Distributed phase modifier locating and sizing method considering frequency stability improvement

Abstract

The invention discloses a distributed phase modifier locating and sizing method considering frequency stability improvement, and belongs to the field of power system stability and control. Comprising the following steps: performing quantitative evaluation on the inertia supporting capacity of a power grid by node inertia, analyzing the influence of access of the phase modifier on the frequency of the power grid, and performing a distributed phase modifier locating and sizing configuration strategy considering the frequency stability constraint. According to the method, aiming at the frequency stability problem of a new energy sending end power grid caused by a large disturbance fault of the system, the frequency supporting capacity of the system is improved to the maximum extent by solving the optimal model with the minimum configuration capacity as an optimization target.

Description

Technical Field

[0001] The present invention belongs to the field of power system stability and control, and in particular relates to a distributed phase regulator site selection and capacity determination method considering frequency stability improvement. Background Art

[0002] my country is expected to increase the total installed capacity of wind and solar power to 1,200GW by 2030, the proportion of non-fossil energy consumption to 25%, and the proportion of renewable energy to more than 60% by 2050. The low-carbonization of the energy system will be an important development direction of China's energy system, and a high proportion of new energy will be the main feature of China's power system in the future. The grid connection of new energy power generation with a high proportion of power electronic interfaces will lead to weak inertia support capacity of the power system and prominent frequency stability problems. For wind and solar power stations, distributed synchronous phase condensers, as rotating elements, can provide voltage support while also providing rotational inertia for the system. By configuring phase condensers, the system inertia level can be effectively improved, and then the frequency support strength of the power grid can be improved. However, in the current power system, the configuration method of distributed phase condensers has yet to be studied, and it is of great significance to formulate an efficient and feasible distributed phase condenser site selection and sizing strategy. Therefore, there is an urgent need for a new, flexible, and adjustable distributed phase condenser site selection and sizing method that considers frequency stability constraints.

[0003] As early as the beginning of the 20th century, the United States had developed a number of small hydrogen-cooled phase-shifters. In the 1940s and 1950s, countries such as Japan, Sweden and the Soviet Union successively developed a number of medium-sized phase-shifters ranging from 37.5MVar to 80MVar, and made a large number of applications on this basis. The 1970s and 1980s were the era of the fastest development of phase-shifters. During this period, foreign countries successively developed 250MVar, 320MVar hydrogen-cooled phase-shifters and 345MVar all-water-cooled phase-shifters. After the 1970s, with the development of power electronic devices, it fell into a research trough and was replaced by compensation devices such as SVC and SVG. Around 2010, it ushered in a new active period. The composition of the phase-shifter system is as follows: Figure 1As shown. Large centralized phase regulators are usually configured at the DC converter bus to support the safe and stable operation of the power system in the event of a fault. In recent years, in addition to centralized phase regulators, small distributed phase regulators can be configured at the grid connection points of new energy stations. By configuring distributed phase regulators, the economy can be effectively improved. By the end of 2021, all 21 small distributed phase regulators planned to be installed by State Grid Corporation of China in Qinghai and Hainan will be put into operation, officially forming the world's largest new energy distributed phase regulator group, which can provide 3.5 million kilowatts of new energy transmission power to Hainan, and increase new energy power generation by 7.02 billion kilowatt-hours per year, which is equivalent to reducing coal burning by 3.189 million tons and reducing carbon emissions by 5.742 million tons. In order to meet the needs of the power market, the dynamic reactive characteristics of the new generation of phase regulators have been greatly improved. It is not just a reactive voltage compensation device, but a synchronous device with inertial response. It has great advantages in the frequency response characteristics of some low-inertia systems and improving the frequency support performance of the system. It also has good network adaptability. It has been widely used in domestic and foreign power systems and has a strong research enthusiasm. Since the phase regulator is a rotating equipment, it is subject to limitations such as primary investment, maintenance, and site selection. Therefore, the configuration of the phase regulator must be reasonably selected to ensure the frequency stability of the system and the scale of new energy access.

[0004] At present, the research on phase condensers can be divided into two categories: 1. A phase condenser site selection and sizing scheme to improve the voltage strength of the power system is proposed, but the role of the phase condenser in increasing the system inertia and improving the frequency support strength is not considered. 2. The inertia response principle of the phase condenser and its role in improving frequency stability are explored, but an efficient and feasible site selection and sizing strategy has not been formed. Synchronous phase condensers are not only a reactive voltage compensation device, but also a synchronous device with inertial response. They have great advantages in the frequency response characteristics of some low inertia systems and improving the frequency support performance of the system. At the same time, they also have good network adaptability. At present, they have been widely used in power systems at home and abroad, and have a strong research enthusiasm. However, most of the current research uses the reactive compensation capability of synchronous phase condensers to solve the voltage stability problem of the power system. There are very few studies on the inertia support role of synchronous phase condensers and improving frequency stability. Summary of the invention

[0005] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art and to solve the frequency stability problem of the power grid at the renewable energy sending end caused by large disturbance failures in the system by solving the optimal model with the minimum configuration capacity as the optimization goal.

[0006] To achieve the above objectives, a specific technical solution of a method for site selection and capacity determination of a distributed phase shifter considering frequency stability improvement of the present invention is as follows:

[0007] A method for selecting a site and determining the capacity of a distributed phase-shifting machine considering frequency stability improvement specifically includes the following steps, and the following steps are performed in sequence:

[0008] Step 1: Calculate and construct the power system node inertia

[0009] At the moment of disturbance in the power grid, the unbalanced power will be distributed among the synchronous units according to the synchronous power coefficient, resulting in the rotation speed of each synchronous machine being inconsistent. The frequency of each node is also affected by the generator frequency, resulting in the phenomenon of spatiotemporal distribution of frequency. The damping effect of inertia hinders the change of node frequency, and the spatiotemporal distribution characteristics of frequency are the embodiment of the spatiotemporal distribution characteristics of inertia. The inertia of the power system also shows spatiotemporal distribution characteristics, that is, the inertia of the same node is different at different times, and the inertia of different nodes is different at the same time.

[0010] Define the inertia H of node k k is the ratio of the disturbance power to the initial frequency change rate at the node, that is:

[0011]

[0012] Where: ΔP is the disturbance power, f k is the frequency of node k.

[0013] The physical representation of node inertia is as follows Figure 2 As shown, Figure 2 The node inertia represented in can be explained as follows: the node itself has no inertia, and the node inertia is the embodiment of the generator inertia distributed at the node according to the synchronous power coefficient. In physical terms, it can be understood as the inertia of a non-existent synchronous machine assumed at the node. Studying the calculated inertia of different nodes can describe the inertia distribution characteristics of the system.

[0014] Assume a power system with n+m nodes. There are n generator end nodes in the system. In addition to the generator end nodes, there are m network nodes. The augmented admittance matrix Y is obtained from this system. s :

[0015]

[0016] Where: Y n It is the diagonal array formed after the transient reactance of the generator is converted into admittance; Y nn and Y mm is the self-admittance of the generator and other network nodes; Y ln and Y lm Y is the equivalent admittance after the loads at the generator and other network nodes are simplified to equivalent admittance; nm and Y mn is the mutual admittance between the generator and other network nodes, and the conductance is neglected.

[0017] The network equation of the system is obtained:

[0018]

[0019] Where: U e and U net is the voltage of the generator terminal node and other nodes; I n is the current input from the potential node in the generator to the network; Y1, Y2, Y3, and Y4 are the four regions of the augmented admittance matrix, where Y1 = Y n , Y2=[-Y n ,0],Y3=[-Y n ,0] T ,

[0020] According to formula (3), the voltage of the network node other than the generator node in the power grid is expressed by the voltage of the potential node inside the generator:

[0021] U net =RU e (4)

[0022] Where: R represents the correlation matrix between voltages, The size of its elements is mainly affected by the grid admittance matrix. According to formula (4), the node voltage is expressed by the generator voltage:

[0023]

[0024] Where: V k ,δ k 、V j ,δ j are the voltage at node k and the internal potential of generator j, respectively; r kj is the element in the matrix R corresponding to the voltage relationship between node k and generator j; j∈k represents the element in the row where node k is located in R.

[0025] Transform and simplify formula (5) to obtain formula (6):

[0026]

[0027] Then we get:

[0028]

[0029] The frequency of node k is obtained from formula (7):

[0030]

[0031] Where: f j is the frequency of generator j.

[0032] That is, the frequency of the network node is represented by the frequency of the synchronous machine. When the disturbance power ΔP appears at the node k, each generator shares the disturbance power according to the synchronous power coefficient:

[0033]

[0034] Where: ΔP j is the unbalanced power shared by generator j, D jk is the synchronous power factor of generator j;

[0035] According to formula (8) and the rotor motion equation df i / dt=ΔP, the frequency change rate of generator j is expressed as:

[0036]

[0037] Where: H j is the inertia of generator j.

[0038] Combining formulas (8) and (10), the inertia of node k is obtained as:

[0039]

[0040] It can be seen from the formula that the inertia of the node depends on the inertia size of the inertia source such as the synchronous machine or the phase regulator and its electrical distance. When the power system is subject to power disturbance, the frequency change is only hindered by inertia before a frequency regulation action. The inertia of different nodes in the system at the same time section is unevenly distributed, and the node with the smallest inertia faces a greater risk of frequency collapse. Therefore, configuring the phase regulator near the low inertia node can more effectively improve the inertia level of the system.

[0041] Step 2: Calculation of critical inertia of power system

[0042] The power system frequency stability indicators mainly include: the maximum frequency change rate RoCoF max , Maximum frequency deviation Quasi-steady-state frequency deviation Δf ss Δf ss It mainly reflects the frequency quality of the system after one frequency modulation after power disturbance. It is not in the process of dynamic frequency change and is a steady-state indicator. It indicates the amplitude of the frequency drop. If the amplitude is too large, the protection device will be triggered, and in severe cases, the frequency will collapse. max Indicates the frequency change rate. If its value is too large, the frequency will drop rapidly or even exceed the threshold. Therefore, when considering transient frequency stability constraints, RoCoF should be considered mainly. max and These two indicators can be used to evaluate the critical inertia of the system from these two aspects of frequency constraints.

[0043] (1) System critical inertia based on RoCoF constraints

[0044] The frequency change rate RoCoF is an important indicator to measure the frequency safety and stability of the system after a disturbance occurs, and its size mainly depends on the system inertia level.

[0045] At present, the frequency stability of my country's power system is mainly constrained by the maximum frequency deviation under disturbance. RoCoF does not have a specific safety range. However, in a power system with a high proportion of new energy, the inertia level is low. When an active power impact occurs in the power grid, excessive RoCoF will cause unit damage and new energy disconnection from the grid, further exacerbating the threat to system frequency safety. Therefore, based on the operating characteristics and stability requirements of my country's power grid, the frequency change rate RoCoF is a frequency safety indicator that cannot be ignored.

[0046] At the moment of disturbance in the power grid, the inertia response of the synchronous unit has not yet taken effect. At this time, the RoCoF is the largest. If a safety range is set for the frequency change rate RoCoF, the RoCoF at the moment of disturbance should be tested. At this time, the frequency is at the rated value, and the generator and load frequency regulation effect has not yet taken effect.

[0047] The maximum frequency change rate after the system is disturbed is proportional to the disturbance power and inversely proportional to the inertia size. The greater the disturbance power and the lower the system inertia, the easier it is to trigger the protection action. The frequency does not change at the moment of the disturbance, and the frequency modulation effect of the generator and load in the system does not work. The frequency change only depends on the size of the system inertia and the disturbance power.

[0048] The critical inertia of the system based on the RoCoF constraint is:

[0049]

[0050] Where: ΔP max is the maximum disturbance power, RoCoF max It can be expressed as the maximum value of the system frequency change rate.

[0051] This means that the maximum disturbance power ΔP occurs in the system max In order to make the center of inertia RoCoF not exceed the threshold RoCoF max , the system inertia should be greater than

[0052] (2) Based on Constrained system critical inertia

[0053] Without considering the frequency regulation of generators and loads, the maximum frequency deviation mainly depends on the inertia level and primary frequency regulation capability. The greater the system inertia level and primary frequency regulation capability, the smaller the maximum frequency deviation of the system after the disturbance occurs. To ensure that the frequency deviation is within the safety constraint range, In order to avoid collapse, the system should have sufficient inertia level to cope with various disturbances; the system frequency deviation depends on the initial power shortage and system inertia, and has a linear relationship with time. According to the frequency response model of the multi-machine system, it is derived The critical inertia expression under constraint is:

[0054]

[0055] Where: f B is the reference frequency, t madir is the moment when the lowest frequency point occurs.

[0056] It can be seen that in a system with low inertia, the RoCoF after the disturbance occurs is max and These two important frequency stability indicators will deteriorate. In summary, the boundary inertia level that satisfies these two indicators within the safe range after the disturbance is the critical inertia considering the frequency stability constraint.

[0057] Based on RoCoF max Constraints and The minimum inertia of the constrained system is:

[0058]

[0059] For both RoCoF max and For a system with two constraints, the grid inertia under the two constraints can be calculated according to formula (14), and the larger of the two is taken as the critical inertia of the system. max and Both of these important frequency stability indicators will deteriorate, and only the system inertia that satisfies both constraints at the same time is the safe inertia that makes the system stable.

[0060] In summary, satisfying these two frequency stability index constraints at the same time after the disturbance can keep the system in a safe and stable range. The inertia level at this time is the critical inertia of the system considering the frequency stability constraint.

[0061]

[0062] Where: H min It is the critical inertia for the safety and stability of the system.

[0063] From the above, we can see that the system inertia distribution is not uniform. Nodes with sufficient inertia have strong frequency anti-interference ability, while nodes with weak inertia have weak frequency anti-interference ability. If the power grid frequency is to be safe and stable, the inertia of all nodes in the system must be greater than the critical inertia, that is, the inertia of the node with the smallest inertia is greater than the critical inertia:

[0064]

[0065] Step 3: Distributed phase-shifting optimization configuration strategy based on the Grey Wolf Optimization Algorithm

[0066] (1) Distributed condenser optimization configuration objective function

[0067] Generally speaking, synchronous phase regulators in power grids can be divided into two types, one is centralized and the other is distributed. Centralized phase regulators refer to large-capacity phase regulators centrally configured in UHV DC converter stations, usually configured on the AC bus of converter stations; while distributed phase regulators refer to small phase regulators dispersedly placed on the low-voltage side of renewable energy aggregation stations or station grid connection points in stations where renewable energy converges. In high-voltage DC transmission scenarios, large centralized phase regulators can be considered to be configured in converter stations. This article focuses on the frequency stability of power systems with renewable energy grid connection, and does not consider the scenario of UHV DC transmission. Therefore, only the configuration of small distributed phase regulators needs to be discussed. According to the information, the current construction of a 300MVar centralized phase regulator costs about 110 million yuan, and a 50MVar distributed phase regulator costs about 15.8 million yuan.

[0068] It is necessary to further optimize the configuration of the installed capacity of synchronous condensers. In order to improve the frequency stability of the new energy power system, it is necessary to increase the system inertia level as much as possible. The synchronous condenser is not only a dynamic reactive source to compensate for the reactive power required by the power grid, but also as a rotating device can provide rotational inertia to increase the system inertia level, but its construction and maintenance costs are also relatively high. Therefore, from the perspective of economic interests, it is required to maximize the configuration effect of the synchronous condenser while reducing the configuration cost of the synchronous condenser as much as possible to obtain the best economy. Therefore, it can be concluded that the optimal configuration target of the condenser is:

[0069]

[0070] Where: S is the total capacity of the phase regulator, S i is the phase-shifting capacity configured at the renewable energy station, and n is the number of renewable energy stations in the system.

[0071] By configuring distributed phase regulators, the frequency support capability of the new energy power system can be improved and the frequency stability can be improved. The optimal configuration of phase regulators is to minimize the configuration capacity while ensuring the configuration effect, so as to achieve the best economic performance.

[0072] (2) Introduction to the Grey Wolf Optimization Algorithm

[0073] In nature, gray wolves are the top predators. They live in groups, usually 5 to 12 individuals, and have a strict hierarchy within the group. Figure 3 This is a hierarchy diagram of wolves. At the top of the pyramid, at position α, is the alpha wolf, the highest authority in the wolf pack. Group hunting activities are also led and executed by the alpha wolf, who is responsible for all matters of the decision-making team; at position β of the pyramid is the alpha wolf's military advisor, whose role in the group is to assist the leader in managing the entire wolf pack. When the alpha wolf is old or disabled, the wolf at position β will quickly fill the position at position α and become the new alpha wolf. The wolf at position δ is mainly responsible for tasks such as reconnaissance, sentry and care; at position ω is a pregnant female wolf or a disabled old wolf pack, which is the largest number of wolves at the bottom of the pyramid and is responsible for the internal balance of the group. The group hunting process of the wolf pack is carried out according to the hierarchical division rules: all members follow the command of the alpha wolf to find prey, lock and surround the target when they are found, and when the alpha wolf issues an attack order, the wolves at positions β and δ attack the prey from all directions. If the prey escapes, the lower-level wolf pack at position ω will quickly carry out targeted capture. The whole process is all-round and has no dead angles, so that the prey can be accurately hunted.

[0074] The Gray Wolf Algorithm simulates the characteristics of gray wolf group hunting to perform optimization calculations, which is mainly divided into three stages: encirclement, pursuit and attack.

[0075] The “encirclement” stage in optimization is reflected in the local search for the optimal solution, and its formula is shown in (18)(19):

[0076]

[0077]

[0078] In the formula, t represents time; Gradually decrease from 2 to 0, r1 and r2 are random numbers between [0, 1]; These are the respective positions of the gray wolf and its prey.

[0079] In the "hunting" stage, the wolf pack at the bottom of the pyramid continuously updates the prey, which is the optimal solution. The wolf packs in the upper three layers of the pyramid update according to the information fed back by the wolf pack at the bottom and finally find the prey.

[0080] The “attack” stage in the optimization is reflected in the final capture of prey, that is, the optimal solution. This stage is based on formula (18) The distance between the prey and the wolf pack Slowly shrink, when When the size of is reduced to the range of [-1, 1], the wolf pack has trapped the prey in the minimum encirclement; on the contrary, if It means that the hunt has failed and the prey has escaped from the wolf pack.

[0081] The Grey Wolf Optimization Algorithm is widely used in many fields. It has good convergence, few parameters, simple and efficient, and strong practicality. This paper uses the Grey Wolf Optimization Algorithm to seek the optimal configuration capacity of distributed phase regulators. Taking the minimum configuration capacity and the highest economy as the optimization goal, and taking the critical inertia of the maximum frequency deviation and the maximum frequency change rate stability constraint as the constraint conditions, a site selection and capacity determination strategy is constructed to achieve optimal configuration.

[0082] (3) Distributed condenser optimization configuration strategy process

[0083] In view of the reduced inertia and weakened frequency support capacity of high-proportion renewable energy power systems, the distributed phase shifter site selection and capacity determination strategy is proposed by comprehensively considering the objective function and constraints of the distributed phase shifter. The specific steps are as follows:

[0084] Step 1): Read the grid structure and related parameters of the power grid;

[0085] Step 2): Determine the maximum frequency change rate and the maximum frequency deviation limit values ​​that can ensure the stability of the system, and calculate the critical inertia of the system based on this;

[0086] Step 3): Calculate the node inertia according to the system related parameters, evaluate the system inertia distribution, and find the minimum inertia node;

[0087] Step 4): Check whether the inertia of the minimum inertia node in the system is lower than the critical inertia. If so, a phase regulator needs to be configured;

[0088] Step 5): Calculate the sensitivity of the minimum inertia node inertia to the inertia of the condenser at each pre-configured node. The expression is as follows, and find the configuration position with the best sensitivity.

[0089]

[0090] In the formula, B jk is the admittance between node j and node k, r kj is the element in the matrix R corresponding to the voltage relationship between node k and generator j, H j is the inertia of generator j;

[0091] Step 6): Input the objective function and constraints, and use the gray wolf optimization algorithm to obtain the configuration plan. Recheck whether the inertia of the system's minimum inertia node is lower than the critical inertia. If so, repeat step 3); if it is reasonable, output the configuration result to form the final site selection and capacity configuration strategy.

[0092] The distributed phase-shifting machine site selection and sizing method considering frequency stability improvement of the present invention has the following advantages: the present invention uses node inertia to quantitatively evaluate the inertial support capacity of the power grid, and analyzes the impact of phase-shifting machine access on the power grid frequency. On this basis, a distributed phase-shifting machine site selection and sizing configuration strategy considering frequency stability constraints is proposed. This method can effectively improve the frequency support capacity of the power grid after the access of new energy, and has great advantages in terms of economy and practicality. The effectiveness of the distributed phase-shifting machine site selection and sizing strategy proposed in this paper is verified by simulation analysis of typical examples. BRIEF DESCRIPTION OF THE DRAWINGS

[0093] Figure 1 This is a diagram of the phase regulator system structure of the distributed phase regulator site selection and capacity determination method considering frequency stability improvement of the present invention.

[0094] Figure 2 This is a physical schematic diagram of node inertia for the distributed phase shifter site selection and capacity determination method considering frequency stability improvement in the present invention.

[0095] Figure 3 This is a wolf pack level classification diagram for the distributed phase shifter site selection and capacity determination method considering frequency stability improvement in the present invention.

[0096] Figure 4 The present invention is a phase regulator configuration flow chart of the distributed phase regulator site selection and capacity determination method considering frequency stability improvement.

[0097] Figure 5 This is a wiring diagram of a simulation system for the method of site selection and capacity determination of distributed phase shifters taking frequency stability improvement into consideration in the present invention.

[0098] Figure 6 This is a comparison chart of system frequency responses before and after phase shifter configuration in the distributed phase shifter site selection and capacity determination method considering frequency stability improvement of the present invention. DETAILED DESCRIPTION

[0099] In order to better understand the purpose, structure and function of the present invention, a method for site selection and capacity determination of a distributed phase-shifting machine considering frequency stability improvement of the present invention is further described in detail below in conjunction with the accompanying drawings.

[0100] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art. Aiming at the frequency stability problem of the power grid at the renewable energy sending end caused by large disturbance failures in the system, a distributed phase-shifting phase selection and sizing strategy considering frequency stability constraints is proposed by solving the optimal model with the minimum configuration capacity as the optimization goal, so as to maximize the frequency support capability of the system.

[0101] Example:

[0102] The invention provides a distributed phase shifter location and capacity determination strategy considering frequency, and the configuration process is as follows: Figure 4 As shown in the figure, computational analysis is carried out on the IEEE 10-machine 39-node simulation system to verify the effectiveness of the proposed calculation method.

[0103] The NEW ENGLAND 10-machine 39-node system with wind farm Figure 5 As shown in Table 3, G5, G7, and G10 are replaced with double-fed wind turbines with the same output, and double-fed wind turbines with capacities of 200MVA, 200MVA, and 300MVA are connected to G6, G8, and G9 respectively. The parameters of generators G1, G2, G3, G4, G6, G8, and G9 are shown in Table 3 to verify the correctness of the proposed method. Set nodes 15, 20, and 25 to have a sudden load increase at 0.5s ( Figure 6 The power disturbances are 300%, 200%, and 250% of the load respectively. The reference frequency is 50Hz, = 0.1Hz / s, and the maximum allowable frequency deviation is 0.5Hz. The inertia time constant of the configured distributed phase regulator is 2s, and the capacity is 50Mvar.

[0104] Under the above working conditions, the minimum critical inertia of the system is calculated through the limit values ​​of the maximum frequency change rate and the maximum frequency deviation. According to the system-related parameters, the inertia of all nodes is calculated, the system inertia distribution is evaluated, the minimum inertia node is found, and a phase regulator is configured at the new energy station closest to the minimum inertia node. After configuration, the node inertia is recalculated, and the minimum inertia node is found to continue to configure the phase regulator until the minimum inertia node is greater than the system minimum critical inertia.

[0105] The phase condenser configuration results are shown in Table 1. It is necessary to configure 3 phase condensers at the new energy station G5, 1 phase condenser at the new energy station G6, 3 phase condensers at the new energy station G7, 1 phase condenser at the new energy station G8, 2 phase condensers at the new energy station G9, and 3 phase condensers at the new energy station G10, totaling 13 phase condensers.

[0106] Table 1 Phase condenser configuration results

[0107]

[0108] The inertia center frequency curve of the system before and after the optimized configuration of the phase regulator is as follows Figure 6 As shown, the inertial center frequency reflecting the system frequency has been significantly optimized. and RoCoF max All are within the permitted range.

[0109] It is to be understood that the present invention is described by some embodiments, and it is known to those skilled in the art that various changes or equivalent substitutions may be made to these features and embodiments without departing from the spirit and scope of the present invention. In addition, under the teachings of the present invention, these features and embodiments may be modified to adapt to specific circumstances and materials without departing from the spirit and scope of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application are within the scope of protection of the present invention.

Claims

1. A method for site selection and capacity determination of distributed phase-shifting generators considering frequency stability improvement, characterized in that: Specifically include the following steps, and the following steps are performed in sequence: Step 1: Calculate and construct the power system node inertia Define the inertia H of node k k is the ratio of the disturbance power to the initial frequency change rate at node k, that is: Where: ΔP is the disturbance power, f k is the frequency of node k; Augmented Admittance Array Y s As shown in formula (2): Where: Y n It is the diagonal array formed after the transient reactance of the generator is converted into admittance; Y nn and Y mm is the self-admittance of the generator and other network nodes; Y ln and Y lm Y is the equivalent admittance after the loads at the generator and other network nodes are simplified to equivalent admittance; nm and Y mn is the mutual admittance between the generator and other network nodes, and the conductance is neglected; The network equation is shown in formula (3): Y1=Y n Y2=[-Y n ,0] Y3=[-Y n ,0] T Where: U e and U net is the voltage of the generator terminal node and other nodes; I n is the current input from the potential node in the generator to the network; Y1, Y2, Y3, and Y4 are the four regions of the augmented admittance matrix; Step 2: Calculation of critical inertia of power system Step 2-1: System critical inertia based on RoCoF constraints The critical inertia of the system based on the RoCoF constraint is: Where: ΔP max is the maximum disturbance power, RoCoF max It can be expressed as the maximum value of the system frequency change rate; Step 2-2: Based on Constrained system critical inertia The inertia of the node with the smallest inertia is specified to be greater than the critical inertia: Step 3: Distributed phase-shifting optimization configuration strategy based on the Grey Wolf Optimization Algorithm Step 3-1: Distributed condenser optimization configuration objective function The optimal configuration target of the phase regulator is: Where: S is the total capacity of the phase regulator, S i is the phase-shifting capacity configured at the renewable energy station, and n is the number of renewable energy stations in the system; Step 3-2: Grey Wolf Optimization Algorithm The Grey Wolf Optimization Algorithm is used to find the optimal configuration capacity of distributed phase regulators. The optimization goal is to minimize the configuration capacity and maximize the economy. The critical inertia of the maximum frequency deviation and the maximum frequency change rate stability constraint is used as the constraint condition to construct a site selection and capacity determination strategy to achieve optimal configuration. Step 3-3: Distributed condenser optimization configuration strategy The process includes the following steps, which are performed in sequence: Step 3-3-1: Read the grid structure and related parameters of the power grid; Step 3-3-2: Determine the maximum frequency change rate and the maximum frequency deviation limit values ​​that can ensure system stability, and use them to calculate the critical inertia of the system; Step 3-3-3: Calculate the node inertia according to the system related parameters, evaluate the system inertia distribution, and find the minimum inertia node; Step 3-3-4: Check whether the inertia of the minimum inertia node in the system is lower than the critical inertia. If so, a phase regulator needs to be configured; Step 3-3-5: Calculate the sensitivity of the minimum inertia node inertia to the phase shifter inertia at each pre-configured node. The expression is shown in formula (20), and find the configuration position with the best sensitivity. In the formula, B jk is the admittance between node j and node k, r kj is the element in the matrix R corresponding to the voltage relationship between node k and generator j, H j is the inertia of generator j; Step 3-3-6: Input the objective function and constraints, and use the Grey Wolf Optimization Algorithm to obtain the configuration plan; recheck whether the inertia of the system's minimum inertia node is lower than the critical inertia, if so, repeat step 3-3-3; if reasonable, output the configuration result to form the final site selection and sizing configuration strategy.

2. The method for site selection and capacity determination of distributed phase condensers considering frequency stability improvement according to claim 1 is characterized in that: In step 1, the voltage of the network nodes other than the generator nodes in the power grid is represented by the voltage of the potential node in the generator according to formula (3): IN net =RU e (4) R=-Y4 -1 Y3 Where: U e and U net is the voltage of the generator terminal node and other nodes, R represents the correlation matrix between voltages, and the size of its elements is mainly affected by the grid admittance matrix; According to formula (4), the node voltage is expressed by the generator voltage: Where: k 、V j , δ j are the voltage at node k and the internal potential of generator j, respectively; r kj is the element in the matrix R corresponding to the voltage relationship between node k and generator j; j∈k means taking the element r in the row where node k is located in R kj ; The frequency of node k is obtained from formula (7): Where: f j is the frequency of generator j; When disturbance power ΔP appears at node k, each generator shares the disturbance power according to the synchronous power coefficient: Where: ΔP j is the unbalanced power shared by generator j, D jk is the synchronous power factor of generator j; According to formula (8) and the rotor motion equation df i / dt=ΔP, the frequency change rate of generator j is shown in formula (10): Where: H j is the inertia of generator j; Combining formulas (8) and (10), the inertia of node k is obtained as:

3. The method for site selection and capacity determination of distributed phase shifters considering frequency stability improvement according to claim 1 is characterized in that: In the step 2-2, The critical inertia expression under constraint is: Where: f B is the reference frequency, t madir is the moment when the lowest frequency point occurs; Based on RoCoF max Constraints and The minimum inertia of the constrained system is: The critical inertia is shown in formula (15): Where: H min It is the critical inertia for the safety and stability of the system.

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