Power distribution network flexible resource regulation and control method and system considering operation safety domain

Abstract

The invention discloses a power distribution network flexible resource regulation and control method and system considering an operation safety domain, and relates to the field of economic operation of a power system. According to the method, a comprehensive response capability model of flexible resources such as an air conditioner, an electric automobile, distributed photovoltaic and energy storage is constructed by evaluating the adjustment potential of the flexible resources; in combination with power distribution network topology and line parameters, voltage stability and thermal stability constraints are deduced based on a power flow equation, and an operation safety domain is established as a safe and feasible injection power space of the system; when the system runs in the security domain, solving an optimal scheduling scheme under the hard constraint of the security domain by taking the benefit maximization of the flexible load aggregator as a target; and when the system is out of limit, automatically switching to an emergency regulation and control mode, adopting a target function for minimizing a deviation weight distance, introducing an energy storage quick response mechanism, and generating a regulation and control instruction for guiding the system to return to a security domain. The technical problems that an existing flexible resource scheduling method is difficult to give consideration to safety and economy under high-proportion renewable energy access and lacks the capability of quickly recovering an out-of-limit state are solved. According to the method, collaborative optimization of safety and economy is realized, and the toughness of the power distribution network is improved.

Description

Technical Field

[0001] This application relates to a method and system for flexible resource regulation of distribution networks that takes into account the operational safety domain, belonging to the field of economic operation of power systems. Background Technology

[0002] In modern active distribution networks, with the large-scale integration of flexible resources such as distributed photovoltaics, electric vehicles, and energy storage systems, traditional centralized dispatching models are no longer sufficient to cope with the challenges posed by strong uncertainties on both the source and load sides. Current mainstream technical approaches mainly revolve around two directions: first, demand response (DR) models based on price signals or incentive mechanisms, using economic levers to guide users to adjust their electricity consumption behavior; second, using optimization algorithms to aggregate and manage multiple types of distributed resources to achieve peak shaving and valley filling, reduce network losses, or improve the absorption capacity of renewable energy. Typical methods include linearized dispatching models based on DC power flow, robust optimization, and stochastic programming to handle uncertainties, combined with a three-level coordination mechanism (day-ahead, intraday, and real-time) to achieve multi-timescale control. Furthermore, some studies introduce network constraints, such as node voltage upper and lower limits and line capacity limitations, as boundary conditions in the optimization process, initially achieving a balance between safety and economy.

[0003] However, existing flexible resource regulation methods still have significant shortcomings in practical applications: On the one hand, most scheduling models simplify safety constraints to static threshold judgments, lacking dynamic quantitative representation of the distribution network's operating state space, leading to potential voltage overruns or line overload risks under complex operating conditions; on the other hand, when the system has already exceeded limits, traditional methods often rely on manual intervention or load shedding, lacking automated emergency control strategies to quickly guide the system back to a safe range. More critically, existing technologies generally lack the concept of an "operational safety domain," failing to clearly define the safe and feasible operating range from a geometric perspective, and failing to achieve an adaptive switching mechanism between "economic optimization within the safety domain" and "rapid pullback outside the safety domain." Therefore, how to construct a collaborative framework integrating operational safety domain modeling, economic optimization, and emergency control has become a crucial technical bottleneck that urgently needs to be overcome to improve the resilience and regulation efficiency of distribution networks in scenarios with a high proportion of renewable energy. Summary of the Invention

[0004] The purpose of this application is to address the shortcomings of the aforementioned background technology by proposing a flexible resource regulation method and system for distribution networks that takes into account the operational safety domain. This method balances safe operation and economic absorption requirements during distribution network operation.

[0005] To achieve the above objectives, the technical solution adopted in this application is as follows: Firstly, this application provides a method for flexible resource regulation of a distribution network that takes into account the operational safety domain, including: Based on historical operational data and equipment parameters of flexible resources, the upward and downward adjustment capabilities at different time scales are evaluated, and a comprehensive adjustment potential model is constructed. Combining the distribution network topology and line parameters, the voltage stability boundary and thermal stability boundary are derived using the power flow equation. An analytical expression for the spatial safety domain with active power and reactive power injected into the nodes as variables is established, forming a safety domain that does not violate the voltage amplitude limit and branch current overload constraints. Based on the comprehensive regulation potential model, when the system operates within the safety domain, a flexible resource aggregation model considering the safety domain constraints of the distribution network is established, including an objective function and constraints. The objective function is to maximize the economic benefits of the flexible resource aggregator. The constraints include distribution network power flow constraints, distribution network safety domain constraints, and flexible resource regulation constraints. The safety domain is used as a hard constraint, and the optimal scheduling scheme is obtained by solving the flexible resource aggregation model. Based on the optimal scheduling scheme, flexible resource regulation of the distribution network is implemented. When the system operating point is detected to be outside the safety domain boundary, it automatically switches to emergency regulation mode. The flexible resource operation and regulation strategy model outside the safety domain is adopted, including objective function and constraints. The objective function is to minimize the weighted distance of deviation from the safety domain. The constraints include safety domain constraints, flexible resource regulation capability constraints, and distribution network-related constraints. The safety domain constraints are adjusted to soft constraints, and combined with the maximum charge and discharge rate limit of fast response resources, emergency regulation instructions are generated to guide the system to quickly return to the safety domain.

[0006] As a further improvement to this application, the method of evaluating the upward and downward adjustment capabilities at different time scales based on historical operating data and equipment parameters of flexible resources, and constructing a comprehensive adjustment potential model, includes: The regulation potential of air conditioning, electric vehicles, distributed photovoltaics, and energy storage are analyzed separately. Taking into account user comfort and willingness to accept dispatch, the regulation potential is summed to obtain the comprehensive range of flexible resource regulation potential.

[0007] As a further improvement of this application, the security domain is surrounded by several high-dimensional surfaces, which are defined by voltage and thermal constraints; the curved surface of the security domain restricts the network to normal operation without violating network constraints. Among them, the thermal stability boundary considers the safety of the distribution network from the perspective of power and line current, while the voltage stability boundary considers the safety of the distribution network from the perspective of voltage. The thermal stability boundary and the voltage stability boundary constitute the constraints of the flexible resource aggregation method within the safety domain and the flexible resource regulation strategy outside the safety domain.

[0008] As a further improvement to this application, the safe operating domain of the distribution network is a feasible injected power space in which the voltage amplitude of all nodes and the branch current meet the limit conditions.

[0009] As a further improvement to this application, the derivation of voltage stability boundary and thermal stability boundary using power flow equations includes: Based on the DistFlow equation and the relationship between line voltage drop, a voltage stability security domain constraint expression with active / reactive power as variables is derived. Using Ohm's law and the branch current limit, a quadratic cone constraint with respect to the total injected power downstream is constructed as the boundary of the thermal stability safety domain; The intersection of the voltage stability domain and the thermal stability domain is used as the comprehensive safe operating area to determine whether the system exceeds the limits.

[0010] As a further improvement to this application, the analytical expression of the thermal stability boundary is as follows:

[0011]

[0012] The analytical expression for the voltage stability boundary is:

[0013] In the formula, α k and β k Representing nodes respectively k The coefficients corresponding to active and reactive power; P k and Q k Representing nodes respectively k The magnitude of active and reactive power; V 0 represents a node j The voltage amplitude; IM ij Represents a node i To the node j The magnitude of the branch current; D j Represents a node j The set of downstream nodes; B Represents the set of branches in a network; V j This indicates the voltage level at the branch receiving end; U j Represents nodes in a distribution network j The set of upstream nodes; R k and X k Representing nodes respectively k The equivalent resistance and equivalent reactance of the downstream nodes; P l and Q l Representing nodes respectivelyl The active power and reactive power.

[0014] As a further improvement to this application, the flexible resource aggregation model considering the security domain constraints of the distribution network is specifically as follows: Objective function:

[0015] In the formula, C flx i This indicates the market price of flexible load aggregators. P flx i This indicates the actual output of the flexible load aggregator; The constraints include: 1) Distribution network power flow constraints

[0016]

[0017]

[0018]

[0019] In the formula, V i,t , V j,t Indicates the corresponding node i ,node j voltage, I ji,t Indicates the line ji The current, PLine ji,t and QLine ji,t Indicates the active and reactive power on the line. r ji and x ji This indicates the resistance and reactance of the circuit. PLine k,t Indicates that at time t Time node k Active power injected into the node, Pload i,t It is a node i In time t The active power of the fixed load present at the time node. Pgen i,t Represents a node In time t Active power of distributed gas turbine units Qload k,t Indicates that at time t Time node k The reactive power injected into the node, Qload i,t It is a node i In time t The reactive power of fixed loads present at the time node, Qgen i,tRepresents a node i In time t The reactive power of distributed gas turbine units; Pflx i,t and Qflx i,t These represent the magnitude of active and reactive power regulated by flexible resources, respectively. 2) Distribution network security domain constraints, including thermal stability security domain constraints and voltage stability security domain constraints:

[0020]

[0021]

[0022] In the formula, Vm j and VM j These represent the minimum and maximum voltage values ​​at the branch receiving end, respectively. 3) Flexible load adjustment constraints:

[0023] In the formula, , These represent the upper and lower limits of flexible resources, respectively.

[0024] As a further improvement to this application, the operational control strategy model for flexible resources outside the security domain is specifically as follows: Objective function:

[0025] In the formula, T It is a collection of time; V and I These are the voltage weights and thermal stability weights, respectively, for deviations from the safe domain. Indicates the line ij The upper limit of current; Specific conditions include: 1) Conventional constraints, including constraints on flexible resource regulation capacity and distribution network-related constraints; 2) Soft constraints of security domains:

[0026]

[0027] 3) Maximum charge / discharge rate constraint for energy storage:

[0028] In the formula, Indicates the magnitude of the soft constraint relaxation voltage; Indicates the magnitude of the soft constraint relaxation current; Indicates the energy storage capacity; ramp This indicates the rate limit for charging and discharging energy storage.

[0029] Secondly, this application provides a flexible resource control system for a distribution network that takes into account the operational safety domain, comprising: The potential assessment module is used to evaluate the upward and downward adjustment capabilities at different time scales based on historical operating data and equipment parameters of flexible resources, and to construct a comprehensive adjustment potential model. The safety domain calculation module is used to combine the distribution network topology and line parameters, use power flow equations to derive voltage stability boundary and thermal stability boundary, establish a spatial safety domain analytical expression with node injected active power and reactive power as variables, and form a safety domain that does not violate voltage amplitude over-limit and branch current overload constraints. The flexible resource aggregation module is used to establish a flexible resource aggregation model considering the distribution network security domain constraints when the system is operating within the security domain, based on the comprehensive regulation potential model. The model includes an objective function and constraints. The objective function is to maximize the economic benefits of the flexible resource aggregator. The constraints include distribution network power flow constraints, distribution network security domain constraints, and flexible resource regulation constraints. The security domain is used as a hard constraint to solve the flexible resource aggregation model and obtain the optimal scheduling scheme. The operation and control module is used to regulate the flexible resources of the distribution network based on the optimal scheduling scheme. When the system operating point is detected to be outside the safety domain boundary, it automatically switches to the emergency control mode and adopts the flexible resource operation and control strategy model outside the safety domain, including objective function and constraints. The objective function is to minimize the weighted distance of deviation from the safety domain. The constraints include safety domain constraints, flexible resource adjustment capability constraints, and distribution network-related constraints. The safety domain constraints are adjusted to soft constraints, and combined with the maximum charge and discharge rate limit of fast response resources, emergency control instructions are generated to guide the system to quickly return to the safety domain.

[0030] Thirdly, this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the flexible resource regulation method for a distribution network that takes into account the operational security domain.

[0031] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the flexible resource regulation method for a distribution network that takes into account the operational security domain.

[0032] Fifthly, this application provides a computer program product, the computer program product including computer instructions, the computer instructions instructing a computer to execute the power distribution network flexible resource regulation method that considers the operational security domain.

[0033] The beneficial effects of the technical solution proposed in this application are: This application effectively addresses the difficulty of balancing safety and economy in traditional scheduling methods by constructing a four-stage collaborative mechanism: "flexible resource potential assessment—operational safety domain modeling—intra-domain economic optimization—extra-domain emergency control." For the first time, it jointly constructs the voltage stability domain and thermal stability domain into a high-dimensional safe and feasible space for distribution network operation, realizing a geometric and visual criterion for the system's operating state. Based on this, a dual-mode control architecture is proposed. Within the safety domain, optimized scheduling aims to maximize aggregator revenue. When limits are exceeded, it automatically switches to an emergency pullback strategy focused on minimizing deviation distance. Furthermore, it introduces energy storage for rapid response and soft constraint mechanisms, significantly improving system recovery speed and robustness. This method not only ensures the physical feasibility of the scheduling scheme but also enhances its adaptability to sudden disturbances. The method in this application differs from previous flexible load aggregators' scheduling processes, which only pursue profit maximization while neglecting safety. This application considers the safety domain characteristics of the distribution network during the aggregation process to ensure that the flexible load aggregator obtains the maximum benefit under the premise of safe and stable operation of the distribution network. When the distribution network is operating outside the safety domain, the adjustment capability of flexible resources is fully mobilized, so that the operation of the distribution network can be quickly adjusted to within the safety domain to ensure stable operation when massive distributed resources enter the distribution network. Attached Figure Description

[0034] Figure 1 This is a schematic diagram representing the safety domain section during the operation of the distribution network provided in this application; Figure 2 A schematic diagram of the distribution network flexible resource aggregation method for computing the operational security domain provided in this application; Figure 3 A comparison of voltage safety during aggregation provided in this application, considering whether or not a safety domain is taken into account; Figure 4 The results of the regulation of flexible resources when operating outside the security domain are provided in this application. Detailed Implementation

[0035] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application. The step numbers in the following embodiments are set only for ease of explanation, and there is no limitation on the order between the steps. The execution order of each step in the embodiments can be adaptively adjusted according to the understanding of those skilled in the art.

[0036] In the description of this application, unless otherwise expressly defined, terms such as "setup," "installation," and "connection" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this application in conjunction with the specific content of the technical solution.

[0037] This application provides a method for regulating flexible resources in a distribution network that considers operational safety domains. This method collects operational data from flexible resources such as distributed energy sources, energy storage, electric vehicles, and controllable loads in the distribution network, and achieves aggregated management and optimized scheduling of user-side resources under a centralized or distributed control architecture. The method includes the following steps: Step (1) Method for assessing the flexible resource regulation potential of distribution networks; Based on historical operating data and equipment parameters of typical flexible resources such as air conditioning, electric vehicles, distributed photovoltaics and energy storage, their up-regulation and down-regulation capabilities at different time scales are evaluated, and a comprehensive regulation potential model is constructed. Specifically, the technical solution for step (1), the method for assessing the flexible resource regulation potential of the distribution network, is described in detail below: Step (1) selected several common resources for regulation potential analysis, including air conditioning, electric vehicles, distributed photovoltaics, and energy storage. In some urban power grids, the proportion of air conditioning load during peak summer load periods has even reached 50%, thus air conditioning has significant regulation value. Large-scale electric vehicle access to the grid on the user side, due to its rapid response, can provide peak-shaving and frequency regulation auxiliary services and reserve capacity services to the grid during peak loads or emergency situations. Distributed photovoltaics have been widely deployed in urban buildings, especially on rooftops. Through these flexible loads, cost-effective system regulation capabilities can be provided to the power system, thereby improving overall operational efficiency.

[0038] As an example, the potential assessment of massive flexible resources includes the evaluation and calculation of the upward and downward adjustment capabilities of flexible resources such as air conditioning, electric vehicles, distributed photovoltaics, and energy storage. For instance, given the huge adjustment potential of flexible loads, the adjustment potential of air conditioning, electric vehicles, distributed photovoltaics, and energy storage are analyzed separately, taking into full account the user's comfort and willingness to accept scheduling. Finally, the adjustment potentials are summed to obtain the comprehensive range of flexible resource adjustment potential. The potential adjustment range of the flexible resources constitutes the constraints in steps (3) and (4).

[0039] Step (2) Method for calculating the security domain of power distribution network operation; Specifically, in this application embodiment, the voltage stability boundary and thermal stability boundary are derived by combining the distribution network topology and line parameters and using the DistFlow power flow equation. An analytical expression for the spatial safety domain with active power and reactive power injected by nodes as variables is established, forming a safety domain that does not violate the voltage amplitude limit and branch current overload constraints.

[0040] Specifically, the technical solution for step (2) of the distribution network operation security domain calculation method is described in detail below: The safety domain of a distribution network is surrounded by several high-dimensional surfaces defined by voltage and thermal constraints. These surfaces confine the network to its normal operation without violating network constraints. In this study, these high-dimensional surfaces are defined as the safety domains of the boundaries. Considering the type of constraints, the boundaries of the safety domains can be further classified as voltage-stability boundaries and thermal-stability boundaries.

[0041] The thermal stability boundary mainly considers the safety of the distribution network from the perspective of power and line current, while the voltage stability boundary mainly considers the safety of the distribution network from the perspective of voltage. The thermal stability boundary and the voltage stability boundary constitute the constraints of the flexible resource aggregation method within the safety domain and the flexible resource regulation strategy outside the safety domain.

[0042] A safety domain is defined and described as the set of feasible operating states of a distribution network without violating network constraints. The analytical expressions for safety domains include analytical expressions for thermal stability safety domains and analytical expressions for voltage stability safety domains.

[0043] Step (3) Considers a flexible resource aggregation method with distribution network security domain constraints; When the system is operating within the security domain, an optimization model is constructed with the goal of maximizing the comprehensive revenue of the flexible load aggregator. The security domain is embedded as a hard constraint in the mixed integer nonlinear programming (MINLP) framework to solve for the optimal scheduling scheme that satisfies the network physical constraints. Specifically, the technical solution for the flexible resource aggregation method considering the security domain constraints of the distribution network in step (3) is described in detail below: A flexible resource aggregation method model considering distribution network security domain constraints is established, including the objective function and constraints. The objective function is to maximize the economic benefits of the flexible resource aggregator. The model constraints include distribution network power flow constraints, distribution network security domain constraints, and flexible resource regulation constraints, forming a flexible resource aggregation method model with shared distribution network security domain constraints.

[0044] By establishing the above model, we can solve for the aggregation method of flexible resources within the safety domain, thereby guiding flexible load aggregators to obtain maximum benefits without affecting the safety of the power grid.

[0045] Based on the previously calculated flexible resource adjustment potential and the analytical expression of the security domain, an aggregation method for flexible resources is established. This includes an objective function and constraints. The objective function is to minimize the overall operating cost. Constraints include security domain constraints, flexible resource adjustment capability constraints, distribution network topology constraints, and node power balance constraints.

[0046] Step (4) Strategies for the operation and regulation of flexible resources outside the security domain.

[0047] When the system operating point is detected to be outside the safety domain boundary, it automatically switches to emergency control mode. It adopts the objective function of minimizing the deviation weight distance, adjusts the safety domain constraint to a soft constraint, and combines the maximum charge and discharge rate limit of fast response resources such as energy storage to generate emergency control instructions to guide the system to quickly return to the safety domain.

[0048] Specifically, the operational control strategy for flexible resources outside the security domain in step (4) is described in detail below: After describing the aggregation method of flexible resources within the safety domain, a flexible resource regulation strategy is proposed for operation outside the safety domain, including an objective function and constraints. The objective function minimizes the weighted distance from the safety domain. The model's constraints include safety domain constraints, flexible resource regulation capability constraints, and distribution network-related constraints. It also considers constraints on rapid flexible resource regulation, such as the maximum charge / discharge rate of energy storage, and adjusts the safety domain constraints to soft constraints.

[0049] After applying second-order cone relaxation to the power flow constraints of the distribution network, the model can be transformed into a linear programming problem, which can be solved using a commercial solver. When operating outside the safety domain, flexible resources must respond to meet the safety needs of the distribution network as much as possible within the scope of flexible resource adjustment. This includes the objective function and constraints.

[0050] The objective function is to minimize the weighted distance from the safety domain. Constraints include safety domain constraints, flexible resource adjustment capability constraints, distribution network topology constraints, and node power balance constraints. Specifically, the safety domain constraint needs to be adjusted to a soft constraint, allowing short-term deviations but requiring minimization.

[0051] The present application will now be described in further detail with reference to the accompanying drawings. Figure 2 As shown, the specific implementation method of the distribution network flexible resource regulation method that takes into account the operational safety domain is described below.

[0052] (1) The method for assessing the flexible resource regulation potential of the distribution network is described in detail below: The user-side control capability is the sum of the control capabilities of various resources, which can be specifically expressed by the following formula: (1) (2) In the formula, W total Indicates the user's control capability (i.e. P total = W total ); W tcl Indicates the air conditioning load regulation capability; W ev This indicates the controllability of electric vehicle charging stations; W pv Indicates the magnitude of photovoltaic control capability; W ess Indicates the size of energy storage regulation capacity; superscript u Indicates the regulating capability, i.e., the discharge capability; superscript d This indicates the ability to regulate, that is, the ability to charge and absorb electrical energy.

[0053] 1) Air Conditioning Capacity Assessment: Compared to the harsher summer and winter seasons, air conditioning usage in spring and autumn is negligible. Therefore, the air conditioning load in summer and winter can be easily calculated using the following formula: (3) In the formula, P tcl Indicates the size of the air conditioning load; P summer This indicates the building load during the summer and winter seasons; P spring This indicates the building load during the spring and autumn seasons.

[0054] However, not all air conditioning loads can be used for regulation. Before participating in regulation, the air conditioner must first meet people's normal production and living needs. Based on a maximum tolerable temperature difference of 2.5℃ (e.g., if the air conditioner is set to 26℃, the maximum tolerable indoor temperature is 28.5℃), simulations were used to obtain the maximum adjustable potential under different outdoor temperatures. η .in,η With outdoor temperature T out And setting the indoor temperature T in It has the following relationship: (4) Among them, the function F ( x The function is a fitting function obtained from simulation, used to establish the relationship between the maximum regulating potential and the indoor-outdoor temperature difference. Therefore, the regulating capacity of the air conditioner can be expressed by the following formula: (5) Furthermore, based on the indoor-outdoor temperature difference, set temperature, and user comfort tolerance range, the maximum adjustable power of the air conditioner is calculated. The adjustment potential of the air conditioner is influenced by both thermodynamic characteristics and user behavior. When the outdoor temperature is higher than the indoor set value, load reduction is achieved by increasing the return air temperature or suspending operation; during spring and autumn when the temperature difference is small, short-term shutdown is allowed without affecting comfort. Using 26°C as the baseline set temperature, the maximum tolerable temperature rise is 28.5°C (ΔT=2.5°C). Combining the building thermal inertia model and historical electricity consumption data, the upper limit of adjustable power under different operating conditions is derived. This modeling method considers both energy-saving potential and user experience. In practical applications, a fuzzy logic controller can also be introduced to dynamically score comfort; this embodiment does not limit this aspect.

[0055] 2) Electric Vehicle Adjustment Capability Assessment: Electric vehicles primarily use charging stations for charging. For electric vehicles that can be scheduled in an orderly manner, the charging stations can adjust their operation based on the time of day. Based on the state of charge, electric vehicles are divided into two groups: the charging group and the discharging group.

[0056] Based on the current state of charge SOCt i and the car owner's preset expected battery capacity SOCE i Grouping: If SOCt i > SOCE i At this point, the electric vehicle has a discharge margin. SOCt i - SOCE i It can be incorporated into a discharge group, and its discharge can be scheduled during the discharge period; if SOCt i ≤ SOCE i At this point, the electric vehicle does not have the ability to discharge, so it is included in the charging group for charging, and its load is accumulated to the load curve. Based on the electric vehicle's current state of charge (SOC) and desired charge, the vehicle is divided into charging group and discharging group, and its up and down adjustment capabilities are calculated separately.

[0057] Let the number of electric vehicles in the discharge group be... m The controllability of the electric vehicle fleet can then be expressed by the following formula: (6) (7) In the formula W i This indicates the control capability of a single electric vehicle. SOC max i Indicates the maximum state of charge; W uev and W d and ev represent the up-adjustment capability and down-adjustment capability of an electric vehicle, respectively.

[0058] 3) Assessment of the regulation capacity of distributed photovoltaics: By combining the relationship between light intensity and rated output of photovoltaic modules, a dynamic output prediction model for distributed photovoltaics is established, and its reduction potential is assessed accordingly.

[0059] Distributed photovoltaic (PV) power generation exhibits diurnal periodicity and intermittent fluctuations with varying solar irradiance. Total irradiance is the sum of solar radiation energy vertically and diffusely projected onto a unit area, and its temporal and distributed characteristics directly determine the temporal and distributed characteristics of distributed PV output power. On sunny days, PV power generation shows a relatively regular variation characteristic with sunlight intensity. PV output varies with the intensity of solar radiation; therefore, the controllability of PV power generation is also closely related to the intensity of solar radiation, which can be expressed by the following formula: (8) In the formula, W pv This indicates the controllability of photovoltaic power, and its value is positively correlated with the photovoltaic output. r n This indicates the rated intensity of sunlight; once this value is exceeded, the photovoltaic output will no longer change. W pvn This indicates the upper limit of the controllability of photovoltaic power generation; r Indicates light intensity.

[0060] 4) Energy Storage Regulation Capability Assessment: The charge / discharge potential of energy storage devices is updated every hour (1 hour), meaning the battery capacity available for system dispatch is updated based on different power load conditions at different times. The charge / discharge potential of energy storage devices... W i It can be calculated using the following formula: (9) (10) (11) (12) In the formula, W i (t) ist Real-time energy storage devices i The amount of electricity, Wmax i The capacity of base station energy storage battery packs that can participate in system dispatch under different power load backup requirements; Wmax i This represents the minimum energy storage capacity of the base station's energy storage battery pack. Wc i( t This indicates the charging capacity of the energy storage system; Wd i( t This indicates the discharge capacity of the energy storage system; Wd ess This indicates the down-regulation capability of the energy storage system; Wu ess This indicates the up-regulation capability of the energy storage system.

[0061] In practical applications, the battery type can be lithium-ion, sodium-sulfur, or flow battery, and this application embodiment does not limit this.

[0062] (2) The calculation method for the safe operating domain of the distribution network is explained in detail below: A safety domain refers to the set of feasible operating states of a distribution network without violating network constraints. Considering that operating states are defined as power injections at different nodes of the distribution network, the safety domain can be described as follows: (13) Where: Ω∈ R 2n It is the safety region in the complex power space, where n It is the number of nodes in the power distribution network (excluding slack buses). x It is the complex power injection vector in the distribution network, where P =( P 1,…, P n ) T and Q =( Q 1,…, Q n ) T These are active power vectors and reactive power vectors. Since the active / reactive power injection at any node in the distribution network corresponds to a one-dimensional security domain, therefore... n The security domain of the node distribution network is 2. n 3D power injection space (i.e.) R 2n ). f (v0,θ0) ( V , θ )= x Represent the power flow equation, where v 0 and θ 0 represents the predetermined voltage amplitude and phase angle of the standby bus, respectively. g ( I, V , θ The expression )=0 represents the relationship between branch current and node voltage, expressed by Ohm's law. V and I These are the node voltage vector and the branch current vector, which respectively satisfy the voltage constraints. C V and thermal constraint C T : (14) (15) In the formula, V i It is a node i The voltage amplitude at that point is determined by its lower limit. Vm i and VM i The upper limit is constrained. The magnitude of the branch current is limited by this limit. IM ij Constraints. N and B Let represent the sets of nodes and branches in the network, respectively, with the following numbers: n and nb .

[0063] 1) Analytical expression for the thermal stability domain and security domain: The direction of the arrow at each node in the network represents the net power load. It is worth noting that a negative net power load at a node, in other words, net power injection, indicates that power generation exceeds the power load at that node. For simplicity, we will... and Defined as any branch in the power distribution network [[ID= The equivalent power load at the receiving node. and The expression is as follows: (16) (17) In the formula, and It is a branch ​ The active and reactive power loads at the receiving node, and and It is a branch ​ The active and reactive power flow at the point. Represents a node j The set of adjacent downstream nodes.

[0064] Considering the effect of voltage phase angle difference, the relationship between voltage drop and power current on the branch can be expressed as: (18) (19) (20) and It is the voltage at the transmitting and receiving ends of the branch ( V i and V j (Indicates their size). R j and X j These are the resistance and reactance of the branch; and These represent the branch voltage drops for the real and imaginary parts, respectively. Based on Ohm's law, the branch... ​ The current can be obtained by the following formula: (twenty one) The magnitude of the branch current can be expressed as: (twenty two) Equation (22) is about and The symmetric equation of , which shows and They have the same effect on the branch current. R / X In high-voltage power distribution networks, active power losses are typically greater than reactive power losses. However, considering that active power losses in a power distribution network represent a relatively small percentage of the total power load, they are negligible. and Power losses in the mid-to-downstream branches. Furthermore, due to the small allowable variation in node voltage (typically within ±3% or ±5%), the voltage amplitude... Assuming Based on these two assumptions, equation (22) can be simplified to: (twenty three) D j Represents nodes in the distribution network j (including nodes) j The set of downstream nodes of ). Set the branch current at its upper limit, that is, if Then the analytical expression for the thermal stability boundary of the safety region can be derived as: (twenty four) (25) 2) Analytical expression for the voltage stability region and safety region: The difference in voltage magnitude between the first and last nodes can be represented by the following scalar equation: (26) According to geometric relations, we have: (27) Due to the small difference in phase angle at the two endpoints of the branch (i.e., Usually very small), molecules ( )yes The first-order element, and yes The second-order elements. We retain the first-order minor elements but ignore the second-order elements. Equation (27) is simplified to: (28) The scalar equation for voltage drop can be expressed as: (29) Ignoring power losses in downstream branches, the voltage amplitude is V 0, (29) can be simplified to: (30) Apply equation (30) to all branches, and we have (31) U j Represents nodes in a distribution network j The set of upstream nodes (including node j). Considering that power loss has a relatively small impact, the voltage magnitude of each node can be expressed as follows: (32) Regarding the upper / lower limits of the voltage amplitude at node j, i.e. The analytical expression for the voltage stability boundary can be obtained as follows: (33) To ensure the convexity of the safety region, the upper voltage bound is represented by a hyperplane.

[0065] The safe operating domain of a distribution network is the feasible injected power space where the voltage amplitude of all nodes and the branch current meet the limit conditions. This provides a geometric representation of the overall system operating state. Any operating point located within the safe domain indicates that it does not violate any network constraints. This concept is the fundamental premise for subsequent optimization and control. In practical applications, the boundary of the safe domain can be dynamically updated through online measurement data to adapt to topology changes; this application does not limit this aspect.

[0066] (3) A flexible resource aggregation method considering the security domain constraints of the distribution network is described in detail below: A flexible resource aggregation method considering the security domain constraints of the distribution network is established, specifically including the objective function and constraints. The model uses minimizing the overall operating cost as the objective function, and the constraints include security domain constraints, flexible resource regulation capability constraints, and distribution network-related constraints.

[0067] The primary objective in flexible resource aggregation is to maximize economic benefits. Therefore, the flexible resource aggregation method considering the security domain constraints of the distribution network has the following objective function: (34) In the formula, This indicates the market price of flexible load aggregators. This indicates the actual output of the flexible load aggregator.

[0068] When flexible loads are aggregated, the following constraints exist: 1) Distribution network power flow constraints: The branch power flow model adopts the DistFlow power flow model, which can be specifically described as follows: (35) (36) (37) (38) In the formula, V i,t , V j,t Indicates the corresponding node i ,node j voltage, ​ Indicates the line ​ The current, ​ and ​ Indicates the active and reactive power on the line. r ji and x ji This indicates the resistance and reactance of the circuit. ​ Indicates that at time t Time node k Active power injected into the node, ​ It is a node i In time t The active power of the fixed load present at the time node. ​ Represents a node In time t Active power of distributed gas turbine units ​ Indicates that at time t Time node k The reactive power injected into the node, ​ It is a node iIn time t The reactive power of fixed loads present at the time node, ​ Represents a node i In time t The reactive power of distributed gas turbine units; ​ and ​ These represent the magnitude of active and reactive power regulated by flexible resources, respectively.

[0069] Since equation (36) is non-convex, it is relaxed, and the specific expression is as follows: (39) 2) Distribution network security domain constraints: Distribution networks are subject to thermal stability security domain constraints and voltage stability security domain constraints, which can be specifically described as follows: (40) (41) (42) 3) Flexible load adjustment constraints The flexible load must meet the aforementioned adjustment constraints, which can be specifically stated as follows: (43) In the formula, , These represent the upper and lower limits of flexible resources, respectively.

[0070] At this point, the model for the flexible resource aggregation method considering the security domain constraints of the distribution network has been established and can be solved using a commercial solver.

[0071] Based on the DistFlow equation and the relationship between line voltage drop, a voltage stability safety domain constraint expression with active / reactive power as variables is derived. Using Ohm's law and branch current limits, a quadratic cone constraint regarding the total downstream injected power is constructed as the boundary of the thermal stability safety domain. This quadratic cone constraint can be directly embedded into a convex optimization solver, effectively preventing line overload. In practical applications, heavier lines can be assigned higher weights to prioritize their safety; this embodiment does not limit this. The intersection of the voltage stability domain and the thermal stability domain is used as the comprehensive safe operating region to determine whether the system exceeds its limits. A single-dimensional safety domain cannot fully reflect the risks under complex operating conditions; both voltage and current factors must be considered together. Only when both subdomains are satisfied is the system considered to be in a safe operating state. This joint boundary constitutes a closed high-dimensional space, providing a complete feasibility criterion for scheduling decisions. In practical applications, the margins of each boundary can be adjusted according to seasonal characteristics; this embodiment does not limit this.

[0072] (4) The operational control strategy for flexible resources outside the security domain is detailed below: A model for the operation and regulation strategy of flexible resources outside the safety domain is established, including an objective function and constraints. The objective function of the model is to minimize the weighted distance from the safety domain. The constraints of the model include safety domain constraints, flexible resource regulation capacity constraints, and distribution network-related constraints. It also considers constraints on the rapid regulation of flexible resources, such as the maximum charge and discharge rate of energy storage, and adjusts the safety domain constraint to a soft constraint. Specifically, it can be represented as follows: When a distribution network is restored, it is required to minimize the weighted distance from the safety domain. Therefore, the flexible resource operation and control strategy model outside the safety domain has the following objective function. (44) In the formula, V and I These are the voltage weights and thermal stability weights for deviations from the safe domain, respectively.

[0073] The model's constraints include safety domain constraints, flexible resource adjustment capability constraints, and distribution network-related constraints. It also considers constraints related to rapid adjustment of flexible resources, such as the maximum charge / discharge rate of energy storage, and adjusts the safety domain constraints to soft constraints. Therefore, the model's constraints are as follows.

[0074] 1) Conventional constraints The conventional constraints are consistent with those used when operating within the safety domain, including flexible resource regulation capacity constraints and distribution network-related constraints, namely Equations (35) to (39) and Equation (43).

[0075] 2) Soft constraints of security domains Since the system is operating outside the safety domain, its operational state cannot meet the constraints of the safety domain. Therefore, the safety domain is adjusted to a soft constraint, allowing short-term exceedances while minimizing the exceedance time. (47) (48) 3) Maximum charge / discharge rate constraint for energy storage When adjusting the distribution network back to its safe operating range, the maximum charge and discharge rate of energy storage needs to be considered, which can be specifically described as follows: (50) In the formula, ​ This indicates the rate limit for charging and discharging energy storage.

[0076] ​ This is a schematic diagram representing the safety domain cross-section during the operation of the distribution network. The safety domain cross-sections of nodes 10 and 14 are visualized to demonstrate the effectiveness of the safety domain algorithm. ​A comparison of voltage safety during aggregation with and without considering the safety domain shows that the voltage does not exceed the limit when the safety domain is considered, and the method proposed in this application is practical and effective. ​ The results of the regulation of flexible resources when operating outside the safety domain show that the method proposed in this application can quickly adjust the voltage into a safe and stable range.

[0077] At this point, the proposed flexible resource operation and control strategy model outside the safety domain has been established and can be effectively solved using a commercial solver. The results show that the proposed flexible resource control strategy can be quickly adjusted to operate within the safety domain of the distribution network in a short period of time.

[0078] To address economic considerations, this application provides an in-depth analysis of the regulation potential and economic benefits of flexible loads. It aims to maximize overall economic benefits while satisfying safety domain constraints. Regarding safety objectives, this application analyzes the analytical expressions for the thermal stability safety domain and voltage stability safety domain existing in the distribution network during operation, and proposes flexible resource regulation strategies when operation exceeds these safety domains. Finally, the economic efficiency under safety domain constraints and the regulation capability outside of safety domain constraints are verified using IEEE 33-node data.

[0079] Furthermore, the objective within the safety domain of this application is to maximize the revenue of the flexible load aggregator; the objective outside the safety domain is to minimize the deviation weight distance. When the system exceeds limits, voltage and current constraints are converted into relaxation constraints that allow short-term overruns, and a penalty term is introduced to guide recovery. Differentiated weights are assigned to voltage overruns and line overloads at different locations to reflect their impact on system safety. The maximum charge and discharge rate limit of energy storage is considered in emergency control to ensure that control commands are physically executable. The non-convex DistFlow power flow equations are subjected to second-order cone relaxation (SOCP) to transform them into a convex optimization problem that can be solved efficiently. Commercial solvers such as Gurobi, CPLEX, or MOSEK are used to solve the mixed-integer nonlinear programming model. Commercial solvers have powerful global search capabilities and stability, and can handle complex scheduling models containing continuous variables, integer variables, and nonlinear constraints. The modeling and solving process is integrated through MATLAB / YALMIP or Python / PuLP interfaces. In practical applications, open-source solvers such as SCIP or Couenne can also be used as alternatives, and this application does not limit this.

[0080] Therefore, the method described in this application is applicable to typical power distribution system scenarios such as urban residential areas, industrial parks, and campus microgrids. This application exhibits good versatility and portability. Urban residential areas, primarily driven by residential loads, are suitable for large-scale demand response; industrial parks have centralized management platforms, facilitating the coordination of high-power equipment; and campus microgrids, integrating rooftop photovoltaics, energy storage, and electric vehicles, are ideal carriers for demonstrating "source-grid-load-storage" synergy. In practical applications, it can also be extended to other scenarios such as commercial buildings and transportation hubs, but this application does not limit these applications.

[0081] The second objective of this application is to provide a method for flexible resource regulation of a distribution network that takes into account the operational safety domain. Based on the above-mentioned method for flexible resource regulation of a distribution network that takes into account the operational safety domain, the method includes: The flexible resource potential model building module is used to build a flexible resource potential model under the constraints of distribution network operation, taking user-side flexible resources as the object. The flexible resource adjustment model establishment module is used to determine the feasible operating range of the distribution network without violating any operating constraints by introducing the quadratic terms of active and reactive power injected by the nodes using the security domain analysis method, thus obtaining a flexible resource adjustment model that combines the operating constraint boundary of the distribution network. The user-side resource aggregation model construction module constructs a user-side resource aggregation model that considers the distribution network operation safety domain, based on the flexible resource potential model under the distribution network operation constraints and the flexible resource adjustment model combined with the distribution network operation constraint boundary. The solution module is used to solve the user-side resource aggregation model that considers the safety domain of the distribution network operation, and to perform user-side resource aggregation scheduling based on the solution results.

[0082] A third objective of this application is to provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the aforementioned flexible resource regulation method for a distribution network considering operational safety domains. The device also includes a communication interface and a bus.

[0083] A fourth objective of this application is to provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned flexible resource regulation method for a distribution network that takes into account operational security domains.

[0084] A fifth objective of this application is to provide a computer program product comprising computer instructions that instruct a computer to execute the aforementioned flexible resource regulation method for a distribution network that takes into account operational security domains.

[0085] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process ​ One or more processes and / or boxes ​ The function specified in one or more boxes.

[0086] These computer program instructions can also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. ​ One or more processes and / or boxes ​ The steps of the function specified in one or more boxes.

[0087] This application may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application may take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, readable storage media, optical storage, etc.) containing computer-usable program code.

[0088] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... ​ One or more processes and / or boxes ​ A device that provides the functions specified in one or more boxes.

[0089] Obviously, the described embodiments are only some, not all, of the embodiments in this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort should fall within the scope of protection of this application.

[0090] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application and not to limit them. Although this application has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of this application. Any modifications or equivalent substitutions that do not depart from the spirit and scope of this application should be covered within the protection scope of the claims of this application.

Claims

1. A method for flexible resource regulation of a distribution network considering the operational safety domain, characterized in that, include: Based on historical operational data and equipment parameters of flexible resources, the upward and downward adjustment capabilities at different time scales are evaluated, and a comprehensive adjustment potential model is constructed. Combining the distribution network topology and line parameters, the voltage stability boundary and thermal stability boundary are derived using the power flow equation. An analytical expression for the spatial safety domain with active power and reactive power injected into the nodes as variables is established, forming a safety domain that does not violate the voltage amplitude limit and branch current overload constraints. Based on the comprehensive regulation potential model, when the system operates within the safety domain, a flexible resource aggregation model considering the safety domain constraints of the distribution network is established, including an objective function and constraints. The objective function is to maximize the economic benefits of the flexible resource aggregator. The constraints include distribution network power flow constraints, distribution network safety domain constraints, and flexible resource regulation constraints. The safety domain is used as a hard constraint, and the optimal scheduling scheme is obtained by solving the flexible resource aggregation model. Based on the optimal scheduling scheme, flexible resource regulation of the distribution network is implemented. When the system operating point is detected to be outside the safety domain boundary, it automatically switches to emergency regulation mode. The flexible resource operation and regulation strategy model outside the safety domain is adopted, including objective function and constraints. The objective function is to minimize the weighted distance of deviation from the safety domain. The constraints include safety domain constraints, flexible resource regulation capability constraints, and distribution network-related constraints. The safety domain constraints are adjusted to soft constraints, and combined with the maximum charge and discharge rate limit of fast response resources, emergency regulation instructions are generated to guide the system to quickly return to the safety domain.

2. The method for flexible resource regulation of a distribution network considering the operational safety domain according to claim 1, characterized in that, Based on historical operational data and equipment parameters of flexible resources, the upward and downward adjustment capabilities are evaluated at different time scales, and a comprehensive adjustment potential model is constructed; including: The regulation potential of air conditioning, electric vehicles, distributed photovoltaics, and energy storage are analyzed separately. Taking into account user comfort and willingness to accept dispatch, the regulation potential is summed to obtain the comprehensive range of flexible resource regulation potential.

3. The method for flexible resource regulation of a distribution network considering the operational safety domain according to claim 1, characterized in that, The security domain is surrounded by several high-dimensional surfaces, which are defined by voltage and thermal constraints; the curved surfaces of the security domain constrain the network to normal operation without violating network constraints. Among them, the thermal stability boundary considers the safety of the distribution network from the perspective of power and line current, while the voltage stability boundary considers the safety of the distribution network from the perspective of voltage. The thermal stability boundary and the voltage stability boundary constitute the constraints of the flexible resource aggregation method within the safety domain and the flexible resource regulation strategy outside the safety domain.

4. The method for flexible resource regulation of a distribution network considering the operational safety domain according to claim 1, characterized in that, The safe operating domain of the distribution network is the feasible power injection space in which the voltage amplitude of all nodes and the branch current meet the limit conditions. The derivation of voltage stability boundary and thermal stability boundary using power flow equations includes: Based on the DistFlow equation and the relationship between line voltage drop, a voltage stability security domain constraint expression with active / reactive power as variables is derived. Using Ohm's law and the branch current limit, a quadratic cone constraint with respect to the total injected power downstream is constructed as the boundary of the thermal stability safety domain; The intersection of the voltage stability domain and the thermal stability domain is used as the comprehensive safe operating area to determine whether the system exceeds the limits.

5. The method for flexible resource regulation of a distribution network considering the operational safety domain according to claim 1, characterized in that, The analytical expression of the thermally stable boundary is: The analytical expression for the voltage stability boundary is: In the formula, α k and β k Representing nodes respectively k The coefficients corresponding to active and reactive power; P k and Q k Representing nodes respectively k The magnitude of active and reactive power; V 0 represents a node j The voltage amplitude; IM ij Represents a node i To the node j The magnitude of the branch current; D j Represents a node j The set of downstream nodes; B Represents the set of branches in a network; V j This indicates the voltage level at the branch receiving end; U j Represents nodes in a distribution network j The set of upstream nodes; R k and X k Representing nodes respectively k The equivalent resistance and equivalent reactance of the downstream nodes; P l and Q l Representing nodes respectively l The active power and reactive power.

6. The method for flexible resource regulation of a distribution network considering the operational safety domain according to claim 1, characterized in that, The flexible resource aggregation model considering the security domain constraints of the distribution network is specifically as follows: Objective function: In the formula, C flx i This indicates the market price of flexible load aggregators. P flx i This indicates the actual output of the flexible load aggregator; The constraints include: 1) Distribution network power flow constraints In the formula, V i,t , V j,t Indicates the corresponding node i ,node j voltage, I ji,t Indicates the line ji The current, PLine ji,t and QLine ji,t Indicates the active and reactive power on the line. r ji and x ji This indicates the resistance and reactance of the circuit. PLine k,t Indicates that at time t Time node k Active power injected into the node, Pload i,t It is a node i In time t The active power of the fixed load present at the time node. Pgen i,t Represents a node In time t The active power of the distributed gas turbine unit. Qload k,t Indicates that at time t Time node k The reactive power injected into the node, Qload i,t It is a node i In time t The reactive power of fixed loads present at the time node, Qgen i,t Represents a node i In time t The reactive power of distributed gas turbine units; Pflx i,t and Qflx i,t These represent the magnitude of active and reactive power regulated by flexible resources, respectively. 2) Distribution network security domain constraints, including thermal stability security domain constraints and voltage stability security domain constraints: In the formula, Vm j and VM j These represent the minimum and maximum voltage values ​​at the branch receiving end, respectively. 3) Flexible load adjustment constraints: In the formula, , These represent the upper and lower limits of flexible resources, respectively.

7. The method for flexible resource regulation of a distribution network considering the operational safety domain according to claim 1, characterized in that, The aforementioned flexible resource operation and control strategy model outside the security domain is specifically as follows: Objective function: In the formula, T It is a collection of time; V and I These are the voltage weights and thermal stability weights, respectively, for deviations from the safe domain. Indicates the line ij The upper limit of current; Specific conditions include: 1) Conventional constraints, including constraints on flexible resource regulation capacity and distribution network-related constraints; 2) Soft constraints of security domains: 3) Maximum charge / discharge rate constraint for energy storage: In the formula, Indicates the magnitude of the soft constraint relaxation voltage; Indicates the magnitude of the soft constraint relaxation current; Indicates the energy storage capacity; ramp This indicates the rate limit for charging and discharging energy storage.

8. A flexible resource regulation system for a distribution network that considers the operational safety domain, characterized in that, include: The potential assessment module is used to evaluate the upward and downward adjustment capabilities at different time scales based on historical operating data and equipment parameters of flexible resources, and to construct a comprehensive adjustment potential model. The safety domain calculation module is used to combine the distribution network topology and line parameters, use power flow equations to derive voltage stability boundary and thermal stability boundary, establish a spatial safety domain analytical expression with node injected active power and reactive power as variables, and form a safety domain that does not violate voltage amplitude over-limit and branch current overload constraints. The flexible resource aggregation module is used to establish a flexible resource aggregation model considering the distribution network security domain constraints when the system is operating within the security domain, based on the comprehensive regulation potential model. The model includes an objective function and constraints. The objective function is to maximize the economic benefits of the flexible resource aggregator. The constraints include distribution network power flow constraints, distribution network security domain constraints, and flexible resource regulation constraints. The security domain is used as a hard constraint to solve the flexible resource aggregation model and obtain the optimal scheduling scheme. The operation and control module is used to regulate the flexible resources of the distribution network based on the optimal scheduling scheme. When the system operating point is detected to be outside the safety domain boundary, it automatically switches to the emergency control mode and adopts the flexible resource operation and control strategy model outside the safety domain, including objective function and constraints. The objective function is to minimize the weighted distance of deviation from the safety domain. The constraints include safety domain constraints, flexible resource adjustment capability constraints, and distribution network-related constraints. The safety domain constraints are adjusted to soft constraints, and combined with the maximum charge and discharge rate limit of fast response resources, emergency control instructions are generated to guide the system to quickly return to the safety domain.

9. A device for running a distribution network location and capacity determination algorithm, characterized in that, include: Memory, used to store computer programs; A processor, configured to implement the flexible resource regulation method for distribution networks considering operational security domains as described in any one of claims 1-6 when executing the computer program.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the flexible resource regulation method for distribution networks that takes into account the operational security domain as described in any one of claims 1-6.

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