Transient stability constraint-based coordinated configuration method for network-constructing energy storage and phase modifier

Abstract

The invention discloses a transient stability constraint-based network construction type energy storage and phase modifier coordinated configuration method. The method comprises the following steps of S1, constructing a target function taking the minimum comprehensive cost in a new energy base as a target; s2, constructing constraint conditions, wherein the constraint conditions comprise a power flow constraint, an investment cost constraint, a new energy base delivery power constraint, a new energy unit power constraint, a network construction type energy storage equipment constraint and a transient stability constraint; s3, adopting an improved sparrow algorithm to solve the target function; s4, obtaining a coordinated configuration scheme of the network construction type energy storage and the phase modifier; according to the method, a power angle and frequency stability constraint model of a new energy base is established on the influence of transient power angle stability and frequency stability generated by access of network-building type equipment based on a virtual synchronous inertia quantification model of network-building type energy storage and network-building type wind and light equipment, and the power angle and frequency stability constraint model of the new energy base is established by taking the minimum comprehensive cost as a target and fully considering constraint conditions. The frequency stability of the system is improved to a certain extent, and the total cost is reduced.

Description

Technical Field

[0001] This invention relates to the field of power grid safety, stability and control technology, and in particular to a method for coordinated configuration of grid-connected energy storage and synchronous condensers based on transient stability constraints. Background Technology

[0002] With the promotion and application of clean energy, new energy sources, represented by wind power and photovoltaics, are developing rapidly towards large-scale and centralized development. However, the grid connection of new energy units through power electronic equipment significantly reduces the frequency regulation capability and power angle stability of the entire power system. New energy bases are typically concentrated in resource-rich areas, and their power transmission relies on long-distance transmission channels. In the event of large power loss or short-circuit faults, problems such as power angle loss of synchronization or frequency exceeding limits are easily triggered. Grid-based control technology can use control strategies to enable converters to simulate the operating mechanism of synchronous generators, actively providing virtual inertia and damping to the system, thereby enhancing the stability support capability of the power grid. Therefore, ensuring the transient stability of new energy bases through the scientific and rational coordinated configuration of grid-based energy storage and synchronous condensers is a prerequisite for economically and efficiently improving the stability of new energy bases.

[0003] However, current research mostly focuses on control strategies or configuration studies for single types of equipment, lacking models for the coordinated optimization configuration of multi-element grid-connected equipment based on the overall system stability requirements. Furthermore, the configuration process fails to meticulously consider the rigid constraints of transient power angle stability and frequency stability. Therefore, conducting research on the optimized configuration of grid-connected equipment in new energy bases, considering power angle and frequency stability constraints, has significant theoretical and engineering value for promoting the safe and efficient consumption of new energy and ensuring the safe and stable operation of new power systems. Summary of the Invention

[0004] To overcome the above problems, the purpose of this invention is to provide a coordinated configuration method for grid-type energy storage and synchronous condensers based on transient stability constraints. This method is based on a virtual synchronous inertia quantification model of grid-type energy storage and grid-type wind and solar equipment. It establishes a power angle and frequency stability constraint model for new energy bases to address the impact of transient power angle stability and frequency stability caused by the access of grid-type equipment. With the goal of minimizing overall cost, it fully considers the constraints and improves the frequency stability of the system to a certain extent while reducing the total cost.

[0005] The technical solution adopted in this invention is:

[0006] The method for coordinated configuration of grid-type energy storage and synchronous condensers based on transient stability constraints includes the following steps:

[0007] S1: Construct an objective function with the goal of minimizing the overall cost within the new energy base.

[0008] S2: Construct constraints, including power flow constraints, investment cost constraints, power transmission constraints from new energy bases, power constraints of new energy units, constraints of grid-type energy storage equipment, and transient stability constraints.

[0009] S3: The objective function is solved using an improved sparrow algorithm.

[0010] S4: Obtain a coordinated configuration scheme for grid-type energy storage and synchronous condensers.

[0011] As a further description of the present invention, the objective function in S1 is based on the virtual synchronous inertia quantization model of grid-type equipment in new energy bases, taking into account the investment cost of grid-type equipment. Operating costs Maintenance costs and processing costs Comprehensive cost The calculation formula is as follows:

[0012] .

[0013] .

[0014] in, , , , The first Investment cost per unit capacity, operating cost per unit power, maintenance cost per unit power, and disposal cost per unit capacity for grid-type equipment; , for Within the time period Construction capacity and operating power of grid-type equipment; For the first The service life of seed-structured mesh equipment; It is the present value factor. ; is the discount rate for funds; T is the equipment lifecycle.

[0015] As a further description of the present invention, the transient stability constraint is a power angle stability constraint and a frequency stability constraint, wherein the frequency stability constraint includes a frequency change rate constraint and a minimum point frequency constraint.

[0016] The power angle stability constraint is:

[0017] .

[0018] in, It serves as an evaluation index for transient work angle stability. for The result after minimization The smaller the value, the stronger the transient power angle stability of the system.

[0019] As a further description of the present invention, the frequency change rate The constraints are:

[0020] .

[0021] in, The maximum rate of change of frequency as specified in the standard; subscript Indicates the instant of the disturbance; , To separately disturb the virtual synchronization inertia of the l-th grid-type wind farm and the energy storage power station; Indicates the first stand; For all power plants; For virtual synchronization inertia; This refers to the active power of the energy storage power station; The active power of a grid-type wind farm; This is the system's power deficit; The system's rated frequency;

[0022] .

[0023] in, for Rate of change of frequency at any given moment;

[0024] As a further description of the present invention, the lowest point frequency The constraints are:

[0025] .

[0026] In the formula: The frequency threshold for triggering the low-frequency load shearing device; This is the lowest frequency for the new energy base.

[0027] As a further description of the present invention, the power flow constraint in S2 is as follows:

[0028] .

[0029] in, , They represent The voltage at nodes b and c of the new energy base at all times; , They are respectively Active and reactive power of node b in the new energy base at all times; , , These represent the conductance, susceptance, and phase angle difference between nodes b and c, respectively.

[0030] The investment cost constraint is:

[0031] .

[0032] in, This represents the maximum investment amount for the energy storage system; the power transmission constraint of the new energy base is:

[0033] .

[0034] .

[0035] .

[0036] .

[0037] in, The actual transmission power during time period t; , These are transmission power limits; , These are binary state variables for upward and downward adjustment, respectively; , These are the maximum climbing power and landslide power limits, respectively. The limit on the number of power adjustments within a scheduling cycle; This is the number of segments operating at the lowest current power after adjustment; Maximum time limit; For the upward adjustment of the binary state variable in time period t+1; Let be the binary state variable for the downward adjustment during time period t+1.

[0038] The power constraint of the new energy unit is:

[0039] .

[0040] in, , These represent the maximum output values ​​for wind power and solar power, respectively. These represent the power outputs of wind power and solar power at time t, respectively.

[0041] The constraints of the grid-type energy storage device are:

[0042] ,

[0043] ,

[0044] in, , These represent the upper and lower limits of the energy storage system capacity, respectively. For energy storage system capacity; , These represent the storage and discharge power of the energy storage device at time t, respectively. , , , These represent the upper and lower limits of the energy storage and dissipation power of the energy storage system, respectively. , These represent the storage and release states of the energy storage system at time t, with values ​​of 0 or 1 indicating that the equipment is in a shutdown or operating state. .

[0045] As a further description of the present invention, the specific process of solving the problem using the improved sparrow algorithm in S3 is as follows:

[0046] S31: The population is initialized using the Circle chaotic mapping, the number of iterations is set, and the ratio of discoverers to joins is initialized. The initialization calculation formula is as follows:

[0047] .

[0048] in, For the modulo operation, the first... Item mapping value mapped to ; The first in the chaotic sequence One value; The first in the chaotic sequence One value; for A random number between [a certain number of points].

[0049] S32: Calculate and sort the fitness values, and designate individuals with high fitness in the sparrow population as discoverers, and the rest as joiners.

[0050] S33: The discoverer updates its own position based on its fitness and the positions of other discoverers. No. The formula for updating the wheel's position is:

[0051] .

[0052] in, , The discoverers In the Vidi Wheel, First The position matrix of the wheels; for A random number; It is the maximum number of iterations; This is a warning value; For a safe value

[18] , , All Random numbers between; It is a normally distributed random number; For all internal elements are 1 The matrix.

[0053] S34: Joiners update their positions based on the group's best position. No. The formula for updating the wheel's position is:

[0054] .

[0055] in, This is the optimal position for the discoverer to date; It represents the discoverer's current worst-case position globally; A is a matrix whose elements are either 1 or -1. .

[0056] when This indicates that sparrows with lower adaptability have not found food and need to go elsewhere to forage.

[0057] S35: In each iteration, 10%–20% of sparrows are randomly selected from the population to act as watchdogs. Once a threat is detected, they will adjust their positions to escape the pursuer. The formula for updating the watchdog's position is as follows:

[0058] .

[0059] in, These are random numbers distributed according to a standard normal distribution. yes Random numbers; This represents the current fitness value of the individual sparrow. This represents the globally optimal fitness value. This represents the worst fitness value globally. For the first The optimal position of the sparrow individual for the vigilant in the next iteration; for The worst-case position of the sparrow in the next iteration; It is a minimum value.

[0060] when At this time, sparrows are vulnerable to attacks from predators; when The sparrows realized the danger and moved closer to the other sparrows.

[0061] S34: When the number of iterations reaches the preset maximum number of iterations, the algorithm stops running and outputs the optimal solution.

[0062] As a further description of the present invention, the virtual synchronous inertia quantization model for grid-type equipment in new energy bases includes a virtual synchronous inertia quantization model for energy storage equipment and a virtual synchronous inertia quantization model for wind and solar power.

[0063] As a further description of the present invention, the virtual synchronous inertia quantization model of the energy storage device uses a linear mapping to represent the virtual inertia of electrochemical energy storage. Its formula is:

[0064] .

[0065] in, , These represent the historical extreme values ​​of the virtual inertia of the electrochemical energy storage power station, namely the maximum and minimum values, respectively. , Represents the maximum and minimum output of new energy sources; This represents the real-time output of new energy sources.

[0066] As a further description of the present invention, the wind-solar virtual synchronization inertia The quantization model has the following formula:

[0067] .

[0068] in, The rated installed capacity of the wind farm This represents the total number of wind turbines operating in the wind farm. Let n be the rated installed capacity of the nth wind turbine. Let be the virtual synchronous inertia of the nth wind turbine.

[0069] The beneficial effects of this invention are:

[0070] This invention presents a method for coordinated configuration of grid-connected energy storage and synchronous condensers based on transient stability constraints. This method quantifies the virtual synchronous inertia of grid-connected equipment containing energy storage, wind power, and photovoltaics. It constructs an optimized configuration model for grid-connected equipment in new energy bases, comprehensively considering transient power angle and frequency stability constraints. With the goal of minimizing overall cost, it fully considers constraints such as investment cost, power transmission, power angle, and frequency stability. Finally, the coordinated configuration model is solved to verify the rationality of the method, which improves the frequency stability of the system to a certain extent while reducing the total cost. Attached Figure Description

[0071] Figure 1 This is the overall flowchart of the present invention.

[0072] Figure 2 This is a topological diagram of the new energy base in Embodiment 5 of the present invention.

[0073] Figure 3 This is a daily photovoltaic and wind power output curve of the new energy base in Embodiment 5 of the present invention.

[0074] Figure 4 This is a daily load demand curve of the new energy base in Embodiment 5 of the present invention.

[0075] Figure 5 This is a diagram showing the minimum daily inertia requirement of a new energy base in Embodiment 5 of the present invention. Detailed Implementation

[0076] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0077] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0078] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0079] This invention is described in detail with reference to the schematic diagrams. When detailing the embodiments of this invention, for ease of explanation, the cross-sectional views illustrating the device structure may be partially enlarged, not adhering to the usual scale. Furthermore, the schematic diagrams are merely examples and should not be construed as limiting the scope of protection of this invention. In actual fabrication, the three-dimensional spatial dimensions of length, width, and depth should be included.

[0080] Furthermore, in the description of this invention, it should be noted that the terms "upper," "lower," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are used solely for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. In addition, the terms "first," "second," or "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0081] Unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" in this invention should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; similarly, they can refer to mechanical connections, electrical connections, or direct connections, or indirect connections through an intermediate medium, or internal connections between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0082] like Figures 1-5 As shown, it illustrates a specific embodiment of the present invention:

[0083] Example 1:

[0084] The method for coordinated configuration of grid-type energy storage and synchronous condensers based on transient stability constraints includes the following steps:

[0085] S1: Construct an objective function with the goal of minimizing the overall cost within the new energy base.

[0086] Specifically, the objective function in S1 is based on the virtual synchronous inertia quantization model of grid-type equipment in new energy bases, taking into account the investment cost of grid-type equipment. Operating costs Maintenance costs and processing costs Comprehensive cost The calculation formula is as follows:

[0087] .

[0088] .

[0089] in, , , , The first Investment cost per unit capacity, operating cost per unit power, maintenance cost per unit power, and disposal cost per unit capacity for grid-type equipment; , for Within the time period Construction capacity and operating power of grid-type equipment; For the first The service life of seed-structured mesh equipment; It is the present value factor. ; is the discount rate for funds; T is the equipment lifecycle.

[0090] S2: Construct constraints, including power flow constraints, investment cost constraints, power transmission constraints from new energy bases, power constraints of new energy units, constraints of grid-type energy storage equipment, and transient stability constraints.

[0091] S3: The objective function is solved using an improved sparrow algorithm.

[0092] S4: Obtain a coordinated configuration scheme for grid-type energy storage and synchronous condensers.

[0093] Example 2:

[0094] Specifically, the power flow constraints in S2 are as follows:

[0095] .

[0096] in, , They represent The voltage at nodes b and c of the new energy base at all times; , They are respectively Active and reactive power of node b in the new energy base at all times; , , These represent the conductance, susceptance, and phase angle difference between nodes b and c, respectively.

[0097] The investment cost constraint is:

[0098] .

[0099] in, This indicates the maximum investment amount for an energy storage system.

[0100] The power transmission constraint of the new energy base is:

[0101] ,

[0102] ,

[0103] ,

[0104] ,

[0105] in, The actual transmission power during time period t; , These are transmission power limits; , These are binary state variables for upward and downward adjustment, respectively; , These are the maximum climbing power and landslide power limits, respectively. The limit on the number of power adjustments within a scheduling cycle; This is the number of segments operating at the lowest current power after adjustment; Maximum time limit; For the upward adjustment of the binary state variable in time period t+1; This is the binary state variable for the downward adjustment during time period t+1.

[0106] The power constraint of the new energy unit is:

[0107] ,

[0108] in, , These represent the maximum output values ​​for wind power and solar power, respectively. These represent the power outputs of wind power and solar power at time t, respectively.

[0109] The constraints of the grid-type energy storage device are:

[0110] ,

[0111] ,

[0112] in, , These represent the upper and lower limits of the energy storage system capacity, respectively. For energy storage system capacity; , These represent the storage and discharge power of the energy storage device at time t, respectively. , , , These represent the upper and lower limits of the energy storage and dissipation power of the energy storage system, respectively. , These represent the storage and release states of the energy storage system at time t, with values ​​of 0 or 1 indicating that the equipment is in a shutdown or operating state. .

[0113] Example 3:

[0114] Specifically, the process of solving S3 using the improved sparrow algorithm is as follows:

[0115] In this embodiment, the traditional Sparrow Algorithm generates the initial population in a random manner, which may lead to uneven population distribution and affect diversity and convergence. Therefore, this embodiment adopts an improved Sparrow Algorithm based on this.

[0116] S31: The population is initialized using the Circle chaotic mapping, the number of iterations is set, and the ratio of discoverers to joins is initialized. The initialization calculation formula is as follows:

[0117] .

[0118] in, For the modulo operation, the first... Item mapping value mapped to ; The first in the chaotic sequence One value; The first in the chaotic sequence One value; for A random number between [a certain number of points].

[0119] S32: Calculate and sort the fitness values, and designate individuals with high fitness in the sparrow population as discoverers, and the rest as joiners.

[0120] S33: The discoverer updates its own position based on its fitness and the positions of other discoverers. No. The formula for updating the wheel's position is:

[0121] .

[0122] in, , The discoverers In the Vidi Wheel, First The position matrix of the wheels; for A random number; It is the maximum number of iterations; This is a warning value; For a safe value

[18] , , All Random numbers between; It is a normally distributed random number; For all internal elements are 1 The matrix.

[0123] S34: Joiners update their positions based on the group's best position. No. The formula for updating the wheel's position is:

[0124] .

[0125] in, This is the optimal position for the discoverer to date; It represents the discoverer's current worst-case position globally; A is a matrix whose elements are either 1 or -1. ;when This indicates that sparrows with lower adaptability have not found food and need to go elsewhere to forage.

[0126] S35: In each iteration, 10%–20% of sparrows are randomly selected from the population to act as watchdogs. Once a threat is detected, they will adjust their positions to escape the pursuer. The formula for updating the watchdog's position is as follows:

[0127] .

[0128] in, These are random numbers distributed according to a standard normal distribution. yes Random numbers; This represents the current fitness value of the individual sparrow. This represents the globally optimal fitness value. This represents the worst fitness value globally. For the first The optimal position of the sparrow individual for the vigilant in the next iteration; for The worst-case position of the sparrow in the next iteration; It is a minimum value; when At this time, sparrows are vulnerable to attacks from predators; when The sparrows realized the danger and moved closer to the other sparrows.

[0129] S36: When the preset maximum number of iterations is reached, the algorithm stops and outputs the optimal solution. In each iteration of the algorithm, the current fitness value is repeatedly evaluated, and the positions of each sparrow are constantly changed to keep them in a region closer to the optimal solution.

[0130] Example 4:

[0131] Specifically, the virtual synchronous inertia quantification model for grid-type equipment in the new energy base includes a virtual synchronous inertia quantification model for energy storage equipment and a virtual synchronous inertia quantification model for wind and solar power.

[0132] The virtual synchronous inertia quantization model of the energy storage device uses a linear mapping to represent the virtual inertia of electrochemical energy storage. Its formula is:

[0133] .

[0134] in, , These represent the historical extreme values ​​of the virtual inertia of the electrochemical energy storage power station, namely the maximum and minimum values, respectively. , Represents the maximum and minimum output of new energy sources; This represents the real-time output of new energy sources.

[0135] The virtual synchronization inertia of wind and solar power The quantization model has the following formula:

[0136] ,

[0137] in, The rated installed capacity of the wind farm This represents the total number of wind turbines operating in the wind farm. Let n be the rated installed capacity of the nth wind turbine. Let be the virtual synchronous inertia of the nth wind turbine.

[0138] Specifically, the transient stability constraints are power angle stability constraints and frequency stability constraints.

[0139] The power angle stability constraint is:

[0140] .

[0141] in, It serves as an evaluation index for transient work angle stability. for The result after minimization The smaller the value, the stronger the transient power angle stability of the system.

[0142] The frequency stability constraints include frequency change rate constraints and minimum point frequency constraints. The frequency change rate... The constraints are:

[0143] .

[0144] in, The maximum rate of change of frequency as specified in the standard; subscript Indicates the instant of the disturbance; , To separately disturb the virtual synchronization inertia of the l-th grid-type wind farm and the energy storage power station; Indicates the first stand; For all power plants; For virtual synchronization inertia, For the active power of the energy storage power station, For the active power of grid-type wind farms, For the system's power deficit, This is the system's rated frequency.

[0145] .

[0146] Among them, Rate of change of frequency at time, This represents the maximum rate of change of frequency.

[0147] In this embodiment, the lowest frequency satisfies the following condition after the system is disturbed: The time it takes for the system frequency to drop to its lowest point after a disturbance. With frequency , can be represented as:

[0148] ,

[0149] ,

[0150] in, The reference frequency; For the unit Gain coefficient; For the unit The response time constant, The initial frequency, For system short-circuit capacity, The change in frequency For the unit The frequency modulation control signal is between 0 and 1. For the unit Frequency modulation capacity coefficient.

[0151] Therefore, the minimum frequency constraint of the new energy base can be expressed as:

[0152] .

[0153] In the formula: The frequency threshold for triggering the low-frequency load shearing device; This is the lowest frequency for the new energy base.

[0154] Example 5:

[0155] In this embodiment, based on the established model, and using actual wind power, photovoltaic, and load data of a new energy base in Northwest China that includes wind power and photovoltaic power stations, an equivalent topology of the new energy base was constructed as follows: Figure 2 As shown. The total installed capacity of wind power is 2.6GW, and the total installed capacity of photovoltaic power is 0.8GW, with a base capacity of 100MVA. To meet the system inertia support requirements, it is planned to configure at least 200MW of grid-type energy storage equipment; other specific relevant parameters of the example system are shown in Table 1 below; the relevant investment and operating cost coefficients of the grid-type energy storage equipment are shown in Table 2 below; based on the distribution function of wind speed, solar intensity and load data for each period of the year in this region, the daily wind power output, daily photovoltaic power output and daily load demand curves are obtained after normalization processing as shown below. Figure 3 , Figure 4 As shown; the minimum inertia requirement for a typical intraday new energy base is as follows: Figure 5 As shown.

[0156] To verify the effectiveness of the proposed optimal configuration model for grid-type equipment in new energy bases, which considers power angle and frequency stability constraints, two scenarios were set up:

[0157] Scenario 1: This paper presents a coordinated configuration model for grid-type energy storage and synchronous condensers in a new energy base, considering transient stability constraints.

[0158] Scenario 2: Coordinated configuration model of grid-type energy storage and synchronous condenser in new energy bases without considering transient stability constraints.

[0159] Table 1 Other specific relevant parameters of the simulation system

[0160] parameter numerical values parameter numerical values W1 Rated Power 700 PV1 rated power 150 W2 Rated Power 750 PV2 rated power 300 W3 Rated Power 500 PV3 rated power 200 W4 Rated Power 650 PV4 rated power 150 DC power transmission 0.82 Load power factor 0.9~0.95

[0161] Table 2 Investment and operating cost coefficients related to grid-type energy storage equipment

[0162] parameter Energy storage devices Distributed synchronous condenser Centralized synchronous condenser Construction cost (ten thousand yuan / MVar) 60 60 50 Operation and maintenance costs (ten thousand yuan / MVar) 20 50 40 efficiency(%) 92 99 98 Disposal Conversion Factor 0.085 0.065 0.065 Service life / year 20 20 20 Upper limit of state of charge 0.82 / / State of charge limit 0.16 / /

[0163] The camera was optimized and the configuration results are shown in Table 3 below. The optimized operation results of the new energy base before and after accessing the multi-network type equipment were analyzed to obtain the optimization results of the new energy base under scenario one and scenario two, as shown in Table 4 below.

[0164] Table 3. Results of Camera Optimization Configuration

[0165] Energy storage equipment (MW) Distributed camera condenser (MVar) Centralized condenser (MVar) Scene 1 85 75 40 Scene 2 80 82 45

[0166] Table 4 Optimized Operation Results of the New Energy Base

[0167] type Scene 1 Scene 2 Transient overvoltage peak / pu 1.16 1.3 Power angle instability rate of power generation equipment under fault influence / % 3.4 6.1 Investment cost / 10,000 yuan 11600 11970 Maintenance cost / 10,000 yuan 4630 5274 Processing cost / 10,000 yuan 856 874 Total cost / 10,000 yuan 17086 18118

[0168] Analysis of the simulation results obtained from Tables 3 and 4 shows that, compared with Scenario 2, the grid-type energy storage configuration of the new energy base proposed in this paper, while improved, can reduce the configuration capacity of synchronous condensers by 10.44%, thereby reducing investment costs and lowering the overall cost of the energy storage system by 6.04%. Under the influence of two consecutive DC commutation failures and blockage faults, the peak transient overvoltage of the new energy base decreased by 12.07%, and the power angle instability rate of the thermal power unit decreased by 94.29%.

[0169] The preferred embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present invention.

[0170] Many other changes and modifications can be made without departing from the concept and scope of this invention. It should be understood that this invention is not limited to the specific embodiments, and the scope of this invention is defined by the appended claims.

Claims

1. A method for coordinated configuration of network-forming energy storage and phase modulators based on transient stability constraints, characterized in that, The method comprises the following steps: S1: constructing a target function with the minimum comprehensive cost in a new energy base as a target; S2: constructing a constraint condition, the constraint condition comprising a power flow constraint, an investment cost constraint, a new energy base out-of-base power constraint, a new energy unit power constraint, a network-constructed energy storage device constraint, and a transient stability constraint; S3: solving the target function by using an improved sparrow algorithm; S4: obtaining a coordinated configuration scheme of the network-constructed energy storage and the phase modifier.

2. The method of claim 1, wherein the method is characterized by, The objective function in the S1 is based on a new energy base network type device virtual synchronous inertia quantitative model, considering the comprehensive cost of investment cost, operation cost, maintenance cost and processing cost of the network type device , and the calculation formula is:​​​​ ， ， in, , , , The first Investment cost per unit capacity, operating cost per unit power, maintenance cost per unit power, and disposal cost per unit capacity for grid-type equipment; , for Within the time period Construction capacity and operating power of grid-type equipment; For the first The service life of seed-structured mesh equipment; It is the present value factor. ; is the discount rate for funds; T is the equipment lifecycle.

3. The method of claim 2, wherein the method is characterized by, The transient stability constraint is a power angle stability constraint and a frequency stability constraint, and the frequency stability constraint comprises a frequency change rate constraint and a minimum point frequency constraint; The power angle stability constraint is: ， wherein, is an evaluation index of transient power angle stability, is the result after the minimization process, the smaller indicates the stronger transient power angle stability of the system.

4. The method of claim 3, wherein the method is characterized by, the rate of change of frequency with the constraint that: ， wherein, is the maximum value of the frequency rate of change specified by the regulation; subscript denotes the instant of disturbance; , is the virtual synchronous inertia of the disturbed l-th wind farm of grid-forming type and energy storage power station, respectively; denotes the l-th power station; is all power stations; is the virtual synchronous inertia; is the active power of the energy storage power station; is the active power of the grid-forming wind farm; is the power deficiency of the system; is the rated frequency of the system; ， wherein is the rate of change of frequency over time.

5. The method of claim 3, wherein the method is characterized by, the lowest frequency with the constraint that: ， In the formula: is the frequency threshold of the low-frequency load shedding device; is the minimum point frequency of the new energy base.

6. The method of claim 2, wherein the method is characterized by, The power flow constraint in S2 is: ， wherein, , respectively represent the voltage of the new energy base node b, c at the moment; , respectively represent the active power and the reactive power of the new energy base node b at the moment; , , respectively represent the conductance, the susceptance and the phase angle difference between the nodes b and c. The investment cost constraint is: ， wherein, represents the maximum investment amount of the energy storage system; The new energy base out-of-base power constraint is: ， , , , wherein, is the actual transmission power for the t period; , are transmission power limits, respectively; , are up and down adjustment binary state variables, respectively; , are maximum ramp up and ramp down power limits, respectively; is the power adjustment limit within a scheduling period; is the number of periods of minimum operation at current power after adjustment; is the time upper limit; is the up adjustment binary state variable for the t+1 period; is the down adjustment binary state variable for the t+1 period; The new energy unit power constraint is: ， wherein, , are the maximum values of the wind and photovoltaic power outputs, respectively; are the wind and photovoltaic power outputs at time t, respectively. The network-constructed energy storage device constraint is: ， ， wherein, , respectively represent the upper and lower limits of the energy storage system capacity; is the energy storage system capacity; , respectively represent the charging and discharging power of the energy storage device at time t; , , , respectively represent the upper and lower limits of the energy storage system charging and discharging power; , respectively represent the charging and discharging state of the energy storage system at time t, taking values of 0 or 1, indicating that the device is in a shutdown or working state, .

7. The method of claim 1, wherein, The specific process of solving by using the improved sparrow algorithm in S3 is: S31: initializing a population by using a Circle chaotic mapping, setting an iteration number, initializing a discoverer and a joiner ratio, and the initialization calculation formula is: ， wherein, is the modulo operation, and the first term is mapped to ; is the first value in the chaotic sequence; is the second value in the chaotic sequence; is the first value in the chaotic sequence; is the second value in the chaotic sequence; is a random number between ; S32: calculating an adaptability value and sorting, taking high adaptability individuals in a sparrow population as discoverers, and taking the rest as joiners; S33: The discoverer updates its own position according to its fitness and other discoverer positions, the discoverer The first The position update formula of the wheel is: ， wherein, , are respectively the discoverer In the first the seventh the eighth the position matrix of the wheel; is a random number; is the maximum number of iterations; is the pre-warning value; is the security value [18], , are respectively the random number between the random number between is a random number of normal distribution; is a matrix of whose internal elements are all 1; S34: The subscriber updates his position according to the group optimum position, the subscriber The The position update formula for the wheel is: ， wherein, is the best position found by the current finder; is the worst position found by the current finder; A is a matrix of elements with values 1 or -1, ; S35: randomly selecting 10%-20% sparrows from the population as sentries in each iteration, and once a threat is detected, the position of the sentry is adjusted to escape from the pursuit of the discoverer, and the sentry position update formula is: ， wherein, is a standard normal distribution random number; is a random number; is the current Sparrow individual fitness value; is the global best fitness value; is the global worst fitness value; is the is the best Sparrow individual position at the is is the worst Sparrow individual position at the is a minimum value; when the Sparrow is vulnerable to predators; when the Sparrow realizes that the danger is approaching other Sparrows; S36: when the iteration number reaches a preset maximum iteration number, the algorithm stops running and outputs an optimal solution.

8. The method of claim 2, wherein the method is characterized by, The network-constructed device virtual synchronous inertia quantification model of the new energy base comprises an energy storage device virtual synchronous inertia quantification model and a wind-solar virtual synchronous inertia quantification model.

9. The method of claim 8, wherein the method is characterized by, The energy storage device virtual synchronous inertia quantification model adopts linear mapping to represent the electrochemical energy storage virtual inertia The formula is: ， wherein, , represent the virtual inertia historical extreme values of the electrochemical energy storage power station, respectively the maximum and minimum values; , represent the maximum and minimum output of new energy; represent the real-time output of new energy.

10. The method of claim 8, wherein the method is characterized by, The wind and light virtual synchronous inertia The quantification model is formula: ， wherein, is the rated installed capacity of the wind farm, is the total number of operating wind turbines of the wind farm, is the rated installed capacity of the nth wind turbine, is the virtual synchronous inertia of the nth wind turbine.

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