Intelligent low-voltage power distribution network interconnection control method and system

Abstract

The invention relates to the technical field of power system control, in particular to an intelligent low-voltage power distribution network interconnection control method and system. The method comprises the following steps: collecting low-distribution voltage network region and node data, and preprocessing the data; a low-voltage power distribution network system is divided into a global optimization layer, a regional coordination layer and an equipment control layer, the global optimization layer generates a global optimization instruction, the regional coordination layer realizes power distribution and voltage regulation in a region through a regional controller, the equipment control layer monitors node operation state information in real time and feeds back the information, and the node operation state information is determined based on a state detection result. And making a control strategy. Through the intelligent control and optimization technology, the real-time monitoring and dynamic adjustment of the power distribution network are realized, and the efficient and stable operation of the power grid is ensured. The multi-level control architecture is adopted, the power grid is finely managed on different levels, and the overall performance of the system is improved. The operation efficiency and reliability of a power grid are improved, and the requirements of a modern power system are met.

Description

Technical Field

[0001] The present invention relates to the technical field of power system control, and in particular to an intelligent low-voltage distribution network interconnection control method and system. Background Art

[0002] In modern power systems, low-voltage distribution networks are an important part of the power supply network and undertake the key task of transmitting electricity from substations to end users. With the continuous growth of electricity demand and the widespread application of new energy, traditional low-voltage distribution networks are facing more and more challenges. These challenges include the access of distributed energy, the fluctuation of power load, and the complexity of power grid operation. With the large-scale access of distributed renewable energy such as photovoltaic and wind power, the structure of the distribution network has become more complex, and the flow of power is no longer unidirectional, but has become a bidirectional flow. This has brought new challenges to the dispatching and management of the distribution network. In addition, the randomness and volatility of user-side loads make the load prediction and regulation of the distribution network more difficult, especially during peak load periods, when traditional distribution networks are prone to voltage instability and reduced power supply reliability. In order to meet these challenges, intelligent low-voltage distribution network interconnection control methods and systems have emerged. By introducing advanced control technology and optimization algorithms, intelligent low-voltage distribution networks can achieve dynamic optimization and regulation of distributed energy and loads, and improve the operating efficiency and stability of the system. Through multi-level control strategies, the coordinated work of the global optimization layer, regional coordination layer, and equipment control layer can effectively solve the complexity of distribution network operation and ensure efficient transmission and reliable supply of electricity. Summary of the invention

[0003] In view of the above problems existing in the prior art, the present invention is proposed.

[0004] Therefore, the present invention provides an intelligent low-voltage distribution network interconnection control method, which can solve the problems of traditional distribution networks in dealing with distributed energy access, power load fluctuations and grid operation complexity, and achieve efficient and stable operation of the system through intelligent control and optimization.

[0005] To solve the above technical problems, the present invention provides the following technical solutions: an intelligent low-voltage distribution network interconnection control method, comprising: collecting low-voltage distribution network area and node data, and preprocessing the data; dividing the low-voltage distribution network system into a global optimization layer, a regional coordination layer and a device control layer, the global optimization layer generates global optimization instructions, the regional coordination layer realizes power distribution and voltage regulation within the region through a regional controller, the device control layer monitors the node operation status information in real time and provides feedback, and formulates a control strategy based on the status detection results.

[0006] As a preferred solution of the intelligent low-voltage distribution network interconnection control method described in the present invention, the preprocessing includes using a forward filling method to fill missing values, ensuring the continuity and integrity of the data, converting the timestamp data into a standard date and time format, detecting and processing abnormal values ​​through statistical methods, filtering the data, removing duplicate records in the data set, eliminating data that does not meet the conditions, scaling the numerical data to the same range, and performing data verification.

[0007] As a preferred solution of the intelligent low-voltage distribution network interconnection control method described in the present invention, wherein: the global optimization layer takes minimization of system operation cost as the first-level optimization goal, the system operation cost includes power supply cost, supply and demand adjustment cost and maintenance cost, and the objective function formula is expressed as:

[0008]

[0009] Among them, C P The cost of powering the system, C Q is the system load adjustment cost, C M is the system operation and maintenance cost, N r To optimize the number of control regions, r is the region index, min is the minimization function, C sys is the system operating cost, C O is the communication and control cost of the regional coordination layer, C M The maintenance and operating costs of the equipment;

[0010] The objective function is decomposed into a matrix form, and the formula is expressed as follows:

[0011]

[0012] in, is the state matrix of the system operation, is the operating cost vector of the coordination layer in each region at time t, and T is the transpose of the matrix.

[0013] As a preferred solution of the intelligent low-voltage distribution network interconnection control method described in the present invention, the regional coordination layer is an optimization control layer, which realizes power distribution and voltage regulation in the region through the regional controller, receives instructions from the global optimization layer, and makes adjustments according to the real-time power demand and supply situation in the region. The regional controller regularly updates the operation plan and adjusts the operation status to maintain system stability;

[0014] When the distribution network is running, operating constraints and coupling relationships are considered, wherein the constraints include power balance constraints and voltage constraints;

[0015] The power balance constraint formula is expressed as:

[0016]

[0017] Among them, P gen,r (t), P load,r (t0 is the power generation power and load power of the rth region respectively;

[0018] The voltage constraint formula is expressed as,

[0019] U min ≤U r (t)≤U max

[0020] Among them, U min , U max are the upper and lower limits of voltage, U r (t0 is the voltage of the rth region;

[0021] The equipment operation constraint formula is expressed as:

[0022]

[0023] in, are the minimum and maximum power generation of the power generation equipment in the rth area respectively;

[0024] The gradient descent method and Lagrange multiplier method optimization algorithm are used to solve the objective function and constraints to achieve power optimization allocation.

[0025] The gradient descent method formula is expressed as:

[0026]

[0027] Among them, θ is the power allocation parameter to be optimized, α is the learning rate, is the gradient;

[0028] The Lagrange multiplier method formula is expressed as,

[0029]

[0030] Where λ is the Lagrange multiplier, is the Lagrangian function;

[0031] By solving The condition that the partial derivative of is zero is used to obtain the optimal solution.

[0032] As a preferred solution of the intelligent low-voltage distribution network interconnection control method described in the present invention, the device control layer is an execution control layer, which realizes the control target through an intelligent controller arranged at the device interface position, converts the instructions of the global optimization layer and the regional coordination layer into device-level control instructions, executes power distribution and voltage regulation, and the device control layer monitors the operation status information of the node in real time and generates a control strategy;

[0033] Calculate the deviation between the actual value and the target value of voltage and frequency. The formula is:

[0034]

[0035] Among them, ΔU i (t), Δf i (t) are the actual value deviations of the voltage and frequency at node i at time t, respectively;

[0036] If |ΔU i (t)|≤ΔU th And |Δf i (t)|≤Δf th , the system determines that the node is in a normal state;

[0037] If |ΔU i (t)|>ΔU th or |Δf i (t)|>Δf th , the system determines that the node is in a state of waiting for maintenance;

[0038] If |ΔU i (t)|>ΔU th And |Δf i (t)|>Δf th , the system determines that the node is in an abnormal state;

[0039] Among them, ΔU th , Δf th are the deviation thresholds for voltage and frequency respectively.

[0040] As a preferred solution of the intelligent low-voltage distribution network interconnection control method described in the present invention, wherein: the control strategy includes each distributed generation unit being a voltage source, and adopting a secondary power optimization control strategy, including droop control and voltage and current dual-loop control;

[0041] The droop control formula is expressed as,

[0042]

[0043] Among them, f i , U i are the actual frequency and actual voltage of node i, Pi , Q i are the actual active and reactive power of node i, respectively, P , k Q For different control parameters, are the rated reference frequency and rated reference voltage of the i-th node respectively;

[0044] The voltage and current dual-loop control formula is expressed as:

[0045]

[0046] in, is the target current of the d-axis, is the target voltage of the d-axis, k di is the current inner loop control gain, k du is the current outer loop control gain, U d,ref is the d-axis voltage reference value, i d,ref is the d-axis current reference value, U d 、i d are the actual values ​​of voltage and current on the d-axis respectively.

[0047] As a preferred solution of the intelligent low-voltage distribution network interconnection control method described in the present invention, wherein: the secondary power optimization control strategy considers adjusting the error value of voltage and frequency, and adopts a distributed algorithm of discrete time signals to improve the secondary power optimization control;

[0048] According to the droop control relationship, the voltage and frequency rated reference quantities in the secondary power optimization control are divided into three mathematical formulas: normal state optimization, maintenance state optimization, and abnormal state optimization;

[0049] If the node is in a normal state, the voltage rated reference quantity in the secondary power optimization control and frequency rated reference The calculation formula is,

[0050]

[0051] in, is the time step, n is the time step index, α U , β U are different voltage control adjustment parameters, α f , β f Different frequency control adjustment parameters are provided. is the reactive power adjustment factor, is the active power adjustment factor, and are the adjustment amounts of voltage and frequency respectively;

[0052] If the node is in the maintenance state, the voltage rated reference quantity in the secondary power optimization control and frequency rated reference The calculation formula is,

[0053]

[0054] Among them, γ U is the voltage control adjustment parameter in the maintenance state, γ f Frequency control adjustment parameters for the maintenance state;

[0055] The calculation formula of the adjustment parameters in the maintenance state is expressed as:

[0056]

[0057] If the node is in an abnormal state, the voltage rating reference and frequency rated reference The calculation formula is,

[0058]

[0059] Among them, δ U ,δ f are the voltage and frequency regulation coefficients under abnormal conditions, ΔQ i , ΔP i They are the abnormal changes of reactive power and active power respectively;

[0060] The calculation formula of abnormal adjustment coefficient is expressed as:

[0061]

[0062] According to the droop control relationship, the voltage and frequency adjustment is obtained, and the formula is expressed as:

[0063]

[0064] Among them, f c is the cutoff frequency of the low-pass filter, are the target values ​​for reactive power and active power respectively.

[0065] Another object of the present invention is to provide an intelligent low-voltage distribution network interconnection control system to solve the problems of traditional distribution networks in terms of distributed energy access, power load fluctuations and complexity of power grid operation. Through intelligent control and optimization technology, real-time monitoring and dynamic adjustment of the distribution network are realized to ensure efficient and stable operation of the power grid. The present invention adopts a multi-level control architecture of a global optimization layer, a regional coordination layer and a device control layer to finely manage the power grid at different levels and improve the overall performance of the system. The global optimization layer generates global optimization instructions, the regional coordination layer makes adjustments based on real-time power demand and supply conditions, and the device control layer monitors the node operating status in real time and provides feedback to ensure the stable operation of each node. Advanced data processing and optimization algorithms improve the response speed and decision-making accuracy of the system. By constructing an intelligent and optimized low-voltage distribution network control system, the present invention improves the operating efficiency and reliability of the power grid to meet the needs of modern power systems.

[0066] As a preferred solution of the intelligent low-voltage distribution network interconnection control system described in the present invention, it includes: a preprocessing module, a global optimization layer module, a regional coordination layer module and a device control layer module;

[0067] The preprocessing module collects low-voltage distribution network data and performs data cleaning, format conversion, outlier processing and data standardization to ensure the continuity, integrity and accuracy of the data;

[0068] The global optimization layer module optimizes system operation costs, generates global optimization instructions, and guides power allocation and voltage regulation in the regional coordination layer;

[0069] The regional coordination layer module receives global optimization instructions through the regional controller, performs power allocation and voltage regulation within the region, and adjusts the operating status in real time to maintain the stability and efficiency of the system;

[0070] The device control layer module executes power allocation and voltage regulation instructions, monitors the operating status of each device in real time, calculates deviations and provides feedback, and formulates control strategies based on actual conditions to ensure the normal operation of the equipment and the stability of the system.

[0071] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and is characterized in that when the processor executes the computer program, the steps of any one of the methods described in an intelligent low-voltage distribution network interconnection control method are implemented.

[0072] 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 any one of the methods described in an intelligent low-voltage distribution network interconnection control method are implemented.

[0073] Beneficial effects of the present invention: The intelligent low-voltage distribution network interconnection control method of the present invention improves the operating efficiency and stability of the distribution network. Integrate distributed energy, dynamically optimize resource allocation, and ensure the continuity and reliability of power supply. Through real-time monitoring and data preprocessing technology, the method of the present invention can timely capture and analyze the operating status of the power grid, quickly respond to load fluctuations and abnormal conditions, and reduce voltage fluctuations and frequency deviations. The multi-level control architecture, including the global optimization layer, the regional coordination layer, and the equipment control layer, work together to optimize the overall operation of the power grid and finely manage the operating status of each node. Enable the intelligent low-voltage distribution network to better adapt to the development needs of the modern power system and provide more reliable and efficient power services. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0075] Figure 1 A schematic flow chart of an intelligent low-voltage distribution network interconnection control method provided for one embodiment of the present invention.

[0076] Figure 2 A module diagram of an intelligent low-voltage distribution network interconnection control system provided for one embodiment of the present invention. DETAILED DESCRIPTION

[0077] 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 drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. 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.

[0078] Example 1, reference Figure 1 , which is the first embodiment of the present invention, and provides an intelligent low-voltage distribution network interconnection control method, comprising:

[0079] S1: Collect low-voltage grid area and node data and pre-process the data.

[0080] It should be noted that the data collected from the low-voltage network area and nodes include real-time operating status information such as voltage, current, and power of each node in the area. Load data includes the load status and change trend of each node. Timestamp data is used for time synchronization and recording of data. System operating status information includes equipment operating status information, real-time monitoring of the operating status of each node equipment, the actual value of voltage and frequency and its deviation from the target value, and the execution of power distribution and voltage regulation.

[0081] The preprocessing includes using a forward filling method to fill missing values, ensuring the continuity and integrity of the data, converting timestamp data into a standard date and time format, detecting and processing outliers through statistical methods, filtering data, removing duplicate records in the data set, eliminating data that does not meet the conditions, scaling numerical data to the same range, and performing data verification.

[0082] S2: The low-voltage distribution network system is divided into a global optimization layer, a regional coordination layer, and an equipment control layer. The global optimization layer generates global optimization instructions. The regional coordination layer implements power distribution and voltage regulation within the region through regional controllers. The equipment control layer monitors the node operation status information in real time and provides feedback. Based on the status detection results, a control strategy is formulated.

[0083] It should be noted that the global optimization layer is the highest layer of the system and is responsible for the optimization control of the entire power grid. Its main optimization goal is to minimize the system operating cost, including power supply cost, load adjustment cost and maintenance cost. The global optimization layer generates global optimization instructions by solving the objective function to guide the power allocation and voltage regulation of each regional coordination layer. It regularly updates the optimization plan and makes adjustments based on the real-time operation of the power grid to ensure the efficiency and stability of the overall system.

[0084] The objective function formula is expressed as:

[0085]

[0086] Among them, C P The cost of powering the system, C Q is the system load adjustment cost, C M is the system operation and maintenance cost, N r To optimize the number of control regions, r is the region index, min is the minimization function, C sys is the system operating cost, C O is the communication and control cost of the regional coordination layer, C M The maintenance and operating costs of the equipment;

[0087] The objective function is decomposed into a matrix form, and the formula is expressed as follows:

[0088]

[0089] in, is the state matrix of the system operation, is the operating cost vector of the coordination layer in each region at time t, and T is the transpose of the matrix.

[0090] The global optimization layer generates global optimization instructions, which include power allocation, voltage set points, and frequency set points for each zone.

[0091] It should be noted that the regional coordination layer is between the global optimization layer and the equipment control layer. It is an intermediate layer responsible for the specific optimization control in each region. Each region has a regional controller, which is responsible for receiving instructions from the global optimization layer and performing power distribution and voltage regulation according to the actual power demand and supply in the region. Real-time monitoring of the operating status of distributed energy and loads in each region, collecting data such as voltage, current, and power. Feedback real-time monitoring data to the global optimization layer for analysis and adjustment of global strategies to ensure stable operation of the power grid in the region. In the event of an abnormal situation, the regional controller can respond quickly and adjust the operating status to maintain the stability of the system.

[0092] When the distribution network is running, operating constraints and coupling relationships are considered, wherein the constraints include power balance constraints and voltage constraints;

[0093] The power balance constraint formula is expressed as:

[0094]

[0095] Among them, P gen,r (t), P load,r (t) are the power generation and load power of the rth region respectively;

[0096] The voltage constraint formula is expressed as,

[0097] U min ≤U r (t)≤U max

[0098] Among them, U min , U max are the upper and lower limits of voltage, U r (t) is the voltage of the rth region;

[0099] The equipment operation constraint formula is expressed as:

[0100]

[0101] in, are the minimum and maximum power generation of the power generation equipment in the rth area respectively;

[0102] The gradient descent method and Lagrange multiplier method optimization algorithm are used to solve the objective function and constraints to achieve power optimization allocation.

[0103] The gradient descent method formula is expressed as:

[0104]

[0105] Among them, θ is the power allocation parameter to be optimized, α is the learning rate, is the gradient;

[0106] The Lagrange multiplier method formula is expressed as,

[0107]

[0108] Where λ is the Lagrange multiplier, is the Lagrangian function;

[0109] By solving The partial derivative of is zero, and the optimal solution is obtained, which can achieve the system operation cost C sys is minimized and the power balance constraints are met.

[0110] It should be noted that the device control layer is the bottom layer of the system and is responsible for the control and execution of specific devices. The intelligent controller is installed at the device interface and is responsible for converting the instructions of the global optimization layer and the regional coordination layer into specific control instructions at the device level, and executing power distribution and voltage regulation. The device control layer monitors the operating status information of each device in real time, such as voltage, current, power, frequency, etc., and provides feedback. It can not only realize the independent operation of the equipment, but also exchange information with neighboring devices, dynamically adjust the operating status of the equipment according to the operating requirements of the power grid, and perform distributed coordinated control;

[0111] Calculate the deviation between the actual value and the target value of voltage and frequency. The formula is:

[0112]

[0113] Among them, ΔU i (t), Δf i (t) are the actual value deviations of the voltage and frequency at node i at time t, respectively;

[0114] If |ΔU i (t)|≤ΔU th And |Δf i (t)|≤Δf th , the system determines that the node is in a normal state;

[0115] If |ΔU i (t)|>ΔUth or |Δf i (t)|>Δf th , the system determines that the node is in a state of waiting for maintenance;

[0116] If |ΔU i (t)|>ΔU th And |Δf i (t)|>Δf th , the system determines that the node is in an abnormal state;

[0117] Among them, ΔU th , Δf th are the deviation thresholds for voltage and frequency respectively.

[0118] Furthermore, the control strategy includes each distributed generation unit being approximately a voltage source, and adopting a two-level power optimization control strategy, including droop control and voltage-current dual-loop control;

[0119] The droop control formula is expressed as,

[0120]

[0121] Among them, f i , U i are the actual frequency and actual voltage of node i, P i , Q i are the actual active and reactive power of node i, respectively, P , k Q For different control parameters, are the rated reference frequency and rated reference voltage of the i-th node respectively;

[0122] The voltage and current dual-loop control formula is expressed as:

[0123]

[0124] in, is the target current of the d-axis, is the target voltage of the d-axis, k di is the current inner loop control gain, k du is the current outer loop control gain, U d,ref is the d-axis voltage reference value, i d,ref is the d-axis current reference value, U d 、i d are the actual values ​​of voltage and current on the d-axis respectively.

[0125] Furthermore, the secondary power optimization control strategy considers adjusting the error value of voltage and frequency and adopts a distributed algorithm of discrete time signal to improve the secondary power optimization control. k,t k+1 ] is the time spent on each iteration of the distributed algorithm, which can be divided into N time intervals.

[0126] [t0,t1],[t1,t2],…,[t N-1 ,t N ]

[0127] Among them, t represents the current time point and is usually used to describe continuous time variables, for example, t k is the start time of the current iteration, t k+1 The time for the next iteration.

[0128] According to the droop control relationship, the voltage and frequency rated reference quantities in the secondary power optimization control are divided into three mathematical formulas: normal state optimization, maintenance state optimization, and abnormal state optimization;

[0129] If the node is in a normal state, the voltage rated reference quantity in the secondary power optimization control and frequency rated reference The calculation formula is,

[0130]

[0131] in, is the time step, n is the time step index, α U , β U are different voltage control adjustment parameters, α f , β f Different frequency control adjustment parameters are provided. is the reactive power adjustment factor, is the active power adjustment factor, and are the adjustment amounts of voltage and frequency respectively;

[0132] If the node is in the maintenance state, the voltage rated reference quantity in the secondary power optimization control and frequency rated reference The calculation formula is,

[0133]

[0134] Among them, γ U is the voltage control adjustment parameter in the maintenance state, γ f Frequency control adjustment parameters for the maintenance state;

[0135] The calculation formula of the adjustment parameters in the maintenance state is expressed as:

[0136]

[0137] If the node is in an abnormal state, the voltage rating reference and frequency rated reference The calculation formula is,

[0138]

[0139] Among them, δ U ,δ f are the voltage and frequency regulation coefficients under abnormal conditions, ΔQ i , ΔP i They are the abnormal changes of reactive power and active power respectively;

[0140] The calculation formula of abnormal adjustment coefficient is expressed as:

[0141]

[0142] According to the droop control relationship, the voltage and frequency adjustment is obtained, and the formula is expressed as:

[0143]

[0144] Among them, f c is the cutoff frequency of the low-pass filter, are the target values ​​for reactive power and active power respectively.

[0145] The control strategy of the device control layer also includes:

[0146] If the node is in a normal state, the execution strategy of the device control layer is to ensure that the device operates in the optimal state and maintain the stability and efficiency of the system. Collect the operating data of the equipment in real time, use the intelligent controller to analyze the operating data, and ensure that the equipment is within the preset normal operating range. Receive optimization instructions from the regional control layer and the global optimization layer, such as power allocation and voltage set values. Perform secondary power optimization control for the normal state of the node, adjust the equipment operating parameters to comply with the optimization instructions, so as to minimize the system operating cost. Calibrate the equipment regularly to ensure the accuracy of sensors and controllers. Routine maintenance, such as cleaning, lubrication, and replacement of wearing parts, to extend the life of the equipment. Feedback the real-time operating data and status information of the equipment to the regional control layer and the global optimization layer. Provide detailed operation reports, including power output, energy efficiency, and equipment health status.

[0147] If the node is in the state of pending maintenance, monitor the key parameters of the equipment in real time to evaluate the health status and remaining life of the equipment. According to the health status of the equipment, predict the maintenance needs of the equipment and arrange the maintenance plan in advance. Arrange routine maintenance and preventive maintenance of the equipment according to the preset maintenance plan. During the maintenance period, according to the instructions of the regional control layer, adjust the operation strategy of the equipment, perform the secondary power optimization control of the state of pending maintenance, reduce the equipment load or switch to the backup equipment to ensure the stable operation of the system. When necessary, temporarily stop the operation of the equipment for thorough maintenance and inspection. Record the work content, problems found and measures taken for each maintenance in detail. Update the maintenance history of the equipment as a reference for subsequent optimization and health management. Feedback the equipment status during maintenance, maintenance work and equipment status after maintenance to the regional control layer and the global optimization layer. Provide maintenance reports, including the content of maintenance work, problems found and health assessment results of the equipment.

[0148] If a node is in an abnormal state, use an intelligent controller to monitor device parameters in real time, identify abnormal signals and fault warnings. Classify and evaluate the severity of abnormal situations through preset thresholds and models. Immediately issue an alarm signal to notify the regional control layer and the global optimization layer. If the abnormal situation may affect the stability of the system, quickly isolate the faulty equipment to prevent the spread of the fault. According to the instructions of the regional control layer and the global optimization layer, adjust the operation strategy, perform secondary power optimization control of the abnormal state, reduce the equipment load or switch to backup equipment. Record detailed fault information, analyze the cause of the abnormality and the scope of impact. Arrange for rapid repair or replacement of the faulty equipment according to the type and severity of the fault. Feedback the abnormal detection results, fault handling process and current status of the equipment to the regional control layer and the global optimization layer. Provide fault reports and repair records to support subsequent optimization and maintenance decisions.

[0149] Through hierarchical control of the global optimization layer, regional coordination layer and equipment control layer, the system can realize intelligent management and dynamic optimization and adjustment of the low-voltage distribution network, ensuring the efficiency and stability of the power grid under various operating conditions.

[0150] The above is a schematic scheme of an intelligent low-voltage distribution network interconnection control method of this embodiment. It should be noted that the technical scheme of the intelligent low-voltage distribution network interconnection control system and the technical scheme of the above-mentioned intelligent low-voltage distribution network interconnection control method belong to the same concept. The details of the technical scheme of the intelligent low-voltage distribution network interconnection control system in this embodiment that are not described in detail can all be referred to the description of the technical scheme of the above-mentioned intelligent low-voltage distribution network interconnection control method.

[0151] In this embodiment, the intelligent low-voltage distribution network interconnection control system includes: a preprocessing module, a global optimization layer module, a regional coordination layer module and a device control layer module;

[0152] The preprocessing module collects low-voltage distribution network data and performs data cleaning, format conversion, outlier processing and data standardization to ensure the continuity, integrity and accuracy of the data;

[0153] The global optimization layer module optimizes system operation costs, generates global optimization instructions, and guides power allocation and voltage regulation in the regional coordination layer;

[0154] The regional coordination layer module receives global optimization instructions through the regional controller, performs power allocation and voltage regulation within the region, and adjusts the operating status in real time to maintain the stability and efficiency of the system;

[0155] The device control layer module executes power allocation and voltage regulation instructions, monitors the operating status of each device in real time, calculates deviations and provides feedback, and formulates control strategies based on actual conditions to ensure the normal operation of the equipment and the stability of the system.

[0156] The above-mentioned unit modules may be embedded in or independent of the processor in the computer device in the form of hardware, or may be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above-mentioned modules.

[0157] This embodiment also provides a computing device suitable for the interconnection control of intelligent low-voltage distribution networks, including: the present invention can be implemented with the help of software and necessary general-purpose hardware, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ReadOnly, Memory, ROM), random access memory (RandomAccess Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods of various embodiments of the present invention.

[0158] Embodiment 2, the second embodiment of the present invention, provides an intelligent low-voltage distribution network interconnection control method. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through experiments.

[0159] In order to verify the effectiveness of the intelligent low-voltage distribution network interconnection control method under different conditions, the operating efficiency and stability of the system under different loads and distributed energy access conditions are evaluated, and the performance differences of the system before and after the application of the intelligent control strategy are compared.

[0160] In the same scenario, we use our technical solution and traditional technical solution to conduct data testing. The experimental scenario settings are as follows:

[0161] (1) Normal state: simulates a scenario with stable load, with voltage and frequency within the allowable range. Evaluates the operating efficiency and stability of the system under normal conditions.

[0162] (2) Abnormal state: Simulate the scenario of sudden load increase or distributed energy fluctuation, causing the voltage and frequency to deviate from the set value. Evaluate the response speed and adjustment ability of the system under abnormal conditions.

[0163] (3) Maintenance waiting state: Simulates the scenario of equipment aging or fault warning, with certain fluctuations in voltage and frequency. Evaluates the stability and maintenance effect of the system in the maintenance waiting state.

[0164] The results of the simulation experiment are shown in Table 1.

[0165] Table 1. Data comparison table

[0166]

[0167] Under normal conditions, the voltage and frequency deviations controlled by the present invention are significantly smaller than those of the traditional solution, and the system runs more stably. The operating cost of the present invention is reduced by 200 yuan compared with the traditional solution, which reflects the optimization effect. The equipment utilization rate of the present invention reaches 95%, which is significantly higher than the 85% of the traditional solution.

[0168] Under abnormal conditions, the present invention can more effectively control voltage and frequency deviations and maintain system stability. The response time of the present invention is 2 seconds, indicating that the present invention is faster than the traditional solution in handling abnormal conditions. The operating cost of the adjusted system is reduced by 200 yuan compared with the traditional solution, indicating that the present invention is more efficient in handling abnormal conditions. The equipment utilization rate of the present invention is 90%, which is higher than the 80% of the traditional solution, indicating that the equipment is more efficient in operating under abnormal conditions.

[0169] In the state of waiting for maintenance, the voltage and frequency deviation of the present invention in the state of waiting for maintenance is smaller than that of the traditional solution, and the maintenance effect is better. The annual maintenance times of the present invention are 5 times, which is much less than 10 times of the traditional solution, indicating that the present invention is more efficient in equipment management and maintenance.

[0170] Through simulation experiments and data comparison, the superiority of the present invention in different states is further verified. Whether in normal, abnormal or maintenance state, the present invention shows higher stability, faster response speed, lower operating cost and higher equipment utilization. These results prove that the intelligent low-voltage distribution network interconnection control method of the present invention has significant superiority and can effectively improve the operating efficiency and reliability of the power grid system.

[0171] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. 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. An intelligent low-voltage distribution network interconnection control method, characterized in that: include, Collect low-voltage grid area and node data and pre-process the data; The low-voltage distribution network system is divided into a global optimization layer, a regional coordination layer and a device control layer. The global optimization layer generates global optimization instructions. The regional coordination layer realizes power distribution and voltage regulation within the region through the regional controller. The device control layer monitors the node operation status information in real time and provides feedback. Based on the status detection results, a control strategy is formulated.

2. The intelligent low-voltage distribution network interconnection control method according to claim 1, characterized in that: The preprocessing includes using a forward filling method to fill missing values, ensuring the continuity and integrity of the data, converting timestamp data into a standard date and time format, detecting and processing outliers through statistical methods, filtering data, removing duplicate records in the data set, removing data that does not meet the conditions, scaling numerical data to the same range, and performing data verification.

3. An intelligent low-voltage distribution network interconnection control method as claimed in claim 2, characterized in that: The global optimization layer takes minimizing the system operation cost as the first-level optimization goal. The system operation cost includes power supply cost, supply and demand adjustment cost and maintenance cost. The objective function formula is expressed as: Among them, C P The cost of powering the system, C Q is the system load adjustment cost, C M is the system operation and maintenance cost, N r To optimize the number of control regions, r is the region index, min is the minimization function, C sys is the system operating cost, C O is the communication and control cost of the regional coordination layer, C M The maintenance and operating costs of the equipment; The objective function is decomposed into a matrix form, and the formula is expressed as follows: in, is the state matrix of the system operation, is the operating cost vector of the coordination layer in each region at time t, and T is the transpose of the matrix.

4. The intelligent low-voltage distribution network interconnection control method according to claim 3, characterized in that: The regional coordination layer is an optimization control layer, which implements power allocation and voltage regulation in the region through the regional controller, receives instructions from the global optimization layer, and makes adjustments based on the real-time power demand and supply in the region. The regional controller regularly updates the operation plan and adjusts the operation status to maintain system stability. When the distribution network is running, operating constraints and coupling relationships are considered, wherein the constraints include power balance constraints and voltage constraints; The power balance constraint formula is expressed as: Among them, P gen,r (t), P load,r (t) are the power generation and load power of the rth region respectively; The voltage constraint formula is expressed as, U min ≤U r (t)≤U max Among them, U min , U max are the upper and lower limits of voltage, U r (t) is the voltage of the rth region; The equipment operation constraint formula is expressed as: in, are the minimum and maximum power generation of the power generation equipment in the rth area respectively; the gradient descent method and Lagrange multiplier method optimization algorithm are used to solve the objective function and constraint conditions to achieve power optimization allocation. The gradient descent method formula is expressed as: Among them, θ is the power allocation parameter to be optimized, α is the learning rate, is the gradient; The Lagrange multiplier method formula is expressed as, Where λ is the Lagrange multiplier, is the Lagrangian function; By solving The condition that the partial derivative of is zero is used to obtain the optimal solution.

5. An intelligent low-voltage distribution network interconnection control method as claimed in claim 4, characterized in that: The device control layer is an execution control layer, which realizes the control target through the intelligent controller set at the device interface position, converts the instructions of the global optimization layer and the regional coordination layer into device-level control instructions, executes power allocation and voltage regulation, and monitors the operation status information of the node in real time and generates a control strategy; Calculate the deviation between the actual value and the target value of voltage and frequency. The formula is: Among them, ΔU i (t), Δf i (t) are the actual value deviations of the voltage and frequency at node i at time t, respectively; If |ΔU i (t)|≤ΔU th And |Δf i (t)|≤Δf th , the system determines that the node is in a normal state; If |ΔU i (t)|>ΔU th or |Δf i (t)|>Δf th , the system determines that the node is in a state of waiting for maintenance; If |ΔU i (t)|>ΔU th And |Δf i (t)|>Δf th , the system determines that the node is in an abnormal state; Among them, ΔU th , Δf th are the deviation thresholds for voltage and frequency respectively.

6. An intelligent low-voltage distribution network interconnection control method as claimed in claim 5, characterized in that: The control strategy includes each distributed generation unit being a voltage source, and adopting a two-level power optimization control strategy, including droop control and voltage-current dual-loop control; The droop control formula is expressed as, Among them, f i , U i are the actual frequency and actual voltage of node i, P i , Q i are the actual active and reactive power of node i, respectively, P , k Q For different control parameters, are the rated reference frequency and rated reference voltage of the i-th node respectively; The voltage and current dual-loop control formula is expressed as: in, is the target current of the d-axis, is the target voltage of the d-axis, k di is the current inner loop control gain, k du is the current outer loop control gain, U d,ref is the d-axis voltage reference value, i d,ref is the d-axis current reference value, U d 、i d are the actual values ​​of voltage and current on the d-axis respectively.

7. An intelligent low-voltage distribution network interconnection control method as claimed in claim 6, characterized in that: The secondary power optimization control strategy considers adjusting the error values ​​of voltage and frequency and adopts a distributed algorithm of discrete time signals to improve the secondary power optimization control; According to the droop control relationship, the voltage and frequency rated reference quantities in the secondary power optimization control are divided into three mathematical formulas: normal state optimization, maintenance state optimization, and abnormal state optimization; If the node is in a normal state, the voltage rated reference quantity in the secondary power optimization control and frequency rated reference The calculation formula is, in, is the time step, n is the time step index, α U , β U are different voltage control adjustment parameters, α f , β f Different frequency control adjustment parameters are provided. is the reactive power adjustment factor, is the active power adjustment factor, and are the adjustment amounts of voltage and frequency respectively; If the node is in the maintenance state, the voltage rated reference quantity in the secondary power optimization control and frequency rated reference The calculation formula is, Among them, γ U is the voltage control adjustment parameter in the maintenance state, γ f Frequency control adjustment parameters for the maintenance state; The calculation formula of the adjustment parameters in the maintenance state is expressed as: If the node is in an abnormal state, the voltage rating reference and frequency rated reference The calculation formula is, Among them, δ U ,δ f are the voltage and frequency regulation coefficients under abnormal conditions, ΔQ i , ΔP i They are the abnormal changes of reactive power and active power respectively; The calculation formula of abnormal adjustment coefficient is expressed as: According to the droop control relationship, the voltage and frequency adjustment is obtained, and the formula is expressed as: Among them, f c is the cutoff frequency of the low-pass filter, are the target values ​​for reactive power and active power respectively.

8. A system based on the intelligent low-voltage distribution network interconnection control method according to any one of claims 1 to 7, characterized in that: It includes preprocessing module, global optimization layer module, regional coordination layer module and equipment control layer module; The preprocessing module collects low-voltage distribution network data and performs data cleaning, format conversion, outlier processing and data standardization to ensure the continuity, integrity and accuracy of the data; The global optimization layer module optimizes system operation costs, generates global optimization instructions, and guides power allocation and voltage regulation in the regional coordination layer; The regional coordination layer module receives global optimization instructions through the regional controller, performs power allocation and voltage regulation within the region, and adjusts the operating status in real time to maintain the stability and efficiency of the system; The device control layer module executes power allocation and voltage regulation instructions, monitors the operating status of each device in real time, calculates deviations and provides feedback, and formulates control strategies based on actual conditions to ensure the normal operation of the equipment and the stability of the 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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