CN114912696A - All-electric ship cluster path optimization method considering power conversion and shore power access - Google Patents
All-electric ship cluster path optimization method considering power conversion and shore power access Download PDFInfo
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Abstract
The invention provides a method for optimizing a cluster path of a full-electric ship considering power conversion and shore power access, which comprises the following steps of: step S1: collecting port and all-electric ship cluster information; step S2: establishing a path optimization model according to the path planning constraint of traffic transportation and the energy management constraint of the full electric ship cluster based on the collected port and full electric ship cluster information; step S3: and obtaining an optimal scheduling decision by the path optimization model, and issuing a scheduling instruction to the full-electric ship cluster.
Description
Technical Field
The invention relates to the technical field of path optimization and ships, in particular to a method for optimizing a cluster path of an all-electric ship considering power conversion and shore power access, and more particularly relates to novel path optimization modeling and a method for scheduling power conversion and shore power access of the all-electric ship.
Background
With the strictness of emission reduction policies of various countries, transformation pressure faced by the global shipping industry is increasing. The full-electric ship is a key means for realizing green transformation of the shipping industry, and the full-electric ship integrating the comprehensive electric propulsion technology and the container energy storage battery technology can effectively improve the energy utilization efficiency and realize zero-carbon navigation. With the large-scale application of all-electric ships, it is a development trend to undertake cargo transportation tasks by using all-electric ship clusters, and how to reduce cluster transportation cost by using a path optimization method in navigation scheduling of all-electric ship clusters and improve cluster transportation efficiency becomes an urgent problem to be solved.
At present, in the field of ship cluster path optimization, related research at home and abroad mainly takes a traditional fuel ship as a research object, the modeling idea of the traditional fuel ship is derived from the classical vehicle path optimization problem, the optimization of a course and speed is performed by focusing on cargo supply and demand balance so as to reduce oil consumption, the cruising ability of a full-electric ship taking an energy storage battery as main power is not considered, and the energy exchange between the ship and a port is not involved. Although a path optimization model of the power conversion ship is provided in part of research, the energy supply and the optimized operation of a port power grid are realized by the aid of the transportation energy storage battery, and energy management of the ship is omitted.
In order to improve the cluster transportation efficiency of the full-electric ship and reduce the running cost of the ship, the invention fully utilizes a cluster path optimization method and an energy optimization management strategy to realize the fusion planning of traffic and energy, comprehensively considers the influence of power change scheduling and shore power access decision on the cluster path optimization, and optimizes the cluster route selection and the ship propulsion speed to achieve a better energy management level by taking economy as a target on the premise of ensuring the transportation requirement.
Xushi hong, Zhang hong Zhi, Linxiangning, etc. based on the ocean island discrete energy optimization scheduling strategy research [ J ] of the power change ship, China Motor engineering reports 2020,40(S1): 108-.
Verma, A.electric vehicle routing protocol with time windows, recharging stations and battery switching stations, EURO J Transp Logist 7,415 and 451(2018), aiming at the electric vehicle cluster, a path optimization modeling method considering the charging and switching behaviors is researched, and a heuristic algorithm is applied to realize efficient solution. However, the proposed optimization model does not take into account the differences between the vehicles and different charging and replacing power stations, the energy consumption model of the vehicles also adopts simplified processing, and the energy management of the all-electric ship is more complicated, so the optimization method proposed by the document is not suitable for the path optimization of the all-electric ship cluster.
Mingchang Gu, Shuli Wen, Miao Zhu, et al, Voyage optimization for All-Electric vehicles Integrated with Swappable connected Battery [ C ].202111th International Conference on Power and Energy Systems (ICPES),2021, pp.586-591, which proposes a flight optimization method that takes into account the trade decision for All-Electric ships powered by container Energy storage batteries, but the optimization model proposed in this document is only applicable to the dispatch of a single ship and the flight is fixed. Compared with the literature, the economical dispatching method provided by the invention also considers a shore power access decision, improves the economy and the environmental friendliness of the ship, and simultaneously can diversify the electric energy supplement modes of the ship and realize the optimal dispatching of the ship cluster.
Patent document CN108062614B (application number: 201711040554.4) discloses a method for scheduling charging and battery replacement of an electric tractor for a port, and belongs to the technical field of operation and control of an electric power system. When an operation task starts, the initial charge state of the battery of the electric tractor is analyzed, and the electric quantity of the battery of the vehicle is ensured to be larger than the minimum specified charge quantity meeting the driving requirement; in the process of an operation task, when the state of charge of the batteries of the existing electric tractors is smaller than the minimum specified charge quantity meeting the driving requirement, the batteries are replaced preferentially for the corresponding batteries, and when the electric quantity of a batch of electric tractors is in the same interval range, a battery replacement plan is made in advance.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a full-electric ship cluster path optimization method considering power conversion and shore power access.
The invention provides an all-electric ship cluster path optimization method considering power conversion and shore power access, which comprises the following steps:
step S1: collecting port and all-electric ship cluster information;
step S2: establishing a path optimization model according to the path planning constraint of traffic transportation and the energy management constraint of the full electric ship cluster based on the collected port and full electric ship cluster information;
step S3: and obtaining an optimal scheduling decision by the path optimization model, and issuing a scheduling instruction to the full-electric ship cluster.
Preferably, the port and all-electric ship cluster information includes: the cargo demand of each port, the cargo demand time window, the maximum cargo capacity of each all-electric ship and the capacity and initial electric quantity of the container energy storage battery, whether the port provides power conversion and shore power access service and corresponding quotations, the upper and lower limits of the shore power access power of the port, the lowest electric quantity allowed by the energy storage battery during sailing and the calculation coefficient of the ship electric propulsion load.
Preferably, the path optimization model employs:
the objective function adopts:
wherein, TC swap 、TC shore 、TC ess_ini 、TC fix Respectively representing the total cluster operation cost, the electricity replacement cost, the shore power cost, the charging cost of charging the energy storage battery to the initial electric quantity after returning to the base and the fixed cost of moving the ship out; a { (i, j) | i, j ∈ V, i ≠ j } represents a directed navigation segment set; v ═ {0,1,2, …, n +1} represents the set of all nodes, i, j each represent a node index; node numbers 0 to n +1 all represent bases; k represents a ship set; lambda [ alpha ] j Indicating the electricity change price, tau j Representing shore power electricity prices; lambda [ alpha ] ini Represents the electricity price of the electricity energy compensated at the base,
which represents the initial amount of power of the vessel,
represents a fixed cost of the ship k going out,
represents a variable of 0 to 1, and when 1 is taken, the ship k does not move, i is equal to delta - (n +1) represents a set of nodes that can go up to the n +1 node,
representing the energy storage battery capacity when the ship k returns to the base from the node i;
represents the electric energy supplemented at the power conversion station after the ship k sails to a port j along the navigation section (i, j),
the method represents the supplemented electric energy accessed by shore power after sailing to a port j, and the calculation formula is as follows:
wherein, the first and the second end of the pipe are connected with each other,
representing the energy storage battery capacity when the ship k sails along the navigation section (i, j) to reach j,
indicating the amount of power at the time of departure from j,
indicating a change in the amount of power at the stop j,
indicates the power of the shore power after j is reached, h j Indicating the parking time;
the constraint conditions include: airline in-out degree balance constraint; a lane connectivity constraint; carrying out transportation, battery replacement, shore power access decision and path planning coupling constraint; a ship and port interaction mechanism; a time window constraint; the method comprises the following steps of cargo capacity constraint, ship speed constraint, container energy storage battery electric quantity change, container energy storage battery electric quantity upper and lower limit constraint, power balance constraint and shore power upper and lower limit constraint.
Preferably, the lane entrance and exit balance constraint employs:
wherein the content of the first and second substances,
is a variable from 0 to 1 and represents the course decision of the kth ship, i, j and l all represent node labels, j is equal to delta + (0) And l ∈ Δ + (j) Respectively representing the node sets to which the node 0 and the node j can reach, i ∈ Delta - (n +1) and i ∈ Δ - (j) Respectively representing a node set which can reach to a node N +1 and a node j, wherein N is {1,2, …, N } represents a port node set;
preferably, the route connectivity constraint employs:
wherein the content of the first and second substances,
all are binary decision variables for representing the order of k routes of the ship
1 is taken to represent that a ship k sails from i to j in sequence in the cluster route planning and thenIn the case of the reaction of (a) to (l),
the variable is 0-1, and represents the course decision of the ship k;
preferably, the transportation, power conversion, shore power access decision and path planning coupling constraint adopts:
wherein, the first and the second end of the pipe are connected with each other,
and
all variables are 0-1 variables and respectively represent decision variables for judging whether to carry out power conversion, shore power access and cargo unloading after the kth ship sails from i to j;
preferably, the ship and port interaction mechanism adopts:
wherein the content of the first and second substances,
the state marks of 0-1 respectively indicate whether the port node j has a cargo demand or not, and whether a power exchange station and a shore power facility are configured or not;
preferably, the time window constraint employs:
wherein A { (i, j, l) | (i, j) ∈ A and (j, l) ∈ A },
and
a decision variable of the arrival time of the ship;
and
a decision variable of the voyage time of the ship k on the flight; a is j 、b j Respectively representing the earliest and latest arrival time allowed by a time window of port cargo demand, wherein M is a positive number meeting a preset requirement, E and L are scheduling starting time and ending time respectively, and a ship must return to a base before the scheduling ending time;
preferably, the cargo capacity constraint employs:
wherein d is j Indicating the cargo demand, Q, for Port j k Represents the upper cargo capacity limit of vessel k;
preferably, the boat speed constraint employs:
in order to optimize the ship speed of each section of ship, the invention adopts a method of adjusting the ship speed in stages;
wherein the content of the first and second substances,
is a variable from 0 to 1, and takes 1 to represent the ship speed on the flight segment (i, j) as the ship speed of the grade r, and the ship speed decision variable
Size v r ，
Decision variable, s, representing the time of flight of a ship k along (i, j) ij Indicating the flight distance of the flight segment (i, j).
Preferably, the container energy storage battery power variation adopts:
wherein the content of the first and second substances,
and
all the decision variables represent the electric quantity of the energy storage battery;
and
all the decision variables represent the electric quantity change of the ship k in the sailing process;
representing the amount of electricity at j, the calculation formula is as follows:
wherein the content of the first and second substances,
rated capacity of a k energy storage battery for the ship;
representing a decision variable of the electric quantity change of the energy storage battery when j is stopped;
wherein the content of the first and second substances,
discharging power of an energy storage battery when a ship k stops at j after sailing along the navigation section (i, j);
representing the service load of vessel k, c 1 Calculating coefficients for the ship electric propulsion load;
the formula (11) contains product terms of binary variables and continuous variables, and linear processing is carried out by introducing a positive number M:
equation (11) is equivalently replaced by equation (13);
preferably, the upper and lower limits of the electric quantity of the energy storage battery of the container are restricted
Wherein, the first and the second end of the pipe are connected with each other,
ensuring the safe sailing of the ship for the lowest allowable electric quantity of the energy storage battery of the ship k in the sailing process;
preferably, the power balance constraint employs:
wherein the content of the first and second substances,
for the discharge power of the energy storage battery when the ship k sails along the navigation section (i, j),
the power of the electric propeller is shown when the ship sails along the section (i, j), and the optimal management of the propulsion load can be realized through the ship speed adjustment;
preferably, the shore power upper and lower limits are constrained to adopt:
wherein, P shore_max 、P shore_min Representing the maximum and minimum power allowed for shore power access.
The system for optimizing the cluster path of the all-electric ship considering the electricity switching and shore power access can be realized by the steps and flows in the method for optimizing the cluster path of the all-electric ship considering the electricity switching and shore power access. The person skilled in the art can understand the method for optimizing the all-electric ship cluster path considering power conversion and shore power access as a preferred example of an all-electric ship cluster path optimizing system considering power conversion and shore power access.
Compared with the prior art, the invention has the following beneficial effects:
1. the full-electric ship adopts the container energy storage battery as a power source, and the energy supplement of the ship adopts a method of combining a battery replacement mode and a shore power access mode, so that zero carbon emission of the ship is realized, and the clean and efficient operation of a traffic energy network is facilitated;
2. the invention not only considers the ship cargo capacity limit and the time window limit of the port on the transportation level, but also considers the configuration conditions of the port electricity exchanging station and the shore power facility, can carry out the optimal decision on the airway, the electricity exchanging and the shore power access, and has a certain universality because the scheduling scheme is fit with the reality;
3. the invention realizes the fusion planning of the cluster traffic and the energy of the full electric ship by finely depicting the electrical constraint conditions between the port and the ship and comprehensively considering the energy and service transaction mechanism;
4. aiming at the solution of the path optimization model, the mixed integer nonlinear programming model is converted into the mixed integer linear programming model by adopting a linearization technology, so that the difficulty of the model solution is reduced;
5. the method carries out combined optimization on the energy management and the path scheduling of the full-electric ship cluster, and the energy management and the path decision are closely coupled.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
fig. 1 is a schematic diagram of a cluster scheduling architecture of an all-electric ship.
Fig. 2 is an economic dispatch flow chart of a full electric ship cluster.
Fig. 3 is a schematic view of a channel and a port.
Fig. 4 is a schematic diagram of the variation of the electric quantity of the energy storage battery of the full-range ship.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that it would be obvious to those skilled in the art that various changes and modifications can be made without departing from the spirit of the invention. All falling within the scope of the present invention.
Example 1
The method aims at the problem of path planning of the full-power ship cluster research, and accords with the development trend of the ship industry. Meanwhile, the full-electric ship in the invention takes the container energy storage battery as a power source, belongs to a new energy ship, and can realize zero-carbon navigation by supplementing electric energy in the modes of electricity conversion and shore power access. The invention develops path optimization research for the full electric ship cluster operating in the electricity conversion and shore power access modes for the first time, emphasizes the differentiation characteristics of different ports and ships, delicately describes the operation mechanism of the full electric ship cluster scheduling, and realizes the fusion planning of traffic and energy.
The port and full electric ship cluster interaction mechanism comprises traffic transportation service, battery replacement service and shore power access service;
the transportation service comprises: the distribution base is provided with a plurality of full electric ships and is responsible for cargo distribution of a plurality of ports, each port provides cargo demand and a corresponding demand time window to the dispatching platform before dispatching planning, the full electric ships are required to deliver the cargo within the time window, and in order to improve the transportation efficiency, the cargo demand of each port can be provided with service only by one full electric ship. The cargo capacity of each full electric ship cannot exceed the maximum cargo capacity limit, and all the distribution tasks can be completed after starting from the base and can not be returned in the midway.
The power conversion and shore power access service comprises: in the invention, the full-electric ship considers that the container energy storage battery provides power, and in order to improve the endurance capacity of the full-electric ship, the mode of combining electricity conversion and shore power access is adopted for electric energy supply. Compared with a shore power access mode, the electric energy supply speed of the full-electric ship in the power conversion mode is higher, but the price is also higher. The shore power access mode may not be able to raise the energy storage battery level to a safe level for cruising within a limited time due to the limitations of charging power and parking time, but is also relatively inexpensive. The unified dispatching platform can select a proper electric energy supply mode according to the capacity of the ship energy storage battery and the electric quantity change condition, and the economic benefit is improved as far as possible on the premise of ensuring the transportation efficiency.
The construction of the power conversion station and the shore power facilities is a trend of the development of future ports, however, at present, not all ports provide power conversion and shore power access services, and therefore, a 0-1 state flag is adopted for each port to represent whether the port provides the power conversion and shore power access services or not. For ports providing power conversion or shore power access services, multiple vessels are allowed to dock multiple times. It is worth noting that in the traditional vehicle path optimization problem, most of the client points are allowed to be accessed only once, and the charging and swapping station and the client points are independent nodes, but the port has the dual attributes of the client points and the charging and swapping station nodes, so that the method for optimizing the full-electric ship cluster path considering swapping and shore power access is more complex in model and more suitable for actual ship scheduling.
According to the full-electric ship cluster path optimization method considering power conversion and shore power access, as shown in fig. 1, the method includes:
step S1: collecting port and all-electric ship cluster information;
specifically, the port and all-electric ship cluster information includes: the cargo demand and the corresponding demand time window of each port, the maximum cargo capacity and the capacity of the container energy storage battery of each all-electric ship, whether the port provides power conversion and shore power access service and corresponding quotations, the port shore power access upper and lower limits, the lowest allowable electric quantity of the energy storage battery during sailing and the ship electric propulsion load calculation coefficient.
Step S2: establishing a path optimization model according to the path planning constraint of traffic transportation and the energy management constraint of the all-electric ship cluster based on the collected port and all-electric ship cluster information;
due to the fact that the capacity of the energy storage battery of the container is limited, the problems of safe endurance and electric energy supplement need to be further considered during path planning, battery replacement and shore power access decisions are directly related to path selection and are tightly coupled with ship energy management, the path selection and the energy management are mutually linked and cannot be divided, integral analysis is needed, and accordingly collaborative optimization is achieved.
Compared with the traditional path optimization model, the path optimization model further considers the differentiation characteristics of the full-electric ship and the port in the aspects of cargo capacity, propulsion coefficient, container energy storage battery capacity, power conversion station and shore power access facility configuration, power conversion and shore power quotation and the like, and carries out multi-dimensional portrayal on the port and the ship, can carry out optimal dispatching on the cluster, and is more practical.
Specifically, in the traditional vehicle path optimization problem, most of the customer points are allowed to be visited once, and the charging and swapping station and the customer points are independent nodes, but the port has the dual attributes of the customer points and the charging and swapping station nodes, so that the full-electric ship cluster is required to meet the transportation service of the full-electric ship cluster, and meanwhile, the electric energy supplement service is provided for the full-electric ship cluster.
Meanwhile, the ship cluster considers ship speed optimization, arrival time and energy consumption are related to path selection and are influenced by the ship speed, and the ship cluster has stronger uncertainty and higher complexity. The invention adopts a method of adjusting the speed of the ship in stages, can realize the optimized management of the propulsion load and increase the flexibility of the ship scheduling.
More specifically, the path optimization model employs:
the purpose of centralized and unified dispatching of the ship cluster is to meet the port cargo transportation requirement and reduce the running cost of the ship as much as possible by reasonably dispatching the ship. Therefore, the lowest total cluster operation cost is set as an objective function, and the method is specifically represented as follows:
wherein, TC swap 、TC shore 、TC ess_ini 、TC fix Respectively representing the total cluster operation cost, the electricity replacement cost, the shore power cost, the charging cost of charging the energy storage battery to the initial electric quantity after returning to the base and the fixed cost of moving the ship out; a { (i, j) | i, j ∈ V, i ≠ j } represents a directed navigation segment set; v ═ {0,1,2, …, n +1} represents the set of all nodes, i, j each represent a node index; node numbers 0 to n +1 all represent bases; k represents a ship set; lambda [ alpha ] j Indicating the electricity change price, tau j Representing shore power electricity prices; lambda [ alpha ] ini Indicating the electricity price of the charging energy at the base,
which represents the initial amount of power of the vessel,
represents a fixed cost of the ship k going out,
represents a variable of 0 to 1, and when 1 is taken, the ship k does not move, i is equal to delta - (n +1) represents a set of nodes that can go up to the n +1 node,
representing the energy storage battery capacity when the ship k returns to the base from the node i;
represents the electric energy supplemented at the power conversion station after the ship k sails to a port j along the navigation section (i, j),
the method represents the electric energy supplemented by shore power access after sailing to port j, and the calculation formula is as follows:
wherein the content of the first and second substances,
representing the energy storage battery capacity when the ship k sails along the navigation section (i, j) to reach j,
indicating the amount of power at the time of departure from j,
indicating the change in the amount of power at the time of j,
indicates the power of the shore power after j is reached, h j Indicating the length of the parking time;
the constraint conditions include: balance constraint of lane entrance and exit; a lane connectivity constraint; carrying out transportation, battery replacement, shore power access decision and path planning coupling constraint; a ship and port interaction mechanism; a time window constraint; the method comprises the following steps of cargo capacity constraint, ship speed constraint, container energy storage battery electric quantity change, container energy storage battery electric quantity upper and lower limit constraint, power balance constraint and shore power upper and lower limit constraint.
Specifically, the lane departure and entrance degree balance constraint adopts:
wherein the content of the first and second substances,
is a variable from 0 to 1 and represents the course decision of the kth ship, i, j and l all represent node labels, j is equal to delta + (0) And l ∈ Δ + (j) Respectively representing the node sets to which the node 0 and the node j can reach, i ∈ Delta - (n +1) and i ∈ Δ - (j) Respectively representing a node set which can reach to a node N +1 and a node j, wherein N is {1,2, …, N } represents a port node set;
the lane connectivity constraint employs:
wherein the content of the first and second substances,
all are binary decision variables for representing the order of k routes of the ship
Taking 1 indicates that the ship k sails from i to j to l in turn in the cluster route plan,
is 0-1 variable representing a course decision of a ship k;
the transportation, power conversion, shore power access decision and path planning coupling constraint adopts:
wherein the content of the first and second substances,
and
all variables are 0-1 variables and respectively represent decision variables for judging whether to carry out power conversion, shore power access and cargo unloading after the kth ship sails from i to j;
the ship and port interaction mechanism adopts:
wherein the content of the first and second substances,
the state marks of 0-1 respectively indicate whether the port node j has a cargo demand or not, and whether a power exchange station and a shore power facility are configured or not;
the time window constraint employs:
wherein A { (i, j, l) | (i, j) ∈ A and (j, l) ∈ A },
and
for decision variables of arrival time of ships, e.g.
Representing the time when the ship k sails along the flight segment (i, j) to reach the port j;
and
decision variables for the time of flight of a vessel k, e.g.
Represents the time of flight along (j, l); a is j 、b j The earliest and latest arrival times allowed by the time window representing port cargo demand, respectively, M being a very large positive number, E and L being the dispatch start time and the dispatch end time, respectively, before which the ship must return to base;
the cargo capacity constraint employs:
wherein, d j Indicating the cargo demand, Q, for Port j k Represents the upper cargo capacity limit of vessel k;
the speed constraint of the ship adopts:
in order to optimize the ship speed of each section of ship, the invention adopts a method of adjusting the ship speed in stages;
wherein the content of the first and second substances,
taking 1 as 0-1 variable to represent the ship speed on the flight segment (i, j) set as the ship speed of the grade r, namely the ship speed decision variable
Size v r ，
Decision variable, s, representing the time of flight of a ship k along (i, j) ij Indicating the flight distance of the flight segment (i, j).
The container energy storage battery electric quantity changes and adopts:
wherein, the first and the second end of the pipe are connected with each other,
and
are all decision variables that characterize the charge of the energy storage cell, e.g.
Representing the electric quantity of an energy storage battery when a ship k sails along a navigation section (j, l) to reach l;
and
are decision variables which characterize the variation of the electrical quantity of the ship k during the course of the voyage, e.g.
Representing the variation of the electrical quantity while navigating along the segment (j, l);
representing the amount of electricity at j, the calculation formula is as follows:
wherein the content of the first and second substances,
rated capacity of the energy storage battery for the ship k;
representing a decision variable of the electric quantity change of the energy storage battery when j is stopped;
wherein the content of the first and second substances,
discharging power of an energy storage battery when a ship k stops at j after sailing along a navigation section (i, j);
representing the service load of vessel k, c 1 Calculating coefficients for the ship electric propulsion load;
the formula (11) contains product terms of binary variables and continuous variables, nonlinear constraint brings difficulty to model solution, and linear processing is carried out by introducing large M:
equation (11) is equivalently replaced by equation (13);
constraint of upper and lower limits of electric quantity of energy storage battery of container
Wherein the content of the first and second substances,
ensuring the safe sailing of the ship for the lowest allowable electric quantity of the energy storage battery of the ship k in the sailing process;
the power balance constraint employs:
wherein the content of the first and second substances,
for the discharge power of the energy storage battery when the ship k sails along the navigation section (i, j),
the power of the electric propeller is shown when the ship sails along the section (i, j), and the optimal management of the propulsion load can be realized through the ship speed adjustment;
the shore power upper and lower limits are constrained to adopt:
wherein, P shore_max 、P shore_min Representing the maximum and minimum power allowed for shore power access.
Step S3: and obtaining an optimal scheduling decision by the path optimization model and issuing a scheduling instruction.
In the invention, decision variables relate to a large number of binary variables, nonlinear constraints in the model are converted into linear constraints by introducing a linearization method, and a problem model is converted into a mixed integer linear programming problem. And solving the model by calling a solver, thereby solving the economic dispatching problem of the full-electric ship cluster. Firstly, a dispatching platform collects cargo demand and a time window of a port to determine demand information and issues the demand information to a ship operator, and the ship operator uploads ship basic parameters such as energy storage battery electric quantity, cargo capacity, service load size, propulsion load calculation coefficient and the like of a full electric ship cluster capable of providing transportation service; then, the dispatching platform counts electricity price information of port electricity conversion and shore electricity access, and then solves the optimization model by combining port demand information and ship parameters to determine a navigation decision; and finally, the ship operator settles the energy transaction fee with the port according to the electricity change amount and the shore power consumption. The specific flow is shown in fig. 2.
The method not only considers the electricity utilization cost in the navigation process, but also considers the electricity conversion cost and the shore power access cost, and aims at the optimization solution of the economic objective, a linear technology is adopted to convert the mixed integer nonlinear programming model into the mixed integer linear programming model, and a commercial solver can be used for realizing efficient solution.
The system for optimizing the cluster path of the all-electric ship considering the electricity switching and shore power access can be realized by the steps and flows in the method for optimizing the cluster path of the all-electric ship considering the electricity switching and shore power access. The person skilled in the art can understand the method for optimizing the all-electric ship cluster path considering power conversion and shore power access as a preferred example of an all-electric ship cluster path optimizing system considering power conversion and shore power access.
Example 2
Example 2 is a preferred example of example 1
As shown in fig. 3 to 4, the present invention selects a full-electric ship cluster for providing transportation service for 6 ports as a test system. The basic parameters of the ship and the air route and the configuration conditions of the port power conversion and shore power facilities are shown in figure 3. The cluster scheduling is optimized by adopting the optimization model provided by the invention, and the optimization result is shown in table 1.
TABLE 1 Cluster Path optimization results
| Serial number | Route selection | Number of times of battery replacement | Shore power access electric quantity/kWh |
| Ship 1 | Base → phi → |
2 | 1988.58 |
| |
Base → first → |
2 | 1350 |
| Ship 3 | Base → ③ → |
0 | 227.56 |
The economic dispatching method provided by the invention enriches and refines the objective function, the optimization result can not only meet the path constraint, but also reduce the ship operation cost as much as possible on the premise of path feasibility. Table 2 shows a comparison of the optimization results of only considering the shortest total path of the cluster voyage as the target and the optimization results of the present invention with the minimum operation cost as the target, and it can be seen that the optimization model provided by the present invention can further reduce the cluster operation cost through the optimization management of the propulsion load and improve the energy management level even under the same route selection.
TABLE 2 comparison of results for different scheduling methods
| Shortest path scheduling method | The scheduling method of the invention | |
| Cluster Total voyage distance (nm) | 543 | 543 |
| Total operating cost of cluster (m.u.) | 29877.1 | 29306.9 |
| Propelling load power consumption (kWh) | 9535.6 | 9144.1 |
Those skilled in the art will appreciate that, in addition to implementing the systems, apparatus, and various modules thereof provided by the present invention in purely computer readable program code, the same procedures can be implemented entirely by logically programming method steps such that the systems, apparatus, and various modules thereof are provided in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Therefore, the system, the device and the modules thereof provided by the present invention can be considered as a hardware component, and the modules included in the system, the device and the modules thereof for implementing various programs can also be considered as structures in the hardware component; modules for performing various functions may also be considered to be both software programs for performing the methods and structures within hardware components.
The foregoing description of specific embodiments of the present invention has been presented. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes or modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention. The embodiments and features of the embodiments of the present application may be combined with each other arbitrarily without conflict.
Claims (10)
1. A full-electric ship cluster path optimization method considering power conversion and shore power access is characterized by comprising the following steps:
step S1: collecting port and all-electric ship cluster information;
step S2: establishing a path optimization model according to the path planning constraint of traffic transportation and the energy management constraint of the full electric ship cluster based on the collected port and full electric ship cluster information;
step S3: and obtaining an optimal scheduling decision by the path optimization model, and issuing a scheduling instruction to the full-electric ship cluster.
2. The all-electric ship cluster path optimization method taking into account power conversion and shore power access according to claim 1, wherein the port and all-electric ship cluster information includes: the cargo demand of each port, the cargo demand time window, the maximum cargo capacity of each all-electric ship and the capacity and initial electric quantity of the container energy storage battery, whether the port provides power conversion and shore power access services and corresponding quotations, the port shore power access upper and lower limits, the lowest allowable electric quantity of the energy storage battery during sailing and the ship electric propulsion load calculation coefficient.
3. The method for optimizing the path of the all-electric ship cluster considering power conversion and shore power access according to claim 1, wherein the path optimization model adopts:
the objective function adopts:
wherein, TC swap 、TC shore 、TC ess_ini 、TC fix Respectively representing the total cluster operation cost, the electricity replacement cost, the shore power cost, the charging cost of charging the energy storage battery to the initial electric quantity after returning to the base, and the fixed cost of moving out the ship; a { (i, j) | i, j belongs to V, i ≠ j } represents a directed leg set; v ═ {0,1,2, …, n +1} represents the set of all nodes, i, j each represent a node index; node numbers 0 to n +1 all represent bases; k represents a ship set; lambda [ alpha ] j Indicating the electricity change price, tau j Representing shore power electricity prices; lambda [ alpha ] ini Represents the electricity price of the electricity energy compensated at the base,
which represents the initial amount of power of the vessel,
represents a fixed cost of the ship k going out,
represents a variable of 0 to 1, and when 1 is taken, the ship k does not move, i is equal to delta - (n +1) represents a set of nodes that can go up to the n +1 node,
representing the energy storage battery capacity when the ship k returns to the base from the node i;
represents the electric energy supplemented at the power conversion station after the ship k sails to a port j along the navigation section (i, j),
the method represents the electric energy supplemented by shore power access after sailing to port j, and the calculation formula is as follows:
wherein the content of the first and second substances,
representing the energy storage battery capacity when the ship k sails along the navigation section (i, j) to reach j,
indicating the amount of power at the time of departure from j,
indicating a change in the amount of power at the stop j,
indicates the power of the shore power after j is reached, h j Indicating the parking time;
the constraint conditions include: balance constraint of lane entrance and exit; a lane connectivity constraint; carrying out transportation, battery replacement, shore power access decision and path planning coupling constraint; a ship and port interaction mechanism; a time window constraint; the method comprises the following steps of cargo capacity constraint, ship speed constraint, container energy storage battery electric quantity change, container energy storage battery electric quantity upper and lower limit constraint, power balance constraint and shore power upper and lower limit constraint.
4. The method for optimizing the route of a full-electric ship cluster taking power conversion and shore power access into account of claim 3, wherein the lane entrance and exit degree balance constraint is implemented by:
wherein the content of the first and second substances,
is a variable from 0 to 1 and represents the course decision of the kth ship, i, j and l all represent node labels, j is equal to delta + (0) And l ∈ Δ + (j) Respectively, that node 0 and node j may be straightSet of nodes reached, i ∈ Δ - (n +1) and i ∈ Δ - (j) Respectively, a node set up to node N +1 and node j, and N ═ {1,2, …, N } represents a port node set.
5. The all-electric ship cluster path optimization method taking into account power conversion and shore power access according to claim 3, wherein the route connectivity constraint employs:
wherein the content of the first and second substances,
all are binary decision variables for representing the order of k routes of the ship
Taking 1 indicates that a ship k sails from i to j to l in turn in the cluster route planning,
is a variable from 0 to 1 and represents the course decision of the ship k.
6. The all-electric ship cluster path optimization method considering power conversion and shore power access according to claim 3, wherein the transportation, power conversion, shore power access decision and path planning coupling constraints adopt:
wherein the content of the first and second substances,
and
all the variables are 0-1 variables and respectively represent decision variables for judging whether to carry out power conversion, shore power access and cargo unloading after the k-th ship sails from i to j.
7. The method for optimizing the route of a full-electric ship cluster considering power conversion and shore power access according to claim 3, wherein the ship-port interaction mechanism employs:
wherein the content of the first and second substances,
the state flags of 0-1 respectively indicate whether the port node j has cargo requirements or not, and whether a power conversion station and a shore power facility are configured or not.
8. The method for optimizing the route of a full-electric ship cluster considering power conversion and shore power access according to claim 3, wherein the time window constraint is:
wherein A { (i, j, l) | (i, j) ∈ A and (j, l) ∈ A },
and
a decision variable of the arrival time of the ship;
and
a decision variable of the voyage time of the ship k on the flight; a is a j 、b j Respectively representing the earliest and latest arrival time allowed by a time window of port cargo demand, wherein M is a positive number meeting a preset requirement, E and L are scheduling starting time and scheduling ending time respectively, and the ship must return to the base before the scheduling ending time;
the cargo capacity constraint employs:
wherein d is j Indicating the cargo demand, Q, for Port j k Represents the upper cargo capacity limit of vessel k;
the ship speed constraint adopts the following steps:
in order to optimize the ship speed of each section of ship, the invention adopts a method of adjusting the ship speed in stages;
wherein the content of the first and second substances,
is a variable from 0 to 1, and takes 1 to represent the ship speed on the flight segment (i, j) as the ship speed of the grade r, and the ship speed decision variable
Size v r ，
Decision variable, s, representing the time of flight of a ship k along (i, j) ij Indicating the distance traveled by leg (i, j).
9. The method for optimizing the route of the all-electric ship cluster considering power conversion and shore power access according to claim 3, wherein the change of the container energy storage battery power is performed by:
wherein the content of the first and second substances,
and
all are decision variables representing the electric quantity of the energy storage battery;
and
all the decision variables represent the electric quantity change of the ship k in the sailing process;
representing the amount of electricity at j, the calculation formula is as follows:
wherein the content of the first and second substances,
rated capacity of the energy storage battery for the ship k;
representing a decision variable of the electric quantity change of the energy storage battery when j is stopped;
wherein the content of the first and second substances,
discharging power of an energy storage battery when a ship k stops at j after sailing along the navigation section (i, j);
representing the service load of vessel k, c 1 Calculating coefficients for the ship electric propulsion load;
the formula (11) contains product terms of binary variables and continuous variables, and linear processing is carried out by introducing a positive number M:
equation (11) is equivalently replaced by equation (13).
10. The all-electric ship cluster path optimization method considering electricity conversion and shore power access according to claim 3, wherein the upper and lower limits of the container energy storage battery capacity are constrained by:
wherein the content of the first and second substances,
ensuring the safe sailing of the ship for the lowest allowable electric quantity of the energy storage battery of the ship k in the sailing process;
the power balance constraint employs:
wherein the content of the first and second substances,
for the discharge power of the energy storage battery when the ship k sails along the navigation section (i, j),
the power of the electric propeller is shown when the ship sails along the section (i, j), and the optimal management of the propulsion load can be realized through the ship speed adjustment;
the shore power upper and lower limits are constrained to adopt:
wherein, P shore_max 、P shore_min Representing the maximum and minimum power allowed for shore power access.
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