A post-fault recovery control method for a flexible soft-switching power distribution network
By selecting a new master station after a fault and optimizing load transfer scheduling, the problem of slow fault response in flexible interconnected distribution networks was solved, enabling rapid recovery of critical loads and smooth system transition, thus improving power supply reliability and economy.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- INTELLIGENT DISTRIBUTION NETWORK CENT OF STATE GRID JIBEI ELECTRIC POWER CO LTD
- Filing Date
- 2026-05-11
- Publication Date
- 2026-06-09
AI Technical Summary
Existing flexible interconnected distribution networks with flexible soft switches lack systematic control schemes when faults occur, resulting in slow fault response, low power supply recovery rate for important loads, and the recovery process is prone to secondary disturbances.
A post-fault recovery control method is adopted, which selects a new master station by calculating dynamic capacity margin and electrical distance, establishes a mixed integer second-order cone programming model for load transfer optimization scheduling, and uses energy storage system to suppress DC voltage fluctuations during the switching transient process, so as to achieve a smooth transition from the fault state to the normal state.
It enables rapid transfer and smooth restoration of critical loads, reduces the impact of power outages, balances power supply reliability and economy, and avoids secondary disturbances.
Smart Images
Figure CN122178315A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of power system distribution network technology, and in particular to a fault recovery control method for a distribution network containing flexible soft switches. Background Technology
[0002] As the energy transition deepens, the power distribution network exhibits high uncertainty on both the source and load sides, posing a severe challenge to system operation. On the source side, large-scale integration of distributed power sources such as wind and solar power into the distribution network results in highly random and fluctuating output due to weather conditions. The intermittent output of individual distributed power sources and the spatiotemporal correlation between multiple distributed power sources make accurate prediction of power flow distribution in the distribution network difficult. On the load side, the rapid growth of new loads such as electric vehicle charging loads and data centers exacerbates the uncertainty of load fluctuations due to their randomness. Furthermore, the flexibility of these new loads, while increasing flexibility, also complicates control measures. The high penetration rate of renewable energy integration makes bidirectional power flow in the distribution network the norm, significantly increasing risks such as voltage exceeding limits and network congestion.
[0003] In the context of new power system construction, the traditional radial structure and operation mode are no longer sufficient to meet the higher requirements for power supply quality and reliability of distribution networks. Regarding power supply reliability, traditional distribution networks adopt an open-loop radial operation mode, requiring mechanical switches for load transfer during faults or maintenance. This transfer operation is time-consuming and complex, leading to prolonged power outages and failing to meet users' urgent needs for highly reliable power supply. Technological advancements in flexible interconnection devices such as flexible soft switches (SOPs) have provided a technical foundation for flexible interconnection between feeders and rapid power transfer. However, systematic control schemes are still lacking in areas such as master station selection strategies under fault conditions, optimized scheduling of rapid load transfer, and reconstruction of normal operation after fault recovery.
[0004] To address the aforementioned technical deficiencies, a solution is proposed. Summary of the Invention
[0005] The purpose of this invention is to address the problem that while existing flexible interconnected distribution networks with flexible soft switches (SOPs) can achieve flexible power distribution between feeders, in the event of a sudden fault, the system must complete the following in a very short time without any prior warning: reselection of the master station and switching of the control mode, rapid transfer of power to the power-loss area, and smooth restoration to normal operation after the fault is cleared. These three stages are time-sensitive and interdependent. Existing technologies lack a systematic control scheme that covers the entire fault process, resulting in slow fault response, low power restoration rate for important loads, and the risk of secondary disturbances during the restoration process.
[0006] To achieve the above objectives, the present invention adopts the following technical solution: a post-fault recovery control method for a distribution network containing flexible soft switches, comprising the following steps: Step 1: After a fault occurs, the original master station converter is taken out of service. The active power, reactive power and rated capacity of the remaining converters are collected to calculate the dynamic capacity margin. The electrical distance from each converter node to the system load center is calculated. A comprehensive score is obtained by weighting the capacity margin and electrical distance. The converter with the highest comprehensive score and a capacity margin greater than the preset threshold is selected as the new master station, and the control mode of the new master station is switched. Step 2: Based on the new master station and with the fault duration as the optimization period, establish an optimization model objective function that minimizes the sum of the main grid power purchase cost, total system loss, distribution transformer load rate balance, load shedding penalty, distribution transformer switching penalty, and master station switching impact penalty. This model is a mixed integer second-order cone programming model that satisfies the system operation constraints. Solve the model to obtain the load transfer optimization scheduling scheme for each converter power command and distribution transformer switching status. Step 3: After the fault is cleared, the operating status at the time the fault ended is used as the initial condition to redetermine the master station for the recovery phase; Step 4: After all loads are restored, switch the converter to the optimal power allocation scheme for normal operation and restore the master-slave control to normal operation.
[0007] Furthermore, the calculation process for the dynamic capacity margin index is as follows: S11. Obtain and analyze the active power, reactive power and rated capacity data of the remaining converters. S12. Calculate the static capacity margin index according to the following formula. : in, For the first The rated capacity of the converter, P i Q represents the current active power output. i This represents the current reactive power output. S13. Combined with the load distribution of the faulted feeder, the dynamic capacity margin index is calculated.
[0008] Furthermore, the electrical distance from each converter node to the system load center is the equivalent impedance modulus of the line resistance and reactance of each segment on the transmission path between the converter node and the system load center.
[0009] Furthermore, the process of selecting a new master station is as follows: a comprehensive score for the master station is constructed by combining dynamic capacity margin and electrical location advantages. The higher the score, the more suitable it is to serve as the master station. From the converters that meet the capacity margin threshold constraints, the one with the highest comprehensive score is selected as the new master station.
[0010] Furthermore, the process of switching the control mode of the new master station is as follows: When switching the control mode, measures such as voltage amplitude ramp start, phase continuity guarantee, and active and reactive power distribution command generation are adopted. The energy storage system is used to automatically respond to DC voltage deviation during the master station switching process through a virtual DC motor control strategy, providing power buffer and inertia support for the DC bus and suppressing DC voltage fluctuations during the switching transient process.
[0011] Furthermore, the calculation process of the objective function of the optimization model is as follows: S21. Obtain and analyze data on main grid electricity purchase cost, total system loss, distribution transformer load balance, load shedding penalty, distribution transformer switching penalty and main station switching impact penalty. S22. The objective function of the optimization model is derived from the following formula: in, Main grid electricity purchase cost, For the total system loss, To balance the load rate of distribution transformers, As a load shedding penalty, Penalty for switching on the distribution transformer. Main site switching impact penalty The preset electricity cost weighting coefficient, The preset loss weighting coefficient, The preset load weighting coefficient, The preset load weighting coefficient, The preset state transition weight coefficient, This is the preset main site switching weight coefficient.
[0012] Furthermore, the specific operational constraints include: System source-load balance constraint: The sum of system power supply meeting load demand and system losses at each time period; AC network constraints: node voltage safety constraints, line load capacity constraints, and distribution transformer load rate economic operating range constraints; Converter operating constraints: active and reactive power transmission balance constraints, converter AC / DC voltage relationship constraints, and converter capacity constraints; DC network constraints: DC power balance constraints, DC node voltage safety constraints, and transmission capacity constraints; Energy storage operation constraints: charging and discharging power constraints, and safe state of charge range constraints; Distribution transformer fault status constraint: The switching variable corresponding to the distribution transformer in the fault outage state is forcibly set to zero.
[0013] Furthermore, the process of redefining the main site during the recovery phase is as follows: S31. During the recovery phase, the selection of the master station is based on the actual operating state at the end of the fault state as the initial condition, ensuring that each independent power supply zone has one and only one master station. The power supply capacity constraint of the master station requires that the rated capacity of the selected master station must meet the net load demand within the zone and reserve a backup margin. The voltage source converter of the selected master station adopts constant DC voltage control, while the other voltage source converters adopt power control. S32. After redetermining the master station for the recovery phase, construct the recovery phase optimization model. The objective function of the recovery phase optimization model is: in, Main grid electricity purchase cost, For the total system loss, To balance the load rate of distribution transformers, Penalty for switching on the distribution transformer. The preset electricity cost weighting coefficient, The preset loss weighting coefficient, The preset load weighting coefficient, The preset state switching weight coefficient.
[0014] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: (1) Priority protection for critical loads. By using a master station selection mechanism based on dynamic capacity margin and electrical distance comprehensive assessment, a stable voltage and frequency reference is quickly established for the power outage area; by using load shedding penalty sub-targets and load tiered and phased recovery strategies, priority is given to ensuring uninterrupted power supply to first-level critical loads when the transfer capacity is limited, effectively reducing the impact of power outages on sensitive users.
[0015] (2) Multi-objective coordination optimization. Taking into account objectives such as electricity purchase cost, system loss, distribution transformer load balance, load shedding penalty, switching impact suppression and master station switching impact suppression, the mixed integer second-order cone programming algorithm is used to solve the problem and achieve the coordination and unity of power supply reliability and system economy.
[0016] (3) Smooth post-fault recovery. Based on the state continuation constraint, the master station reselects a scheme, and with the SOP power feedforward pre-adjustment and the orderly switching and coordination control of distribution transformers, the system can achieve a safe and smooth transition from the fault operation state to the normal operation state, avoiding secondary disturbances. Attached Figure Description
[0017] Figure 1 A schematic diagram of the method flow of the present invention is shown; Figure 2 A schematic diagram of the five-terminal flexible interconnection power distribution of the present invention is shown. Detailed Implementation
[0018] 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, and 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.
[0019] Example 1: like Figure 1 As shown, a fault recovery control method for a distribution network with flexible switching includes the following steps: Step 1: After a fault occurs, the original master station converter is taken out of service. The active power, reactive power and rated capacity of the remaining converters are collected to calculate the dynamic capacity margin. The electrical distance from each converter node to the system load center is calculated. A comprehensive score is obtained by weighting the capacity margin and electrical distance. The converter with the highest comprehensive score and a capacity margin greater than the preset threshold is selected as the new master station, and the control mode of the new master station is switched. The calculation process for the dynamic capacity margin index is as follows: S11. Obtain and analyze the active power, reactive power and rated capacity data of the remaining converters. S12. Calculate the static capacity margin index according to the following formula. : in, For the first The rated capacity of the converter, P i Q represents the current active power output. i This represents the current reactive power output. S13. Combined with the load distribution of the faulted feeder, the dynamic capacity margin index is calculated.
[0020] The electrical distance from each converter node to the system load center is the equivalent impedance modulus of the line resistance and reactance of each segment on the transmission path between the converter node and the system load center.
[0021] The process of selecting a new master station is as follows: A comprehensive score is constructed by combining dynamic capacity margin and electrical location advantages. A higher score indicates greater suitability as the master station. Typically, the weight of capacity margin is increased in capacity-constrained scenarios, while the weight of electrical location is increased in voltage-sensitive scenarios. From the converters that meet the capacity margin threshold constraints, the one with the highest comprehensive score is selected as the new master station. The entire scoring and decision-making process is completed within 100 milliseconds.
[0022] The process of switching the control mode of the new master station is as follows: When switching the control mode, measures such as voltage amplitude ramp start, phase continuity guarantee, and active and reactive power distribution command generation are adopted. The energy storage system is used to automatically respond to DC voltage deviation during the master station switching process through a virtual DC motor control strategy, providing power buffer and inertia support for the DC bus and suppressing DC voltage fluctuations during the switching transient process.
[0023] Step 2: Based on the new master station and with the fault duration as the optimization period, establish an optimization model objective function that minimizes the sum of the main grid power purchase cost, total system loss, distribution transformer load rate balance, load shedding penalty, distribution transformer switching penalty, and master station switching impact penalty. This model is a mixed integer second-order cone programming problem that satisfies the system operation constraints. Solving this model yields the load transfer optimization scheduling scheme for each converter power command and distribution transformer switching status. It should be noted that the solution algorithm uses the second-order cone relaxation method to transform the model into a mixed integer second-order cone programming problem, which can be solved efficiently using mature commercial solvers. The calculation process of the objective function of the optimization model is as follows: S21. Obtain and analyze data on main grid electricity purchase cost, total system loss, distribution transformer load balance, load shedding penalty, distribution transformer switching penalty and main station switching impact penalty. S22. The objective function of the optimization model is derived from the following formula: in, Main grid electricity purchase cost, For the total system loss, To balance the load rate of distribution transformers, As a load shedding penalty, Penalty for switching on the distribution transformer. Main site switching impact penalty The preset electricity cost weighting coefficient, The preset loss weighting coefficient, The preset load weighting coefficient, The preset load weighting coefficient, The preset state transition weight coefficient, This is the preset main site switching weight coefficient.
[0024] The specific runtime constraints include: System source-load balance constraint: The system power supply (main grid power purchase, distributed photovoltaic, wind power, energy storage discharge) at each time period must meet the sum of load demand and system losses; AC network constraints: node voltage safety constraints, line load capacity constraints, and distribution transformer load rate economic operating range constraints; Converter operating constraints: active and reactive power transmission balance constraints, converter AC / DC voltage relationship constraints, and converter capacity constraints; DC network constraints: DC power balance constraints, DC node voltage safety constraints, and transmission capacity constraints; Energy storage operation constraints: charge and discharge power constraints, state of charge (SOC) safety range constraints; Distribution transformer fault status constraint: The switching variable corresponding to the distribution transformer in the fault outage state is forcibly set to zero.
[0025] Step 3: After the fault is cleared, the operating status at the time the fault ended is used as the initial condition to redetermine the master station for the recovery phase; Step 4: After all loads are restored, switch the converter to the optimal power allocation scheme for normal operation and restore the master-slave control to normal operation.
[0026] The process of re-determining the main site for the recovery phase is as follows: S31. During the recovery phase, the selection of the master station is based on the actual operating state at the end of the fault state as the initial condition, ensuring that each independent power supply zone has one and only one master station. The power supply capacity constraint of the master station requires that the rated capacity of the selected master station must meet the net load demand within the zone and reserve a certain spinning reserve margin. Furthermore, the voltage source converter (VSC) of the selected master station adopts constant DC voltage control (V / f control), while the other voltage source converters (VSC) adopt power control (PQ control). S32. After redetermining the master station for the recovery phase, construct the recovery phase optimization model. The objective function of the recovery phase optimization model is: in, Main grid electricity purchase cost, For the total system loss, To balance the load rate of distribution transformers, Penalty for switching on the distribution transformer. The preset electricity cost weighting coefficient, The preset loss weighting coefficient, The preset load weighting coefficient, The preset state switching weight coefficient.
[0027] This invention establishes a stable voltage and frequency reference for power outage areas by using a master station selection mechanism based on a comprehensive assessment of dynamic capacity margin and electrical distance. By employing load shedding penalty sub-objectives and a graded and phased load recovery strategy, it prioritizes uninterrupted power supply to critical loads when transfer capacity is limited, effectively reducing the impact of power outages on sensitive users.
[0028] Meanwhile, taking into account objectives such as electricity purchase costs, system losses, distribution transformer load balance, load shedding penalties, switching impact suppression, and master station switching impact suppression, a mixed integer second-order cone programming algorithm is used to solve the problem, thereby achieving a coordinated balance between power supply reliability and system economy.
[0029] Furthermore, by reselecting a scheme based on state continuity constraints, and in conjunction with SOP power feedforward pre-adjustment and orderly switching coordination control of distribution transformers, a safe and smooth transition of the system from fault operation state to normal operation state can be achieved, avoiding secondary disturbances.
[0030] Example 2: like Figure 2 As shown, a five-terminal flexible interconnected power distribution system is used as an example for explanation. The system consists of five feeders interconnected through a common DC bus. Each feeder is connected to the DC bus via a back-to-back voltage source converter. An energy storage system is configured on the DC side, and each feeder is connected to distributed photovoltaic, wind power, and various types of loads. During normal operation, the system adopts a master-slave control architecture, with one converter acting as the master station to maintain the stability of the DC bus voltage, and the remaining converters acting as slave stations operating according to power commands.
[0031] (1) Fault Triggering and Master Station Reselection: After the distribution network automation system detects a fault signal, the faulty feeder circuit breaker trips, and the corresponding converter (the original master station) goes out of operation, disrupting the power balance of the DC bus. The system immediately performs a comprehensive evaluation of the remaining converters: calculating the dynamic capacity margin based on the load distribution from the faulty feeder; calculating the current load center of gravity of the system to obtain the electrical position superiority index of each converter; calculating the comprehensive score according to the set weights, and selecting the converter with the highest score and a dynamic capacity margin of not less than 30% as the new master station.
[0032] (2) Online optimization of fault-state load transfer: After the new master station is confirmed, the system initiates online optimization for fault-state load transfer. During the recovery strategy formulation phase: using the current system state as input and the fault duration T as the optimization period, a mixed-integer second-order cone programming model with multiple objectives is solved to generate a load transfer plan.
[0033] (3) Restoration to normal operation after a fault: After the fault is repaired, the system state at the final moment of the fault is used as the initial condition for the recovery phase. First, the master station is reselected: based on the uniqueness and capacity constraints of the master station, combined with the state continuation constraints, the master station for the recovery phase is re-determined. Then, distribution transformers are coordinated for orderly switching, and loads are restored in three phases: the first phase restores primary critical loads, the second phase restores secondary loads, and the third phase restores tertiary ordinary loads. Finally, all distribution areas in the system are restored to normal power supply, and the converters switch to the optimal power allocation scheme for normal operation.
[0034] The size of the interval and threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by those skilled in the art for each set of sample data; as long as it does not affect the ratio between the parameter and the quantized value.
[0035] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation. The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.
Claims
1. A fault recovery control method for a distribution network containing flexible soft switches, characterized in that, Includes the following steps: Step 1: After a fault occurs, the original master station converter is taken out of service. The active power, reactive power and rated capacity of the remaining converters are collected to calculate the dynamic capacity margin. The electrical distance from each converter node to the system load center is calculated. A comprehensive score is obtained by weighting the capacity margin and electrical distance. The converter with the highest comprehensive score and a capacity margin greater than the preset threshold is selected as the new master station, and the control mode of the new master station is switched. Step 2: Based on the new master station and with the fault duration as the optimization period, establish an optimization model objective function that minimizes the sum of the main grid power purchase cost, total system loss, distribution transformer load rate balance, load shedding penalty, distribution transformer switching penalty, and master station switching impact penalty. This model is a mixed integer second-order cone programming model that satisfies the system operation constraints. Solve the model to obtain the load transfer optimization scheduling scheme for each converter power command and distribution transformer switching status. Step 3: After the fault is cleared, the operating status at the time the fault ended is used as the initial condition to redetermine the master station for the recovery phase; Step 4: After all loads are restored, switch the converter to the optimal power allocation scheme for normal operation and restore the master-slave control to normal operation.
2. The fault recovery control method for a distribution network with flexible soft switches according to claim 1, characterized in that, The calculation process for the dynamic capacity margin index is as follows: S11. Obtain and analyze the active power, reactive power and rated capacity data of the remaining converters. S12. Calculate the static capacity margin index according to the following formula. : in, For the first The rated capacity of the converter, P i Q represents the current active power output. i This represents the current reactive power output. S13. Combined with the load distribution of the faulted feeder, the dynamic capacity margin index is calculated.
3. The fault recovery control method for a distribution network with flexible soft switches according to claim 1, characterized in that, The electrical distance from each converter node to the system load center is the equivalent impedance modulus of the line resistance and reactance of each segment on the transmission path between the converter node and the system load center.
4. The fault recovery control method for a distribution network with flexible soft switches according to claim 1, characterized in that, The process of selecting a new master station is as follows: a comprehensive score for the master station is constructed by combining dynamic capacity margin and electrical location advantages. The higher the score, the more suitable it is to serve as the master station. From the converters that meet the capacity margin threshold constraints, the one with the highest comprehensive score is selected as the new master station.
5. The fault recovery control method for a distribution network with flexible soft switches according to claim 1, characterized in that, The process of switching the control mode of the new master station is as follows: When switching the control mode, measures such as voltage amplitude ramp start, phase continuity guarantee, and active and reactive power distribution command generation are adopted. The energy storage system is used to automatically respond to DC voltage deviation during the master station switching process through a virtual DC motor control strategy, providing power buffer and inertia support for the DC bus and suppressing DC voltage fluctuations during the switching transient process.
6. The fault recovery control method for a distribution network with flexible soft switches according to claim 1, characterized in that, The calculation process of the objective function of the optimization model is as follows: S21. Obtain and analyze data on main grid electricity purchase cost, total system loss, distribution transformer load balance, load shedding penalty, distribution transformer switching penalty and main station switching impact penalty. S22. The objective function of the optimization model is derived from the following formula: in, Main grid electricity purchase cost, For the total system loss, To balance the load rate of distribution transformers, As a load shedding penalty, Penalty for switching on the distribution transformer. Main site switching impact penalty The preset electricity cost weighting coefficient, The preset loss weighting coefficient, The preset load weighting coefficient, The preset load weighting coefficient, The preset state transition weight coefficient, This is the preset main site switching weight coefficient.
7. The fault recovery control method for a distribution network with flexible soft switches according to claim 1, characterized in that, The specific runtime constraints include: System source-load balance constraint: The sum of system power supply meeting load demand and system losses at each time period; AC network constraints: node voltage safety constraints, line load capacity constraints, and distribution transformer load rate economic operating range constraints; Converter operating constraints: active and reactive power transmission balance constraints, converter AC / DC voltage relationship constraints, and converter capacity constraints; DC network constraints: DC power balance constraints, DC node voltage safety constraints, and transmission capacity constraints; Energy storage operation constraints: charging and discharging power constraints, and safe state of charge range constraints; Distribution transformer fault status constraint: The switching variable corresponding to the distribution transformer in the fault outage state is forcibly set to zero.
8. The fault recovery control method for a distribution network with flexible soft switches according to claim 1, characterized in that, The process of re-determining the main site for the recovery phase is as follows: S31. During the recovery phase, the selection of the master station is based on the actual operating state at the end of the fault state as the initial condition, ensuring that each independent power supply zone has one and only one master station. The power supply capacity constraint of the master station requires that the rated capacity of the selected master station must meet the net load demand within the zone and reserve a backup margin. The voltage source converter of the selected master station adopts constant DC voltage control, while the other voltage source converters adopt power control. S32. After redetermining the master station for the recovery phase, construct the recovery phase optimization model. The objective function of the recovery phase optimization model is: in, Main grid electricity purchase cost, For the total system loss, To balance the load rate of distribution transformers, Penalty for switching on the distribution transformer. The preset electricity cost weighting coefficient, The preset loss weighting coefficient, The preset load weighting coefficient, The preset state switching weight coefficient.