Photovoltaic equivalent inertia evaluation method based on measurement data of synchronous generator in region

Abstract

The invention discloses a photovoltaic equivalent inertia evaluation method based on measurement data of a synchronous generator in a region, and belongs to the field of power systems, and the method comprises the steps: carrying out the motor partitioning of a power system based on the electrical distance between the nodes in the generator; performing node partitioning on the power system based on the linear relationship between the generator frequency and the node frequency; measuring data of a synchronous generator in a photovoltaic area are collected, and the overall equivalent inertia of the area is evaluated according to the measuring data of the synchronous generator in the area; and calculating the equivalent inertia of the photovoltaic equipment by using the regional overall equivalent inertia and the regional synchronous generator inertia. According to the invention, the equivalent inertia of all photovoltaic devices in the system can be evaluated at the same time, the required evaluation data is reduced, and the accuracy of the evaluation process is ensured. Through the method, the engineering practicability of photovoltaic inertia evaluation can be improved, and an important reference is provided for frequency control and stable operation of a power system.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a photovoltaic equivalent inertia evaluation method based on regional synchronous generator measurement data. Background Art

[0002] With the rapid development of new energy power generation technology, especially the large-scale application of photovoltaic power generation technology, the structure and operating characteristics of the power system have changed significantly. Compared with traditional synchronous generators, photovoltaic power generation systems do not have physical inertia in the traditional sense without virtual inertia control. At present, the gradual increase in photovoltaic penetration will lead to a decrease in system inertia, resulting in a decrease in the system's ability to respond to power disturbances, thereby affecting the system's frequency stability and reliability, and bringing new challenges to the frequency stability of the power system.

[0003] In the prior art, the assessment based on large disturbance events is currently the most widely used assessment method, which uses the power and frequency data after the disturbance to assess the inertia. According to the assessment object, the inertia assessment method can be divided into the overall system inertia assessment and the photovoltaic equipment inertia assessment. In the assessment method with photovoltaic power generation equipment as the assessment object, the existing research mostly defines the equivalent inertia of photovoltaic equipment by analogy with the swing equation of the synchronous motor. In the prior art, the change of photovoltaic DC voltage is analogized to the change of the rotor speed of the synchronous generator, and the theoretical inertia of the photovoltaic single-machine equipment when the DC capacitor is used as the energy source is derived from the mechanism, but there is a lack of simulation comparison between the theoretical inertia and the actual inertia. In the prior art, for a single unit or station, the inertia support capacity is quantified based on the relationship between the unit frequency modulation energy and the change in frequency. In addition, some prior arts use the node inertia at the photovoltaic grid-connected point as the equivalent inertia of a single photovoltaic device, but this method has certain errors. This is because the node inertia is a quantitative representation of the system's ability to hinder frequency changes at a single node, which is essentially the inertia support of the node by the overall inertia resources of the system. Summary of the invention

[0004] The present invention provides a photovoltaic equivalent inertia evaluation method based on the measurement data of synchronous generators in a region, which can provide the actual inertia of photovoltaic equipment under virtual inertia control for the power system operation and dispatching department, and provide an important reference for the frequency control and stable operation of the power system, belonging to the field of power system safety and stability analysis.

[0005] An embodiment of the present invention provides a photovoltaic equivalent inertia evaluation method based on regional synchronous generator measurement data, comprising the following steps:

[0006] Step 1: partition the power system into motors based on the electrical distance between nodes within the generator;

[0007] Step 2: partition the power system nodes based on the linear relationship between generator frequency and node frequency;

[0008] Step 3: Collect the measurement data of synchronous generators in the photovoltaic area, and evaluate the overall equivalent inertia of the area based on the measurement data of synchronous generators in the area;

[0009] Step 4: Calculate the equivalent inertia of the PV equipment using the regional overall equivalent inertia and the regional synchronous generator inertia.

[0010] Optionally, in one embodiment of the present invention, step 1 specifically includes:

[0011] Step 1-1, collecting transient reactances of all synchronous generators in the power system and system line parameters to generate a system admittance matrix;

[0012] Step 1-2, based on the system admittance matrix, the transient reactance inside the generator is considered to generate the admittance augmented matrix Y S :

[0013]

[0014] The power system contains M+N network nodes, M is the number of nodes at the generator end, and N is the number of other nodes; g is the node inside the generator, g∈[1,M]; m is the node outside the generator end, m∈[1,M]; n is the other node in the power system, n∈[M+1,M+N]; Y gg , Y gm , Y mm , Y mn , Y nn are the self-admittance and mutual-admittance of the internal nodes, external nodes and other nodes of the generator, respectively. m is the diagonal array of transient reactance of the generator, Y lm and Y ln are the equivalent earth admittances formed by the loads at the generator node and other nodes respectively; the admittance augmented matrix Y S The middle zero position indicates that there is no direct connection between nodes;

[0015] Step 1-3, simplify the admittance augmentation matrix and determine the optimal number of clusters based on the elbow method:

[0016] For the admittance augmentation matrix Y S Perform kron simplification and shrink to an M×M matrix Y g , matrix Y gThe i-th row and j-th column of represents the admittance from the node in the i-th generator to the node in the j-th generator. The larger the admittance, the closer the electrical connection between the generators, which can be regarded as the correlation between the i-th generator and the j-th generator. The elbow method based on the sum of squared errors is used to confirm the optimal number of clusters of the power system, where the sum of squared errors is defined as the sum of squares of the differences between each sample point and the average value after clustering. The smaller the sum of squared errors, the better the clustering result. The calculation formula is:

[0017]

[0018] Among them, C i is the i-th cluster, p is C i The sample points in m i It is C i The sample mean of S SSE For the image with cluster number k, the image is elbow-shaped, and the k value corresponding to the elbow is the optimal cluster number k opt ;

[0019] Steps 1-4, based on the optimal number of clusters, the phase admittance augmentation matrix Y S Use K-means clustering method to complete motor partitioning.

[0020] Optionally, in one embodiment of the present invention, step 2 specifically includes:

[0021] Step 2-1, derive the linear relationship between generator frequency and node frequency:

[0022] The network node voltage is represented by the potential node voltage inside the generator, that is:

[0023] U net =RU e

[0024] Among them, U e and U net are the voltage vectors of the potential nodes in the generator and the voltage vectors of the network nodes, respectively, and R is the correlation matrix between the voltages of the potential nodes in the generator and the voltages of the network nodes:

[0025]

[0026] If a failure occurs at node k, based on U net =RU e In the k-related expansion, the fault point voltage is expressed as the internal potential of each generator, and the voltage angle of node k is obtained as follows:

[0027]

[0028] Where V k 、V jare the voltage amplitudes at node k and motor j, respectively, k , δ j are the phase angles corresponding to the potentials of node k and generator j respectively; r kj is the element in the correlation matrix R that represents the voltage relationship between node k and generator j. After simplification, the voltage angle of node k is obtained as follows:

[0029]

[0030] The voltage angle can be extended to the frequency relationship, that is:

[0031]

[0032] In the formula, f k 、f j are the frequencies of node k and generator j, respectively;

[0033] Step 2-1, based on the linear relationship between generator frequency and node frequency, each node in the power system is divided into the generator with the largest correlation coefficient with its own node, and then allocated to the corresponding area to complete the node partitioning.

[0034] Optionally, in one embodiment of the present invention, step 3 specifically includes:

[0035] Step 3-1, based on the motor partitioning and node partitioning results, collect the rated parameters and operating data of the photovoltaic area, such as the operating angular frequency of the synchronous generator and the regional inertia center frequency;

[0036] Taking the region as the object, the system frequency response model regional inertia center frequency ω acoi The definition is as follows:

[0037]

[0038] Where n G,area Represents the number of synchronous generators in the area after partitioning;

[0039] Step 3-2, evaluate the regional equivalent inertia based on the disturbance size and the regional inertia center frequency;

[0040] After adopting virtual inertia control, the frequency model of the photovoltaic power area is analyzed, the photovoltaic equipment and the feedback loop of the interconnection line with other areas are added, and a simplified system frequency response model of the photovoltaic area under disturbance is established;

[0041] According to the definition of the system frequency response model, the overall equivalent inertia H of the region containing photovoltaics area It is defined by the ratio of the sum of the disturbance power and the tie line power and the rate of change of the inertial center frequency:

[0042]

[0043] Where ΔP d is the disturbance value of the power grid, ΔP T It is the change in transmission power of the inter-regional interconnection line at the moment of disturbance.

[0044] Optionally, in one embodiment of the present invention, step 4 specifically includes:

[0045] Step 4-1, collect the rated capacity and rated inertia time constant of all synchronous generators in the area, where the rated capacity and rated inertia time constant of the jth synchronous generator are S j and H j , calculate the equivalent inertia H of the synchronous generator in the area g,a ;

[0046] Step 4-2: Evaluate the equivalent inertia of the photovoltaic equipment under the set parameters based on the measurement data of the synchronous generators in the area;

[0047] When the equivalent damping coefficient D of the synchronous motor is ignored, the equivalent inertia time constant H of the synchronous generator in the region g,a It is expressed as follows:

[0048]

[0049] Where ΔP m,a is the mechanical power variation of the synchronous motor in the region, ΔP a is the power difference allocated to the synchronous motors in the area, ΔP vir Power support provided for photovoltaic virtual inertia control at disturbance instant;

[0050] Considering that the mechanical power of the synchronous generator cannot change suddenly at the beginning of the disturbance, ΔP m,a is approximately 0, so the time constant H of the equivalent inertia of the photovoltaic equipment in the area pv It is expressed as:

[0051]

[0052] For actual power systems, when PV adopts virtual inertia control and the rated inertia time and rated capacity of regional synchronous generators are known, the equivalent inertia time constant of PV equipment can be finally obtained according to the above formula.

[0053] The photovoltaic equivalent inertia evaluation method based on the measurement data of synchronous generators in the region according to the embodiment of the present invention can evaluate the equivalent inertia provided by photovoltaic equipment under virtual inertia control by using less synchronous generator measurement data. By introducing the partitioning idea, the power system is divided into multiple regions with similar frequency characteristics, and then the regional inertia is evaluated. The equivalent inertia of the photovoltaic equipment is obtained by subtracting the inertia of the regional synchronous generator from the overall inertia of the region. This method can provide the actual inertia of the photovoltaic equipment under virtual inertia control to the power system operation and dispatching department, and provide an important reference for the frequency control and stable operation of the power system, which belongs to the field of power system safety and stability analysis.

[0054] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0056] Figure 1 Simplify the SFR model under traditional power system disturbance;

[0057] Figure 2 It is a block diagram of virtual inertia control for two-stage photovoltaic power generation;

[0058] Figure 3 A flowchart of a photovoltaic equivalent inertia evaluation method based on regional synchronous generator measurement data provided according to an embodiment of the present invention;

[0059] Figure 4 It is a simplified SFR model under disturbance of the photovoltaic region according to an embodiment of the present invention;

[0060] Figure 5 The topology of the photovoltaic four-machine two-zone system according to an embodiment of the present invention;

[0061] Figure 6 The zoning result of the system with four photovoltaic machines and two zones according to the embodiment of the present invention;

[0062] Figure 7 are the photovoltaic equipment inertia evaluation results based on the synchronous generator data in the region. (a) is the photovoltaic equivalent inertia evaluation result based on the synchronous generator measurement data in the region under working condition 1, and (b) is the photovoltaic equivalent inertia evaluation result based on the synchronous generator measurement data in the region under working condition 2. DETAILED DESCRIPTION

[0063] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0064] Before introducing the photovoltaic equivalent inertia evaluation method based on regional synchronous generator measurement data of the present invention, the background is first introduced.

[0065] First, define the inertia of the photovoltaic equipment. Analogous to the inertia of the synchronous motor, the photovoltaic theoretical inertia is defined by the photovoltaic equipment's instantaneous power increase and the photovoltaic equipment's grid-connected point frequency change rate at the instant of disturbance, as shown in the following formula:

[0066]

[0067] In the formula, H pv is the equivalent inertia time constant provided by the photovoltaic device under the system base capacity with virtual inertia control, ΔP vir is the power provided by the photovoltaic device to the system at the instant of disturbance under virtual inertia control, df pv / dt is the frequency of the photovoltaic equipment grid connection point at the moment of disturbance. Secondly, the inertia composition of the system in the partitioned area is analyzed. In addition to the inertia of photovoltaic power generation, the regional inertia mainly considers the contribution of synchronous generators. Therefore, the inertia of the photovoltaic area can be expressed as follows:

[0068] H area =H g,a +H pv

[0069] In the above formula, the equivalent inertia H of the synchronous generator in the area g,a It is defined by aggregating the parameters of synchronous generators as follows:

[0070]

[0071] In the above formula, n G,area represents the number of synchronous generators in the area after partitioning, S j and H j Represent the rated capacity and rated inertia time constant of the jth generator respectively. Then, the system frequency response (SFR) model is introduced to quantitatively evaluate the actual inertia of the power system containing photovoltaics. The SFR model is a model that describes the average frequency response of the power system after a disturbance. A single synchronous generator model is used instead of the entire power system to study the frequency. In traditional power systems, the SFR model usually includes models such as the speed regulator, prime mover, and load, which can simulate the dynamic changes in the frequency of the system after power imbalance. The simplified SFR model of the system under disturbance is as follows: Figure 1shown.

[0072] Figure 1 In the d is the change in power generation or load in the power grid, ΔP m is the change in mechanical power of the synchronous motor, ΔP a is the power difference allocated to the synchronous motor, D is the equivalent damping coefficient of the generator, R is the speed regulator adjustment coefficient, T R is the reheating time constant of the synchronous motor, F H K is the work ratio of the high-pressure cylinder of the synchronous motor. m is a coefficient related to the generator power factor and reserve capacity. In the SFR model, the inertia center frequency ω coi The definition is as follows:

[0073]

[0074] In the formula, ω j Represents the operating angular frequency of the jth generator.

[0075] Finally, to verify the accuracy of the proposed evaluation method, the theoretical inertia of photovoltaic equipment is derived as a reference value. In order to enable photovoltaic equipment to have frequency response capabilities without configuring additional energy storage, load reduction control is introduced as an energy source in the maximum frequency tracking control (MPPT) control of the boost circuit. At the same time, virtual inertia control is adopted, and the frequency of the photovoltaic grid-connected point is used as feedback. The reference value of the photovoltaic active power output is changed through the virtual inertia control coefficient, thereby instantly changing the photovoltaic output after the disturbance. According to the rated capacity S of the photovoltaic equipment PV and system rated capacity S B After conversion to rated capacity, the duty cycle d is obtained through PI control to control the output of the boost circuit. Finally, the inverter is controlled in the form of DC capacitor voltage to change the photovoltaic active output. The process is as follows: Figure 2 shown.

[0076] In this process, although there is a certain delay in the boost circuit and inverter circuit, the response speed of power electronic devices is much faster than the inertia response and electromagnetic transient response process. Therefore, the dynamics of power electronic devices can be ignored. The photovoltaic active output ΔP PV Approximately equal to the power reference value ΔP ref In summary, when the PV load reduction rate is constant, the additional power generated by PV power generation under virtual inertia control in the frequency domain can be expressed as follows:

[0077]

[0078] According to the definition of photovoltaic inertia, the above formula is substituted into the photovoltaic theoretical inertia expression and simplified, and the theoretical inertia of photovoltaic equipment in the frequency domain is calculated as follows:

[0079]

[0080] By performing an inverse Laplace transform on the above formula, the theoretical inertia of the photovoltaic device in the time domain is obtained:

[0081]

[0082] It can be seen from the above formula that when the low-pass filter time constant is small, H pv (t) will reach a stable value in a very short time, so it can be approximated as follows:

[0083]

[0084] According to the above steps, the theoretical inertia value of photovoltaic under virtual inertia control can be calculated.

[0085] In the existing literature, the assessment based on large disturbance events is currently the most widely used assessment method, which uses the power and frequency data after the disturbance to assess the inertia. According to the assessment object, the inertia assessment method can be divided into the overall system inertia assessment and the photovoltaic equipment inertia assessment. In the assessment method with photovoltaic power generation equipment as the assessment object, the existing research mostly defines the equivalent inertia of photovoltaic equipment by analogy with the swing equation of synchronous motor. Taking into account the limitations of the existing methods, for the power system containing photovoltaic power generation equipment, the present invention proposes an inertia assessment method that simultaneously evaluates the equivalent inertia of all photovoltaic power generation equipment in the area.

[0086] Figure 3 The present invention provides a flowchart of a photovoltaic equivalent inertia evaluation method based on regional synchronous generator measurement data according to an embodiment of the present invention.

[0087] like Figure 3 As shown, the photovoltaic equivalent inertia evaluation method based on the measurement data of synchronous generators in the region includes the following steps:

[0088] Step 1: Partition the power system into motor zones based on the electrical distances between nodes within the generator.

[0089] Optionally, in one embodiment of the present invention, step 1 specifically includes:

[0090] Step 1-1, collecting transient reactances of all synchronous generators in the power system and system line parameters to generate a system admittance matrix;

[0091] Step 1-2, based on the system admittance matrix, consider the transient reactance inside the generator and generate the admittance augmented matrix Y S :

[0092]

[0093] The power system contains M+N network nodes, M is the number of nodes at the generator end, and N is the number of other nodes; g is the node inside the generator, g∈[1,M]; m is the node outside the generator end, m∈[1,M]; n is the other node in the power system, n∈[M+1,M+N]; Y gg , Y gm , Y mm , Y mn , Y nn are the self-admittance and mutual-admittance of the internal nodes, external nodes and other nodes of the generator, respectively. m is the diagonal array of transient reactance of the generator, Y lm and Y ln are the equivalent ground admittances formed by the loads at the generator node and other nodes; the admittance augmented matrix Y S The middle zero position indicates that there is no direct connection between nodes;

[0094] Steps 1-3, simplify the admittance augmented matrix and determine the optimal number of clusters based on the elbow method;

[0095] For the admittance augmented matrix Y S Perform kron simplification and shrink to M×M matrix Y g , matrix Y g The i-th row and j-th column represent the admittance from the node in the i-th generator to the node in the j-th generator. The larger the admittance, the closer the electrical connection between the generators, which can be regarded as the correlation between the i-th generator and the j-th generator. The elbow method based on the sum of squared errors is used to confirm the optimal number of clusters for the power system; the sum of squared errors (SSE) is defined as the sum of squares of the difference between each sample point and the average value after clustering. The smaller the sum of squared errors, the better the clustering result. The calculation formula is as follows:

[0096]

[0097] In the formula, C i is the i-th cluster, p is C i The sample points in m i C i As the number of clusters k increases, the sample division will become more refined, the degree of aggregation of each cluster will gradually increase, and the error sum of squares S SSE will gradually become smaller, but if k is too large, the partition characteristics will not be reflected, so we need to find an optimal clustering number k. opt , which can reflect the partition characteristics and increase the similarity within the cluster. According to the clustering characteristics and the definition of the optimal number of clusters, when k < k opt When k increases, the degree of aggregation of each cluster will increase significantly, so SSSE The decrease is large, and when k>k opt When k is increased, the degree of aggregation within the cluster will decrease sharply, so S SSE The drop will drop sharply and become flat as the k value increases. SSE For the image with cluster number k, the image is in the shape of an elbow. The k value corresponding to the elbow is the optimal cluster number k. opt .

[0098] Steps 1-4, based on the optimal number of clusters to augment the admittance matrix Y S Use K-means clustering method to complete motor partitioning.

[0099] Step 2: Partition the power system into nodes based on the linear relationship between generator frequency and node frequency.

[0100] Optionally, in one embodiment of the present invention, step 2 specifically includes:

[0101] Step 2-1, derive the linear relationship between generator frequency and node frequency:

[0102] The network node voltage is represented by the potential node voltage inside the generator, that is:

[0103] U net =RU e

[0104] Among them, U e and U net are the voltage vectors of the potential nodes in the generator and the voltage vectors of the network nodes, respectively, and R is the correlation matrix between the voltages of the potential nodes in the generator and the voltages of the network nodes:

[0105]

[0106] If a failure occurs at node k, based on U net =RU e In the k-related expansion, the fault point voltage is expressed as the internal potential of each generator, and the voltage angle of node k can be obtained as follows:

[0107]

[0108] Where V k 、V j are the voltage amplitudes at node k and motor j, respectively, k , δ j are the phase angles corresponding to the potentials of node k and generator j respectively; r kj is the element in the correlation matrix R that represents the voltage relationship between node k and generator j. After simplification, the voltage angle of node k is obtained as follows:

[0109]

[0110] The voltage angle can be extended to the frequency relationship, that is:

[0111]

[0112] In the formula, f k 、f j are the frequencies of node k and generator j, respectively.

[0113] Step 2-2, based on the linear relationship between generator frequency and node frequency, each node in the power system is divided into the generator with the largest correlation coefficient with its own node, and then allocated to the corresponding area to complete the node partitioning.

[0114] Step 3: Collect the measurement data of synchronous generators in the photovoltaic area, and evaluate the overall equivalent inertia of the area based on the measurement data of synchronous generators in the area.

[0115] Optionally, in an embodiment of the present invention, step 3 specifically includes:

[0116] Step 3-1, based on the motor partitioning and node partitioning results, collect the rated parameters and operating data of the photovoltaic area, such as the operating angular frequency of the synchronous generator and the regional inertia center frequency;

[0117] Taking the region as the object, the system frequency response model regional inertia center frequency ω acoi The definition is as follows:

[0118]

[0119] Where n G,area Represents the number of synchronous generators in the area after partitioning;

[0120] Step 3-2, evaluate the regional equivalent inertia based on the disturbance size and the regional inertia center frequency;

[0121] After adopting virtual inertia control, the frequency model of the photovoltaic power area is analyzed, the photovoltaic equipment and the feedback loop of the interconnection line with other areas are added, and a simplified system frequency response model of the photovoltaic area under disturbance is established, such as Figure 4 shown.

[0122] According to the definition of the system frequency response model, the overall equivalent inertia H of the region containing photovoltaics area It is defined by the ratio of the sum of the disturbance power and the tie line power and the rate of change of the inertial center frequency:

[0123]

[0124] Where ΔP dis the disturbance value of the power grid, ΔP T It is the change in transmission power of the inter-regional interconnection line at the moment of disturbance.

[0125] Therefore, the equivalent inertia value of the photovoltaic area can be measured according to the set disturbance and the measured frequency data.

[0126] Step 4: Calculate the equivalent inertia of the PV equipment using the regional overall equivalent inertia and the regional synchronous generator inertia.

[0127] Optionally, in one embodiment of the present invention, step 4 specifically includes:

[0128] Step 4-1, collect the rated capacity and rated inertia time constant of all synchronous generators in the area, where the rated capacity and rated inertia time constant of the jth synchronous generator are S j and H j , according to S j and H j Calculate the equivalent inertia H of the synchronous generator in the area g,a ;

[0129] Step 4-2, evaluating the equivalent inertia of the photovoltaic equipment under the set parameters based on the measurement data of the synchronous generators in the area;

[0130] according to Figure 2 The model shows that when the equivalent damping coefficient D of the synchronous motor is ignored, the equivalent inertia time constant H of the synchronous generator in the region is g,a It can be expressed as follows:

[0131]

[0132] In the formula, ΔP m,a is the mechanical power variation of the synchronous motor in the region, ΔP a is the power difference allocated to the synchronous motors in the area, ΔP vir Power support provided for photovoltaic virtual inertia control at disturbance instant;

[0133] Considering that the mechanical power of the synchronous generator cannot change suddenly at the beginning of the disturbance, ΔP m,a is approximately 0. Therefore, the time constant H of the equivalent inertia of the photovoltaic equipment in the region pv It is expressed as:

[0134]

[0135] Therefore, for actual power systems, when PV adopts virtual inertia control and the rated inertia time and rated capacity of regional synchronous generators are known, the equivalent inertia time constant of PV equipment can be finally obtained according to the above formula.

[0136] The photovoltaic equivalent inertia evaluation method based on the measurement data of synchronous generators in the region proposed by the present invention can evaluate the equivalent inertia of photovoltaic equipment, and reduces the demand for synchronous generator data through system partitioning and node partitioning. Only the rated parameters and operating data of synchronous generators in the region are required, which is convenient for application in practical engineering. At the same time, the method has parallel evaluation capability, and can simultaneously evaluate the equivalent inertia of all photovoltaic equipment in the region, thereby improving the evaluation efficiency and having a higher evaluation accuracy.

[0137] The photovoltaic equivalent inertia evaluation method based on regional synchronous generator measurement data of the present invention is described in detail below through a specific embodiment.

[0138] like Figure 5 As shown in Figure 1, a four-machine two-zone system is built in Matlab / Simulink. The frequency of the model is set to 50 Hz and all loads are set to constant power load models. The rated capacity of all generators is 900 MVA, of which the inertia time constant of generators G1 and G2 is 6.5 s, and the inertia time constant of G3 and G4 is 6.175 s.

[0139] In order to verify that the present invention can simultaneously evaluate the equivalent inertia of all photovoltaic devices in a region, different numbers of photovoltaic devices are connected in the region, and the working conditions are set as follows:

[0140] Condition 1: Only the photovoltaic unit PV1 with a rated capacity of 250MW is connected at the node 8 in area 2, and virtual inertia control is adopted with a low-pass filter time constant T p = 0.001s. Set node 9 to have an impact load disturbance at 15s, the disturbance size is 176MW, and the frequency measurement window is 200ms.

[0141] Condition 2: PV1 and PV2 with a rated capacity of 250MW are connected at nodes 8 and 9 in area 2 at the same time, and virtual inertia control is adopted with a low-pass filter time constant T p =0.001s. Similarly, node 9 is set to have an impact load disturbance at 15s, the disturbance size is 176MW, and the frequency measurement window is 200ms.

[0142] For the connected photovoltaic power station, different photovoltaic virtual inertia control coefficients are set to simulate the inertia evaluation under different working conditions. The photovoltaic equivalent inertia time constant after disturbance is calculated as shown in Table 1.

[0143] Table 1 Photovoltaic theoretical equivalent inertia time constant under different virtual inertia control

[0144] Photovoltaic virtual inertia control coefficient <![CDATA[K d =10]]> <![CDATA[K d =15]]> <![CDATA[K d =20]]> Working condition 1 Photovoltaic theoretical inertia time constant / s 1.389 2.083 2.778 Working condition 2 Photovoltaic theoretical inertia time constant / s 2.778 4.167 5.555

[0145] At the same time, in order to examine the accuracy of the evaluation results, the error calculation formula is introduced:

[0146]

[0147] Among them, H C and H T Inertia values ​​and theoretical inertia values ​​are evaluated for PV equipment respectively.

[0148] In order to adopt the inertia evaluation strategy based on the measured data of synchronous generators in the region, the system is first partitioned. Based on the K-means clustering method, the motor partitioning is performed. Under both working conditions, the four-machine two-zone system is divided into two zones, generator 1 and generator 2 belong to zone one, and generator 3 and generator 4 belong to zone two.

[0149] Further node partitioning is performed, and the relationship matrix between motor frequency and node frequency is calculated. The node partitioning results are shown in Table 2, where the partitioning results of nodes 1 to 11 are applicable to both working conditions.

[0150] Table 2 PV system node partition results

[0151] Node Number Motor Area 1 G1 Area 1 2 G2 Area 1 3 G3 Area 2 4 G4 Area 2 5 G1 Area 1 6 G2 Area 1 7 G2 Area 1 8 G4 Area 2 9 G4 Area 2 10 G3 Area 2 11 G4 Area 2 12 G4 Area 2

[0152] Therefore, the topology and zoning results of the system with four photovoltaic machines and two zones are as follows: Figure 6 shown.

[0153] According to the results of motor partitioning and node partitioning, the photovoltaic equipment belongs to area 2, so the equivalent inertia time constant of area 2 is calculated first, as shown in the following formula:

[0154]

[0155] When the PV system adopts virtual inertia control, the overall equivalent inertia time constant of the system is evaluated under different virtual inertia magnification factors. The evaluation results of the regional equivalent inertia under working conditions 1 and 2 are shown in Table 3. The inertia time constants in the table are all based on the system benchmark capacity.

[0156] Table 3 Evaluation results of regional equivalent inertia time constant under different virtual inertia control of photovoltaic

[0157]

[0158] The photovoltaic equivalent inertia time constant was further evaluated and compared with the theoretical value, such as Figure 7 shown.

[0159] As shown in Table 3 and Figure 7 As shown, when the photovoltaic system adopts virtual inertia control, the present invention can accurately evaluate the photovoltaic equivalent inertia based on the measurement data of the synchronous generator in the area, and the evaluation error between the theoretical value and the measured value is within 10%.

[0160] The photovoltaic equivalent inertia evaluation method based on the measurement data of synchronous generators in the region proposed in the embodiment of the present invention can evaluate the equivalent inertia provided by photovoltaic equipment under virtual inertial control, and can simultaneously evaluate the equivalent inertia of all photovoltaic equipment in the system, reducing the required evaluation data while ensuring the accuracy of the evaluation process. Through this method, the engineering practicality of photovoltaic inertia evaluation can be improved, providing an important reference for frequency control and stable operation of power systems.

[0161] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0162] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "N" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0163] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present invention belong.

Claims

1. A photovoltaic equivalent inertia evaluation method based on regional synchronous generator measurement data, characterized in that: The following steps are involved: Step 1: partition the power system into motors based on the electrical distance between nodes within the generator; Step 2: partition the power system nodes based on the linear relationship between generator frequency and node frequency; Step 3: Collect the measurement data of synchronous generators in the photovoltaic area, and evaluate the overall equivalent inertia of the area based on the measurement data of synchronous generators in the area; Step 4: Calculate the equivalent inertia of the PV equipment using the regional overall equivalent inertia and the regional synchronous generator inertia.

2. The method according to claim 1, characterized in that Step 1 specifically includes: Step 1-1, collecting transient reactances of all synchronous generators in the power system and system line parameters to generate a system admittance matrix; Step 1-2, based on the system admittance matrix, the transient reactance inside the generator is considered to generate the admittance augmented matrix Y S : The power system contains M+N network nodes, M is the number of nodes at the generator end, and N is the number of other nodes; g is the node inside the generator, g∈[1,M]; m is the node outside the generator end, m∈[1,M]; n is the other node in the power system, n∈[M+1,M+N]; Y gg , Y gm , Y mm , Y mn , Y nn are the self-admittance and mutual-admittance of the internal nodes, external nodes and other nodes of the generator, respectively. m is the diagonal array of transient reactance of the generator, Y lm and Y ln are the equivalent earth admittances formed by the loads at the generator node and other nodes respectively; the admittance augmented matrix Y S The middle zero position indicates that there is no direct connection between nodes; Step 1-3, simplify the admittance augmentation matrix and determine the optimal number of clusters based on the elbow method: For the admittance augmentation matrix Y S Perform kron simplification and shrink to an M×M matrix Y g , matrix Y g The i-th row and j-th column of represents the admittance from the node in the i-th generator to the node in the j-th generator. The larger the admittance, the closer the electrical connection between the generators, which can be regarded as the correlation between the i-th generator and the j-th generator. The elbow method based on the sum of squared errors is used to confirm the optimal number of clusters of the power system, where the sum of squared errors is defined as the sum of squares of the differences between each sample point and the average value after clustering. The smaller the sum of squared errors, the better the clustering result. The calculation formula is: Among them, C i is the i-th cluster, p is C i The sample points in m i C i The sample mean of S SSE For the image with cluster number k, the image is elbow-shaped, and the k value corresponding to the elbow is the optimal cluster number k opt ; Steps 1-4, based on the optimal number of clusters to augment the admittance matrix Y S Use K-means clustering method to complete motor partitioning.

3. The method according to claim 1, characterized in that Step 2 specifically includes: Step 2-1, derive the linear relationship between generator frequency and node frequency: The network node voltage is represented by the potential node voltage inside the generator, that is: IN net =RU e Among them, U e and U net are the voltage vectors of the potential nodes in the generator and the voltage vectors of the network nodes, respectively, and R is the correlation matrix between the voltages of the potential nodes in the generator and the voltages of the network nodes: If a failure occurs at node k, based on U net =RU e In the k-related expansion, the fault point voltage is expressed as the internal potential of each generator, and the voltage angle of node k is obtained as follows: Where V k 、V j are the voltage amplitudes at node k and motor j, respectively, k ,δ j are the phase angles corresponding to the potentials of node k and generator j respectively; r kj is the element in the correlation matrix R that represents the voltage relationship between node k and generator j. After simplification, the voltage angle of node k is obtained as follows: The voltage angle can be extended to the frequency relationship, that is: In the formula, f k 、f j are the frequencies of node k and generator j, respectively; Step 2-1, based on the linear relationship between generator frequency and node frequency, each node in the power system is divided into the generator with the largest correlation coefficient with its own node, and then allocated to the corresponding area to complete the node partitioning.

4. The method according to claim 3, characterized in that Step 3 specifically includes: Step 3-1, based on the motor partitioning and node partitioning results, collect the rated parameters and operating data of the photovoltaic area, such as the operating angular frequency of the synchronous generator and the regional inertia center frequency; Taking the region as the object, the system frequency response model regional inertia center frequency ω acoi The definition is as follows: Where n G,area Represents the number of synchronous generators in the area after partitioning; Step 3-2, evaluate the regional equivalent inertia based on the disturbance size and the regional inertia center frequency; After adopting virtual inertia control, the frequency model of the photovoltaic power area is analyzed, the photovoltaic equipment and the feedback loop of the interconnection line with other areas are added, and a simplified system frequency response model of the photovoltaic area under disturbance is established; According to the definition of the system frequency response model, the overall equivalent inertia H of the region containing photovoltaics area It is defined by the ratio of the sum of the disturbance power and the tie line power and the rate of change of the inertial center frequency: In the formula, ΔP d is the disturbance value of the power grid, ΔP T It is the change in transmission power of the inter-regional interconnection line at the moment of disturbance.

5. The method according to claim 4, characterized in that Step 4 specifically includes: Step 4-1, collect the rated capacity and rated inertia time constant of all synchronous generators in the area, where the rated capacity and rated inertia time constant of the jth synchronous generator are S j and H j , calculate the equivalent inertia H of the synchronous generator in the area g,a ; Step 4-2: Evaluate the equivalent inertia of the photovoltaic equipment under the set parameters based on the measurement data of the synchronous generators in the area; When the equivalent damping coefficient D of the synchronous motor is ignored, the equivalent inertia time constant H of the synchronous generator in the region g,a It is expressed as follows: Where ΔP m,a is the mechanical power variation of the synchronous motor in the region, ΔP a is the power difference allocated to the synchronous motors in the area, ΔP vir Power support provided for photovoltaic virtual inertia control at disturbance instant; Considering that the mechanical power of the synchronous generator cannot change suddenly at the beginning of the disturbance, ΔP m,a is approximately 0, so the time constant H of the equivalent inertia of the photovoltaic equipment in the area pv It is expressed as: For actual power systems, when PV adopts virtual inertia control and the rated inertia time and rated capacity of regional synchronous generators are known, the equivalent inertia time constant of PV equipment can be finally obtained according to the above formula.

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