Power system restoration methods, systems, media, and electronic equipment for black-start power supplies

Abstract

This invention provides a power system restoration method, system, medium, and electronic equipment using black-start power sources, comprising: establishing the frequency-power response characteristics of a first preset generating unit and a second preset generating unit working collaboratively; obtaining a target frequency response model under power deficit conditions due to a load surge based on the frequency-power response characteristics of the collaborative operation; determining the constraints of the power system based on the target frequency response model; obtaining the target frequency response result of each black-start power source to the power system upon startup, combined with the target frequency response model; determining multiple power aggregation methods for each black-start power source based on the target frequency response results and the constraints; and determining the optimal restoration path for each black-start power source in the shortest time based on the shortest path algorithm and each power aggregation method, so as to restore the power system according to the optimal restoration path. This invention solves the problem of low adaptability of existing black-start methods.

Description

Technical Field

[0001] This invention relates to the technical field of power system control, and in particular to a power system restoration method, system, medium, and electronic equipment for black-start power supplies. Background Technology

[0002] Against the backdrop of the low-carbon energy transition, the large-scale grid connection of new energy sources has altered the structure, scale, and operation of the power system, increasing the risk of major blackouts in the new power system. Therefore, enhancing the black-start capability of the power system is a significant requirement for the security defense of the new power system.

[0003] Currently, black start in power systems mainly relies on external power supply or large hydropower units to drive thermal power units that cannot start on their own. For central and northern regions lacking hydropower resources, traditional black start methods suffer from problems such as large regional variations and a lack of backup plans. This deficiency also applies to new power systems, where the volatility of renewable energy generation increases system recovery risk, meaning existing black start methods have low adaptability. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a power system restoration method, system, medium, and electronic equipment for black-start power supplies, solving the problem of low adaptability of existing black-start methods.

[0005] At least one embodiment of the present invention provides a power system restoration method for black-start power supplies, comprising:

[0006] Establish the frequency-power response characteristics of the first and second preset generator units working together;

[0007] Based on the frequency-power response characteristics of the cooperative operation, the step response is taken as the frequency response under power deficit to obtain the target frequency response model of load surge under power deficit.

[0008] Based on the target frequency response model, the constraints of the power system are determined, including power constraints, inertia constraints, frequency change rate constraints, and frequency minimum point constraints.

[0009] By combining the target frequency response model, the target frequency response of each black-start power source to the power system at startup is obtained;

[0010] Based on the target frequency response results and the constraints, the multiple power aggregation methods of each black-start power supply are determined.

[0011] Based on the shortest path algorithm and the power aggregation methods described, the optimal recovery path for each black-start power source in the shortest time is determined, so as to restore the power system according to the optimal recovery path.

[0012] The technical solution disclosed in this invention has at least the following beneficial effects:

[0013] Using the above method, the first and second preset generating units distributed around the power system can be restored in a coordinated manner. By establishing the frequency-power response characteristics of the coordinated operation and the target frequency response model of the load surge under power deficit, the target frequency response results of multiple black-starting power sources distributed around the power system at startup can be determined. Based on the constraints and the above target frequency results, the aggregation mode of multiple black-starting power sources can be determined, and the optimal restoration path can be found to restore the power system.

[0014] This invention can mobilize and combine multiple black-start power sources of various types to restore the power system. Compared with the existing technology that relies on external power supply or drives thermal power units that cannot start on their own through a single large hydropower unit, this invention is more adaptable to the central and northern regions where hydropower resources are scarce.

[0015] In a power system restoration method for a black-start power supply provided in one embodiment of the present invention, the step of establishing the frequency-power response characteristics for the coordinated operation of the first preset unit and the second preset unit includes:

[0016] Establish the first frequency-power response characteristics between the first preset generating unit and the power system, and establish the second frequency-power response characteristics between the second preset generating unit and the power system;

[0017] Based on the first frequency-power response characteristics and the second frequency-power response characteristics, frequency-power response characteristics for the coordinated operation of the first preset unit and the second preset unit are established.

[0018] The technical solution disclosed in this invention has at least the following beneficial effects:

[0019] By establishing the first frequency-power response characteristics and the second frequency-power response characteristics between the first preset generator unit, the second preset generator unit, and the power system, the frequency-power response characteristics of the first preset generator unit and the second preset generator unit working together can be obtained, which facilitates subsequent frequency response analysis.

[0020] In a power system restoration method for a black-start power supply provided in one embodiment of the present invention, the first preset unit is a new energy unit controlled by a virtual synchronous machine, and the step of establishing a first frequency-power response characteristic between the first preset unit and the power system includes:

[0021] Based on the frequency dynamics of the new energy generating units, the first relationship between the output power change of the new energy generating units and the frequency change of the power system is obtained, and the first frequency-power response characteristics between the new energy generating units and the power system are established according to the first relationship.

[0022] The technical solution disclosed in this invention has at least the following beneficial effects:

[0023] By analyzing the frequency dynamics of new energy generating units, the first relationship between their output power changes and the frequency changes of the power system, as well as the first frequency-power response characteristics, can be established sequentially.

[0024] In a power system restoration method for a black-start power supply provided in one embodiment of the present invention, the second preset unit is a small hydropower unit, and the second frequency-power response characteristics between the second preset unit and the power system include:

[0025] Based on the frequency dynamics of the small hydropower unit, the increase in the output power of the small hydropower unit is obtained;

[0026] By combining the water hammer effect of small hydropower units, the response time of speed governors, and transient descent compensation, a second relationship between the output power variation of small hydropower units and the frequency variation of the power system is obtained.

[0027] By combining the increase in the output power of the small hydropower unit with the second relationship, a second frequency-power response characteristic between the small hydropower unit and the power system is established.

[0028] The technical solution disclosed in this invention has at least the following beneficial effects:

[0029] By taking into account the water hammer effect of small hydropower units, the adverse effects of black start regulation can be mitigated or even avoided, thereby improving the power system recovery effect.

[0030] In a power system restoration method for a black-start power supply provided in one embodiment of the present invention, the constraints of the power system are determined according to the target frequency response model. These constraints include power constraints, inertia constraints, frequency change rate constraints, and frequency minimum point constraints, including:

[0031] Based on the target frequency response model, determine the frequency change rate and minimum frequency of the power system;

[0032] By combining the target frequency response model, the rate of frequency change, and the minimum frequency, the steady-state error of the power system is obtained.

[0033] Obtain the power constraints and inertia constraints of the power system, and combine the steady-state error, power constraints, and inertia constraints to determine the frequency change rate constraints and frequency minimum point constraints of the power system.

[0034] The technical solution disclosed in this invention has at least the following beneficial effects:

[0035] Through the above settings, the power constraints, inertia constraints, frequency change rate constraints, and frequency minimum point constraints of the power system can be accurately obtained, providing a constraint basis for the subsequent confirmation of power aggregation methods.

[0036] In a power system restoration method for black-start power sources provided in one embodiment of the present invention, the optimal restoration path for each black-start power source in the shortest time is determined based on the shortest path algorithm and the power source aggregation method, including:

[0037] For each of the power aggregation methods, based on the target frequency response results and the constraints, determine the multiple target black-start power supplies that need to be restored;

[0038] Based on the shortest path algorithm, the recovery order of each node in each target black start power supply is determined, and the recovery order of each node is taken as the undetermined recovery path.

[0039] The recovery path with the shortest recovery time among all the pending recovery paths is selected as the optimal recovery path.

[0040] The technical solution disclosed in this invention has at least the following beneficial effects:

[0041] By finding the optimal recovery path with the shortest time among multiple power aggregation methods, the speed of power system recovery can be accelerated.

[0042] In a power system restoration method for a black-start power source provided in one embodiment of the present invention, based on the shortest path algorithm, the restoration order of each node in each target black-start power source is determined, and the restoration order of each node is taken as the undetermined restoration path, including:

[0043] S1. Select any node as the initial node;

[0044] S2. Use the initial node as the starting node;

[0045] S3. Calculate the time taken to restore the starting node to each of the remaining unrestored nodes, and take the node with the shortest time as the path node.

[0046] S4. Use the path node as the new starting node and return to step S3 until the target node is restored;

[0047] S5. Take the recovery order of each path node as the initial recovery path, select another node that does not overlap with the initial node as the new initial node, and return to step S2 until all nodes have been selected.

[0048] S6. Select the initial recovery path with the shortest time among the initial recovery paths as the pending recovery path.

[0049] The technical solution disclosed in this invention has at least the following beneficial effects:

[0050] The above steps for finding a potential recovery path involve less computation and are faster than existing technologies that typically use network topology-based algorithms to find the shortest path from one point to another.

[0051] At least one embodiment of the present invention provides a power system restoration system for black-start power supplies, comprising:

[0052] The collaborative processing module establishes the frequency-power response characteristics of the collaborative operation of the first and second preset generator units.

[0053] The response module, based on the frequency-power response characteristics of the cooperative operation, takes the step response as the frequency response under power deficit to obtain the target frequency response model for load surge under power deficit.

[0054] The constraint module determines the constraints of the power system based on the target frequency response model. The constraints include power constraints, inertia constraints, frequency change rate constraints, and frequency minimum point constraints.

[0055] The prediction module, combined with the target frequency response model, obtains the target frequency response of each black-start power source to the power system at startup.

[0056] The aggregation method determination module determines multiple power aggregation methods for each of the black-start power supplies based on the target frequency response results and the constraints.

[0057] The optimal path determination module determines the optimal recovery path for each black-start power source in the shortest time based on the shortest path algorithm and the power aggregation method, so as to restore the power system according to the optimal recovery path.

[0058] The present invention also provides a computer-readable storage medium storing instructions that, when executed on a terminal device, cause the terminal device to perform a power system restoration method for a black-start power supply as described above.

[0059] The present invention also provides an electronic device, including a memory, a processor, and a program stored in the memory and running on the processor, wherein the processor executes the program to implement a power system restoration method for a black-start power supply as described above. Attached Figure Description

[0060] Figure 1 This is a schematic flowchart of a power system restoration method for a black-start power supply according to the present invention;

[0061] Figure 2 A frequency response model for virtual synchronous new energy generating units;

[0062] Figure 3 A frequency response model for small hydropower units;

[0063] Figure 4 A frequency response model for the coordinated operation of small hydropower units and new energy units;

[0064] Figure 5 Optimization strategy for recovery path of multi-machine collaborative black boot;

[0065] Figure 6 This is the topology of an IEEE 39-node system.

[0066] Figure 7 The target frequency response result when two power sources are combined;

[0067] Figure 8 The target frequency response result when three or more power sources are aggregated;

[0068] Figure 9 This is a schematic diagram of the power system restoration system of a black-start power supply according to the present invention. Detailed Implementation

[0069] The principles and features of the present invention are described below. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0070] In the black start process of new power systems, this invention utilizes distributed black start power sources to assist in enhancing black start capability. Many regions have a large number of distributed small hydropower stations, and distributed new energy generating units are widely distributed. Virtual synchronization control technology can set the virtual inertia and damping of new energy generating unit systems, making it possible for them to participate in the black start of the power system.

[0071] This research focuses on the black start of large-scale renewable energy units. Through appropriate control methods, it aims to achieve successful grid connection and maintain system stability while enabling these units to start automatically. Based on the widespread existence of small hydropower units and distributed wind and solar power (renewable energy units), this patent investigates the feasibility of black start aggregation of multiple distributed resources (small hydropower, distributed renewable energy, etc.). It emphasizes the impact of different aggregation schemes on auxiliary equipment deployment and their influence on system operation, and improves the shortest path algorithm to obtain the optimal path for multi-point aggregation.

[0072] This invention provides a method for restoring a power system from a black-start power supply; please refer to [reference here]. Figure 1As shown, it includes:

[0073] Establish the frequency-power response characteristics of the first and second preset generator units working together;

[0074] Based on the frequency-power response characteristics of the cooperative operation, the step response is taken as the frequency response under power deficit to obtain the target frequency response model of load surge under power deficit.

[0075] Based on the target frequency response model, the constraints of the power system are determined, including power constraints, inertia constraints, frequency change rate constraints, and frequency minimum point constraints.

[0076] By combining the target frequency response model, the target frequency response of each black-start power source to the power system at startup is obtained;

[0077] Based on the target frequency response results and the constraints, the multiple power aggregation methods of each black-start power supply are determined.

[0078] Based on the shortest path algorithm and the power aggregation methods described, the optimal recovery path for each black-start power source in the shortest time is determined, so as to restore the power system according to the optimal recovery path.

[0079] Using the above method, the first and second preset generating units distributed around the power system can be restored in a coordinated manner. By establishing the frequency-power response characteristics of the coordinated operation and the target frequency response model of the load surge under power deficit, the target frequency response results of multiple black-starting power sources distributed around the power system at startup can be determined. Based on the constraints and the above target frequency results, the aggregation mode of multiple black-starting power sources can be determined, and the optimal restoration path can be found to restore the power system.

[0080] This invention can mobilize and combine multiple black-start power sources of various types to restore the power system. Each power unit represents a black-start power source. Compared with the existing technology that relies on external power supply or uses a single large hydropower unit to drive thermal power units that cannot start on their own, this invention is more adaptable to the central and northern regions where hydropower resources are scarce.

[0081] Specifically:

[0082] S10, the establishment of the frequency-power response characteristics for the coordinated operation of the first preset unit and the second preset unit includes:

[0083] In this embodiment, the first preset unit is a new energy unit controlled by a virtual synchronous machine, and the second preset unit is a small hydropower unit. The first frequency-power response characteristics between the first preset unit and the power system are established, and the second frequency-power response characteristics between the second preset unit and the power system are established.

[0084] The establishment of the first frequency-power response characteristics between the first preset generating unit and the power system includes:

[0085] Based on the frequency dynamics of the new energy generating units, the first relationship between the output power change of the new energy generating units and the frequency change of the power system is obtained. Based on the first relationship, the first frequency-power response characteristics between the new energy generating units and the power system are established. Through the frequency dynamics of the new energy generating units, the first relationship between their output power change and the frequency change of the power system and the first frequency-power response characteristics can be established in sequence.

[0086] More specifically, the process of establishing the first frequency-power response characteristics is as follows:

[0087] Virtual synchronous control technology leverages the flexibility of power electronics to provide frequency support for power systems. The frequency dynamics of a new energy unit controlled by a virtual synchronous machine can be expressed as:

[0088]

[0089] In the above formula, H v The virtual inertia of the virtual synchronous unit is represented by Δf(t), the frequency change of the system at time t, D is the load damping constant, and ΔP is the virtual inertia of the virtual synchronous unit. v (t) represents the increase in generator output power at time t, ΔP e (t) represents the increase in system load at time t. Taking the Laplace transform of equation (1) yields:

[0090]

[0091] For new energy generating units with virtual synchronous control, the first relationship between the generator output power change and the system frequency change in the s-domain can be expressed as equation (2):

[0092]

[0093] R v T is the droop coefficient. v This is the time constant representing the inverter's response speed.

[0094] The relationship between the frequency change and load change of the virtual synchronous new energy unit can be obtained, that is, the first frequency-power response characteristic is:

[0095]

[0096] in

[0097] Figure 2 The control block diagram shown is a frequency response model, which can be used to represent the first frequency-power response characteristics of a virtual synchronous new energy unit.

[0098] The establishment of the second frequency-power response characteristic between the second preset generating unit and the power system includes:

[0099] Based on the frequency dynamics of the small hydropower unit, the increase in the output power of the small hydropower unit is obtained;

[0100] By combining the water hammer effect of small hydropower units, the response time of speed governors, and transient descent compensation, a second relationship between the output power variation of small hydropower units and the frequency variation of the power system is obtained.

[0101] By combining the increase in the output power of the small hydropower unit with the second relationship, a second frequency-power response characteristic between the small hydropower unit and the power system is established.

[0102] By taking into account the water hammer effect of small hydropower units, the adverse effects of black start regulation can be mitigated or even avoided, thereby improving the power system recovery effect.

[0103] More specifically, the process of establishing the second frequency-power response characteristics is as follows:

[0104] Small hydropower units have fast start-up, shutdown, and grid connection speeds, and can participate in the black start process during grid restoration after major power outages. However, the water hammer effect of small hydropower units can adversely affect the black start regulation process. The water hammer effect of small hydropower units can be expressed as:

[0105]

[0106] P m G represents the mechanical power of the hydroelectric generator, G represents the guide vane position, and T represents the mechanical power of the hydroelectric generator. w Let be the time constant for the water hammer effect. Equation (5) represents the relationship between the output power of the hydroelectric generator and the guide vane opening, i.e., the initial power impact is opposite to the direction of the guide vane position change. This phenomenon is called the water hammer effect. Due to the power characteristics of the hydroelectric generator, it cannot meet the requirement of a 5% steady-state descent rate for the entire power system. Therefore, to ensure the stable operation of the system, a transient descent compensation element needs to be introduced into the hydroelectric generator model. The transfer function is shown in Equation (6):

[0107]

[0108] In the formula (6) shown above, R h R is the droop coefficient for small hydropower units.T T R and can be accessed T R =[5-(T) w -1)0.5]T w Setting, including mechanical start-up time T M =2H h (H h (This refers to the inertia of the hydroelectric generator unit).

[0109] Considering the water hammer effect, governor response time, and transient descent compensation, the relationship between the output power variation of a small hydropower unit and the power system frequency variation in the s-domain can be expressed as:

[0110]

[0111] Among them, T G This is the governor's response time constant.

[0112] Similar to the frequency dynamic analysis of new energy generating units, the frequency dynamics of small hydropower units can be expressed as:

[0113]

[0114] H h The inertia of a small hydropower unit is represented by ΔP. h (t) represents the increase in the output power of the hydroelectric generator at time t. Taking a Laplace transform of equation (8) yields:

[0115]

[0116] Combining equations (7) and (9), we can use Figure 3 The control block diagram shown is the frequency response model of a small hydropower unit, which can represent the second frequency-power response characteristics of a small hydropower unit considering water hammer effect and transient drop compensation.

[0117] Subsequently, based on the first and second frequency-power response characteristics, the frequency-power response characteristics of the first and second preset generating units working together are established. The frequency response model of the first and second preset generating units working together is as follows: Figure 4 As shown, this can be used to represent the frequency-power response characteristics of cooperative operation.

[0118] S20. Based on the frequency-power response characteristics of the cooperative operation, the step response is taken as the frequency response under power deficit to obtain the target frequency response model under power deficit for load surge.

[0119] exist Figure 4 In the middle, ΔP v ΔP hH represents the power changes caused by frequency control of virtual synchronous new energy units and small hydropower units, respectively. Σ The total inertia of the unit is represented by K. v K h The mechanical power gain is used to accurately represent the frequency regulation capability of new energy generating units and hydropower. The specific calculation formulas for the relevant parameters are as follows:

[0120]

[0121] In equation (10), N1 and N2 represent the number of new energy generating units and small hydropower units in the system, respectively, and H vi S Bvi H represents the virtual inertia and rated capacity set by the virtual synchronous controller of the i-th new energy unit. hi S Bhi Let represent the inertia and rated capacity of the i-th small hydropower unit.

[0122]

[0123] In equations (11) and (12), P vi P represents the rated power of the i-th new energy unit. hi This represents the rated power of the i-th small hydropower unit.

[0124] For virtual-controlled new energy generating units, h is used. v (s) represents the virtual synchronous control model; for small hydropower units, h is used. h (s) represents the combined model of the hydroelectric generator and the speed governor. Then...

[0125]

[0126] Depend on Figure 4 The transfer function of the frequency response of a power system containing multiple types of generators can be obtained as follows:

[0127]

[0128] This is a high-order control model, in which This indicates a parallel control loop. The frequency response under power deficit can be viewed as a step response, i.e.

[0129] Therefore, the time-domain expression for the target frequency response model under the load surge step response, i.e., the power deficit, can be expressed as:

[0130]

[0131] In the formula, n1 is the number of real roots; n2 is the number of conjugate complex roots; ζ jω is the damping coefficient of the second-order system corresponding to the conjugate complex root; nj A0 is the angular frequency of the second-order system oscillation reflected by the conjugate complex root; A0 is the residue of Δf(s) at s = 0; ... i For Δf(s) at the real pole s = p i Residue at point B; j and C j At the conjugate complex poles The real and imaginary parts of the residue.

[0132] S30. Based on the target frequency response model, the constraints of the power system are determined. These constraints include power constraints, inertia constraints, frequency change rate constraints, and frequency minimum point constraints, including:

[0133] Based on the target frequency response model, determine the frequency change rate and minimum frequency of the power system;

[0134] The process of obtaining the frequency change rate includes: the inertial response acts immediately after the system disturbance, at which time the unit's control system has not yet acted, and the frequency decrease rate is at its maximum, which is:

[0135]

[0136] The process of obtaining the lowest frequency includes: the lowest frequency reflects the degree of frequency reduction after a power deficit occurs in the system. Figure 4 The high-order control system shown has the following at the lowest frequency point: Right now:

[0137]

[0138] The maximum frequency change can be obtained by solving the above formula and substituting t0 into the time domain expression.

[0139] By combining the target frequency response model, the rate of frequency change, and the minimum frequency, the steady-state error of the power system is obtained.

[0140] When the frequency of a power system approaches steady state, the steady-state error Δf when the power system frequency is stable can be obtained using the final value theorem. ss for:

[0141]

[0142] Obtain the power constraints and inertia constraints of the power system, and combine the steady-state error, power constraints, and inertia constraints to determine the frequency change rate constraints and frequency minimum point constraints of the power system.

[0143] The process of obtaining specific constraints includes:

[0144] When selecting an aggregated equivalent black start, a series of security constraints must first be met, as follows:

[0145] (1) Power constraint

[0146]

[0147] N1 represents the number of nodes participating in the black start group, P i P represents the active power of the black-start power supply. a P represents the power required to start the auxiliary equipment of a thermal power unit. m To ensure a safe power margin during the recovery process.

[0148] (2) Inertia constraint

[0149]

[0150] S i H represents the rated capacity of node i. i Let H be the inertia of the unit at node i. min The minimum level of inertia required for the safe operation of the system.

[0151] (3) Frequency change rate constraint

[0152] The rate of frequency change of the power system must not exceed the upper limit of the rate of frequency change, that is:

[0153]

[0154] |RoCoF M |≤RoCoF max (twenty four)

[0155] RoCoF M RoCoF represents the system's maximum rate of frequency change. max ΔP is the upper limit of the rate of change of frequency. e For the system's power deficit, H Σ This is the equivalent inertia of the units already in parallel operation.

[0156] (4) Minimum frequency point constraint

[0157] Maximum frequency change Δf t The system's transient frequency deviation extreme value constraint needs to be satisfied, i.e.

[0158] max(|Δf t |)≤Δf max (25)

[0159] max(·) is the maximum value operator; Δf max The maximum allowable frequency variation deviation of the system.

[0160] Constraints (3)-(4) can be solved using equations (20)-(22).

[0161] Through the above settings, the power constraints, inertia constraints, frequency change rate constraints, and frequency minimum point constraints of the power system can be accurately obtained, providing a constraint basis for the subsequent confirmation of power aggregation methods.

[0162] S40. Combining the target frequency response model, the target frequency response of each black-start power source to the power system at startup is obtained.

[0163] S50. Based on the shortest path algorithm and each of the power aggregation methods, the optimal recovery path for each black-start power source in the shortest time is determined, so as to perform power system maintenance according to the optimal recovery path.

[0164] System recovery includes:

[0165] For each of the power aggregation methods, based on the target frequency response results and the constraints, determine the multiple target black-start power supplies that need to be restored;

[0166] Based on the shortest path algorithm, the recovery order of each node in each target black start power supply is determined, and the recovery order of each node is taken as the undetermined recovery path.

[0167] Specifically, the step of determining the recovery order of each node in each target black-start power supply based on the shortest path algorithm, and using the recovery order of each node as the undetermined recovery path, includes:

[0168] S1. Select any node as the initial node;

[0169] S2. Use the initial node as the starting node;

[0170] S3. Calculate the time taken to restore the starting node to each of the remaining unrestored nodes, and take the node with the shortest time as the path node.

[0171] S4. Use the path node as the new starting node and return to step S3 until the target node is restored;

[0172] S5. Take the recovery order of each path node as the initial recovery path, select another node that does not overlap with the initial node as the new initial node, and return to step S2 until all nodes have been selected.

[0173] S6. Select the initial recovery path with the shortest time among the initial recovery paths as the pending recovery path.

[0174] The shortest recovery path among all the pending recovery paths is selected as the optimal recovery path, and the power system is restored according to the optimal recovery path.

[0175] The above steps for finding a potential recovery path involve less computation and are faster than existing technologies that typically use network topology-based algorithms to find the shortest path from one point to another.

[0176] The general shortest path algorithm is based on the network topology to find the optimal path from one point to another. When considering the aggregation of multiple units to start up a single thermal power unit, the shortest path algorithm needs to be improved.

[0177] Initially, each distributed power source is a subsystem. Assuming there are m black-start power sources to be aggregated, the process involves m-1 transition stages before the aggregated black-start power sources start the thermal power units in parallel. The objective function is to minimize the time required to start the auxiliary equipment of the thermal power units.

[0178]

[0179] In equation (26), l i The first phase includes the nodes whose routes have been restored in the i-th phase, while the second phase only includes the initial point 1. Find the shortest recovery time from the line that has been restored in stage i to point i+1, and add the recovery path corresponding to this time to l. i And updated to l i+1 When all the black starter power supplies are combined, This represents the shortest time from the black-start power source aggregation path to the thermal power unit. The optimal recovery scheme is found by employing different node sorting schemes.

[0180] If exhaustive sorting is used, there are a total of m! possible solutions, which involves a large amount of computation and has high redundancy.

[0181] In this patent, such as Figure 5 As shown:

[0182] First, after reading the network topology and power structure, the power structure is analyzed to determine the N black-start power sources needed to aggregate power for the generator sets to be started. Each black-start power source is a pre-set generator set, which can be either New Energy Generator Set 1 or New Energy Generator Set 2 as shown in Table 2, or Small Hydropower Generator Set 1 or Small Hydropower Generator Set 2. Among the N nodes of the multiple distributed power sources, the algorithm uses one node as the starting point and calculates the time taken from the starting point to the remaining N-1 nodes. The node with the shortest time is selected as the second point to be traversed. Similarly, the time taken from the second point to the remaining N-2 points is calculated, and the node with the shortest time is determined again. The determination of the remaining points is carried out in the same way. After completing the above node sorting, the algorithm uses the remaining nodes as the first node in sequence, repeating the aforementioned steps to finally obtain the recovery path with the shortest time. The algorithm includes the following steps:

[0183] Step 1: Frequency response model based on small hydropower units and new energy units. Based on the equivalent frequency model of power systems with high renewable energy penetration, taking the IEEE 10-unit 39-bus system as an example, the unit parameters are designed. The parameters of each line and the generator node are shown in Table 1 and Table 2.

[0184] Table 1 Restoration Time of Specific Lines in the Power System

[0185]

[0186]

[0187] Table 2 Power System Unit Parameters

[0188]

[0189] The power system topology diagram in this embodiment is as follows: Figure 6 As shown.

[0190] Step 2: Analyze the response characteristics of the aggregated black-start power supply from a frequency perspective. Nodes 34 and 36 are small hydropower units, and nodes 32 and 35 are new energy storage systems with virtual synchronous control, exhibiting inertial response characteristics. A feasibility analysis of aggregating these units into a black-start power supply is required. We take node 33 as the unit to be started. The auxiliary unit of this unit has a capacity of 6MW, and the auxiliary unit will be activated in four stages, with each stage lasting 1.5MW. Each activation period is 15 minutes. After each activation, the secondary frequency regulation and voltage control of the system will restore the system frequency and voltage to near the rated values ​​before the next operation is performed. Considering capacity constraints, the feasible power aggregation schemes for nodes 32, 34, 35, and 36 are shown in Table 3.

[0191] Table 3. Feasible black-start power supply aggregation schemes based on capacity constraints.

[0192]

[0193] The following analysis examines the target frequency response results of a 1.5MW thermal power auxiliary unit under various aggregation schemes when it is put into operation, such as... Figure 7 and Figure 8 As shown.

[0194] Step 3: Obtain the aggregated black-start power supply scheme with constraints. Considering all types of constraints in the recovery process and combining the aforementioned target frequency response results, the black-start power supply aggregation methods that meet the safety constraints in the recovery process are shown in Table 4.

[0195] Table 4. Black-start power aggregation methods that meet the safety constraints during the recovery process.

[0196]

[0197] Step 4: Analyze the optimality of the aggregated black start power supply from the perspective of minimizing recovery time and economic efficiency.

[0198] Based on the optimal shortest path aggregation algorithm for black-start power supplies, the optimal recovery path and time under various feasible schemes are obtained, as shown in Table 5.

[0199] Table 5. Time required to restore units to startup for each power aggregation method

[0200]

[0201] Based on the safety verification and recovery time of the recovery process, the optimal and feasible aggregated black start scheme is to aggregate and start thermal power unit 2 with "small hydropower unit 2 + wind storage unit 1 + wind storage unit 2", that is, after the aggregation of nodes 34, 35 and 36, node 33 is started.

[0202] This case study analyzes the black-start strategy of a power system using aggregated black-start power sources, focusing on frequency stability analysis based on inertia and the analysis of the optimal path for multi-point power source aggregation. The paper uses IEEE 39 power system simulation for verification. Through scheme verification, it is found that the aggregated black-start power source aggregation scheme with the shortest aggregation time that satisfies frequency constraints can effectively improve recovery efficiency and meet safety constraints.

[0203] This invention also provides a power system restoration system for black-start power supplies, please refer to [link / reference here]. Figure 9 As shown, it includes:

[0204] The collaborative processing module establishes the frequency-power response characteristics of the collaborative operation of the first and second preset generator units.

[0205] The response module, based on the frequency-power response characteristics of the cooperative operation, takes the step response as the frequency response under power deficit to obtain the target frequency response model for load surge under power deficit.

[0206] The constraint module determines the constraints of the power system based on the target frequency response model. The constraints include power constraints, inertia constraints, frequency change rate constraints, and frequency minimum point constraints.

[0207] The prediction module, combined with the target frequency response model, obtains the target frequency response of each black-start power source to the power system at startup.

[0208] The aggregation method determination module determines multiple power aggregation methods for each of the black-start power supplies based on the target frequency response results and the constraints.

[0209] The optimal path determination module determines the optimal recovery path for each black-start power source in the shortest time based on the shortest path algorithm and the power aggregation method, so as to restore the power system according to the optimal recovery path.

[0210] Furthermore, the collaborative processing module includes:

[0211] Establish the first frequency-power response characteristics between the first preset generating unit and the power system, and establish the second frequency-power response characteristics between the second preset generating unit and the power system;

[0212] Based on the first frequency-power response characteristics and the second frequency-power response characteristics, frequency-power response characteristics for the coordinated operation of the first preset unit and the second preset unit are established.

[0213] Furthermore, the collaborative processing module includes:

[0214] Based on the frequency dynamics of the new energy generating units, the first relationship between the output power change of the new energy generating units and the frequency change of the power system is obtained, and the first frequency-power response characteristics between the new energy generating units and the power system are established according to the first relationship.

[0215] Furthermore, the collaborative processing module includes:

[0216] Based on the frequency dynamics of the small hydropower unit, the increase in the output power of the small hydropower unit is obtained;

[0217] By combining the water hammer effect of small hydropower units, the response time of speed governors, and transient descent compensation, a second relationship between the output power variation of small hydropower units and the frequency variation of the power system is obtained.

[0218] By combining the increase in the output power of the small hydropower unit with the second relationship, a second frequency-power response characteristic between the small hydropower unit and the power system is established.

[0219] Furthermore, the constraint module includes:

[0220] Based on the target frequency response model, determine the frequency change rate and minimum frequency of the power system;

[0221] By combining the target frequency response model, the rate of frequency change, and the minimum frequency, the steady-state error of the power system is obtained.

[0222] Obtain the power constraints and inertia constraints of the power system, and combine the steady-state error, power constraints, and inertia constraints to determine the frequency change rate constraints and frequency minimum point constraints of the power system.

[0223] Furthermore, the optimal path determination module includes:

[0224] For each of the power aggregation methods, based on the target frequency response results and the constraints, determine the multiple target black-start power supplies that need to be restored;

[0225] Based on the shortest path algorithm, the recovery order of each node in each target black start power supply is determined, and the recovery order of each node is taken as the undetermined recovery path.

[0226] The recovery path with the shortest recovery time among all the pending recovery paths is selected as the optimal recovery path.

[0227] Furthermore, the optimal path determination module includes:

[0228] S1. Select any node as the initial node;

[0229] S2. Use the initial node as the starting node;

[0230] S3. Calculate the time taken to restore the starting node to each of the remaining unrestored nodes, and take the node with the shortest time as the path node.

[0231] S4. Use the path node as the new starting node and return to step S3 until the target node is restored;

[0232] S5. Take the recovery order of each path node as the initial recovery path, select another node that does not overlap with the initial node as the new initial node, and return to step S2 until all nodes have been selected.

[0233] S6. Select the initial recovery path with the shortest time among the initial recovery paths as the pending recovery path.

[0234] The present invention also provides a computer-readable storage medium storing instructions that, when executed on a terminal device, cause the terminal device to perform a power system restoration method for a black-start power supply as described above.

[0235] The present invention also provides an electronic device, including a memory, a processor, and a program stored in the memory and running on the processor, wherein the processor executes the program to implement a power system restoration method for a black-start power supply as described above.

[0236] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0237] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0238] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for restoring a power system using a black-start power supply, characterized in that, include: Establish the frequency-power response characteristics of the first preset unit and the second preset unit working together. The first preset unit is a new energy unit controlled by a virtual synchronous machine, and the second preset unit is a small hydropower unit. Based on the frequency-power response characteristics of the cooperative operation, the step response is taken as the frequency response under power deficit to obtain the target frequency response model of load surge under power deficit. Based on the target frequency response model, the constraints of the power system are determined, including power constraints, inertia constraints, frequency change rate constraints, and frequency minimum point constraints. By combining the target frequency response model, the target frequency response of each black-start power source to the power system at startup is obtained; Based on the target frequency response results and the constraints, the multiple power aggregation methods of each black-start power supply are determined. Based on the shortest path algorithm and the power aggregation methods described, the optimal recovery path for each black-start power source in the shortest time is determined, so as to restore the power system according to the optimal recovery path.

2. The power system restoration method for a black-start power supply according to claim 1, characterized in that, The establishment of the frequency-power response characteristics for the coordinated operation of the first and second preset generator units includes: Establish the first frequency-power response characteristics between the first preset generating unit and the power system, and establish the second frequency-power response characteristics between the second preset generating unit and the power system; Based on the first frequency-power response characteristics and the second frequency-power response characteristics, frequency-power response characteristics for the coordinated operation of the first preset unit and the second preset unit are established.

3. The power system restoration method for a black-start power supply according to claim 2, characterized in that, The establishment of the first frequency-power response characteristics between the first preset generating unit and the power system includes: Based on the frequency dynamics of the new energy generating units, the first relationship between the output power change of the new energy generating units and the frequency change of the power system is obtained, and the first frequency-power response characteristics between the new energy generating units and the power system are established according to the first relationship.

4. The power system restoration method for a black-start power supply according to claim 2, characterized in that, The second frequency-power response characteristics between the second preset unit and the power system include: Based on the frequency dynamics of the small hydropower unit, the increase in the output power of the small hydropower unit is obtained; By combining the water hammer effect of small hydropower units, the response time of speed governors, and transient descent compensation, a second relationship between the output power variation of small hydropower units and the frequency variation of the power system is obtained. By combining the increase in the output power of the small hydropower unit with the second relationship, a second frequency-power response characteristic between the small hydropower unit and the power system is established.

5. The power system restoration method for a black-start power supply according to claim 1, characterized in that, Based on the target frequency response model, the constraints of the power system are determined. These constraints include power constraints, inertia constraints, frequency change rate constraints, and frequency minimum point constraints. Based on the target frequency response model, determine the frequency change rate and minimum frequency of the power system; By combining the target frequency response model, the rate of frequency change, and the minimum frequency, the steady-state error of the power system is obtained. Obtain the power constraints and inertia constraints of the power system, and combine the steady-state error, power constraints, and inertia constraints to determine the frequency change rate constraints and frequency minimum point constraints of the power system.

6. The power system restoration method for a black-start power supply according to claim 1, characterized in that, Based on the shortest path algorithm and the power aggregation methods described above, the optimal recovery path for each black-start power supply under the shortest time is determined, including: For each of the power aggregation methods, based on the target frequency response results and the constraints, determine the multiple target black-start power supplies that need to be restored; Based on the shortest path algorithm, the recovery order of each node in each target black start power supply is determined, and the recovery order of each node is taken as the undetermined recovery path. The recovery path with the shortest recovery time among all the pending recovery paths is selected as the optimal recovery path.

7. The power system restoration method for a black-start power supply according to claim 6, characterized in that, Based on the shortest path algorithm, the recovery order of each node in each target black-start power supply is determined, and the recovery order of each node is used as the undetermined recovery path, including: S1. Select any node as the initial node; S2. Use the initial node as the starting node; S3. Calculate the time taken to restore the starting node to each of the remaining unrestored nodes, and take the node with the shortest time as the path node. S4. Use the path node as the new starting node and return to step S3 until the target node is restored; S5. Take the recovery order of each path node as the initial recovery path, select another node that does not overlap with the initial node as the new initial node, and return to step S2 until all nodes have been selected. S6. Select the initial recovery path with the shortest time among the initial recovery paths as the pending recovery path.

8. A power system restoration system for a black-start power supply, characterized in that, include: The collaborative processing module establishes the frequency-power response characteristics of the collaborative operation of the first preset unit and the second preset unit. The first preset unit is a new energy unit controlled by a virtual synchronous machine, and the second preset unit is a small hydropower unit. The response module, based on the frequency-power response characteristics of the cooperative operation, takes the step response as the frequency response under power deficit to obtain the target frequency response model for load surge under power deficit. The constraint module determines the constraints of the power system based on the target frequency response model. The constraints include power constraints, inertia constraints, frequency change rate constraints, and frequency minimum point constraints. The prediction module, combined with the target frequency response model, obtains the target frequency response of each black-start power source to the power system at startup. The aggregation method determination module determines multiple power aggregation methods for each of the black-start power supplies based on the target frequency response results and the constraints. The optimal path determination module determines the optimal recovery path for each black-start power source in the shortest time based on the shortest path algorithm and the power aggregation method, so as to restore the power system according to the optimal recovery path.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed on a terminal device, cause the terminal device to perform a power system restoration method for a black-start power supply as described in any one of claims 1 to 7.

10. An electronic device comprising a memory, a processor, and a program stored in the memory and running on the processor, characterized in that, When the processor executes the program, it implements a power system restoration method for a black-start power supply as described in any one of claims 1 to 7.

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