Access method and system for power distribution network containing new energy power generation system and special load

Abstract

The invention discloses a new energy power generation system and special load-containing power distribution network access method and system, and the method comprises the steps: carrying out the data collection on nodes and equipment of a power distribution network, and carrying out the preprocessing; establishing a comprehensive energy model, and constructing a simulation environment; the method comprises the following steps: dividing a power distribution network into a plurality of areas, constructing a hierarchical positioning model, identifying and positioning different types of faults, and processing and repairing the faults; and optimizing the access point position of the new energy power generation system according to the fault processing result and the adjustment condition of the energy storage system. By optimizing the access point position of the new energy power generation system in real time, power distribution is effectively balanced, and power grid instability caused by load fluctuation is reduced. A layered positioning model is constructed, faults in the power distribution network can be quickly and accurately identified and positioned, and the faults are timely processed and repaired through an intelligent scheduling system, so that the power failure time of the faults is shortened.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a method and system for accessing a distribution network including a new energy power generation system and special loads. Background Art

[0002] New energy generally refers to renewable energy that is developed and utilized based on new technologies, including solar energy, biomass energy, wind energy, geothermal energy, wave energy, ocean current energy and tidal energy, as well as thermal cycles between the ocean surface and deep layers; in addition, there are hydrogen energy, biogas, alcohol, methanol, etc., while the widely used energy such as coal, oil, natural gas, and hydropower are called conventional energy. With the limitation of conventional energy and the increasing prominence of environmental problems, new energy with environmental protection and renewable characteristics has been increasingly valued by various countries.

[0003] With the rapid development of the national economy and modern industry, the loads in the power system are becoming increasingly complex and diversified. The large-scale use of high-power nonlinear, impact and fluctuating special loads such as electrified railways, metallurgy, and electric vehicle charging piles has shown its impact on the regional power grid and even the entire power system, and has brought a series of power quality problems.

[0004] Special loads are self-variable loads that can draw or release tens of megawatts or even hundreds of megawatts of power from the power grid in seconds or even milliseconds. They mainly include loads with power generation characteristics and loads with strong volatility and impact. Among them, the large-scale decentralized access of special loads will also have a series of impacts on the health of the distribution network. The high-penetration distributed power sources in special loads change the flow direction of the single-source radial distribution network to a non-unidirectional flow; strong volatility and impact loads are prone to cause forced power oscillations in the power system, making the originally determined flow distribution random, thereby reducing the economic benefits of the distribution network and increasing the operating risk. Therefore, it is urgent to provide a distribution network optimization access method containing new energy power generation systems and special loads. Summary of the invention

[0005] In view of the above-mentioned problems, the present invention is proposed.

[0006] Therefore, the technical problem solved by the present invention is: how to optimize the access point location of the renewable energy power generation system in a complex power distribution network, and efficiently identify and handle faults to ensure the stability of the power grid and the continuity of power supply.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions: A method for accessing a distribution network including a new energy power generation system and a special load, comprising: collecting data on nodes and devices of the distribution network, and performing preprocessing;

[0008] Establish a photovoltaic power generation model, a new energy power generation model, a special load model, and a distributed energy storage model, and build a simulation environment for simulating the dynamic interaction between the new energy power generation system and the distribution network;

[0009] Divide the distribution network into multiple areas, build a hierarchical positioning model, identify and locate different types of faults, and handle and repair the faults through an intelligent dispatching system;

[0010] According to the fault handling results and the adjustment of the energy storage system, the access point location of the new energy power generation system is optimized in real time.

[0011] As a preferred solution of the distribution network access method containing a new energy power generation system and special loads described in the present invention, wherein: the data collection includes voltage data, current data, power data and light intensity data, temperature data, wind speed data, sun angle and radiation energy data;

[0012] The preprocessing includes data cleaning, missing data processing, feature extraction and data compression.

[0013] 5. As a preferred solution of the method for connecting the distribution network containing the new energy power generation system and the special load described in the present invention, wherein: the voltaic power generation model includes using simulation software to build a photovoltaic power generation model and calculate the output voltage V of the photovoltaic cell, the formula is:

[0014] V=V oc -I·R s

[0015] Among them, V oc is the open circuit voltage, I is the current, R s is the series resistance;

[0016] Considering the influence of temperature coefficient α on the performance of photovoltaic cells, the influence of temperature change on power output is calculated. The formula is:

[0017] P=P max ·[1+α·(TT ref )]

[0018] Among them, P max is the maximum power output, T is the current temperature, T ref is the reference temperature;

[0019] To simulate the nonlinear effect of radiation intensity on photovoltaic power generation, the relationship between light intensity and current is used:

[0020]

[0021] Among them, I sc is the short-circuit current, G is the current radiation intensity, Gref is the reference radiation intensity;

[0022] The new energy generation model includes: for wind power generation, establishing a model based on wind speed v and output power P w The relationship model is used to calculate the wind power generation power, and the formula is:

[0023]

[0024] Where ρ is the air density, A is the swept area, C p is the power coefficient;

[0025] Combined with the photovoltaic power generation model, calculate the output power P of the solar power generation system solar , the formula is:

[0026]

[0027] Among them, G ref is the reference radiation intensity, P max Indicates the maximum output power of the solar power generation system;

[0028] The special load model includes establishing a model that takes into account time variation, intermittency and load, using a time series analysis method to predict changes in loads at different time periods, and simulating the start and stop behavior of loads;

[0029] The distributed energy storage system model includes simulating the working state of the energy storage system under different load conditions through the battery charging and discharging characteristic curve.

[0030] 6. As a preferred solution of the method for connecting a distribution network containing a new energy power generation system and a special load according to the present invention, wherein: the construction of a simulation environment for simulating the dynamic interaction between the new energy power generation system and the distribution network includes constructing a distribution network topology model including a substation, a power generation node, a load node and a transmission line, and defining the electrical parameters of each node and branch;

[0031] Use the node admittance matrix Y to represent the topological relationship of the system:

[0032] Y=D+jB

[0033] Where D is the conductance matrix, B is the susceptance matrix, and j represents the imaginary unit;

[0034] Integrate photovoltaic power generation model, new energy power generation model, special load model and distributed energy storage system model into the topological structure model of the distribution network;

[0035] During the simulation, the power balance equation is used to calculate the power distribution of each node:

[0036]

[0037] Among them, P i and Q i are the active power and reactive power of node i, V i and V j The voltages θ at nodes i and j are ij is the phase angle difference between nodes i and j, G ij represents the conductance component between nodes i and j, B ij represents the susceptance component between nodes i and j.

[0038] As a preferred solution of the distribution network access method containing a new energy power generation system and a special load described in the present invention, wherein: the construction of a hierarchical positioning model includes dividing the distribution network into a layer for locating a fault area, and reading the fault codes of all port nodes in the hierarchical model to determine the fault area;

[0039] Compare the rated and measured values ​​of voltage and current to calculate the voltage deviation ΔV of the node i , current deviation ΔI i , the formula is:

[0040] ΔV i =V i,nominal -V i,measured

[0041] ΔI i =I i,nominal -I i,measured

[0042] Among them, V i,nominal and I i,nominal Respectively represent the rated voltage and current of node i, V i,measured and I i,measured denote the measured voltage and current of node i respectively;

[0043] When the voltage deviation of a node is ΔV i Exceeding the set threshold ∈ V , or current deviation ΔI i Exceeding the set threshold ∈ I When the current node is determined to be faulty, the fault code of the node is activated; when the fault codes of multiple adjacent nodes are activated, these nodes are classified into the same area and determined as the fault area;

[0044] The second layer is the fault section location layer, which reads the fault information of the nodes in the fault area of ​​the first layer, locates the section where the fault occurs and determines the fault section;

[0045] For each phase in the fault area, at each node in the area, calculate the positive sequence current I1:

[0046]

[0047] Among them, I a ,I b ,I c They are three-phase currents respectively; a=e J120° is a complex number, indicating a rotation of 120° in phase shift; a 2 =e J240° is a complex number, indicating a rotation of the phase shift 240; e is a natural number, and J is an imaginary number;

[0048] For each pair of adjacent nodes i and j, calculate the phase angle difference θ of the positive sequence current ij :

[0049] θ ij =∠I 1i -∠I 1j

[0050] Among them, ∠I 1i Represents the phase angle of the positive sequence current I1 at node i, ∠I 1j represents the phase angle of the positive sequence current I1 at node j;

[0051] When θ ij Exceeding the set threshold ∈ θ When , it indicates that the fault is located in the segment between nodes i and j;

[0052] The positive sequence current fault component is used to identify and encode the fault current direction of the regional end node to locate the fault;

[0053] Set up micro PMU measurement points at the main power outgoing line, distributed power incoming line, large inductive special load incoming line nodes, and multi-branch nodes;

[0054] The positive sequence current information is obtained at the node measurement point, the positive sequence current fault component of the node is calculated, and the fault current direction coding of each node is obtained.

[0055] As a preferred solution of the distribution network access method containing a new energy power generation system and a special load described in the present invention, wherein: the processing and repairing of the fault by the intelligent dispatching system includes that after determining the fault section, the intelligent dispatching system automatically performs an isolation operation on the fault section, and isolates the fault section from the normal operating area by cutting off the line switch connected to the fault section;

[0056] When the faulty section is isolated, the intelligent dispatching system redistributes the power flow in the area to ensure that the power supply of the non-faulty sections is not affected;

[0057] When it is detected that the load of the faulty section needs to be redistributed, the intelligent dispatching system automatically transfers the load of the faulty section to other available power supply sections;

[0058] When load transfer cannot meet demand, the intelligent dispatching system activates the backup power supply to provide emergency power support for high-priority loads;

[0059] The intelligent dispatching system automatically generates repair instructions based on the fault type and location. The instructions are sent to on-site maintenance personnel through the digital platform to notify them to carry out repairs.

[0060] When fault repair begins, the intelligent dispatching system monitors the repair process in real time and collects electrical parameter data to ensure the effectiveness and safety of the repair operation;

[0061] When the fault is repaired, the intelligent dispatching system automatically adjusts the grid structure dynamically, restores the normal power supply path, and optimizes the power flow path;

[0062] When the repair and reconstruction are completed, the intelligent scheduling system performs self-checking and debugging to verify the stability of the repaired system and the normal recovery of all protection measures;

[0063] Record all operations and data that occur during the fault handling process.

[0064] As a preferred solution of the method for accessing a distribution network containing a renewable energy power generation system and special loads described in the present invention, the real-time optimization of the access point position of the renewable energy power generation system includes, according to the fault handling result and the adjustment of the energy storage system, the system adjusts the access point position of the renewable energy power generation system in real time, and connects the power generation unit to the distribution network through a step-up transformer.

[0065] A distribution network access system including a new energy power generation system and special loads, characterized by: including:

[0066] Data acquisition and preprocessing module: collects data on nodes and devices in the distribution network and performs preprocessing;

[0067] Dynamic simulation and modeling module: Establish a photovoltaic power generation model, a new energy power generation model, a special load model, a distributed energy storage model, and build a simulation environment for simulating the dynamic interaction between the new energy power generation system and the distribution network;

[0068] Fault identification and processing module: divides the distribution network into multiple areas, builds a hierarchical positioning model, identifies and locates different types of faults, and processes and repairs the faults through an intelligent dispatching system;

[0069] Access point optimization and control module: optimizes the access point location of the new energy power generation system in real time based on the fault handling results and the adjustment of the energy storage system.

[0070] Beneficial effects of the present invention: The present invention optimizes the access point locations of new energy power generation systems in real time, effectively balances power distribution, and reduces grid instability caused by load fluctuations. A hierarchical positioning model is constructed to quickly and accurately identify and locate faults in the distribution network, and to process and repair them in a timely manner through an intelligent dispatching system, thereby shortening the power outage time. Combined with the regulation of the energy storage system, the allocation of power resources is optimized to ensure continuous power supply to critical loads under high load or emergency conditions, thereby improving the overall reliability of the power grid. Through dynamic simulation and modeling, full use is made of new energy resources such as photovoltaics and wind power, and their access and operation in the distribution network are optimized, achieving efficient access and use of green energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the figures required for use in the description of the embodiments will be briefly introduced below. Obviously, the figures described below are only some embodiments of the present invention. For ordinary technicians in this field, other figures can be obtained based on these figures without paying creative work.

[0072] Figure 1 A flow chart of a method for connecting a distribution network including a new energy power generation system and a special load to the first embodiment of the present invention. DETAILED DESCRIPTION

[0073] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the specification drawings. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0074] Example 1, reference Figure 1 , which is an embodiment of the present invention, provides a method for connecting a distribution network including a new energy power generation system and a special load, including:

[0075] S1: Collect data on nodes and devices in the distribution network and perform preprocessing.

[0076] Data collection includes voltage data, current data, power data, light intensity data, temperature data, wind speed data, solar angle and radiation energy data; preprocessing includes data cleaning, missing data processing, feature extraction and data compression.

[0077] It should be noted that voltage and current data are key parameters that reflect the quality of power transmission, while power data directly affects load distribution decisions. Light intensity and temperature data have a direct impact on the output power of photovoltaic power generation, while wind speed data is an important variable for wind power generation output. Sun angle and radiation energy data further refine the prediction accuracy of photovoltaic power generation and ensure its effectiveness when connected to the distribution network.

[0078] S2: Establish a photovoltaic power generation model, a new energy power generation model, a special load model, and a distributed energy storage model, and build a simulation environment for simulating the dynamic interaction between the new energy power generation system and the distribution network.

[0079] The photovoltaic power generation model includes using simulation software to build a photovoltaic power generation model and calculate the output voltage V of the photovoltaic cell. The formula is:

[0080] V=V oc -I·R s

[0081] Among them, V oc is the open circuit voltage, I is the current, R s is the series resistance.

[0082] Considering the influence of temperature coefficient α on the performance of photovoltaic cells, the influence of temperature change on power output is calculated. The formula is:

[0083] P=P max ·[1+α·(TT ref )]

[0084] Among them, P max is the maximum power output, T is the current temperature, T ref is the reference temperature.

[0085] To simulate the nonlinear effect of radiation intensity on photovoltaic power generation, the relationship between light intensity and current is used:

[0086]

[0087] Among them, I sc is the short-circuit current, G is the current radiation intensity, G ref is the reference radiation intensity.

[0088] The new energy generation model includes: for wind power generation, establishing a model based on wind speed v and output power P w The relationship model is used to calculate the wind power generation power, and the formula is:

[0089]

[0090] Where ρ is the air density, A is the swept area, C p is the power coefficient.

[0091] Combined with the photovoltaic power generation model, calculate the output power P of the solar power generation system solar , the formula is:

[0092]

[0093] Among them, G ref is the reference radiation intensity, P max Indicates the maximum output power of the solar power generation system;

[0094] Special load models include establishing models that take into account time changes, intermittency and load, using time series analysis methods to predict load changes in different time periods, and simulating load start and stop behaviors.

[0095] The distributed energy storage system model includes simulating the working state of the energy storage system under different load conditions through the battery charging and discharging characteristic curve.

[0096] Special load models include establishing models that take into account time changes, intermittency and load, using time series analysis methods to predict load changes in different time periods, and simulating load start and stop behaviors.

[0097] The distributed energy storage system model includes simulating the working state of the energy storage system under different load conditions through the battery charging and discharging characteristic curve.

[0098] Furthermore, the nonlinear characteristics of photovoltaic and wind power generation systems under different environmental and weather conditions are taken into account, so that the simulation model can truly reflect the dynamic performance of the power generation system in actual operation. Compared with the simplified model in the prior art, the present invention can better simulate the complex dynamic response of the power generation system by introducing detailed parameters (such as temperature, radiation intensity, wind speed, etc.) for accurate modeling, solving the problem of difficulty in accurately predicting the output of new energy power generation in traditional power systems.

[0099] It should be noted that the combination of special loads and distributed energy storage systems with the new energy power generation system model enables the simulation environment to simultaneously consider the dynamic changes in power supply and demand and the regulation capacity of the energy storage system. Through the introduction of time series analysis and charge-discharge characteristic curves, the present invention solves the problem of delayed response of the power grid in the face of load fluctuations and instability of new energy power generation, and improves the stability and response speed of the power grid.

[0100] S3: Divide the distribution network into multiple areas, build a hierarchical positioning model, identify and locate different types of faults, and handle and repair the faults through an intelligent dispatching system.

[0101] Construct a distribution network topology model including substations, generation nodes, load nodes and transmission lines, and define the electrical parameters of each node and branch.

[0102] Use the node admittance matrix Y to represent the topological relationship of the system:

[0103] Y=D+jB

[0104] Where D is the conductance matrix, B is the susceptance matrix, and j represents the imaginary unit.

[0105] The photovoltaic power generation model, new energy power generation model, special load model and distributed energy storage system model are integrated into the topological structure model of the distribution network.

[0106] During the simulation, the power balance equation is used to calculate the power distribution of each node:

[0107]

[0108] Among them, P i and Q i are the active power and reactive power of node i, V i and V j The voltages θ at nodes i and j are ij is the phase angle difference between nodes i and j, G ij represents the conductance component between nodes i and j, B ij represents the susceptance component between nodes i and j.

[0109] It should be noted that by constructing a distribution network topology model including substations, power generation nodes, load nodes and transmission lines, the present invention can fully and accurately simulate the operating status of the actual power system. By integrating photovoltaic power generation, new energy power generation, special loads and distributed energy storage system models into the topology model, the present invention can dynamically simulate the interaction of various types of power generation and loads in a unified simulation environment. This integration not only improves the integrity of the simulation system, but also enhances the system's ability to respond to complex situations.

[0110] The distribution network is divided into a layer, which is the fault area location layer. The fault codes of all port nodes in the hierarchical model are read to determine the fault area.

[0111] Compare the rated and measured values ​​of voltage and current to calculate the voltage deviation ΔV of the node i , current deviation ΔI i , the formula is:

[0112] ΔV i =V i,nominal -V i,measured

[0113] ΔI i =I i,nominal -I i,measured

[0114] Among them, V i,nominal and I i,nominal Respectively represent the rated voltage and current of node i, V i,measured and I i,measured represent the measured voltage and current of node i respectively.

[0115] When the voltage deviation of a node is ΔV i Exceeding the set threshold ∈ V , or current deviation ΔI i Exceeding the set threshold ∈ I When the fault codes of multiple adjacent nodes are activated, these nodes are classified into the same area and determined as the fault area.

[0116] The second layer is the fault section location layer, which reads the fault information of the nodes in the fault area of ​​the first layer, locates the section where the fault occurs and determines the fault section.

[0117] For each phase in the fault area, at each node in the area, calculate the positive sequence current I1:

[0118]

[0119] Among them, I a ,I b ,I c They are three-phase currents respectively; a=e J120° is a complex number, indicating a rotation of 120° in phase shift; a 2 =e J240° is a complex number, indicating a rotation of the phase shift 240°; e is a natural number, and J is an imaginary number.

[0120] For each pair of adjacent nodes i and j, calculate the phase angle difference θ of the positive sequence current ij :

[0121] θ ij =∠I 1i -∠I 1j

[0122] Among them, ∠I 1i Represents the phase angle of the positive sequence current I1 at node i, ∠I 1j Represents the phase angle of the positive sequence current I1 at node j.

[0123] When θ ij Exceeding the set threshold ∈ θ , it indicates that the fault is located in the segment between nodes i and j.

[0124] The positive sequence current fault component is used to identify and encode the fault current direction of the regional end node to locate the fault.

[0125] Micro PMU measurement points are set up at the main power outgoing line, distributed power incoming line, large inductive special load incoming line nodes, and multi-branch nodes.

[0126] The positive sequence current information is obtained at the node measurement point, the positive sequence current fault component of the node is calculated, and the fault current direction coding of each node is obtained.

[0127] It should be noted that by dividing the distribution network into multiple areas and constructing a hierarchical positioning model, the present invention can quickly locate faults in complex power systems. This model uses the node admittance matrix and the power balance equation to not only identify the fault area, but also accurately locate the specific section where the fault occurs. By monitoring the voltage and current deviations of the nodes and setting thresholds to judge node faults, this step can quickly and effectively identify the fault area in the power grid. The activation of multi-node fault coding further enhances the reliability and accuracy of fault location. By calculating the phase angle difference of the positive sequence current to further refine the fault location, the fault section can be accurately identified, especially when the fault location is unclear or the fault range is large in the distribution network. Through the calculation of the positive sequence current fault component and the current direction coding, the present invention can further confirm the fault point and accurately locate the fault according to the current direction information. This method can identify anomalies in the positive sequence component and is suitable for processing complex multi-branch power grid structures.

[0128] After the fault section is determined, the intelligent dispatching system automatically performs the isolation operation on the fault section, and isolates the fault section from the normal operating area by cutting off the line switch connected to the fault section; this effectively prevents the spread of the fault and avoids the impact on power supply to other areas. At the same time, the real-time power flow redistribution of the intelligent dispatching system ensures the continuous power supply of non-fault sections.

[0129] When the faulty section is isolated, the intelligent dispatching system redistributes the power flow in the area to ensure that the power supply of the non-faulty sections is not affected; when it is detected that the load of the faulty section needs to be redistributed, the intelligent dispatching system automatically transfers the load of the faulty section to other available power supply sections; when the load transfer cannot meet the demand, the intelligent dispatching system starts the backup power supply to provide emergency power support for high-priority loads; the intelligent dispatching system automatically generates repair instructions based on the type and location of the fault, and the instructions are sent to on-site maintenance personnel through the digital platform to notify them to carry out repairs; when the fault repair begins, the intelligent dispatching system monitors the repair process in real time, collects electrical parameter data, and ensures the effectiveness and safety of the repair operation; when the fault repair is completed, the intelligent dispatching system automatically performs dynamic adjustments to the grid structure, restores the normal power supply path, and optimizes the power flow path; when the repair and reconstruction are completed, the intelligent dispatching system performs self-inspection and debugging to verify the stability of the system after the repair and the normal recovery of all protection measures.

[0130] All operations and data occurring during the troubleshooting process are recorded, providing data support for subsequent analysis and system optimization.

[0131] S4: According to the fault handling results and the adjustment of the energy storage system, the access point location of the new energy power generation system is optimized in real time.

[0132] According to the fault handling results and the adjustment of the energy storage system, the system adjusts the access point location of the new energy power generation system in real time, and connects the power generation unit to the distribution network through a step-up transformer.

[0133] It should be noted that by adjusting the access point location of the new energy power generation system in real time, the present invention can dynamically optimize power distribution according to the actual operation of the power grid and reduce the occurrence of power grid load imbalance. Combining the fault handling results and the adjustment of the energy storage system, the system can make more intelligent access point adjustment decisions to ensure that the power grid structure can be quickly restored and the power transmission path can be optimized after the fault is repaired. The power generation unit is connected to the distribution network through a step-up transformer to ensure voltage matching and system stability during power transmission.

[0134] The above embodiments also include a distribution network access system including a new energy power generation system and special loads, specifically:

[0135] Data acquisition and preprocessing module: collects data and performs preprocessing on nodes and devices in the distribution network.

[0136] Dynamic simulation and modeling module: Establish a photovoltaic power generation model, a new energy power generation model, a special load model, a distributed energy storage model, and build a simulation environment for simulating the dynamic interaction between the new energy power generation system and the distribution network.

[0137] Fault identification and processing module: Divide the distribution network into multiple areas, build a hierarchical positioning model, identify and locate different types of faults, and process and repair the faults through an intelligent dispatching system.

[0138] Access point optimization and control module: optimizes the access point location of the new energy power generation system in real time based on the fault handling results and the adjustment of the energy storage system.

[0139] The computer device may be a server. The computer device includes a processor, a memory, an input / output interface (I / O for short) and a communication interface. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data cluster data of the power monitoring system. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a distribution network access method containing a new energy power generation system and a special load is implemented.

[0140] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0141] Example 2 is an embodiment of the present invention, which provides a distribution network access method including a new energy power generation system and special loads. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation / comparative experiments.

[0142] In order to verify the effectiveness and innovation of the invention, a systematic experiment was conducted, covering the electrical parameter collection, simulation modeling, fault identification and processing, and access point location optimization of distribution network nodes. The experiment was conducted in a simulated distribution network environment, which contains 6 main nodes, each of which represents a different type of power generation or load equipment.

[0143] First, the experimental team deployed high-precision sensors on various nodes and devices in the distribution network to collect key electrical parameters such as voltage, current, and power fluctuations in real time. At the same time, the charging and discharging power data of the energy storage system were also collected, and these data were transmitted to the central control system via a wireless network for unified processing.

[0144] Next, a detailed model of photovoltaic power generation, renewable energy generation, special loads and distributed energy storage systems was built using specialized simulation software, and these models were integrated into a unified simulation environment. The simulation environment can simulate various dynamic interactions, such as changes in light intensity, load fluctuations and faults, to analyze the response and stability of the power system under different conditions.

[0145] In the fault identification and location phase of the experiment, a hierarchical location model was constructed by dividing the distribution network into multiple areas. The voltage deviation, current deviation and other data of each node are monitored in real time. When the deviation of a node exceeds the set threshold, the system automatically activates the fault code and uses the intelligent dispatching system to quickly identify and isolate the fault section. Then, by analyzing the regulation status of the energy storage system, the system automatically optimizes the access point location of the new energy power generation system to ensure the stability and efficiency of the power supply after the fault is handled.

[0146] Finally, the effectiveness of the above process was verified through simulation. In particular, in the face of complex and diverse fault conditions, the system can quickly recover and re-optimize power distribution, significantly improving the stability and response capabilities of the entire distribution network. The specific experimental data are shown in Table 1.

[0147] Table 1 Implementation data table

[0148]

[0149] Through experimental data analysis, the data in the table clearly demonstrates the innovation and practicality of the invention. In the monitoring of voltage and current deviations, it can be seen that the deviation ranges of each node are different. Among them, the voltage deviation and current deviation of node 5 are the largest, reaching 3.8V and 6.3A respectively, which is closely related to its fault type of overload. Compared with the smaller deviations of 0.9V and 1.6A of node 3, the power fluctuation rate of node 5 is also larger, reaching 3.0%. This data performance clearly shows the different responses of each node in the event of a fault, verifying that the hierarchical positioning model can effectively identify and classify different types of faults.

[0150] In addition, the charging and discharging power data of the energy storage system also reflects the important role of the system in fault recovery. For example, nodes 2 and 5 successfully recovered from overload faults at high energy storage outputs of 135kW and 140kW respectively, while node 3 handled the circuit breaker fault at an output of 150kW with more stable power. These data show that the regulation capability of the energy storage system directly affects the efficiency of fault recovery and the overall stability of the power grid.

[0151] Most importantly, the data of fault recovery time demonstrates the advantages of the intelligent dispatching system. Compared with the prior art, the fault recovery time of the nodes in the present invention is generally shorter, especially node 3, which only takes 8 minutes to complete the processing of the circuit breaker fault. Compared with the traditional manual processing method, this method significantly improves efficiency. At the same time, the rapid response of fault processing between nodes also avoids secondary damage caused by fault propagation, further enhancing the reliability of the power grid.

[0152] In summary, the experimental data fully proves the creativity and practicality of the present invention in distribution network fault handling and new energy access optimization. Compared with the prior art, the present invention not only improves the efficiency of fault handling through intelligent and automated system management, but also significantly optimizes the allocation and use of power resources, which has important practical application value.

[0153] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for connecting a distribution network including a new energy power generation system and special loads, characterized in that: include: Collect data at nodes and devices in the distribution network and perform preprocessing; Establish a photovoltaic power generation model, a new energy power generation model, a special load model, and a distributed energy storage model, and build a simulation environment for simulating the dynamic interaction between the new energy power generation system and the distribution network; Divide the distribution network into multiple areas, build a hierarchical positioning model, identify and locate different types of faults, and handle and repair the faults through an intelligent dispatching system; According to the fault handling results and the adjustment of the energy storage system, the access point location of the new energy power generation system is optimized in real time.

2. The method for connecting a distribution network including a new energy power generation system and a special load as claimed in claim 1, characterized in that: The data collection includes voltage data, current data, power data, light intensity data, temperature data, wind speed data, sun angle and radiation energy data; The preprocessing includes data cleaning, missing data processing, feature extraction and data compression.

3. The method for connecting a distribution network including a new energy power generation system and a special load as claimed in claim 2, characterized in that: The photovoltaic power generation model includes using simulation software to build a photovoltaic power generation model and calculate the output voltage V of the photovoltaic cell. The formula is: V=V oc -I·R s Among them, V oc is the open circuit voltage, I is the current, R s is the series resistance; Considering the influence of temperature coefficient α on the performance of photovoltaic cells, the influence of temperature change on power output is calculated. The formula is: P=P max ·[1+α·(T-T ref )] Among them, P max is the maximum power output, T is the current temperature, T ref is the reference temperature; To simulate the nonlinear effect of radiation intensity on photovoltaic power generation, the relationship between light intensity and current is used: Among them, I sc is the short-circuit current, G is the current radiation intensity, G ref is the reference radiation intensity; The new energy generation model includes: for wind power generation, establishing a model based on wind speed v and output power P w The relationship model is used to calculate the wind power generation power, and the formula is: Where ρ is the air density, A is the swept area, C p is the power coefficient; Combined with the photovoltaic power generation model, calculate the output power P of the solar power generation system solar , the formula is: Among them, G ref is the reference radiation intensity, P max Indicates the maximum output power of the solar power generation system; The special load model includes establishing a model that takes into account time variation, intermittency and load, using a time series analysis method to predict changes in loads at different time periods, and simulating the start and stop behavior of loads; The distributed energy storage system model includes simulating the working state of the energy storage system under different load conditions through the battery charging and discharging characteristic curve.

4. The method for connecting a distribution network including a new energy power generation system and a special load as claimed in claim 3, characterized in that: The construction of a simulation environment for simulating the dynamic interaction between a new energy power generation system and a distribution network includes constructing a distribution network topology model including a substation, a power generation node, a load node, and a transmission line, and defining electrical parameters of each node and branch; Use the node admittance matrix Y to represent the topological relationship of the system: Y=D+jB Where D is the conductance matrix, B is the susceptance matrix, and j represents the imaginary unit; Integrate photovoltaic power generation model, new energy power generation model, special load model and distributed energy storage system model into the topological structure model of the distribution network; During the simulation, the power balance equation is used to calculate the power distribution of each node: Among them, P i and Q i are the active power and reactive power of node i, V i and V j The voltages θ at nodes i and j are ij is the phase angle difference between nodes i and j, G ij represents the conductance component between nodes i and j, B ij represents the susceptance component between nodes i and j.

5. The method for connecting a distribution network including a new energy power generation system and a special load as claimed in claim 4, characterized in that: The construction of the hierarchical positioning model includes dividing the distribution network into a layer for locating the fault area, and reading the fault codes of all port nodes in the hierarchical model to determine the fault area; Compare the rated and measured values ​​of voltage and current to calculate the voltage deviation ΔV of the node i , current deviation ΔI i , the formula is: ΔV i =V i,nominal -V i,measured ΔI i =I i,nominal -I i,measured Among them, V i,nominal and I i,nominal Respectively represent the rated voltage and current of node i, V i,measured and I i,measured denote the measured voltage and current of node i respectively; When the voltage deviation of a node is ΔV i Exceeding the set threshold ∈ V , or current deviation ΔI i Exceeding the set threshold ∈ I When the current node is determined to be faulty, the fault code of the node is activated; when the fault codes of multiple adjacent nodes are activated, these nodes are classified into the same area and determined as the fault area; The second layer is the fault section location layer, which reads the fault information of the nodes in the fault area of ​​the first layer, locates the section where the fault occurs and determines the fault section; For each phase in the fault area, at each node in the area, calculate the positive sequence current I1: Among them, I a ,I b ,I c They are three-phase currents respectively; a=e J120° is a complex number, indicating a rotation of 120° in phase shift; a 2 =e J240° is a complex number, indicating a rotation of the phase shift 240; e is a natural number, and J is an imaginary number; For each pair of adjacent nodes i and j, calculate the phase angle difference θ of the positive sequence current ij : i ij =∠I 1i -∠I 1j Among them, ∠I 1i Represents the phase angle of the positive sequence current I1 at node i, ∠I 1j represents the phase angle of the positive sequence current I1 at node j; When θ ij Exceeding the set threshold ∈ θ When , it indicates that the fault is located in the segment between nodes i and j; The positive sequence current fault component is used to identify and encode the fault current direction of the regional end node to locate the fault; Set up micro PMU measurement points at the main power outgoing line, distributed power incoming line, large inductive special load incoming line nodes, and multi-branch nodes; The positive sequence current information is obtained at the node measurement point, the positive sequence current fault component of the node is calculated, and the fault current direction coding of each node is obtained.

6. The method for connecting a distribution network including a new energy power generation system and a special load as claimed in claim 5, characterized in that: The processing and repairing of the fault by the intelligent dispatching system includes that after determining the fault section, the intelligent dispatching system automatically performs an isolation operation on the fault section, and isolates the fault section from the normal operating area by cutting off the line switch connected to the fault section; When the faulty section is isolated, the intelligent dispatching system redistributes the power flow in the area to ensure that the power supply of the non-faulty sections is not affected; When it is detected that the load of the faulty section needs to be redistributed, the intelligent dispatching system automatically transfers the load of the faulty section to other available power supply sections; When load transfer cannot meet demand, the intelligent dispatching system activates the backup power supply to provide emergency power support for high-priority loads; The intelligent dispatching system automatically generates repair instructions based on the fault type and location. The instructions are sent to on-site maintenance personnel through the digital platform to notify them to carry out repairs. When fault repair begins, the intelligent dispatching system monitors the repair process in real time and collects electrical parameter data to ensure the effectiveness and safety of the repair operation; When the fault is repaired, the intelligent dispatching system automatically adjusts the grid structure dynamically, restores the normal power supply path, and optimizes the power flow path; When the repair and reconstruction are completed, the intelligent scheduling system performs self-checking and debugging to verify the stability of the repaired system and the normal recovery of all protection measures; Record all operations and data that occur during the fault handling process.

7. The method for connecting a distribution network including a new energy power generation system and a special load as claimed in claim 6, characterized in that: The real-time optimization of the access point location of the new energy power generation system includes: according to the fault processing result and the adjustment of the energy storage system, the system adjusts the access point location of the new energy power generation system in real time, and connects the power generation unit to the distribution network through a step-up transformer.

8. A distribution network access system including a new energy power generation system and special loads using the method according to any one of claims 1 to 7, characterized in that: Data acquisition and preprocessing module: collects data on nodes and devices in the distribution network and performs preprocessing; Dynamic simulation and modeling module: Establish a photovoltaic power generation model, a new energy power generation model, a special load model, a distributed energy storage model, and build a simulation environment for simulating the dynamic interaction between the new energy power generation system and the distribution network; Fault identification and processing module: divides the distribution network into multiple areas, builds a hierarchical positioning model, identifies and locates different types of faults, and processes and repairs the faults through an intelligent dispatching system; Access point optimization and control module: optimizes the access point location of the new energy power generation system in real time based on the fault handling results and the adjustment of the energy storage system.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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