Electrolytic hydrogen assisted island micro-grid load frequency control method, system, device, medium and product

Abstract

The application discloses a kind of electric hydrogen production auxiliary island micro-grid load frequency control method, system, equipment, medium and product, it is related to electric power system technical field, the method includes based on micro-grid operating parameter and the equipment operating parameter of participating micro-grid load frequency control to construct open-loop load frequency control model;Using double side dynamic updating mechanism designs trigger threshold;Based on trigger threshold design event trigger judgment rule;Based on open-loop load frequency control model, combined with climbing constraint to obtain closed-loop load frequency control model;Based on event trigger judgment rule and closed-loop load frequency control model, using Lyapunov stability theory, obtain closed-loop load frequency control scheme;Using closed-loop load frequency control scheme, control micro-grid load frequency stability.The application can reduce the load frequency deviation of micro-grid, improve the stability of micro-grid, on the basis of ensuring that micro-grid load frequency maintains stable, reduce the adjustment frequency of load frequency control.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power systems, in particular to a power-to-hydrogen assisted islanded microgrid load frequency control method, system, device, medium and product. BACKGROUND

[0002] With the advancement of global energy transformation, the proportion of renewable energy (such as wind energy and solar energy) in the energy structure is gradually increasing. Microgrids are valued for their flexibility and reliability as an effective way to integrate these distributed energy sources. However, due to the intermittency and uncertainty of new energy generation, power supply and demand imbalance in microgrids is prone to occur, leading to frequency fluctuations in microgrids. Continuous deviation of frequency can threaten the safe operation of microgrids, causing network loss to rise, generating equipment to be off-grid, and even power outages. Therefore, microgrids often rely on load frequency control (LFC) mechanisms to collect microgrid operating conditions using communication networks and adjust the power operating point of generating equipment to achieve power balance at the rated power point.

[0003] In the prior art, the devices participating in LFC are generally synchronous generators and conventional battery energy storage systems. Although battery energy storage has the advantages of fast response speed and high charging and discharging rate, the capacity of batteries in battery energy storage is generally small, and in the scenario of high penetration of new energy, the investment cost of battery energy storage is high when participating in LFC. Hydrogen energy, as a high-calorific value and zero-carbon energy source, can provide high-quality frequency modulation resources for microgrids. Power-to-hydrogen (P2H) technology can convert electrical energy into hydrogen energy, providing additional frequency modulation capability and energy storage options for microgrids.

[0004] However, P2H devices are affected by operating constraints such as response times and ramp rates when participating in microgrid load frequency control, which not only relate to the safety of the devices, but also affect the economy of microgrid operation. Therefore, when designing a microgrid load frequency control strategy with P2H devices, these operating constraints must be considered. Although there are existing technologies for modeling P2H devices and evaluating their frequency modulation capabilities, there is still insufficient research on P2H devices participating in load frequency control strategies, especially considering the safety and economy of the devices, and the ramp rate constraint of frequency modulation devices is not considered. In addition, traditional periodic control strategies can cause unnecessary communication burden and control actions in microgrids, 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 power-to-hydrogen assisted islanded microgrid load frequency control method that reduces the response times of frequency modulation devices (i.e., the number of control times for microgrid load frequency control) while ensuring the stability of the microgrid system. SUMMARY

[0005] The purpose of the present application is to provide an electric hydrogen production assisted island micro-grid load frequency control method, system, device, medium and product, which can improve the stability of the micro-grid, and reduce the control frequency of the micro-grid load frequency control on the basis of ensuring the stability of the micro-grid load frequency.

[0006] To achieve the above purpose, the present application provides the following solutions:

[0007] In a first aspect, the present application provides an electric hydrogen production assisted island micro-grid load frequency control method, comprising:

[0008] Obtaining micro-grid operation parameters and device operation parameters participating in micro-grid load frequency control; the device operation parameters participating in micro-grid load frequency control include P2H device operation parameters, gas turbine generator operation parameters and energy storage battery operation parameters;

[0009] Based on the micro-grid operation parameters and the device operation parameters participating in micro-grid load frequency control, an open-loop load frequency control model is constructed;

[0010] A double-sided dynamic updating mechanism is used to design a trigger threshold; based on the trigger threshold, an event trigger judgment rule is designed;

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

[0012] Based on the event trigger judgment rule and the closed-loop load frequency control model, a Lyapunov stability theory is used to obtain a closed-loop load frequency control scheme;

[0013] Real-time acquisition of micro-grid load frequency deviation;

[0014] Using the closed-loop load frequency control scheme, when the micro-grid load frequency deviation decreases, the control frequency of the closed-loop load frequency control scheme on the micro-grid load frequency is reduced; when the micro-grid load frequency deviation increases, the control frequency of the closed-loop load frequency control scheme on the micro-grid load frequency is increased, and the micro-grid load frequency is controlled to be stable.

[0015] Optionally, constructing an open-loop load frequency control model based on the micro-grid operation parameters and the device operation parameters participating in micro-grid load frequency control comprises:

[0016] Based on the device operation parameters participating in micro-grid load frequency control, a P2H device frequency-electrolysis power response model, a gas turbine generator dynamic characteristic model and an energy storage battery model are respectively constructed;

[0017] Based on the P2H device frequency-hydrogen production power response model, the gas turbine generator dynamic characteristic model and the energy storage battery model, a micro-grid dynamic characteristic model is constructed in combination with the micro-grid operation parameters;

[0018] Based on the P2H device frequency-hydrogen production power response model, the gas turbine generator dynamic characteristic model, the energy storage battery model and the micro-grid dynamic characteristic model, an open-loop load frequency control model is obtained by using a frequency modulation participation condition.

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

[0020]

[0021] In the formula, is a reference output active power adjustment amount of the gas turbine generator, is a reference output active power adjustment amount of the energy storage battery, is a reference hydrogen production power adjustment amount of the P2H device; α1, α2 and α3 are frequency modulation participation factors, α1+α2+α3=1, and u(t) is a 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 an event trigger threshold at t=t k h, y(t k h) is a micro-grid load frequency deviation at t=t k h; μ∈(0,1), δ M ∈(0,1), δ m ∈(0,1), δ m <δ M ; δ m is a minimum trigger threshold; δ M is a maximum trigger threshold; and ξ is a bilateral adaptive parameter.

[0026] Optionally, based on the event trigger determination rule and the closed-loop load frequency control model, a closed-loop load frequency control scheme is obtained by using Lyapunov stability theory, including:

[0027] Based on the event-triggered decision rule and the closed-loop load frequency control model, a first set of linear matrix inequalities is obtained by using Lyapunov stability theory;

[0028] Based on the contractive transformation technique and the first set of linear matrix inequalities, a second set of linear matrix inequalities is obtained.

[0029] According to the second set of linear matrix inequalities, the event-triggered decision rule and the closed-loop load frequency control model, a closed-loop load frequency control scheme is obtained.

[0030] Optionally, according to the second set of linear matrix inequalities, the event-triggered decision rule and the closed-loop load frequency control model, a closed-loop load frequency control scheme is obtained, including:

[0031] According to the second set of linear matrix inequalities, control parameters of the event-triggered decision rule and the closed-loop load frequency control model are obtained.

[0032] According to the control parameters, the event-triggered decision rule and the closed-loop load frequency control model, a closed-loop load frequency control scheme is obtained.

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

[0034] A load frequency variation module is configured to acquire a microgrid load frequency deviation in real time.

[0035] An event-triggered module is configured to determine a control frequency of a closed-loop load frequency control scheme on a microgrid load frequency according to the microgrid load frequency deviation.

[0036] A saturation constraint module is configured to control a load frequency of a 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, a computer program stored in the memory and executable on the processor, and the processor executes the computer program to implement the steps of the electric hydrogen production assisted island microgrid load frequency control method according to any one of the above.

[0038] In a fourth aspect, the present application provides a computer readable storage medium, which stores a computer program executable by a processor to implement the steps of the electric hydrogen production assisted island microgrid load frequency control method according to any one of the above.

[0039] In a fifth aspect, the present application provides a computer program product, comprising a computer program executable by a processor to implement the steps of the electric hydrogen production assisted island microgrid load frequency control method according to any one of the above.

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

[0041] The application provides an electric hydrogen production assisted island micro-grid load frequency control method, system, device, medium and product. An open-loop load frequency control model is constructed based on micro-grid operation parameters and device operation parameters participating in micro-grid load frequency control, the power supply source of the micro-grid and the device participating in the load frequency control are described, and an island micro-grid operation architecture containing hydrogen energy is designed. By adopting a double-sided dynamic updating mechanism to design a trigger threshold, an event trigger judgment rule is designed according to the trigger threshold, so that the closed-loop load frequency control scheme is allowed to adjust the operating power point of the frequency modulation device including the P2H device only when the control performance is reduced to below a preset level, the response frequency of the P2H device is effectively reduced under the premise of ensuring the stability of the micro-grid frequency. Based on the event trigger judgment rule and the closed-loop load frequency control model, the Lyapunov stability theory is adopted to obtain the closed-loop load frequency control scheme, which ensures the asymptotic stability of the micro-grid under the bounded transmission delay, and makes the micro-grid have H∞(H-infinity) damping performance to external disturbances. The application can reduce the load frequency deviation of the micro-grid, improve the stability of the micro-grid, and reduce the response frequency of the frequency control device on the premise of ensuring the stability of the micro-grid load frequency. BRIEF DESCRIPTION OF DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the drawings needed in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0043] Figure 1 A flowchart of an electric hydrogen production assisted island micro-grid load frequency control method in an embodiment of the application;

[0044] Figure 2 A comparison chart of load frequency deviations of micro-grids assisted by P2H devices and micro-grids not assisted by P2H devices in an embodiment of the application;

[0045] Figure 3 A comparison chart of closed-loop load frequency control trigger times of micro-grids assisted by P2H devices and micro-grids not assisted by P2H devices in an embodiment of the application;

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

[0047] With reference to the drawings and embodiments of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0048] The above purposes, features and advantages of the present application will be more apparent and understandable. The present application will be further described in detail below with reference to the drawings and specific embodiments.

[0049] In an exemplary embodiment, an electric hydrogen production assisted island microgrid load frequency control method is provided, which is executed by a computer device, specifically, can be executed by a terminal or a server, or can be executed by a terminal and a server. In all the embodiments of the present application, the method is applied to electric hydrogen production equipment assisted island microgrid for load frequency control. As shown in the figure, Figure 1 The electric hydrogen production assisted island microgrid load frequency control method includes:

[0050] Step 1, obtaining microgrid operation parameters and device operation parameters participating in microgrid load frequency control. The device operation parameters participating in microgrid load frequency control include: P2H device operation parameters, gas turbine generator operation parameters and energy storage battery operation parameters.

[0051] Step 2, constructing an open-loop load frequency control model based on microgrid operation parameters and device operation parameters participating in microgrid load frequency control.

[0052] By constructing P2H device frequency-electrolysis power response model, gas turbine generator dynamic characteristic model and energy storage battery model based on device operation parameters participating in microgrid load frequency control, and constructing open-loop load frequency control model based on P2H device frequency-electrolysis power response model, gas turbine generator dynamic characteristic model and energy storage battery model, combining with microgrid operation parameters, the power supply source of microgrid and the device participating in load frequency control are described, and the island microgrid operation architecture containing hydrogen energy is designed.

[0053] Step 201, constructing P2H device frequency-electrolysis power response model, gas turbine generator dynamic characteristic model and energy storage battery model based on device operation parameters participating in microgrid load frequency control.

[0054] The island micro-grid operation architecture comprising hydrogen energy includes a P2H device frequency-electrolysis power response model, a gas turbine generator dynamic characteristic model and a battery energy storage system (BESS) model. The P2H device participates in island micro-grid load frequency control, realizes collaborative optimization and regulation of electric energy-hydrogen energy, and can effectively expand the frequency modulation resources of the island micro-grid.

[0055] For example, the P2H device frequency-electrolysis power response model, the gas turbine generator dynamic characteristic model and the battery energy storage system model can be constructed by the following process:

[0056] 1) Construct the P2H device frequency-electrolysis power response model.

[0057] T P2H is the inertia time constant of the electrolysis tank part of the P2H device, P2H is the electrolysis tank conversion efficiency, is the reference hydrogen production power adjustment amount of the P2H device. It should be noted that T P2H and η P2H are generally identified according to the operating parameters of the actual P2H device, and the conversion efficiency of the existing commercial P2H device is between 65% and 80%. When the electrolysis power of the electrolysis tank changes, the electrolysis tank conversion efficiency will reach a new stable point due to reasons such as micro-bubble transportation and reactant concentration diffusion, and this chemical reaction process has typical time delay characteristics, so it is modeled as a first-order inertia link. Wherein, ΔP P2H (t) represents the electrolysis power of the P2H device, is the first derivative of ΔP P2H (t). The P2H device frequency-electrolysis power response model is represented as:

[0058]

[0059] 2) Construct the gas turbine generator dynamic characteristic model.

[0060] The micro gas turbine (MGT) controls the valve opening degree through the speed regulator, thereby adjusting the natural gas intake to change the output mechanical power of the turbine, and then driving the output electric power adjustment of the synchronous generator. T g,MGT is the MGT speed regulator time constant, t,MGT is the turbine time constant. ΔP v,MGT (t) is the increment of the MGT speed regulator valve opening degree, is the first derivative of ΔP v,MGT (t). ΔP m,MGT (t) is the output mechanical power of the turbine, is the first derivative of ΔPm,MGT The first derivative of (t). The reference output active power adjustment of the MGT is given by Δf(t), where Δf(t) is the microgrid load frequency deviation, and R is the value of R. MGT Let MGT be the droop coefficient. The dynamic characteristic model of the gas turbine generator is expressed as:

[0061]

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

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

[0064] The energy storage battery model is represented as follows: In the formula, ΔP BESS (t) represents the output active power of BESS. For ΔP BESS The first derivative of (t), T BESS K is the BESS time constant. BESS This is the BESS unit adjustment factor. This is the reference output active power adjustment for BESS.

[0065] Step 202: Based on the frequency-electrolysis power response model of P2H equipment, the dynamic characteristic model of gas turbine generator and energy storage battery, and combined with the microgrid operating parameters, construct the microgrid dynamic characteristic model.

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

[0067] In the formula, M MG and D MG Let ΔP represent the inertia and damping coefficient of the microgrid, respectively. PV (t) represents the output power of photovoltaic power generation, ΔP WT (t) represents the output power of the wind turbine, ΔP D (t) represents load fluctuation, and Δf(t) represents microgrid load fluctuation. It is the first derivative of Δf(t).

[0068] Step 203: Based on the frequency-electrolysis power response model of P2H equipment, the dynamic characteristic model of gas turbine generator, the energy storage battery model, and the dynamic characteristic model of microgrid, the open-loop load frequency control model is obtained by adopting the frequency regulation participation condition.

[0069] For example, the conditions for frequency modulation participation can be expressed as:

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

[0071] Based on the model constructed in steps 201 and 202 and the frequency modulation participation condition, an open-loop load frequency control model is obtained to represent the open-loop dynamic characteristics of the load frequency control of the island microgrid. The open-loop load frequency control model can be represented by a state space equation:

[0072] wherein, 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: A double-sided dynamic updating mechanism is used to design a triggering threshold, and an event-triggered determination rule is designed based on the triggering threshold.

[0075] In the known technology of the inventors, most P2H systems use strong corrosive KOH solution or noble metal catalyst as the electrolytic hydrogen production reaction medium. Therefore, in order to reduce the maintenance cost of the P2H system, the response frequency of the P2H system participating in the load frequency control of the microgrid needs to be reduced as much as possible under the premise of ensuring the stability of the microgrid frequency. Therefore, a load frequency control scheme containing event triggering needs to be designed. The basic idea is to additionally add an event-triggered detector (ETD), and update the reference operating point of each device participating in the load frequency control of the microgrid only when the operating state of the microgrid deteriorates to a preset threshold, so as to effectively reduce the response frequency of the frequency modulation devices including the P2H device and prolong the service life thereof.

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

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

[0078] In the formula, h is a sampling period. e(i k h) = x(i k h) - x(t k h), e(i k h) is a deviation vector of the micro-grid load state quantity at the current time t = i k h and the last time t = t k h when the event is triggered. Φ is a performance weight matrix, and Φ > 0. δ(t k h) is an event-triggered threshold at t = t k h. t k and t k+1 respectively represent the t k th sampling and the t k+1 th sampling of the signals adjacent to each other that meet the triggering condition, and x(t k h) represents the micro-grid load state quantity currently transmitted.

[0079] Among them, the triggering threshold δ(t k h) adopts a double-sided dynamic updating mechanism that adaptively increases following the control error decrease, and the triggering threshold δ(t k h) is expressed as:

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

[0081]

[0082] In the formula, δ(t k h) is an event-triggered threshold at t = t k h, y(t k h) is a micro-grid load frequency deviation at t = t k h; μ ∈ (0, 1), δ M ∈ (0, 1), δ m ∈ (0, 1), δ m < δM . δ m is the minimum value of the triggering threshold; δ M is the maximum value of the triggering threshold; ξ is the bilateral adaptive parameter.

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

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

[0085] Step 4, based on the open-loop load frequency control model, the closed-loop load frequency control model is obtained in combination with the ramping constraint. The ramping constraint includes the P2H device ramping constraint, the gas turbine generator ramping constraint and the energy storage battery ramping constraint.

[0086] Assuming that the island microgrid load frequency control adopts a state feedback control scheme, according to the event-triggered decision rule, within the adjacent two event-triggered intervals, since the control performance of the microgrid load frequency control has not decreased to below the preset level, the control command remains unchanged. Therefore, under ideal conditions, the control command of the microgrid load frequency control within the adjacent two triggering intervals is represented as:

[0087]

[0088] In the formula, K f is the control gain. is the transmission delay, d is the maximum transmission delay. The triggering interval is divided into a set i l h = t k h + lh. Wherein, η(t) = t - i l h is defined, from e(i l h) = x(i l h) - x(t k h) has x(t k h) = e(i l h) - e(il h) = x(t - η(t)) - e(i l h), thereby u(t) = K f [x(t - η(t)) - e(i l h)].

[0089] It is noted that the existing commercial P2H devices are generally subject to the chemical reaction rate, and in order to avoid the risk of explosion caused by the decline in hydrogen purity due to the rapid change in electrolysis power, it is necessary to strictly limit the electrolysis power ramping interval of the P2H device. Similarly, there is also the same ramping rate limit for the gas turbine generator and the energy storage battery. That is, the ramping constraints include P2H device ramping constraints, gas turbine generator ramping constraints, and energy storage battery ramping constraints. Among them:

[0090] The P2H device ramping constraint is expressed as: In the formula, represents the maximum ramping rate of the P2H device.

[0091] The gas turbine generator ramping constraint is expressed as: In the formula, represents the maximum ramping rate of the gas turbine generator device.

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

[0093] According to the above description, further 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 a saturation function, is a function for describing the degree of nonlinearity of saturation, The physical meaning of is to characterize the difference between the ideal control input and the actual input. The intersection of the function image and the horizontal axis is -u max and u max . Further define the function g(K f x(ilh)) = -λK f x(i l h), 0 ≤ λ ≤ 1. Thus The horizontal coordinates of the intersection of the function images of and g(K f x(i l h)) have two, respectively and and and

[0097] Therefore, for any positive definite matrix Π, there is always:

[0098]

[0099] Finally, based on the open-loop load frequency control model, 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-triggered decision rule and the closed-loop load frequency control model, the Lyapunov stability theory is used to obtain the closed-loop load frequency control scheme.

[0102] For example, based on the event-triggered decision rule and the closed-loop load frequency control model, the Lyapunov stability theory is used to obtain a set of linear matrix inequalities. According to the set of linear matrix inequalities, the performance weight matrix in the event-triggered decision rule and the control gain in the closed-loop load frequency control model are obtained, and then the closed-loop load frequency control scheme is obtained. Specifically, based on the event-triggered decision rule and the closed-loop load frequency control model, the Lyapunov stability theory is used to obtain a first set of linear matrix inequalities. Based on the contractive transformation technique and the first set of linear matrix inequalities, a second set of linear matrix inequalities is obtained. According to the second set of linear matrix inequalities, the control parameters of the event-triggered decision rule and the closed-loop load frequency control model are obtained. According to the control parameters, the event-triggered decision rule and the closed-loop load frequency control model, the 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 all greater than 0, and λ ∈ [0, 1]. I is the identity matrix. If there exist matrices X, Π and symmetric positive definite matrices P, Q, R and Φ that satisfy the first set of matrix inequalities, then the microgrid load frequency control system using the event-triggered rule is asymptotically stable under the bounded transmission delay [0, d] and has H∞ damping performance for external power disturbances. The first set of matrix inequalities is expressed as:

[0104]

[0105] In the formula, ψ ij represents the elements of the matrix, i = 1, 2,..., 8, j = 1, 2,..., 8. ψ 11 = Q - R + PA + A T P, ψ 12 = X T, ψ 13 = 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 = -Q-R, ψ 23 = R-X, 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 the nonlinear multiplicative relationship between the to-be-solved matrices K f , Π, P, etc. in the first matrix inequality set is difficult to be directly solved by using a linear matrix inequality solving method, a second linear matrix inequality set is obtained based on a contractive transformation technique and the first linear matrix inequality set.

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

[0108]

[0109] Θ ij denote the 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-triggered decision rule and the control parameters of the closed-loop load frequency control model, i.e. the performance weight matrix in the event-triggered decision rule and the control gain in the closed-loop load frequency control model, can be obtained. The control gain K f = ΓΛ -1 . Thus, according to the control parameters, the event-triggered decision rule and the closed-loop load frequency control model, the closed-loop load frequency control scheme can be obtained.

[0111] Step 6, real-time acquisition of the micro-grid load frequency deviation. The closed-loop load frequency control scheme is adopted, when the micro-grid load frequency deviation decreases, the control frequency of the closed-loop load frequency control scheme on the micro-grid load frequency is reduced. When the micro-grid load frequency deviation increases, the control frequency of the closed-loop load frequency control scheme on the micro-grid load frequency is increased, and the micro-grid load frequency is controlled to be stable.

[0112] Based on the same inventive concept, the application further provides an electric hydrogen production assisted island micro-grid load frequency control system for implementing the above-mentioned electric hydrogen production assisted island micro-grid load frequency control method. The system provides a solution to the implementation scheme as described in the above-mentioned method, and the specific limitations in the embodiments provided below can be referred to the limitations of the electric hydrogen production assisted island micro-grid load frequency control method described above, which will not be repeated here.

[0113] In one exemplary embodiment, an electric hydrogen production assisted island micro-grid load frequency control system is provided, comprising:

[0114] A load frequency variation module is configured to acquire the micro-grid load frequency deviation in real time.

[0115] An event triggering module is configured to determine the control frequency of the closed-loop load frequency control scheme on the micro-grid load frequency according to the micro-grid load frequency deviation.

[0116] A saturation constraint module is configured to control the load frequency of the micro-grid according to the closed-loop load frequency control scheme.

[0117] In one exemplary embodiment, to verify the effectiveness of the electric hydrogen production assisted island micro-grid load frequency control method, a relevant simulation model is built in the Matlab / Simulink environment. The P2H device is selected as an alkaline electrolytic cell, and the relevant simulation parameter settings are shown in Table 1. By comparing the closed-loop load frequency control scheme with and without the assistance of the P2H device, the effectiveness of the electric hydrogen production assisted island micro-grid load frequency control method in the application is verified.

[0118] Table 1 Simulation parameter setting table

[0119]

[0120]

[0121] The simulation results of the closed-loop load frequency control scheme with and without the assistance of the P2H device are shown in Table 2. By comparing the simulation results of the two, it can be found that the number of event triggering does not change greatly by adding the P2H device, but the closed-loop load frequency control scheme with the assistance of the P2H device makes the frequency deviation of the micro-grid output significantly decreased, the frequency deviation amplitude is decreased by 1.5%, and the frequency absolute value integral is decreased by 2.2%, which indicates that the closed-loop load frequency control of the island micro-grid with the assistance of the P2H device can further improve the stability of the micro-grid.

[0122] Table 2 Simulation result table

[0123] P2H device P2H device Trigger times 135 130 Frequency deviation amplitude / Hz 0.02177 0.02211 Adjustment time / s (5% of peak) 24.15 24.33 Frequency deviation absolute value integral / Hz-s 0.3091 0.3162

[0124] In an example embodiment, a computer device, which can be a server or a terminal, is provided, and an internal structure diagram of the computer device can be as shown in FIG. 1. Figure 4 The computer device includes a processor, a memory, an input / output interface (I / O) and a communication interface. 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. The processor of the computer device is configured 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 running the operating system and the computer program in the non-volatile storage medium. The database of the computer device is configured to store relevant data in the method for load frequency control of a hydrogen production assisted island micro-grid. The input / output interface of the computer device is configured to exchange information between the processor and external devices. The communication interface of the computer device is configured to communicate with external terminals through network connection. The computer program is executed by the processor to implement a method for load frequency control of a hydrogen production assisted island micro-grid.

[0125] Those skilled in the art can understand that Figure 4 the structure shown in FIG. 1 is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components. In an example embodiment, a computer device is provided, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0126] In an example embodiment, a computer readable storage medium is provided, which stores a computer program. The computer program is executed by a processor to implement the steps in the above method embodiments.

[0127] In an example embodiment, a computer program product is provided, which includes a computer program. The computer program is executed by a processor to implement the steps in the above method embodiments.

[0128] Those skilled 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. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to 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 storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration but not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0129] The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a blockchain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without being limited thereto.

[0130] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above embodiments are not described, however, as long as the combinations of the technical features do not exist contradictory, they should be considered as the scope of the present application.

[0131] The principles and implementation modes of the present application are described by applying specific examples in the present application. The above-mentioned embodiments are only used to help understand the method and its core idea of the present application; at the same time, for those skilled in the art, according to the idea of the present application, the specific implementation mode and application range will be changed. In conclusion, the content of the present application should not be understood as a limitation.

Claims

1. A method for controlling the load frequency of an islanded microgrid assisted by electric hydrogen production, characterized in that, The method for controlling the load frequency of an islanded microgrid assisted by hydrogen production includes: The microgrid operating parameters and the operating parameters of the equipment participating in the microgrid load frequency control are obtained; the operating parameters of the equipment participating in the microgrid load frequency control include: P2H equipment operating parameters, gas turbine generator operating parameters, and energy storage battery operating parameters. An open-loop load frequency control model is constructed based on the microgrid operating parameters and the operating parameters of the equipment participating in the microgrid load frequency control. A two-sided dynamic update mechanism is used to design the trigger threshold; based on the trigger threshold, an event triggering determination rule is designed; the trigger threshold is expressed as: δ(t) k h)=min{δ M ,max{δ m ,ξδ(t k-1 h)}};wherein, In the formula, δ(t) k h) is t = t k The event trigger 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 The minimum trigger threshold; δ M ξ is the maximum trigger threshold; ξ is the bilateral adaptive parameter. Based on the open-loop load frequency control model, a closed-loop load frequency control model is obtained by combining ramping constraints; the ramping constraints include ramping constraints for P2H equipment, ramping constraints for gas turbine generators, and ramping constraints for energy storage batteries. Based on the event triggering determination rule and the closed-loop load frequency control model, the closed-loop load frequency control scheme is obtained by adopting Lyapunov stability theory. Real-time acquisition of microgrid load frequency deviation; The closed-loop load frequency control scheme reduces the control frequency of the microgrid load frequency when the microgrid load frequency deviation decreases, and increases the control frequency of the microgrid load frequency when the microgrid load frequency deviation increases, thereby stabilizing the microgrid load frequency.

2. The method for controlling the load frequency of an islanded microgrid assisted by electro-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 operating parameters of the equipment participating in the microgrid load frequency control, including: Based on the operating parameters of the equipment involved in microgrid load frequency control, a frequency-electrolysis power response model for P2H equipment, a dynamic characteristic model for gas turbine generators, and an energy storage battery model are constructed respectively. Based on the frequency-electrolysis power response model of the P2H equipment, the dynamic characteristic model of the gas turbine generator, and the energy storage battery model, and combined with the microgrid operating parameters, a microgrid dynamic characteristic model is constructed. Based on the frequency-electrolysis power response model of the P2H equipment, the dynamic characteristic model of the gas turbine generator, the energy storage battery model, and the dynamic characteristic model of the microgrid, an open-loop load frequency control model is obtained by adopting frequency regulation participation conditions.

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

4. The method for controlling the load frequency of an islanded microgrid assisted by electro-hydrogen production according to claim 1, characterized in that, Based on the event triggering determination rule and the closed-loop load frequency control model, and using Lyapunov stability theory, the closed-loop load frequency control scheme includes: Based on the event triggering determination rule and the closed-loop load frequency control model, the first set of linear matrix inequalities is obtained using Lyapunov stability theory. A second set of linear matrix inequalities is obtained based on the congruence transformation technique and the first set of linear matrix inequalities; Based on the second set of linear matrix inequalities, the event triggering determination rule, and the closed-loop load frequency control model, a closed-loop load frequency control scheme is obtained.

5. The method for controlling the load frequency of an islanded microgrid assisted by electro-hydrogen production according to claim 4, characterized in that, Based on the second set of linear matrix inequalities, the event triggering determination rule, and the closed-loop load frequency control model, a closed-loop load frequency control scheme is obtained, including: Based on the second set of linear matrix inequalities, the event triggering determination rule and the control parameters of the closed-loop load frequency control model are obtained; Based on the control parameters, the event triggering determination rules, and the closed-loop load frequency control model, a closed-loop load frequency control scheme is obtained.

6. A frequency control system for an islanded microgrid load assisted by electric hydrogen production, characterized in that, The hydrogen-powered islanded microgrid load frequency control system is used to implement the hydrogen-powered islanded microgrid load frequency control method as described in claim 1, wherein the hydrogen-powered islanded microgrid load frequency control system includes: The load frequency variation module is used to acquire the microgrid load frequency deviation in real time. The event triggering module is used to determine the control frequency of the microgrid load frequency by the closed-loop load frequency control scheme based on 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.

7. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the electric hydrogen production-assisted islanded microgrid load frequency control method according to any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the load frequency control method for an islanded microgrid assisted by electro-hydrogen production, as described in any one of claims 1-5.

9. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the load frequency control method for an islanded microgrid assisted by electro-hydrogen production, as described in any one of claims 1-5.

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