CN115511182A - Energy optimization scheduling method, system, device and medium for shore power micro-grid group system - Google Patents
Energy optimization scheduling method, system, device and medium for shore power micro-grid group system Download PDFInfo
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Abstract
The invention discloses a shore power microgrid group system energy optimization scheduling method, a system, a device and a medium, wherein the method comprises the steps of acquiring operation data of shore power and ships during berthing of the ships; based on the operation data of the shore power and the ship, an optimized scheduling function is constructed by taking the minimum system operation cost as a target and the safe system operation as a constraint; calculating and obtaining an optimized scheduling strategy of the system by adopting an ADMM algorithm based on an optimized scheduling function; according to the method, the characteristics of the topological structure of the shore power system after the ship is connected and the safe operation condition of the system are analyzed, the optimized scheduling function is constructed, the optimized scheduling scheme of the shore power system is solved by adopting the ADMM algorithm, the safe and economic operation of the shore power system is realized, and the stability of the operation of the system is improved.
Description
Technical Field
The invention relates to an energy optimization scheduling method, system, device and medium for a shore power microgrid group system, and belongs to the technical field of power systems.
Background
During the port berthing of a ship, port air and water areas are polluted greatly in a mode of meeting the requirements of shipboard electric equipment through fuel oil power generation. The port shore power technology utilizes a shore-based power supply to supply power to ships stopping at ports, realizes the replacement of oil by electricity, particularly introduces a renewable energy power generation technology into a shore power system, and plays a remarkable role in realizing the integral emission reduction of the shore power.
However, in an actual shore power system, when a ship is in different mooring manners during port berthing, electrical connection structures are greatly different, which causes a topological structure of the system and a system parameter to change, which increases the complexity of the structure of the shore power system to a certain extent, and meanwhile, the intermittent and random properties of a renewable power generation unit configured in the shore power system directly affect the operation characteristics of the whole system, which brings challenges to energy management of the shore power system.
Due to the fact that wiring modes of different mooring modes are different when ships are berthed, system topology structures and parameters are changed, and for example, a scheduling scheme suitable for the radial connection mode does not always provide an optimal operation strategy for the system in other connection modes. Meanwhile, the fluctuation of the ship load in the shore power system also influences the safety and stability of the system.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, provides a shore power microgrid group system energy optimization scheduling method, system, device and medium, and can realize safe and stable operation of a shore power system.
In order to achieve the purpose, the invention is realized by adopting the following technical scheme:
in a first aspect, the invention provides an energy optimization scheduling method for a shore power microgrid group system, which comprises the following steps:
acquiring operation data of shore power and a ship during port berthing of the ship;
based on the operation data of the shore power and the ship, an optimized scheduling function is constructed by taking the minimum system operation cost as a target and the safe system operation as a constraint;
and calculating to obtain the optimized scheduling strategy of the system by adopting an ADMM algorithm based on the optimized scheduling function.
Optionally, the operation data of the shore power includes a power supply power and a power supply efficiency of the shore power unit at each moment, and the shore power unit includes a power grid and a renewable energy source of the shore power; the operation data of the shore power also comprises the power generated by the renewable energy source of the shore power at each moment; the operation data of the ship comprises the electric quantity state of an energy storage device in the ship, and the power supply power and the power supply efficiency of the ship unit at each moment, wherein the ship unit comprises the renewable energy source of the ship and other ships connected with the ship.
Optionally, the optimized scheduling function is:
in the formula, alpha g，t The grid electricity price at time t, P g，t For the supply power of the grid at the instant t,
for the supply power of the grid to vessel m at time t,
the electric quantity state eta of the energy storage equipment in the ship m at the time t and t-1 m The loss coefficient of the energy storage equipment in the ship M is, and M is the number of ships.
Optionally, the system safely operating as the constraint includes:
supply and demand balance constraint:
in the formula (I), the compound is shown in the specification,
providing power supply for a power grid, an energy storage device of a ship m, renewable energy of shore power, renewable energy of the ship m, and a ship n connected with the ship m to the ship m at a time t; ρ is a unit of a gradient g 、ρ s 、ρ r 、ρ sr 、ρ p The power supply efficiency of a power grid, an energy storage device, renewable energy of shore power, renewable energy of a ship and a ship n connected with a ship m;
the electric power of the fixed load and the elastic load of the ship m at the moment t; n is the number of ships connected with the ship m;
energy storage charging and discharging and capacity constraint:
in the formula (I), the compound is shown in the specification,
the minimum value and the maximum value of the charging and discharging power of the energy storage device of the ship m,
the electric quantity state eta of the energy storage equipment in the ship m at the time t and t-1 m，s For the charging and discharging efficiency of the energy storage device in the vessel m,
the minimum value and the maximum value of the electric quantity state of the energy storage equipment in the ship m are obtained;
and (3) power upper and lower limit constraint:
in the formula, P r，t The power generated by the renewable energy source for shore power at time t,
for the minimum and maximum values of the supply power supplied by the grid to the vessel m at the time t,
the minimum value and the maximum value of the electric power of the elastic load of the ship m at the moment t,
the minimum and maximum values of the supply power to the vessel m at the time t are provided for the vessel n connected to the vessel m.
Optionally, the obtaining of the optimized scheduling policy of the system by calculating with the ADMM algorithm based on the optimized scheduling function includes:
method for constructing augmented Lagrangian equation L based on optimized scheduling function g (x g ，z g ，ζ g )：
In the formula (I), the compound is shown in the specification,
ζ g is a dual variable, δ g To extend the Lagrangian parameter, and delta g ＞0；
For the ship m, the augmented Lagrange equation L corresponding to the optimized scheduling function is adopted m (x m ，z m ，ζ m ) Comprises the following steps:
in the formula (I), the compound is shown in the specification,
ζ m solving a dual variable corresponding to the ship m in the process; delta. For the preparation of a coating m For solving the corresponding augmented Lagrange parameter, and delta, of the ship m in question m ＞0；
Lagrange equation L for augmentation g (x g ，z g ，ζ g ) And extended lagrange equation L m (x m ，z m ，ζ m ) Zeta dual variable of g And ζ m Performing iterative optimizationSolving until convergence:
in the formula, k is iteration times;
α g ，α m update coefficients for dual variables;
obtaining a converged dual variable ζ g And ζ m And introducing into the augmented Lagrange equation L g (x g ，z g ，ζ g ) And L m (x m ，z m ，ζ m ) In, calculate
And the optimized result is used as the optimized scheduling strategy of the system.
In a second aspect, the invention provides an energy optimization scheduling system for a shore power microgrid system, comprising:
the data acquisition module is used for acquiring the operation data of shore power and ships during the berthing of the ships;
the function construction module is used for constructing an optimized scheduling function based on the operation data of the shore power and the ship, with the minimum system operation cost as a target and the safe system operation as a constraint;
and the optimized scheduling module is used for calculating and obtaining an optimized scheduling strategy of the system by adopting an ADMM algorithm based on the optimized scheduling function.
Optionally, the operation data of the shore power includes a power supply power and a power supply efficiency of the shore power unit at each moment, and the shore power unit includes a power grid and a renewable energy source of the shore power; the operation data of the shore power also comprises the power generated by renewable energy sources of the shore power at each moment; the operation data of the ship comprises the electric quantity state of an energy storage device in the ship, and the power supply power and the power supply efficiency of the ship unit at each moment, wherein the ship unit comprises the renewable energy source of the ship and other ships connected with the ship.
Optionally, the optimized scheduling function is:
in the formula, alpha g，t For grid electricity prices at time t, P g，t For the supply power of the grid at the instant t,
for the supply power of the grid to vessel m at time t,
the electric quantity state eta of the energy storage equipment in the ship m at the time t and t-1 m The loss coefficient of the energy storage equipment in the ship M is, and M is the number of ships.
Optionally, the system safely operating as the constraint includes:
supply and demand balance constraint:
in the formula (I), the compound is shown in the specification,
providing power supply for a power grid, an energy storage device of a ship m, renewable energy of shore power, renewable energy of the ship m, and a ship n connected with the ship m to the ship m at a time t; rho g 、ρ s 、ρ r 、ρ sr 、ρ p The power supply efficiency of a power grid, an energy storage device, renewable energy of shore power, renewable energy of a ship and a ship n connected with a ship m;
the electric power for the fixed load and the elastic load of the ship m at the moment t; n is the number of ships connected with the ship m;
energy storage charging and discharging and capacity constraint:
in the formula (I), the compound is shown in the specification,
the minimum value and the maximum value of the charging and discharging power of the energy storage device of the ship m,
the electric quantity state eta of the energy storage equipment in the ship m at the time t and t-1 m，s For the charging and discharging efficiency of the energy storage device in the vessel m,
the minimum value and the maximum value of the electric quantity state of the energy storage equipment in the ship m are obtained;
and (3) power upper and lower limit constraint:
in the formula, P r，t The power generated by the renewable energy source which is shore power at time t,
for the minimum and maximum values of the supply power supplied by the grid to the vessel m at the time t,
the minimum value and the maximum value of the electric power of the elastic load of the ship m at the moment t,
the minimum and maximum values of the supply power to vessel m at time t are provided for vessel n connected to vessel m.
Optionally, the obtaining of the optimized scheduling policy of the system by calculating with the ADMM algorithm based on the optimized scheduling function includes:
method for constructing augmented Lagrange equation L based on optimized scheduling function g (x g ，z g ，ζ g )：
In the formula (I), the compound is shown in the specification,
ζ g is a dual variable, δ g To extend the Lagrangian parameter, and delta g ＞0；
For the ship m, the augmented Lagrange equation L corresponding to the optimized scheduling function is adopted m (x m ，z m ，ζ m ) Comprises the following steps:
in the formula (I), the compound is shown in the specification,
ζ m solving a dual variable corresponding to the ship m in the process; delta m For solving the corresponding augmented Lagrange parameter, and delta, of the ship m in question m ＞0；
Lagrange equation for augmentation L g (x g ，z g ，ζ g ) And extended lagrange equation L m (x m ，z m ，ζ m ) Couple variable ζ of g And ζ m Performing iterative optimization solution until convergence:
in the formula, k is iteration times;
α g ，α m update coefficients for dual variables;
obtaining a converged dual variable ζ g And ζ m And introducing into the augmented Lagrange equation L g (x g ，z g ，ζ g ) And L m (x m ，z m ，ζ m ) In, calculate
And the optimized result is used as the optimized scheduling strategy of the system.
In a third aspect, the invention provides an energy optimization scheduling device for a shore power microgrid group system, which comprises a processor and a storage medium;
the storage medium is used for storing instructions;
the processor is configured to operate in accordance with the instructions to perform the steps according to the above-described method.
In a fourth aspect, the invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the above-described method.
Compared with the prior art, the invention has the following beneficial effects:
according to the shore power micro-grid group system energy optimization scheduling method, system, device and medium, the fact that when a ship is in different berthing modes, the connection mode of the ship is different from that of a shore power system is considered, the different connection modes are considered by setting system safe operation as constraint, an optimization scheduling strategy can be provided for the ship in any connection mode of the shore power system, and the universality of energy optimization management of the shore power system is expanded; in the optimized scheduling process, information interaction is directly carried out through the ship and shore power, the power utilization information of ship users is not involved, and the privacy of the ship users in the scheduling participation is improved.
Drawings
Fig. 1 is a flowchart of an energy optimization scheduling method for a shore power microgrid group system according to an embodiment of the present invention;
fig. 2 is a flowchart for calculating an optimized scheduling policy of an acquisition system by using an ADMM algorithm according to an embodiment of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
The first embodiment is as follows:
as shown in fig. 1, the invention provides an energy optimization scheduling method for a shore power microgrid group system, which comprises the following steps:
1. acquiring operation data of shore power and a ship during port berthing of the ship;
in the embodiment, the operation data of the shore power comprises the power supply power and the power supply efficiency of the shore power unit at each moment, and the shore power unit comprises a power grid and renewable energy sources of the shore power; the operation data of the shore power also comprises the power generated by renewable energy sources of the shore power at each moment; the operation data of the ship comprises the electric quantity state of an energy storage device in the ship, and the power supply power and the power supply efficiency of the ship unit at each moment, wherein the ship unit comprises the renewable energy source of the ship and other ships connected with the ship.
2. Based on the operation data of the shore power and the ship, an optimized scheduling function is constructed by taking the minimum system operation cost as a target and the safe system operation as a constraint;
2.1, the system safely operates as the constraint and comprises the following steps:
2.1.1, supply and demand balance constraint:
in the formula (I), the compound is shown in the specification,
providing power supply for a power grid, an energy storage device of a ship m, renewable energy of shore power, renewable energy of the ship m, and a ship n connected with the ship m to the ship m at a time t; ρ is a unit of a gradient g 、ρ s 、ρ r 、ρ sr 、ρ p The power supply efficiency of a power grid, an energy storage device, renewable energy of shore power, renewable energy of a ship and a ship n connected with a ship m;
the electric power of the fixed load and the elastic load of the ship m at the moment t; n is the number of ships connected with the ship m;
2.1.2, energy storage charging and discharging and capacity constraint:
in the formula (I), the compound is shown in the specification,
the minimum value and the maximum value of the charging and discharging power of the energy storage device of the ship m,
the electric quantity state eta of the energy storage equipment in the ship m at the time t and t-1 m，s For vesselsThe charge-discharge efficiency of the energy storage device in m,
the minimum value and the maximum value of the electric quantity state of the energy storage equipment in the ship m are obtained;
2.1.3, power upper and lower limit constraint:
in the formula, P r，t The power generated by the renewable energy source which is shore power at time t,
for the minimum and maximum values of the supply power supplied by the grid to the vessel m at the instant t,
the minimum value and the maximum value of the electric power of the elastic load of the ship m at the moment t,
the minimum and maximum values of the supply power to the vessel m at the time t are provided for the vessel n connected to the vessel m.
2.2, the optimized scheduling function is as follows:
in the formula, alpha g，t The grid electricity price at time t, P g，t For the supply power of the grid at the instant t,
for the supply power of the grid to vessel m at time t,
the electric quantity state eta of the energy storage equipment in the ship m at the time t and t-1 m The loss coefficient of the energy storage equipment in the ship M is, and M is the number of ships.
3. Calculating and obtaining an optimized scheduling strategy of the system by adopting an ADMM algorithm based on an optimized scheduling function;
the Alternating Direction Method (ADMM) is a simple Method to solve the resolvable convex optimization problem. The method can equivalently decompose the objective function of the original problem into a plurality of sub-problems which can be solved, then solve each sub-problem in parallel, and finally coordinate the solution of the sub-problems to obtain the global solution of the original problem.
As shown in fig. 2, the method specifically includes:
3.1 constructing augmented Lagrange equation L based on optimized scheduling function g (x g ，z g ，ζ g )：
In the formula (I), the compound is shown in the specification,
ζ g is a dual variable, δ g To broaden the Lagrangian parameter, and delta g ＞0；
3.2 for vessel m, optimization thereofCorresponding augmented Lagrange equation L of scheduling function m (x m ，z m ，ζ m ) Comprises the following steps:
in the formula (I), the compound is shown in the specification,
ζ m solving a dual variable corresponding to the ship m in the solution; delta m For solving the corresponding augmented Lagrangian parameter, and delta, of the medium ship m m ＞0；
3.3 Lagrange's equation for augmentation g (x g ，z g ，ζ g ) And extended lagrange equation L m (x m ，z m ，ζ m ) Couple variable ζ of g And ζ m Performing iterative optimization solution until convergence:
in the formula, k is iteration times;
α g ，α m update coefficients for dual variables;
3.4 obtaining the converged dual variable zeta g And ζ m And introducing into the augmented Lagrange equation L g (x g ，z g ，ζ g ) And L m (x m ，z m ，ζ m ) In, calculating
The optimized result is used as the optimized scheduling strategy of the system.
In the embodiment, the operation data of the shore power and the ship is acquired during the berthing of the ship; based on the operation data of the shore power and the ship, an optimized dispatch letter is constructed by taking the minimum system operation cost as a target and the safe system operation as a constraint; optimized dispatching strategy can be provided for the ship under any connection mode of the shore power system through system safe operation for constraint (when the ship is in different berthing modes, the connection mode is different from that of the shore power system, the connection mode is different, the operation data is different, and the system safe operation constraint
The system also changes), and the universality of energy optimization management of the shore power system is expanded; calculating by adopting an ADMM algorithm based on an optimized scheduling function to obtain an optimized scheduling strategy of the system; in the optimized dispatching process, information interaction is directly carried out through ships and shore power
The power utilization information of the ship user is not involved, and the privacy of the ship user in scheduling is improved.
Example two:
the embodiment of the invention provides an energy optimization scheduling system of a shore power microgrid group system, which comprises:
the data acquisition module is used for acquiring the operation data of shore power and ships during the berthing period of the ships;
the function construction module is used for constructing an optimized scheduling function based on the operation data of the shore power and the ship, with the minimum system operation cost as a target and the safe system operation as a constraint;
and the optimized scheduling module is used for calculating and obtaining the optimized scheduling strategy of the system by adopting an ADMM algorithm based on the optimized scheduling function.
Specifically, the operation data of the shore power comprises the power supply power and the power supply efficiency of the shore power unit at each moment, and the shore power unit comprises a power grid and renewable energy sources of the shore power; the operation data of the shore power also comprises the power generated by renewable energy sources of the shore power at each moment; the operation data of the ship comprises the electric quantity state of the energy storage equipment in the ship, the power supply power and the power supply efficiency of the ship unit at each moment, and the ship unit comprises the renewable energy source of the ship and other ships connected with the ship.
Specifically, the optimized scheduling function is:
in the formula, alpha g，t For grid electricity prices at time t, P g，t For the supply power of the grid at the instant t,
for the supply power of the grid to vessel m at time t,
the electric quantity state eta of the energy storage equipment in the ship m at the time t and t-1 m The loss coefficient of the energy storage equipment in the ship M, and M is the number of ships.
Specifically, the system safe operation as a constraint includes:
supply and demand balance constraint:
in the formula (I), the compound is shown in the specification,
the power supply power provided to the ship m at time t is the power grid, the energy storage device of the ship m, the renewable energy of the shore power, the renewable energy of the ship m, and the ship n connected with the ship m; ρ is a unit of a gradient g 、ρ s 、ρ r 、ρ sr 、ρ p The power supply efficiency of a power grid, an energy storage device, renewable energy of shore power, renewable energy of a ship and a ship n connected with a ship m;
the electric power of the fixed load and the elastic load of the ship m at the moment t; n is the number of ships connected with the ship m;
energy storage charging and discharging and capacity constraint:
in the formula (I), the compound is shown in the specification,
the minimum value and the maximum value of the charging and discharging power of the energy storage device of the ship m,
the electric quantity state eta of the energy storage equipment in the ship m at the time t and t-1 m，s For the charging and discharging efficiency of the energy storage device in the vessel m,
the minimum value and the maximum value of the electric quantity state of the energy storage equipment in the ship m are obtained;
and (3) power upper and lower limit constraint:
in the formula, P r，t The power generated by the renewable energy source for shore power at time t,
for the minimum and maximum values of the supply power supplied by the grid to the vessel m at the time t,
the minimum value and the maximum value of the electric power of the elastic load of the ship m at the moment t,
the minimum and maximum values of the supply power to the vessel m at the time t are provided for the vessel n connected to the vessel m.
Specifically, the method for obtaining the optimized scheduling strategy of the system by adopting the ADMM algorithm based on the optimized scheduling function includes:
augmented Lagrange construction based on optimized scheduling functionEquation of day L g (x g ，z g ，ζ g )：
In the formula (I), the compound is shown in the specification,
ζ g for dual variables, δ g To broaden the Lagrangian parameter, and delta g ＞0；
For the ship m, the augmented Lagrange equation L corresponding to the optimized scheduling function is adopted m (x m ，z m ，ζ m ) Comprises the following steps:
in the formula (I), the compound is shown in the specification,
ζ m solving a dual variable corresponding to the ship m in the process; delta m For solving the corresponding augmented Lagrange parameter, and delta, of the ship m in question m ＞0；
Lagrange equation for augmentation L g (x g ，z g ，ζ g ) And extended lagrange equation L m (x m ，z m ，ζ m ) Zeta dual variable of g And ζ m Performing iterative optimization solution until convergence:
in the formula, k is iteration times;
α g ，α m update coefficients for dual variables;
obtaining a converged dual variable ζ g And ζ m And carry over into the Lagrange's equation L of augmentation g (x g ，z g ，ζ g ) And L m (x m ，z m ，ζ m ) In, calculating
And the optimized result is used as the optimized scheduling strategy of the system.
Example three:
based on the first embodiment, the embodiment of the invention provides an energy optimization scheduling device for a shore power microgrid system, which comprises a processor and a storage medium, wherein the processor is used for processing the energy optimization scheduling device;
a storage medium to store instructions;
the processor is configured to operate in accordance with instructions to perform steps in accordance with the above-described method.
Example four:
according to a first embodiment, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, and the computer program, when executed by a processor, implements the steps of the method.
The invention establishes a general system energy optimal distribution model suitable for safe and stable operation of a shore power system on the basis of considering uncertainty factors such as renewable energy output power of the shore power system, fluctuation of ship load and the like, and simultaneously gives consideration to safe operation conditions of ships in the shore power system in different mooring modes. The Method adopts an Alternating Direction Method of Multipliers (ADMM) Method to calculate the established mathematical optimization problem, and combines a simulation example to verify the correctness and the effectiveness of the Method.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, it is possible to make various improvements and modifications without departing from the technical principle of the present invention, and those improvements and modifications should be considered as the protection scope of the present invention.
Claims (12)
1. An energy optimization scheduling method for a shore power microgrid group system is characterized by comprising the following steps:
acquiring operation data of shore power and a ship during port berthing of the ship;
based on the operation data of the shore power and the ship, an optimized scheduling function is constructed by taking the minimum system operation cost as a target and the safe system operation as a constraint;
and calculating to obtain the optimized scheduling strategy of the system by adopting an ADMM algorithm based on the optimized scheduling function.
2. The energy optimization scheduling method of the shore power microgrid cluster system according to claim 1,
the operation data of the shore power comprises the power supply power and the power supply efficiency of a shore power unit at each moment, and the shore power unit comprises a power grid and renewable energy sources of the shore power; the operation data of the shore power also comprises the power generated by renewable energy sources of the shore power at each moment;
the operation data of the ship comprises the electric quantity state of an energy storage device in the ship, and the power supply power and the power supply efficiency of the ship unit at each moment, wherein the ship unit comprises the renewable energy source of the ship and other ships connected with the ship.
3. The energy optimization scheduling method of the shore power microgrid cluster system according to claim 2, wherein the optimization scheduling function is as follows:
in the formula, alpha g,t For grid electricity prices at time t, P g,t For the supply power of the grid at the instant t,
for the supply power of the grid to the vessel m at the instant t,
the electric quantity state eta of the energy storage equipment in the ship m at the time t and t-1 m The loss coefficient of the energy storage equipment in the ship M, and M is the number of ships.
4. The energy optimization scheduling method for the shore power microgrid cluster system according to claim 3, wherein the safe operation of the system as a constraint comprises:
supply and demand balance constraint:
in the formula (I), the compound is shown in the specification,
the power supply power provided to the ship m at time t is the power grid, the energy storage device of the ship m, the renewable energy of the shore power, the renewable energy of the ship m, and the ship n connected with the ship m; rho g 、ρ s 、ρ r 、ρ sr 、ρ p The power supply efficiency for the power grid, the energy storage device, the renewable energy of shore power, the renewable energy of the ship, and the ship n connected with the ship m;
the electric power for the fixed load and the elastic load of the ship m at the moment t; n is the number of ships connected with the ship m;
energy storage charging and discharging and capacity constraint:
in the formula (I), the compound is shown in the specification,
the minimum value and the maximum value of the charging and discharging power of the energy storage device of the ship m,
the electric quantity state eta of the energy storage equipment in the ship m at the time t and t-1 m,s For the charging and discharging efficiency of the energy storage device in the vessel m,
the minimum value and the maximum value of the electric quantity state of the energy storage equipment in the ship m are obtained;
and (3) power upper and lower limit constraint:
in the formula, P r,t The power generated by the renewable energy source which is shore power at time t,
for the minimum and maximum values of the supply power supplied by the grid to the vessel m at the instant t,
the minimum value and the maximum value of the electric power of the elastic load of the ship m at the moment t,
the minimum and maximum values of the supply power to vessel m at time t are provided for vessel n connected to vessel m.
5. The energy optimization scheduling method of the shore power microgrid cluster system as claimed in claim 3, wherein the calculating of the optimal scheduling strategy of the obtained system by using the ADMM algorithm based on the optimal scheduling function comprises:
method for constructing augmented Lagrangian equation L based on optimized scheduling function g (x g ,z g ,ζ g )：
In the formula (I), the compound is shown in the specification,
ζ g for dual variables, δ g To extend the Lagrangian parameter, and delta g >0；
For the ship m, the augmented Lagrange equation L corresponding to the optimized scheduling function m (x m ,z m ,ζ m ) Comprises the following steps:
in the formula (I), the compound is shown in the specification,
ζ m solving a dual variable corresponding to the ship m in the process; delta. For the preparation of a coating m For solving the corresponding augmented Lagrange parameter, and delta, of the ship m in question m >0；
Lagrange equation for augmentation L g (x g ,z g ,ζ g ) And extended lagrange equation L m (x m ,z m ,ζ m ) Couple variable ζ of g And ζ m Performing iterative optimization solution until convergence:
in the formula, k is iteration times;
α g ,α m update coefficients for dual variables;
obtaining a converged dual variable ζ g And ζ m And carry over into the Lagrange's equation L of augmentation g (x g ,z g ,ζ g ) And L m (x m ,z m ,ζ m ) In, calculating
The optimized result is used as the optimized scheduling strategy of the system.
6. An energy optimization scheduling system of a shore power microgrid system, characterized in that the system comprises:
the data acquisition module is used for acquiring the operation data of shore power and ships during the berthing of the ships;
the function construction module is used for constructing an optimized scheduling function based on the operation data of the shore power and the ship, with the minimum system operation cost as a target and the safe system operation as a constraint;
and the optimized scheduling module is used for calculating and obtaining an optimized scheduling strategy of the system by adopting an ADMM algorithm based on the optimized scheduling function.
7. The energy optimization scheduling system of the shore power microgrid system according to claim 6, characterized in that,
the operation data of the shore power comprises the power supply power and the power supply efficiency of a shore power unit at each moment, and the shore power unit comprises a power grid and renewable energy sources of the shore power; the operation data of the shore power also comprises the power generated by renewable energy sources of the shore power at each moment;
the operation data of the ship comprises the electric quantity state of an energy storage device in the ship, and the power supply power and the power supply efficiency of the ship unit at each moment, wherein the ship unit comprises the renewable energy source of the ship and other ships connected with the ship.
8. The system as claimed in claim 7, wherein the optimal scheduling function is:
in the formula, alpha g,t For grid electricity prices at time t, P g,t For the supply power of the grid at the instant t,
for the supply power of the grid to vessel m at time t,
the electric quantity state eta of the energy storage equipment in the ship m at the time t and t-1 m Is the loss coefficient of the energy storage equipment in the ship M, M isThe number of ships.
9. The energy-optimized scheduling system for the shore power microgrid system of claim 8, wherein the system safe operation as a constraint comprises:
supply and demand balance constraint:
in the formula (I), the compound is shown in the specification,
the power supply power provided to the ship m at time t is the power grid, the energy storage device of the ship m, the renewable energy of the shore power, the renewable energy of the ship m, and the ship n connected with the ship m; rho g 、ρ s 、ρ r 、ρ sr 、ρ p The power supply efficiency for the power grid, the energy storage device, the renewable energy of shore power, the renewable energy of the ship, and the ship n connected with the ship m;
the electric power of the fixed load and the elastic load of the ship m at the moment t; n is the number of ships connected with the ship m;
energy storage charging and discharging and capacity constraint:
in the formula，
The minimum value and the maximum value of the charging and discharging power of the energy storage device of the ship m,
the electric quantity state eta of the energy storage equipment in the ship m at the time t and t-1 m,s For the charging and discharging efficiency of the energy storage device in the vessel m,
the minimum value and the maximum value of the electric quantity state of the energy storage equipment in the ship m are obtained;
and (3) power upper and lower limit constraint:
in the formula, P r,t The power generated by the renewable energy source for shore power at time t,
for the minimum and maximum values of the supply power supplied by the grid to the vessel m at the instant t,
the minimum value and the maximum value of the electric power of the elastic load of the ship m at the moment t,
the minimum and maximum values of the supply power to the vessel m at the time t are provided for the vessel n connected to the vessel m.
10. The energy optimization scheduling system of the shore power microgrid system as claimed in claim 8, wherein the calculating of the optimized scheduling policy of the obtained system by using the ADMM algorithm based on the optimized scheduling function comprises:
method for constructing augmented Lagrangian equation L based on optimized scheduling function g (x g ,z g ,ζ g )：
In the formula (I), the compound is shown in the specification,
ζ g for dual variables, δ g To extend the Lagrangian parameter, and delta g >0；
For the ship m, the augmented Lagrange equation L corresponding to the optimized scheduling function is adopted m (x m ,z m ,ζ m ) Comprises the following steps:
in the formula (I), the compound is shown in the specification,
ζ m solving a dual variable corresponding to the ship m in the process; delta m For solving the corresponding augmented Lagrangian parameter, and delta, of the medium ship m m >0；
Lagrange equation L for augmentation g (x g ,z g ,ζ g ) And extended lagrange equation L m (x m ,z m ,ζ m ) Zeta dual variable of g And ζ m Performing iterative optimization solution until convergence:
in the formula, k is iteration times;
α g ,α m update coefficients for dual variables;
obtaining a converged dual variable ζ g And ζ m And introducing into the augmented Lagrange equation L g (x g ,z g ,ζ g ) And L m (x m ,z m ,ζ m ) In, calculating
As a result of the optimization of the systemAnd (4) strategy.
11. An energy optimization scheduling device for a shore power microgrid group system is characterized by comprising a processor and a storage medium;
the storage medium is used for storing instructions;
the processor is configured to operate in accordance with the instructions to perform the steps of the method according to any one of claims 1 to 5.
12. Computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 5.
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| CN116760034B (en) * | 2023-08-22 | 2023-11-14 | 南京邮电大学 | Virtual voltage-based complete distributed optimal scheduling method for multi-harbor district shore power system |
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