Power system recovery method and system of black-start power supply, medium and electronic equipment

Abstract

The invention provides a power system recovery method and system of a black-start power supply, a medium and electronic equipment. The method comprises the following steps: establishing a frequency-power response characteristic of cooperative work of a first preset unit and a second preset unit; according to frequency-power response characteristics of cooperative work, obtaining a target frequency response model of sudden load increase under power shortage; determining constraint conditions of the power system according to the target frequency response model; in combination with the target frequency response model, obtaining a target frequency response result of each black-start power supply to the power system when the black-start power supply is started; determining a plurality of power supply aggregation modes of each black-start power supply according to each target frequency response result in combination with a constraint condition; and determining an optimal recovery path of each black-start power supply under the shortest time consumption based on a shortest path algorithm and each power supply aggregation mode, so as to recover the power system according to the optimal recovery path. The problem that a black start method in the prior art is low in adaptability is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system control, and in particular to a power system recovery method, system, medium and electronic equipment of a black start power supply. Background Art

[0002] In the context of low-carbon energy transformation, the large-scale grid connection of new energy sources has changed the structure, scale and operation mode of the power system, and increased the risk of blackouts in the new power system. Therefore, improving the black start capability of the power system is a major demand for the security defense of the new power system.

[0003] At present, the black start of the power system mainly relies on external power supply or large hydropower units to drive thermal power units that cannot start automatically. For the central and northern regions where hydropower resources are scarce, the traditional black start method will have problems such as large partitions and lack of backup plans. This defect increases the risk of system recovery for new power systems and the volatility of renewable energy generation, that is, the existing black start method has low adaptability. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a method, system, medium and electronic equipment for restoring an electric power system of a black start power supply, which solves the problem of low adaptability of the black start method in the prior art.

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

[0006] Establishing the frequency-power response characteristics of the coordinated operation of the first preset unit and the second preset unit;

[0007] According to the frequency-power response characteristics of the collaborative work, a step response is used as a frequency response under power shortage to obtain a target frequency response model of a load surge under power shortage;

[0008] Determining constraints of the power system according to the target frequency response model, wherein the constraints include power constraints, inertia constraints, frequency change rate constraints, and frequency minimum point constraints;

[0009] Combined with the target frequency response model, the target frequency response result of the power system when each black start power supply is started is obtained;

[0010] Determine a plurality of power aggregation modes of each black start power source according to each of the target frequency response results and in combination with the constraint conditions;

[0011] Based on the shortest path algorithm and the power aggregation modes, the optimal restoration path of each black start power source in the shortest time is determined, so as to restore the power system according to the optimal restoration path.

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

[0013] Through the above method, the first preset unit and the second preset unit distributed around the power system can be restored to work in coordination. By establishing the frequency-power response characteristics of coordinated work and the target frequency response model of load surge under power shortage, the target frequency response results of multiple black start power sources distributed around the power system to the power system at startup can be determined. According to the constraint conditions and the above target frequency results, the aggregation mode of multiple power sources of the black start power sources can be determined, and the optimal restoration path can be found to restore the power system.

[0014] The present invention can mobilize and combine multiple black start power sources of various types to restore the power system. Compared with the prior art that relies on external power supply or uses a single large hydropower unit to drive a thermal power unit that cannot start by itself, the present invention has higher adaptability when applied to the central and northern regions where hydropower resources are scarce.

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

[0016] respectively establishing a first frequency-power response characteristic between the first preset unit and the power system, and establishing a second frequency-power response characteristic between the second preset unit and the power system;

[0017] Based on the first frequency-power response characteristic and the second frequency-power response characteristic, a frequency-power response characteristic of the first preset unit and the second preset unit working in collaboration is established.

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

[0019] By establishing the first frequency-power response characteristic and the second frequency-power response characteristic between the first preset unit and the second preset unit and the power system, the frequency-power response characteristics of the first preset unit and the second preset unit working in coordination can be obtained to facilitate subsequent frequency response analysis.

[0020] In a method for restoring a power system of a black start power supply provided by one embodiment of the present invention, the first preset unit is a new energy unit controlled by a virtual synchronous machine, and the establishing of 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 unit, a first relationship between the output power change of the new energy unit and the frequency change of the power system is obtained, and a first frequency-power response characteristic between the new energy unit and the power system is established according to the first relationship.

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

[0023] Through the frequency dynamics of the new energy units, the first relationship between their output power changes and power system frequency changes and the first frequency-power response characteristics can be established in turn.

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

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

[0026] Combining the water hammer effect of small hydropower units, the response time of the speed governor and the transient droop compensation, the second relationship between the output power change of small hydropower units and the frequency change of the power system is obtained;

[0027] In combination with the increase in the output power of the small hydropower generator set and the second relationship, a second frequency-power response characteristic between the small hydropower generator set and the power system is established.

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

[0029] By considering the water hammer effect of small hydropower units, the adverse effects of the adjustment process during black start can be reduced or even avoided, and the effect of power system restoration can be improved.

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

[0031] Determining the frequency change rate and the lowest frequency of the power system according to the target frequency response model;

[0032] Combining the target frequency response model, the frequency change rate and the lowest point frequency, a steady-state error of the power system is obtained;

[0033] The power constraint and inertia constraint of the power system are obtained, and the frequency change rate constraint and the frequency minimum point constraint of the power system are determined by combining the steady-state error, the power constraint and the inertia constraint.

[0034] The technical solution disclosed in the present 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 the power aggregation method.

[0036] In a power system restoration method for a black start power supply provided in one embodiment of the present invention, based on the shortest path algorithm and each power aggregation mode, determining the optimal restoration path of each black start power supply in the shortest time, includes:

[0037] For each of the power aggregation modes, determining multiple target black start power sources that need to be restored according to the target frequency response results and the constraint conditions;

[0038] Based on the shortest path algorithm, determining the recovery order of each node in each target black start power supply, and taking the recovery order of each node as a pending recovery path;

[0039] The pending restoration path with the shortest time consumption among the pending restoration paths is taken as the optimal restoration path.

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

[0041] By finding the optimal restoration path with the shortest corresponding 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 supply provided in one embodiment of the present invention, based on a shortest path algorithm, a restoration order of each node in each target black start power supply is determined, and the restoration order of each node is used as a pending restoration path, including:

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

[0044] S2, taking the initial node as the starting node;

[0045] S3, respectively calculating the time taken to restore the starting node to each of the remaining unrestored nodes, and taking the node corresponding to the shortest time as the path node;

[0046] S4, taking the path node as a new starting node, and returning to step S3 until the target node is restored;

[0047] S5, taking the recovery order of each of the path nodes as the initial recovery path, selecting another node that does not overlap with the initial node as the new initial node, and returning to step S2 until all nodes are selected;

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

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

[0050] The above steps are used to find the pending restoration path, which has lower computational complexity and higher speed than the conventional algorithm for finding the shortest path from one point to another based on network topology used in the prior art.

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

[0052] A collaborative processing module, for establishing a frequency-power response characteristic of collaborative operation of the first preset unit and the second preset unit;

[0053] A response module, according to the frequency-power response characteristics of the collaborative work, uses the step response as the frequency response under the power shortage to obtain a target frequency response model of the load surge under the power shortage;

[0054] A constraint module, which determines the constraint conditions of the power system according to the target frequency response model, wherein the constraint conditions include power constraint, inertia constraint, frequency change rate constraint and frequency minimum point constraint;

[0055] The prediction module, combined with the target frequency response model, obtains the target frequency response result of the power system when each black start power supply is started;

[0056] An aggregation mode determining module, which determines a plurality of power aggregation modes of each of the black start power sources according to each of the target frequency response results and in combination with the constraint conditions;

[0057] The optimal path judgment module determines the optimal restoration path of each black start power supply in the shortest time based on the shortest path algorithm and each power aggregation mode, so as to restore the power system according to the optimal restoration path.

[0058] The present invention also provides a computer-readable storage medium, in which instructions are stored. When the instructions are executed on a terminal device, the terminal device executes the above-mentioned method for restoring a power system of a black start power supply.

[0059] The present invention also provides an electronic device, comprising a memory, a processor and a program stored in the memory and running on the processor, wherein the processor implements the above-mentioned method for restoring a power system of a black start power supply when executing the program. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 It is a flow chart of a method for restoring a power system of a black start power supply according to the present invention;

[0061] Figure 2 Frequency response model for virtually synchronized renewable energy units;

[0062] Figure 3 It is the frequency response model of 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 Optimize the recovery path strategy for multi-machine collaborative black start;

[0065] Figure 6 It is the IEEE39 node system topology;

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

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

[0068] Fig. 9 The present invention is a flow chart of a power system restoration system for a black start power supply. DETAILED DESCRIPTION

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

[0070] In the black start process of the new power system, the present invention uses distributed black start power to assist in improving the black start capability. There are a large number of distributed small hydropower in some areas. At the same time, distributed new energy units are widely distributed, and the virtual synchronous control technology can set the virtual inertia and damping of the new energy unit system, making it possible for it to participate in the black start of the power system.

[0071] The study of large-scale new energy units participating in black start-up can realize the self-starting of new energy units and smooth grid connection and maintain system stability through appropriate control methods. This patent is based on the reality that small hydropower units and distributed wind and solar power generation (new energy units) are widely available. It studies the feasibility of black start-up of multiple distributed resources (small hydropower, distributed new energy, etc.), focusing on the impact of different aggregation schemes on the auxiliary machine input process and the impact on system operation, and improves the shortest path algorithm to obtain the optimal path for multi-point aggregation.

[0072] The present invention provides a method for restoring a power system of a black start power supply, which is referred to herein Figure 1As shown, including:

[0073] Establishing the frequency-power response characteristics of the coordinated operation of the first preset unit and the second preset unit;

[0074] According to the frequency-power response characteristics of the collaborative work, a step response is used as a frequency response under power shortage to obtain a target frequency response model of a load surge under power shortage;

[0075] Determining constraints of the power system according to the target frequency response model, wherein the constraints include power constraints, inertia constraints, frequency change rate constraints, and frequency minimum point constraints;

[0076] Combined with the target frequency response model, the target frequency response result of the power system when each black start power supply is started is obtained;

[0077] Determine a plurality of power aggregation modes of each black start power source according to each of the target frequency response results and in combination with the constraint conditions;

[0078] Based on the shortest path algorithm and the power aggregation modes, the optimal restoration path of each black start power source in the shortest time is determined, so as to restore the power system according to the optimal restoration path.

[0079] Through the above method, the first preset unit and the second preset unit distributed around the power system can be restored to work in coordination. By establishing the frequency-power response characteristics of coordinated work and the target frequency response model of load surge under power shortage, the target frequency response results of multiple black start power sources distributed around the power system to the power system at startup can be determined. According to the constraint conditions and the above target frequency results, the aggregation mode of multiple power sources of the black start power sources can be determined, and the optimal restoration path can be found to restore the power system.

[0080] The present invention can mobilize and combine multiple black start power sources of various types to restore the power system. Each power supply unit represents a black start power source. Compared with the prior art that relies on external power supply or uses a single large hydropower unit to drive a thermal power unit that cannot start by itself, the present invention has higher adaptability when applied to the central and northern regions where hydropower resources are scarce.

[0081] Specifically:

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

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

[0084] Wherein, the step of establishing a first frequency-power response characteristic between the first preset unit and the power system includes:

[0085] Based on the frequency dynamics of the new energy units, a first relationship between the output power change of the new energy units and the frequency change of the power system is obtained. According to the first relationship, a first frequency-power response characteristic between the new energy units and the power system is established. Through the frequency dynamics of the new energy units, the first relationship between the output power change of the new energy units and the frequency change of the power system and the first frequency-power response characteristic can be established in turn.

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

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

[0088]

[0089] In the above formula, H v represents the virtual inertia set by the virtual synchronous unit, Δf(t) is the frequency change of the system at time t, D is the load damping constant, ΔP v (t) is the increase in generator output power at time t, ΔP e (t) is the increase in system load at time t. By Laplace transforming equation (1), we can get:

[0090]

[0091] For the new energy units under 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 formula (2):

[0092]

[0093] R v is the droop coefficient, T v is the time constant representing the inverter response speed.

[0094] The relationship between the frequency change of the virtual synchronous new energy unit and the load change 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 the virtually synchronized new energy generator set.

[0098] Wherein, the establishing of the second frequency-power response characteristic between the second preset unit and the power system includes:

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

[0100] Combining the water hammer effect of small hydropower units, the response time of the speed governor and the transient droop compensation, the second relationship between the output power change of small hydropower units and the frequency change of the power system is obtained;

[0101] In combination with the increase in the output power of the small hydropower generator set and the second relationship, a second frequency-power response characteristic between the small hydropower generator set and the power system is established.

[0102] By considering the water hammer effect of small hydropower units, the adverse effects of the adjustment process during black start can be reduced or even avoided, and the effect of power system restoration can be improved.

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

[0104] Small hydropower units have fast startup, shutdown and grid connection speeds and can participate in the black start process of grid restoration after a blackout. However, the water hammer effect of small hydropower units will have an adverse effect on the black start regulation process. The water hammer effect of small hydropower units can be expressed as:

[0105]

[0106] P m is the mechanical power of the hydroelectric motor, G is the guide vane position, T w is the time constant of water hammer effect. Equation (5) shows the relationship between the output power of the hydroelectric generator and the guide vane opening, that is, the initial power impact is opposite to the direction of the guide vane position change. This phenomenon is called water hammer effect. Due to the power characteristics of the hydroelectric generator, it is impossible to meet the requirement of 5% steady-state decline rate of the entire power system. Therefore, in order to ensure the stable operation of the system, it is necessary to introduce a transient decline compensation link in the hydroelectric generator model. The transfer function is as shown in equation (6):

[0107]

[0108] In the above formula (6), R h is the regulation coefficient of small hydropower units.T , T R and can be passed T R =[5-(T w -1)0.5]T w Setting, where the mechanical starting time T M =2H h (H h is the inertia of the hydropower unit).

[0109] Considering the water hammer effect, governor response time, and transient sag compensation, the relationship between the output power change of small hydropower units and the frequency change of the power system in the s domain can be expressed as follows:

[0110]

[0111] Among them, T G is the speed regulator response time constant.

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

[0113]

[0114] H h Indicates the inertia of the small hydropower unit, ΔP h (t) is the increase in the output power of the hydroelectric generator at time t. By performing Laplace transformation on equation (8), we can obtain:

[0115]

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

[0117] Subsequently, based on the first frequency-power response characteristic and the second frequency-power response characteristic, a frequency-power response characteristic of the first preset unit and the second preset unit working in coordination is established. The frequency response model of the first preset unit and the second preset unit working in coordination is as follows: Figure 4 As shown, it can be used to represent the frequency-power response characteristics of collaborative work.

[0118] S20. According to the frequency-power response characteristics of the collaborative work, a step response is used as a frequency response under power shortage to obtain a target frequency response model of a sudden load increase under power shortage.

[0119] exist Figure 4 In the v , ΔP hThey represent the power changes caused by the frequency control of the virtual synchronous new energy units and small hydropower units, respectively. Σ Expressed as the total inertia of the unit, K v , K h The mechanical power gain is expressed to accurately express the frequency regulation capability of new energy units and hydropower. The specific calculation formula of the relevant parameters is as follows:

[0120]

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

[0122]

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

[0124] For the new energy units under virtual control, h v (s) represents the virtual synchronous control model; for small hydropower units, h h (s) represents the aggregation model of the hydroelectric generator and the speed regulator.

[0125]

[0126] Depend on Figure 4 , we can get the transfer function of the frequency response of the power system containing multiple types of generators as:

[0127]

[0128] This is a high-order control model where represents the parallel control link. The frequency response process under power shortage can be regarded as a step response, that is,

[0129] Then, the target frequency under the load sudden increase step response, that is, the target frequency response model under the power shortage, can be expressed in the time domain as follows:

[0130]

[0131] Where n1 is the number of real roots; n2 is the conjugate complex root logarithm; ζ jis the damping coefficient of the second-order system corresponding to the conjugate complex root; ω nj is the oscillation angular frequency of the second-order system reflected by the conjugate complex root; A0 is the residue of Δf(s) at s=0; A i For Δf(s) at the real pole s=p i The residue at B j and C j They are respectively at the conjugate complex poles The real and imaginary parts of the residue.

[0132] S30, determining the constraints of the power system according to the target frequency response model, wherein the constraints include power constraints, inertia constraints, frequency change rate constraints, and frequency minimum point constraints, including:

[0133] Determining the frequency change rate and the lowest frequency of the power system according to the target frequency response model;

[0134] The frequency change rate acquisition process includes: the inertial response takes effect immediately after the system disturbance, at which time the control system of the unit has not yet taken action, and the frequency drop rate is the largest, which is:

[0135]

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

[0137]

[0138] By solving the above formula to obtain t0 and substituting t0 into the time domain expression, the maximum frequency change can be obtained.

[0139] Combining the target frequency response model, the frequency change rate and the lowest point frequency, a steady-state error of the power system is obtained;

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

[0141]

[0142] The power constraint and inertia constraint of the power system are obtained, and the frequency change rate constraint and the frequency minimum point constraint of the power system are determined by combining the steady-state error, the power constraint and the inertia constraint.

[0143] The process of obtaining specific constraints includes:

[0144] When selecting an aggregate equivalent black start, a series of safety constraints must be met. The specific constraints are as follows:

[0145] (1) Power Constraint

[0146]

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

[0148] (2) Inertia constraint

[0149]

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

[0151] (3) Frequency change rate constraint

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

[0153]

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

[0155] RoCoF M is the maximum frequency change rate of the system; RoCoF max is the upper limit of the frequency change rate, ΔP e is the power deficit of the system, H ∑ is the equivalent inertia of the parallel units.

[0156] (4) Frequency minimum point constraint

[0157] Maximum frequency change Δf t It is necessary to satisfy the system transient frequency deviation extreme value constraint, that is,

[0158] max(Δf t |)≤Δf max (25)

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

[0160] Constraints (3)-(4) can be solved by 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 the power aggregation method.

[0162] S40. In combination with the target frequency response model, a target frequency response result of the power system when each black start power supply is started is obtained.

[0163] S50, determining the optimal restoration path of each black start power source in the shortest time based on the shortest path algorithm and each power source aggregation mode, so as to restore the power system according to the optimal restoration path includes:

[0164] For each of the power aggregation modes, determining multiple target black start power sources that need to be restored according to the target frequency response results and the constraint conditions;

[0165] Based on the shortest path algorithm, determining the recovery order of each node in each target black start power supply, and taking the recovery order of each node as a pending recovery path;

[0166] The method of determining the recovery order of each node in each target black start power supply based on the shortest path algorithm and taking the recovery order of each node as a pending recovery path specifically includes:

[0167] S1. Set any node as the initial node;

[0168] S2, taking the initial node as the starting node;

[0169] S3, respectively calculating the time taken to restore the starting node to each of the remaining unrestored nodes, and taking the node corresponding to the shortest time as the path node;

[0170] S4, taking the path node as a new starting node, and returning to step S3 until the target node is restored;

[0171] S5, taking the recovery order of each of the path nodes as the initial recovery path, selecting another node that does not overlap with the initial node as the new initial node, and returning to step S2 until all nodes are selected;

[0172] S6. Using the initial recovery path with the shortest time consumption among the initial recovery paths as the pending recovery path.

[0173] The pending restoration path with the shortest time consumption among the pending restoration paths is used as the optimal restoration path, so as to restore the power system according to the optimal restoration path.

[0174] The above steps are used to find the pending restoration path, which has lower computational complexity and higher speed than the conventional algorithm for finding the shortest path from one point to another based on network topology used in the prior art.

[0175] The general shortest path algorithm is to find the optimal path from one point to another based on the network topology. When considering the aggregation and start-up of multiple units into a single thermal power unit, the shortest path algorithm needs to be improved.

[0176] Initially, each distributed power source is a subsystem. Assuming that there are m black start power sources to be aggregated, it will go through m-1 transition stages, and the aggregated black start power sources will restart the thermal power units in parallel. The objective function is to minimize the time required to start the auxiliary equipment of the thermal power unit:

[0177]

[0178] In formula (26), l i The nodes included in the restored line in the i-th stage. The first stage only includes the initial point 1. The shortest restoration time from the restored line in stage i to the i+1th point, and the restoration path corresponding to this time is added to l i And update to l i+1 When all black start power sources are aggregated, It represents the shortest time from the black start power aggregation path to the thermal power unit. By adopting different node sorting schemes, the optimal recovery scheme can be found.

[0179] If exhaustive sorting is used, there are a total of m! solutions, which are computationally intensive and highly redundant.

[0180] In this patent, Figure 5 As shown:

[0181] First, after reading the network topology and power structure, analyze the power structure and determine the N black start power aggregated power units to be started, where each black start power source is a preset unit, which can be a new energy unit 1 or a new energy unit 2 as shown in Table 2, or a small hydropower unit 1 or a small hydropower unit 2. Among the N nodes of multiple distributed power sources, the algorithm will take one of the nodes as the starting point, and then calculate the time from the starting point to the remaining N-1 nodes respectively, compare the node with the shortest time, and determine it as the second point passed; according to the same method, calculate the time from the second point to the remaining N-2 points respectively, and determine the node with the shortest time again; the determination of the remaining points is similar. After completing the above-mentioned node sorting, the algorithm uses the remaining nodes as the first node in turn, repeats the above steps, and finally obtains the recovery path with the shortest time. It includes the following steps:

[0182] Step 1: Based on the frequency response model of small hydropower units and new energy units, according to the equivalent frequency model of the power system with high renewable energy penetration, taking the IEEE10 machine 39 node 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;

[0183] Table 1 Restoration time of specific lines in the power system

[0184]

[0185]

[0186] Table 2 Power system unit parameters

[0187]

[0188] The power system topology diagram of this embodiment is as follows Figure 6 shown.

[0189] Step 2: Analyze the response characteristics of the aggregated black start power supply from the frequency perspective. Nodes 34 and 36 are small hydropower units, and nodes 32 and 35 are new energy storage systems with virtual synchronous control, which have inertia response characteristics. It is necessary to conduct a feasibility analysis of unit aggregation as a black start power supply. We take node 33 as the unit to be started. The auxiliary machine of this unit is 6MW. The auxiliary machine is put into operation four times, each time with 1.5MW. Each time the input period is 15 minutes. Each time the secondary frequency regulation and voltage control of the system are put into operation, the system frequency and voltage are restored to near the rated value before the next operation is carried out. Considering the capacity constraints, the feasible power aggregation schemes for nodes 32, 34, 35, and 36 are shown in Table 3.

[0190] Table 3 Feasible black start power aggregation scheme based on capacity constraints

[0191]

[0192] The following is an analysis of the target frequency response results when the 1.5MW thermal power auxiliary equipment is put into use under various aggregation schemes, such as Figure 7 and Figure 8 shown.

[0193] Step 3: Obtain an aggregated black start power supply solution with constraints. Taking into account various types of constraints in the recovery process and combining the above target frequency response results, the black start power supply aggregation method that meets the safety constraints in the recovery process is shown in Table 4.

[0194] Table 4 Black start power aggregation method that meets the safety constraints during the recovery process

[0195]

[0196] Step 4: Analyze the optimality of the aggregated black start power supply from the economic perspective of shortest recovery time.

[0197] Based on the optimal black start power aggregation shortest path algorithm, the optimal recovery path and time under various feasible solutions are obtained, as shown in Table 5.

[0198] Table 5 Time taken by each power aggregation method to restore the units to be started

[0199]

[0200] Combined with the safety verification and recovery time of the recovery process, the optimal and feasible aggregated black start solution is "small hydropower unit 2 + wind storage unit 1 + wind storage unit 2" to aggregate and start thermal power unit 2, that is, nodes 34, 35, and 36 are aggregated to start node 33.

[0201] This example analyzes the black start strategy of the power system with aggregated black start power sources, focusing on the frequency stability analysis based on inertia and the analysis of the optimal path for multi-point power aggregation. This paper relies on the IEEE39 power system for simulation verification. Through the scheme verification, it is found that the aggregated black start power aggregation scheme with the shortest aggregation time that meets the frequency constraints can effectively improve the recovery efficiency and meet the safety constraints.

[0202] The present invention also provides a black start power supply power system recovery system, please refer to Fig. 9 As shown, including:

[0203] A collaborative processing module, for establishing a frequency-power response characteristic of collaborative operation of the first preset unit and the second preset unit;

[0204] A response module, according to the frequency-power response characteristics of the collaborative work, uses the step response as the frequency response under the power shortage to obtain a target frequency response model of the load surge under the power shortage;

[0205] A constraint module, which determines the constraint conditions of the power system according to the target frequency response model, wherein the constraint conditions include power constraint, inertia constraint, frequency change rate constraint and frequency minimum point constraint;

[0206] The prediction module, combined with the target frequency response model, obtains the target frequency response result of the power system when each black start power supply is started;

[0207] An aggregation mode determining module, which determines a plurality of power aggregation modes of each of the black start power sources according to each of the target frequency response results and in combination with the constraint conditions;

[0208] The optimal path judgment module determines the optimal restoration path of each black start power supply in the shortest time based on the shortest path algorithm and each power aggregation mode, so as to restore the power system according to the optimal restoration path.

[0209] Furthermore, the collaborative processing module includes:

[0210] respectively establishing a first frequency-power response characteristic between the first preset unit and the power system, and establishing a second frequency-power response characteristic between the second preset unit and the power system;

[0211] Based on the first frequency-power response characteristic and the second frequency-power response characteristic, a frequency-power response characteristic of the first preset unit and the second preset unit working in collaboration is established.

[0212] Furthermore, the collaborative processing module includes:

[0213] Based on the frequency dynamics of the new energy unit, a first relationship between the output power change of the new energy unit and the frequency change of the power system is obtained, and a first frequency-power response characteristic between the new energy unit and the power system is established according to the first relationship.

[0214] Furthermore, the collaborative processing module includes:

[0215] Based on the frequency dynamics of small hydropower units, the increase in output power of small hydropower units is obtained;

[0216] Combining the water hammer effect of small hydropower units, the response time of the speed governor and the transient droop compensation, the second relationship between the output power change of small hydropower units and the frequency change of the power system is obtained;

[0217] In combination with the increase in the output power of the small hydropower generator set and the second relationship, a second frequency-power response characteristic between the small hydropower generator set and the power system is established.

[0218] Furthermore, the constraint module includes:

[0219] Determining the frequency change rate and the lowest frequency of the power system according to the target frequency response model;

[0220] Combining the target frequency response model, the frequency change rate and the lowest point frequency, a steady-state error of the power system is obtained;

[0221] The power constraint and inertia constraint of the power system are obtained, and the frequency change rate constraint and the frequency minimum point constraint of the power system are determined by combining the steady-state error, the power constraint and the inertia constraint.

[0222] Furthermore, the optimal path determination module includes:

[0223] For each of the power aggregation modes, determining multiple target black start power sources that need to be restored according to the target frequency response results and the constraint conditions;

[0224] Based on the shortest path algorithm, determining the recovery order of each node in each target black start power supply, and taking the recovery order of each node as a pending recovery path;

[0225] The pending restoration path with the shortest time consumption among the pending restoration paths is taken as the optimal restoration path.

[0226] Furthermore, the optimal path determination module includes:

[0227] S1. Set any node as the initial node;

[0228] S2, taking the initial node as the starting node;

[0229] S3, respectively calculating the time taken to restore the starting node to each of the remaining unrestored nodes, and taking the node corresponding to the shortest time as the path node;

[0230] S4, taking the path node as a new starting node, and returning to step S3 until the target node is restored;

[0231] S5, taking the recovery order of each of the path nodes as the initial recovery path, selecting another node that does not overlap with the initial node as the new initial node, and returning to step S2 until all nodes are selected;

[0232] S6. Using the initial recovery path with the shortest time consumption among the initial recovery paths as the pending recovery path.

[0233] The present invention also provides a computer-readable storage medium, in which instructions are stored. When the instructions are executed on a terminal device, the terminal device executes the above-mentioned method for restoring a power system of a black start power supply.

[0234] The present invention also provides an electronic device, comprising a memory, a processor and a program stored in the memory and running on the processor, wherein the processor implements the above-mentioned method for restoring a power system of a black start power supply when executing the program.

[0235] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0236] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0237] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary 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: Establishing the frequency-power response characteristics of the coordinated operation of the first preset unit and the second preset unit; According to the frequency-power response characteristics of the collaborative work, a step response is used as a frequency response under power shortage to obtain a target frequency response model of a load surge under power shortage; Determining constraints of the power system according to the target frequency response model, wherein the constraints include power constraints, inertia constraints, frequency change rate constraints, and frequency minimum point constraints; Combined with the target frequency response model, the target frequency response result of the power system when each black start power supply is started is obtained; Determine a plurality of power aggregation modes of each black start power source according to each of the target frequency response results and in combination with the constraint conditions; Based on the shortest path algorithm and the power aggregation modes, the optimal restoration path of each black start power source in the shortest time is determined, so as to restore the power system according to the optimal restoration path.

2. The method for restoring a power system of a black start power supply according to claim 1, characterized in that: The establishing of the frequency-power response characteristics of the coordinated operation of the first preset unit and the second preset unit comprises: respectively establishing a first frequency-power response characteristic between the first preset unit and the power system, and establishing a second frequency-power response characteristic between the second preset unit and the power system; Based on the first frequency-power response characteristic and the second frequency-power response characteristic, a frequency-power response characteristic of the first preset unit and the second preset unit working in collaboration is established.

3. The method for restoring a power system of a black start power supply according to claim 2, characterized in that: The first preset unit is a new energy unit controlled by a virtual synchronous machine, and the establishing of a first frequency-power response characteristic between the first preset unit and the power system includes: Based on the frequency dynamics of the new energy unit, a first relationship between the output power change of the new energy unit and the frequency change of the power system is obtained, and a first frequency-power response characteristic between the new energy unit and the power system is established according to the first relationship.

4. The method for restoring a power system of a black start power supply according to claim 2, characterized in that: The second preset unit is a small hydropower unit, and the second frequency-power response characteristic between the second preset unit and the power system includes: Based on the frequency dynamics of small hydropower units, the increase in output power of small hydropower units is obtained; Combining the water hammer effect of small hydropower units, the response time of the speed governor and the transient droop compensation, the second relationship between the output power change of small hydropower units and the frequency change of the power system is obtained; In combination with the increase in the output power of the small hydropower generator set and the second relationship, a second frequency-power response characteristic between the small hydropower generator set and the power system is established.

5. The method for restoring a power system of a black start power supply according to claim 1, characterized in that: According to the target frequency response model, the constraints of the power system are determined, wherein the constraints include power constraints, inertia constraints, frequency change rate constraints and frequency minimum point constraints, including: Determining the frequency change rate and the lowest frequency of the power system according to the target frequency response model; Combining the target frequency response model, the frequency change rate and the lowest point frequency, a steady-state error of the power system is obtained; The power constraint and inertia constraint of the power system are obtained, and the frequency change rate constraint and the frequency minimum point constraint of the power system are determined by combining the steady-state error, the power constraint and the inertia constraint.

6. The method for restoring a power system of a black start power supply according to claim 1, characterized in that: Based on the shortest path algorithm and the power aggregation modes, the optimal recovery path of each black start power source in the shortest time is determined, including: For each of the power aggregation modes, determining multiple target black start power sources that need to be restored according to the target frequency response results and the constraint conditions; Based on the shortest path algorithm, determining the recovery order of each node in each of the target black start power supplies, and taking the recovery order of each of the nodes as a pending recovery path; The pending restoration path with the shortest time consumption among the pending restoration paths is taken as the optimal restoration path.

7. The method for restoring a power system of a black start power supply according to claim 6, characterized in that: Determining the recovery order of each node in each target black start power supply based on the shortest path algorithm, and taking the recovery order of each node as a pending recovery path, including: S1. Set any node as the initial node; S2, taking the initial node as the starting node; S3, respectively calculating the time taken to restore the starting node to each of the remaining unrestored nodes, and taking the node corresponding to the shortest time as the path node; S4, taking the path node as a new starting node, and returning to step S3 until the target node is restored; S5, taking the recovery order of each of the path nodes as the initial recovery path, selecting another node that does not overlap with the initial node as the new initial node, and returning to step S2 until all nodes are selected; S6. Using the initial recovery path with the shortest time consumption among the initial recovery paths as the pending recovery path.

8. A black start power supply power system restoration system, characterized in that: include: A collaborative processing module, for establishing a frequency-power response characteristic of collaborative operation of the first preset unit and the second preset unit; A response module, according to the frequency-power response characteristics of the collaborative work, uses the step response as the frequency response under the power shortage to obtain a target frequency response model of the load surge under the power shortage; A constraint module, which determines the constraint conditions of the power system according to the target frequency response model, wherein the constraint conditions include power constraint, inertia constraint, frequency change rate constraint and frequency minimum point constraint; The prediction module, combined with the target frequency response model, obtains the target frequency response result of the power system when each black start power supply is started; An aggregation mode determination module determines a plurality of power aggregation modes of each of the black start power sources according to each of the target frequency response results and in combination with the constraint conditions; The optimal path judgment module determines the optimal restoration path of each black start power supply in the shortest time based on the shortest path algorithm and each power aggregation mode, so as to restore the power system according to the optimal restoration path.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed on a terminal device, the terminal device executes 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, the power system recovery method of the black start power supply according to any one of claims 1 to 7 is implemented.

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