Transformer area micro-grid mutual aid regulation and control operation method and system considering flexible interconnection device and topology flexibility

Abstract

The invention belongs to the technical field of intelligent power distribution networks, distributed energy management and energy internet, and particularly relates to a transformer area micro-grid mutual aid regulation and control operation method and system considering a flexible interconnection device and topology flexibility. Acquiring basic data; constructing a node power flow balance model containing a flexible interconnection device, taking energy storage of each transformer area as an independent regulation and control unit, and establishing an energy storage operation model in combination with charge state constraint, capacity limitation, charge and discharge mutual exclusion and life constraint; virtual commodity flow constraints and spanning tree structure constraints are introduced, and a radiation type topology model capable of being dynamically switched is constructed; constructing a comprehensive optimization model, and solving by utilizing power flow-topology-energy storage coupling constraint to obtain a multi-transformer-area global optimal scheduling scheme; and outputting an optimal topological structure, a flexible interconnection device power instruction and an energy storage charging and discharging scheme. According to the invention, a traditional fixed topology and isolated energy storage scheduling mode is broken through, a unified optimization mechanism of power flow-topology-energy storage linkage is established, and active and flexible operation of the power distribution network is realized.

Description

Technical Field

[0001] This invention belongs to the fields of smart distribution network, distributed energy management and energy internet technology, and in particular, it is a method and system for mutual regulation and control of microgrids in distribution areas that considers flexible interconnection devices and topological flexibility. Background Technology

[0002] The high proportion of distributed renewable energy (such as photovoltaic and wind power) is gradually becoming the norm for distribution network operation. At the same time, the rapid development of power electronics and information technology, as well as the large-scale integration of new loads such as electric vehicles and distributed energy storage, have significantly changed the operating characteristics of distribution network areas, and their uncertainty, dynamism, and complexity are constantly increasing.

[0003] On the one hand, the volatility and unpredictability of distributed energy significantly increase the operational risks of the distribution network. Photovoltaic output is severely affected by weather conditions, easily leading to problems such as voltage exceeding limits and power flow reversal; at the same time, the accumulation of renewable energy output prediction errors makes it difficult for traditional scheduling modes based on deterministic plans to guarantee real-time performance and reliability. The operation of the power grid under high-proportion renewable energy integration exhibits complex characteristics of multi-timescale coupling and multi-source randomness superposition.

[0004] On the other hand, while the types of flexible resources at the distribution substation level are abundant, their utilization efficiency is low. Typical resources include battery energy storage systems (BESS), electric vehicles (EVs), and interruptible loads on the user side. Energy storage has rapid adjustment capabilities, but under isolated operation conditions in a single distribution substation, its charging and discharging behavior is limited by local load and electricity price changes, making system-level coordinated optimization impossible. Electric vehicles, as mobile energy storage units, have increased load fluctuations due to their random charging characteristics and the uncertainty of travel behavior. While building loads such as HVAC systems are adjustable, they struggle to participate in rapid dynamic response while ensuring comfort. Overall, the potential flexibility of various resources within a distribution substation has not been fully explored, and the mechanism for cross-distribution substation collaborative optimization remains imperfect.

[0005] Furthermore, existing distribution network dispatching methods generally suffer from fixed topology structures and limited optimization strategies. Traditional dispatching is primarily based on centralized optimization models, requiring modeling and unified solutions for the entire system, resulting in high computational complexity, heavy communication load, and poor real-time performance. While heuristic or rule-based dispatching methods offer fast computation speeds, they lack adaptability and coordination, making it difficult to balance economy and security. In operating environments with high renewable energy penetration, frequent power flow reversals, and significant voltage limit exceedance risks, relying solely on static distribution network structures and isolated dispatching methods is insufficient to meet the demands for flexible operation.

[0006] To address the aforementioned issues, there is an urgent need for a collaborative scheduling method that integrates the power flow regulation capabilities of flexible interconnected devices (SOPs) with topology flexibility reconfiguration mechanisms. This method would enable active energy sharing and dynamic structural optimization between distribution substations, synergistically leveraging the comprehensive regulation capabilities of energy storage and distributed energy sources. Ultimately, this would allow for the economical, efficient, and clean operation of the distribution network while ensuring power quality and network security. Summary of the Invention

[0007] This invention aims to propose a multi-region energy storage collaborative scheduling method and device based on flexible interconnection and topology flexibility. It achieves cross-region energy mutual assistance by introducing a flexible interconnection device (SOP) and uses virtual flow and spanning tree constraints to flexibly construct the distribution network topology. Furthermore, it integrates multi-region energy storage resources into a unified system-level control framework, significantly improving the distributed photovoltaic absorption capacity and reducing operating costs while ensuring the safe operation of the distribution network. This invention breaks through the traditional fixed topology and isolated energy storage scheduling mode, establishing a unified optimization mechanism linking power flow, topology, and energy storage, enabling proactive and flexible operation of the distribution network.

[0008] To achieve the above objectives, the present invention adopts the following technical solution:

[0009] The first aspect of this invention is to provide a method for coordinated scheduling of multi-area energy storage based on flexible interconnection and topology flexibility, comprising the following steps:

[0010] S1. Collect basic data on the distribution network's basic topology, line parameters, transformer load curves, distributed photovoltaic power output prediction, transformer energy storage capacity and operating parameters, and the capacity and control characteristics of flexible interconnection devices.

[0011] S2. Construct a node power flow balance model with flexible interconnection devices, establish active and reactive power constraints and energy conservation relationships at SOP ports, and clarify the power flow regulation capability of multi-terminal flexible interconnection devices for the power distribution system.

[0012] S3. Treat each transformer area's energy storage as an independent control unit, establish an energy storage operation model by combining state of charge constraints, capacity limits, charge-discharge mutual exclusion and lifetime constraints, and coordinate with the SOP adjustment strategy to achieve coordinated optimization of cross-transformer area energy storage resources.

[0013] S4. Introduce virtual commodity flow constraints and spanning tree structure constraints to construct a dynamically switchable radial topology model. By linking the line switch status with virtual topology variables, the dynamic structure reconfiguration capability of the distribution network is realized, ensuring global connectivity and loop-free operation of the system.

[0014] S5. Construct a comprehensive optimization model with the objectives of minimizing system operating costs, minimizing photovoltaic curtailment, reducing network losses, and suppressing voltage deviations. Solve the model using power flow-topology-energy storage coupling constraints to obtain the global optimal scheduling scheme for multiple transformer areas.

[0015] S6 outputs the optimal topology, power commands for flexible interconnect devices, and energy storage charging and discharging schemes, and completes operation control and achieves closed-loop regulation through the execution layer.

[0016] Furthermore, the node power flow balance model with flexible interconnection devices constructed in S2 includes total power balance constraints, loss-related port active power definitions, port capacity constraints, and voltage operation constraints.

[0017] The total power balance constraint is:

[0018]

[0019] The above formula characterizes the active power balance relationship of multi-terminal flexible interconnection devices under steady-state operating conditions, where Indicates the number of flexible interconnect ports. For the first Active power exchange between each port and the connected distribution network. The internal losses of the flexible interconnect device are equivalent to the first... The equivalent active power carried by the port;

[0020] The loss-related active power at the port is defined as follows:

[0021]

[0022] in This is the equipment loss coefficient. This is reactive power loss;

[0023] The port capacity constraint is expressed as follows:

[0024]

[0025] in This is the rated capacity of the port;

[0026] The voltage operating constraint is expressed as follows:

[0027]

[0028] This formula relates to the bus voltage of the flexible interconnect device. To impose constraints, Upper and lower limits.

[0029] Furthermore, the energy storage operation model described in S3 includes: energy storage state of charge constraints, charge-discharge mutual exclusion constraints, and energy storage safe operation boundary constraints;

[0030] The energy storage state of charge constraint is expressed as follows:

[0031] (2.1)

[0032] The above formula describes the dynamic energy evolution process of an energy storage system. For a moment t Transit Node i The state of charge of energy storage, It is determined by the state of the previous cycle and the charging and discharging behavior of the current cycle, and is also affected by the charging and discharging efficiency. Influence;

[0033] The charge-discharge mutual exclusion constraint is expressed as follows:

[0034] (2.2)

[0035] These represent the charging switch and the discharging switch, respectively.

[0036] The energy storage safety operation boundary constraints are expressed as follows:

[0037] (2.3)

[0038] and This represents the upper limit of charging and discharging power.

[0039] Furthermore, the comprehensive optimization model described in S4 includes a comprehensive operational objective function:

[0040]

[0041] Of which: electricity purchase cost , Price per unit Taiwan District i The power output reflects the cost of electricity purchased by the distribution area from the upper-level power grid; network loss costs. , This is the network loss coefficient. For the line k The current, For the line k impedance, For line aggregation; photovoltaic curtailment penalty items , To cover the cost of light curtailment, Wasted light; SOP loss cost item , Cost of loss at SOP; voltage deviation cost item , For voltage deviation cost, For reference voltage, For nodes i The voltage.

[0042] Furthermore, the comprehensive optimization model described in S4 includes node power balance constraints:

[0043]

[0044] in, and Representing the transformer nodes respectively The exchange of active and reactive power with the upper-level power grid, with positive values ​​representing nodes drawing power from the upper-level power grid; For nodes i The set of adjacent nodes; and Indicates from adjacent nodes Flow to Node Active and reactive power, and This indicates that the node is... Power flow injected into adjacent nodes; and For flexible interconnect devices at nodes The active and reactive power injected are positive values, indicating that electrical energy is injected into the local node. and For nodes The active and reactive power required by the load; and These represent the active and reactive power injected into the grid by the distributed power sources at the node, respectively, and can be zero or positive. Represents nodes The relevant line losses are equivalent to active power.

[0045] Furthermore, the comprehensive optimization model described in S4 includes topology flexibility constraints:

[0046]

[0047] in, For a moment t On the line Virtual goods traffic variables; For a moment t Virtual branch A binary variable representing the open / closed state, where a value of 1 indicates the line is closed and 0 indicates it is open; Represents the root node (Usually chosen as the substation busbar) Injected into the system Unit virtual traffic; formula Ensure that each node except the root node consumes 1 unit of virtual traffic, thereby ensuring that all nodes are connected to the main network; This forces virtual flows to pass only through closed loops, thus binding the virtual flow to the actual topology; Set the number of closed branches as This ensures that the system forms only one spanning tree; Defines the actual switching state of the line. With virtual topology state The logical relationship between them, among which This indicates that the circuit is actually closed. This indicates that the switch is open; this constraint requires that the actual switch state cannot violate the virtual feasible topology, i.e., if... If so, the corresponding line must be disconnected; Then, the line can be closed based on the scheduling strategy. The representation theory allows for feasible topological spaces, while Select the final actual operating topology within the allowed operating range so that network reconstruction does not disrupt the radiation structure.

[0048] A second aspect of the present invention is to provide a microgrid mutual assistance and control operation system for substations that considers flexible interconnection devices and topology flexibility, the system being used to implement the above-described method, the system comprising:

[0049] The data acquisition module is used to collect basic data such as the basic topology of the distribution network, line parameters, transformer load curves, distributed photovoltaic power output prediction, transformer energy storage capacity and operating parameters, and capacity and control characteristics of flexible interconnection devices.

[0050] The flexible interconnection device modeling module is used to construct a node power flow balance model containing flexible interconnection devices, establish active and reactive power constraints and energy conservation relationships at SOP ports, and clarify the power flow regulation capabilities of multi-terminal flexible interconnection devices in the power distribution system.

[0051] The energy storage collaborative scheduling model construction module treats each transformer area's energy storage as an independent control unit, and establishes an energy storage operation model by combining state of charge constraints, capacity limits, charge-discharge mutual exclusion, and lifetime constraints. It also coordinates with the SOP adjustment strategy to achieve coordinated optimization of energy storage resources across transformer areas.

[0052] The power flow and topology flexibility model building module of the distribution network is used to introduce virtual commodity flow constraints and spanning tree structure constraints to build a dynamically switchable radial topology model. By linking the line switch status with virtual topology variables, the dynamic structure reconfiguration capability of the distribution network is realized, ensuring that the system is globally connected and loop-free.

[0053] The integrated optimization model construction and solution module is used to construct an integrated optimization model with the objectives of minimizing system operating costs, minimizing photovoltaic curtailment, reducing network losses, and suppressing voltage deviations. It uses power flow-topology-energy storage coupling constraints to solve the model and obtain the global optimal scheduling scheme for multiple transformer areas.

[0054] The output and execution module is used to output the optimal topology, power commands for flexible interconnect devices, and energy storage charging and discharging schemes. It completes operation control and achieves closed-loop regulation through the execution layer.

[0055] A third aspect of the present invention is to provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method.

[0056] Compared with existing technologies, the multi-area energy storage collaborative scheduling method and system based on flexible interconnection and topology flexibility provided by this invention have the following beneficial effects:

[0057] 1. To achieve active energy exchange and real-time power flow optimization among multiple transformer substations, this invention introduces flexible interconnection devices and constructs a power flow-topology-energy storage coupled control framework, enabling bidirectional power exchange and dynamic power flow optimization between different transformer substations. Compared with the traditional fixed topology and isolated control mode, it can significantly improve voltage stability and line utilization efficiency.

[0058] 2. Constructing a virtual flow-guided topology flexibility mechanism to unleash the potential of the network structure: This invention utilizes a virtual commodity flow model and radial structure constraints to achieve dynamic reconfigurability of the distribution network topology, enabling the network structure to adaptively adjust in real time according to load changes and renewable energy output. This overcomes the local bottlenecks and voltage over-limit problems caused by the static operation of traditional distribution networks, significantly improving system flexibility and adaptability.

[0059] 3. To achieve cross-regional energy storage collaborative scheduling and improve resource utilization efficiency and economy, this invention uses energy storage as the core regulation unit and combines it with flexible interconnection devices to achieve collaborative operation and unified optimization of multiple regions. It is no longer limited to the independent operation mode of a single region, effectively improving the energy storage charging and discharging sequence and utilization efficiency, significantly reducing the curtailment rate and electricity purchase cost, and realizing multi-regional energy collaborative management.

[0060] The computational results demonstrate that, compared to traditional fixed topology and single-area independent optimization methods, this invention achieves significant improvements in key indicators such as voltage deviation, electricity purchase cost, photovoltaic grid integration rate, and line losses. For example, in a typical daily dispatch scenario, the method reduces voltage deviation by approximately 57%, system electricity purchase cost by approximately 20%, photovoltaic curtailment by approximately 79%, and line losses by approximately 31%. This method maintains stable, efficient, and economical dispatch performance in environments with higher penetration rates of distributed renewable energy, load fluctuations, and multi-energy storage collaborative operation, providing crucial support for active distribution systems and multi-microgrid collaborative operation. Attached Figure Description

[0061] Figure 1 This is a flowchart of the multi-area energy storage collaborative scheduling method based on flexible interconnection and topology flexibility of the present invention. Detailed Implementation

[0062] The following, in conjunction with the accompanying drawings and implementation steps, provides a more detailed description of the multi-region energy storage collaborative optimization scheduling method proposed in this invention, based on flexible interconnection and topology flexibility. The method unfolds around a closed-loop process of power flow modeling, topology construction, energy storage collaboration, optimization solution, and execution feedback. It achieves cross-region energy mutual assistance through flexible interconnection devices, realizes dynamic reconfiguration of the distribution network structure through virtual flow and spanning tree constraints, and forms a unified optimization scheduling framework with multi-region energy storage as the core regulating resource, thereby achieving flexible, safe, and economical operation of the distribution network under uncertain scenarios.

[0063] like Figure 1 The method for coordinated scheduling of multi-area energy storage based on flexible interconnection and topology flexibility, as shown, includes the following steps:

[0064] S1. Input data preparation:

[0065] Collect basic data such as the distribution network's basic topology, line parameters, transformer area load curves, distributed photovoltaic power output prediction, transformer area energy storage capacity and operating parameters, and the capacity and control characteristics of flexible interconnection devices.

[0066] S2 and SOP node modeling:

[0067] Construct a node power flow balance model with flexible interconnection devices, establish active and reactive power constraints and energy conservation relationships at SOP ports, and clarify the power flow regulation capabilities of multi-terminal flexible interconnection devices for the power distribution system.

[0068] Total power balance constraints

[0069]

[0070] The above formula characterizes the active power balance relationship of multi-terminal flexible interconnection devices under steady-state operating conditions, where Indicates the number of flexible interconnect ports. For the first Active power exchange between each port and the connected distribution network. The internal losses of the flexible interconnect device are equivalent to the first... The equivalent active power carried by the port. Equation (1.1) shows that the sum of the total power injection and the internal equivalent loss is zero, that is, no net energy is generated inside the system, thereby ensuring that the multi-terminal converter system meets the energy conservation principle and realizes stable and controllable multi-point power coordination capability.

[0071] Port active power definition related to losses

[0072]

[0073] This formula represents the first flexible interconnect device. Port loss power It is proportional to its apparent power magnitude, where This is the equipment loss coefficient. This represents reactive power loss, reflecting the combined characteristics of switching and conduction losses in the converter. This relationship allows for the explicit incorporation of the converter's energy loss into the scheduling optimization model, making the control strategy more aligned with the actual operating characteristics of power electronic equipment and improving the engineering accuracy of simulation and control strategies.

[0074] Port capacity constraints

[0075]

[0076] Equation (1.3) represents the apparent power limitation of the port of the flexible interconnect device, where This is the rated capacity of the port. This constraint ensures that the converter operates within its rated capacity, preventing thermal failures and overload damage to components, and is an important condition for ensuring the safe operation of power electronic systems.

[0077] Voltage operating constraints

[0078]

[0079] This formula relates to the bus voltage of the flexible interconnect device. To impose constraints, Upper and lower limits ensure that the voltage is maintained within the allowable range of the distribution network (e.g., – (pu). By using voltage constraints, the flexible AC / DC interface equipment is ensured to operate within the electromagnetic compatibility range, avoiding power quality problems and protection malfunctions, and supporting stable operation in voltage-sensitive sections.

[0080] S3. Construction of Energy Storage Coordinated Scheduling Model:

[0081] Each energy storage area is treated as an independent control unit. An energy storage operation model is established by combining state of charge constraints, capacity limitations, charge-discharge mutual exclusion and lifetime constraints. This model is then coordinated with the SOP (Start of Operation) regulation strategy to achieve coordinated optimization of energy storage resources across different energy storage areas.

[0082] Energy storage state of charge

[0083] (2.1)

[0084] The above formula describes the dynamic evolution of energy in an energy storage system. For a moment t Transit Node i The state of charge of energy storage, It is determined by the state of the previous cycle and the charging and discharging behavior of the current cycle, and is also affected by the charging and discharging efficiency. Impact. This constraint ensures that the model maintains energy balance during long-term operation, avoids overcharging or over-discharging of the energy storage system, and gives energy storage scheduling time-coupled characteristics, thereby enabling prediction of future available capacity and ensuring service continuity.

[0085] Charge and discharge mutual exclusion constraint

[0086] (2.2)

[0087] The above formula stipulates that an energy storage system cannot simultaneously perform charging and discharging operations within any given cycle, which conforms to physical operating characteristics and battery management logic. This constraint can be implemented using binary variables. The implementation refers to the charging switch and the discharging switch, respectively, to ensure that the energy regulation logic is clear, avoid conflicts with the actual control strategy, and ensure the feasibility and efficiency of energy storage.

[0088] Energy storage safe operation boundary

[0089] (2.3)

[0090] This constraint defines the upper limit of the charging and discharging power of the energy storage system. and This limit is combined with... Safety range constraints work together to ensure safe battery operation, meeting engineering life, safety level, and operational strategy requirements.

[0091] S4, Distribution Network Power Flow and Topology Flexibility Modeling

[0092] By introducing virtual commodity flow constraints and spanning tree structure constraints, a dynamically switchable radial topology model is constructed. Through the linkage between line switch states and virtual topology variables, the dynamic structure reconfiguration capability of the distribution network is realized, ensuring global system connectivity and loop-free operation.

[0093] Synthetic execution objective function

[0094]

[0095] in:

[0096] Electricity purchase cost item , Price per unit Taiwan District i The power output reflects the cost of electricity purchased by the distribution area from the upper-level power grid.

[0097] Network loss cost item , This is the network loss coefficient. For the line k The current, For the line kimpedance, For line sets, characterize the line losses caused by branch currents to reflect the benefits of power flow optimization;

[0098] Solar curtailment penalty items , To cover the cost of light curtailment, To reduce curtailment of solar power, we encourage the full utilization of intermittent distributed power sources and enhance the capacity for green energy consumption;

[0099] SOP loss cost item , To characterize the additional losses introduced by the converter and suppress unnecessary energy transfer for the loss cost of SOP;

[0100] Voltage deviation cost item , For voltage deviation cost, For reference voltage, For nodes i The voltage is high enough to ensure a good voltage level and improve power quality.

[0101] By weighted summing of the above multiple indicators, the system can achieve a comprehensive balance between economy, power quality, and renewable energy absorption capacity. Flexible interconnection devices, through controllable active / reactive power injection and multi-terminal power flow distribution capabilities, make the distribution network operation more proactive and flexible, thereby achieving the coordinated operation goals of "safety, superior voltage, low loss, and efficient use of green electricity."

[0102] Node power balancing

[0103]

[0104] The above equations describe the distribution network nodes (transformer areas) when they exist. The balance between active and reactive power flows. and Representing the transformer nodes respectively The exchange of active and reactive power with the upper-level power grid, with positive values ​​representing nodes drawing power from the upper-level power grid; For nodes i The set of adjacent nodes; and Indicates from adjacent nodes Flow to Node Active and reactive power, and This indicates that the node is... Power flow injected into adjacent nodes. and For flexible interconnect devices at nodes The active and reactive power injected are positive values, indicating that electrical energy is injected into the local node. and For nodes The active and reactive power required by the load; and These represent the active and reactive power injected into the grid by distributed power sources (such as photovoltaics and energy storage) at the node, respectively, and can be zero or positive; finally, Represents nodes The equivalent active power of the relevant line losses can usually be calculated from the square of the current and the line resistance. Through this constraint, the distribution network power flow calculation and SOP coordinated control are coupled, enabling the SOP adjustment behavior to affect the power flow, voltage, and distributed photovoltaic absorption capacity in real time. This is a core step in constructing a new distribution network power flow model with multi-terminal interconnection of power electronics.

[0105] Topology flexibility constraints

[0106] (3.4)

[0107]

[0108] The above constraints are used to ensure that the distribution network containing flexible interconnection devices forms a uniquely connected, loop-free, reconfigurable radial structure at every moment. Among them, For a moment t On the line The virtual commodity flow variables are used to establish a unified topological logic judgment mechanism; For a moment t Virtual branch The open / closed state is a binary variable, with a value of 1 indicating that the line is closed and 0 indicating that it is open. Represents the root node (Usually chosen as the substation busbar) Injected into the system Unit virtual traffic; formula Ensure that each node except the root node consumes 1 unit of virtual traffic, thereby ensuring that all nodes are connected to the main network; This forces virtual flows to pass only through closed loops, thus binding the virtual flow to the actual topology; Set the number of closed branches as This ensures that the system forms only one spanning tree. Defines the actual switching state of the line. With virtual topology state The logical relationship between them, among which This indicates that the circuit is actually closed. This indicates that the switch is open. This constraint requires that the actual switch state cannot violate the virtual feasible topology, i.e., if... If so, the corresponding line must be disconnected; Then, the line can be closed based on the scheduling strategy. In other words, The representation theory allows for feasible topological spaces, while Select the final actual operating topology within the allowed operating range so that network reconstruction does not disrupt the radiation structure.

[0109] This set of constraints enables simultaneous energy storage scheduling, flexible interconnected power flow configuration, and dynamic distribution network topology optimization during scheduling optimization. This fully leverages the energy routing capabilities and distributed resource utilization potential of the SOP, achieving proactive reconfiguration and inter-distribution operation of the distribution network with power electronic interfaces.

[0110] S5. Comprehensive Optimization Solution

[0111] A comprehensive optimization model is constructed with the objectives of minimizing system operating costs, minimizing photovoltaic curtailment, reducing network losses, and suppressing voltage deviations. The model is solved using power flow-topology-energy storage coupling constraints to obtain the global optimal scheduling scheme for multiple transformer areas.

[0112] S6, Output and Execution

[0113] It outputs the optimal topology, power commands for flexible interconnect devices, and energy storage charging and discharging schemes, and completes operation control and achieves closed-loop regulation through the execution layer.

[0114] This invention provides a specific embodiment:

[0115] Taking a typical distribution network with 32 transformer substations as an example, a 500kW distributed photovoltaic system and a 300 kWh substation energy storage system are configured, along with a flexible interconnection device (SOP, dual-ended type, rated capacity 500 kVA). Under a typical 24-hour daily operation scenario, the following two operating strategies are compared:

[0116] Option A: Traditional distribution network operation

[0117] Without flexible interconnection devices, the network structure is fixed, and topological flexibility and cross-regional energy exchange are not considered.

[0118] Option B: The flexible interconnection and topology flexibility optimization method

[0119] Enable SOP for cross-regional power flow regulation and introduce dynamic radiation topology reconfiguration to enable the system to find an economical and voltage-friendly operating structure in real time.

[0120] Evaluation indicators include: voltage deviation (pu), electricity purchase cost (¥), curtailment of solar power (kWh), and line network loss (kWh).

[0121] Table 1 Comparison Results

[0122]

[0123] Compared to traditional fixed topology operation without flexible interconnection, the method of this invention achieves optimized energy allocation across distribution areas through flexible interconnection devices and realizes reconfigurable line scheduling by combining dynamic topology flexibility constraints. Results show that, under the same operating conditions:

[0124] Voltage deviation significantly reduced: The system voltage deviation decreased from 0.021 pu to 0.009 pu, the overall voltage distribution became more balanced, weak voltage nodes were effectively supported, and the voltage quality of the distribution network was significantly improved.

[0125] Electricity purchase costs have decreased significantly: Through off-peak energy storage, cross-regional utilization of surplus photovoltaic power, and topology optimization, electricity purchase costs have been reduced by approximately 20.4%, demonstrating the advantages of flexible interconnection in improving the utilization and economic efficiency of renewable energy.

[0126] Photovoltaic absorption capacity has been significantly improved: the amount of curtailed solar power has decreased from 128 kWh to 27 kWh, a reduction of approximately 78.9%, achieving efficient absorption of intermittent distributed energy.

[0127] Line losses were effectively reduced: the system network loss decreased from 192 kWh to 133 kWh, a reduction of about 30.7%, indicating a better power flow distribution and more energy-efficient grid operation.

[0128] This invention further provides a microgrid mutual assistance and control operation system for distribution areas that considers flexible interconnection devices and topology flexibility. The system is used to implement the above-mentioned method and includes:

[0129] The data acquisition module is used to collect basic data such as the basic topology of the distribution network, line parameters, transformer load curves, distributed photovoltaic power output prediction, transformer energy storage capacity and operating parameters, and capacity and control characteristics of flexible interconnection devices.

[0130] The flexible interconnection device modeling module is used to construct a node power flow balance model containing flexible interconnection devices, establish active and reactive power constraints and energy conservation relationships at SOP ports, and clarify the power flow regulation capabilities of multi-terminal flexible interconnection devices in the power distribution system.

[0131] The energy storage collaborative scheduling model construction module treats each transformer area's energy storage as an independent control unit, and establishes an energy storage operation model by combining state of charge constraints, capacity limits, charge-discharge mutual exclusion, and lifetime constraints. It also coordinates with the SOP adjustment strategy to achieve coordinated optimization of energy storage resources across transformer areas.

[0132] The power flow and topology flexibility model building module of the distribution network is used to introduce virtual commodity flow constraints and spanning tree structure constraints to build a dynamically switchable radial topology model. By linking the line switch status with virtual topology variables, the dynamic structure reconfiguration capability of the distribution network is realized, ensuring that the system is globally connected and loop-free.

[0133] The integrated optimization model construction and solution module is used to construct an integrated optimization model with the objectives of minimizing system operating costs, minimizing photovoltaic curtailment, reducing network losses, and suppressing voltage deviations. It uses power flow-topology-energy storage coupling constraints to solve the model and obtain the global optimal scheduling scheme for multiple transformer areas.

[0134] The output and execution module is used to output the optimal topology, power commands for flexible interconnect devices, and energy storage charging and discharging schemes. It completes operation control and achieves closed-loop regulation through the execution layer.

[0135] The present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method described herein.

[0136] In summary, the method of this invention is superior to traditional solutions in terms of voltage safety, economy, clean energy consumption and energy efficiency, demonstrating the important value and engineering feasibility of flexible interconnection and topology flexibility optimization in new power distribution network operation scenarios.

Claims

1. A multi-regional energy storage collaborative scheduling method based on flexible interconnection and topology flexibility, characterized in that, Includes the following steps: S1. Collect basic data on the distribution network's basic topology, line parameters, transformer load curves, distributed photovoltaic power output prediction, transformer energy storage capacity and operating parameters, and the capacity and control characteristics of flexible interconnection devices. S2. Construct a node power flow balance model with flexible interconnection devices, establish active and reactive power constraints and energy conservation relationships at SOP ports, and clarify the power flow regulation capability of multi-terminal flexible interconnection devices for the power distribution system. S3. Treat each transformer area's energy storage as an independent control unit, establish an energy storage operation model by combining state of charge constraints, capacity limits, charge-discharge mutual exclusion and lifetime constraints, and coordinate with the SOP adjustment strategy to achieve coordinated optimization of cross-transformer area energy storage resources. S4. Introduce virtual commodity flow constraints and spanning tree structure constraints to construct a dynamically switchable radial topology model. By linking the line switch status with virtual topology variables, the dynamic structure reconfiguration capability of the distribution network is realized, ensuring global connectivity and loop-free operation of the system. S5. Construct a comprehensive optimization model with the objectives of minimizing system operating costs, minimizing photovoltaic curtailment, reducing network losses, and suppressing voltage deviations. Solve the model using power flow-topology-energy storage coupling constraints to obtain the global optimal scheduling scheme for multiple transformer areas. S6 outputs the optimal topology, power commands for flexible interconnect devices, and energy storage charging and discharging schemes, and completes operation control and achieves closed-loop regulation through the execution layer.

2. The method according to claim 1, characterized in that, The node power flow balance model with flexible interconnection devices in S2 includes total power balance constraints, loss-related port active power definitions, port capacity constraints, and voltage operation constraints. The total power balance constraint is: ; The above formula characterizes the active power balance relationship of multi-terminal flexible interconnection devices under steady-state operating conditions, where Indicates the number of flexible interconnect ports. For the first Active power exchange between each port and the connected distribution network. The internal losses of the flexible interconnect device are equivalent to the first... The equivalent active power carried by the port; The loss-related active power at the port is defined as follows: ; in This is the equipment loss coefficient. This is reactive power loss; The port capacity constraint is expressed as follows: ; in This is the rated capacity of the port; The voltage operating constraint is expressed as follows: ; This formula relates to the bus voltage of the flexible interconnect device. To impose constraints, Upper and lower limits.

3. The method according to claim 2, characterized in that, The energy storage operation model described in S3 includes: energy storage state of charge constraints, charge and discharge mutual exclusion constraints, and energy storage safe operation boundary constraints; The energy storage state of charge constraint is expressed as follows: （2.1） The above formula describes the dynamic energy evolution process of an energy storage system. For a moment t Transit Node i The state of charge of energy storage, It is determined by the state of the previous cycle and the charging and discharging behavior of the current cycle, and is also affected by the charging and discharging efficiency. Influence; The charge-discharge mutual exclusion constraint is expressed as follows: （2.2） These represent the charging switch and the discharging switch, respectively. The energy storage safety operation boundary constraints are expressed as follows: （2.3） and This represents the upper limit of charging and discharging power.

4. The method according to claim 3, characterized in that, The comprehensive optimization model described in S4 includes a comprehensive operational objective function: ; Of which: electricity purchase cost , Price per unit Taiwan District i The power output reflects the cost of electricity purchased by the distribution area from the upper-level power grid; network loss costs. , This is the network loss coefficient. For the line k The current, For the line k impedance, For line aggregation; photovoltaic curtailment penalty items , To cover the cost of light curtailment, Wasted light; SOP loss cost item , Cost of loss at SOP; voltage deviation cost item , For voltage deviation cost, For reference voltage, For nodes i The voltage.

5. The method according to claim 4, characterized in that, The comprehensive optimization model described in S4 includes node power balance constraints: ; in, and Representing the transformer nodes respectively The exchange of active and reactive power with the upper-level power grid, with positive values ​​representing the node drawing power from the upper-level power grid; For nodes i The set of adjacent nodes; and Indicates from adjacent nodes Flow to Node Active and reactive power, and This indicates that the node is... Power flow injected into adjacent nodes; and For flexible interconnect devices at nodes The active and reactive power injected are positive values, indicating that electrical energy is injected into the local node. and For nodes The active and reactive power required by the load; and These represent the active and reactive power injected into the grid by the distributed power sources at the node, respectively, and can be zero or positive. Represents nodes The relevant line losses are equivalent to active power.

6. The method according to claim 5, characterized in that, The comprehensive optimization model described in S4 includes topology flexibility constraints: ; in, For a moment t On the line Virtual goods traffic variables; For a moment t Virtual branch A binary variable representing the open / closed state, where a value of 1 indicates the line is closed and 0 indicates it is open; Represents the root node (Usually chosen as the substation busbar) Injected into the system Unit virtual traffic; formula Ensure that each node except the root node consumes 1 unit of virtual traffic, thereby ensuring that all nodes are connected to the main network; This forces virtual flows to pass only through closed loops, thus binding the virtual flow to the actual topology; Set the number of closed branches as This ensures that the system forms only one spanning tree; Defines the actual switching state of the line. With virtual topology state The logical relationship between them, among which This indicates that the circuit is actually closed. This indicates that the switch is open; this constraint requires that the actual switch state cannot violate the virtual feasible topology, i.e., if... If so, the corresponding line must be disconnected; Then, the line can be closed based on the scheduling strategy. The representation theory allows for feasible topological spaces, while Select the final actual operating topology within the allowed operating range so that network reconstruction does not disrupt the radiation structure.

7. A microgrid mutual assistance and control operation system for distribution areas considering flexible interconnection devices and topology flexibility, characterized in that, The system is used to implement the method according to any one of claims 1-6, the system comprising: The data acquisition module is used to collect basic data such as the basic topology of the distribution network, line parameters, transformer load curves, distributed photovoltaic power output prediction, transformer energy storage capacity and operating parameters, and capacity and control characteristics of flexible interconnection devices. The flexible interconnection device modeling module is used to construct a node power flow balance model containing flexible interconnection devices, establish active and reactive power constraints and energy conservation relationships at SOP ports, and clarify the power flow regulation capabilities of multi-terminal flexible interconnection devices in the power distribution system. The energy storage collaborative scheduling model construction module treats each transformer area's energy storage as an independent control unit, and establishes an energy storage operation model by combining state of charge constraints, capacity limits, charge-discharge mutual exclusion, and lifetime constraints. It also coordinates with the SOP adjustment strategy to achieve coordinated optimization of energy storage resources across transformer areas. The power flow and topology flexibility model building module of the distribution network is used to introduce virtual commodity flow constraints and spanning tree structure constraints to build a dynamically switchable radial topology model. By linking the line switch status with virtual topology variables, the dynamic structure reconfiguration capability of the distribution network is realized, ensuring that the system is globally connected and loop-free. The integrated optimization model construction and solution module is used to construct an integrated optimization model with the objectives of minimizing system operating costs, minimizing photovoltaic curtailment, reducing network losses, and suppressing voltage deviations. It uses power flow-topology-energy storage coupling constraints to solve the model and obtain the global optimal scheduling scheme for multiple transformer areas. The output and execution module is used to output the optimal topology, power commands for flexible interconnect devices, and energy storage charging and discharging schemes. It completes operation control and achieves closed-loop regulation through the execution layer.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method described in any one of claims 1-6.

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