Virtual power plant power tracking control optimization method and system considering instantaneous power support, equipment and medium

Abstract

The invention discloses a virtual power plant power tracking control optimization method, system, equipment and medium considering instantaneous power support, and the method comprises the steps: obtaining a dynamic output model of distributed energy through constructing a target virtual power plant architecture based on the distributed energy, determining a dynamic output transfer function of the distributed energy, and optimizing the power tracking control of the distributed energy; formulating a power tracking strategy of the distributed energy, compensating unmatched generating capacity by using droop power, and sharing the unmatched generating capacity to the online distributed energy; the output of a proportional-integral controller of the total generating capacity of a virtual power plant is used as dynamic frequency compensation to be compensated to each distributed energy reference frequency so as to compensate mismatched power deviation and realize instantaneous power support, and an open-loop transfer function of POC power compensation is introduced by standardizing control parameters so as to realize instantaneous power support. And the cross frequency of the open-loop transfer function is limited, the parameters of the optimal power tracking strategy are determined, the performance of the virtual power plant in instantaneous power tracking is improved, the power deviation is reduced, and the stability and reliability of the system are enhanced.

Description

Technical Field

[0001] The present invention relates to the field of virtual power plant control, and in particular to a virtual power plant power tracking control optimization method, system, equipment and medium taking into account instantaneous power support. Background Art

[0002] In modern power systems, with the widespread application of renewable energy, the operation of power systems has become increasingly complex. The power generation of renewable energy such as wind power and solar power is highly volatile and uncertain, which brings new challenges to the stability of the power system and the reliability of power supply. In order to meet these challenges, Virtual Power Plant (VPP), as an emerging power system management model, has gradually received widespread attention and application.

[0003] Virtual power plants can effectively balance electricity supply and demand and improve the overall stability and economy of the power system by integrating and optimizing the scheduling of different types of resources such as distributed energy resources, demand response resources, and energy storage equipment. However, in actual operation, due to the high volatility of renewable energy generation and sudden changes in power system load, the support and tracking of instantaneous power has become the main challenge facing virtual power plants. The ability to support instantaneous power is the key to the stable operation of virtual power plants. Instantaneous power fluctuations may come from fluctuations in renewable energy generation, sudden changes in load, or disturbances within the power system. Therefore, virtual power plants need to have the ability to respond quickly to ensure accurate tracking and regulation of instantaneous power. Summary of the invention

[0004] Purpose of the invention: The present invention aims to provide a virtual power plant power tracking control optimization method that ensures that the virtual power plant can achieve accurate power regulation and system stability maintenance when facing instantaneous power fluctuations; another purpose of the present invention is to provide a virtual power plant power tracking control optimization system, equipment and medium that takes instantaneous power support into consideration.

[0005] Technical solution: The virtual power plant power tracking control optimization method considering instantaneous power support described in the present invention includes the following steps:

[0006] Build a target virtual power plant architecture based on distributed energy;

[0007] Obtain a dynamic output model of distributed energy in the target virtual power plant;

[0008] Determine the dynamic output transfer function of distributed energy in the target virtual power plant;

[0009] Develop power tracking strategies for distributed energy resources in target virtual power plants;

[0010] Determine the parameters of the power tracking strategy.

[0011] Furthermore, in the target virtual power plant architecture based on distributed energy, distributed energy includes battery energy storage systems, electric vehicles, wind power and photovoltaics. Each distributed energy is connected to the virtual power plant through a common coupling point PCC, and the virtual power plant is connected to the public power grid through a public connection point POC; the operator determines the command based on the collected power output, node voltage and grid frequency of the distributed energy, and sends the command to the distributed energy through a two-way communication system.

[0012] Furthermore, the dynamic output model of distributed energy in the target virtual power plant is as follows:

[0013] Considering the grid construction control and grid following control of distributed energy, the output dynamic power P of distributed energy is

[0014]

[0015] δ i =∫ω i -ω g (2)

[0016] Among them, P i * is the reference power of the ith distributed energy source, is the derivative of the angular frequency of the distributed energy, ω * is the reference frequency; ω g It is the grid frequency detected by the phase-locked loop PLL at its PCC or the grid-connected frequency centrally detected by the PMU at the virtual power plant POC; ω i is the distributed energy frequency; K d，i is the droop gain, inertia coefficient and damping coefficient of the i-th distributed energy source; δ i is the phase difference between the voltage of the i-th distributed energy source PCC and POC; in the grid control, M i and D i is the control parameter. In the network control, M i and D i is the equivalent value of the PLL parameter;

[0017] If n distributed energy resources in the virtual power plant use POC as the observation point, the n distributed energy resources are represented by the Thevenin equivalent circuit and connected in parallel; the active power P provided by the i-th distributed energy resource to the POC is i for

[0018]

[0019] Among them, V poc is the POC voltage; E i is the voltage of the ith distributed energy source at the PCC, lg,i is the Thevenin equivalent impedance of the i-th distributed energy source.

[0020] Furthermore, the dynamic output transfer function of distributed energy in the target virtual power plant is as follows:

[0021] By Laplace transforming equations (1) and (2), we can obtain:

[0022]

[0023] Among them, G P,i (s) is the transfer function of the dynamic output power of distributed energy, ΔP i =P i -P i * , Δδ i is the power change ΔP i The phase change at the PCC caused by is, and s is the frequency domain transmission factor;

[0024] Calculate Δδ for equation (3) i The differential of , we get the transfer function H from the phase change at the distributed energy PCC to the power change at the virtual power plant POC i (s)

[0025]

[0026] Among them, R i is the equivalent resistance of the ith distributed energy source, X i is the equivalent reactance of the ith distributed energy source, L i is the equivalent inductance of the ith distributed energy source, a 1 、a 2 、a 3 is the coefficient.

[0027] Furthermore, the coefficient a 1 、a 2 、a 3 The following conditions are met:

[0028] a 1 =U g L i 2 (R i sinδ i +X i cosδ i )-E i L i 2 X i

[0029] a 2 =2U gR i L i (R i sinδ i +X i cosδ i )-2E i R i L i X i

[0030] a 3 =U g (R i 2 +X i 2 )(R i sinδ i +X i cosδ i )

[0031] Among them, U g is the grid-side voltage amplitude.

[0032] Furthermore, the power tracking strategy of distributed energy in the target virtual power plant is as follows:

[0033] Subtract the planned total power generation of the virtual power plant from the actual total power generation to obtain the total power generation error ΔP of the virtual power plant to ;

[0034] The total power generation error of the virtual power plant ΔP to Sent to the proportional-integral controller to obtain the frequency error compensation Δω s ;

[0035]

[0036] Δω s =K ps ΔP to +∫K is ΔP to (7)

[0037] ω * =ω n +Δω s (8)

[0038] Among them, P * to is the planned total power generation of the virtual power plant, P to is the actual virtual power plant generation measured at the POC, ω n is the rated frequency, K ps and K is is the proportional-integral coefficient;

[0039] When an unexpected event occurs in the virtual power plant, each distributed energy source will control the redistribution of the power reference, and the mismatched power will be compensated by increasing the reference power, so that the reference frequency returns to the nominal value and achieves instantaneous power support.

[0040] Further, the parameters of the power tracking strategy are determined. The specific steps are as follows:

[0041] The proposed power tracking strategy of the virtual power plant with distributed energy is designed to quickly reach the planned power generation after an emergency event within the virtual power plant, while performing primary control over the distributed energy;

[0042] Standardize the control parameters and perform the Laplace transform of equation (6-8) to obtain the transfer function G of the proportional-integral controller. T (s):

[0043]

[0044] Multiplying equation (4) and equation (5) together, we get the power mismatch of the ith distributed energy source from the POC, and the POC gets the open-loop transfer function G of power compensation: U,i (s)

[0045] G U,i (s) = G T (s)·K d,i ·G P,i (s)·H i (s) (10)

[0046] The line resonance gain is H i (s=0), then G U,i (s) crossover frequency ω co,i for

[0047]

[0048] Among them, b 1 =H i (s=0)K d,i K ps ; b 2 =H i (s=0)K d,i K is ;

[0049] Crossover frequency ω co,i satisfy:

[0050]

[0051] When the frequency is less than K is / K psWhen the frequency is greater than K, the phase changes from -180° to -90° and the slope changes from -40dB to -20dB. is / K ps and less than D i / M i Afterwards, the phase changes from -90° to -180° and the slope changes from -20dB to -40dB.

[0052] The virtual power plant power tracking control optimization system considering instantaneous power support of the present invention comprises:

[0053] Build a target virtual power plant architecture based on distributed energy;

[0054] A model building module, used for building a dynamic output model of distributed energy in a target virtual power plant based on a target virtual power plant architecture of distributed energy;

[0055] The decision-making solution module is used to determine the dynamic output transfer function of distributed energy in the target virtual power plant according to the dynamic output model of distributed energy in the target virtual power plant; formulate the power tracking strategy of distributed energy in the target virtual power plant; and solve the parameters of the optimal power tracking strategy.

[0056] The computer device of the present invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the steps of the above method are implemented when the processor executes the computer program.

[0057] The computer-readable storage medium of the present invention stores a computer program thereon, and the computer program implements the steps of the above method when executed by a processor.

[0058] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages: 1. The optimization method of the present invention obtains the dynamic output model of distributed energy in the target virtual power plant, determines the dynamic output transfer function of distributed energy in the target virtual power plant, formulates the power tracking strategy of distributed energy in the target virtual power plant, uses droop power to compensate for the mismatched power generation, and shares it with the online distributed energy; uses the proportional-integral controller output of the total power generation of the virtual power plant as dynamic frequency compensation, and compensates to each distributed energy reference frequency respectively to compensate for the mismatched power deviation and realize instantaneous power support; 2. The present invention introduces the open-loop transfer function of POC power compensation by standardizing control parameters, and limits the crossover frequency of the open-loop transfer function to determine the parameters of the optimal power tracking strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 It is a schematic diagram of a virtual power plant architecture based on distributed energy in the present invention;

[0060] Figure 2 This is a block diagram of the power tracking control optimization method of a virtual power plant of the present invention;

[0061] Figure 3 This is a schematic diagram of the structure of a virtual power plant used for experimental testing of the present invention;

[0062] Figure 4 A line graph of the active power of each distributed energy source of the present invention;

[0063] Figure 5 A line graph of the reference frequency of the virtual power plant of the present invention;

[0064] Figure 6 It is a line graph of the reference frequency of the virtual power plant under unstable operating conditions of the present invention. DETAILED DESCRIPTION

[0065] The present invention will be further described below in conjunction with the accompanying drawings.

[0066] The virtual power plant power tracking control optimization method considering instantaneous power support of the present invention comprises the following steps:

[0067] (1) Building a target virtual power plant architecture based on distributed energy

[0068] The target virtual power plant includes: battery energy storage system, electric vehicles, wind power and photovoltaics; each distributed energy is connected to the virtual power plant at the point of common coupling (PCC), and the entire virtual power plant is connected to the public grid at the point of common connection (POC); the operator collects information from measuring instruments (such as: power output of distributed energy, node voltage, grid frequency, etc.) and sends commands to distributed energy through a two-way communication system (such as: reference voltage, frequency and power reference, etc.); the main control is implemented in a separate distributed energy unit to synchronize with the system and provide fast frequency and voltage response.

[0069] (2) According to the target virtual power plant architecture based on distributed energy, a dynamic output model of distributed energy in the target virtual power plant is obtained.

[0070] The control of distributed energy can be divided into grid control and grid-following control. For a reasonably designed distributed energy, its output dynamics can be simplified and summarized as follows:

[0071]

[0072] δ i =∫ω i -ω g (2)

[0073] Among them, P i *is the reference power of the ith distributed energy source, ω * is the reference frequency, both of which are set by the virtual power plant operator; ω g It is the grid frequency detected by the phase-locked loop (PLL) at its PCC, or the grid-connected frequency centrally detected by the PMU at the POC of the virtual power plant; ω i is the distributed energy frequency; K d 、M i and D i is the droop gain, inertia coefficient and damping coefficient of the ith distributed energy source, corresponding to the droop gain. i is the phase difference between the voltage of the i-th distributed energy source PCC and POC; M i and D i is a control parameter, and in network control M i and D i are equivalent values ​​related to PLL parameters;

[0074] If it is assumed that there are n distributed energy resources in the virtual power plant and the POC is used as the observation point, these distributed energy resources can be represented by the Thevenin equivalent circuit and they are connected in parallel; for each of them, the active power it provides to the POC is:

[0075]

[0076] Among them, V poc is the POC voltage; E i is the voltage of the ith distributed energy source at the PCC, l g,i is the Thevenin equivalent impedance of the i-th distributed energy source.

[0077] (3) According to the dynamic output model of distributed energy in the target virtual power plant, the dynamic output transfer function of distributed energy in the target virtual power plant is determined.

[0078] In order to analyze the stability of the proposed control, the Laplace transform of equations (1) and (2) is:

[0079]

[0080] Among them, ΔP i =P i -P i * , Δδ i is the power change ΔP i The phase change at the PCC caused by

[0081] Calculate Δδ for equation (3) i By taking the derivative of , we get the transfer function from the phase change at the distributed energy source PCC to the power change at the virtual power plant POC.

[0082]

[0083] The coefficient a in the above formula (5) is 1 、a 2 and a 3 The following conditions are met:

[0084] a 1 =U g L i 2 (R i sinδ i +X i cosδ i )-E i L i 2 X i

[0085] a 2 =2U g R i L i (R i sinδ i +X i cosδ i )-2E i R i L i X i

[0086] a 3 =U g (R i 2 +X i 2 )(R i sinδ i +X i cosδ i );

[0087] The above equations (4) and (5) are the transfer functions of the i-th distributed energy source from its reference power change to its output power change.

[0088] (4) Develop a power tracking strategy for distributed energy in the target virtual power plant.

[0089] The core of the power tracking strategy for building a virtual power plant of distributed energy is to use droop power to compensate for the mismatched power generation and share it with online distributed energy resources; the proportional-integral controller output of the total power generation of the virtual power plant is used as dynamic frequency compensation to compensate for the reference frequency of each distributed energy resource to compensate for the mismatched power deviation;

[0090] like Figure 3 Specifically, first, the planned total power generation of the virtual power plant is subtracted from the actual total power generation to obtain the total power generation error of the virtual power plant, as shown in formula (6); then, the total power generation error of the virtual power plant is sent to the proportional integral controller to obtain the frequency error compensation Δω s , see formula (7); further, the rated frequency ω n and frequency error compensation Δω s Add them together, see formula (8), and multiply them by the droop gain K of the i-th distributed energy source di , and then combine equation (4) and equation (5) to get the actual power output of the i-th distributed energy source;

[0091]

[0092] ω s =K ps ΔP to +∫K is ΔP to (7)

[0093] ω * =ω n +Δω s (8)

[0094] Among them, P * to is the planned total power generation of the virtual power plant, P to is the actual virtual power plant generation measured at the POC, ω n is the rated frequency, K ps and K is is the proportional-integral coefficient.

[0095] In the above control link, when an unexpected event occurs in the virtual power plant, such as a distributed energy outage, the output power of the virtual power plant at the POC will change, and the proposed control will be activated to increase the frequency reference and force the distributed energy to increase the reduced power; at this time, each distributed energy will control the redistribution of the power reference, and the unmatched power will be compensated by increasing the reference power, and then the reference frequency will be restored to the nominal value to achieve instantaneous power support

[0096] (5) Determine the parameters of the power tracking strategy.

[0097] The proposed power tracking strategy of the virtual power plant with distributed energy is designed to quickly reach the planned power generation after an emergency event within the virtual power plant, while performing primary control over the distributed energy;

[0098] The parameter design of the proposed control is standardized below, and the Laplace transform of equation (6-8) is:

[0099]

[0100] Then, the open-loop transfer function of the ith distributed energy source from the power mismatch at the POC to the power compensation of the POC through the proposed control and the master control is:

[0101] G U,i (s) = G T (s)·K d,i ·G P,i (s)·H i (s) (10)

[0102] The proposed control uses a lower frequency and the line resonance can be simplified to the gain H i (s=0), then G U,i The crossover frequency of (s) can be calculated as:

[0103]

[0104] Among them, b 1 =H i (s=0)K d,i K ps ; b 2 =H i (s=0)K d,i K is

[0105] There are five poles in formula (10), namely: 2 at 0 and 2 at ω g , 1 in D i / M i , 1 zero in K is / K ps ; Therefore, the initial slope of the gain starting from -180° is -40dB;

[0106] In order to ensure that the transfer function (Equation (10)) is stable, its crossover frequency (Equation (11)) should be located K after zero. is / K ps and pole D i / M i Before, that is, satisfy:

[0107]

[0108] At this time, when the frequency is less than K is / K ps When the frequency is greater than K, the phase changes from -180° to -90° and the slope changes from -40dB to -20dB. is / K ps and less than D i / Mi Afterwards, the phase changes from -90° to -180° and the slope changes from -20 dB to -40 dB. In summary, formula (15) can ensure satisfactory phase margin and amplitude margin at the crossover frequency.

[0109] Based on the above principles, the proportional-integral controller parameter K of the proposed control strategy can be realized. ps and K is design and ensure its stability.

[0110] Real-time simulation solved in Matlab / Simulink is used to verify the effectiveness of the proposed dispatch power tracking control. Figure 4 As shown in Figure 1, the tested virtual power plant system consists of four distributed energy resources connected to a 50Hz / 10kV infinite bus. Table 1 gives the parameters and settings. The converter parameters of all distributed energy resources are the same. The PI parameters of the converter current control are 0.0093 / 10.41, and the LC filter impedance is 0.5H / 2.77μF.

[0111] Table 1 Distributed energy parameter settings

[0112]

[0113]

[0114] like Figure 5 As shown, the proposed control is verified to track the power of the virtual power plant dispatch, where distributed energy 4 is lost at 2 seconds and the secondary control reallocates the power reference at 4 seconds.

[0115] The planned power generation of the virtual power plant is 1.4MW, and the initial powers of DERs 1-4 are 5.0MW, 2.5MW, 3.5MW and 3MW. After DER 4 is lost, the reference frequency increases immediately due to the proportional part of the power mismatch caused by the proposed control. Then, DERs 1-3 increase their power output proportionally according to their descent gains until the actual power generation of the virtual power plant approaches the planned value again and the frequency reference stabilizes at 50.3Hz; until 4 seconds, the power reference of DERs 1-3 is reallocated in the virtual power plant operator to 6MW, 3.5MW and 4.5MW to meet the planned power generation, the actual power of the virtual power plant further increases beyond the planned value, and the reference frequency reduction is activated; finally, the reference frequency is restored to 50Hz, and DERs 1-3 output power at the updated reference value.

[0116] like Figure 6 As shown, the stability of the proposed control is verified relative to its stability formula (15), where K is / K psis 4.4286. The crossover frequency of each distributed energy source satisfies the stability condition. When formula (15) is violated, the proposed control will introduce instability into the distributed energy source. At this time, K is / K ps is 68.5, and the distributed energy becomes unstable; although in theory only distributed energy 4 shows instability, the entire virtual power plant gradually loses stability, such as Figure 6 This is because the oscillating power delivered from DERs to the POC introduces the proposed control, causing the reference frequency to oscillate, and then the entire virtual power plant becomes unstable.

Claims

1. A virtual power plant power tracking control optimization method considering instantaneous power support, characterized in that: The following steps are involved: Build a target virtual power plant architecture based on distributed energy; Obtain a dynamic output model of distributed energy in the target virtual power plant; Determine the dynamic output transfer function of distributed energy in the target virtual power plant; Develop power tracking strategies for distributed energy resources in target virtual power plants; Determine the parameters of the power tracking strategy.

2. The virtual power plant power tracking control optimization method considering instantaneous power support according to claim 1 is characterized in that: In the target virtual power plant architecture based on distributed energy, distributed energy includes battery energy storage systems, electric vehicles, wind power and photovoltaics. Each distributed energy is connected to the virtual power plant through a common coupling point PCC, and the virtual power plant is connected to the public power grid through a public connection point POC; the operator determines the command based on the collected power output, node voltage and grid frequency of the distributed energy, and sends the command to the distributed energy through a two-way communication system.

3. The virtual power plant power tracking control optimization method considering instantaneous power support according to claim 1 is characterized in that: The dynamic output model of distributed energy in the target virtual power plant is as follows: Considering the grid construction control and grid following control of distributed energy, the output dynamic power P of distributed energy is d i =∫ω i -oh g (2) Among them, P i * is the reference power of the ith distributed energy source, is the derivative of the angular frequency of the distributed energy, ω * is the reference frequency; ω g It is the grid frequency detected by the phase-locked loop PLL at its PCC or the grid-connected frequency centrally detected by the PMU at the virtual power plant POC; ω i is the distributed energy frequency; K d，i is the droop gain, inertia coefficient and damping coefficient of the ith distributed energy source; δ i is the phase difference between the voltage of the i-th distributed energy source PCC and POC; in the grid control, M i and D i is the control parameter. In the network control, M i and D i is the equivalent value of the PLL parameter; If n distributed energy resources in the virtual power plant use POC as the observation point, the n distributed energy resources are represented by the Thevenin equivalent circuit and connected in parallel; the active power P provided by the i-th distributed energy resource to the POC i for Among them, V poc is the POC voltage; E i is the voltage of the ith distributed energy source at the PCC, l g,i is the Thevenin equivalent impedance of the i-th distributed energy source.

4. The virtual power plant power tracking control optimization method considering instantaneous power support according to claim 3 is characterized in that: The dynamic output transfer function of distributed energy in the target virtual power plant is as follows: By Laplace transforming equations (1) and (2), we can obtain: Among them, G P,i (s) is the transfer function of the dynamic output power of distributed energy, ΔP i =P i -P i * , Δδ i is the power change ΔP i The phase change at the PCC caused by is, and s is the frequency domain transmission factor; Calculate Δδ for equation (3) i The differential of , we get the transfer function H from the phase change at the distributed energy PCC to the power change at the virtual power plant POC i (s) Among them, R i is the equivalent resistance of the ith distributed energy source, X i is the equivalent reactance of the ith distributed energy source, L i is the equivalent inductance of the ith distributed energy source, and a1, a2, and a3 are coefficients.

5. The virtual power plant power tracking control optimization method considering instantaneous power support according to claim 4 is characterized in that: The coefficients a1, a2, and a3 satisfy the following conditions: a1=U g L i 2 (R i sinδ i +X i cosδ i )-E i L i 2 X i a2=2U g R i L i (R i sinδ i +X i cosδ i )-2E i R i L i X i a3=U g (R i 2 +X i 2 )(R i sinδ i +X i cosδ i ) Among them, U g is the grid-side voltage amplitude.

6. The virtual power plant power tracking control optimization method considering instantaneous power support according to claim 5 is characterized in that: The power tracking strategy of distributed energy in the target virtual power plant is as follows: Subtract the planned total power generation of the virtual power plant from the actual total power generation to obtain the total power generation error ΔP of the virtual power plant to ; The total power generation error of the virtual power plant ΔP to Sent to the proportional-integral controller to obtain the frequency error compensation Δω s ; Give s =K ps ΔP to +∫K is ΔP to (7) oh * =ω n +See s (8) Among them, P * to is the planned total power generation of the virtual power plant, P to is the actual virtual power plant generation measured at the POC, ω n is the rated frequency, K ps and K is is the proportional-integral coefficient; When an unexpected event occurs in the virtual power plant, each distributed energy source will control the redistribution of the power reference, and the mismatched power will be compensated by increasing the reference power, so that the reference frequency returns to the nominal value and achieves instantaneous power support.

7. The virtual power plant power tracking control optimization method considering instantaneous power support according to claim 6 is characterized in that: Determine the parameters of the power tracking strategy. The specific steps are as follows: The proposed power tracking strategy of the virtual power plant with distributed energy is designed to quickly reach the planned power generation after an emergency event within the virtual power plant, while performing primary control over the distributed energy; Standardize the control parameters and perform the Laplace transform of equation (6-8) to obtain the transfer function G of the proportional-integral controller. T (s): Multiplying equation (4) and equation (5) together, we get the power mismatch of the ith distributed energy source from the POC, and the POC gets the open-loop transfer function G of power compensation: U,i (s) G U,i (s)=G T (s)·K d,i ·G P,i (s)·H i (s) (10) The line resonance gain is H i (s=0), then G U,i (s) crossover frequency ω co,i for Where b1 = H i (s=0)K d,i K ps ; b2=H i (s=0)K d,i K is ; Crossover frequency ω co,i satisfy: When the frequency is less than K is / K ps When the frequency is greater than K, the phase changes from -180° to -90° and the slope changes from -40dB to -20dB. is / K ps and less than D i / M i Afterwards, the phase changes from -90° to -180° and the slope changes from -20dB to -40dB.

8. A virtual power plant power tracking control optimization system considering instantaneous power support, characterized in that: include: Build a target virtual power plant architecture based on distributed energy; A model building module, used for building a dynamic output model of distributed energy in a target virtual power plant based on a target virtual power plant architecture of distributed energy; The decision-making solution module is used to determine the dynamic output transfer function of distributed energy in the target virtual power plant according to the dynamic output model of distributed energy in the target virtual power plant; formulate the power tracking strategy of distributed energy in the target virtual power plant; and solve the parameters of the optimal power tracking strategy.

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

Images