Electric hydrogen production assisted island micro-grid load frequency control method, system, equipment, medium and product

Abstract

The invention discloses an electric hydrogen production assisted island microgrid load frequency control method, system and device, a medium and a product, and relates to the technical field of power systems, and the method comprises the steps: building an open-loop load frequency control model based on microgrid operation parameters and device operation parameters participating in microgrid load frequency control; designing a trigger threshold by adopting a bilateral dynamic updating mechanism; designing an event triggering judgment rule based on the triggering threshold value; based on the open-loop load frequency control model, a closed-loop load frequency control model is obtained in combination with the climbing constraint; based on the event triggering judgment rule and the closed-loop load frequency control model, a Lyapunov stability theory is adopted to obtain a closed-loop load frequency control scheme; and a closed-loop load frequency control scheme is adopted to control the stability of the load frequency of the micro-grid. The load frequency deviation of the micro-grid can be reduced, the stability of the micro-grid is improved, and on the basis of ensuring that the load frequency of the micro-grid is kept stable, the adjustment times of load frequency control are reduced.

Description

Technical Field

[0001] The present application relates to the technical field of power systems, and in particular to a method, system, device, medium and product for load frequency control of an isolated island microgrid assisted by electric hydrogen production. Background Art

[0002] With the advancement of global energy transformation, the proportion of renewable energy (such as wind and solar energy) in the energy structure has gradually increased. Microgrids, as an effective way to integrate these distributed energy sources, have attracted attention due to their flexibility and reliability. However, due to the intermittent and uncertain nature of renewable energy generation, microgrids are prone to imbalances in power supply and demand, resulting in frequency fluctuations in microgrids. Continuous frequency deviations threaten the safe operation of microgrids, causing increased network losses, disconnection of power generation equipment, and even power outages. Therefore, microgrids often rely on load frequency control (LFC) mechanisms, using communication networks to collect microgrid operating status and adjust the power operating point of power generation equipment to achieve power balance at the rated power point.

[0003] In the prior art, the equipment involved in LFC is generally a synchronous generator and a conventional battery energy storage system. Although battery energy storage has the advantages of fast response speed and high charging and discharging rate, the capacity of the battery in battery energy storage is generally small, and in the scenario of high penetration of new energy, the investment cost of battery energy storage when participating in LFC is relatively high. Hydrogen energy, as a high calorific value, zero carbon emission energy, can provide high-quality frequency regulation resources for microgrids. Power to hydrogen (P2H) technology can convert electrical energy into hydrogen energy, providing microgrids with additional frequency regulation capabilities and energy storage options.

[0004] However, when the P2H device participates in the load frequency control of the microgrid, it is affected by operational constraints such as the number of responses and the ramp rate. These constraints are not only related to the safety of the equipment, but also affect the economic efficiency of the microgrid operation. Therefore, these operational constraints must be considered when designing a microgrid load frequency control strategy that cooperates with the hydrogen production device. Although there are equipment modeling and frequency regulation capability evaluation for P2H devices in the prior art, in-depth research on the P2H device's collaborative participation in the load frequency control strategy is still insufficient, especially when considering the safety and economy of the equipment, and the ramp rate constraints of the frequency regulation device are still lacking. In addition, the traditional periodic control strategy may cause unnecessary communication burdens and control actions in the microgrid, while event-triggered control, as an emerging control strategy, can reduce communication and control costs while ensuring system performance. Therefore, there is an urgent need for a load frequency control method for an isolated microgrid assisted by hydrogen production, which reduces the number of responses of the frequency regulation equipment (i.e., the number of control times for the load frequency control of the microgrid) while ensuring the stability of the microgrid system. Summary of the invention

[0005] The purpose of this application is to provide a method, system, device, medium and product for load frequency control of an isolated island microgrid assisted by electric hydrogen production, which can improve the stability of the microgrid and reduce the control frequency of the microgrid load frequency control on the basis of ensuring that the microgrid load frequency remains stable.

[0006] To achieve the above objectives, this application provides the following solutions:

[0007] In a first aspect, the present application provides a method for controlling load frequency of an isolated island microgrid assisted by electric hydrogen production, comprising:

[0008] Acquire microgrid operating parameters and equipment operating parameters involved in microgrid load frequency control; the equipment operating parameters involved in microgrid load frequency control include: P2H equipment operating parameters, gas turbine generator operating parameters and energy storage battery operating parameters;

[0009] Constructing an open-loop load frequency control model based on the microgrid operating parameters and the equipment operating parameters participating in the microgrid load frequency control;

[0010] A trigger threshold is designed by adopting a bilateral dynamic update mechanism; an event trigger determination rule is designed based on the trigger threshold;

[0011] Based on the open-loop load frequency control model, a closed-loop load frequency control model is obtained in combination with a climbing constraint; the climbing constraint includes a P2H device climbing constraint, a gas turbine generator climbing constraint, and an energy storage battery climbing constraint;

[0012] Based on the event triggering judgment rule and the closed-loop load frequency control model, a closed-loop load frequency control scheme is obtained by using Lyapunov stability theory;

[0013] Obtain microgrid load frequency deviation in real time;

[0014] By adopting the closed-loop load frequency control scheme, when the microgrid load frequency deviation decreases, the control frequency of the microgrid load frequency by the closed-loop load frequency control scheme is reduced; when the microgrid load frequency deviation increases, the control frequency of the microgrid load frequency by the closed-loop load frequency control scheme is increased to control the microgrid load frequency to be stable.

[0015] Optionally, constructing an open-loop load frequency control model based on the microgrid operating parameters and the device operating parameters participating in the microgrid load frequency control includes:

[0016] Based on the operating parameters of the equipment involved in the microgrid load frequency control, a P2H equipment frequency-electrolysis power response model, a gas turbine generator dynamic characteristics model and an energy storage battery model are respectively constructed;

[0017] Based on the P2H equipment frequency-electrolysis power response model, the gas turbine generator dynamic characteristic model and the energy storage battery model, combined with the microgrid operation parameters, a microgrid dynamic characteristic model is constructed;

[0018] Based on the P2H equipment frequency-electrolysis power response model, the gas turbine generator dynamic characteristic model, the energy storage battery model and the microgrid dynamic characteristic model, an open-loop load frequency control model is obtained by adopting frequency modulation participation conditions.

[0019] Optionally, the frequency modulation participation condition is expressed as:

[0020]

[0021] In the formula, is the reference output active power adjustment of the gas turbine generator, is the reference output active power adjustment of the energy storage battery, is the reference hydrogen production power adjustment of the P2H equipment; α1, α2 and α3 are frequency modulation participation factors, α1+α2+α3=1, and u(t) is the load frequency control instruction.

[0022] Optionally, the trigger threshold is expressed as:

[0023] δ(t k h)=min{δ M ,max{δ m ,ξδ(t k-1 h)}};

[0024]

[0025] In the formula, δ(t k h) is t=t k The event triggering threshold at time h, y(t k h) is t=t k Microgrid load frequency deviation at time h; μ∈(0,1), δ M ∈(0,1),δ m ∈(0,1),δ m <δ M ; δ m is the minimum trigger threshold; δ M is the maximum trigger threshold; ξ is the bilateral adaptive parameter.

[0026] Optionally, based on the event triggering judgment rule and the closed-loop load frequency control model, Lyapunov stability theory is adopted to obtain a closed-loop load frequency control scheme including:

[0027] Based on the event triggering judgment rule and the closed-loop load frequency control model, a first linear matrix inequality group is obtained by using Lyapunov stability theory;

[0028] Obtaining a second linear matrix inequality group based on the contract transformation technique and the first linear matrix inequality group;

[0029] A closed-loop load frequency control scheme is obtained according to the second linear matrix inequality group, the event triggering determination rule and the closed-loop load frequency control model.

[0030] Optionally, according to the second linear matrix inequality group, the event triggering determination rule and the closed-loop load frequency control model, a closed-loop load frequency control scheme is obtained, including:

[0031] According to the second linear matrix inequality group, the event triggering determination rule and the control parameters of the closed-loop load frequency control model are obtained;

[0032] A closed-loop load frequency control scheme is obtained according to the control parameters, the event triggering determination rules and the closed-loop load frequency control model.

[0033] In a second aspect, the present application provides a load frequency control system for an isolated microgrid assisted by electric hydrogen production, comprising:

[0034] Load frequency change module, used to obtain microgrid load frequency deviation in real time;

[0035] An event triggering module, used to determine the control frequency of the microgrid load frequency by the closed-loop load frequency control scheme according to the microgrid load frequency deviation;

[0036] The saturation constraint module is used to control the load frequency of the microgrid according to the closed-loop load frequency control scheme.

[0037] In a third aspect, the present application provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of any of the above-described methods for controlling load frequency of an isolated island microgrid assisted by electric hydrogen production.

[0038] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the above-mentioned methods for controlling load frequency of an isolated island microgrid assisted by hydrogen production.

[0039] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of any of the above-mentioned methods for controlling the load frequency of an isolated island microgrid assisted by hydrogen production.

[0040] According to the specific embodiments provided in this application, this application has the following technical effects:

[0041] The present application provides a method, system, device, medium and product for load frequency control of an isolated microgrid assisted by electric hydrogen production. An open-loop load frequency control model is constructed based on the operating parameters of the microgrid and the operating parameters of the equipment involved in the load frequency control of the microgrid, the power supply source of the microgrid and the equipment involved in the load frequency control are described, and an isolated microgrid operation architecture containing hydrogen energy is designed. By adopting a bilateral dynamic update mechanism to design a trigger threshold, and designing an event trigger judgment rule according to the trigger threshold, the closed-loop load frequency control scheme is allowed to adjust the operating power point of the frequency modulation equipment including the P2H device only when the control performance drops below the preset level, and the number of responses of the P2H device is effectively reduced while ensuring the stability of the microgrid frequency. Based on the event trigger judgment rule and the closed-loop load frequency control model, the Lyapunov stability theory is adopted to obtain a closed-loop load frequency control scheme, which ensures the asymptotic stability of the microgrid under bounded transmission delay, and enables the microgrid to have H∞ (H-infinity) damping performance to external disturbances. The present application can reduce the load frequency deviation of the microgrid, improve the stability of the microgrid, and reduce the number of responses of the frequency control device on the basis of ensuring that the load frequency of the microgrid remains stable. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0043] Figure 1 This is a flow chart of a method for controlling load frequency of an isolated island microgrid assisted by electric hydrogen production in one embodiment of the present application;

[0044] Figure 2 A comparison diagram of load frequency deviation of a microgrid using P2H equipment and not using P2H equipment in an embodiment of the present application;

[0045] Figure 3 This is a comparison chart of the triggering times of closed-loop load frequency control with and without the assistance of P2H equipment in an embodiment of the present application;

[0046] Figure 4 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0048] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0049] In an exemplary embodiment, a method for load frequency control of an isolated microgrid assisted by electric hydrogen production is provided. The method is executed by a computer device, and can be executed by a computer device such as a terminal or a server alone, or by a terminal and a server together. In all the embodiments given in this application, the method is applied to an electric hydrogen production device to assist an isolated microgrid in load frequency control as an example. Figure 1 As shown, the load frequency control method of the isolated island microgrid assisted by electric hydrogen production includes:

[0050] Step 1: Obtain the microgrid operating parameters and the equipment operating parameters involved in the microgrid load frequency control. The equipment operating parameters involved in the microgrid load frequency control include: P2H equipment operating parameters, gas turbine generator operating parameters and energy storage battery operating parameters.

[0051] Step 2: construct an open-loop load frequency control model based on the microgrid operating parameters and the operating parameters of the equipment involved in the microgrid load frequency control.

[0052] Based on the operating parameters of the equipment involved in the microgrid load frequency control, the P2H equipment frequency-electrolysis power response model, the gas turbine generator dynamic characteristics model and the energy storage battery model are constructed respectively. Based on the P2H equipment frequency-electrolysis power response model, the gas turbine generator dynamic characteristics model and the energy storage battery model, combined with the microgrid operating parameters, an open-loop load frequency control model is constructed, which describes the power supply source of the microgrid and the equipment involved in the load frequency control, and designs the operation architecture of the isolated microgrid including hydrogen energy.

[0053] Step 201, based on the operating parameters of the equipment involved in the microgrid load frequency control, construct a P2H equipment frequency-electrolysis power response model, a gas turbine generator dynamic characteristics model and an energy storage battery model.

[0054] The operation architecture of the isolated microgrid including hydrogen energy includes the P2H equipment frequency-electrolysis power response model, the gas turbine generator dynamic characteristics model and the battery energy storage system (BESS) model. Among them, the P2H equipment is involved in the load frequency control of the isolated microgrid to achieve the coordinated optimization and regulation of electricity and hydrogen energy, which can effectively expand the frequency regulation resources of the isolated microgrid.

[0055] For example, the construction of the P2H equipment frequency-electrolysis power response model, the gas turbine generator dynamic characteristics model and the energy storage battery model can adopt the following process:

[0056] 1) Construct a frequency-electrolysis power response model of P2H equipment.

[0057] T P2H As the inertia time constant of the electrolyzer part of the P2H device, η P2H is the electrolyzer conversion efficiency, is the reference hydrogen production power adjustment of the P2H equipment. It should be noted that T P2H and η P2H It is generally obtained based on the operating parameter identification of the actual P2H equipment. The conversion efficiency of existing commercial P2H equipment is between 65% and 80%. When the electrolytic power of the electrolyzer changes, the electrolyzer conversion efficiency will reach a new stable point due to microbubble transport, reactant concentration diffusion, etc. The chemical reaction process has a typical time lag characteristic, so it is modeled as a first-order inertia link. Among them, ΔP P2H (t) represents the electrolysis power of the P2H device, ΔP P2H The first-order derivative of (t). The P2H device frequency-electrolysis power response model is expressed as:

[0058]

[0059] 2) Construct a dynamic characteristics model of the gas turbine generator.

[0060] Micro Gas Turbine (MGT) controls the valve opening through the speed regulator, thereby adjusting the natural gas intake to achieve the change of the turbine output mechanical power, and then drives the adjustment of the synchronous generator output electrical power. g,MGT As the MGT governor time constant, T t,MGT As the turbine time constant. ΔP v,MGT (t) is the increment of the MGT governor valve opening, ΔP v,MGT The first derivative of (t). ΔP m,MGT (t) is the mechanical power output of the steam turbine, ΔPm,MGT The first derivative of (t). is the reference output active power adjustment of MGT, Δf(t) is the microgrid load frequency deviation, R MGT is the MGT droop coefficient. The dynamic characteristic model of the gas turbine generator is expressed as:

[0061]

[0062] 3) Construct an energy storage battery model.

[0063] The battery energy storage system (BESS) responds to the load frequency control command of the microgrid by adjusting the output active power of the power electronic inverter.

[0064] The energy storage battery model is expressed as: Where ΔP BESS (t) is the output active power of BESS, ΔP BESS The first derivative of (t), T BESS is the BESS time constant, K BESS is the BESS unit adjustment coefficient, is the reference output active power adjustment of BESS.

[0065] Step 202, based on the P2H equipment frequency-electrolysis power response model, the gas turbine generator dynamic characteristic model and the energy storage battery model, combined with the microgrid operation parameters, a microgrid dynamic characteristic model is constructed.

[0066] For example, when the frequency deviation of the microgrid is caused by uncertain power fluctuations on both sides of the source and load, the dynamic characteristic model of the microgrid is expressed as follows under the coordinated participation of MGT, BESS and P2H in the load frequency control of the microgrid:

[0067] Where M MG and D MG Respectively represent the microgrid inertia and damping coefficient, ΔP PV (t) is the photovoltaic power output power, ΔP WT (t) is the wind turbine output power, ΔP D (t) is the load fluctuation, Δf(t) is the microgrid load fluctuation, is the first-order derivative of Δf(t).

[0068] Step 203, based on the P2H equipment frequency-electrolysis power response model, the gas turbine generator dynamic characteristic model, the energy storage battery model and the microgrid dynamic characteristic model, the frequency modulation participation condition is adopted to obtain an open-loop load frequency control model.

[0069] For example, the FM participation condition can be expressed as:

[0070] In the formula, is the reference output active power adjustment of the gas turbine generator, is the reference output active power adjustment of the energy storage battery, is the reference hydrogen production power adjustment of the P2H equipment; α1, α2 and α3 are frequency modulation participation factors, α1+α2+Δ3=1, and u(y) is the load frequency control instruction.

[0071] Combining the models constructed in step 201 and step 202 and the frequency modulation participation conditions, an open-loop load frequency control model is obtained to represent the open-loop dynamic characteristics of the load frequency control of the isolated island microgrid. The open-loop load frequency control model can be represented by the state space equation:

[0072] Where x(t) = [Δf(t), ΔP m,MGT (t),ΔP v,MGT (y),ΔP BESS (t),ΔP P2H (t),∫Δf(t)] T , w(t)=[ΔP WT (t),ΔP PV (t),ΔP D (t)] T , y(t)=Δf(t).

[0073] C=[1 0 0 0 0 0].

[0074] Step 3: Use the bilateral dynamic update mechanism to design the trigger threshold, and design the event trigger determination rule based on the trigger threshold.

[0075] Among the technologies known to the inventors, most P2H systems use highly corrosive KOH solutions or precious metal catalysts as the reaction medium for electrolytic hydrogen production. Therefore, in order to reduce the maintenance cost of the P2H system, it is necessary to reduce the number of responses of the P2H system participating in the load frequency control of the microgrid as much as possible while ensuring the stability of the microgrid frequency. To this end, it is necessary to design a load frequency control scheme that includes event triggering. The basic idea is to add an event-triggered detector (ETD) to detect the load operation status information of the microgrid. When the microgrid operation status degenerates to a preset threshold, the reference operating point of each device participating in the load frequency control of the microgrid is updated, thereby effectively reducing the response frequency of frequency modulation equipment including P2H equipment and extending its service life.

[0076] For example, the event triggering decision rule can be expressed as:

[0077] t k+1 =t k +min{l|e T (i k h)Φe(i k h)≥δ(t k h)x T (t k h)Φx(t k h)}.

[0078] Where h is the sampling period. e(i k h)=x(i k h)-x(t k h), e(i k h) is the current time t=i k h The microgrid load state quantity and the last triggering time t = t k h is the deviation vector of the microgrid load state quantity. Φ is the performance weight matrix, and Φ>0. δ(t k h) is t=t k Event trigger threshold at time h. k and t k+1 Respectively represent the tth signal of the two adjacent signals that meet the trigger condition k subsampling and t k+1 Subsampling, x(t k h) represents the microgrid load state quantity currently transmitted.

[0079] Among them, the trigger threshold δ(t k h) Adopt a bilateral dynamic update mechanism that increases adaptively as the control error decreases, triggering the threshold δ(t k h) is expressed as:

[0080] δ(t k h)=min{δ M ,max{δ m ,ξδ(t k-1 h)}}.

[0081]

[0082] In the formula, δ(t k h) is t=t k The event triggering threshold at time h, y(t k h) is t=t k Microgrid load frequency deviation at time h; μ∈(0,1), δ M ∈(0,1),δ m ∈(0,1),δ m <δ M δm is the minimum trigger threshold; δ M is the maximum trigger threshold; ξ is the bilateral adaptive parameter.

[0083] When the control error (i.e., microgrid load frequency deviation) decreases, the trigger threshold will gradually increase, so that the reference operating point of each device participating in the microgrid load frequency control can be updated at a lower interaction frequency, that is, the number of microgrid load frequency controls can be reduced. Conversely, when the control error increases, the trigger threshold immediately returns to the preset minimum value, so that each device participating in the microgrid load frequency control can be controlled at a more frequent interaction frequency, that is, the number of microgrid load frequency controls can be increased.

[0084] When the frequency deviation increases, ξ∈(0,1), which means that the trigger threshold gradually decreases from the current value to the preset minimum value δ m Therefore, in the same scenario, compared with the unilateral dynamic update mechanism, the use of the bilateral dynamic update mechanism to design the trigger threshold can further reduce the control frequency (i.e., interaction frequency) of the microgrid load frequency control.

[0085] Step 4: Based on the open-loop load frequency control model, a closed-loop load frequency control model is obtained in combination with the ramp constraints, wherein the ramp constraints include the P2H equipment ramp constraints, the gas turbine generator ramp constraints, and the energy storage battery ramp constraints.

[0086] Assuming that the load frequency control of the isolated microgrid adopts a state feedback control scheme, according to the event triggering judgment rule, within the interval between two adjacent event triggering, since the control performance of the microgrid load frequency control has not dropped below the preset level, the control command remains unchanged. Therefore, in an ideal situation, the control command of the microgrid load frequency control within the interval between two adjacent triggering events is expressed as:

[0087]

[0088] In the formula, K f To control the gain. is the transmission delay, d is the maximum transmission delay. Divide into sets according to the sampling period h i l h=t k h+lh. Here, η(t)=ti l h, by e(i l h)=x(i l h)-x(t k h) has x(t k h)=e(i l h)-e(i lh)=x(t-η(t))-e(i l h), so we get u(t) = K f [x(t-η(t))-e(i l h)],

[0089] Note that existing commercial P2H equipment is generally subject to chemical reaction rate constraints, and in order to avoid the risk of explosion caused by the decrease in hydrogen purity due to too fast electrolysis power changes, the electrolysis power ramp range of the P2H equipment needs to be strictly limited. Similarly, there are the same ramp rate restrictions for gas turbine generators and energy storage batteries. That is, the ramp constraints include P2H equipment ramp constraints, gas turbine generator ramp constraints, and energy storage battery ramp constraints. Among them:

[0090] The P2H equipment climbing constraint is expressed as: In the formula, Indicates the maximum ramp rate of the P2H device.

[0091] The gas turbine generator ramp constraint is expressed as: In the formula, Indicates the maximum ramp rate of the gas turbine generator equipment.

[0092] The energy storage battery climbing constraint is expressed as: In the formula, Indicates the maximum climbing rate of the energy storage battery.

[0093] According to the above description, combined with the frequency modulation participation condition in step 2, the actual control instruction can be expressed in a nonlinear form, and the control instruction u(t) is expressed as:

[0094]

[0095]

[0096] In the formula, sat(·) represents the saturation function, is a function describing the degree of nonlinear saturation, The physical meaning of is the difference between the ideal control input and the actual input. The intersection points of the function graph and the horizontal axis are -u max and u max . Further define the function g(K f x(ilh))=-λK f x(i l h),0≤λ≤1. Thus and g(K f x(i l h)) has two horizontal coordinates of the intersection of the function graph, which are and and as well as

[0097] Therefore, for any positive definite matrix Π, we always have:

[0098]

[0099] Finally, based on the open-loop load frequency control model and combined with the above description, the closed-loop load frequency control model is obtained, which is expressed as:

[0100]

[0101] Step 5: Based on the event triggering judgment rule and the closed-loop load frequency control model, the Lyapunov stability theory is used to obtain a closed-loop load frequency control scheme.

[0102] For example, based on the event triggering judgment rule and the closed-loop load frequency control model, the Lyapunov stability theory is used to obtain a group of linear matrix inequalities, and the performance weight matrix in the event triggering judgment rule and the control gain in the closed-loop load frequency control model are obtained according to the linear matrix inequality group, thereby obtaining a closed-loop load frequency control scheme. Specifically, it includes: based on the event triggering judgment rule and the closed-loop load frequency control model, the Lyapunov stability theory is used to obtain a first group of linear matrix inequalities. Based on the contract transformation technology and the first group of linear matrix inequalities, a second group of linear matrix inequalities is obtained. According to the second group of linear matrix inequalities, the event triggering judgment rule and the control parameters of the closed-loop load frequency control model are obtained. According to the control parameters, the event triggering judgment rule and the closed-loop load frequency control model, a closed-loop load frequency control scheme is obtained.

[0103] Given scalars ρ, γ, δ M , d and λ, ρ, γ, δ M and d are both greater than 0, λ∈[0,1]. I is the unit matrix. If there exist matrices X, Π and symmetric positive definite matrices P, Q, R and Ф that satisfy the first matrix inequality group, then the microgrid load frequency control system using event triggering rule is asymptotically stable under bounded transmission delay [0,d] and has H∞ damping performance for external power disturbances. The first matrix inequality group is expressed as:

[0104]

[0105] In the formula, ψ ij represents matrix elements, i=1,2,...,8,j=1,2,...,8. ψ 11 =Q-R+PA+A T P,ψ 12 =X T , ψ13 =PBK f -X T +R,ψ 14 =-PBK f , ψ 15 =-PH,ψ 16 =PB,ψ 17 =A T P,ψ 18 =C T , ψ 22 = -QR,ψ 23 =RX,ψ 33 =-2R+X T +X+δ M Φ,ψ 36 = -λK f Π,ψ 37 =K f T B T P,ψ 44 = -Φ, ψ 46 =λK f ∏,ψ 47 =-K f T B T P,ψ 55 =-γ 2 I,ψ 57 =H T P,ψ 66 =-2Π,ψ 67 =B T P,ψ 77 =ρ 2 d 2 R-2ρP,ψ 88 =-I.

[0106] Since in the first matrix inequality group, the matrix K to be solved f , Π, P, etc. are nonlinear multiplicative relationships, and it is difficult to directly use the linear matrix inequality solution method to determine the relevant parameters for solution. Therefore, based on the contract transformation technology and the first linear matrix inequality group, the second linear matrix inequality group is obtained.

[0107] Given scalars ρ, γ, δ M , d and λ, ρ, γ, δ M and d are both greater than 0, λ∈[0,1]. If there is a scalar and a matrix Γ and the positive definite matrix Λ, If Z satisfies the second linear matrix inequality group, the microgrid load frequency control system under closed-loop load control is asymptotically stable.

[0108]

[0109] In the formula, Θ ij Represents matrix elements, i=1,2,...,8, j=1,2,...,8. Θ 14 = -BΓ, Θ 15 =H, θ 16 =BZ,θ 17 = ΛA T , Θ 18 =ΛC T , Θ 36 = -λΓ T , Θ 37 =Γ T B T , Θ 46 =λΓ T , Θ 47 =-Γ T B T , Θ 55 =-γ 2 I, θ 57 =-H T , Θ 66 = -2Z, θ 67 =ZB T , Θ 88 =-I.

[0110] According to the second linear matrix inequality, the event triggering judgment rule and the control parameters of the closed-loop load frequency control model can be obtained, that is, the performance weight matrix in the event triggering judgment rule and the control gain in the closed-loop load frequency control model, the performance weight matrix Control gain K f =ΓΛ -1 Therefore, a closed-loop load frequency control scheme can be obtained according to the control parameters, event triggering judgment rules and closed-loop load frequency control model.

[0111] Step 6, real-time acquisition of the microgrid load frequency deviation. A closed-loop load frequency control scheme is adopted. When the microgrid load frequency deviation decreases, the control frequency of the microgrid load frequency by the closed-loop load frequency control scheme is reduced. When the microgrid load frequency deviation increases, the control frequency of the microgrid load frequency by the closed-loop load frequency control scheme is increased to control the microgrid load frequency to be stable.

[0112] Based on the same inventive concept, the embodiment of the present application also provides a hydrogen-assisted island microgrid load frequency control system for implementing the hydrogen-assisted island microgrid load frequency control method involved above. The implementation scheme for solving the problem provided by the system is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments provided below can refer to the limitations of the hydrogen-assisted island microgrid load frequency control method above, and will not be repeated here.

[0113] In an exemplary embodiment, a load frequency control system for an isolated island microgrid assisted by electric hydrogen production is provided, comprising:

[0114] The load frequency change module is used to obtain the microgrid load frequency deviation in real time.

[0115] The event trigger module is used to determine the control frequency of the microgrid load frequency by the closed-loop load frequency control scheme according to the microgrid load frequency deviation.

[0116] The saturation constraint module is used to control the load frequency of the microgrid according to a closed-loop load frequency control scheme.

[0117] In an exemplary embodiment, in order to verify the effectiveness of the load frequency control method of the isolated microgrid assisted by hydrogen production, a relevant simulation model is built in the Matlab / Simulink environment. Among them, the P2H device is selected as an alkaline electrolyzer, and the relevant simulation parameter settings are shown in Table 1. The effectiveness of the load frequency control method of the isolated microgrid assisted by hydrogen production in this application is verified by comparing whether the closed-loop load frequency control scheme assisted by the P2H device is used.

[0118] Table 1 Simulation parameter setting table

[0119]

[0120]

[0121] The simulation results of the closed-loop load frequency control scheme assisted by P2H devices and the closed-loop load frequency control scheme not assisted by P2H devices are shown in Table 2. By comparing the simulation results of the two, it can be found that by adding P2H devices, the number of event triggering will not change significantly, but the addition of P2H devices to assist the closed-loop load frequency control scheme has significantly reduced the frequency deviation of the microgrid output, the frequency deviation amplitude has decreased by 1.5%, and the frequency absolute value integral has decreased by 2.2%, indicating that adding P2H devices to assist the load frequency control of the isolated microgrid can further improve the stability of the microgrid.

[0122] Table 2 Simulation results

[0123] Add P2H device Without P2H device Trigger times 135 130 Frequency deviation amplitude / Hz 0.02177 0.02211 Adjustment time / s (5% of peak value) 24.15 24.33 Frequency deviation absolute value integral / Hz·s 0.3091 0.3162

[0124] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store relevant data in the load frequency control method of the isolated island microgrid assisted by hydrogen production. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a load frequency control method of an isolated island microgrid assisted by hydrogen production is implemented.

[0125] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components. In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0126] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0127] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0128] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0129] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0130] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0131] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for controlling the load frequency of an isolated island microgrid assisted by electric hydrogen production, characterized in that: The method for controlling load frequency of an isolated island microgrid assisted by electric hydrogen production comprises: Acquire microgrid operating parameters and equipment operating parameters involved in microgrid load frequency control; the equipment operating parameters involved in microgrid load frequency control include: P2H equipment operating parameters, gas turbine generator operating parameters and energy storage battery operating parameters; Constructing an open-loop load frequency control model based on the microgrid operating parameters and the equipment operating parameters participating in the microgrid load frequency control; A trigger threshold is designed by adopting a bilateral dynamic update mechanism; an event trigger determination rule is designed based on the trigger threshold; Based on the open-loop load frequency control model, a closed-loop load frequency control model is obtained in combination with a climbing constraint; the climbing constraint includes a P2H device climbing constraint, a gas turbine generator climbing constraint, and an energy storage battery climbing constraint; Based on the event triggering judgment rule and the closed-loop load frequency control model, a closed-loop load frequency control scheme is obtained by using Lyapunov stability theory; Obtain microgrid load frequency deviation in real time; By adopting the closed-loop load frequency control scheme, when the microgrid load frequency deviation decreases, the control frequency of the microgrid load frequency by the closed-loop load frequency control scheme is reduced; when the microgrid load frequency deviation increases, the control frequency of the microgrid load frequency by the closed-loop load frequency control scheme is increased to control the microgrid load frequency to be stable.

2. The method for controlling load frequency of an isolated island microgrid assisted by electric hydrogen production according to claim 1, characterized in that: An open-loop load frequency control model is constructed based on the microgrid operating parameters and the equipment operating parameters participating in the microgrid load frequency control, including: Based on the operating parameters of the equipment involved in the microgrid load frequency control, a P2H equipment frequency-electrolysis power response model, a gas turbine generator dynamic characteristics model and an energy storage battery model are respectively constructed; Based on the P2H equipment frequency-electrolysis power response model, the gas turbine generator dynamic characteristic model and the energy storage battery model, combined with the microgrid operation parameters, a microgrid dynamic characteristic model is constructed; Based on the P2H equipment frequency-electrolysis power response model, the gas turbine generator dynamic characteristic model, the energy storage battery model and the microgrid dynamic characteristic model, an open-loop load frequency control model is obtained by adopting frequency modulation participation conditions.

3. The method for controlling load frequency of an isolated island microgrid assisted by electric hydrogen production according to claim 2 is characterized in that: The FM participation condition is expressed as: In the formula, is the reference output active power adjustment of the gas turbine generator, is the reference output active power adjustment of the energy storage battery, is the reference hydrogen production power adjustment of the P2H equipment; α1, α2 and α3 are frequency modulation participation factors, α1+α2+α3=1, and u(t) is the load frequency control instruction.

4. The method for controlling load frequency of an isolated island microgrid assisted by electric hydrogen production according to claim 1, characterized in that: The trigger threshold is expressed as: δ(t k h)=min{δ M ,max{δ m ,ξδ(t k-1 h)}}; in, In the formula, δ(t k h) is t=t k The event triggering threshold at time h, y(t k h) is t=t k Microgrid load frequency deviation at time h; μ∈(0,1), δ M ∈(0,1),δ m ∈(0,1),δ m <δ M ; δ m is the minimum trigger threshold; δ M is the maximum trigger threshold; ξ is the bilateral adaptive parameter.

5. The method for controlling load frequency of an isolated island microgrid assisted by electric hydrogen production according to claim 1, characterized in that: Based on the event triggering judgment rule and the closed-loop load frequency control model, the Lyapunov stability theory is adopted to obtain a closed-loop load frequency control scheme including: Based on the event triggering judgment rule and the closed-loop load frequency control model, a first linear matrix inequality group is obtained by using Lyapunov stability theory; Obtaining a second linear matrix inequality group based on the contract transformation technique and the first linear matrix inequality group; A closed-loop load frequency control scheme is obtained according to the second linear matrix inequality group, the event triggering determination rule and the closed-loop load frequency control model.

6. The method for controlling load frequency of an isolated island microgrid assisted by electric hydrogen production according to claim 5 is characterized in that: According to the second linear matrix inequality group, the event triggering determination rule and the closed-loop load frequency control model, a closed-loop load frequency control scheme is obtained, including: According to the second linear matrix inequality group, the event triggering determination rule and the control parameters of the closed-loop load frequency control model are obtained; A closed-loop load frequency control scheme is obtained according to the control parameters, the event triggering determination rules and the closed-loop load frequency control model.

7. A load frequency control system for an isolated island microgrid assisted by electric hydrogen production, characterized in that: The load frequency control system of the hydrogen production-assisted isolated island microgrid is used to implement the load frequency control method of the hydrogen production-assisted isolated island microgrid according to claim 1, and the load frequency control system of the hydrogen production-assisted isolated island microgrid includes: Load frequency change module, used to obtain microgrid load frequency deviation in real time; An event triggering module, used to determine the control frequency of the microgrid load frequency by the closed-loop load frequency control scheme according to the microgrid load frequency deviation; The saturation constraint module is used to control the load frequency of the microgrid according to the closed-loop load frequency control scheme.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for load frequency control of an isolated island microgrid assisted by electric hydrogen production according to any one of claims 1 to 6.

9. A 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 controlling the load frequency of an isolated island microgrid assisted by electric hydrogen production according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for controlling the load frequency of an isolated island microgrid assisted by electric hydrogen production according to any one of claims 1 to 6 is implemented.

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