Rapid power recovery method, system and equipment for multi-type clean energy power distribution network and storage medium

Abstract

The invention discloses a multi-type clean energy power distribution network rapid power recovery method, system and device and a storage medium, and aims to solve the problems that dynamic network reconstruction of an existing power distribution network power recovery system depends on physical topology switching, dynamic reconstruction depends on physical switch action, the response speed is limited, fault recovery and oscillation suppression strategies are separated, and the power recovery efficiency is low. The rapidity and the stability are difficult to consider at the same time. The method includes: determining a power restoration area according to fault data of the power distribution network; generating a logic power supply path diagram according to the virtual nodes of the power distribution network and the power grid topological graph; obtaining the weight of each power supply path in the logic power supply path diagram, and determining an optimal power supply path based on the weight and the power recovery area; obtaining the response speed of each clean energy, and dividing the clean energy into a fast response cluster and a slow response cluster according to the response speed; calculating the real-time inertia of the fast response cluster and the real-time damping coefficient of the slow response cluster; and according to the optimal power supply path, the real-time inertia and the real-time damping coefficient, clean energy is supplied to the power recovery area.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power distribution network, and particularly relates to a multi-type clean energy power distribution network fast power restoration method, system, device and storage medium. BACKGROUND

[0002] With the multi-type clean energy such as wind power, photovoltaic, energy storage and hydrogen energy connected to the power distribution network, the power system presents strong heterogeneity and low inertia characteristics, which is easy to cause power oscillation and difficult to adjust quickly. The existing power distribution network power restoration system depends on physical topology switching for dynamic network reconstruction, and depends on physical switch action for dynamic reconstruction, which is limited in response speed, and the fault recovery and oscillation suppression strategies are separated, which is difficult to balance the speed and stability. SUMMARY

[0003] The present application provides a multi-type clean energy power distribution network fast power restoration method, system, device and storage medium, which is used to solve the technical problem that the existing power distribution network power restoration system depends on physical topology switching for dynamic network reconstruction, and depends on physical switch action for dynamic reconstruction, which is limited in response speed, and the fault recovery and oscillation suppression strategies are separated, which is difficult to balance the speed and stability.

[0004] The present application provides a multi-type clean energy power distribution network fast power restoration method, comprising:

[0005] Obtain fault data of the power distribution network, and determine a power restoration area according to the fault data;

[0006] Obtain a power grid topology graph of the power distribution network and virtual nodes corresponding to power equipment in the power distribution network, and generate a logical power supply path graph according to the virtual nodes and the power grid topology graph;

[0007] Obtain the weight of each power supply path in the logical power supply path graph, and determine an optimal power supply path based on the weight and the power restoration area;

[0008] Obtain the response speed of each clean energy, and divide the clean energy into a fast response cluster and a slow response cluster according to the response speed;

[0009] Calculate the real-time inertia of the fast response cluster and the real-time damping coefficient of the slow response cluster;

[0010] According to the optimal power supply path, the real-time inertia and the real-time damping coefficient, supply the clean energy to the power restoration area.

[0011] Optionally, the step of obtaining the weight of each power supply path in the logical power supply path graph, and determining an optimal power supply path based on the weight and the power restoration area, comprises:

[0012] acquiring voltage amplitude and phase angle of each line in the logical power supply path graph;

[0013] constructing a virtual adjacency matrix according to the voltage amplitude and the phase angle;

[0014] determining connection relationship of each line based on the virtual adjacency matrix;

[0015] generating available paths according to the connection relationship;

[0016] calculating oscillation risk index, oscillation energy index and estimated loss of each available path in the logical power supply path graph;

[0017] determining risk paths according to the oscillation energy index;

[0018] determining power supply paths according to the available paths and the risk paths;

[0019] calculating weight of the power supply paths based on the oscillation risk index and the estimated loss;

[0020] searching optimal power supply paths of the complex power supply area according to the weight.

[0021] Optionally, the step of calculating oscillation risk index, oscillation energy index and estimated loss of each available path in the logical power supply path graph comprises:

[0022] acquiring oscillation frequency, oscillation amplitude and damping ratio of the available path;

[0023] calculating oscillation risk index of the available path according to the oscillation frequency, the oscillation amplitude and the damping ratio;

[0024] calculating oscillation energy index according to the oscillation frequency and the oscillation amplitude;

[0025] acquiring historical experience data, and calculating estimated loss of the available path according to the historical experience data.

[0026] Optionally, the step of calculating real-time inertia of the fast-response cluster and real-time damping coefficient of the slow-response cluster comprises:

[0027] acquiring frequency change rate and basic inertia of the fast-response cluster;

[0028] adjusting real-time inertia of the fast-response cluster according to the frequency change rate and the basic inertia;

[0029] acquiring frequency deviation of the slow-response cluster, and adjusting real-time damping coefficient of the slow-response cluster according to the frequency deviation.

[0030] Optionally, the step of adjusting the real-time inertia of the fast-response cluster according to the frequency change rate and the base inertia comprises:

[0031] An inertia adjustment coefficient, an available energy capacity, a charge-discharge efficiency, a reference capacity, a sensitivity factor and a rated frequency of the fast-response cluster are obtained;

[0032] The base inertia is calculated using the inertia adjustment coefficient, the available energy capacity, the charge-discharge efficiency and the reference capacity;

[0033] The real-time inertia of the fast-response cluster is calculated using the base inertia, the frequency change rate, the sensitivity factor and the rated frequency.

[0034] Optionally, the step of obtaining the frequency deviation of the slow-response cluster and adjusting the real-time damping coefficient of the slow-response cluster according to the frequency deviation comprises:

[0035] The maximum power disturbance, the allowed frequency deviation, the frequency deviation of the slow-response cluster, and the current available power and the rated maximum power of each clean energy in the slow-response cluster are obtained;

[0036] The real-time damping coefficient of the slow-response cluster is calculated using the maximum power disturbance, the allowed frequency deviation, the frequency deviation, the current available power and the rated maximum power.

[0037] Optionally, the method further comprises:

[0038] The damping current component and the reverse harmonic current of the clean energy are calculated;

[0039] The damping current component and the reverse harmonic current are injected into a preset inverter to suppress synchronous oscillation and transient disturbance of the power restoration area.

[0040] The application also provides a multi-type clean energy power distribution network fast power restoration system, comprising:

[0041] A fault unit is configured to obtain fault data of a power distribution network and determine a power restoration area according to the fault data;

[0042] A reconstruction unit is configured to obtain a power grid topology of the power distribution network and virtual nodes corresponding to power equipment in the power distribution network, and generate a logical power supply path diagram according to the virtual nodes and the power grid topology; obtain a weight of each power supply path in the logical power supply path diagram, and determine an optimal power supply path based on the weight and the power restoration area;

[0043] a synchronization unit configured to obtain response speeds of the clean energy sources, and divide the clean energy sources into a fast-response cluster and a slow-response cluster according to the response speeds; calculate real-time inertia of the fast-response cluster and real-time damping coefficients of the slow-response cluster;

[0044] a power restoration unit configured to supply the clean energy sources to the power restoration area according to the optimal power supply path, the real-time inertia and the real-time damping coefficients.

[0045] The application further provides an electronic device, which comprises a processor and a memory:

[0046] The memory is configured to store program codes and transmit the program codes to the processor.

[0047] The processor is configured to execute the method according to the instructions in the program codes.

[0048] The application further provides a computer readable storage medium configured to store program codes, which are used to execute the method.

[0049] As can be seen from the above technical solutions, the application has the following advantages: the application provides a method for fast power restoration of a multi-type clean energy power distribution network, and specifically discloses the following: obtaining fault data of the power distribution network, and determining a power restoration area according to the fault data; obtaining a power grid topology graph of the power distribution network and virtual nodes corresponding to power equipment in the power distribution network, and generating a logical power supply path graph according to the virtual nodes and the power grid topology graph; obtaining weights of each power supply path in the logical power supply path graph, and determining an optimal power supply path based on the weights and the power restoration area; obtaining response speeds of the clean energy sources, and dividing the clean energy sources into a fast-response cluster and a slow-response cluster according to the response speeds; calculating real-time inertia of the fast-response cluster and real-time damping coefficients of the slow-response cluster; and supplying the clean energy sources to the power restoration area according to the optimal power supply path, the real-time inertia and the real-time damping coefficients.

[0050] The application constructs a logical power supply path by abstracting power equipment as a virtual node, decouples a software-defined energy flow control layer from a physical layer, realizes dynamic virtual topology reconstruction, breaks through the speed limit of physical switch action, and gets rid of the limitation of physical switches; the application uses the fast response characteristics of distributed clean energy to dynamically aggregate the clean energy into a virtual synchronous unit with adjustable inertia and damping, simulates the dynamic characteristics of a traditional synchronous generator to suppress power oscillation of a multi-source heterogeneous power distribution network, and provides inertia support to realize real-time adaptive allocation of inertia and damping and adapt to a multi-source power fluctuation scenario; and the application divides clean energy into fast / slow response equipment according to response speed for hierarchical control, such as providing instantaneous inertia by energy storage and providing continuous damping by hydrogen energy to play the advantages of dynamic characteristics. BRIEF DESCRIPTION OF DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, hereinafter, a brief introduction will be made to the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0052] Figure 1 A step flowchart of a multi-type clean energy power distribution network fast restoration method provided by the embodiment of the present application.

[0053] Figure 2 A structural block diagram of a multi-type clean energy power distribution network fast restoration system provided by the embodiment of the present application. DETAILED DESCRIPTION

[0054] The embodiment of the present application provides a multi-type clean energy power distribution network fast restoration method, system, device and storage medium, which is used to solve the technical problem that the existing power distribution network restoration system depends on physical topology switching for dynamic network reconstruction, depends on physical switch action for dynamic reconstruction, is limited in response speed, and the fault recovery and oscillation suppression strategies are separated, and it is difficult to balance the speed and stability.

[0055] In order to make the application purpose, features and advantages of the present application more obvious and easy to understand, the technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. Obviously, the following described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0056] Please refer to Figure 1 , Figure 1 A step flowchart of a multi-type clean energy power distribution network fast restoration method provided by the embodiment of the present application.

[0057] The application provides a multi-type clean energy power distribution network fast power restoration method, which can specifically include the following steps.

[0058] Step 101, obtaining fault data of a power distribution network, and determining a power restoration area according to the fault data;

[0059] Step 102, obtaining a power grid topology graph of the power distribution network and virtual nodes corresponding to power equipment in the power distribution network, and generating a logical power supply path graph according to the virtual nodes and the power grid topology graph;

[0060] In the embodiment of the application, a software-defined network (SDN) and a software-defined energy flow controller (SDEC) can be used, a virtual node can be obtained based on an SDN protocol stack development, and a logical power supply path graph can be generated based on the virtual node and a power grid topology graph.

[0061] Step 103, obtaining a weight of each power supply path in the logical power supply path graph, and determining an optimal power supply path based on the weight and the power restoration area;

[0062] In the embodiment of the application, the weight of each power supply path in the logical power supply path graph can be obtained, and the optimal power supply path can be determined based on the weight and the power restoration area.

[0063] In a specific implementation, the optimal power supply path of the power restoration area can be determined by taking the minimum weight of all clean energy as the optimization target.

[0064] Step 104, obtaining a response speed of each clean energy, and dividing the clean energy into a fast response cluster and a slow response cluster according to the response speed;

[0065] In the embodiment of the application, the clean energy can be wind power, photovoltaic power, energy storage and hydrogen energy, and the response speed can be a dynamic response time constant. According to the difference in the dynamic response time constant, the clean energy can be divided into a fast response cluster and a slow response cluster. For example, a millisecond-level response energy storage system (such as a lithium ion battery and a super capacitor), a hydrogen energy system, a photovoltaic inverter and the like.

[0066] Step 105, calculating a real-time inertia of the fast response cluster and a real-time damping coefficient of the slow response cluster;

[0067] Step 106, supplying the clean energy to the power restoration area according to the optimal power supply path, the real-time inertia and the real-time damping coefficient.

[0068] After the fast response cluster and the slow response cluster are divided, the real-time inertia of the fast response cluster and the real-time damping coefficient of the slow response cluster can be calculated, and then clean energy is supplied to the power restoration area according to the optimal power supply path, the real-time inertia and the real-time damping coefficient.

[0069] The application abstracts power equipment as a virtual node, constructs a logical power supply path, decouples the software-defined energy flow control layer from the physical layer, realizes dynamic virtual topology reconstruction, breaks through the speed limit of physical switch action, and gets rid of the limitation of physical switches; the fast response characteristics of distributed clean energy are used to dynamically aggregate the virtual synchronous generator with adjustable inertia and damping, simulate the dynamic characteristics of the traditional synchronous generator, suppress the power oscillation of the multi-source heterogeneous distribution network, provide inertia support, realize real-time adaptive distribution of inertia and damping, and adapt to the multi-source power fluctuation scene; the clean energy is divided into fast / slow response equipment according to the response speed for hierarchical control, such as energy storage providing instantaneous inertia and hydrogen energy providing continuous damping, so as to play the advantages of each dynamic characteristic.

[0070] Please refer to Figure 2 , Figure 2 A step flowchart of a multi-type clean energy distribution network fast power restoration method provided by another embodiment of the application is shown in FIG. 2. The method can include the following steps:

[0071] In step 201, fault data of a distribution network is obtained, and a power restoration area is determined according to the fault data;

[0072] In step 202, a power grid topology graph of the distribution network and virtual nodes corresponding to power equipment in the distribution network are obtained, and a logical power supply path graph is generated according to the virtual nodes and the power grid topology graph;

[0073] Steps 201-202 are the same as steps 101-102, and the description of steps 101-102 can be referred to.

[0074] In step 203, the weight of each power supply path in the logical power supply path graph is obtained, and the optimal power supply path is determined based on the weight and the power restoration area.

[0075] In the embodiment of the application, the weight of each power supply path in the logical power supply path graph can be obtained, and the optimal power supply path can be determined based on the weight and the power restoration area.

[0076] In a specific implementation, the optimal power supply path of the power restoration area can be determined by taking the minimum weight of all clean energy as the optimization target.

[0077] In one example, step 203 can include the following sub-steps:

[0078] In S31, the voltage amplitude and phase angle of each line in the logical power supply path graph are obtained.

[0079] S32, constructing a virtual adjacency matrix according to the voltage amplitude and the phase angle;

[0080] S33, determining a connection relationship of each line based on the virtual adjacency matrix;

[0081] S34, generating an available path according to the connection relationship;

[0082] In a specific implementation, the voltage amplitude and the phase angle of each line in a logical power supply path diagram can be acquired, a virtual adjacency matrix is constructed based on the voltage amplitude and the phase angle, a connection relationship of the line is acquired based on the virtual adjacency matrix, and an available path is obtained based on the connection relationship.

[0083] In one example, a calculation formula for constructing the virtual adjacency matrix is as follows (wherein 1 represents connectivity, and 0 represents disconnection):

[0084]

[0085]

[0086] wherein, the virtual adjacency matrix is represented by A, and the phase angle of the first line and the second line is represented by , the phase angle of the first line and the second line is represented by the impedance of the xth line to the yth line is represented by Zxy, the current amplitude of the xth line to the yth line is represented by Ixy, a phase difference threshold is represented by the voltage amplitude of the xth line and the yth line is represented by the voltage amplitude of the xth line and the yth line is represented by and the impedance deviation allowance value is represented by , the impedance deviation allowance value is represented by the impedance deviation allowance value is represented by

[0087] In one example, a plurality of reconstruction states (such as normal, island, overload, oscillation, and fault) can be defined by using the virtual adjacency matrix, and a preset virtual topology template is triggered. For example, if the connection relationship is all 1, there is no fault; if voltage sag is detected, it is in an island state; if the line current exceeds the threshold, it is in an overload state; if the absolute value of frequency fluctuation is greater than a preset threshold and the duration exceeds a certain range, it is in an oscillation state; if short-circuit current is detected, the current suddenly rises, it is in a fault state, the local circuit breaker is tripped, the fault area is isolated, the virtual adjacency matrix is generated, and the available path is identified.

[0088] S35, calculate the oscillation risk index, oscillation energy index and estimated loss for each available path in the logic power supply path diagram;

[0089] In this embodiment of the invention, the oscillation frequency, oscillation amplitude, and damping ratio of the power supply path can be obtained. Based on the oscillation frequency, the oscillation amplitude, and the damping ratio, the oscillation risk index, the oscillation energy index, and the estimated loss of the power supply path can be obtained.

[0090] In one example, step S35 may include the following sub-steps:

[0091] S351, the step of calculating the oscillation risk index, oscillation energy index, and estimated loss of each available path in the logic power supply path diagram includes:

[0092] S352, obtain the oscillation frequency, oscillation amplitude, and damping ratio of the available path;

[0093] S353, Calculate the oscillation risk index of the available path based on the oscillation frequency, the oscillation amplitude, and the damping ratio;

[0094] S354, Calculate the oscillation energy index based on the oscillation frequency and the oscillation amplitude;

[0095] S355, Obtain historical experience data, and calculate the estimated loss of the available path based on the historical experience data.

[0096] In practical implementation, the estimated loss can be obtained based on historical experience data, such as existing data and expert experience, while the oscillation risk index can be calculated by extracting the dominant oscillation mode using the Prony algorithm. The damping ratio is calculated using the following formula:

[0097] ;

[0098] The formula for calculating the oscillation risk index is as follows:

[0099] ;

[0100] in, Indicates the first Damping ratio of each power supply path Indicates the attenuation coefficient. Represents angular frequency. Indicates the risk index of volatility. Indicates the first The oscillation amplitude of each power supply path, Indicates the reference amplitude. Indicates the reference frequency. Indicates the first The oscillation frequency of the power supply path, represents the number of power supply paths.

[0101] The calculation formula of the oscillation energy index is:

[0102]

[0103] wherein, represents the oscillation energy index.

[0104] S36, determining a risk path according to the oscillation energy index;

[0105] S37, determining a power supply path according to the available path and the risk path;

[0106] After the oscillation energy index and the damping ratio are calculated, it can be judged whether the oscillation energy index is greater than a preset index or the damping ratio is less than a preset threshold. If yes, the available path is marked as a risk path.

[0107] S38, calculating the weight of the power supply path based on the oscillation risk index and the estimated loss;

[0108] S39, searching for an optimal power supply path of the power restoration area according to the weight.

[0109] In a specific implementation, the calculation formula of the weight is:

[0110]

[0111] wherein, represents the weight, and both represent weight coefficients, represents the oscillation risk index, represents the estimated loss.

[0112] In addition, the Dijkstra algorithm or the existing improved Dijkstra algorithm can also be used to search for an optimal power supply path with the minimum weight as the target.

[0113] Step 204, acquiring the response speed of each clean energy, and dividing the clean energy into a fast response cluster and a slow response cluster according to the response speed;

[0114] In the embodiment of the application, the clean energy can be wind power, photovoltaic, energy storage, hydrogen energy and the like, and the response speed can be a dynamic response time constant. According to the difference of the dynamic response time constant, the clean energy can be divided into a fast response cluster and a slow response cluster. For example, a millisecond-level response energy storage system (such as a lithium ion battery, a super capacitor), a hydrogen energy system, a photovoltaic inverter and the like.

[0115] ​​Step 205, calculating the real-time inertia of the fast-response cluster and the real-time damping coefficient of the slow-response cluster;

[0116] In the embodiments of the present application, step 205 can include the following sub-steps:

[0117] S51, obtaining the frequency change rate and the basic inertia of the fast-response cluster;

[0118] S52, adjusting the real-time inertia of the fast-response cluster according to the frequency change rate and the basic inertia;

[0119] In the embodiments of the present application, the frequency change rate and the basic inertia of the fast-response cluster can be obtained to adjust the real-time inertia of the fast-response cluster.

[0120] In one example, step S52 can include the following sub-steps:

[0121] S521, obtaining the inertia adjustment coefficient, the available energy capacity, the charge-discharge efficiency, the reference capacity, the sensitivity factor and the rated frequency of the fast-response cluster;

[0122] S522, calculating the basic inertia by using the inertia adjustment coefficient, the available energy capacity, the charge-discharge efficiency and the reference capacity;

[0123] S523, calculating the real-time inertia of the fast-response cluster by using the basic inertia, the frequency change rate, the sensitivity factor and the rated frequency.

[0124] In a specific implementation, the calculation formula for adjusting the real-time inertia of the fast-response cluster is:

[0125] ;

[0126] ;

[0127] wherein, represents the basic inertia, represents the inertia adjustment coefficient, represents the available energy capacity of the fast-response cluster, represents the charge-discharge efficiency of the fast-response cluster, represents the reference capacity of the fast-response cluster, represents the real-time inertia, represents the sensitivity factor, represents the frequency change rate, represents the rated frequency.

[0128] S53, obtaining the frequency deviation of the slow-response cluster, and adjusting the real-time damping coefficient of the slow-response cluster according to the frequency deviation.

[0129] In the embodiments of the present application, the real-time damping coefficient of the slow response cluster can be adjusted according to the frequency deviation of the slow response cluster.

[0130] In one example, step S53 can include:

[0131] S531, acquiring the maximum power disturbance, the allowed frequency deviation, the frequency deviation of the slow response cluster, and the current available power and the rated maximum power of each clean energy in the slow response cluster;

[0132] S532, calculating the real-time damping coefficient of the slow response cluster using the maximum power disturbance, the allowed frequency deviation, the frequency deviation, the current available power and the rated maximum power.

[0133] In a specific implementation, the calculation formula for adjusting the real-time damping of the slow response cluster is:

[0134] ;

[0135] ;

[0136] wherein, Dk represents the real-time damping coefficient of the kth clean energy in the slow response cluster, Dk represents the damping adjustment coefficient, Pk represents the current available power of the kth clean energy in the slow response cluster, Pk represents the rated maximum power of the kth clean energy in the slow response cluster, Dk represents the frequency deviation, Dk represents the prevention zero constant, Dk represents the maximum power disturbance, Dk represents the allowed frequency deviation. By using a distributed consistency algorithm, the total damping is ensured to meet the condition, and the damping is coordinated and optimized. Step 206, supplying the clean energy to the power restoration area according to the optimal power supply path, the real-time inertia and the real-time damping coefficient.

[0137] Step 206, supplying the clean energy to the power restoration area according to the optimal power supply path, the real-time inertia and the real-time damping coefficient.

[0138] In the embodiments of the present application, the fast response cluster is also supplied with energy by a power supply device for storing clean energy.

[0139] The power supply device includes a graphene super capacitor, a lithium ion capacitor and a bidirectional direct current converter, wherein the bidirectional direct current converter is connected with the graphene super capacitor and the lithium ion capacitor.

[0140] The power supply device includes a graphene super capacitor, a lithium ion capacitor and a bidirectional direct current converter, wherein the bidirectional direct current converter is connected with the graphene super capacitor and the lithium ion capacitor.

[0141] ​In this embodiment, graphene supercapacitors (manufactured using graphene materials) in 6 parallel and 2 series can be used, connected in parallel-serial hybrid connection, balancing power and energy density, with a capacity of 100 F, and 4 parallel lithium ion capacitors, with a capacity of 3500 F, and a bidirectional DC converter that can be a four-phase interleaved parallel Buck-Boost circuit.

[0142] and obtaining load power and load duration based on the grid data, adjusting the power supply mode of the power supply device based on the load power and the load duration, the power supply device providing electrical energy based on the power supply mode; if the load power is greater than or equal to a power threshold, an instantaneous mode is adopted, and the graphene supercapacitor supplies power to the load; if the load power is less than the threshold and the duration is greater than or equal to a time threshold, a continuous mode is adopted, and the lithium ion capacitor converts power through the bidirectional DC converter; if both are less than the two thresholds, a hybrid mode is adopted.

[0143] and if the power supply mode is a hybrid mode, obtaining maximum power and average power based on a preset time range and the grid data, obtaining a first weight and a second weight based on the maximum power and the average power, and the graphene supercapacitor and the lithium ion capacitor providing electrical energy based on the first weight and the second weight. For example, the maximum power in the past 10 ms and the average power in the past 1 s are obtained, the first weight = maximum power / (maximum power + average power), and the second weight = 1 - first weight, so as to allocate different power supply amounts.

[0144] Step 207, calculating the damping current component and the reverse harmonic current of the clean energy;

[0145] Step 208, injecting the damping current component and the reverse harmonic current into the preset inverter to suppress the synchronous oscillation and transient disturbance of the complex power area.

[0146] In the embodiment of the application, the clean energy can be converted into a virtual synchronous second-order model, an angular velocity deviation is obtained based on the virtual synchronous second-order model, and the inverter injects a damping current component based on the angular velocity deviation to offset the power oscillation energy of the clean energy; for example, the energy storage inverter adopts VSG control, adjusts the output voltage frequency and phase in real time, injects a damping current component, detects the high-frequency component (such as 10-100 Hz) of the angular velocity deviation, and triggers the energy storage inverter to inject a reverse damping current.

[0147] The oscillation component frequency of the clean energy can also be obtained, which is analyzed by FFT (Fast Fourier Transform), and the inverter injects a reverse harmonic current based on the oscillation component frequency to offset the power oscillation energy of the clean energy. For example, the time domain characteristics (such as 0.1-2 Hz fluctuation) of the angular velocity deviation are analyzed, and the hydrogen energy output phase is adjusted to offset the oscillation energy.

[0148] The second-order model of the virtual synchronous machine equivalent to the multi-source system is obtained by mapping the dynamic behavior of the distributed energy (such as energy storage, photovoltaic, hydrogen energy, etc.) to the rotor motion equation of the traditional synchronous generator through mathematical modeling. The rotor motion equation of the traditional synchronous generator is obtained, the voltage phase angle of the grid-connected point of the multi-source system is equivalent to the virtual rotor angle, the virtual mechanical torque is calculated, which represents the total output power of the multi-source system and is superimposed by the output of each device; the virtual electromagnetic torque is calculated, which represents the power exchange between the multi-source system and the grid and is determined by the phase difference between the voltage and current of the grid-connected point; the above parameters, real-time damping coefficient and real-time inertia are substituted into the rotor motion equation to obtain the equivalent model of the multi-source system.

[0149] The calculation formula of the clean energy converted into the virtual synchronous second-order model is:

[0150] ;

[0151] ;

[0152] ;

[0153] The calculation formula of the damping current component is:

[0154] ;

[0155] The calculation formula of the reverse harmonic current is:

[0156] ;

[0157] wherein, represents the angular velocity deviation, represents the real-time inertia, represents the real-time damping coefficient of the th clean energy in the slow response cluster, represents the virtual mechanical torque, represents the virtual electromagnetic torque, represents the electromagnetic torque coefficient, represents the voltage amplitude of the th clean energy, represents the current amplitude of the th clean energy, represents the phase difference between the voltage and current of the th clean energy, represents the power-torque conversion coefficient, represents the output power of the th clean energy, represents the number of clean energies, Represents the damping current component. Represents the time constant. Represents differential gain. Indicates proportional gain. Represents a complex frequency variable. Indicates reverse harmonic current. Indicates compensation gain. Indicates the amplitude of the oscillating current. Indicates the frequency of the oscillation component. Indicates time, Indicates the phase compensation angle. This indicates frequency deviation.

[0158] In this embodiment, the frequency can be adaptively adjusted according to the oscillation frequency. / The ratio, for example, increases when high-frequency oscillations (>30Hz) are detected. Enhances the differential action; increases the efficiency of low-frequency oscillations (<5 Hz). Enhance the proportion adjustment.

[0159] In this embodiment of the invention, risk warning information can also be generated by obtaining line galloping warning level, lightning tripping probability, hidden danger results and tree obstacle detection results.

[0160] In one example, line galloping warning levels and lightning tripping probabilities can be calculated by acquiring meteorological data. This meteorological data can include wind speed, rainfall, and lightning data; for instance, a miniature weather station can be deployed atop the tower, comprising an ultrasonic anemometer (for wind speed), an optical rain gauge (for rainfall), and an atmospheric electric field meter (for lightning data).

[0161] Then, based on the lightning data, lightning density is obtained, and the probability of lightning-induced tripping is calculated based on the lightning density. The lightning-induced tripping probability can be combined with the lightning fault type to more accurately locate the lightning fault. A line galloping warning level is obtained based on wind speed, rainfall, and lightning density. Different weights can be assigned to wind speed, rainfall, and lightning density, and these weights can be added together to obtain the line galloping warning level. The probability of line breakage or tower collapse due to fluctuations caused by wind and other factors is calculated.

[0162] In one example, inspection images can be acquired using drones, and defect detection models can be used to identify potential hazards within these images.

[0163] For example, the unmanned aerial vehicle can carry a visible light camera, an infrared thermal imager, a laser radar LiDAR, and an ultraviolet imager to obtain inspection images, train a YOLOv7 model through historical labeled image samples (containing defects of power equipment such as insulator breakage and hardware corrosion), obtain a defect detection model, identify defects of power equipment in the inspection images through the defect detection model, early warn possible failures of the power equipment, and obtain a hidden danger result.

[0164] In one example, a line corridor digital elevation model can be generated based on LiDAR point clouds, a tree barrier safety distance can be obtained based on the line corridor digital elevation model, and a tree barrier detection result can be obtained based on the tree barrier safety distance. For example, an alarm is triggered when the distance between the conductor and the vegetation is less than 3 m. The tree barrier safety distance refers to the distance between the power line and the tree to ensure the safe operation of the power line and prevent line failures or safety accidents caused by tree growth or lodging.

[0165] In the embodiments of the present application, by fusing meteorological monitoring, geographic information, and equipment state data, the association between external environment and power grid failure is established, external environmental factors are converted into quantifiable power grid risk indicators, failure risk prediction is realized, grounding failure is predicted in advance, and further damage of failure is reduced.

[0166] Further, considering that clean energy is different from traditional coal power generation and hydropower generation, the power generation capacity and power generation time of clean energy are uncontrollable, and clean energy can only generate power in the corresponding time period and environment, and the randomness is large. For example, when there is wind and sunlight, wind energy and solar energy can generate power, and the power generation capacity changes with the environment. When the power distribution network fails, if the power supply is insufficient or excessive, the traditional power generation mode can be started and stopped as needed, but clean energy will still generate power during the power distribution network failure, and excess power will be generated. In other dispatching modes (such as micro-grid operation and island operation mode), there is still excess power, and the power may be abandoned to ensure the stability of the power grid, thereby causing power waste. Therefore, in the embodiments of the present application, the electricity demand of users can be adjusted by adjusting the electricity price to consume excess power, such as reducing the price to support users to charge new energy vehicles or adjusting industrial processes to reduce power waste.

[0167] In a specific implementation, meteorological satellite data can be obtained, predicted meteorological data can be obtained based on the meteorological satellite data, and predicted power generation capacity of clean energy can be obtained based on the predicted meteorological data. The specific process is as follows:

[0168] First, historical meteorological data and historical power generation capacity of clean energy corresponding to the historical meteorological data are obtained, the historical meteorological data and the predicted meteorological data are matched, the predicted power generation capacity corresponding to the historical yield point is obtained, and the power generation capacity of clean energy is predicted through historical weather data.

[0169] Then, a predicted load demand is obtained, an adjustment amount is obtained based on the predicted load demand and the predicted power generation amount, if the adjustment amount is less than 0, then based on the adjustment amount, the traditional power supply generates power and inputs the power grid, if the adjustment amount is greater than 0 and less than or equal to the power storage amount of the power supply device, then based on the adjustment amount, the clean energy delivers power to the power supply device, if the adjustment amount is greater than 0 and greater than the power storage amount, then based on the adjustment amount and the power storage amount, an overflow amount is obtained, based on a preset level range and the overflow amount, an electricity price is adjusted, based on the adjusted electricity price, a user adjusts a work plan and a charging plan, and the clean energy delivers power to the user end.

[0170] Wherein, the predicted load demand can be obtained according to the historical load demand.

[0171] The predicted load demand and the predicted power generation amount are compared, if the power generation amount does not meet the load demand, then the traditional power generation mode (such as coal power generation) is used for power generation, and the power is supplemented to meet the load demand, if the load demand is met, then the power supply device is preferentially charged to support the power supply device to provide power in case of failure, after the power supply device is fully charged, according to the overflow amount and the preset level range, the electricity price is adjusted, the more the overflow amount, the lower the electricity price, the factory adjusts the work plan of the factory in real time according to the electricity price, and the user can drive the new energy vehicle to the charging pile for charging, so as to reduce the waste of power.

[0172] The application breaks through the limitation of the action speed of the physical switch by constructing a logical power supply path by abstracting the power equipment as a virtual node, decoupling the software-defined energy flow control layer from the physical layer, and realizing dynamic virtual topology reconstruction; by using the fast response characteristics of distributed clean energy, the distributed clean energy is dynamically aggregated as a virtual synchronous unit with adjustable inertia and damping to simulate the dynamic characteristics of the traditional synchronous generator to suppress the power oscillation of the multi-source heterogeneous distribution network and provide inertia support to realize real-time adaptive distribution of inertia and damping and adapt to the multi-source power fluctuation scene; the clean energy is divided into fast / slow response equipment hierarchical control according to the response speed, for example, the energy storage provides instantaneous inertia, and the hydrogen energy provides continuous damping to play the advantages of the dynamic characteristics.

[0173] Please refer to Figure 2 , Figure 2 The structure block diagram of the multi-type clean energy distribution network fast power recovery system provided by the embodiment of the application.

[0174] The embodiment of the application provides a multi-type clean energy distribution network fast power recovery system.

[0175] The fault unit 201 is used for obtaining fault data of the distribution network, and determining a power recovery area according to the fault data.

[0176] The reconstruction unit 202 is configured to acquire a power grid topology of the power distribution network and virtual nodes corresponding to power equipment in the power distribution network, and generate a logical power supply path diagram according to the virtual nodes and the power grid topology; acquire a weight of each power supply path in the logical power supply path diagram, and determine an optimal power supply path based on the weight and the power restoration area;

[0177] The synchronization unit 203 is configured to acquire a response speed of each clean energy, and divide the clean energy into a fast-response cluster and a slow-response cluster according to the response speed; calculate a real-time inertia of the fast-response cluster and a real-time damping coefficient of the slow-response cluster;

[0178] The power restoration unit 204 is configured to supply the clean energy to the power restoration area according to the optimal power supply path, the real-time inertia and the real-time damping coefficient.

[0179] In this embodiment, the system further comprises:

[0180] The suppression unit 205 is configured to convert the clean energy into a virtual synchronous second-order model, obtain an angular velocity deviation based on the virtual synchronous second-order model, and inject a damping current component into an inverter based on the angular velocity deviation to offset power oscillation energy of the clean energy; for example, when a VSG control is used for the energy storage inverter, the output voltage frequency and phase are adjusted in real time, the damping current component is injected, and the high-frequency component (for example, 10-100 Hz) of the angular velocity deviation is detected to trigger the energy storage inverter to inject a reverse damping current.

[0181] In addition, the oscillation component frequency of the clean energy is acquired, analyzed by FFT (Fast Fourier Transform), and based on the oscillation component frequency, the inverter injects a reverse harmonic current to offset the power oscillation energy of the clean energy. For example, the time domain characteristics (for example, 0.1-2 Hz fluctuation) of the angular velocity deviation are analyzed, and the hydrogen energy output phase is adjusted to offset the oscillation energy.

[0182] The second-order model of the virtual synchronous machine equivalent to the multi-source system is obtained by mapping the dynamic behavior of the distributed energy (such as energy storage, photovoltaic, hydrogen energy, etc.) to the rotor motion equation of the traditional synchronous generator through mathematical modeling. The rotor motion equation of the traditional synchronous generator is obtained, the voltage phase angle of the grid-connected point of the multi-source system is equivalent to the virtual rotor angle, the virtual mechanical torque is calculated, which represents the total output power of the multi-source system and is superimposed by the output of each device; the virtual electromagnetic torque is calculated, which represents the power exchange between the multi-source system and the power grid and is determined by the phase difference between the grid-connected point voltage and current; the above parameters, the real-time damping coefficient and the real-time inertia are substituted into the rotor motion equation to obtain the equivalent model of the multi-source system.

[0183] The embodiment of the present application also provides an electronic device, the device comprising a processor and a memory:

[0184] The memory is used for storing program codes and transmitting the program codes to the processor.

[0185] The processor is used for executing the method for fast power restoration of a multi-type clean energy power distribution network according to instructions in the program codes.

[0186] The embodiment of the present application also provides a computer readable storage medium, the computer readable storage medium is used for storing program codes, and the program codes are used for executing the method for fast power restoration of a multi-type clean energy power distribution network.

[0187] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system, the device and the unit described above can refer to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0188] Each embodiment in the specification is described in a progressive manner, and each embodiment focuses on the difference from other embodiments, and the same and similar parts between each embodiment can be referred to each other.

[0189] Those skilled in the art should understand that the embodiments of the embodiment of the present application can be provided as a method, a device or a computer program product. Therefore, the embodiments of the present application can adopt a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the embodiments of the present application can adopt the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program codes.

[0190] The embodiments of the present application are described with reference to flowcharts and / or block diagrams according to the method, terminal device (system) and computer program product of the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be realized by computer program instructions. These computer program instructions can be provided to a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing terminal device to produce a machine, so that the instructions executed by the computer or other programmable data processing terminal device produce a machine for realizing the functions specified in the flowcharts and / or block diagrams. Figure 1 The device for realizing the functions specified in one flow or multiple flows and / or blocks Figure 1 The device for realizing the functions specified in one block or multiple blocks.

[0191] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the flow Figure 1 flow or flows and / or blocks Figure 1 function specified in the flow or flows and / or blocks.

[0192] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the flow Figure 1 flow or flows and / or blocks Figure 1 function specified in the flow or flows and / or blocks.

[0193] While preferred embodiments of the application have been described, those skilled in the art will recognize that additional modifications and variations can be made thereto without departing from the scope of the application. It is therefore intended that the appended claims cover all such modifications and variations as fall within the scope of the application.

[0194] It should be noted that the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of related data need to comply with relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation portal for user to choose authorization or refusal.

[0195] Finally, it should be noted that in this document, the terms such as first and second are used only to distinguish one entity or operation from another, and do not necessarily require or imply that these entities or operations have any such actual relationship or order. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or terminal device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or terminal device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of other identical elements in the process, method, article or terminal device including the element.

[0196] The above-described embodiments are only used to illustrate the technical solutions of the present application, and are not intended to limit the present application; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those skilled in the art that the technical solutions recorded in the foregoing embodiments can still be modified, or some technical features can be replaced by equivalent replacements; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for rapid power restoration in multi-type clean energy distribution networks, characterized in that, include: Obtain fault data of the power distribution network and determine the power restoration area based on the fault data; Obtain the power grid topology diagram of the distribution network and the virtual nodes corresponding to the power equipment in the distribution network, and generate a logical power supply path diagram based on the virtual nodes and the power grid topology diagram; Obtain the weight of each power supply path in the logical power supply path diagram, and determine the optimal power supply path based on the weight and the power restoration area; The response speed of each clean energy source is obtained, and the clean energy sources are divided into fast response clusters and slow response clusters based on the response speed. Calculate the real-time inertia of the fast-response cluster and the real-time damping coefficient of the slow-response cluster; The clean energy is supplied to the restored power area based on the optimal power supply path, the real-time inertia, and the real-time damping coefficient.

2. The method according to claim 1, characterized in that, The step of obtaining the weight of each power supply path in the logical power supply path diagram and determining the optimal power supply path based on the weight and the power restoration area includes: Obtain the voltage amplitude and phase angle of each line in the logical power supply path diagram; A virtual adjacency matrix is ​​constructed based on the voltage amplitude and the phase angle; The connection relationships of each line are determined based on the virtual adjacency matrix; Generate available paths based on the connection relationships; Calculate the oscillation risk index, oscillation energy index, and estimated loss for each available path in the logic power supply path diagram; The risk path is determined based on the oscillation energy index; The power supply path is determined based on the available paths and the risky paths; The weight of the power supply path is calculated based on the oscillation risk index and the estimated loss; The optimal power supply path for the restored power area is searched based on the weights.

3. The method according to claim 2, characterized in that, The steps for calculating the oscillation risk index, oscillation energy index, and estimated loss for each available path in the logic power supply path diagram include: Obtain the oscillation frequency, oscillation amplitude, and damping ratio of the available path; Calculate the oscillation risk index of the available path based on the oscillation frequency, the oscillation amplitude, and the damping ratio; Calculate the oscillation energy index based on the oscillation frequency and the oscillation amplitude; Obtain historical experience data, and calculate the estimated loss of the available path based on the historical experience data.

4. The method according to claim 1, characterized in that, The steps of calculating the real-time inertia of the fast-response cluster and the real-time damping coefficient of the slow-response cluster include: Obtain the frequency change rate and basic inertia of the fast response cluster; The real-time inertia of the fast response cluster is adjusted according to the frequency change rate and the base inertia. The frequency deviation of the slow response cluster is obtained, and the real-time damping coefficient of the slow response cluster is adjusted according to the frequency deviation.

5. The method according to claim 4, characterized in that, The step of adjusting the real-time inertia of the fast response cluster according to the frequency change rate and the base inertia includes: Obtain the inertia adjustment factor, available energy capacity, charge / discharge efficiency, reference capacity, sensitivity factor, and rated frequency of the fast response cluster; The basic inertia is calculated using the inertia adjustment coefficient, the available energy capacity, the charge / discharge efficiency, and the reference capacity. The real-time inertia of the fast response cluster is calculated using the base inertia, the rate of change of frequency, the sensitivity factor, and the rated frequency.

6. The method according to claim 4, characterized in that, The step of obtaining the frequency deviation of the slow response cluster and adjusting the real-time damping coefficient of the slow response cluster according to the frequency deviation includes: Obtain the maximum power disturbance, allowable frequency deviation, frequency deviation, and the current available power and rated maximum power of each clean energy source in the slow response cluster; The real-time damping coefficient of the slow response cluster is calculated using the maximum power disturbance, the allowable frequency deviation, the frequency deviation, the current available power, and the rated maximum power.

7. The method according to any one of claims 1-6, characterized in that, Also includes: Calculate the damping current component and reverse harmonic current of the clean energy source; The damping current component and the reverse harmonic current are injected into the preset inverter to suppress synchronous oscillations and transient disturbances in the power restoration region.

8. A rapid power restoration system for multi-type clean energy distribution networks, characterized in that, include: The fault unit is used to acquire fault data of the distribution network and determine the power restoration area based on the fault data; The reconfiguration unit is used to obtain the power grid topology diagram of the distribution network and the virtual nodes corresponding to the power equipment in the distribution network, and generate a logical power supply path diagram based on the virtual nodes and the power grid topology diagram; Obtain the weight of each power supply path in the logical power supply path diagram, and determine the optimal power supply path based on the weight and the power restoration area; A synchronization unit is used to acquire the response speed of each clean energy source and divide the clean energy sources into fast response clusters and slow response clusters based on the response speed. Calculate the real-time inertia of the fast-response cluster and the real-time damping coefficient of the slow-response cluster; The power restoration unit is used to supply the clean energy to the power restoration area according to the optimal power supply path, the real-time inertia, and the real-time damping coefficient.

9. An electronic device, characterized in that, The device includes a processor and a memory: The memory is used to store program code and transmit the program code to the processor; The processor is used to execute the rapid power restoration method for multi-type clean energy distribution networks according to any one of the claims 1-7, based on the instructions in the program code.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store program code for executing the rapid power restoration method for multi-type clean energy distribution networks as described in any one of claims 1-7.

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