Power distribution network regulation method and device and power distribution network

Abstract

The application discloses a power distribution network adjusting method and device and a power distribution network, and belongs to the technical field of electric power control. The method comprises the following steps: acquiring power distribution network topology structure information and power distribution network operation constraint information; performing primary optimization according to a first target function, the power distribution network topology structure information and the power distribution network operation constraint information, and obtaining a primary optimization result; predicting a current flowing through a branch at a next moment according to the primary optimization result; optimizing a switch state of an internal converter of the power distribution network according to a second target function, the current flowing through the branch, a current reference value and a three-phase imbalance degree by using an optimization algorithm, and taking the switch state as a secondary optimization result; and adjusting the switch state of the internal converter of the power distribution network according to the secondary optimization result, so as to adjust the current flowing through the branch of the power distribution network. By the application, line loss and voltage deviation can be effectively reduced, and three-phase imbalance of the power distribution network can be effectively inhibited.

Description

Technical Field

[0001] This invention relates to a distribution network regulation method, device, and distribution network, belonging to the field of power control technology. Background Technology

[0002] With the advancement of new power system construction, medium-voltage distribution networks, as a crucial link in energy consumption and power supply security, face higher requirements for operational safety, economy, and stability. Loop operation, as an important way to improve the reliability of power supply and the flexibility of load transfer in distribution networks, presents new challenges to the control accuracy, response speed, and global optimization capabilities of core power conversion and compensation units. Maintaining low-loss, low-deviation, and low-imbalance operation under complex conditions has become one of the core requirements for current distribution network upgrades.

[0003] In real-world scenarios where distributed power output fluctuations are intensifying and three-phase load changes are becoming increasingly drastic, the traditional closed-loop operation mode of medium-voltage distribution networks is gradually revealing significant shortcomings. The traditional mode relies on fixed-capacity compensation devices or centralized converters, leading to problems such as high line losses, large voltage deviations, and high three-phase imbalance during distribution network operation, making it difficult to adapt to the complex operating characteristics of new distribution networks.

[0004] Existing research on loop control in medium-voltage distribution networks also has limitations. It often focuses solely on suppressing peak loop current or reducing the number of switching operations, failing to achieve multi-period global coordination and real-time dynamic adjustment. This results in redundant compensation capacity, increased system operating losses, and a continued worsening of three-phase imbalance, ultimately failing to guarantee power supply continuity. Therefore, developing an operational optimization control method and device that balances multi-period global optimization and real-time dynamic adjustment, while simultaneously reducing line losses, voltage deviations, and three-phase imbalance, has become a critical issue urgently needing to be addressed. Summary of the Invention

[0005] To solve the above-mentioned technical problems, or at least partially solve them, the present invention provides a power distribution network regulation method, apparatus, and power distribution network.

[0006] The technical solution of this invention is:

[0007] According to a first aspect of the present invention, a distribution network regulation method is provided, comprising: acquiring distribution network topology information and distribution network operation constraint information; performing a first optimization based on a first objective function, the distribution network topology information, and the distribution network operation constraint information to obtain a first optimization result; predicting the current flowing through the branch at the next moment based on the first optimization result; optimizing the switching state of the converters inside the distribution network using an optimization algorithm based on a second objective function, the current flowing through the branch, the current reference value, and the three-phase imbalance, as a second optimization result; and adjusting the switching state of the converters inside the distribution network based on the second optimization result to adjust the current flowing through the distribution network branches.

[0008] Further, the step of performing a primary optimization based on the first objective function, distribution network topology information, and distribution network operation constraint information to obtain a primary optimization result includes: constructing the first objective function; calculating the line network loss value in the first objective function based on the current flowing through each branch of the distribution network and the resistance of each branch in the distribution network topology information; calculating the voltage deviation in the first objective function based on the voltage of each node in the distribution network topology information; and performing a primary optimization based on the first objective function and the distribution network operation constraint information to obtain a primary optimization result; wherein, the primary optimization result is the current flowing through each branch of the distribution network and the node voltage.

[0009] Furthermore, the first objective function is:

[0010] .

[0011] in, Let the first objective function be... For network loss optimization coefficient, For voltage deviation optimization coefficient, This represents the network loss value of the distribution network lines. This refers to the voltage deviation in the distribution network.

[0012] Furthermore, the expression for the network loss value is:

[0013] .

[0014] in, For a period of time; Branch numbering in the distribution network; This represents the number of branches in the distribution network. For the phases of the distribution network, including Mutually, phase and Mutually; The resistance of branch L in the distribution network; This refers to the number of converters in each phase of the distribution network. For distribution network Xiangzai The current flowing through branch L during time period.

[0015] Furthermore, the expression for the voltage deviation is:

[0016] .

[0017] in, For a period of time; For nodes; This represents the number of nodes in the distribution network. The rated voltage of a node in the distribution network; In order to be in In the time-sharing distribution network, the first The voltage of each node.

[0018] Furthermore, the constraint information includes node power balance constraints, node voltage constraints, branch transmission capacity constraints, and loop current constraints.

[0019] Furthermore, the expression for predicting the current flowing through the branch at the next moment based on the first optimization result is as follows:

[0020] .

[0021] in, For distribution network The starting node of the branch; In order to be in Time of the first The voltage of each node; The sampling period; These are the inductance parameters of the converter; In order to be in The current flowing through branch L in the time-period distribution network; For distribution network The resistance value of the branch circuit; In order to be in The current flowing through branch L in the distribution network during the +1 time period is the predicted current flowing through the branch in the next time period of the distribution network.

[0022] Furthermore, the second objective function is:

[0023] .

[0024] in, 2 represents the second objective function; For the optimization coefficient of branch current in the distribution network; This is the current reference value. In order to be in The current flowing through branch L in the distribution network during the +1 time period is the predicted current flowing through the branch in the next time period of the distribution network. These are the phases of the distribution network, including phase A, phase B, and phase C; This is information on the three-phase imbalance.

[0025] According to a second aspect of the present invention, a distribution network regulation system is provided, comprising: an acquisition module for acquiring distribution network topology information and distribution network operation constraint information; a first optimization module for performing a first optimization based on a first objective function, the distribution network topology information, and the distribution network operation constraint information to obtain a first optimization result; a prediction module for predicting the current flowing through a branch at the next moment based on the first optimization result; a second optimization module for optimizing the switching state of the converters inside the distribution network using an optimization algorithm based on a second objective function, the current flowing through the branch, a current reference value, and a three-phase imbalance, as a second optimization result; and a regulation module for regulating the switching state of the converters inside the distribution network based on the second optimization result to adjust the current flowing through the branches of the distribution network.

[0026] According to a third aspect of the present invention, a power distribution network is provided, wherein the power distribution network regulation method described in any one of the above-described methods is applied.

[0027] The beneficial effects of this invention are:

[0028] I. Reducing line loss and voltage deviation: The first objective function directly uses line network loss and voltage deviation as optimization indicators and is solved by the QTP-PSO algorithm, which significantly reduces line loss and the risk of voltage exceeding limits, and solves the problems of high loss and large voltage deviation.

[0029] II. Effective suppression of three-phase imbalance: By generating the switching state of converters in the distribution network with the goal of minimizing line network losses, voltage deviations, and three-phase imbalance, the additional losses due to three-phase imbalance are significantly reduced, avoiding capacity redundancy and high loss problems caused by difficulties in suppressing circulating currents; enhancing the distribution network's adaptability to distributed power source fluctuations, avoiding power curtailment caused by three-phase imbalance or voltage deviation, thereby improving the efficiency of distributed energy consumption. Attached Figure Description

[0030] Figure 1 The diagram shown is a flowchart of the power distribution network regulation and optimization method according to an embodiment of the present invention.

[0031] Figure 2 The diagram shown is a schematic diagram of the first sub-process of the power distribution network regulation method according to an embodiment of the present invention.

[0032] Figure 3 The diagram shown is a schematic diagram of the second sub-process of the power distribution network regulation method according to an embodiment of the present invention.

[0033] Figure 4The diagram shown is a schematic diagram of the first application scenario of the power distribution network regulation method according to an embodiment of the present invention.

[0034] Figure 5 The diagram shown is a schematic representation of the calculation principle of the power distribution network regulation method according to an embodiment of the present invention.

[0035] Figure 6 The diagram shown is a schematic diagram of the circuit structure of the converter in the power distribution network according to an embodiment of the present invention.

[0036] Figure 7 The diagram shown is a schematic diagram of a second application scenario of the power distribution network regulation method according to an embodiment of the present invention.

[0037] Figure 8 The diagram shown is a structural block diagram of a power distribution network regulation system according to an embodiment of the present invention.

[0038] Figure 9 The figure shown is a convergence curve of the objective function of the QTP-PSO algorithm according to an embodiment of the present invention.

[0039] Figure 10 The figure shows the three-phase current diagrams before and after optimization in an embodiment of the present invention.

[0040] Figure 11 The figure shown is a comparison of line losses and voltage deviations within the distribution network before and after optimization according to an embodiment of the present invention. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other.

[0042] Figure 1 The diagram shown is a flowchart illustrating the power distribution network regulation and optimization method according to an embodiment of the present invention. Figure 1 As shown, the power distribution network regulation method specifically includes the following steps;

[0043] Step 10: Obtain distribution network topology information and distribution network operation constraint information;

[0044] Step 20: Perform a first optimization based on the first objective function, distribution network topology information, and distribution network operation constraint information to obtain the first optimization result; wherein, the first optimization result is the current flowing through each branch of the distribution network and the node voltage;

[0045] Step 30: Predict the current flowing through the branch at the next moment based on the optimization results;

[0046] Step 40: Based on the second objective function, the current flowing through the branch, the current reference value, and the three-phase imbalance, the switching state of the converter inside the distribution network is optimized using an optimization algorithm, which is used as the result of the secondary optimization.

[0047] Step 50: Adjust the state of the switches of the converters inside the distribution network according to the secondary optimization results, so as to adjust the current flowing through the distribution network branches.

[0048] As can be seen from the above technical solutions, the first optimization reduces the network loss and voltage deviation of the distribution network lines, and the second optimization reduces the difference between the current flowing through the distribution network branches and the current reference value. This reduces the additional losses caused by the unbalanced current of the three phases inside the distribution network during phase-by-phase operation, improves the stability and safety of the distribution network operation, and at the same time improves the distributed energy consumption rate of the distribution network.

[0049] Specifically, in the distribution network, the day is divided into 24 time periods to obtain the distribution network topology information and establish distribution network operation constraints. The topology information includes the number of branches, the current flowing through the branches, the branch resistance, the node voltage, the node injected power, the node load power, the distributed generation injected power, the branch resistance, and the node rated voltage. Furthermore, the Quantum-Topological Particle Swarm Optimization (QTP-PSO) algorithm is used to optimize the current flowing through the branches and the node voltage within the distribution network, thereby reducing network losses and voltage fluctuations. For example, starting from 00:00, the day is divided into 24 time periods, each lasting one hour.

[0050] Figure 2 The diagram shown is a schematic representation of the first sub-process of the power distribution network optimization and regulation method according to an embodiment of the present invention. In this embodiment, step 20 specifically includes the following steps.

[0051] Step 201: Construct the first objective function; calculate the line network loss value in the first objective function based on the current flowing through each branch of the distribution network and the resistance of each branch in the distribution network topology information; calculate the voltage deviation in the first objective function based on the voltage of each node in the distribution network topology information.

[0052] Step 202: Based on the first objective function, perform an optimization using the distribution network operation constraint information to obtain the first optimization result.

[0053] The first objective function is:

[0054] .

[0055] in, Let the first objective function be... For network loss optimization coefficient, For voltage deviation optimization coefficient, This represents the network loss value of the distribution network lines. This refers to the voltage deviation in the distribution network.

[0056] The expression for the network loss value is:

[0057] .

[0058] in, For a period of time; Branch numbering in the distribution network; This represents the number of branches in the distribution network. For the phases of the distribution network, including Mutually, phase and Mutually; The resistance of branch L in the distribution network; This refers to the number of converters in each phase of the distribution network. For distribution network Xiangzai The current flowing through branch L during time period.

[0059] The expression for the voltage deviation is:

[0060] .

[0061] in, For a period of time; For nodes; This represents the number of nodes in the distribution network. The rated voltage of a node in the distribution network; In order to be in In the time-sharing distribution network, the first The voltage of each node.

[0062] In this embodiment of the invention, the constraint information includes node power balance constraints, node voltage constraints, branch transmission capacity constraints, and loop current constraints.

[0063] The node power balance constraint is:

[0064] .

[0065] in, Let be the injected power at the g-th node; Let g be the load power of the g-th node; Inject power into the distributed power source of the g-th node.

[0066] The node voltage constraint is:

[0067] .

[0068] in, and These represent the maximum and minimum allowable node voltage values ​​in the distribution network, respectively. In order to be in In the time-sharing distribution network, the first The voltage of each node; In order to be in In the time-sharing distribution network, the first The voltage of each node; In order to be in In time-limited distribution networks Active power transmitted through the branch; For distribution network The resistance value of the branch circuit; In order to be in Branch circuits in time-of-use distribution network Transmitted reactive power; For distribution network The inductance value of the branch circuit; In order to be in The current flowing through branch L in the distribution network during a given time period.

[0069] The tributary transmission capacity constraint is:

[0070] .

[0071] in, and For distribution network The start and end points of the branch; For process variables; , for The conductance and susceptance of the branch circuit; and These represent the maximum active power and maximum reactive power allowed to flow through the branches within the distribution network. In order to be in In time-limited distribution networks Active power transmitted through the branch; In order to be in Branch circuits in time-of-use distribution network Transmitted reactive power; In order to be in Time of the first The voltage of each node; In order to be in Time of the first The voltage of each node; In order to be in Time period The voltage phase difference between the start and end nodes of a branch.

[0072] The loop current constraint is:

[0073] .

[0074] in, In order to be in The current flowing through branch L in the distribution network during the time period This is the maximum current allowed to pass through the internal branches of the distribution network during closed-loop operation.

[0075] The first objective function is constructed based on the criterion of minimizing the weighted sum of line network loss and voltage deviation. The quantum-topological particle swarm optimization (QTP-PSO) algorithm is used to optimize the voltage deviation and line loss of the distribution network.

[0076] Furthermore, an optimization is performed using the quantum-topological particle swarm optimization algorithm, including:

[0077] Initialize N particles in the search space, with the position and velocity of each particle following a uniform distribution, and assign quantum state properties to each particle.

[0078] Based on the aforementioned power distribution network topology information, update the position of each particle;

[0079] The network loss and voltage deviation of the distribution network are calculated using the new particle positions until the maximum number of iterations is reached.

[0080] Figure 3 The diagram shown is a second sub-process flow chart of the power distribution network regulation method according to an embodiment of the present invention. In this embodiment, step 30 specifically includes the following steps.

[0081] Step 301: Input the optimization results into the distribution network controller to change the inductance parameters of the converters in the distribution network, as well as the voltage and current of the distribution network.

[0082] Step 302: Use the prediction model in the distribution network controller to predict the current flowing through the branch of the distribution network at the next moment.

[0083] The prediction model is as follows:

[0084] .

[0085] in, For distribution network The starting node of the branch; In order to be in Time of the first The voltage of each node; The sampling period of the controller; These are the inductance parameters of the converter; In order to be in The current flowing through branch L in the time-period distribution network; For distribution network The resistance value of the branch circuit; In order to be in The current flowing through branch L in the distribution network during the +1 time period is the predicted current flowing through the branch in the next time period of the distribution network.

[0086] In this embodiment of the invention, step 40 includes: optimizing the switching state of the converter inside the distribution network using an optimization algorithm based on the second objective function, the current flowing through the branch, the current reference value, and the three-phase imbalance, as the result of the secondary optimization.

[0087] The second objective function is:

[0088] .

[0089] in, 2 represents the quadratic optimization objective function, i.e., the second objective function; For the optimization coefficient of branch current in the distribution network; This is the current reference value. In order to be in The current flowing through branch L in the distribution network during the +1 time period; These are the phases of the distribution network, including phase A, phase B, and phase C; This is information on the three-phase imbalance.

[0090] Furthermore, the three-phase imbalance is expressed as follows:

[0091] .

[0092] in, This is the average value of the three-phase current; , , These are the number of branches for phases A, B, and C, respectively. , , The first one inside the distribution network The output current of phases A, B, and C of a converter.

[0093] Furthermore, the optimal switching state is obtained using a particle swarm optimization algorithm. Specifically, the entire search space is first filled with particles, with each particle corresponding to a set of 24 time-period combinations of A, B, and C three-phase switching states. Then, the combinations are fed into power flow calculations to obtain a weighted sum of line network loss and voltage deviation as fitness. Particles update their positions according to the optimal direction for both the individual and the swarm, and simultaneously perform quantum tunneling perturbations to prevent getting trapped in local extrema. After continuous iteration, the second objective function value of the swarm's optimal particle reaches a preset accuracy, and its position is decoded into the specific converter switching state of A, B, and C phases for each time period.

[0094] Figure 4 The diagram illustrates a specific optimization application scenario of the distribution network regulation method according to an embodiment of the present invention. By real-time acquisition of the three-phase node voltages and branch currents within the distribution network and feeding them into the support unit control module, the support unit control module offline optimizes the node voltage values ​​and branch current values ​​using the QTP-PSO algorithm. Then, the controller generates an online current reference value, which is transmitted to the converter control module via an electrical signal control line. The converter control module then controls the converter to output compensating current and voltage, reducing distribution network line losses and voltage deviations.

[0095] Figure 5 The diagram illustrates the principle of calculating distribution network line losses and voltage deviations in the distribution network regulation method according to an embodiment of the present invention. The superposition method for solving the loop current decomposes the ring network into a pure radial network before loop closure and an equivalent passive ring network after loop closure. The superposition method is used to calculate the distribution branch currents and node voltages, simplifying the solution process.

[0096] Figure 6 The diagram shows a circuit structure of a single-phase converter in a power distribution network according to an embodiment of the present invention. Specifically, the converter's switching circuit converts DC power into AC power by controlling the state of multiple switches and smooths the current through an output filter.

[0097] Figure 7 The diagram illustrates a secondary optimization application scenario of the distribution network optimization and regulation method according to an embodiment of the present invention. Based on the second objective function, the current flowing through the branch, the current reference value, and the three-phase imbalance, an optimization algorithm is used to optimize the switch states within the distribution network. Specifically, the switch state optimization process involves the system using a phase-locked loop (PLL) to ensure current synchronization with the distribution network and adjusting the converter switch states according to the current reference value generated by the controller. This minimizes current error, improves three-phase balance, and enhances system stability and energy absorption rate.

[0098] Table 1 shows the output voltage of the converter under different switching states. Each row in the table represents the operating state corresponding to a specific switching combination, denoted by S. a1 S a2 S b1 S b2 S a and S b S indicates the operating state of the corresponding phase bridge arm switch of the converter. a1 S a2 S indicates the status of the first pair of upper and lower bridge arm switches of the converter. b1 S b2 S indicates the status of the second pair of upper and lower bridge arm switches of the converter. a S bThis indicates the state of the main converter switch. Each switch state can be either open (1) or closed (0). U ab This refers to the reverse AB phase-to-phase output voltage of a single-phase L-type grid-connected system, and its values ​​include 0 and +U. dc / 2、U dc -U dc / 2 and -U dc Z i2 This represents the output characteristic impedance of the converter. These states and switching combinations are adjusted in real time by the converter controller to minimize current errors and achieve three-phase balance, thereby improving the energy stability and operational safety of the system. By dynamically adjusting the switching states, the converter can precisely control the output voltage and current to adapt to the needs of the distribution network and optimize energy consumption.

[0099] Table 1 Output voltage and characteristic impedance of the converter under different switching states

[0100]

[0101] The beneficial effects of this invention are as follows.

[0102] 1) Effectively suppress three-phase imbalance: By generating the switching state of converters in the distribution network with the goal of minimizing line network losses, voltage deviations, and three-phase imbalance, the additional losses due to three-phase imbalance are reduced, and circulating currents are suppressed, avoiding capacity redundancy and high loss problems caused by difficulties in suppressing circulating currents. Furthermore, the adaptability of the distribution network to distributed power source fluctuations is enhanced, avoiding power curtailment caused by three-phase imbalance or voltage deviation, thereby improving the efficiency of distributed energy consumption.

[0103] 2) Reduce line loss and voltage deviation: The first objective function directly uses line network loss and voltage deviation as optimization indicators and is solved by the QTP-PSO algorithm, which significantly reduces line loss and the risk of voltage exceeding limits.

[0104] Figure 8 The diagram shown is a structural block diagram of a power distribution network regulation system according to an embodiment of the present invention. Figure 8 As shown, the distribution network regulation system 1 includes:

[0105] Module 11 is used to acquire distribution network topology information and distribution network operation constraint information;

[0106] The first optimization module 12 is used to perform an optimization based on the first objective function, the distribution network topology information and the distribution network operation constraint information, and obtain an optimization result.

[0107] Prediction module 13 is used to predict the current flowing through the branch at the next moment based on the optimization result;

[0108] The second optimization module 14 is used to optimize the switching state of the converter inside the distribution network based on the second objective function, the current flowing through the branch, the current reference value, and the three-phase imbalance, and to use the optimization algorithm as the result of the secondary optimization.

[0109] The adjustment module 15 is used to adjust the state of the switches of the converters inside the distribution network according to the secondary optimization results, so as to adjust the current flowing through the distribution network branches.

[0110] Furthermore, in the distribution network regulation method shown in this invention, the QTP-PSO algorithm is used to simulate and optimize the medium-voltage distribution network over a 24-hour period. The simulation results are as follows: Figures 9-11 As shown.

[0111] Figure 9 The figure shows the convergence curve of the objective function of the QTP-PSO algorithm in an embodiment of the present invention. It illustrates the convergence process of the objective function of the QTP-PSO algorithm. The curve in the figure shows that after multiple iterations, the objective function value gradually decreases and stabilizes, proving that the algorithm can effectively find the optimal solution that minimizes both line loss and voltage deviation.

[0112] Figure 10 The figure shown is a simulation comparison of the current flowing through the three-phase branches before and after optimization according to an embodiment of the present invention. After optimization, the current waveforms flowing through the three-phase branches tend to be consistent, and the three-phase imbalance phenomenon is significantly improved, indicating that the method of the present invention can effectively suppress the three-phase imbalance of the distribution network.

[0113] Figure 11 The figure shown is a comparison of line losses and node voltage deviations before and after optimization according to an embodiment of the present invention. The results show that after adopting the optimization method of the present invention, line losses are significantly reduced, voltage deviations are decreased, and the operating efficiency and power quality of the distribution network are improved.

[0114] In summary, the above simulations were conducted on a typical medium-voltage distribution network system. The figures clearly demonstrate the significant effects of the method of this invention in reducing losses, controlling voltage deviations, and improving three-phase current balance, providing strong support for the efficient integration of distributed energy resources and the safe and stable operation of the distribution network.

[0115] It should be understood that while the steps in the flowchart above are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated in this invention, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0116] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0117] It should be noted that in this invention, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0118] The specific embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present invention.

Claims

1. A distribution network regulation method, characterized in that, include: Obtain information on the distribution network topology and operational constraints. Based on the first objective function, the distribution network topology information, and the distribution network operation constraint information, an optimization is performed to obtain the first optimization result; Predict the current flowing through the branch at the next moment based on the results of the first optimization. Based on the second objective function, the current flowing through the branch, the current reference value, and the three-phase imbalance, the switching state of the converters inside the distribution network is optimized using an optimization algorithm, which is used as the result of the secondary optimization. Based on the results of the secondary optimization, the switching status of the converters inside the distribution network is adjusted to regulate the current flowing through the distribution network branches; The first optimization, based on the first objective function, distribution network topology information, and distribution network operation constraint information, yields the first optimization result, including: Construct the first objective function; calculate the line network loss value in the first objective function based on the current flowing through each branch of the distribution network and the resistance of each branch in the distribution network topology information; calculate the voltage deviation in the first objective function based on the voltage of each node in the distribution network topology information; Based on the first objective function, a primary optimization is performed using the distribution network operation constraint information to obtain the primary optimization result; wherein, the primary optimization result is the current flowing through each branch of the distribution network and the node voltage; The first objective function is: ； in, Let the first objective function be... For network loss optimization coefficient, For voltage deviation optimization coefficient, This represents the network loss value of the distribution network lines. For distribution network voltage deviation; The expression for the network loss value is: ； in, For a period of time; Branch numbering in the distribution network; This represents the number of branches in the distribution network. For the phases of the distribution network, including Mutually, phase and Mutually; The resistance of branch L in the distribution network; This refers to the number of converters in each phase of the distribution network. For distribution network Xiangzai The current flowing through branch L during time period.

2. The power distribution network regulation method according to claim 1, characterized in that, The expression for the voltage deviation is: ； in, For a period of time; For nodes; This represents the number of nodes in the distribution network. The rated voltage of a node in the distribution network; In order to be in In the time-sharing distribution network, the first The voltage of each node.

3. The power distribution network regulation method according to claim 1, characterized in that, The constraint information includes node power balance constraints, node voltage constraints, branch transmission capacity constraints, and loop current constraints.

4. The power distribution network regulation method according to claim 1, characterized in that, The expression for predicting the current flowing through the branch at the next moment based on the first optimization result is as follows: ； in, For distribution network The starting node of the branch; In order to be in Time of the first The voltage of each node; The sampling period; These are the inductance parameters of the converter; In order to be in The current flowing through branch L in the time-period distribution network; For distribution network The resistance value of the branch circuit; In order to be in The current flowing through branch L in the distribution network during the +1 time period is the predicted current flowing through the branch in the next time period of the distribution network.

5. The power distribution network regulation method according to claim 1, characterized in that, The second objective function is: ； in, 2 represents the second objective function; For the optimization coefficient of branch current in the distribution network; This is the current reference value. In order to be in The current flowing through branch L in the distribution network during the +1 time period is the predicted current flowing through the branch in the next time period of the distribution network. These are the phases of the distribution network, including phase A, phase B, and phase C; This is information on the three-phase imbalance.

6. A power distribution network regulation system, characterized in that, include: The acquisition module is used to acquire distribution network topology information and distribution network operation constraint information; The first optimization module is used to perform an optimization based on the first objective function, the distribution network topology information, and the distribution network operation constraint information to obtain an optimization result. The prediction module is used to predict the current flowing through the branch at the next moment based on the result of one optimization. The second optimization module is used to optimize the switching state of the converters inside the distribution network based on the second objective function, the current flowing through the branch, the current reference value, and the three-phase imbalance, and to obtain the secondary optimization result. The adjustment module is used to adjust the state of the switches of the converters inside the distribution network based on the secondary optimization results, so as to adjust the current flowing through the distribution network branches; The first optimization, based on the first objective function, distribution network topology information, and distribution network operation constraint information, yields the first optimization result, including: Construct the first objective function; calculate the line network loss value in the first objective function based on the current flowing through each branch of the distribution network and the resistance of each branch in the distribution network topology information; calculate the voltage deviation in the first objective function based on the voltage of each node in the distribution network topology information; Based on the first objective function, a primary optimization is performed using the distribution network operation constraint information to obtain the primary optimization result; wherein, the primary optimization result is the current flowing through each branch of the distribution network and the node voltage; The first objective function is: ； in, Let the first objective function be... For network loss optimization coefficient, For voltage deviation optimization coefficient, This represents the network loss value of the distribution network lines. For distribution network voltage deviation; The expression for the network loss value is: ； in, For a period of time; Branch numbering in the distribution network; This represents the number of branches in the distribution network. For the phases of the distribution network, including Mutually, phase and Mutually; The resistance of branch L in the distribution network; This refers to the number of converters in each phase of the distribution network. For distribution network Xiangzai The current flowing through branch L during time period.

7. A power distribution network, characterized in that, The power distribution network regulation method as described in any one of claims 1 to 5 is applied.

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