A power distribution network multi-source automatic switching method and system

Abstract

This invention relates to the field of multi-source coordinated control technology in distribution networks, and discloses an automatic switching method and system for multiple power sources in a distribution network. The switching method includes: dynamically modeling the transient power flow of the main power source and distributed power sources in a multi-source distribution network, and performing dynamic response analysis of topology changes; evaluating the system energy obtained from the dynamic modeling using the transient energy function method, calculating the kinetic and potential energy components before and after the switching, and determining the system energy balance state based on the comparison result of the energy difference and the critical energy threshold; and executing phased soft switching control based on the energy evaluation result, through sequential control logic of synchronization stage, power sharing stage, and switching transition stage, and performing gradual power transition between the main power source and distributed power sources according to a predictive control algorithm. This invention achieves real-time power flow reconstruction under topology changes, energy-driven switching decisions, and smooth power transition, reducing voltage fluctuations and transient impacts caused by switching.

Description

Technical Field

[0001] This invention relates to the field of multi-source coordinated control technology in power distribution networks, and specifically to an automatic switching method and system for multiple power sources in power distribution networks. Background Technology

[0002] With the large-scale integration of distributed power sources, distribution networks are gradually evolving from a single-source centralized power supply mode to a multi-source collaborative power supply mode. Multi-source distribution networks can achieve power complementarity and energy balance between primary and distributed power sources, effectively improving power supply reliability and operational flexibility. However, during parallel operation of multiple power sources, the system's power flow exhibits strong nonlinearity and transient dynamic characteristics, especially during power switching, islanding operation, and reconnection, where voltage and frequency coupling fluctuations increase significantly. To ensure the stability and security of distribution network operation, automated switching control has become a key research focus, with its core being the achievement of seamless transition and dynamic energy balance between different power sources.

[0003] Existing multi-power switching systems are mostly based on steady-state power flow analysis or traditional time-delay switching logic, lacking a precise description of transient power flow dynamics under topology changes and failing to reflect the energy exchange process between primary and distributed power sources. When a system switch occurs, rapid shifts in voltage phase angle and frequency can easily cause power surges, leading to transient inrush currents and bus voltage fluctuations, thus affecting the dynamic stability of the distribution network. Simultaneously, existing control strategies generally employ fixed switching thresholds and time-delay logic, lacking real-time assessment of transient energy states, making it difficult to achieve energy balance and dynamic coordination during the switching process. While some studies have introduced fuzzy control or droop characteristic regulation, a unified model from transient energy evolution to power-sharing control has not yet been established, resulting in a lack of smooth transition during the switching process. Therefore, minimizing energy disturbances caused by power flow surges while ensuring power continuity during the coordinated switching of primary and distributed power sources remains a pressing technical challenge. Summary of the Invention

[0004] This invention provides an automatic switching method and system for multiple power sources in a distribution network, aiming to solve the technical challenge of minimizing energy disturbances caused by sudden power flow changes while ensuring power continuity during the coordinated switching process between main power sources and distributed power sources.

[0005] In a first aspect, the present invention provides an automatic switching method for multiple power sources in a distribution network, the method comprising:

[0006] Dynamic modeling of transient power flow between main power sources and distributed power sources in multi-source power distribution networks is performed, and dynamic response analysis of topology changes is conducted. The transient energy function method is used to evaluate the system energy obtained from dynamic modeling, calculate the kinetic and potential energy components before and after switching, and determine the system energy balance state based on the comparison between the energy difference and the critical energy threshold. Based on the energy assessment results, phased soft switching control is implemented. Through sequential control logic of synchronization phase, power sharing phase and switching transition phase, the power transition between main power supply and distributed power supply is carried out step by step according to the predictive control algorithm.

[0007] This invention provides an automatic switching method for multiple power sources in a distribution network. By establishing a dynamic power flow model, it achieves real-time reconstruction of the power flow distribution under topology switching, enabling the system to have adaptive response capabilities. A transient energy function method is used to quantitatively evaluate the system's kinetic and potential energy, and a stability criterion based on energy difference and critical threshold is proposed, realizing energy self-sensing and self-constrained control during the switching process. By combining staged soft switching with predictive control algorithms, continuous power transition between the main power source and distributed power sources is achieved under energy deviation constraints, reducing voltage fluctuations and transient impacts caused by switching. This invention transforms multi-power source systems from static control to dynamic energy coordination control, forming a closed-loop mechanism from modeling and stability assessment to control, effectively improving the stability, robustness, and intelligence level of the distribution network under complex operating conditions.

[0008] In one optional implementation, dynamic modeling of the transient power flow of primary power sources and distributed power sources in a multi-source power distribution network is performed, along with dynamic response analysis of topology changes, including: Between the nodes of the main power supply and the distributed power supply, the power balance relationship of each node is calculated by real-time monitoring of node voltage and current signals, and a transient power flow dynamic model is automatically generated. Voltage phase angle, frequency change, node power and inverter control parameters are used as variables in the transient power flow dynamic model, and the voltage transfer characteristics between nodes are calculated within the admittance matrix framework of the distribution network. For distributed power sources, the output stage, filtering stage, current control stage, and voltage control stage of the inverter they are configured with are combined and modeled as a dynamic response module. When the network topology changes, an internal topology switching command is triggered, which automatically reconstructs the node connection relationships and power flow direction.

[0009] In one optional implementation, when the network topology changes, an internal topology switching command is triggered to automatically reconstruct node connectivity and power flow direction, including: When the network topology changes, the connection status, voltage deviation and frequency deviation between the main power supply and the distributed power supply are detected in real time. When both voltage deviation and frequency deviation exceed the set threshold, it is automatically determined to be in an asynchronous state and a topology reconfiguration operation is initiated. During topology reconfiguration, the bus connection relationship is adjusted through the control logic of the switch matrix, so that the electrical connection of the corresponding node is updated in real time. During the switching process, transient voltage and current data of each node are collected and input into the transient power flow dynamic model to recalculate the power flow distribution.

[0010] In one optional implementation, the system energy obtained from dynamic modeling is evaluated using the transient energy function method, the kinetic and potential energy components before and after the switching are calculated, and the system energy balance state is determined based on the comparison between the energy difference and the critical energy threshold, including: Substitute the system state variables output from the transient power flow dynamic model into the energy analysis module, and add the kinetic energy term corresponding to the frequency change and the potential energy term corresponding to the voltage offset to obtain the total system energy. The total system energy is calculated before and after each power switching action, and the difference is obtained as the transient energy change. When the transient energy change is below the critical energy threshold, the system is determined to be in a stable state, and power transfer is allowed. When the transient energy change is not lower than the critical energy threshold, the switching is temporarily suspended and the power output rate is adjusted to reduce the energy fluctuation amplitude.

[0011] In one optional implementation, when the transient energy change is not lower than a critical energy threshold, the switching is temporarily suspended, and the power output rate is adjusted to reduce the energy fluctuation amplitude, including: When the transient energy change is lower than the critical energy threshold, the optimal power transfer increment is calculated based on the current trend of the total energy change of the system. Synchronization control signals are sent to the distributed power source and the main power source to adjust their output power curves respectively, so that the output power of the main power source gradually decreases while the output power of the distributed power source gradually increases.

[0012] In one optional implementation, phased soft switching control is performed based on energy assessment results. This involves sequential control logic through a synchronization phase, a power-sharing phase, and a switching transition phase, using a predictive control algorithm to gradually transition power between the main power source and the distributed power source. This includes: During the synchronization phase, phase angle tracking control is used to gradually make the output voltage phase angle of the distributed power source and the voltage phase angle of the main power source consistent. When the phase angle difference is less than a predetermined threshold, the synchronization is considered complete. During the power sharing phase, a feedback control strategy based on voltage and frequency offset is adopted to dynamically adjust the active and reactive power outputs of the main power supply and distributed power supply according to the current load distribution ratio, and share the load according to a predetermined ratio. When the power distribution is detected to have reached a stable state, the switching transition phase is entered. During the switching transition phase, based on the feedback energy deviation signal, the output power of the main power supply is reduced in stages, while the output power of the distributed power supply is increased proportionally, so that the total power change curve is continuous and smooth.

[0013] In one optional implementation, phased soft switching control is performed based on energy assessment results. This involves sequential control logic through a synchronization phase, a power-sharing phase, and a switching transition phase, using a predictive control algorithm to gradually transition power between the main power source and the distributed power source. The implementation also includes: During the soft handover execution, the operating status of the system for several future sampling periods is predicted, and the optimal adjustment of each control variable is calculated in real time with the goal of minimizing power deviation and voltage deviation. Within each control cycle, based on the latest measured voltage, current, frequency, and energy difference, the system state at the next moment is predicted, and optimized control quantities are generated. The power output commands of the main power supply and distributed power supply are updated on a rolling basis according to the prediction results, so that the power output curve always meets the energy balance condition. When the system detects that the deviation between the predicted value and the actual measured value exceeds the set range, it immediately resets the parameters of the prediction model and triggers the safety switching logic, suspends power transfer, and rebuilds the prediction model.

[0014] Secondly, the present invention provides an automatic switching system for multiple power sources in a power distribution network, the system comprising: The dynamic response analysis module is used to dynamically model the transient power flow of main power sources and distributed power sources in multi-source power distribution networks and perform dynamic response analysis of topology changes. The equilibrium state analysis module is used to evaluate the system energy obtained from dynamic modeling using the transient energy function method, calculate the kinetic and potential energy components before and after switching, and determine the system energy equilibrium state based on the comparison results of the energy difference and the critical energy threshold. The switching control module is used to perform phased soft switching control based on energy assessment results. Through sequential control logic of synchronization phase, power sharing phase and switching transition phase, it performs gradual power transition between main power supply and distributed power supply according to predictive control algorithm.

[0015] This invention provides an automatic switching system for multiple power sources in a distribution network. By establishing a dynamic power flow model, it achieves real-time reconstruction of power flow distribution under topology switching, enabling the system to have adaptive response capabilities. It employs the transient energy function method to quantitatively evaluate the system's kinetic and potential energy, and proposes a stability criterion based on energy difference and critical threshold, realizing energy self-sensing and self-constrained control during the switching process. By combining staged soft switching with predictive control algorithms, it achieves continuous power transition between the main power source and distributed power sources under energy deviation constraints, reducing voltage fluctuations and transient impacts caused by switching. This invention transforms multi-power source systems from static control to dynamic energy coordination control, forming a closed-loop mechanism from modeling and stability assessment to control, effectively improving the stability, robustness, and intelligence level of the distribution network under complex operating conditions.

[0016] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the automatic switching method for multiple power sources in a power distribution network as described in the first aspect or any corresponding embodiment.

[0017] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the automatic switching method for multiple power sources in a distribution network according to the first aspect or any corresponding embodiment described above. Attached Figure Description

[0018] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating an automatic switching method for multiple power sources in a distribution network according to an embodiment of the present invention. Figure 2 This is a structural block diagram of an automatic switching system for multiple power sources in a distribution network according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0020] 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. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. 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.

[0021] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0022] This invention provides an automatic switching method for multiple power sources in a power distribution network, such as... Figure 1 As shown, it includes the following steps: Step S1: Dynamically model the transient power flow of the main power source and distributed power sources in the multi-power source distribution network, and perform dynamic response analysis of topology changes.

[0023] In this embodiment, step S1 includes the following process: Step S11: Between the nodes of the main power supply and the distributed power supply, the power balance relationship of each node is calculated by real-time monitoring of node voltage and current signals, and a transient power flow dynamic model is automatically generated.

[0024] Step S12 uses voltage phase angle, frequency change, node power and inverter control parameters as variables in the transient power flow dynamic model, and calculates the voltage transfer characteristics between nodes within the admittance matrix framework of the distribution network.

[0025] Step S13: For distributed power sources, the output stage, filtering stage, current control stage, and voltage control stage of the inverter configured in the distributed power source are combined and modeled into a dynamic response module.

[0026] Step S14: When the network topology changes, an internal topology switching command is triggered to automatically reconstruct the node connection relationship and power flow direction.

[0027] Specifically, the power distribution network is equipped with... There are 1 node, with node number 1. Voltage of each node With current The signals are defined as follows:

[0028]

[0029] in, Represents a node The voltage amplitude; Represents a node The voltage phase angle; Represents a node The current amplitude; Represents a node The current phase angle; Indicates the real-time sampling time. Represents the imaginary unit, and the main power node number is... The distributed power node number is The phase angle difference between the two Represented as:

[0030] in, Main power supply phase angle, For distributed generation phase angle, frequency deviation Represented as:

[0031] At any given moment, node Complex power Represented as:

[0032] in, Active power Reactive power It is the complex conjugate of the node current.

[0033] According to the system admittance matrix The relationship between node voltage and current is as follows:

[0034] in, , and Representing nodes respectively and The conductivity and susceptance between them Represents a node The voltage.

[0035] The transient power flow equilibrium equation is expressed as:

[0036] This equation describes the dynamic relationship between node voltage and time, and is the basic form of transient power flow dynamic model.

[0037] For distributed power nodes Its output is regulated by the inverter control circuit, and the inverter model consists of three parts: Current control circuit: Adjusting the output current ; Voltage control circuit: Adjusts the modulation signal according to the voltage deviation; Filtering stage: through inductor and capacitor The smooth output waveform and its dynamic response equation are expressed as follows:

[0038]

[0039] in, , , These are the filter inductor, capacitor, and parasitic resistance, respectively. This refers to the output voltage of the inverter bridge arm. This refers to the bus voltage. For node load current, the inverter control reference is dynamically corrected based on voltage and frequency offset:

[0040] in, This is a reference value for the inverter output voltage. For reference voltage, , For control coefficients, , The angular frequency of the distributed power source. This provides the real-time frequency at the output of the distributed power source, enabling rapid dynamic adjustment of the distributed power source under voltage disturbances and frequency changes, thus giving the dynamic power flow model real-time performance.

[0041] Topology Change Triggering and Automatic Power Flow Reconfiguration: When the system topology changes, such as a line disconnection, switch action, or source switching, the topology state function is triggered.

[0042] in, This represents the network connection diagram after the system switch. This represents the network connection graph before the system switchover, with the network connection matrix at time [time value missing]. When an update occurs, the system automatically triggers a topology switching command signal. And recalculate the node admittance matrix after system switching. The reconstructed power flow equations are solved again:

[0043] in, This indicates the current signal after system switching, ensuring that power flow direction and node power allocation are automatically updated as the topology changes.

[0044] Furthermore, step S14 above includes the following: Step S141: When the network topology changes, the connection status, voltage deviation and frequency deviation between the main power supply and the distributed power supply are detected in real time.

[0045] Step S142: When the voltage deviation and frequency deviation both exceed the set threshold, the system is automatically determined to be in an asynchronous state and a topology reconfiguration operation is initiated.

[0046] Step S143: During the topology reconfiguration process, the bus connection relationship is adjusted through the control logic of the switch matrix so that the electrical connection of the corresponding node is updated in real time.

[0047] Step S144: During the switching process, the transient voltage and current data of each node are collected and input into the transient power flow dynamic model to recalculate the power flow distribution.

[0048] Specifically, during the dynamic response analysis process, the voltage difference between the main power supply and the distributed power supply is calculated in real time. With frequency difference , is represented as:

[0049]

[0050] in, Main power supply voltage, For distributed power supply voltage, The real-time frequency at the main power supply output terminal, when the following combined conditions are met:

[0051] That is, both voltage deviation and frequency deviation exceed the set threshold. , When the system determines that it is in an asynchronous state, it immediately triggers a topology reconfiguration operation, which is controlled by a switch matrix. Control, its elements Represents a node and Whether it is connected. When a trigger condition is detected, the controller updates the switch matrix according to a preset logic table, as shown below:

[0052] in, This represents the updated switch matrix. This represents the switching matrix before the update. After the topology switch is completed, the system immediately collects the transient voltage and current signals of each node and inputs them into the transient power flow balance equation for solution:

[0053] The solution obtained As the new initial state of the system, dynamic integration calculations continue. To prevent system oscillations caused by frequent topology switching in a short period, the transient power flow dynamic model sets a lockout time window after each topology event, allowing new switching commands only after detecting that the system has reached a steady state again. That is, a lockout time window is set. ,exist After the switch is triggered, the system enters a locked state, as indicated by:

[0054] Only when it is detected that the system has returned to steady state, that is:

[0055] in, and When the voltage and frequency stability thresholds are reached respectively, the system unlocks, allowing new switching commands to enter.

[0056] It should also be noted that in multi-source distribution networks, frequent changes in topology and the nonlinear output characteristics of distributed sources make traditional steady-state power flow calculation models unable to reflect dynamic behavior during switching transients. Existing technologies typically use static power balance equations or linearized power flow models for analysis, assuming a constant network topology and unchanging system parameters. This assumption leads to the inability to capture changes in voltage, frequency, and phase angle in real time during power switching, switching actions, or the formation of local islands, making the system prone to sudden power flow changes and control lags. The dynamic power flow modeling mechanism, which uses voltage phase angle, frequency changes, and inverter control parameters as state variables and achieves real-time admittance matrix self-reconstruction through topology switching trigger functions, essentially solves the long-standing problem of maintaining the computability and continuity of the power flow model under dynamic topology changes, transforming power flow calculation from static analysis to event-driven dynamic response modeling. It not only constructs a unified time-varying equation system for power flow and topology changes but also ensures stable convergence of the model during switching transients through a time window locking mechanism.

[0057] Step S2: The system energy obtained from dynamic modeling is evaluated using the transient energy function method. The kinetic and potential energy components before and after the switching are calculated, and the system energy balance state is determined based on the comparison between the energy difference and the critical energy threshold.

[0058] In this embodiment, step S2 includes the following process: Step S21: Substitute the system state variables output by the transient power flow dynamic model into the energy analysis module, and add the kinetic energy term corresponding to the frequency change and the potential energy term corresponding to the voltage shift to obtain the total system energy.

[0059] Step S22: Calculate the total system energy before and after each power switching action, and obtain the difference as the transient energy change.

[0060] Step S23: When the transient energy change is lower than the critical energy threshold, the system is determined to be in a stable state, and power transfer is allowed.

[0061] Step S24: When the transient energy change is not lower than the critical energy threshold, the switching is temporarily suspended, and the power output rate is adjusted to reduce the energy fluctuation amplitude.

[0062] Specifically, the total energy of the system It consists of two parts:

[0063] in, The kinetic energy term reflects the energy accumulation of the system's rotational or electrical inertia as frequency changes; This is the potential energy term, reflecting the electromagnetic potential energy stored by the system voltage deviation; in a distribution network system, the frequency deviation between the main power source and distributed power sources is:

[0064] The corresponding angular frequency offset is:

[0065] The equivalent inertia constant of the system is defined as , representing the inertia of the main power supply and distributed power supply combination under electrical equivalence, and the system kinetic energy is:

[0066] The magnitude of the kinetic energy change of the system under frequency fluctuations reflects the inertial support capability of the system before and after the switching.

[0067] For electrical systems, the deviation of node voltage reflects the energy stored or released by energy storage elements, and the node voltage relative to the reference voltage. offset for:

[0068] Let the equivalent capacitance of the node voltage be Then the node electric potential energy for:

[0069] The total potential energy of the system is the sum of the potential energies of all nodes, expressed as:

[0070] This potential energy term is used to reflect the transient energy accumulation effect caused by voltage disturbances.

[0071] Before power switching (at any moment) ) and after the switch (time) The total energy of the system is as follows:

[0072]

[0073] Total system energy before power switching Total system energy after power switching The energy difference between two moments is defined as the transient energy change. 。 is represented as:

[0074] When the system is in a stable state It should be lower than the preset critical energy threshold. ,Right now:

[0075] If this condition is met, the system is in energy balance and is allowed to proceed with the next power switching operation; If the conditions are not met, the system enters energy protection logic and suspends power transfer operations.

[0076] Furthermore, step S24 above includes the following: Step S241: When the transient energy change is lower than the critical energy threshold, calculate the optimal power transfer increment based on the current trend of the total energy change of the system.

[0077] Step S242: Send synchronization control signals to the distributed power source and the main power source to adjust their output power curves respectively, so that the output power of the main power source gradually decreases while the output power of the distributed power source gradually increases.

[0078] Specifically, an energy deviation signal is generated during the energy assessment phase as an input for soft switching control. When the energy deviation signal exceeds a preset threshold, the power transfer rate is dynamically modified through the logic unit. Based on the current energy change trend of the system, the optimal increment for power transfer is calculated. At the same time, a synchronization control signal is sent to the distributed power source and the main power source to adjust the output power curves respectively, so that the output power of the main power source gradually decreases while the output of the distributed power source gradually increases.

[0079] Critical energy threshold It can be determined through system modeling and simulation, and its value depends on the system capacity, inertia parameters, and voltage tolerance range. In this application, The setting method is as follows:

[0080] in, The total energy storage under the rated operating conditions of the system; As a safety factor, its value ranges from 0.05 to 0.1, with a fixed period. Perform energy calculation and stability assessment, and output a judgment signal in each cycle. , is represented as:

[0081] when When the system is stable, it can enter the soft handover phase; when At the same time, the system maintains a monitoring state and adjusts control parameters.

[0082] Simultaneously, an energy deviation signal is generated. This represents the degree of deviation between the current energy state and the stable energy, expressed as:

[0083] in, This indicates that the system energy has exceeded its limit. This indicates insufficient energy.

[0084] when Exceeding the threshold At this time, the logic unit automatically slows down the power switching speed to prevent further accumulation of transient energy. The controller calculates the power transfer rate correction. , is represented as:

[0085] in It is the energy feedback gain constant, used to convert energy deviation into power adjustment.

[0086] Under the influence of energy assessment and deviation feedback, the controller sends synchronization control signals to both the main power source and the distributed power source. , The control law is:

[0087]

[0088] in, , These are the reference power for the main power supply and the distributed power supply, respectively. , For real-time control commands.

[0089] The control law ensures that the power regulation of the two power sources cancels each other out, thus achieving total power conservation, expressed as:

[0090] This enables synchronous power transition in an energy balance state.

[0091] It should also be noted that the essence of power switching in a distribution network is an energy redistribution process. Traditional control methods generally use voltage, current, or frequency deviations as control criteria, but they are difficult to reveal the essence of system stability from an energy perspective. Current technologies lack a mechanism that can quantify system energy changes during switching and use this as a control trigger. Introducing the transient energy function method into the switching control of multi-source distribution networks, by mapping the state variables output by the power flow dynamic model to kinetic and potential energy terms, establishes a functional relationship between the total system energy and the steady state, achieving energy-driven steady-state discrimination. This breaks through the limitations of the traditional voltage-frequency dual-loop criterion, transforming the system stability problem into an energy conservation and balance problem, and enabling dynamic identification of safe switching windows under critical energy thresholds. By comparing energy changes with critical energy thresholds, a calculable stability evaluation during switching is achieved, solving the long-standing technical problem of being unable to quantitatively assess the safety of power switching. The energy function model achieves consistency between control logic and the physical system, enabling the system to self-determine steady state and self-constrain power regulation capabilities, promoting the evolution of distribution networks from traditional signal-driven control to energy self-sensing and self-regulating control.

[0092] Step S3: Based on the energy assessment results, perform phased soft switching control. Through the sequential control logic of the synchronization phase, power sharing phase and switching transition phase, the main power supply and distributed power supply are gradually switched over according to the predictive control algorithm.

[0093] In this embodiment, step S3 includes the following process: Step S31: During the synchronization phase, the phase angle of the output voltage of the distributed power source is gradually brought into alignment with the phase angle of the main power source through phase angle tracking control. When the phase angle difference is less than a predetermined threshold, the synchronization is determined to be complete.

[0094] Step S32: In the power sharing phase, a feedback control strategy based on voltage and frequency offset is adopted to dynamically adjust the active and reactive power outputs of the main power supply and the distributed power supply according to the current load distribution ratio, and they share the load according to a predetermined ratio. When the power distribution is detected to have reached a stable state, the switching transition phase is entered.

[0095] Step S33: During the switching transition phase, based on the feedback energy deviation signal, the output power of the main power supply is reduced in stages, while the output power of the distributed power supply is increased proportionally, so that the total power change curve is continuous and smooth.

[0096] Specifically, calculate the total load power. , is represented as:

[0097] Indicates the main power supply output power. This represents the output power of the distributed power source. The control objective is to ensure power conservation, that is:

[0098] in, This is the real-time load reference power for the system.

[0099] The phase angle tracking controller gradually brings the voltage phase angles of the main power supply and the distributed power supply to converge. The phase angle difference is expressed as:

[0100] The phase angle control law is:

[0101] in, The reference angular frequency; This is the phase angle synchronization control gain.

[0102] The controller dynamically adjusts the output frequency of the distributed power supply. , is represented as:

[0103] When the synchronization criterion is met:

[0104] in, When the phase angle tolerance, i.e., the predetermined threshold, is used, the system determines that synchronization is complete and enters the power sharing phase.

[0105] During the power sharing phase, the main power supply and distributed power supplies dynamically adjust their power output according to the droop characteristics of voltage and frequency offsets. The main power supply's active power adjustment mechanism is as follows:

[0106] Distributed power generation active power adjustment rules:

[0107] The reactive power adjustment rules for main power sources and distributed power sources are as follows:

[0108]

[0109] in, , , , This is the corresponding reference power; , , , These are the corresponding active and reactive power droop coefficients; and This represents the system reference frequency and voltage. Through this feedback adjustment process, the system achieves a predetermined ratio. (e.g., 6:4) Sharing load power:

[0110] in, The main power supply power sharing factor represents the target proportion of the main power supply in the total power. The distributed generation power sharing factor represents the target proportion of distributed generation in the total power, when the continuous time window... Internal satisfaction:

[0111] That is, the rate of change of power output is lower than the stability threshold. When the system determines that the power distribution is stable, it enters the switching transition phase.

[0112] During the switching transition phase, the system uses the energy deviation signal. To achieve a smooth transition under energy balance, power correction is performed. The power regulation laws for main power sources and distributed power sources are as follows:

[0113]

[0114] in, This indicates the output power of the main power supply at the next sampling time. This indicates the output power of the distributed power source at the next sampling time. To control the time step:

[0115] in, The energy deviation feedback gain coefficient is used to achieve total power conservation.

[0116] And ensure the total power curve is continuous and without abrupt changes, the system continuously monitors the power change rate and frequency offset, when the following conditions are met:

[0117] Then it is determined that the system has completed the switching transition, the main power supply gradually withdraws, and the distributed power supply completely takes over the load.

[0118] Furthermore, step S3 above also includes the following process: Step S34: During the soft handover execution, the operating state of the system for several future sampling periods is predicted, and the optimal adjustment amount of each control variable is calculated in real time with the goal of minimizing power deviation and voltage deviation.

[0119] Step S35: In each control cycle, based on the latest measured voltage, current, frequency and energy difference, predict the system state at the next moment and generate the optimized control quantity.

[0120] Step S36: Update the power output commands of the main power supply and distributed power supply on a rolling basis according to the prediction results, so that the power output curve always meets the energy balance condition.

[0121] Step S37: When the system detects that the deviation between the predicted value and the actual measured value exceeds the set range, it immediately resets the parameters of the prediction model and triggers the safety switching logic, suspends power transfer and rebuilds the prediction model.

[0122] Specifically, based on the modeling and energy relationship, the system state vector is defined. , is represented as:

[0123] Control input vector Represented as:

[0124] Discretized form of the prediction state equation Represented as:

[0125] Where the matrix and Derived from system identification or linearization, the MPC controller aims to minimize power error and voltage deviation.

[0126] in, The optimization objective value that the MPC controller needs to minimize is... Indicates the prediction step size. and As the weight of power and voltage deviation, This indicates that the system predicts future moments. Actual load power Indicates the system in the future The expected power value for each prediction step. This indicates that distributed power sources will be available in the future. Voltage amplitude prediction results for each prediction step. The index value represents the prediction time step, and the control optimization constraints include:

[0127]

[0128] in, The energy deviation signal indicates the system's energy deviation in the future. Energy deviation at each prediction step The energy deviation threshold, This is the main power supply control input, indicating the main power supply's position during the prediction step. Control commands, For distributed generation control inputs, this represents the distributed generation's control input during the prediction step. Control commands, To control the upper limit of the input value, in each control cycle Inside, the controller, based on the latest measured data... Perform rolling optimization to obtain the optimal control input. , is represented as:

[0129] Take the first step control command Send to the execution end. Among them, This is the optimal input vector for the first control step. and These are the optimal control inputs for the main power supply and the distributed power supply, respectively. The system state is then updated to enter the next cycle, continuing the rolling optimization to achieve continuous prediction and adjustment.

[0130] When the actual measured power Compared with the predicted value The error between them satisfies:

[0131] or energy deviation The system immediately triggers the safety handover logic:

[0132] in, The power error threshold, To safely switch the trigger flag, the current control commands are frozen, power transfer operations are paused, and a safe waiting state is entered. The controller re-identifies the system matrix. , The prediction model is reconstructed and then resumed.

[0133] It should also be noted that the core challenge in multi-source switching scenarios is how to achieve continuous power transition. Traditional switching control relies on simple phase angle synchronization or fixed delay logic, and the switching point often experiences sudden power changes, leading to short-term voltage drops, frequency drift, and system oscillations. Although existing research has proposed power sharing methods based on droop control, it still cannot guarantee the energy balance and continuity of the switching process. This paper subdivides the switching process into a synchronization stage, a power sharing stage, and a switching transition stage, and introduces a predictive control algorithm to achieve multi-step rolling optimization. This realizes the transformation of switching control from passive triggering to active prediction, which can adjust the power output curve in advance before the energy deviation exceeds the limit, making the power change continuously differentiable. By using the energy deviation signal as a feedback variable and the dynamic prediction model as a feedforward compensation, the paper achieves the integration of energy-level closed-loop control and time-domain optimization. This solves the engineering problem of how to maintain the continuity of the power curve during multi-source switching, enabling the distribution network to have dynamic stability and disturbance rejection capability during switching.

[0134] This invention provides an automatic switching method for multiple power sources in a distribution network. By establishing a dynamic power flow model, it achieves real-time reconstruction of the power flow distribution under topology switching, enabling the system to have adaptive response capabilities. A transient energy function method is used to quantitatively evaluate the system's kinetic and potential energy, and a stability criterion based on energy difference and critical threshold is proposed, realizing energy self-sensing and self-constrained control during the switching process. By combining staged soft switching with predictive control algorithms, continuous power transition between the main power source and distributed power sources is achieved under energy deviation constraints, reducing voltage fluctuations and transient impacts caused by switching. This invention transforms multi-power source systems from static control to dynamic energy coordination control, forming a closed-loop mechanism from modeling and stability assessment to control, effectively improving the stability, robustness, and intelligence level of the distribution network under complex operating conditions.

[0135] This embodiment also provides an automatic switching system for multiple power sources in a distribution network. This system is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the systems described in the following embodiments are preferably implemented in software, hardware implementations, or a combination of software and hardware, are also possible and contemplated.

[0136] This embodiment provides an automatic switching system for multiple power sources in a distribution network, such as... Figure 2 As shown, it includes: The dynamic response analysis module 21 is used to dynamically model the transient power flow of the main power source and distributed power sources in a multi-power source distribution network and perform dynamic response analysis of topology changes.

[0137] The equilibrium state analysis module 22 is used to evaluate the system energy obtained by dynamic modeling using the transient energy function method, calculate the kinetic and potential energy components before and after switching, and determine the system energy equilibrium state based on the comparison results of the energy difference and the critical energy threshold.

[0138] The switching control module 23 is used to perform phased soft switching control based on the energy assessment results. Through the sequential control logic of the synchronization phase, power sharing phase and switching transition phase, the main power supply and distributed power supply are gradually switched according to the predictive control algorithm.

[0139] The automatic switching system for multiple power sources in a distribution network provided in this embodiment of the invention can execute the automatic switching method for multiple power sources in a distribution network provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the various modules and units described above are the same as in the corresponding embodiments described above, and will not be repeated here.

[0140] This invention provides an automatic switching system for multiple power sources in a distribution network. By establishing a dynamic power flow model, it achieves real-time reconstruction of power flow distribution under topology switching, enabling the system to have adaptive response capabilities. It employs the transient energy function method to quantitatively evaluate the system's kinetic and potential energy, and proposes a stability criterion based on energy difference and critical threshold, realizing energy self-sensing and self-constrained control during the switching process. By combining staged soft switching with predictive control algorithms, it achieves continuous power transition between the main power source and distributed power sources under energy deviation constraints, reducing voltage fluctuations and transient impacts caused by switching. This invention transforms multi-power source systems from static control to dynamic energy coordination control, forming a closed-loop mechanism from modeling and stability assessment to control, effectively improving the stability, robustness, and intelligence level of the distribution network under complex operating conditions.

[0141] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0142] The following is a detailed reference. Figure 3The diagram illustrates a structural schematic suitable for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 301, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 302 or a program loaded from memory 308 into random access memory (RAM) 303. The RAM 303 also stores various programs and data required for the operation of the electronic device. The processor 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0143] Typically, the following devices can be connected to I / O interface 305: input devices 306 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 307 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 308 including, for example, magnetic tapes, hard disks, etc.; and communication devices 309. Communication device 309 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 3 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0144] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 309, or installed from a memory 308, or installed from a ROM 302. When the computer program is executed by the processor 301, it performs the functions defined in the automatic switching method for multiple power sources in a distribution network according to embodiments of the present invention.

[0145] Figure 3 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0146] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the automatic switching method for multiple power sources in a power distribution network shown in the above embodiments is implemented.

[0147] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0148] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. An automatic switching method for multiple power sources in a power distribution network, characterized in that, The method includes: Dynamic modeling of transient power flow between main power sources and distributed power sources in multi-source power distribution networks is performed, and dynamic response analysis of topology changes is conducted. The transient energy function method is used to evaluate the system energy obtained from dynamic modeling, calculate the kinetic and potential energy components before and after switching, and determine the system energy balance state based on the comparison between the energy difference and the critical energy threshold. Based on the energy assessment results, phased soft switching control is implemented. Through sequential control logic of synchronization phase, power sharing phase and switching transition phase, the power transition between main power supply and distributed power supply is carried out step by step according to the predictive control algorithm.

2. The automatic switching method for multiple power sources in a distribution network according to claim 1, characterized in that, Dynamic modeling of transient power flow between primary and distributed power sources in multi-source power distribution networks is performed, along with dynamic response analysis of topology changes, including: Between the nodes of the main power supply and the distributed power supply, the power balance relationship of each node is calculated by real-time monitoring of node voltage and current signals, and a transient power flow dynamic model is automatically generated. Voltage phase angle, frequency change, node power and inverter control parameters are used as variables in the transient power flow dynamic model, and the voltage transfer characteristics between nodes are calculated within the admittance matrix framework of the distribution network. For distributed power sources, the output stage, filtering stage, current control stage, and voltage control stage of the inverter they are configured with are combined and modeled as a dynamic response module. When the network topology changes, an internal topology switching command is triggered, which automatically reconstructs the node connection relationships and power flow direction.

3. The automatic switching method for multiple power sources in a distribution network according to claim 2, characterized in that, When the network topology changes, an internal topology switching command is triggered, automatically reconstructing node connectivity and power flow direction, including: When the network topology changes, the connection status, voltage deviation and frequency deviation between the main power supply and the distributed power supply are detected in real time. When both voltage deviation and frequency deviation exceed the set threshold, it is automatically determined to be in an asynchronous state and a topology reconfiguration operation is initiated. During topology reconfiguration, the bus connection relationship is adjusted through the control logic of the switch matrix, so that the electrical connection of the corresponding node is updated in real time. During the switching process, transient voltage and current data of each node are collected and input into the transient power flow dynamic model to recalculate the power flow distribution.

4. The automatic switching method for multiple power sources in a distribution network according to claim 1, characterized in that, The transient energy function method is used to evaluate the system energy obtained from dynamic modeling. The kinetic and potential energy components before and after the switching are calculated. The system energy balance state is determined based on the comparison between the energy difference and the critical energy threshold, including: Substitute the system state variables output from the transient power flow dynamic model into the energy analysis module, and add the kinetic energy term corresponding to the frequency change and the potential energy term corresponding to the voltage offset to obtain the total system energy. The total system energy is calculated before and after each power switching action, and the difference is obtained as the transient energy change. When the transient energy change is below the critical energy threshold, the system is determined to be in a stable state, and power transfer is allowed. When the transient energy change is not lower than the critical energy threshold, the switching is temporarily suspended and the power output rate is adjusted to reduce the energy fluctuation amplitude.

5. The automatic switching method for multiple power sources in a distribution network according to claim 4, characterized in that, When the transient energy change is not lower than the critical energy threshold, the switching is temporarily suspended, and the power output rate is adjusted to reduce the energy fluctuation amplitude, including: When the transient energy change is lower than the critical energy threshold, the optimal power transfer increment is calculated based on the current trend of the total energy change of the system. Synchronization control signals are sent to the distributed power source and the main power source to adjust their output power curves respectively, so that the output power of the main power source gradually decreases while the output power of the distributed power source gradually increases.

6. The automatic switching method for multiple power sources in a distribution network according to claim 1, characterized in that, Based on energy assessment results, phased soft switching control is implemented. Through sequential control logic comprising a synchronization phase, a power sharing phase, and a switching transition phase, a predictive control algorithm is used to gradually transition power between the main power source and distributed power sources, including: During the synchronization phase, phase angle tracking control is used to gradually make the output voltage phase angle of the distributed power source and the voltage phase angle of the main power source consistent. When the phase angle difference is less than a predetermined threshold, the synchronization is considered complete. During the power sharing phase, a feedback control strategy based on voltage and frequency offset is adopted to dynamically adjust the active and reactive power outputs of the main power supply and distributed power supply according to the current load distribution ratio, and share the load according to a predetermined ratio. When the power distribution is detected to have reached a stable state, the switching transition phase is entered. During the switching transition phase, based on the feedback energy deviation signal, the output power of the main power supply is reduced in stages, while the output power of the distributed power supply is increased proportionally, so that the total power change curve is continuous and smooth.

7. The automatic switching method for multiple power sources in a distribution network according to claim 6, characterized in that, Based on energy assessment results, phased soft switching control is implemented. This involves sequential control logic through synchronization, power sharing, and switching transition phases, and a predictive control algorithm to gradually transition power between the main power source and distributed power sources. The system also includes: During the soft handover execution, the operating status of the system for several future sampling periods is predicted, and the optimal adjustment of each control variable is calculated in real time with the goal of minimizing power deviation and voltage deviation. Within each control cycle, based on the latest measured voltage, current, frequency, and energy difference, the system state at the next moment is predicted, and optimized control quantities are generated. The power output commands of the main power supply and distributed power supply are updated on a rolling basis according to the prediction results, so that the power output curve always meets the energy balance condition. When the system detects that the deviation between the predicted value and the actual measured value exceeds the set range, it immediately resets the parameters of the prediction model and triggers the safety switching logic, suspends power transfer, and rebuilds the prediction model.

8. An automatic switching system for multiple power sources in a power distribution network, characterized in that, The system includes: The dynamic response analysis module is used to dynamically model the transient power flow of main power sources and distributed power sources in multi-source power distribution networks and perform dynamic response analysis of topology changes. The equilibrium state analysis module is used to evaluate the system energy obtained from dynamic modeling using the transient energy function method, calculate the kinetic and potential energy components before and after switching, and determine the system energy equilibrium state based on the comparison results of the energy difference and the critical energy threshold. The switching control module is used to perform phased soft switching control based on energy assessment results. Through sequential control logic of synchronization phase, power sharing phase and switching transition phase, it performs gradual power transition between main power supply and distributed power supply according to predictive control algorithm.

9. An electronic device, characterized in that, include: The system includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes the computer instructions to perform the automatic switching method for multiple power sources in a power distribution network as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the automatic switching method for multiple power sources in a distribution network as described in any one of claims 1 to 7.

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