total number of electric cards.
6. The port comprehensive energy coordination optimization method based on multiple constraints according to claim 1, wherein constraints constructed by ship electricity, cold and heat loads are utilized to ensure the balance requirements of the electricity and the cold and heat loads of each ship at each moment, and specific constraint conditions comprise: (36) Wherein equation (36) represents the ship electrical load demand; the total electrical load requirement for all ships; Whether or not to park for wheel c at time t; Is a postal wheel An electrical load demand; Is a refrigerating ship An electrical load demand; Is a refrigerating ship Whether the system is parked at the moment T or not, wherein C is the number of the total loading and unloading subsystems, and T is a scheduling period; (37) Wherein equation (37) represents the ship thermal load demand; Is a postal wheel Is not required for the heat load; total heat load demand for all vessels; indicating whether the mail wheel C is parked at the moment t, wherein C is the number of the total loading and unloading subsystems; (38) wherein equation (38) represents a cold load demand constraint; Is a refrigerating ship Is not required for the cooling load; The total cooling load requirement of all ships; Indicating a refrigerated vessel Whether or not the system is parked at the moment t, and C is the total number of the loading and unloading subsystems.
7. The port comprehensive energy coordination optimization method based on multiple constraints according to claim 1, wherein the constraint constructed by ship units is utilized to ensure the required output of each unit, and specific constraint conditions comprise: (39) (40) (41) wherein equations (39) - (41) represent PGU constraints, i.e., genset constraints; Fuel consumption for PGU; An electrical force for the PGU; Is that Electrical efficiency; The waste heat is recovered; Is that Thermal efficiency; Is that Maximum force; a variable of 0-1, indicating whether the PGU is outputting; (42) Wherein, formula (42) represents a main network purchase power constraint; The upper limit of the electricity purchasing quantity of the power grid; representing the main network purchase power at the time t; (43) (44) Wherein formulas (43) - (44) represent EB constraints, i.e., energy storage device constraints; Is that Outputting heat; Is that Output power; Is that Heating efficiency; Representing the upper limit of the maximum power of the EB output; is a 0-1 variable, which indicates whether the EB unit works; (45) (46) wherein formulas (45) - (46) represent AC constraints, i.e., absorption chiller constraints; Is that Outputting refrigeration power; Is that Consuming thermal power; representing the AC unit coefficients; Is that An upper limit of the force; a variable of 0-1, indicating whether the AC is outputting; (47) (48) wherein formulas (47) - (48) represent EC constraints, i.e., electric refrigerator constraints; Is that Outputting cold power; Is that Consuming electric power; Representation of A unit coefficient; An upper EC output limit; a variable of 0-1, indicating whether the EC is outputting; (49) Wherein equation (49) represents the HX constraint, i.e., the heat exchanger constraint; 0-1 variable, representing Whether to exert force; Representation of The upper limit of the output of the unit; (50) Wherein, equation (50) represents TES charging and discharging state constraints; Is that Injecting thermal power; Is that Releasing thermal power; (51) (52) Wherein formulas (51) - (52) represent TES device power constraints, Q TES,in,t is TES injection thermal power, Q TES,dr,t is TES release thermal power; Injecting a maximum limit value of thermal power for TES; Is that Releasing a thermal power maximum limit; Is that Releasing the thermal power efficiency coefficient; Is that Injecting thermal power; Is that Releasing thermal power; (53) (54) wherein formulas (53) - (54) represent TES device capacity constraints; Is that Is used for storing heat; Is the minimum limit value of the heat storage quantity; Is that Maximum limit of heat storage capacity; Releasing a thermal power efficiency coefficient for the TES; injecting a thermal power efficiency coefficient for the TES; Representation of Injecting thermal power; Representation of Releasing thermal power; (55) (56) (57) (58) (59) Wherein formulas (55) - (59) represent EES constraints, i.e., electrical storage device constraints; Is that A discharge state; Is that A state of charge; Is that Discharge power; Is that Maximum discharge power limit; Discharge efficiency for EES; Is that Charging efficiency; Is that An electric quantity; The maximum limit value of the EES electric quantity is set; Is that Minimum limit of electric quantity; (60) Wherein equation (60) represents protecting EES device constraints; Is that Charging efficiency; Is that Discharge efficiency; Is that Discharge power; Is that The T is a scheduling period; (61) (62) Wherein formulas (61) - (62) represent wind-solar power output constraints; Is that Generating power; Indicating an upper limit of light output; Is that Generating power; indicating an upper wind output limit.
8. The port comprehensive energy coordination optimization method based on multiple constraints according to claim 1, wherein constraints constructed by using load demand balance ensure load demand balance of each ship at each moment, and specific constraint conditions comprise: (63) Wherein equation (63) represents an electric power balance; An electrical force for the PGU; Representing the purchase of electricity from a main network; Is that Generating power; Is that Generating power; Representation of Discharge power; Representation of The unit consumes electric power; Representation of Output power; Representation of Charging power; representing the total electrical load demand of all ships; Representing the total power consumed by the quay bridge; representing the total charging power of the electric collecting card; (64) wherein equation (64) represents the thermal power balance; The waste heat is recovered; The thermal power released by the TES unit is represented; 0-1 variable, representing Whether to exert force; Is that Consuming thermal power; representing the thermal power absorbed by the TES unit; (65) wherein equation (65) represents a thermal load supply and demand balance constraint; 0-1 variable, representing Whether to exert force; Is that Outputting heat; The total cooling load requirement of all ships; (66) wherein equation (66) represents a cold load supply and demand balance constraint; consuming thermal power for the AC; Thermal power is consumed for EC; total cooling load demand for all vessels.
9. A port comprehensive energy coordination optimization system based on multiple constraints, comprising: The first module is used for acquiring ship arrival data and establishing a port comprehensive energy coordination optimization model based on the ship arrival data; the port comprehensive energy coordination optimization model comprises a port comprehensive energy coordination optimization model, a loading and unloading subsystem and an electric integrated card operation logic, wherein the port comprehensive energy coordination optimization model comprises carbon emission generated by fuel consumption, carbon emission generated by electricity purchased from a main network, total fuel consumption cost in the whole dispatching period, cost generated by electricity purchased from the main network, starting and stopping cost of an energy power supply unit and punishment cost of unloaded goods after the dispatching period is finished; the second module is used for calling Gurobi a solver to solve the objective function to obtain a port comprehensive energy coordination optimization strategy for the port comprehensive energy coordination optimization model constructed in the step 1, and the constraint conditions participate in solving; and the third module is used for executing port comprehensive energy coordination according to the port comprehensive energy coordination optimization strategy.

Description

Port comprehensive energy coordination optimization method and system based on multiple constraints Technical Field The invention relates to the technical field of port management and coordination optimization, in particular to a port comprehensive energy coordination optimization method and system based on multiple constraints. Background Ports are important hubs for global trade and logistics, and energy coordination and optimization systems face great challenges. With the increase of global trade volume, port energy demands continue to increase, and particularly in the links of ship coordination optimization, cargo transferring operation, loading and unloading subsystem operation, electric integrated card transportation and the like, the problems of energy consumption and carbon energy consumption are increasingly displayed. Port energy coordination optimization involves coordination of multiple forms of energy, including renewable energy such as electricity, fuel, wind energy, and photovoltaic. However, the conventional port coordination optimization methods mostly adopt traditional hard time constraint and rules, and the conventional port coordination optimization methods fail to fully consider unpredictable factors in ship coordination optimization, such as the influence of cargo transportation or emergency when ships are not completed on time, which results in inflexible resource coordination optimization, energy waste and increased carbon energy consumption cost. Therefore, a port comprehensive energy coordination optimization method and system based on multiple constraints are needed to solve the defects in the prior art. Disclosure of Invention The invention aims to provide a port comprehensive energy coordination optimization method and system based on multiple constraints, which are used for solving the technical problems in the background technology. In order to achieve the above object, the first aspect of the present invention provides a port comprehensive energy coordination optimization method based on multiple constraints, which includes the following steps: The method comprises the steps of 1, obtaining ship arrival data, and establishing a port comprehensive energy coordination optimization model based on the ship arrival data, wherein an objective function of the port comprehensive energy coordination optimization model comprises carbon emission generated by fuel consumption, carbon emission generated by main network electricity purchasing quantity, total fuel cost, main network electricity purchasing cost, energy power supply unit start-stop cost and punishment cost of unloaded goods after a dispatching cycle is finished; Step 2, calling Gurobi a solver to solve the objective function to obtain a port comprehensive energy coordination optimization strategy for the port comprehensive energy coordination optimization model constructed in the step 1, wherein constraint conditions participate in solving; And 3, executing port comprehensive energy coordination according to the port comprehensive energy coordination optimization strategy. Further, the calculation formula of the objective function of the port comprehensive energy coordination optimization model is as follows: (1) Wherein, the D is the fuel emission coefficient; fuel consumed for the PGU; e is the cost coefficient of the power carbon energy consumption; to consume fuel costs; The electricity purchasing cost is the main network; The start-stop cost of the energy supply unit is set; The method comprises the steps of determining a punishment cost coefficient for the unloaded goods after the dispatching cycle is finished, wherein T represents the moment, and T represents the dispatching cycle. Further, constraints constructed by ship berthing scheduling are utilized to ensure that each ship can berth orderly, berthing tasks are completed, and specific constraint conditions comprise: (2) Wherein, the formula (2) represents the consistency relation constraint between the ship berthing state and berthing allocation decision, s.t. A variable 0-1, indicating whether or not the vessel k is moored; A variable of 0-1 is used for indicating whether the ship k occupies the berthing station at the moment T of the berthing station B; (3) wherein equation (3) represents a berth service constraint; The variable is 0-1, which indicates whether the ship k occupies the berthing station at the time T of the berthing station B, wherein N is the number of ships, B is the number of berths, and T indicates a scheduling period; (4) Wherein equation (4) represents allocation constraints on the berths in the scheduling period; The variable is 0-1, which indicates whether the ship k starts berthing at the moment T of the berthing station B, N is the number of ships, B is the number of berths, T indicates a scheduling period; (5) wherein equation (5) represents a continuity constraint of the berthing state; a variable of 0-1 indicates whether the s