A wind-solar-hydrogen storage microgrid power optimization control method and experimental system

Abstract

The present invention discloses a wind-solar-hydrogen storage microgrid power optimization control method and experimental system. The wind-solar-hydrogen storage microgrid power optimization control method includes: S1, establishing a polymorphic integrator for a wind-solar-hydrogen storage microgrid consisting of six subsystems: a wind power generation system, a photovoltaic power generation system, a hydrogen production system, a hydrogen storage system, a fuel cell system, and an energy storage system; S2, establishing a multi-mode optimization solver to achieve economic optimal control of the wind-solar-hydrogen storage microgrid based on internal power balance; S3, establishing a wind-solar-hydrogen storage microgrid system multi-controller hardware-in-the-loop simulation experimental platform to achieve modeling of the wind-solar-hydrogen storage microgrid and verify the economic optimal control simulation of the polymorphic integrator and the multi-mode optimization solver. The present invention can improve the power balance control and economic optimal operation of the wind-solar-hydrogen storage microgrid through the synergistic effect of the polymorphic integrator and the multi-mode optimization solver, and enhance the stable operation level of the wind-solar-hydrogen storage microgrid.

Description

Technical Field

[0001] The present invention relates to the technical field of microgrids, and in particular to a wind-solar-hydrogen storage microgrid power optimization control method and an experimental system. Background Art

[0002] New energy hydrogen production technology represented by wind power generation and photovoltaic power generation has the advantages of being green, environmentally friendly, and flexible in layout, and has developed rapidly in recent years. After the produced hydrogen is stored, it is used to generate electricity through fuel cells, which can achieve efficient conversion of hydrogen energy in different time and space and effective transmission of electrical energy. Microgrids can be used as an efficient system for new energy power generation, hydrogen production, storage and utilization of hydrogen energy. However, how to achieve stable control of wind, solar, hydrogen storage microgrids, reduce costs on the basis of achieving power balance and thus achieve economic optimal control, and at the same time realize simulation analysis of wind, solar, hydrogen storage microgrids, has become an urgent problem to be solved. Summary of the invention

[0003] In order to overcome the deficiencies of the above technologies, the present invention provides a wind-solar-hydrogen-storage microgrid power optimization control method and a wind-solar-hydrogen-storage microgrid power optimization experimental system.

[0004] The technical solution adopted by the present invention to overcome the technical problems is:

[0005] A wind-solar-hydrogen-storage microgrid power optimization control method comprises the following steps:

[0006] S1. Establish a multi-state integrator for the wind-solar-hydrogen-storage microgrid consisting of six subsystems: wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system, and energy storage system;

[0007] S2. Establish a multi-mode optimization solver to achieve economic optimal control of the wind-solar-hydrogen storage microgrid based on internal power balance;

[0008] S3. Establish a multi-controller hardware-in-the-loop simulation experimental platform for wind-solar-hydrogen storage microgrid systems to realize the modeling of wind-solar-hydrogen storage microgrids and verify the economic optimal control simulation of multi-state integrators and multi-mode optimization solvers.

[0009] Furthermore, step S1 specifically includes:

[0010] For the wind-solar-hydrogen-storage microgrid composed of six subsystems: wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system, and energy storage system, a polymorphic integrator is established to integrate the power and economic information of the wind-solar-hydrogen-storage microgrid. The polymorphic fusion perception matrix of the wind-solar-hydrogen-storage microgrid is obtained through an iterative calculation method, in which the economic information includes cost and benefit.

[0011] Furthermore, step S2 specifically includes:

[0012] Based on the multi-state fusion perception matrix of the wind-solar-hydrogen-storage microgrid obtained in step S1, a multi-mode optimization solver is established to solve the power command values ​​with the best cost for the six subsystems of wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system and energy storage system respectively. Then, the six subsystems of wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system and energy storage system complete their respective power control, thereby realizing the economic optimal control of the six subsystems of wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system and energy storage system based on internal power balance.

[0013] Furthermore, the six subsystems of wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system and energy storage system complete their respective power control, which is specifically achieved in the following ways:

[0014] The wind power generation system, photovoltaic power generation system, hydrogen production system, fuel cell system, and energy storage system realize power control through the power outer loop and current inner loop of their respective grid-connected inverters;

[0015] The hydrogen storage system realizes the input and output control of hydrogen energy through the hydrogen storage system controller.

[0016] Furthermore, step S3 specifically includes:

[0017] A multi-controller hardware-in-the-loop simulation experimental platform for a wind-solar-hydrogen-storage microgrid system is established, which includes at least a virtual layer, a device layer, and an information interaction layer. Based on the cost-optimal power command values ​​of the six subsystems of the wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system, and energy storage system obtained by the multi-mode optimization solver in step S2, the economic optimal control simulation of the wind-solar-hydrogen-storage microgrid is completed.

[0018] Furthermore, the polymorphic integrator in step S1 is represented as follows:

[0019] (1)

[0020] (2)

[0021] (3)

[0022] (4)

[0023] (5)

[0024] (6)

[0025] (7)

[0026] (8)

[0027] Formula (1)-Formula (8): , , , , , Represent 6 sub-matrices respectively, Represents the output power of the wind power generation system; Represents the output power of the photovoltaic power generation system; Represents the input power of the hydrogen production system; Represents the energy stored in the hydrogen storage system; Represents the output power of the fuel cell system; Represents the power of the energy storage system; , , , , , They represent the revenues of wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system and energy storage system respectively; , , , , , They represent the costs of wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system, and energy storage system respectively; represents the polymorphic gain, which is a constant; Represents the intermediate calculation matrix; Stands for Polymorphic Integrator.

[0028] Furthermore, the multi-mode optimization solver in step S2 is expressed as follows:

[0029] (9)

[0030] In formula (9): A represents the multi-state gain matrix, A= [ a 1, a 2, a 3, a 4, a 5, a 6], a 1. a 2. a 3. a 4. a 5. a 6 representA The first to sixth elements of; B represents the difference gain matrix, B= [ b 1, b 2, b 3, b 4, b 5, b 6], b 1. b 2. b 3. b 4. b 5. b 6 represent B The first to sixth elements of; Represents the power command value matrix, which is the result of the multi-mode optimization solver.

[0031] Further, in step S3, the wind-solar-hydrogen-storage microgrid system multi-controller hardware-in-the-loop simulation experiment platform at least includes:

[0032] The virtual layer simulates the subsystem power circuit model of the wind-solar-hydrogen-storage microgrid composed of at least a wind power generation system, a photovoltaic power generation system, a hydrogen production system, a hydrogen storage system, a fuel cell system, and an energy storage system, and the overall power circuit model of the wind-solar-hydrogen-storage microgrid through a real-time simulation device to establish a hardware-in-the-loop controlled object;

[0033] The equipment layer includes six sampling control circuits for controlling the various subsystems that make up the wind-solar-hydrogen-storage microgrid, an energy management system for building a multi-controller hardware-in-the-loop simulation experimental platform for the wind-solar-hydrogen-storage microgrid system, and a real-time simulation device for simulation;

[0034] The information interaction layer combines the port communication protocol and DSP communication method of the real-time simulation device to establish an information interaction platform that links the virtual layer and the equipment layer components in the wind, solar, and hydrogen storage microgrid.

[0035] Furthermore, the real-time simulation device uses Typhoon HIL simulators, including Typhoon HIL 602 and Typhoon HIL 402, wherein Typhoon HIL 602 is used to simulate the power circuit part of the wind-solar-hydrogen storage microgrid, and Typhoon HIL 402 is used to simulate the energy management platform part of the wind-solar-hydrogen storage microgrid;

[0036] The sampling control circuit at least includes a main control module equipped with DSP28377, an analog quantity acquisition expansion module and an adapter board module, wherein the main control module includes a fan controller based on DSP28377, a photovoltaic controller based on DSP28377, a hydrogen production controller based on DSP28377, a hydrogen storage controller based on DSP28377, a fuel cell controller based on DSP28377, and an energy storage controller based on DSP28377; the analog quantity acquisition expansion module is used to connect to the DSP main control modules of the fan controller based on DSP28377, the photovoltaic controller based on DSP28377, the hydrogen production controller based on DSP28377, the hydrogen storage controller based on DSP28377, the fuel cell controller based on DSP28377, and the energy storage controller based on DSP28377 through several parallel interfaces, so as to realize connection with the Typhoon HIL simulator and monitor the process control analog quantity and collect signals of the whole process; the adapter board module is used to realize connection between boards and between devices;

[0037] The energy management system is a graphically editable energy management system, comprising at least a graphically editable energy management system controller;

[0038] The information interaction layer includes at least a communication circuit and a UI interface, wherein the communication circuit includes at least network communication, serial port communication, PWM control circuit, and AD sampling circuit; the UI interface includes at least a microgrid composition control main interface, a microgrid information monitoring interface, a main grid simulation operation status control interface, each unit operation information monitoring interface, and each module independent sub-interface.

[0039] The present invention also discloses a wind-solar-hydrogen-storage microgrid power optimization experimental system, which is used to implement the wind-solar-hydrogen-storage microgrid power optimization control method, including:

[0040] The polymorphic integration module is configured to establish a polymorphic integrator for a wind-solar-hydrogen-storage microgrid consisting of six subsystems: a wind power generation system, a photovoltaic power generation system, a hydrogen production system, a hydrogen storage system, a fuel cell system, and an energy storage system;

[0041] A multi-mode optimization solver module is configured to establish a multi-mode optimization solver for realizing economic optimal control of a wind-solar-hydrogen storage microgrid based on internal power balance;

[0042] The wind-solar-hydrogen-storage microgrid system multi-controller hardware-in-the-loop simulation experiment module is configured to establish a wind-solar-hydrogen-storage microgrid system multi-controller hardware-in-the-loop simulation experiment platform, which is used to realize the modeling of the wind-solar-hydrogen-storage microgrid and verify the economic optimal control simulation of the multi-state integrator and multi-mode optimization solver.

[0043] The beneficial effects of the present invention are:

[0044] The present invention creatively proposes a multi-state integrator and a multi-mode optimization solver for a wind-solar-hydrogen-storage microgrid consisting of six subsystems: a wind power generation system, a photovoltaic power generation system, a hydrogen production system, a hydrogen storage system, a fuel cell system, and an energy storage system. Through their synergistic effect, the power balance control and economically optimal operation of the wind-solar-hydrogen-storage microgrid can be improved, and the stable operation level of the wind-solar-hydrogen-storage microgrid can be enhanced.

[0045] By establishing a polymorphic integrator, accurate description of power information and cost-benefit information is achieved, laying the foundation for the calculation of power command values ​​of a wind-solar-hydrogen-storage microgrid composed of a wind power generation system, a photovoltaic power generation system, a hydrogen production system, a hydrogen storage system, a fuel cell system, and an energy storage system.

[0046] By establishing a multi-mode optimization solver, accurate calculation of the power command value of the wind-solar-hydrogen-storage microgrid composed of wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system and energy storage system is achieved.

[0047] By establishing a multi-controller hardware-in-the-loop simulation experimental platform for wind-solar-hydrogen-storage microgrid systems, a basis is provided for the verification of semi-physical simulation and control methods of wind-solar-hydrogen-storage microgrids composed of wind power generation systems, photovoltaic power generation systems, hydrogen production systems, hydrogen storage systems, fuel cell systems, and energy storage systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 This is a schematic diagram of the power optimization control method of the wind-solar-hydrogen storage microgrid described in an embodiment of the present invention.

[0049] Figure 2 This is a schematic diagram of the multi-controller hardware-in-the-loop simulation experiment platform for the wind-solar-hydrogen storage microgrid system described in an embodiment of the present invention. DETAILED DESCRIPTION

[0050] In order to facilitate those skilled in the art to better understand the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The following is only exemplary and does not limit the protection scope of the present invention.

[0051] The present invention discloses a wind-solar-hydrogen-storage microgrid power optimization control method, comprising the following steps:

[0052] S1. Establish a multi-state integrator for the wind-solar-hydrogen-storage microgrid consisting of six subsystems: wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system, and energy storage system;

[0053] S2. Establish a multi-mode optimization solver to achieve economic optimal control of the wind-solar-hydrogen storage microgrid based on internal power balance;

[0054] S3. Establish a multi-controller hardware-in-the-loop simulation experimental platform for wind-solar-hydrogen storage microgrid systems to realize the modeling of wind-solar-hydrogen storage microgrids and verify the economic optimal control simulation of multi-state integrators and multi-mode optimization solvers.

[0055] In order to better understand the above technical solution, the exemplary embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. These are only exemplary embodiments of the present invention. However, it should be understood that the present invention can also be implemented in various forms and is not limited to the embodiments described herein. These embodiments are intended to enable those skilled in the art to understand the present invention more clearly and thoroughly.

[0056] Example 1

[0057] like Figure 1 As shown, a wind-solar-hydrogen-storage microgrid power optimization control method described in this embodiment is aimed at a wind-solar-hydrogen-storage microgrid composed of six subsystems: a wind power generation system, a photovoltaic power generation system, a hydrogen production system, a hydrogen storage system, a fuel cell system, and an energy storage system. First, based on a polymorphic integrator, the power and economic information of the wind-solar-hydrogen-storage microgrid are efficiently integrated. Then, a multi-mode optimization solver is used to calculate the cost-optimal power command values ​​of the six subsystems: the wind power generation system, the photovoltaic power generation system, the hydrogen production system, the hydrogen storage system, the fuel cell system, and the energy storage system. Finally, a multi-controller hardware-in-the-loop simulation experimental platform for the wind-solar-hydrogen-storage microgrid system is established to realize the modeling of the wind-solar-hydrogen-storage microgrid and verify the economic optimal control simulation of the polymorphic integrator and the multi-mode optimization solver.

[0058] The specific steps are as follows:

[0059] S1. Establish a multi-state integrator for the wind-solar-hydrogen-storage microgrid consisting of six subsystems: wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system, and energy storage system.

[0060] Furthermore, step S1 specifically includes:

[0061] For the wind-solar-hydrogen-storage microgrid composed of six subsystems: wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system, and energy storage system, a polymorphic integrator is established to integrate the power and economic information of the wind-solar-hydrogen-storage microgrid. The polymorphic fusion perception matrix of the wind-solar-hydrogen-storage microgrid is obtained through an iterative calculation method, in which the economic information includes cost and benefit.

[0062] In this embodiment, the polymorphic integrator in step S1 is represented as follows:

[0063] (1)

[0064] (2)

[0065] (3)

[0066] (4)

[0067] (5)

[0068] (6)

[0069] (7)

[0070] (8)

[0071] Formula (1)-Formula (8): , , , , , Represent 6 sub-matrices respectively, Represents the output power of the wind power generation system; Represents the output power of the photovoltaic power generation system; Represents the input power of the hydrogen production system; Represents the energy stored in the hydrogen storage system; Represents the output power of the fuel cell system; Represents the power of the energy storage system; , , , , , They represent the revenues of wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system and energy storage system respectively; , , , , , They represent the costs of wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system, and energy storage system respectively; represents the polymorphic gain, which is a constant; Represents the intermediate calculation matrix; Stands for Polymorphic Integrator.

[0072] Some preferred main parameters of this embodiment are: =0.5 yuan / kWh, =0.5 yuan / kWh, =0.9 yuan / kWh, =0.93 yuan / kWh, =0.45 yuan / kWh, =0.61 yuan / kWh; =0.3 yuan / kWh, =0.32 yuan / kWh, =0.55 yuan / kWh, =0.72 yuan / kWh, =0.25 yuan / kWh, =0.3 yuan / kWh.

[0073] S2. Establish a multi-mode optimization solver to achieve economic optimal control of wind, solar, hydrogen and storage microgrids based on internal power balance.

[0074] Furthermore, step S2 specifically includes:

[0075] Based on the multi-state fusion perception matrix of the wind-solar-hydrogen-storage microgrid obtained in step S1, a multi-mode optimization solver is established to solve the power command values ​​with the best cost for the six subsystems of wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system and energy storage system respectively. Then, the six subsystems of wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system and energy storage system complete their respective power control, thereby realizing the economic optimal control of the six subsystems of wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system and energy storage system based on internal power balance.

[0076] In this embodiment, the multi-mode optimization solver in step S2 is represented as follows:

[0077] (9)

[0078] In formula (9): A represents the multi-state gain matrix, A= [ a 1, a 2, a 3, a 4, a 5, a 6], a 1. a 2. a 3. a 4. a 5. a 6 represent A The first to sixth elements of; B represents the difference gain matrix, B= [ b 1, b 2, b 3, b 4, b 5, b6], b 1. b 2. b 3. b 4. b 5. b 6 represent B The first to sixth elements of; Represents the power command value matrix, which is the result of the multi-mode optimization solver.

[0079] Some preferred main parameters of this embodiment are:

[0080] , .

[0081] in, A , B In t Represents time.

[0082] In this embodiment, the six subsystems of wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system and energy storage system complete their respective power control, which is specifically achieved in the following ways:

[0083] The wind power generation system, photovoltaic power generation system, hydrogen production system, fuel cell system, and energy storage system respectively realize power control through the power outer loop and current inner loop of their respective grid-connected inverters. This part is the existing technology and will not be described in detail here.

[0084] The hydrogen storage system realizes the input and output control of hydrogen energy through the hydrogen storage system controller. This part is the existing technology and will not be described in detail here.

[0085] S3. Establish a multi-controller hardware-in-the-loop simulation experimental platform for wind-solar-hydrogen storage microgrid systems to realize the modeling of wind-solar-hydrogen storage microgrids and verify the economic optimal control simulation of multi-state integrators and multi-mode optimization solvers.

[0086] Furthermore, if Figure 2 As shown, step S3 specifically includes:

[0087] A multi-controller hardware-in-the-loop simulation experimental platform for a wind-solar-hydrogen-storage microgrid system is established, which includes at least a virtual layer, a device layer, and an information interaction layer. Based on the cost-optimal power command values ​​of the six subsystems of the wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system, and energy storage system obtained by the multi-mode optimization solver in step S2, the economic optimal control simulation of the wind-solar-hydrogen-storage microgrid is completed.

[0088] Further, in step S3, the wind-solar-hydrogen-storage microgrid system multi-controller hardware-in-the-loop simulation experiment platform at least includes:

[0089] The virtual layer simulates the subsystem power circuit model of the wind-solar-hydrogen-storage microgrid composed of at least a wind power generation system, a photovoltaic power generation system, a hydrogen production system, a hydrogen storage system, a fuel cell system, and an energy storage system, and the overall power circuit model of the wind-solar-hydrogen-storage microgrid through a real-time simulation device to establish a hardware-in-the-loop controlled object;

[0090] The equipment layer includes six sampling control circuits for controlling the various subsystems that make up the wind-solar-hydrogen-storage microgrid, an energy management system for building a multi-controller hardware-in-the-loop simulation experimental platform for the wind-solar-hydrogen-storage microgrid system, and a real-time simulation device for simulation;

[0091] The information interaction layer combines the port communication protocol and DSP communication method of the real-time simulation device to establish an information interaction platform that links the virtual layer and the equipment layer components in the wind, solar, and hydrogen storage microgrid.

[0092] The overall functions of the multi-controller hardware-in-the-loop simulation experiment platform of the entire wind-solar-hydrogen storage microgrid system are completed through the virtual layer, device layer and information interaction layer.

[0093] In this embodiment, the real-time simulation device adopts a Typhoon HIL simulator, including Typhoon HIL 602 and Typhoon HIL 402, wherein Typhoon HIL 602 is used to simulate the power circuit part of the wind-solar-hydrogen storage microgrid, and Typhoon HIL 402 is used to simulate the energy management platform part of the wind-solar-hydrogen storage microgrid.

[0094] The sampling control circuit at least includes a main control module equipped with DSP28377, an analog quantity acquisition expansion module and an adapter board module, wherein the main control module includes a fan controller based on DSP28377, a photovoltaic controller based on DSP28377, a hydrogen production controller based on DSP28377, a hydrogen storage controller based on DSP28377, a fuel cell controller based on DSP28377, and an energy storage controller based on DSP28377; the analog quantity acquisition expansion module is used to connect to the DSP main control modules of the fan controller based on DSP28377, the photovoltaic controller based on DSP28377, the hydrogen production controller based on DSP28377, the hydrogen storage controller based on DSP28377, the fuel cell controller based on DSP28377, and the energy storage controller based on DSP28377 through several parallel interfaces, thereby realizing connection with the Typhoon HIL simulator and monitoring of process control analog quantities and signal acquisition of the entire process; the adapter board module is used to realize connection between boards and between devices.

[0095] The energy management system is a graphically editable energy management system, which at least includes a graphically editable energy management system controller, namely Figure 2The graphically editable EMS controller in , where EMS is the abbreviation for Energy Management System.

[0096] The information interaction layer includes at least a communication circuit and a UI interface, wherein the communication circuit includes at least network communication, serial communication, PWM control circuit, and AD sampling circuit, and the UI interface includes at least a microgrid composition control main interface, a microgrid information monitoring interface, a main network simulation operation status control interface, each unit operation information monitoring interface, and each module independent sub-interface. Specifically, in the microgrid composition control main interface, the user can select the required modules by checking, including wind power generation module, photovoltaic power generation module, hydrogen production module, hydrogen storage module, fuel cell module, and energy storage module, and adjust the wind, light, hydrogen storage microgrid system multi-controller hardware-in-the-loop simulation experiment platform for grid-connected operation or island operation. After the selection is successful, the system status light will light up. In addition, the real-time active power offset and reactive power offset curves can be seen, and the update speed is 500ms. In the microgrid information monitoring interface, users can monitor the active and reactive power emitted by the wind, light, hydrogen storage microgrid system multi-controller hardware-in-the-loop simulation experiment platform and the synchronous status of the platform, observe the active and reactive curves, and display the circuit breaker opening and closing status, bus power transmission status, grid voltage and frequency offset status, etc. through indicator lights. In the main grid simulation operation status control interface, users can choose to modify the main grid voltage and frequency per unit value according to the actual possible operation conditions, and simulate the condition of fault operation. At the same time, the interface is equipped with two instrument components, which allows users to intuitively and clearly see the fluctuations of system voltage and system frequency during operation. When each unit operation information monitoring interface is running, the most basic state quantities of each module, such as terminal voltage, active and reactive power, frequency, etc., will also be displayed again in the full-function sub-interface of each module, and displayed again to facilitate users to monitor their status. At the same time, for the load module, the size of its active and reactive power can also be easily adjusted. The independent sub-interfaces of each module include wind power generation interface, photovoltaic power generation interface, hydrogen production interface, hydrogen storage interface, fuel cell interface, and energy storage interface. Users can enter the sub-panel by clicking the corresponding button. Each panel contains all control quantities and monitorable quantities in the module.

[0097] Example 2

[0098] This embodiment discloses a wind-solar-hydrogen-storage microgrid power optimization experimental system, which is used to implement the wind-solar-hydrogen-storage microgrid power optimization control method described in Example 1, including:

[0099] The polymorphic integration module is configured to establish a polymorphic integrator for a wind-solar-hydrogen-storage microgrid consisting of six subsystems: a wind power generation system, a photovoltaic power generation system, a hydrogen production system, a hydrogen storage system, a fuel cell system, and an energy storage system;

[0100] A multi-mode optimization solver module is configured to establish a multi-mode optimization solver for realizing economic optimal control of a wind-solar-hydrogen storage microgrid based on internal power balance;

[0101] The wind-solar-hydrogen-storage microgrid system multi-controller hardware-in-the-loop simulation experiment module is configured to establish a wind-solar-hydrogen-storage microgrid system multi-controller hardware-in-the-loop simulation experiment platform, which is used to realize the modeling of the wind-solar-hydrogen-storage microgrid and verify the economic optimal control simulation of the multi-state integrator and multi-mode optimization solver.

[0102] The implementation process of the functions and effects of the above-mentioned multi-state integration module, multi-mode optimization solution module and wind-solar-hydrogen storage microgrid system multi-controller hardware-in-the-loop simulation experiment module is specifically described in Example 1 regarding the implementation process of the corresponding steps in the wind-solar-hydrogen storage microgrid power optimal control method, which will not be repeated here.

[0103] As for the implementation example of the wind-solar-hydrogen-storage microgrid power optimization experimental system, since it basically corresponds to the method implementation example, the relevant parts can be referred to the partial description of the method implementation example.

[0104] The above only describes the basic principles and preferred embodiments of the present invention. Those skilled in the art may make many changes and improvements based on the above description, and these changes and improvements should fall within the protection scope of the present invention.

Claims

1. A wind-solar-hydrogen-storage microgrid power optimization control method, characterized in that: The steps include: S1. For the wind-solar-hydrogen-storage microgrid consisting of six subsystems, namely, wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system and energy storage system, a multi-state integrator is established; the multi-state integrator is represented as follows: （1） （2） （3） （4） （5） （6） （7） （8） Formula (1)-Formula (8): , , , , , Represent 6 sub-matrices respectively, Represents the output power of the wind power generation system; Represents the output power of the photovoltaic power generation system; Represents the input power of the hydrogen production system; Represents the energy stored in the hydrogen storage system; Represents the output power of the fuel cell system; Represents the power of the energy storage system; , , , , , They represent the revenues of wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system and energy storage system respectively; , , , , , They represent the costs of wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system, and energy storage system respectively; represents the polymorphic gain, which is a constant; Represents the intermediate calculation matrix; stands for Polymorphic Integrator; S2. Establish a multi-mode optimization solver to achieve economic optimal control of the wind-solar-hydrogen storage microgrid based on internal power balance; S3. Establish a multi-controller hardware-in-the-loop simulation experimental platform for wind-solar-hydrogen storage microgrid systems to realize the modeling of wind-solar-hydrogen storage microgrids and verify the economic optimal control simulation of multi-state integrators and multi-mode optimization solvers.

2. The wind-solar-hydrogen-storage microgrid power optimization control method according to claim 1 is characterized in that: Step S1 specifically includes: For the wind-solar-hydrogen-storage microgrid composed of six subsystems: wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system, and energy storage system, a polymorphic integrator is established to integrate the power and economic information of the wind-solar-hydrogen-storage microgrid. The polymorphic fusion perception matrix of the wind-solar-hydrogen-storage microgrid is obtained through an iterative calculation method, in which the economic information includes cost and benefit.

3. The wind-solar-hydrogen-storage microgrid power optimization control method according to claim 2 is characterized in that: Step S2 specifically includes: Based on the multi-state fusion perception matrix of the wind-solar-hydrogen-storage microgrid obtained in step S1, a multi-mode optimization solver is established to solve the power command values ​​with the best cost for the six subsystems of wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system and energy storage system respectively. Then, the six subsystems of wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system and energy storage system complete their respective power control, thereby realizing the economic optimal control of the six subsystems of wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system and energy storage system based on internal power balance.

4. The wind-solar-hydrogen-storage microgrid power optimization control method according to claim 3 is characterized in that: The six subsystems of wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system and energy storage system complete their respective power control, which is specifically achieved through the following methods: The wind power generation system, photovoltaic power generation system, hydrogen production system, fuel cell system, and energy storage system realize power control through the power outer loop and current inner loop of their respective grid-connected inverters; The hydrogen storage system realizes the input and output control of hydrogen energy through the hydrogen storage system controller.

5. The wind-solar-hydrogen-storage microgrid power optimization control method according to claim 3 is characterized in that: Step S3 specifically includes: A multi-controller hardware-in-the-loop simulation experimental platform for a wind-solar-hydrogen-storage microgrid system is established, which includes at least a virtual layer, a device layer, and an information interaction layer. Based on the cost-optimal power command values ​​of the six subsystems of the wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system, and energy storage system obtained by the multi-mode optimization solver in step S2, the economic optimal control simulation of the wind-solar-hydrogen-storage microgrid is completed.

6. The wind-solar-hydrogen-storage microgrid power optimization control method according to claim 1 is characterized in that: The multi-mode optimization solver in step S2 is represented as follows: （9） In formula (9): A represents the multi-state gain matrix, A= [ a 1, a 2, a 3, a 4, a 5, a 6], a 1. a 2. a 3. a 4. a 5. a 6 represent A The first to sixth elements of; B represents the difference gain matrix, B= [ b 1, b 2, b 3, b 4, b 5, b 6], b 1. b 2. b 3. b 4. b 5. b 6 represent B The first to sixth elements of; Represents the power command value matrix, which is the result of the multi-mode optimization solver.

7. The power optimization control method for a wind-solar-hydrogen-storage microgrid according to any one of claims 1 to 6, characterized in that: In step S3, the wind-solar-hydrogen-storage microgrid system multi-controller hardware-in-the-loop simulation experiment platform at least includes: The virtual layer simulates the subsystem power circuit model of the wind-solar-hydrogen-storage microgrid composed of at least a wind power generation system, a photovoltaic power generation system, a hydrogen production system, a hydrogen storage system, a fuel cell system, and an energy storage system, and the overall power circuit model of the wind-solar-hydrogen-storage microgrid through a real-time simulation device to establish a hardware-in-the-loop controlled object; The equipment layer includes six sampling control circuits for controlling the various subsystems that make up the wind-solar-hydrogen-storage microgrid, an energy management system for building a multi-controller hardware-in-the-loop simulation experimental platform for the wind-solar-hydrogen-storage microgrid system, and a real-time simulation device for simulation; The information interaction layer combines the port communication protocol and DSP communication method of the real-time simulation device to establish an information interaction platform that links the virtual layer and the equipment layer components in the wind, solar, and hydrogen storage microgrid.

8. The wind-solar-hydrogen-storage microgrid power optimization control method according to claim 7 is characterized in that: The real-time simulation device uses Typhoon HIL simulators, including Typhoon HIL 602 and Typhoon HIL 402. Typhoon HIL 602 is used to simulate the power circuit part of the wind-solar-hydrogen storage microgrid, and Typhoon HIL 402 is used to simulate the energy management platform part of the wind-solar-hydrogen storage microgrid. The sampling control circuit at least includes a main control module equipped with DSP28377, an analog quantity acquisition expansion module and an adapter board module, wherein the main control module includes a fan controller based on DSP28377, a photovoltaic controller based on DSP28377, a hydrogen production controller based on DSP28377, a hydrogen storage controller based on DSP28377, a fuel cell controller based on DSP28377, and an energy storage controller based on DSP28377; the analog quantity acquisition expansion module is used to connect to the DSP main control modules of the fan controller based on DSP28377, the photovoltaic controller based on DSP28377, the hydrogen production controller based on DSP28377, the hydrogen storage controller based on DSP28377, the fuel cell controller based on DSP28377, and the energy storage controller based on DSP28377 through several parallel interfaces, so as to realize connection with the Typhoon HIL simulator and monitor the process control analog quantity and collect signals of the whole process; the adapter board module is used to realize connection between boards and between devices; The energy management system is a graphically editable energy management system, comprising at least a graphically editable energy management system controller; The information interaction layer includes at least a communication circuit and a UI interface, wherein the communication circuit includes at least network communication, serial port communication, PWM control circuit, and AD sampling circuit; the UI interface includes at least a microgrid composition control main interface, a microgrid information monitoring interface, a main grid simulation operation status control interface, each unit operation information monitoring interface, and each module independent sub-interface.

9. A wind-solar-hydrogen-storage microgrid power optimization experimental system, used to implement the wind-solar-hydrogen-storage microgrid power optimization control method according to any one of claims 1 to 8, characterized in that: include: The polymorphic integration module is configured to establish a polymorphic integrator for a wind-solar-hydrogen-storage microgrid consisting of six subsystems: a wind power generation system, a photovoltaic power generation system, a hydrogen production system, a hydrogen storage system, a fuel cell system, and an energy storage system. The polymorphic integrator is represented as follows: （1） （2） （3） （4） （5） （6） （7） （8） Formula (1)-Formula (8): , , , , , Represent 6 sub-matrices respectively, Represents the output power of the wind power generation system; Represents the output power of the photovoltaic power generation system; Represents the input power of the hydrogen production system; Represents the energy stored in the hydrogen storage system; Represents the output power of the fuel cell system; Represents the power of the energy storage system; , , , , , They represent the revenues of wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system and energy storage system respectively; , , , , , They represent the costs of wind power generation system, photovoltaic power generation system, hydrogen production system, hydrogen storage system, fuel cell system, and energy storage system respectively; represents the polymorphic gain, which is a constant; Represents the intermediate calculation matrix; stands for Polymorphic Integrator; A multi-mode optimization solver module is configured to establish a multi-mode optimization solver for realizing economic optimal control of a wind-solar-hydrogen storage microgrid based on internal power balance; The wind-solar-hydrogen-storage microgrid system multi-controller hardware-in-the-loop simulation experiment module is configured to establish a wind-solar-hydrogen-storage microgrid system multi-controller hardware-in-the-loop simulation experiment platform, which is used to realize the modeling of the wind-solar-hydrogen-storage microgrid and verify the economic optimal control simulation of the multi-state integrator and multi-mode optimization solver.

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