Offshore island micro-grid optimal scheduling method and device considering frequency constraint

Abstract

The invention provides an offshore island micro-grid optimal scheduling method and device considering frequency constraint, and the method comprises the steps: obtaining the operation parameters of an offshore island micro-grid, the operation parameters comprise the load condition, topological structure, equipment physical parameters and sea area wind speed of the micro-grid, and constructing an operation model of the micro-grid based on the operation parameters; constructing a frequency response model, wherein the frequency response model reflects the frequency response of the micro-grid in the transient fault event occurrence process; determining constraint conditions of the micro-grid based on the operation parameters and a frequency response model; and solving a target optimization function based on the operation model and the constraint condition to obtain an optimal scheduling scheme of the micro-grid, the optimization target of the target optimization function being to make the operation cost of the micro-grid lowest, and the optimal scheduling scheme including the operation state of the equipment in the micro-grid in each scheduling period. According to the invention, reliable optimization scheduling can be carried out on the micro-grid when a transient fault event occurs in the micro-grid.

Description

Technical Field

[0001] The present invention relates to the field of microgrids, and in particular to a method and device for optimizing and dispatching an offshore island microgrid taking frequency constraints into account. Background Art

[0002] An offshore island microgrid is a small power system designed for islands, offshore platforms, or remote waters far from the mainland. It is typically composed of distributed power sources, energy storage devices, loads, control systems, and other equipment and devices, and has the ability to operate independently and self-consistently. Connecting offshore island microgrids to renewable energy is an important means of addressing system energy needs and promoting low-carbon operation. Among offshore renewable energy sources, wind energy has attracted widespread attention due to its abundant resources, relatively mature technology, and high degree of location overlap with offshore island microgrids. In complex offshore environments, failures in wind power generation equipment and submarine cables can cause wind turbines to disconnect from the grid, increasing the probability of transient failures and posing a significant challenge to the frequency security mechanism in the optimized scheduling of small-capacity, low-inertia offshore island microgrids.

[0003] However, in the prior art, only the normal operation situation is often considered during the scheduling of offshore island microgrids, and the frequency safety optimization scheduling method when transient faults occur during the scheduling of offshore island microgrids is not considered. Summary of the Invention

[0004] The present invention provides an optimized scheduling method and device for an offshore island microgrid taking frequency constraints into account, so as to overcome the defect of the optimized scheduling method in the prior art that does not take into account the frequency safety when transient faults occur during the scheduling of the offshore island microgrid, realize the consideration of frequency safety when transient faults occur during the scheduling of the offshore island microgrid, and ensure the reliability of the optimized scheduling of the offshore island microgrid.

[0005] The present invention provides an optimized scheduling method for an offshore island microgrid taking frequency constraints into account, the method comprising: Acquiring operating parameters of an offshore island microgrid, the operating parameters including a load condition, topology, physical parameters of equipment, and wind speed in the sea area of the microgrid, and constructing an operating model of the microgrid based on the operating parameters, the operating model reflecting the relationship between the physical parameters of various equipment in the microgrid during operation; Constructing a frequency response model, wherein the frequency response model reflects the frequency response of the microgrid during a transient fault event; determining a constraint condition of the microgrid based on the operating parameters and the frequency response model, wherein the constraint condition reflects a limitation of equipment operation of the microgrid; Based on the operation model and the constraint conditions, the target optimization function is solved to obtain an optimized scheduling plan for the microgrid. The optimization goal of the target optimization function is to minimize the operation cost of the microgrid. The optimized scheduling plan includes the operating status of the equipment in the microgrid during each scheduling period.

[0006] According to an optimized scheduling method for an offshore island microgrid taking frequency constraints into account, the operation model includes a power flow model, which reflects the network power distribution and node voltage levels during the operation of the microgrid; the power flow model is: ; in, t represents the optimized scheduling period; Ω B and Ω N Represent the collection of branches and nodes in the network respectively; U j ( t ) represents a node j In the period t The voltage amplitude; z ij 、 I ij ( t )and S ij ( t ) represent branches ( i , j ) between the impedance, in the period t The current and complex power flow; express I ij ( t )'s conjugation; S j ( t ) represents a node j In the period t The injected complex power; Ω gt ,Ω wt ,Ω ess and Ω load Respectively represent the collection of turbine generators, wind turbines, energy storage equipment and loads, g 、 w 、 e and l Represent the set Ω gt ,Ω wt ,Ω ess and Ω load The equipment in S g,j ( t ), S w,j (t ), S e,j ( t )and S l,j ( t ) represent nodes respectively j The complex operating power of turbine generators, wind turbines, energy storage equipment and loads.

[0007] According to a method for optimizing and dispatching an offshore island microgrid taking frequency constraints into account, the present invention provides a method for optimizing and dispatching an offshore island microgrid taking frequency constraints into account, wherein the constraints include energy storage device operation constraints, the energy storage device operation constraints include energy type energy storage device constraints, and the energy type energy storage device constraints include: ; ; ; ; ; ; ; ; ; ; ; in, and Energy storage devices Rated energy and rated power; and Energy storage devices In the period t 0 / 1 variables for internal charge and discharge states, and Energy storage eE In the period t The charging and discharging power within Energy storage device In the period t Reactive power; and They are Upper and lower limits of ; and Energy storage devices The maximum and minimum state of charge limits, and Represent energy storage devices The energy at the beginning and end of the period, Energy storage device In the time period t The transient frequency response reserve, Energy storage device In the period t Power, Energy storage device The frequency response limiting coefficient, The time required for a stationary standby turbine generator to reach target power from the start of a transient fault event.

[0008] According to an offshore island microgrid optimization scheduling method taking frequency constraints into account provided by the present invention, the energy storage device operation constraint conditions also include power type energy storage device constraint conditions, and the power type energy storage device constraint conditions include: ; ; in, Indicates power type energy storage device During the scheduling period t Frequency response reserve within and Power type energy storage devices Rated power and rated energy; Power-type energy storage equipment The frequency response limiting coefficient of Power-type energy storage equipment Maintaining state of charge, It is the time for the power type energy storage device to exit the frequency response.

[0009] According to an offshore island microgrid optimization scheduling method taking frequency constraints into account, the frequency response model includes a rotating standby gas turbine generator, a power type energy storage device, an energy type energy storage device and a load in the microgrid. τ The frequency response power at time , where , τ = 0 indicates the moment when the transient fault event starts, The time required for a stationary standby turbine generator to reach target power from the start of a transient fault event; The frequency response model is: ; ; ; ; in, 、 、 and They are the frequency response reserves of rotating standby gas turbine generator, power type energy storage equipment, energy type energy storage equipment and load, 、 and are the frequency response delay times of energy storage equipment, load and spinning standby turbine generator, 、 and are the frequency complete response times of power type energy storage equipment, energy type energy storage equipment and rotating standby turbine generator, It is the time for the power type energy storage device to exit the frequency response.

[0010] According to an offshore island microgrid optimization scheduling method taking frequency constraints into account, the constraints provided by the present invention include frequency constraints, and the frequency constraints include frequency change rate constraints, frequency quasi-steady-state constraints, and frequency maximum deviation constraints.

[0011] The present invention also provides an offshore island microgrid optimization scheduling device taking frequency constraints into account, the device comprising: A first model building module is configured to obtain operating parameters of the offshore island microgrid, wherein the operating parameters include the load condition, topology, physical parameters of the equipment, and wind speed in the sea area of the microgrid, and to build an operating model of the microgrid based on the operating parameters, wherein the operating model reflects the relationship between the physical parameters of each equipment in the microgrid during operation; A second model building module is used to build a frequency response model, wherein the frequency response model reflects the frequency response of the microgrid during a transient fault event; a constraint condition building module, configured to determine the constraint conditions of the microgrid based on the operating parameters and the frequency response model, wherein the constraint conditions reflect the limitations of the equipment in the microgrid during operation; An optimization module is configured to solve a target optimization function based on the operation model and the constraints to obtain an optimized scheduling plan for the microgrid, wherein the optimization goal of the target optimization function is to minimize the operation cost of the microgrid, and the optimized scheduling plan includes the operating status of the equipment in the microgrid during each scheduling period.

[0012] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for optimizing and scheduling an offshore island microgrid taking frequency constraints into account is implemented as described in any one of the above.

[0013] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for optimizing and dispatching an offshore island microgrid taking frequency constraints into account is implemented as described in any one of the above.

[0014] The present invention also provides a computer program product, comprising a computer program, which, when executed by a processor, implements any of the above-described methods for optimizing and scheduling an offshore island microgrid taking frequency constraints into account.

[0015] The present invention provides an offshore island microgrid optimization scheduling method and device taking frequency constraints into account. By acquiring the operating parameters of the offshore island microgrid, an operating model is constructed that reflects the relationship between the physical parameters of each device in the microgrid during operation, and a frequency response model is constructed that reflects the microgrid during the occurrence of a transient fault event. The constraints of the microgrid are determined based on the operating parameters and the frequency response model. The target optimization function is solved based on the operating model and the constraints to obtain an optimized scheduling scheme for the microgrid. The optimization goal of the target optimization function is to minimize the operating cost of the microgrid. This ensures that the microgrid can be reliably optimized and scheduled even when a transient fault event occurs in the microgrid, thereby ensuring the frequency safety and economy of the microgrid. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 It is a flow chart of the method for optimizing the scheduling of an offshore island microgrid taking frequency constraints into account provided by the present invention.

[0018] Figure 2 This is a schematic diagram of the offshore island microgrid structure.

[0019] Figure 3 This is a schematic diagram of the frequency response strategy and frequency fluctuation after a transient fault in the offshore island microgrid optimization scheduling method taking frequency constraints into account provided by the present invention.

[0020] Figure 4 This is a microgrid system structure diagram of an experimental example of the offshore island microgrid optimization scheduling method taking frequency constraints into account provided by the present invention.

[0021] Figure 5 This is a comparison chart of experimental results of the offshore island microgrid optimization scheduling method taking frequency constraints into account provided by the present invention.

[0022] Figure 6 It is a structural schematic diagram of the offshore island microgrid optimization scheduling device taking frequency constraints into account provided by the present invention.

[0023] Figure 7 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0024] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0025] The following combination Figure 1-5 The present invention describes the method for optimizing the scheduling of an offshore island microgrid taking frequency constraints into account. Figure 1 As shown, the method for optimizing and dispatching an offshore island microgrid taking frequency constraints into account provided by the present invention includes the following steps: S110, obtaining operating parameters of the offshore island microgrid, the operating parameters including the load condition, topology, physical parameters of the equipment, and wind speed in the sea area of the microgrid, and constructing an operating model of the microgrid based on the operating parameters, the operating model reflecting the relationship between the physical parameters of each equipment in the microgrid during operation; S120, constructing a frequency response model, where the frequency response model reflects the frequency response of the microgrid during a transient fault event; S130, determining constraints of the microgrid based on the operating parameters and the frequency response model, where the constraints reflect limitations of equipment in the microgrid during operation; S140. Solve the target optimization function based on the operation model and the constraints to obtain an optimized scheduling plan for the microgrid. The optimization goal of the target optimization function is to minimize the operation cost of the microgrid. The optimized scheduling plan includes the operating status of the equipment in the microgrid during each scheduling period.

[0026] An offshore island microgrid is a small power system designed for islands far from the mainland, offshore platforms or remote sea areas. It is usually composed of distributed power sources, energy storage devices, loads, control systems and other equipment. Figure 2 As shown, the island microgrid may include energy storage devices, which can be divided into power-type energy storage devices (such as supercapacitors) and energy-type energy storage devices (such as lithium-ion batteries).

[0027] Based on the operating parameters of the offshore island microgrid, the microgrid operation model, frequency response model and constraint conditions are constructed. Furthermore, cost parameters can be collected to construct the target optimization function, such as parameters such as energy storage, gas, carbon water, and equipment operation and maintenance prices.

[0028] The operational model of an offshore island microgrid reflects the relationship between the physical parameters of each device in the microgrid. The operational model is described in detail below.

[0029] The operation model includes a power flow model. The network power flow reflects the network power distribution and node voltage levels during the operation of the offshore island microgrid. It is used to support the optimal scheduling and energy management of source-storage-load devices. The power flow model is shown below: (1) Where: t represents the optimized scheduling period; Ω B and Ω N Represent the collection of branches and nodes in the network respectively; U j ( t ) represents a node j In the period t The voltage amplitude; z ij 、 I ij ( t )and S ij ( t ) represent branches ( i , j ) between the impedance, in the period t The current and complex power flow; express I ij ( t )'s conjugation; S j ( t ) represents a node j In the period t The injected complex power; Ω gt ,Ω wt ,Ω ess and Ω load Represent the collection of turbine generator, wind turbine generator, energy storage and load respectively, g 、 w 、 e and l Represent the set Ω gt ,Ω wt ,Ω ess and Ω load The equipment in Sg,j ( t ), S w,j ( t ), S e,j ( t )and S l,j ( t ) represent nodes respectively j The complex operating power of turbine generators, wind turbines, energy storage and loads.

[0030] The operation model also includes an energy storage model. The energy storage model reflects the relationship between the physical parameters of the energy storage device. Specifically, in the energy storage model, the charging and discharging process of the energy storage device when participating in the optimization scheduling is modeled as follows: (2) Where: ,in It is a collection of energy-type energy storage; Energy storage device eE In the period t stored energy; and Energy storage devices eE In the period t Charging and discharging power within; Optimize the duration of the scheduling period for the system; 、 and Energy storage devices eE Self-consumption rate, charging efficiency and discharging efficiency.

[0031] In the energy storage model, the equivalent virtual inertia of the energy storage system is an adjustable quantity, as shown below: (3) Where: For energy storage e The equivalent virtual inertia of For energy storage e The equivalent virtual inertia time constant of ; For energy storage e Rated power; for The upper limit of the value.

[0032] The operation model also includes a wind turbine model, which includes the output power of the wind turbine in the maximum power point tracking mode. Wind speed at current time The relationship between them is as follows: (4) Where: 、 and are the cut-in wind speed, rated wind speed and cut-out wind speed of the wind turbine respectively; Indicates wind turbine w Rated power.

[0033] The operation model also includes a gas turbine generator model, and the fuel consumption characteristics of the gas turbine generator are included in the gas turbine generator model as shown below: (5) Where: Indicates the gas turbine generator in the time period t fuel consumption, and Based on turbine generator g Power-fuel consumption constant obtained by fitting experimental data; For turbine generators g Rated power; Turbine generator g In the period t Power, To characterize the turbine generator g 0 / 1 variable for start / stop status, a value of 1 indicates a turbine generator g In the starting state, a value of 0 indicates a turbine generator g In closed state.

[0034] The gas turbine generator model also includes the relationship between the turbine generator inertia and the rotor kinetic energy, which is expressed as follows: (6) (7) Where: and Turbine generator g Inertia and inertia time constant; For turbine generators g The rotor moment of inertia; For turbine generators g Rated apparent power; is the system synchronization angular velocity.

[0035] Considering that the carbon glaze deposition caused by the low load rate operation of the turbine generator will shorten the operation and maintenance cycle, the method provided by the present invention uses formula (8) to calculate the equivalent operating hours of the turbine generator , to reflect the impact of different operating conditions on the operation and maintenance costs of turbine generators.

[0036] (8) Where: For turbine generators g Number of starts; 、 and Turbine generator g operating hours at low, medium, and high load rates; 、 、 and are the corresponding weight coefficients respectively.

[0037] In the method provided by the present invention, a frequency response model reflecting the microgrid during a transient fault event is constructed. The frequency response model includes a rotating standby gas turbine generator, a power type energy storage device, an energy type energy storage device and a load in the microgrid. τ The frequency response power at time , where , τ = 0 indicates the moment when the transient fault event starts, The time required for a stationary standby turbine generator to reach target power from the start of a transient fault event.

[0038] Specifically, in the method provided by the present invention, the source-storage-load coordinated frequency response strategy, i.e., the frequency fluctuation schematic diagram is as follows: Figure 3 As shown, to avoid and optimize the scheduling period t Obfuscation, using symbols τ To represent the time during the frequency response process.

[0039] In the figure, τ = 0 indicates the moment when the transient fault event starts, 、 、 and They are rotating standby gas turbine generator, power-type energy storage, energy-type energy storage and load frequency response reserve. 、 and They are the frequency response delay times of energy storage, load and spinning standby turbine generator, which means the time required for each device to start power regulation from the occurrence of a transient fault event. 、 and They are the frequency full response time of power-type energy storage, energy-type energy storage and rotating standby turbine generator, which means the time required for each device to start power adjustment to reach the frequency response target power. The time it takes for power-type energy storage to exit frequency response. In offshore island microgrids, the capacity of static standby turbine generators is generally sufficient. The time required for a stationary standby turbine generator to reach target power from the start of a transient fault event.

[0040] Offshore island microgrid Total frequency response power within the time period It can be expressed as: (9) Where: 、 、 and They represent the rotating standby gas turbine generator, power type energy storage, energy type energy storage and load in the system. τ The frequency response power at the moment. Figure 3 The frequency response strategy shown can be used to obtain the expressions of various frequency response powers as follows: (10) (11) (12) (13) Frequency response target power in offshore island microgrid source-storage-load system 、 、 and It is obtained by aggregating single devices, so the expressions of the above frequency response target power are as follows: (14) Where: 、 、 and They represent the collection of gas turbine generator, power type energy storage, energy type energy storage and load respectively; g 、 eP 、 eE and l The devices in the corresponding collection respectively; 、 、 and Respectively represent devices g 、 eP 、 eE and l The frequency response of the target power.

[0041] Based on the above strategy, the power disturbance can be derived from the rotor motion equation: The frequency constraints under the system include frequency change rate constraints, frequency quasi-steady-state constraints, and frequency maximum deviation constraints. The system frequency change rate constraints are as follows: (15) Where: is the initial frequency change rate under transient fault events; for The maximum allowed value of is the total inertia of the system; is the nominal frequency of the system.

[0042] The quasi-steady-state constraints of the system frequency are as follows: (16) The maximum deviation constraint of the system frequency is as follows: (17) (18) Where: ||x||2 represents the two-norm of x; H gt 、 H Eess 、 H Pess They are the inertia of gas turbine generator, energy type energy storage, and power type energy storage respectively; is the maximum tolerance of system frequency deviation; 、 、 、 、 and To simplify the coefficients, the values of the coefficients are as follows: .

[0043] In the method provided by the present invention, the optimization objective function is to minimize the cost of optimizing the scheduling of the offshore island microgrid, as shown below: (20) Where: Optimizing dispatch costs for offshore island microgrids; and are annual gas costs and carbon tax costs, respectively; and are the annual operation and maintenance costs of energy storage and turbine generator respectively.

[0044] The expressions of various costs in formula (20) are shown in formulas (21)-(24).

[0045] (twenty one) (twenty two) (twenty three) (twenty four) Where: To optimize the number of scheduling periods; is the unit gas consumption cost; For turbine generators g In the period t Gas consumption rate within Optimize the duration of the scheduling period for the system; is the unit carbon emission cost; The conversion rate of carbon emissions to gas; is the operation and maintenance cost of the turbine generator per unit power; is the collection of stored energy, and ; and Energy storage e In the period t Charging power and discharging power; It is the operation and maintenance cost of energy storage under unit charging and discharging power.

[0046] In order to ensure that the results obtained during the optimization solution are feasible, the method provided by the present invention also constructs the constraints of the equipment operation. The constraints of the equipment operation are explained one by one below.

[0047] 1) System network trends In the power flow model, the branch power flow needs to be , branch current and node voltage Make the constraints as follows: (25) Where: and Respectively Upper and lower limits of ; and Respectively Upper and lower limits of ; and Respectively upper and lower limits.

[0048] Note that constraint (25) is a non-convex constraint, which can be transformed into a convex constraint by relaxation, and the result is as follows: (26) (27) (28) Where: , , are auxiliary variables introduced; and Represents nodes respectively j In the period t Active and reactive injection power; and Respectively represent branches ( i , j ) during the period t Active power flow and reactive power flow; and Respectively represent branches ( i , j ) between the resistance and reactance.

[0049] 2) Energy storage Energy storage during the period t Charging power and discharge power The following constraints need to be met: (29) (30) (31) Where: Energy storage eE Rated power; and Energy storage eE In the period t 0 / 1 variables for internal charge and discharge states.

[0050] During the energy storage operation, the reactive power boundary constraint (32), the complex power boundary constraints (33) and (34), and the energy storage boundary constraint (35) should also be satisfied, as shown below: (32) (33) (34) (35) Where: Energy storage eE In the period t Reactive power; and They are Upper and lower limits of ; and Energy storage eEThe maximum and minimum state of charge limits are set.

[0051] Energy storage needs to complete a charge and discharge cycle in each scheduling cycle, so that the energy at the initial and final states is and To achieve equilibrium, the constraints are as follows: (36) Energy storage transient frequency response reserve The following constraints need to be met: (37) (38) (39) Where: Energy storage eE The frequency response limiting factor.

[0052] Power storage during the dispatch period t Frequency response reserve within The following constraints should be met: (40) (41) Where: and Power type energy storage eP Rated power and rated energy; Power-type energy storage eP The frequency response limiting coefficient of Power-type energy storage eP Maintaining state of charge.

[0053] 3) Wind turbines Active power output of wind turbine and reactive power The following constraints should be met: (42) (43) Where: and Wind turbines w The leading power factor and lagging power factor boundaries.

[0054] 4) Gas turbine generator The operating power of the gas turbine generator should meet the following constraints: (44) (45) (46) (47) Where: and Turbine generator g The upper and lower limits of active power in the startup state; and Turbine generator g Upper and lower limits of reactive power in the startup state; For turbine generators g Rated apparent power; and Turbine generator g Rate limits for ramping up and ramping down.

[0055] Turbine generator in period t Transient frequency response reserve It is also limited by steady-state operating power and frequency response limitations as shown below: (48) (49) Where: is the rated power of the turbine generator g; For turbine generators g The speed regulator frequency response limiting coefficient.

[0056] 5) Load Load in period t Frequency response reserve The following constraints must be met: (50) Where: for This paper takes it as the upper limit of the system load shedding capacity.

[0057] 6) Frequency constraints under wind turbine off-grid transient faults Based on the proposed source-storage-load frequency response strategy of the offshore island microgrid, the system frequency constraints under wind turbine off-grid failure are derived. The frequency change rate should meet the following constraints: (51) Based on the constraints and the operating model, the target optimization function is solved, which can be expressed as: (52) From the above analysis, it can be seen that the optimization model shown in formula (52) is a mixed integer quadratic convex programming problem, which can be solved by interior point method, heuristic algorithm, commercial solver and other methods.

[0058] In order to verify the effectiveness of the method provided by the present invention, a certain offshore island microgrid is used as a research object for verification. The system structure and equipment parameters of the research object are as follows: Figure 4 As shown in Figure 2, the maximum load shedding capacity is 2MW. The optimized dispatching cost of the above microgrid under the existing method and the method provided by the present invention is as follows: Figure 5 The wind curtailment rate and average expected load rejection are shown in Table 1.

[0059] Table 1

[0060] These results demonstrate that, compared to existing methods, the proposed method reduces optimized dispatch operating costs by 3.47%, wind curtailment by 5.45%, and average expected load rejection by 31.6%. Therefore, the proposed method outperforms existing methods in terms of economic efficiency, wind power absorption, and frequency security.

[0061] The following describes the offshore island microgrid optimization scheduling device taking into account frequency constraints provided by the present invention. The offshore island microgrid optimization scheduling device taking into account frequency constraints described below and the offshore island microgrid optimization scheduling method taking into account frequency constraints described above can be referred to each other. Figure 6 As shown, the frequency-constrained offshore island microgrid optimization and scheduling device provided by the present invention includes the following modules: A first model building module 610 is configured to obtain operating parameters of the offshore island microgrid, including the microgrid's load status, topology, physical parameters of the equipment, and wind speed in the sea area, and to build an operating model of the microgrid based on the operating parameters. The operating model reflects the relationship between the physical parameters of each device in the microgrid during operation. A second model building module 620 is used to build a frequency response model, which reflects the frequency response of the microgrid during the transient fault event; A constraint condition building module 630 is used to determine the constraint conditions of the microgrid based on the operating parameters and the frequency response model, where the constraint conditions reflect the limitations of the equipment in the microgrid during operation; The optimization module 640 is used to solve the target optimization function based on the operation model and the constraints to obtain the optimal scheduling plan for the microgrid. The optimization goal of the target optimization function is to minimize the operating cost of the microgrid. The optimal scheduling plan includes the operating status of the equipment in the microgrid during each scheduling period.

[0062] Figure 7An example of a physical structure diagram of an electronic device is shown below. Figure 7 As shown, the electronic device may include: a processor (processor) 710 , a communication interface (Communications Interface) 720 , a memory (memory) 730 and a communication bus 740 , wherein the processor 710 , the communication interface 720 and the memory 730 communicate with each other via the communication bus 740 . The processor 710 can call the logic instructions in the memory 730 to execute the offshore island microgrid optimization scheduling method taking into account frequency constraints, the method including: obtaining the operating parameters of the offshore island microgrid, the operating parameters including the load condition, topology, equipment physical parameters and sea wind speed of the microgrid, constructing an operation model of the microgrid based on the operating parameters, the operation model reflecting the relationship between the physical parameters of each device in the microgrid during operation; constructing a frequency response model, the frequency response model reflecting the frequency response of the microgrid during a transient fault event; determining the constraints of the microgrid based on the operating parameters and the frequency response model, the constraints reflecting the limitations of the equipment in the microgrid during operation; solving the target optimization function based on the operation model and the constraints to obtain an optimized scheduling plan for the microgrid, the optimization goal of the target optimization function is to minimize the operating cost of the microgrid, and the optimized scheduling plan includes the operating status of the equipment in the microgrid during each scheduling period.

[0063] Furthermore, the logic instructions in the aforementioned memory 730 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product, stored in a storage medium, includes instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0064] On the other hand, the present invention also provides a computer program product, which includes a computer program, which can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the offshore island microgrid optimization scheduling method taking into account frequency constraints provided by the above methods. The method includes: obtaining operating parameters of the offshore island microgrid, the operating parameters including the load condition, topology, equipment physical parameters and sea wind speed of the microgrid, constructing an operating model of the microgrid based on the operating parameters, and the operating model reflects the relationship between the physical parameters of each device in the microgrid during operation; constructing a frequency response model, and the frequency response model reflects the frequency response of the microgrid during a transient fault event; determining the constraints of the microgrid based on the operating parameters and the frequency response model, and the constraints reflect the limitations of the equipment in the microgrid during operation; solving the target optimization function based on the operating model and the constraints to obtain an optimized scheduling plan for the microgrid, and the optimization goal of the target optimization function is to minimize the operating cost of the microgrid. The optimized scheduling plan includes the operating status of the equipment in the microgrid during each scheduling period.

[0065] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the offshore island microgrid optimization scheduling method taking into account frequency constraints provided by the above-mentioned methods, the method comprising: obtaining operating parameters of the offshore island microgrid, the operating parameters including the load condition, topology, equipment physical parameters and sea wind speed of the microgrid, constructing an operating model of the microgrid based on the operating parameters, the operating model reflecting the relationship between the physical parameters of each device in the microgrid during operation; constructing a frequency response model, the frequency response model reflecting the frequency response of the microgrid during a transient fault event; determining the constraints of the microgrid based on the operating parameters and the frequency response model, the constraints reflecting the limitations of the equipment in the microgrid during operation; solving the target optimization function based on the operating model and the constraints to obtain an optimized scheduling scheme for the microgrid, the optimization goal of the target optimization function is to minimize the operating cost of the microgrid, and the optimized scheduling scheme includes the operating status of the equipment in the microgrid during each scheduling period.

[0066] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0067] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0068] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for optimizing the scheduling of an offshore island microgrid taking frequency constraints into account, characterized in that: The method comprises: Acquiring operating parameters of an offshore island microgrid, the operating parameters including a load condition, topology, physical parameters of equipment, and wind speed in the sea area of the microgrid, and constructing an operating model of the microgrid based on the operating parameters, the operating model reflecting the relationship between the physical parameters of various equipment in the microgrid during operation; Constructing a frequency response model, wherein the frequency response model reflects the frequency response of the microgrid during a transient fault event; determining a constraint condition of the microgrid based on the operating parameters and the frequency response model, wherein the constraint condition reflects a limitation of equipment operation of the microgrid; Based on the operation model and the constraint conditions, the target optimization function is solved to obtain an optimized scheduling plan for the microgrid. The optimization goal of the target optimization function is to minimize the operation cost of the microgrid. The optimized scheduling plan includes the operating status of the equipment in the microgrid during each scheduling period.

2. The method for optimizing and dispatching an offshore island microgrid taking frequency constraints into account according to claim 1, characterized in that: The operation model includes a power flow model, which reflects the network power distribution and node voltage level when the microgrid is running; the power flow model is: ； in, t represents the optimized scheduling period; Ω B and Ω N Represent the collection of branches and nodes in the network respectively; U j ( t ) represents a node j In the period t The voltage amplitude; z ij 、 I ij ( t )and S ij ( t ) represent branches ( i , j ) between the impedance, in the period t The current and complex power flow; express I ij ( t )'s conjugation; S j ( t ) represents a node j In the period t The injected complex power; Ω gt ,Ω wt ,Ω ess and Ω load Respectively represent the collection of turbine generators, wind turbines, energy storage equipment and loads, g 、 w 、 e and l Represent the set Ω gt ,Ω wt ,Ω ess and Ω load The equipment in S g,j ( t ), S w,j ( t ), S e,j ( t )and S l,j ( t ) represent nodes respectively j The complex operating power of turbine generators, wind turbines, energy storage equipment and loads.

3. The method for optimizing and dispatching an offshore island microgrid taking frequency constraints into account according to claim 1, characterized in that: The constraints include energy storage device operation constraints, which include energy storage device constraints. The energy storage device operation constraints include energy storage device constraints, which include: ； ； ； ； ； ； ； ； ； ； ； in, and Energy storage devices Rated energy and rated power; and Energy storage devices In the period t 0 / 1 variables for internal charge and discharge states, and Energy storage eE In the period t The charging and discharging power within Energy storage device In the period t Reactive power; and They are Upper and lower limits of ; and Energy storage devices The maximum and minimum state of charge limits, and Represent energy storage devices The energy at the beginning and end of the period, Energy storage device In the time period t The transient frequency response reserve, Energy storage device In the period t Power, Energy storage device In the period t stored energy, Energy storage device The frequency response limiting coefficient, The time required for a stationary standby turbine generator to reach target power from the start of a transient fault event.

4. The method for optimizing and dispatching an offshore island microgrid taking frequency constraints into account according to claim 3, characterized in that: The energy storage device operation constraint conditions also include power type energy storage device constraint conditions, and the power type energy storage device constraint conditions include: ； ； in, Indicates power type energy storage device During the scheduling period t Frequency response reserve within and Power type energy storage devices Rated power and rated energy; Power-type energy storage equipment The frequency response limiting coefficient of Power-type energy storage equipment Maintaining state of charge, It is the time for the power type energy storage device to exit the frequency response.

5. The method for optimizing and dispatching an offshore island microgrid taking frequency constraints into account according to claim 1, characterized in that: The frequency response model includes the rotating standby gas turbine generator, power type energy storage device, energy type energy storage device and load in the microgrid. τ The frequency response power at time , where , τ = 0 indicates the moment when the transient fault event begins, The time required for a stationary standby turbine generator to reach target power from the start of a transient fault event; The frequency response model is: ； ； ； ； in, 、 、 and They are the frequency response reserves of rotating standby gas turbine generator, power type energy storage equipment, energy type energy storage equipment and load, 、 and are the frequency response delay times of energy storage equipment, load and spinning standby turbine generator, 、 and are the frequency complete response times of power type energy storage equipment, energy type energy storage equipment and rotating standby turbine generator, It is the time for the power type energy storage device to exit the frequency response.

6. The method for optimizing and dispatching an offshore island microgrid taking frequency constraints into account according to claim 2, characterized in that: The constraint conditions include frequency constraint conditions, and the frequency constraint conditions include frequency change rate constraint conditions, frequency quasi-steady-state constraint conditions, and frequency maximum deviation constraint conditions.

7. An offshore island microgrid optimization and dispatching device taking frequency constraints into account, characterized in that: The device comprises: A first model building module is configured to obtain operating parameters of the offshore island microgrid, wherein the operating parameters include the load condition, topology, physical parameters of the equipment, and wind speed in the sea area of the microgrid, and to build an operating model of the microgrid based on the operating parameters, wherein the operating model reflects the relationship between the physical parameters of each equipment in the microgrid during operation; A second model building module is used to build a frequency response model, wherein the frequency response model reflects the frequency response of the microgrid during a transient fault event; a constraint condition building module, configured to determine the constraint conditions of the microgrid based on the operating parameters and the frequency response model, wherein the constraint conditions reflect the limitations of the equipment in the microgrid during operation; An optimization module is configured to solve a target optimization function based on the operation model and the constraints to obtain an optimized scheduling plan for the microgrid, wherein the optimization goal of the target optimization function is to minimize the operation cost of the microgrid, and the optimized scheduling plan includes the operating status of the equipment in the microgrid during each scheduling period.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the offshore island microgrid optimization scheduling method taking frequency constraints into account as described in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for optimizing and dispatching an offshore island microgrid taking frequency constraints into account is implemented as claimed in any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the method for optimizing and dispatching an offshore island microgrid taking frequency constraints into account is implemented as claimed in any one of claims 1 to 6.

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