An automatic shore power dispatching method and system for a hybrid energy power supply system based on an improved genetic algorithm

Abstract

The application discloses a shore power automatic scheduling method and system for a hybrid energy power supply system based on an improved genetic algorithm, and the method comprises the following steps: constructing a power supply cost calculation model of the hybrid energy power supply system; establishing a power supply source and load balance constraint condition in the hybrid energy power supply system; establishing an upper and lower limit constraint condition of output power for a wind power and photovoltaic power generation system, and establishing an upper limit constraint condition for an energy storage system; based on the power supply cost calculation model of the hybrid energy power supply system, taking the lowest power supply cost of the hybrid energy power supply system in a period of time as a target, and establishing a target function; performing parameter optimization of the target function under all constraint conditions through the improved genetic algorithm, calculating the power supply coefficient and the lowest power supply cost of each power supply system of the hybrid energy power supply system at the moment, and generating a shore power automatic scheduling recommendation scheme in real time. The application can add renewable energy to the shore power supply system and reasonably distribute shore power in the hybrid energy power supply system.

Description

Technical Field

[0001] This invention belongs to the field of new energy shore power, specifically relating to an automatic shore power dispatching method and system for a hybrid energy power supply system based on an improved genetic algorithm. Background Technology

[0002] In recent years, port construction has been accelerating. However, the increasing number of ships berthed in ports has also brought challenges to port operation and management. During berthing, to ensure the operation of ships and the basic living needs of crew members, the port must provide electricity to meet the energy demands of ships docking; this is shore power technology. Using shore power can protect the environment, reduce emissions from fuel combustion, and save costs after ships dock, bringing certain economic benefits to the port. Currently, shore power technology is not yet widespread in ports, which has significant implications for economic development and environmental protection.

[0003] Establishing shore power systems and dispatching systems is of significant research importance. On the one hand, shore power systems can reduce pollution caused by the use of non-renewable energy sources for power supply during ship berthing, aligning with sustainable development goals and protecting both the marine and air environments. On the other hand, shore power systems can reduce the reliance on non-renewable energy sources. With global resources becoming increasingly scarce, the utilization of renewable energy is a hot topic. Furthermore, the cost of using renewable energy is lower than that of non-renewable energy sources to some extent, bringing economic benefits to port operators.

[0004] Currently, most shore power supplies for ships utilize electricity transmitted from the power grid, but research on shore power systems employing hybrid energy sources is limited. Therefore, further research is needed on how to incorporate renewable energy into shore power systems and how to rationally allocate shore power in hybrid energy systems. Summary of the Invention

[0005] Purpose of the invention: The purpose of this invention is to provide an automatic shore power dispatching method and system for a hybrid energy power supply system based on an improved genetic algorithm, which can add renewable energy to the shore power supply system and perform reasonable shore power allocation for the hybrid energy power supply system.

[0006] Technical solution: The present invention provides an automatic shore power dispatching method for a hybrid energy supply system based on an improved genetic algorithm, comprising:

[0007] Construct a power supply cost calculation model for a hybrid energy power supply system, including the power supply cost of wind power generation system, photovoltaic power generation system, energy storage system, and grid system;

[0008] Based on the power conditions of the wind power generation system, photovoltaic power generation system, energy storage system, and power grid system in the hybrid energy power supply system, as well as the power supply demand of each berth in the port, the power supply and load balance constraints in the hybrid energy power supply system are established.

[0009] Establish upper and lower limit constraints on the output power of wind power generation systems and photovoltaic power generation systems, and establish upper limit constraints on energy storage systems;

[0010] Based on the power supply cost calculation model of the hybrid energy power supply system, the objective function for optimizing the automatic dispatch of shore power of the hybrid energy power supply system is established with the goal of minimizing the power supply cost of the hybrid energy power supply system over a period of time.

[0011] By improving the genetic algorithm, the parameters of the objective function for the automatic shore power dispatch of the hybrid energy power supply system are optimized under all constraints. Based on the power supply demand of each berth in the port, the power supply coefficient and minimum power supply cost of each power supply system of the hybrid energy power supply system at that time are obtained, and a recommended scheme for automatic shore power dispatch is generated in real time.

[0012] Furthermore, the expression for the power supply cost calculation model of the hybrid energy power supply system is as follows:

[0013]

[0014] Where C represents the total cost of power supply for the power supply system; C w The cost of generating electricity for wind power electronic systems; C PV The cost of electricity generated by a photovoltaic power generation system; C m The power generation cost of the power grid system; C SOC The power generation cost of the energy storage system; P w t P represents the output power of the wind turbine at time t. PV t P represents the output power of the photovoltaic power generation at time t. m t P represents the output power of the main power grid at time t. SOC t Let t be the output power of the energy storage system at time t.

[0015] Furthermore, obtain the wind power output P at time t. w t The output power P of photovoltaic power generation at time t PV t During the process, the perturbation observation method is used to perform maximum power tracking on the wind power generation system and the photovoltaic power generation system. In the initial stage, the maximum power point is searched using a step size until a stable output is achieved.

[0016] Furthermore, the power supply and load balance constraint in the hybrid energy power supply system, namely, the power required by the ship at time t in the i-th berth is equal to the power provided by each subsystem at that time, is expressed by the following expression:

[0017]

[0018] in, Let be the power required for the i-th berth to berth at time t; Let be the output power of the wind turbine at time t; Let be the output power of the photovoltaic power generation at time t; Let be the output power generated by the main power grid at time t; Let t be the output power of the energy storage system at time t.

[0019] Furthermore, the power generation mode of the hybrid energy power supply system is determined according to the working environment, and the power generation mode includes:

[0020] P w +P PV ≥P L P SOC <0: At this time, the output power of the wind power generation system and the photovoltaic power generation system meets the load power required by the port berth. The excess electrical energy charges the energy storage system. At this time, the energy storage system does negative work, i.e., P SOC <0;

[0021] P w +P PV <P L P SOC >0: At this time, the output power of the wind power generation system and the photovoltaic power generation system cannot meet the power requirements of the port, so the energy storage system discharges. At this time, the energy storage system does positive work, i.e., P SOC >0; where P w For the output power of the wind power generation electronic system, P PV For the output power of the photovoltaic power generation system, P SOC P is the output power of the energy storage system. L This represents the load power.

[0022] Furthermore, the establishment of upper and lower limit constraints on the output power of the wind power generation system and the photovoltaic power generation system, and the establishment of an upper limit constraint on the energy storage system, are as follows:

[0023]

[0024] in, This represents the maximum output power of the wind power generation system. This represents the maximum output power of the photovoltaic power generation system. This represents the maximum output power of the energy storage system.

[0025] Furthermore, the expression for the objective function of the automatic shore power dispatch optimization of the hybrid energy power supply system is as follows:

[0026]

[0027] In the formula, C represents the total cost of the power supply system; C w The cost of generating electricity for wind power electronic systems; C PV The cost of electricity generated by a photovoltaic power generation system; C m The power generation cost of the power grid system; C SOC The cost of generating electricity for energy storage systems; Let be the output power of the wind turbine at time t; Let be the output power of the photovoltaic power generation at time t; Let be the output power generated by the main power grid at time t; Let t be the output power of the energy storage system at time t.

[0028] Furthermore, the improved genetic algorithm includes: calculating the fitness at this initial value, determining whether the fitness meets the requirements, and if it meets the requirements, outputting the solution at this time as the optimal solution; if it does not meet the requirements, performing adaptive crossover and mutation of the genetic algorithm.

[0029] By calculating the adaptive crossover probability and adaptive mutation probability of individuals, crossover and mutation are performed based on the calculated adaptive genetic factors.

[0030] The fitness function of the newly obtained individuals is recalculated until the individual with the best fitness value is selected. Finally, the individual that meets the conditions is output and decoded as the optimal solution.

[0031] Furthermore, adaptive genetic factors are designed based on the fitness of individuals, and the crossover and mutation probabilities are adaptively adjusted based on these adaptive genetic factors. The expression for this is as follows:

[0032]

[0033] In the formula, P c For adaptive crossover probability, P m α represents the adaptive mutation probability; x represents the individual to be iterated, and α represents the adaptive genetic factor.

[0034] Based on the same inventive concept, the present invention provides an automatic shore power dispatching system for a hybrid energy supply system based on an improved genetic algorithm, comprising:

[0035] The model building module is used to build a power supply cost calculation model for hybrid energy power supply systems, including the power supply cost of wind power generation systems, the power supply cost of photovoltaic power generation systems, the cost of energy storage systems, and the cost of power grid systems.

[0036] The constraint establishment module is used to establish power supply and load balance constraints in the hybrid energy power supply system based on the power conditions of the wind power generation system, photovoltaic power generation system, energy storage system, and power grid system, as well as the power supply demand of each berth in the port; it is also used for

[0037] Establish upper and lower limit constraints on the output power of wind power generation systems and photovoltaic power generation systems, and establish upper limit constraints on energy storage systems;

[0038] The objective function establishment module, based on the power supply cost calculation model of the hybrid energy power supply system, takes the minimum power supply cost of the hybrid energy power supply system within a certain period of time as the objective and establishes the objective function for the automatic dispatch optimization of shore power of the hybrid energy power supply system.

[0039] The scheduling scheme generation module is used to optimize the parameters of the shore power automatic scheduling optimization objective function of the hybrid energy power supply system under all constraints by using an improved genetic algorithm. Based on the power supply demand of each berth in the port, it obtains the power supply coefficient and minimum power supply cost of each power supply system of the hybrid energy power supply system at that time, and generates a recommended shore power automatic scheduling scheme in real time.

[0040] Based on the same inventive concept, the present invention provides an automatic shore power dispatching device for a hybrid energy power supply system based on an improved genetic algorithm, comprising a processor and a memory. The memory stores computer instructions, and the processor is used to execute the computer instructions stored in the memory. When the computer instructions are executed by the processor, the electronic device implements the steps of the above-mentioned automatic shore power dispatching method for a hybrid energy power supply system based on an improved genetic algorithm.

[0041] Based on the same inventive concept, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method for automatic shore power dispatching of a hybrid energy power supply system based on an improved genetic algorithm.

[0042] Beneficial effects: Compared with the prior art, the significant technical effects of the present invention are as follows:

[0043] This invention proposes a method for establishing a shore power supply system using renewable energy sources. This method can incorporate subsystems such as wind power generation, photovoltaic power generation, and energy storage systems into the shore power supply system, and employs maximum power tracking for wind power generation and photovoltaic power generation to improve energy utilization efficiency.

[0044] By establishing an objective function for the automatic scheduling optimization of shore power in a hybrid energy power supply system, and using an improved genetic algorithm to find the optimal solution under constraints with economic efficiency as an important indicator, a scheme for the hybrid energy power supply system to supply power to ships docked in port berths is obtained, thus realizing the automatic scheduling of the hybrid energy power supply system.

[0045] An improved genetic algorithm is used to automatically adjust the dynamic crossover and mutation probabilities based on fitness. This enhances the global optimization capability of the genetic algorithm, avoids getting trapped in local optima, and improves the accuracy and applicability of the shore power automatic dispatching system. Attached Figure Description

[0046] Figure 1 This is a flowchart illustrating an automatic shore power dispatching method for a hybrid energy power supply system based on an improved genetic algorithm, as disclosed in an embodiment of the present invention.

[0047] Figure 2 This is a flowchart of an improved genetic algorithm with adaptive crossover and mutation, as disclosed in an embodiment of the present invention.

[0048] Figure 3 This is a schematic diagram of the structure of an automatic shore power dispatching system for a hybrid energy power supply system based on an improved genetic algorithm, as disclosed in an embodiment of the present invention.

[0049] Figure 4 This is a schematic diagram of the structure of an automatic shore power dispatching device for a hybrid energy power supply system based on an improved genetic algorithm, as disclosed in an embodiment of the present invention. Detailed Implementation

[0050] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. Those skilled in the art will understand that the objectives and advantages achievable with the present invention are not limited to those specifically described above, and that the above and other objectives achievable by the present invention will become clearer from the following detailed description.

[0051] Those skilled in the art will understand that the exemplary components, systems, and methods described in conjunction with the embodiments disclosed herein can be implemented in hardware, software, or a combination of both. Whether implemented in hardware or software depends on the specific application, design, and conditions of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0052] In this invention, the term "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0053] Example 1

[0054] Please see Figure 1 , Figure 1 This is a flowchart illustrating an automatic shore power dispatching method for a hybrid energy supply system based on an improved genetic algorithm, as disclosed in an embodiment of the present invention. Figure 1 The described shore power automatic dispatching method is applied to power systems, such as for shore power automatic dispatching, etc., and the embodiments of this invention are not limited thereto. Figure 1 As shown, the automatic shore power dispatching method for a hybrid energy supply system based on an improved genetic algorithm may include the following operations:

[0055] S1. Construct a power supply cost calculation model for a hybrid energy power supply system, including the power supply cost of wind power generation system, photovoltaic power generation system, energy storage system, and grid system.

[0056] In this embodiment, the expression for the power supply cost calculation model of the hybrid energy power supply system is as follows:

[0057]

[0058] Where C represents the total cost of power supply for the power supply system; C w The cost of generating electricity for wind power electronic systems; C PV The cost of electricity generated by a photovoltaic power generation system; C m The power generation cost of the power grid system; C SOC The power generation cost of the energy storage system; P w t P represents the output power of the wind turbine at time t. PV t P represents the output power of the photovoltaic power generation at time t. m t P represents the output power of the main power grid at time t. SOC t Let t be the output power of the energy storage system at time t.

[0059] For intermittent and unstable power sources such as wind power and photovoltaic power, in order to maximize energy utilization, the output power P of wind power generation at time t needs to be obtained. w t The output power P of photovoltaic power generation at time t PV t During the process, the perturbation observation method is used to perform maximum power tracking on the wind power generation system and the photovoltaic power generation system. In the initial stage, the maximum power point is searched using a step size until a stable output is achieved.

[0060] S2. Based on the power status of the wind power generation system, photovoltaic power generation system, energy storage system, and power grid system in the hybrid energy power supply system, as well as the power supply demand of each berth in the port, establish the power supply and load balance constraints in the hybrid energy power supply system.

[0061] In this embodiment, the power supply and load balance constraint in the hybrid energy power supply system, namely, the power required by the ship at time t in the i-th berth is equal to the power provided by each subsystem at that time, is expressed by the following expression:

[0062]

[0063] in, Let be the power required for the i-th berth to berth at time t; Let be the output power of the wind turbine at time t; Let be the output power of the photovoltaic power generation at time t; Let be the output power generated by the main power grid at time t; Let t be the output power of the energy storage system at time t.

[0064] In this step, the power generation of the hybrid energy power supply system varies depending on the port's natural conditions. Wind speed at the port affects the output power of the wind power generation system, while port temperature and sunlight intensity affect the output power of the photovoltaic power generation system. Furthermore, the load on the port berths is constantly changing. The power generation mode of the hybrid energy power supply system is determined based on the working environment. The power generation modes (i.e., the operating modes of the hybrid energy power supply system) include:

[0065] Mode 1: P w +P PV ≥P L P SOC <0: At this time, the output power of the wind power generation system and the photovoltaic power generation system meets the load power required by the port berth. The excess electrical energy charges the energy storage system. At this time, the energy storage system does negative work, i.e., P SOC <0;

[0066] Mode 2: P w +P PV <P L P SOC >0: At this time, the output power of the wind power generation system and the photovoltaic power generation system cannot meet the power requirements of the port, so the energy storage system discharges. At this time, the energy storage system does positive work, i.e., P SOC >0; where P w For the output power of the wind power generation electronic system, P PV For the output power of the photovoltaic power generation system, P SOC P is the output power of the energy storage system. L This refers to the load power. Load power PL It can be approximated as the sum of the power required by each berth.

[0067] Based on the actual situation at the port each day, the power generation mode of the hybrid energy power supply system will automatically switch to maintain the normal power supply of the power supply system.

[0068] S3. Establish upper and lower limit constraints on the output power of wind power generation systems and photovoltaic power generation systems, and establish upper limit constraints on energy storage systems. Details are as follows:

[0069]

[0070] in, This represents the maximum output power of the wind power generation system. This represents the maximum output power of the photovoltaic power generation system. This represents the maximum output power of the energy storage system.

[0071] S4. A power supply cost calculation model based on a hybrid energy power supply system is established, with the goal of minimizing the power supply cost of the hybrid energy power supply system over a period of time;

[0072] In this embodiment, the expression for the objective function is as follows:

[0073]

[0074] In the formula, C represents the total cost of the power supply system; C w The cost of generating electricity for wind power electronic systems; C PV The cost of electricity generated by a photovoltaic power generation system; C m The power generation cost of the power grid system; C SOC The cost of generating electricity for energy storage systems; Let be the output power of the wind turbine at time t; Let be the output power of the photovoltaic power generation at time t; Let be the output power generated by the main power grid at time t; Let t be the output power of the energy storage system at time t.

[0075] In this embodiment, economic efficiency is an important indicator, that is, the objective function is to minimize the power supply cost of the hybrid energy power supply system for 24 hours a day.

[0076] S5. By improving the genetic algorithm, the parameters of the objective function are optimized under all constraints. Based on the power supply demand of each berth in the port, the power supply coefficient and minimum power supply cost of each power supply system of the hybrid energy power supply system at that time are obtained, and a recommended scheme for automatic shore power dispatch is generated in real time.

[0077] In traditional genetic algorithms, the default values ​​for crossover and mutation probabilities directly affect the algorithm's global optimization capability and convergence speed. Therefore, traditional genetic algorithms can be improved by replacing fixed crossover and mutation probabilities with dynamic crossover and mutation probabilities that automatically adjust based on fitness.

[0078] In this embodiment, as Figure 2 As shown, the improved genetic algorithm includes: first, initializing the population and setting initial values ​​such as the number of iterations and the population size; then, calculating the fitness under these initial values, determining whether the fitness meets the requirements, and if it does, outputting the current solution as the optimal solution; otherwise, performing adaptive crossover and mutation in the genetic algorithm. This involves calculating the adaptive crossover and mutation probabilities for individuals and performing crossover and mutation based on the calculated adaptive genetic factors; then recalculating the fitness function of the newly obtained individuals until the individual with the best fitness value is selected; finally, outputting the individual that meets the conditions and decoding it as the optimal solution. This improved genetic algorithm is used for automatic shore power scheduling in a hybrid energy power supply system to improve the efficiency and economic benefits of port management and operation.

[0079] This invention designs adaptive genetic factors based on the fitness of individuals, and adaptively adjusts the crossover probability and mutation probability according to the adaptive genetic factors, as expressed by the following formula:

[0080]

[0081]

[0082] In the formula, P c For adaptive crossover probability, P m Let α be the adaptive mutation probability; x be the individual to be iterated; and α be the adaptive genetic factor. This adaptive crossover probability and adaptive mutation probability enhance the global optimization ability of the genetic algorithm, preventing it from getting trapped in local optima.

[0083] In this embodiment, under the constraints established above, an improved genetic algorithm is used to find the optimal solution until the power supply cost of the 24-hour hybrid power supply system is minimized. The solution is then obtained to provide power to the ships docked in the port berths, thus achieving automatic scheduling of the hybrid power supply system.

[0084] This invention utilizes two new energy sources, solar and wind power, to supply electricity to ports. Taking into account the characteristics of these two energy sources, a maximum power point tracking (MPPT) method is employed to improve energy utilization and ensure maximum resource utilization. Simultaneously, an energy storage system is used to maintain inverter voltage and store and release excess wind and solar energy. Finally, combined with the national power grid, a hybrid energy power supply system is obtained. A shore power supply system integrating wind, solar, energy storage, and grid energy is constructed, and an automatic shore power dispatching system is established. With economic efficiency as a key indicator, an improved genetic algorithm is used to adaptively optimize the model. The optimal solution is then used to determine the automatic shore power dispatching scheme for the hybrid energy power supply system.

[0085] Example 2

[0086] Please see Figure 3 , Figure 3 This is a schematic diagram of the structure of an automatic shore power dispatching system based on an improved genetic algorithm for a hybrid energy power supply system disclosed in an embodiment of the present invention. The system can realize automatic shore power dispatching, specifically including:

[0087] The model building module is used to build a power supply cost calculation model for hybrid energy power supply systems, including the power supply cost of wind power generation systems, the power supply cost of photovoltaic power generation systems, the cost of energy storage systems, and the cost of power grid systems.

[0088] The constraint establishment module is used to establish power supply and load balance constraints in the hybrid energy power supply system based on the power conditions of the wind power generation system, photovoltaic power generation system, energy storage system, and power grid system, as well as the power supply demand of each berth in the port; it is also used for

[0089] Establish upper and lower limit constraints on the output power of wind power generation systems and photovoltaic power generation systems, and establish upper limit constraints on energy storage systems;

[0090] The objective function establishment module, based on the power supply cost calculation model of the hybrid energy power supply system, takes the minimum power supply cost of the hybrid energy power supply system over a period of time as the objective and establishes the objective function.

[0091] The scheduling scheme generation module is used to optimize the parameters of the objective function under all constraints by improving the genetic algorithm. Based on the power supply demand of each berth in the port, it obtains the power supply coefficient and minimum power supply cost of each power supply system of the hybrid energy power supply system at that time, and generates a recommended scheme for automatic shore power scheduling in real time.

[0092] In one optional implementation, the automatic shore power dispatching of a hybrid energy power supply system based on an improved genetic algorithm includes: a) constructing a power supply cost calculation model for the hybrid energy power supply system; b) establishing power supply and load balance constraints in the hybrid energy power supply system; c) establishing upper and lower limits of output power constraints for wind power generation systems and photovoltaic power generation systems, and upper limit constraints for energy storage systems; d) based on the power supply cost calculation model of the hybrid energy power supply system, setting the minimum power supply cost of the hybrid energy power supply system over a period of time as the objective, and establishing an objective function; e) optimizing the parameters of the objective function under all constraints using an improved genetic algorithm, obtaining the power supply coefficient and minimum power supply cost of each power supply system in the hybrid energy power supply system at that moment according to the power supply demand of each berth in the port, and generating a recommended automatic shore power dispatching scheme in real time.

[0093] Example 3

[0094] Please see Figure 4 , Figure 4 This is a schematic diagram of the structure of an automatic shore power dispatching device for a hybrid energy power supply system based on an improved genetic algorithm, as disclosed in an embodiment of the present invention. Figure 4 The described shore power automatic dispatching equipment is applied to power systems, such as for shore power automatic dispatching, etc., and the embodiments of the present invention are not limited thereto.

[0095] like Figure 4 As shown, the device may include a processor and a memory, the memory storing computer instructions, and the processor executing the computer instructions stored in the memory. When the computer instructions are executed by the processor, the electronic device implements the steps of the method described in the above embodiments and achieves the same technical effect as the above method.

[0096] The memory may include computer system readable media in the form of volatile memory, such as random access memory (RAM) and / or cache memory. The device may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the memory may be used to read and write non-removable, non-volatile magnetic media (commonly referred to as a "hard disk drive"). A program / utility having a set (at least one) of program modules may be stored in, for example, memory. Such program modules include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. The program modules typically perform the functions and / or methods described in the embodiments of the present invention.

[0097] The processor executes various functional applications and data processing by running programs stored in memory, such as the method provided in Embodiment 1 of the present invention.

[0098] Example 4

[0099] Embodiment 4 of the present invention also provides a computer-readable storage medium storing a computer program thereon. When the program is executed by a processor, it implements the steps of the method described in the above embodiments and achieves the same technical effect as the above method.

[0100] The computer storage medium of this invention can be any combination of one or more computer-readable media. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0101] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0102] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0103] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0104] Of course, the computer-executable instructions provided in the embodiments of the present invention are not limited to the above-described method operations, but can also perform related operations in the methods provided in any embodiment of the present invention.

[0105] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An automatic shore power dispatching method for a hybrid energy power supply system based on an improved genetic algorithm, characterized in that, include: Construct a power supply cost calculation model for a hybrid energy power supply system, including the power supply cost of wind power generation system, photovoltaic power generation system, energy storage system, and grid system; Based on the power conditions of the wind power generation system, photovoltaic power generation system, energy storage system, and power grid system in the hybrid energy power supply system, as well as the power supply demand of each berth in the port, the power supply and load balance constraints in the hybrid energy power supply system are established. Establish upper and lower limits of output power constraints for wind power generation systems and photovoltaic power generation systems, and establish upper limit constraints for energy storage systems; Based on the power supply cost calculation model of the hybrid energy power supply system, the objective function for optimizing the automatic dispatch of shore power of the hybrid energy power supply system is established with the goal of minimizing the power supply cost of the hybrid energy power supply system over a period of time. An improved genetic algorithm is used to optimize the parameters of the shore power automatic dispatching objective function of the hybrid energy power supply system under all constraints. Based on the power supply demand of each berth in the port, the power supply coefficient and minimum power supply cost of each power supply system in the hybrid energy power supply system at that time are obtained, and a recommended shore power automatic dispatching scheme is generated in real time. The improved genetic algorithm includes: Initialize the population by setting initial values ​​for the number of iterations and the population size; Calculate the fitness at this initial value, determine whether the fitness meets the requirements, and if it does, output the current solution as the optimal solution; otherwise, perform adaptive crossover and mutation using a genetic algorithm. Adaptive crossover and adaptive mutation probabilities are calculated for individuals, and crossover and mutation are performed based on the calculated adaptive genetic factors. Specifically, adaptive genetic factors are designed based on the fitness of individuals, and the crossover and mutation probabilities are adaptively adjusted based on these factors. The expressions are as follows: ； ； wherein is the adaptive crossover probability, is the adaptive mutation probability; is the number of individuals to iterate, is the adaptive genetic factor; The fitness function of the newly obtained individuals is recalculated until the individual with the best fitness value is selected. Finally, the individual that meets the conditions is output and decoded as the optimal solution. 2.The shore power automatic dispatching method of the hybrid energy power supply system based on the improved genetic algorithm of claim 1, characterized in that, The expression for the power supply cost calculation model of the hybrid energy power supply system is as follows: ； in, The total cost of power supply for the power supply system; The cost of generating electricity for wind power electronic systems; The cost of electricity generated by a photovoltaic power generation system; The power generation cost of the power grid system; The cost of generating electricity for the energy storage system; for The output power of wind power generation at any given moment; for The output power of photovoltaic power generation at any given moment; for The output power of the main power grid at any given time; for The output power of the energy storage system at all times.

3. The shore power automatic dispatching method for the hybrid energy power supply system based on the improved genetic algorithm according to claim 2, characterized in that, acquiring output power of wind power generation at the moment and output power of photovoltaic power generation at the moment In the process of wind power generation and photovoltaic power generation, the maximum power point tracking is performed on the wind power generation system and the photovoltaic power generation system by using the perturbation and observation method. In the initial stage, the step length is used to search for the maximum power point until the stable output is reached.

4. The shore power automatic dispatching method for the hybrid energy power supply system based on the improved genetic algorithm according to claim 1, characterized in that, The mixed energy power supply system has a power supply source and a load balance constraint condition, namely The power required by the ship at the i-th berth at the j-th moment is equal to the power provided by each subsystem at the j-th moment, and is expressed by the following expression: The power required by the ship at the i-th berth at the j-th moment is equal to the power provided by each subsystem at the j-th moment, and is expressed by the following expression: ； in, for The first moment The power required for ships to berth at each berth; for The output power of wind power generation at any given moment; for The output power of photovoltaic power generation at any given moment; for The output power of the main power grid at any given time; for The output power of the energy storage system at all times.

5. The shore power automatic dispatching method for the hybrid energy power supply system based on the improved genetic algorithm according to claim 4, characterized in that, The power generation mode of the hybrid energy power supply system is determined according to the working environment, and the power generation modes include: , : At this time, the output power of the wind power generation system and the photovoltaic power generation system meets the load power required by the port berth, and the excess power charges the energy storage system. At this time, the energy storage system does negative work, that is, ; , : At this time, the output power of the wind power generation system and the photovoltaic power generation system does not meet the required power of the port, the energy storage system discharges, at this time the energy storage system does positive work, that is ; wherein, is the output power of the wind power generation system, is the output power of the photovoltaic power generation system, is the output power of the energy storage system, is the load power.

6. The shore power automatic dispatching method of the hybrid energy power supply system based on the improved genetic algorithm according to claim 4, characterized in that, The upper and lower limit constraints on the output power of wind power generation systems and photovoltaic power generation systems, and the upper limit constraint on energy storage systems, are established as follows: ； ； ； wherein, Pmax, wind is the maximum output power of the wind power generation subsystem; Pmax, pv is the maximum output power of the photovoltaic power generation subsystem; Pmax, storage is the maximum output power of the energy storage subsystem.

7. The shore power automatic dispatching method of the hybrid energy power supply system based on the improved genetic algorithm according to claim 1, characterized in that, The objective function for optimizing the automatic shore power dispatch of the hybrid energy supply system is expressed as follows: ； In the formula, The total cost of power supply for the power supply system; The cost of generating electricity for wind power electronic systems; The cost of electricity generated by a photovoltaic power generation system; The power generation cost of the power grid system; The cost of generating electricity for the energy storage system; for The output power of wind power generation at any given moment; for The output power of photovoltaic power generation at any given moment; for The output power of the main power grid at any given time; for The output power of the energy storage system at all times.

8. An automatic shore power dispatching system for a hybrid energy power supply system based on an improved genetic algorithm, characterized in that, include: The model building module is used to build a power supply cost calculation model for hybrid energy power supply systems, including the power supply cost of wind power generation systems, the power supply cost of photovoltaic power generation systems, the cost of energy storage systems, and the cost of power grid systems. The constraint establishment module is used to establish power supply and load balance constraints in the hybrid energy power supply system based on the power conditions of the wind power generation system, photovoltaic power generation system, energy storage system, and power grid system, as well as the power supply demand of each berth in the port; it is also used for Establish upper and lower limits of output power constraints for wind power generation systems and photovoltaic power generation systems, and establish upper limit constraints for energy storage systems; The objective function establishment module establishes a shore power automatic dispatching optimization objective function of the hybrid energy power supply system based on a power supply cost calculation model of the hybrid energy power supply system, and takes the lowest power supply cost of the hybrid energy power supply system in a period of time as a target. The dispatching scheme generation module is used for parameter optimization of the shore power automatic dispatching optimization objective function of the hybrid energy power supply system under all constraint conditions through an improved genetic algorithm, and obtains the power supply coefficient and the lowest power supply cost of each power supply subsystem of the hybrid energy power supply system at the moment according to the power supply demand of each berth of the port, and generates a shore power automatic dispatching recommendation scheme in real time. The initialization population, the initial value of the iteration number and the population number are set. The fitness of the initial value is calculated, and it is judged whether the fitness meets the requirement. The adaptive crossover probability and the adaptive mutation probability of the individual are calculated, and the crossover and mutation are performed according to the adaptive genetic factor obtained by calculation. ； ； wherein is the adaptive crossover probability, is the adaptive mutation probability; is the number of individuals to iterate, is the adaptive genetic factor; The fitness function of the new individual obtained by recalculation is calculated until the individual with the best fitness value is selected, and finally the individual meeting the condition is output and decoded as the optimal solution.

9. A shore power automatic dispatching device for a hybrid energy power supply system based on an improved genetic algorithm, characterized in that, The electronic device includes a processor and a memory, and the memory stores computer instructions.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the program is executed by the processor to realize the steps of the shore power automatic dispatching method of the hybrid energy power supply system based on the improved genetic algorithm.

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