A user side resource aggregation scheduling method, system and related device

Abstract

The application discloses a user-side resource aggregation scheduling method and system and related devices, and belongs to the technical field of power system scheduling. The method comprises the following steps: determining a safe domain of a distribution network under the condition that any operation constraint is not violated, and obtaining a flexible resource regulation model combined with a boundary of the operation constraint of the distribution network; describing an accurate safe domain of a single resource by using a convex polyhedron; then, a user-side flexible resource is aggregated by using a zonotope to describe the accurate safe domain of the single resource; and based on a flexible resource potential model under the operation constraint of the distribution network and the flexible resource regulation model combined with the boundary of the operation constraint of the distribution network, a user-side resource aggregation model considering the safe domain of the operation of the distribution network is constructed; the user-side resource aggregation model considering the safe domain of the operation of the distribution network is solved by using a zonotope, and user-side resource aggregation scheduling is performed based on a solving result. The application is helpful to solve the concurrent scheduling problem of a plurality of small-scale distributed resource clusters.

Description

TECHNICAL FIELD

[0001] The application relates to a user-side resource aggregation scheduling method and system and related devices, and belongs to the technical field of power system scheduling. BACKGROUND

[0002] With the reform of the energy ecosystem and the rapid development of distributed energy, integrating scattered demand-side flexible distributed resources and realizing resource centralized scheduling have become a solution to the power system scheduling strategy. In a distributed energy community, small-scale flexible resources come from the adjustable load of producers and consumers and small-scale energy storage systems. A large number of small-scale flexible resources scattered at the bottom can be aggregated by aggregating the feasible adjustment range of each device to obtain the overall flexible response capability of the electrical equipment cluster, thereby achieving unified management and scheduling.

[0003] However, without proper coordination, the power injected by distributed energy may violate the operation limits of the distribution network and cause problems such as overvoltage and line congestion. In the process of net-zero carbon transformation, the distribution network is facing the problems of increased total demand and peak demand due to the electrification of transportation and heating, as well as the great challenge of significant uncertainty brought by renewable energy generation and customer behavior (such as electric vehicle travel behavior). Therefore, distribution network operators need effective tools to assess the capacity of the distribution network and actively manage and effectively expand the distribution network in the integration of generation and demand. SUMMARY

[0004] The purpose of the present application is to solve the problems of the prior art, and provide a user-side resource aggregation scheduling method, system and related devices based on a security domain to realize the aggregation of distributed energy.

[0005] To achieve the above-mentioned objectives, the technical solutions adopted by the present application are as follows:

[0006] In a first aspect, the present application provides a user-side resource aggregation scheduling method, comprising:

[0007] A flexible resource potential model under the operation constraint requirements of the distribution network is established for the user-side flexible resources;

[0008] A security domain analysis method is used to determine the security domain of the distribution network under the condition that no operation constraints are violated by introducing the quadratic term of the active and reactive power injected by the node, and a flexible resource adjustment model combined with the boundary of the operation constraints of the distribution network is obtained;

[0009] The precise security domain of a single resource is described using a convex polyhedron, and then the precise security domain of a single resource is described using a chino polyhedron to aggregate user-side flexible resources. Based on the aggregation of user-side flexible resources in the precise security domain of a single resource, and based on the flexible resource potential model under the aforementioned distribution network operation constraints and the flexible resource adjustment model combined with the distribution network operation constraint boundary, a user-side resource aggregation model considering the distribution network operation security domain is constructed.

[0010] The user-side resource aggregation model considering the safety domain of the distribution network is solved using the Chino polyhedron, and user-side resource aggregation scheduling is performed based on the solution results.

[0011] As a further improvement to this application, the user-side flexible resources include temperature-controlled loads and distributed energy storage;

[0012] Establishing a flexible resource potential model under the constraints of distribution network operation includes:

[0013] Establish a safety domain for the temperature-controlled load, specifically, the response deviation of the temperature-controlled load is directly related to temperature, describing the temperature changes in the room containing the temperature-controlled load; the safety domain of the temperature-controlled load satisfies comfort constraints and power constraints;

[0014] Establish a safety domain for distributed energy storage, specifically where the energy storage charging capacity is consistent with the energy storage discharging capacity within a cycle; the safety domain for temperature-controlled loads satisfies comfort constraints, power constraints, and energy constraints.

[0015] Among them, the comfort constraint meets the minimum and maximum temperature for user comfort, the power constraint meets the corresponding maximum and minimum power limits, and the energy constraint must meet the charging or discharging power being limited by the maximum and minimum charging or discharging power, and is also subject to the upper and lower limits of energy.

[0016] As a further improvement to this application, the security domain analysis method is adopted, which determines the security domain of the distribution network without violating any operating constraints by introducing quadratic terms of active and reactive power injected by nodes, thus obtaining a flexible resource adjustment model that combines the operating constraint boundary of the distribution network, including:

[0017] The safety domain analysis method is used to analyze the operating state of the distribution network. First, the equivalent node power injection is defined. Then, by considering the relationship between voltage drop and current, quadratic expressions describing the thermal boundary and voltage boundary are derived to describe the thermal boundary and voltage boundary of the distribution network. Based on the boundary conditions of the distribution network under different operating states, the safety domain of the distribution network is determined without violating any operating constraints.

[0018] Based on the safety domain under the condition that the distribution network does not violate any operating constraints, the direction of power increase within the safety domain is generated, and then the true boundary points of the safety domain are solved.

[0019] A flexible resource regulation model that incorporates the operational constraints of the distribution network is derived from the actual boundary points of the security domain.

[0020] As a further improvement to this application, the method of deriving the quadratic expressions describing the thermal boundary and the voltage boundary includes:

[0021] Construct a safe domain and determine its boundaries. Based on the boundaries of the safe domain, determine the analytical expressions for the safe domain boundaries, including analytical expressions for the thermal boundaries and analytical expressions for the voltage boundaries.

[0022] As a further improvement to this application, the step of generating the power increase direction within the safety domain based on the safety domain under the condition that the distribution network does not violate any operating constraints, and then solving for the true boundary points of the safety domain, includes:

[0023] The direction of power increase is represented by the power injection vector in the high-dimensional power injection space of the safety domain. The origin of the power injection space is chosen as the starting point of all power injection vectors, and the endpoints of the power injection vectors are evenly distributed in the high-dimensional power injection space.

[0024] Generate a spatial vector, where each component of the power injection vector follows a normal distribution; along the direction of sufficient power increase, obtain the true boundary points on all thermal and voltage boundaries surrounding the safe domain;

[0025] Along each power increase direction, a true boundary point is obtained by extending the initial power injection vector to its maximum value. A positive constant is introduced as a coefficient to extend the power increase direction, and the true boundary point along any power increase direction is calculated by the optimization model.

[0026] By repeatedly solving the optimization model that considers different power growth directions, the actual boundary points on each thermal boundary and voltage boundary were obtained.

[0027] As a further improvement to this application, the step of describing the precise security domain of a single resource using a convex polyhedron, and then aggregating user-side flexible resources by describing the precise security domain of a single resource using a chino polyhedron, includes:

[0028] The precise security domain of a single resource is described using a Chino polyhedron, which is described by a convex polygon. The Chino polyhedron of the precise security domain is described by a mathematical expression. A Chino polyhedron is a convex polyhedron generated by generating vectors, and the boundary of the convex polyhedron is formed by a linear combination of vectors.

[0029] For a single precise security domain, the approximation metric is calculated by using the Cino polyhedron with the highest approximation. By defining an approximation metric, a set of normal vectors is selected, and the total width of the Cino polyhedron in one direction and the total width of the precise security domain in that direction are calculated along the direction of each normal vector. Based on the approximation metric, the precise security domain of a single resource is used to aggregate user-side flexible resources.

[0030] Secondly, this application provides a user-side resource aggregation and scheduling system, comprising:

[0031] 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.

[0032] The flexible resource regulation model establishment module is used to determine the safety domain 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 regulation model that combines the operating constraint boundary of the distribution network.

[0033] The user-side resource aggregation model construction module is used to describe the precise security domain of a single resource using convex polyhedra, and then use the chino polyhedra to describe the precise security domain of a single resource to aggregate user-side flexible resources. Based on the aggregation of user-side flexible resources in the precise security domain of a single resource, and based on the flexible resource potential model under the power distribution network operation constraints and the flexible resource adjustment model combined with the power distribution network operation constraint boundary, a user-side resource aggregation model considering the power distribution network operation security domain is constructed.

[0034] 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.

[0035] 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 user-side resource aggregation and scheduling method.

[0036] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the user-side resource aggregation and scheduling method.

[0037] Fifthly, this application provides a computer program product, the computer program product including computer instructions, the computer instructions instructing a computer to execute the user-side resource aggregation and scheduling method.

[0038] The beneficial effects of the technical solution proposed in this application are:

[0039] To achieve the effective utilization of flexible distributed resources, this application takes user-side flexible resources as the main body for potential mining and establishes a flexible resource potential model under the constraints of distribution network operation. To ensure the safe operation of the distribution network during the flexible resource potential mining process, distribution network operators need effective tools to assess the network's capabilities. This is achieved by combining a security domain model considering both thermal and voltage boundaries to ensure active and effective aggregation. Furthermore, the precise security domain of a single resource is described using a Chino polyhedron, making it easier to handle aggregation processes in high-dimensional spaces and large-scale groups. The precise security domain of a single resource can be described in the form of a convex polyhedron. Aggregating user-side flexible resources through this precise security domain constructs a user-side resource aggregation model considering the distribution network's operational security domain, which helps solve the concurrent scheduling challenges of numerous small-scale distributed resource clusters. Compared with traditional methods, this application is more helpful in accurately assessing the operating status of the distribution network and ensuring its safe operation within the security boundary, improving computational efficiency and the accuracy and efficiency of calculating the security domain boundary in high-dimensional space. This method can effectively aggregate and schedule distributed resources, improving the computational feasibility of decision-making. It solves the problem of concurrent scheduling of large-scale flexible energy equipment and small distributed resource clusters, improving the flexibility and efficiency of scheduling. Attached Figure Description

[0040] Figure 1 This is a schematic diagram of the user-side resource aggregation and scheduling method provided in this application;

[0041] Figure 2 This is a schematic diagram of the user-side resource aggregation and scheduling system for the distribution network operation security domain provided in this application;

[0042] Figure 3 A schematic diagram of an electronic device provided in this application. Detailed Implementation

[0043] 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.

[0044] 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.

[0045] Terminology Explanation:

[0046] Prosumers are a portmanteau of "producer" and "consumer," referring to individuals or entities that both produce energy (such as electricity and heat) and consume the energy they produce. In the energy sector, prosumers typically possess distributed energy resources (DERs), such as solar photovoltaic panels, small wind turbines, energy storage systems, and electric vehicles, enabling them to flexibly produce, store, and consume energy according to their own needs and energy market conditions.

[0047] A security domain refers to a logical subnet or distribution network environment within the same system, divided according to factors such as the nature of the information, the users, security objectives, and policies. It is a collection of subnets or distribution networks with shared security protection needs, mutual trust, and identical security access control and boundary control policies.

[0048] Flexible resources are those that are highly adaptable, adjustable, and convertible, capable of rapidly adjusting their function, scale, or use to cope with uncertainty or change under different needs, environments, or mission conditions.

[0049] Kinohedron is a dynamic polyhedron whose geometry can be dynamically adjusted through parametric design, thereby changing its shape, volume or surface features while keeping topological properties (such as the connection relationships between vertices, edges and faces) unchanged.

[0050] Voltage boundaries refer to the permissible voltage fluctuation range in a power grid. They are usually based on the rated voltage and specify an upper limit (overvoltage) and a lower limit (undervoltage).

[0051] Thermal boundary refers to the maximum temperature limit that power grid equipment (such as transmission lines and transformers) is allowed to operate. Exceeding this temperature may lead to accelerated aging or damage to the equipment.

[0052] Example 1

[0053] like Figure 1 As shown, this application provides a user-side resource aggregation and scheduling method. Based on the distribution network operation security domain, the user-side resource aggregation and scheduling method includes the following steps:

[0054] Step (1) Construct a flexible resource potential model under the constraints of power distribution network operation;

[0055] Specifically, the construction of the flexible resource potential model under the operational constraints of the distribution network in step (1) above is described in detail below:

[0056] User-side flexible resources include temperature-controlled loads and distributed energy storage.

[0057] Temperature-controlled loads are common electrical devices among producers and consumers, and as adjustable controllable loads, they possess significant regulation potential. The user's willingness and response to temperature-controlled loads are highly sensitive to temperature; that is, the response deviation of temperature-controlled loads is directly related to temperature, and temperature-controlled loads must meet comfort constraints. Generally, constraints describing the safety domain of a device include power constraints, energy constraints, and ramp rate constraints. Since temperature-controlled loads do not involve energy storage, they can be characterized by describing power constraints over a given time scale, ultimately establishing the system's safety domain.

[0058] The power constraints of distributed energy storage are similar to those of temperature-controlled loads, but in addition, the energy storage problem of distributed energy storage also needs to be considered, so energy constraints should also be included. Within a complete charging cycle, it is necessary to ensure that the remaining energy at the start of the energy storage system is equal to the remaining energy at the end of the cycle, that is, within one cycle, the amount of energy stored for charging is consistent with the amount of energy stored for discharging.

[0059] This application considers user-side flexible resources such as temperature-controlled loads and distributed energy storage, and transforms them into a model at a certain confidence level through a conditional value at risk model, thereby further supporting the calculation of regulation capacity.

[0060] Step (2) Construct a flexible resource adjustment model that incorporates the operational constraints of the distribution network;

[0061] This application utilizes the Chino polyhedron to approximate the precise security domain of a single resource, making it easier to handle aggregation processes in high-dimensional spaces and large-scale groups. The precise security domain of a single resource can be described in the form of a convex polyhedron. User-side flexible resources are aggregated using this precise security domain to construct a user-side resource aggregation model that considers the operational security domain of the distribution network.

[0062] Specifically, the technical solution for constructing a flexible resource adjustment model that incorporates the operational constraints of the distribution network in step (2) above is detailed below:

[0063] First, this application proposes a safety domain analysis method for the operational state analysis of distribution networks. The core of this method lies in describing the thermal and voltage boundaries of the distribution network using novel expressions, thereby determining the safety domain of the distribution network without violating any operational constraints. In distribution networks, thermal and voltage boundaries are key factors ensuring the safe and stable operation of the system. Voltage boundaries relate to the upper and lower limits of node voltages, while thermal boundaries are related to the current carrying capacity of lines. Traditional analysis methods often use linearized hyperplane expressions to approximate these boundaries, but this method has limitations when dealing with distribution networks because distribution networks typically have high resistance-to-reactance ratios, making it impossible to accurately describe the operational capabilities of the distribution network.

[0064] To address this issue, this application proposes a safety domain boundary analysis method. This method, by introducing quadratic terms of active and reactive power injected at nodes, can more accurately reflect the boundary conditions of the distribution network under different operating states. Specifically, the method first defines the equivalent node power injection, and then, by considering the relationship between voltage drop and current, derives quadratic expressions describing the thermal and voltage boundaries. These expressions not only include traditional linear terms but also incorporate quadratic terms, thereby capturing the nonlinear characteristics of the distribution network in high-dimensional space. Using this method, the safety domain of the distribution network, i.e., the region encompassing all possible operating states under a given distribution network topology and parameters, can be calculated more accurately.

[0065] Step (3) Flexible distributed resource aggregation and scheduling method based on regional topology.

[0066] Specifically, the technical solution of the flexible distributed resource aggregation and scheduling method based on regional topology in step (3) above is described in detail below:

[0067] This application utilizes the Chino polyhedron to approximate the precise security domain of a single resource, making it easier to handle aggregation processes in high-dimensional spaces and large-scale groups. The precise security domain of a single resource can be described in the form of a convex polyhedron. User-side flexible resources are aggregated using this precise security domain to construct a user-side resource aggregation model that considers the operational security domain of the distribution network.

[0068] Example 2

[0069] The present application will now be described in further detail with reference to the accompanying drawings. A specific embodiment of the present application provides a user-side resource aggregation and scheduling method, the specific implementation of which is described below.

[0070] (1) Construct a flexible resource potential model under the constraints of distribution network operation, as detailed below:

[0071] The producers and consumers in the energy community are mainly residential users, and the flexible resources on the user side include temperature-controlled loads and distributed energy storage.

[0072] 1) Temperature-controlled load:

[0073] Temperature-controlled loads are common electrical devices among consumers and, as adjustable control loads, possess significant adjustment potential. The willingness and response of temperature-controlled load users are highly sensitive to air temperature; that is, the response deviation of temperature-controlled loads is directly related to temperature. Equations (1) and (2) can be used to describe the temperature changes in a room containing a temperature-controlled load. The temperature changes when the temperature-controlled equipment is stopped and started are respectively:

[0074] (1)

[0075] (2)

[0076] In the formula: and They are respectively t Real-time room temperature and outside temperature; R The equivalent thermal resistance of the room; C Equivalent heat capacity; t For a specific moment; The time interval between adjacent moments; The coefficient of performance (COP) of the temperature control equipment; Power of the temperature control equipment.

[0077] Temperature control load T in Comfort constraints must be met, specifically:

[0078] (3)

[0079] In the formula: , These are the minimum and maximum temperatures that meet user comfort standards.

[0080] Generally, constraints describing the safety domain of a device include power constraints, energy constraints, and ramp rate constraints. Since temperature-controlled loads do not involve energy storage, they can be characterized by power constraints over a given timescale. The safety domain of a temperature-controlled load. as follows:

[0081] (4)

[0082] In the formula: , express t The maximum and minimum power limits correspond to each moment.

[0083] 2) Distributed energy storage:

[0084] The power constraints of distributed energy storage are similar to those of temperature-controlled loads, but in addition, the energy storage problem of distributed energy storage also needs to be considered, so energy constraints should also be included.

[0085] (5)

[0086] (6)

[0087] In the formula: It is the first i Distributed energy storage at a time t The charging or discharging power, which is subject to the maximum charging or discharging power. and minimum charging or discharging power It is limited and subject to an upper limit on energy. and lower limit The energy constraint introduces a high-dimensional space, which significantly increases the computational complexity during aggregation. T It is a moment t A set of.

[0088] Within a complete charging cycle, the remaining energy capacity at the start of the energy storage system must be equal to the remaining energy capacity at the end of the cycle. In other words, the amount of energy charged must match the amount of energy discharged within a single cycle.

[0089] (7)

[0090] In the formula: This refers to the actual charging power. for t The actual discharge power at any given moment; For charging efficiency; For discharge efficiency; This is the final moment of the charging synchronization.

[0091] (2) Establish a flexible resource adjustment model that combines the operational constraints of the distribution network, as detailed below:

[0092] 1) The concept of security domain is explained as follows:

[0093] Definition of a safety domain: A safety domain refers to the set of feasible operating states of a distribution network without violating its constraints. Considering that operating states are defined as power injections at different nodes of the distribution network, a safety domain can be described as follows:

[0094] (8)

[0095] In the formula: It is the safety region in the complex power space, where n It is the number of nodes in the distribution network (excluding slack buses). x It is the complex power injection vector in the distribution network, where and 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 Dimensional power injection space. Represent the power flow equation, where v 0 and θ 0 represents the predetermined voltage amplitude and phase angle of the standby bus, respectively; The relationship between branch current and node voltage is expressed using Ohm's law; V and IThese are the node voltage vector and the branch current vector, which respectively satisfy voltage constraints. C V : and thermal constraint C T The details are as follows:

[0096] (9)

[0097] (10)

[0098] in, It is a node i The voltage amplitude at that point is determined by its lower limit. and upper limit Constraints. Branches ij The magnitude of the current is limited by its limits Constraints. N and B Let these represent the sets of nodes and branches in the distribution network, respectively, and their numbers are respectively... n and nb .

[0099] According to the definition of a safety domain, all feasible operating states exist within its boundaries, while any operating state outside the boundaries is infeasible. In this respect, the boundaries of a safety domain represent all limitations on power injection that can be managed by the distribution network, providing information about the distribution network's capabilities. A safety domain is only associated with the distribution network topology and component parameters. As long as the operating state (i.e., net node power injection) is within the safety domain, however generation / consumption variations will limit node voltages / branch currents to their upper / lower limits.

[0100] The boundary of the safety region: The safety region of a distribution network is surrounded by several high-dimensional surfaces defined by voltage and thermal constraints. These surfaces confine the distribution network to its normal operation without violating distribution network constraints. In this study, these high-dimensional surfaces are defined as the boundary of the safety region. Considering the type of constraint, the boundary of the safety region can be further classified into voltage constraint boundaries and thermal boundaries. These are explained separately below.

[0101] 2) The analytical expression for the security domain boundary is explained below:

[0102] 2.1 The analytical expression for the thermal boundary of the safety domain is as follows:

[0103] The direction of the arrows at each node of the distribution network indicates 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 generation exceeds the power load at that node. For simplicity, this application will... and Defined as any branch in the distribution network ijThe equivalent power load at the receiving node. and The expression is as follows:

[0104] (11)

[0105] (12)

[0106] In the formula: and It is a branch ij The active and reactive power loads at the receiving node; and and It is a branch jk The active and reactive power flow at the point; Represents a node j The set of adjacent downstream nodes.

[0107] Branches ij The voltage drop across the voltage can be represented as a voltage phase diagram. This differs from the previous approach, which neglected the transverse component. Compared to the hyperplane expression study, this application considers the influence of voltage phase angle difference (i.e. θ ij )and If it is retained, then the relationship between the voltage drop and power current on the branch can be expressed as:

[0108] (13)

[0109] (14)

[0110] (15)

[0111] 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 It refers to the resistance and reactance of the branch. This represents the longitudinal component of the voltage. Based on Ohm's law, the branches... ij The current can be obtained by the following formula:

[0112] (16)

[0113] The magnitude of the branch current can be expressed as:

[0114] (17)

[0115] Equation (17) 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 (17) can be simplified to:

[0116] (18)

[0117] 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, Let be the current phasor of branch ij. This is the upper limit of the current phasor value. Then the analytical expression for the thermal boundary of the safety domain can be derived as:

[0118] (19)

[0119] (20)

[0120] Where n is the number of node-related parameters involved in the summation. It is with nodes k Correlation coefficient; Let be the active power at node k; For nodes k reactive power at the location; V 0 represents a voltage-related quantity; B This represents the set of branches in a power distribution network.

[0121] As can be seen from equation (12), the thermal boundary is a quadratic form of the net power load at different nodes of the distribution network, which differs from the expression of the hyperplane. When the derivation process involves... P k and Q k Define as a node kWhen net power is injected at a point, the analytical expression of the thermal boundary remains the same as that in (12).

[0122] 2.2 Construct the analytical expression for the voltage boundary of the safety domain, as follows:

[0123] Draw a radius of V i The circle (i.e., the voltage magnitude at the transmitting node of the branch) is used to observe the difference in voltage magnitude between the transmitting and receiving nodes. This can be replaced by the following scalar equation:

[0124] (twenty one)

[0125] in, V i For branch sending end node i Voltage amplitude at the location; V j For branch sending end node j Voltage amplitude at the location; For nodes i and nodes j The voltage amplitude difference between them. The geometric line segment between points B and C;

[0126] Extend the geometric line segment AB so that the circles intersect at point A′. Based on the fact that points A and A′ on the circle are symmetric about OB perpendicular to AA′, we have...

[0127] (twenty two)

[0128] Due to the small difference in phase angle at the two endpoints of the branch (i.e., the node i , j Related angles Usually very small), molecules ( )yes First-order elements, For nodes i , j A change related to the voltage difference between the two sides, and yes The second-order elements. This application retains the first-order minor elements but ignores the second-order elements. (22) is simplified to:

[0129] (twenty three)

[0130] The scalar equation for voltage drop can be expressed as:

[0131] (twenty four)

[0132] Ignoring power losses in downstream branches, the voltage amplitude is (24) can be simplified to:

[0133] (25)

[0134] Apply (25) to all branches, and you will have

[0135] (26)

[0136] U j Represents nodes in a distribution network j (including nodes) j The set of upstream nodes of ). By substituting (4)-(5) into (19) and considering that the effect of power loss is small (compared to the effect of power load), the voltage amplitude of each node can be expressed as:

[0137] (27)

[0138] Regarding nodes j The upper / lower limits of the voltage amplitude at that point, i.e. The analytical expression for the voltage boundary can be obtained as follows:

[0139] (28)

[0140] (29)

[0141] in, This represents the upper limit of the voltage amplitude at node j, indicating the node's voltage level. j The highest voltage amplitude that it can withstand. For nodes j The lower limit of the voltage amplitude at node j, i.e. the minimum voltage amplitude allowed for normal operation of node j; Reference voltage; V j For nodes j The actual voltage amplitude at that location; These are the resistance parameters related to node k in the distribution network; These are the reactance parameters related to node k in the distribution network; For the set related to node j, Let k be the set of downstream nodes. For nodes l Active power at the location; For nodes l reactive power at the location; This is the summation symbol.

[0142] 2.3 The specific steps for generating the power increase direction within the safety domain are as follows:

[0143] Direction of power increase ( The power injection vector in the high-dimensional power injection space of the security domain can be represented by the power injection vector. Considering that power injection at any node can be bidirectional (positive or negative), this embodiment chooses the origin of the power injection space (i.e., The origin (n) serves as the starting point for all power injection vectors. Statistically, the endpoints of these power injection vectors can be uniformly distributed within the high-dimensional power injection space. First, a 2n-dimensional space vector (starting from the origin) is generated, where n represents the number of nodes in the distribution network. :

[0144] (30)

[0145] in, For the power injection vector, P This is the active power injection vector part. Q It is the reactive power injection vector part; , indicating 2 n The number space is real, because the distribution network has... n There are 10 nodes, and each node corresponds to 2 power injection components: active and reactive. For the first k In the simulated vector, the first... i The active power injection component of each node. For the first k In the simulated vector, the first... i The reactive power injection component of each node, d k For the first k A power increase direction vector.

[0146] Where the power injection vector Each component (i.e. , The power follows a normal distribution N(0,1). Then there is a direction that increases the power:

[0147] (31)

[0148] In the formula: d k Inject vector for initial power; This is the power injection vector.

[0149] If sufficient power increase directions are generated after this step, the true boundary points on all thermal and voltage boundaries surrounding the safety region can be obtained along these directions. Operating points on different analytical safety region boundaries can also be obtained.

[0150] 2.4 To find the true boundary points of the safe region, the specific steps are as follows:

[0151] Along each power increase direction in step 1, the initial power can be injected into the vector. d k Extending to its maximum value yields a true boundary point where the power injection vector remains within the safe region, but small increases will cause it to exceed the safe region. A positive constant is introduced. As a coefficient, for The model is then extended. The actual boundary points along any power-increasing direction are calculated using the optimized model, as follows:

[0152] (32)

[0153] in, Add a direction vector to the power. Let P be the active power injection vector, where P is the active power injection vector portion. Q Injecting a vector component into reactive power. A positive constant coefficient is used to determine the direction vector of power increase. To extend, It is related to voltage V Phase angle The relevant function; V is the node voltage magnitude vector. This represents the voltage magnitude at node i. It is a constraint on the node voltage amplitude. This represents the lower limit of the voltage amplitude at node i. This is the upper limit, ensuring that the node voltage remains within a safe operating range. The node voltage phase angle vector. is the voltage phase angle of node i, N: the set of nodes in the distribution network; This indicates that a voltage magnitude constraint is applied to all nodes i. , Let be the current phasor magnitude of branch ij. It is its upper limit. It is a current constraint, where B is the set of branches of the distribution network, ensuring that the branch current does not exceed the upper limit of safe operation. To optimize the variables in the model, the objective function is to maximize... By solving this optimization model, we can obtain the power increase along any direction. d k The corresponding true boundary points of the safe domain are where the power injection vector is inside the safe domain. Further increases would cause it to exceed the safe domain. These boundary points are used to characterize the boundary conditions of the safe domain in each power increase direction.

[0154] The goal of optimizing the model is to derive the maximum value in the predefined direction of increasing power. The constraint will extend the power injection vector. Restricted to a security domain. When At maximum, power injection On the actual boundary of the security domain.

[0155] Furthermore, the optimal critical constraints in the model provide specific safety domain boundaries, and the obtained true boundary points can be used to find critical constraints by determining which inequality constraints of node voltage / branch current are "valid" at the optimal solution.

[0156] For example, if at the optimal solution The obtained true boundary point (i.e., the maximum power injection along the specified power increase direction) leads to V i It reaches its upper limit. This indicates that the obtained true boundary points belong to the range of points obtained from the boundary conditions. A defined upper voltage boundary is established. It's worth noting that optimization solvers (e.g., the Matlab solver) cannot mathematically determine the optimality of a solution during the iteration process using the Lagrangian function of the optimization problem. Therefore, determining which constraint is positive for the optimal solution involves observing that the constraint on the Lagrangian multipliers is non-zero. By iteratively solving the optimization model considering different power growth directions, the true boundary points on each thermal and voltage boundary are obtained, thus forming a set of boundary points.

[0157] (3) Finally, a user-side resource aggregation and scheduling method based on the distribution network operation security domain is constructed, which is described in detail below:

[0158] This application uses the Chino polyhedron to approximate the exact security region of a single resource, making it easier to handle aggregation processes in high-dimensional spaces and large-scale groups. The exact security region of a single resource can be described in the form of a convex polyhedron:

[0159] (33)

[0160] In the formula: P For a single resource, the precise security domain is represented as a convex polyhedron; p For resources in N A point in 3D space; A This is the constraint matrix; b This is the constraint vector.

[0161] The Chino polyhedron Z is mathematically described by the following three elements:

[0162] (34)

[0163] (35)

[0164] A chino polyhedron can be considered as a convex polyhedron generated by generating vectors, the boundaries of which are formed by a linear combination of these vectors. Z For the mathematical description of the Chino polyhedron, c It is the center of the Chino polyhedron. G Describes a set of generators, each generator g This determines the direction of extension of the Cinno polyhedron. It is a set of vectors corresponding to the generators, which determine the extension length in each extension direction.

[0165] For a single exact security domain, the goal is to find a Chino polyhedron that represents it with the highest approximation, and therefore an approximation metric is defined:

[0166] (36)

[0167] (37)

[0168] In the formula: m f As an approximation measure, it represents the degree of approximation between the Chino polyhedron and the exact safe region; △ z j It is the first polyhedron of the Kino polyhedron. j The width along the direction of each normal vector; △ p j It is the precise security domain in the first j The width along the direction of each normal vector; △ z The total width of the Chino polyhedron in a certain direction; F The normal vector matrix; G This is the set of generated vectors.

[0169] In this embodiment, a set of normal vectors is selected, and the total width of the Chino polyhedron in a certain direction is calculated along the direction of each normal vector. and the total width of the precise security domain in a certain direction This allows for the calculation of an approximate metric. Clearly, The maximum value is 1.

[0170] for The calculation first utilizes n The normal vector of the 3D space is calculated. n Find the distance from a point outside the hyperplane to the hyperplane, and then find the maximum distance using an optimization method. The embodiments in this application are not described in detail.

[0171] Based on the Chino polyhedron that is closest to the precise security domain obtained by approximate measurement, the precise security domain of a single resource is used to aggregate user-side flexible resources. Based on the aggregation of user-side flexible resources in the precise security domain of a single resource, and based on the flexible resource potential model under the power distribution network operation constraints and the flexible resource adjustment model combined with the power distribution network operation constraint boundary, a user-side resource aggregation model considering the power distribution network operation security domain is constructed.

[0172] Finally, the user-side resource aggregation model considering the safety domain of the distribution network operation is solved using the Chino polyhedron, and user-side resource aggregation scheduling is performed based on the solution results.

[0173] By solving the following optimization problem, this application can find the Chino polyhedron that best approximates the exact safe domain:

[0174] (38)

[0175] The expression is as follows:

[0176] (39)

[0177] In the formula: c agg It is the center of the aggregated Cino polyhedron; The coefficient vector of the aggregated Chino polyhedron The upper boundary. This is the power deviation vector. To reflect the mapping relationship between the safety domain boundary and power injection, Let be the coefficient vector of the Chino polyhedron, n be the number of nodes in the distribution network, A be the coefficient matrix of the constraints, c be the center vector of the Chino polyhedron, and b be the upper limit vector of the constraints. Represents the coefficient vector Symbolic constraints, J : Sub-unit set,

[0178] In the above scheme, the "power constraints and voltage / current limits" of the distribution network are transformed into the "center, shape factor, and constraint boundary" of a geometric polyhedron. Optimization is used to make the "Chino polyhedron" fit as closely as possible to the real safety domain (all power / voltage combinations that satisfy the operating constraints). The objective function maximizes the "approximation degree," the constraints ensure the polyhedron is within the physically feasible domain, and the aggregation parameters are used to simplify large-scale power grid analysis. Compared with other aggregation scheduling methods, solving the Minkowski inequality using the Chino polyhedron is a simple linear superposition. This linear structure facilitates the calculation of the Minkowski sum, and the computational complexity of adding or deleting devices within the Chino polyhedron after aggregation is also very low.

[0179] In summary, the method proposed in this application can tap the regulation potential of demand-side prosumers and consumers, more accurately describe the operating state range of the distribution network under the condition of not violating thermal and voltage constraints, and help solve the concurrent scheduling problem of many small-scale distributed resource clusters.

[0180] like Figure 2 As shown, the second objective of this application is to provide a user-side resource aggregation and scheduling system. Based on the aforementioned user-side resource aggregation and scheduling method, the system includes:

[0181] 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.

[0182] The flexible resource regulation model establishment module is used to determine the safety domain 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 regulation model that combines the operating constraint boundary of the distribution network.

[0183] The user-side resource aggregation model construction module is used to describe the precise security domain of a single resource using convex polyhedra, and then use the chino polyhedra to describe the precise security domain of a single resource to aggregate user-side flexible resources. Based on the aggregation of user-side flexible resources in the precise security domain of a single resource, and based on the flexible resource potential model under the power distribution network operation constraints and the flexible resource adjustment model combined with the power distribution network operation constraint boundary, a user-side resource aggregation model considering the power distribution network operation security domain is constructed.

[0184] The solution module is used to solve the user-side resource aggregation model considering the safety domain of the distribution network using the Chino polyhedron, and to perform user-side resource aggregation scheduling based on the solution results.

[0185] like Figure 3 As shown, a third objective of this application embodiment is to provide 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 aforementioned user-side resource aggregation and scheduling method. It also includes a communication interface and a bus.

[0186] 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 user-side resource aggregation and scheduling method.

[0187] A fifth objective of this application is to provide a computer program product comprising computer instructions that instruct a computer to execute the aforementioned user-side resource aggregation and scheduling method.

[0188] 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 Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0189] These computer program instructions may 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. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0190] 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.

[0191] 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... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0192] 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.

[0193] 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 methods 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 this application.

Claims

1. A user side resource aggregation scheduling method, characterized in that, include: Taking user-side flexible resources as the object, a flexible resource potential model is established under the constraints of distribution network operation. By adopting the security domain analysis method and introducing the quadratic terms of active and reactive power injected by nodes, the security domain of the distribution network is determined without violating any operating constraints, and a flexible resource regulation model combining the operating constraint boundary of the distribution network is obtained. The precise security domain of a single resource is described using a convex polyhedron, and then the precise security domain of a single resource is described using a chino polyhedron to aggregate user-side flexible resources. Based on the aggregation of user-side flexible resources in the precise security domain of a single resource, and based on the flexible resource potential model under the aforementioned distribution network operation constraints and the flexible resource adjustment model combined with the distribution network operation constraint boundary, a user-side resource aggregation model considering the distribution network operation security domain is constructed. The user-side resource aggregation model considering the safety domain of the distribution network operation is solved by the Chino polyhedron, and user-side resource aggregation scheduling is performed based on the solution results. The user-side flexible resources include temperature-controlled loads and distributed energy storage; The establishment of a flexible resource potential model under the constraints of distribution network operation includes: Establish a safety domain for the temperature-controlled load, specifically, the response deviation of the temperature-controlled load is directly related to temperature, describing the temperature changes in the room containing the temperature-controlled load; the safety domain of the temperature-controlled load satisfies comfort constraints and power constraints; Establish a safety domain for distributed energy storage, specifically where the energy storage charging capacity is consistent with the energy storage discharging capacity within a cycle; the safety domain for temperature-controlled loads satisfies comfort constraints, power constraints, and energy constraints. Among them, the comfort constraint meets the minimum and maximum temperature for user comfort, the power constraint meets the corresponding maximum and minimum power limits, and the energy constraint must meet the charging or discharging power being limited by the maximum and minimum charging or discharging power, and is also subject to the upper and lower limits of energy. The aforementioned security domain analysis method, by introducing quadratic terms of active and reactive power injected by nodes, determines the security domain of the distribution network without violating any operational constraints, resulting in a flexible resource adjustment model that incorporates the operational constraint boundaries of the distribution network, including: The safety domain analysis method is used to analyze the operating state of the distribution network. First, the equivalent node power injection is defined. Then, by considering the relationship between voltage drop and current, quadratic expressions describing the thermal boundary and voltage boundary are derived, thereby obtaining the boundary conditions of the distribution network under different operating states. The safety domain of the distribution network under different operating states is determined by the boundary conditions of the distribution network under different operating states without violating any operating constraints. Based on the safety domain under the condition that the distribution network does not violate any operating constraints, the direction of power increase within the safety domain is generated, and then the true boundary points of the safety domain are solved. A flexible resource regulation model that incorporates the operational constraints of the distribution network is derived from the actual boundary points of the security domain.

2. The method of claim 1, wherein, The derived quadratic expressions describing the thermal and voltage boundaries include: Construct a safe domain and determine its boundaries. Based on the boundaries of the safe domain, determine the analytical expressions for the safe domain boundaries, including analytical expressions for the thermal boundaries and analytical expressions for the voltage boundaries.

3. The method of claim 1, wherein, The safe domain inside the power increase direction is generated based on the safe domain of the power distribution network without violating any operation constraint condition, and then the real boundary point of the safe domain is solved, including: The power increase direction is represented by a power injection vector in a high-dimensional power injection space of the safe domain, the origin of the power injection space is selected as the starting point of all power injection vectors, and the endpoints of the power injection vectors are uniformly distributed in the high-dimensional power injection space; A space vector is generated, each component of the power injection vector obeys a normal distribution; along the generated sufficient power increase direction, the real boundary point on all thermal boundaries and voltage boundaries surrounding the safe domain is obtained; Along each power increase direction, a real boundary point is obtained by expanding the initial power injection vector to its maximum value, a positive constant is introduced as a coefficient, the power increase direction is extended, and the real boundary point along the arbitrary power increase direction is calculated by optimizing the model; By repeatedly solving the optimization model considering different power growth directions, the real boundary point on each thermal boundary and voltage boundary is obtained.

4. The method of claim 1, wherein, The accurate safe domain of a single resource is described by a convex polyhedron, and the accurate safe domain of a single resource is aggregated user-side flexible resource by using a zonotope, including: The accurate safe domain of a single resource is described by a zonotope, and the accurate safe domain of a single resource is described by a convex polygon; the zonotope of the accurate safe domain is described by a mathematical expression, and a zonotope is a convex polyhedron generated by a generating vector, and the boundary of the convex polyhedron is formed by the linear combination of the vector; For a single accurate safe domain, the zonotope with the highest approximation degree is represented, the approximation degree is defined, a set of normal vectors is selected, and the total width of the zonotope in a direction and the total width of the accurate safe domain in the direction are calculated along the direction of each normal vector, so as to calculate the approximation degree, and the accurate safe domain of a single resource is aggregated user-side flexible resource based on the approximation degree.

5. A user side resource aggregation scheduling system, implementing the user side resource aggregation scheduling method of any one of claims 1-4; characterized in that, It includes: A flexible resource potential model establishing module is configured to establish a flexible resource potential model under the operation constraint requirement of a power distribution network by taking user-side flexible resources as objects; A flexible resource regulation model establishing module is configured to determine a safe domain of the power distribution network without violating any operation constraint condition by introducing a quadratic term of active and reactive power injection of nodes through a safe domain analysis method, and obtain a flexible resource regulation model combined with an operation constraint boundary of the power distribution network; A user-side resource aggregation model constructing module is configured to describe an accurate safe domain of a single resource by a convex polyhedron, and aggregate user-side flexible resources of the accurate safe domain of a single resource by using a zonotope, and construct a user-side resource aggregation model considering a power distribution network operation safe domain based on the flexible resource potential model under the operation constraint requirement of the power distribution network and the flexible resource regulation model combined with the operation constraint boundary of the power distribution network on the basis of the accurate safe domain of a single resource aggregated user-side flexible resources; A solving module is configured to solve the user-side resource aggregation model considering the power distribution network operation safe domain, and perform user-side resource aggregation scheduling based on a solving result.

6. An electronic device, comprising: The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the user side resource aggregation scheduling method in any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the user side resource aggregation scheduling method in any one of claims 1-4.

8. A computer program product comprising computer instructions, characterized in that, The computer instructions instruct the computer to execute the user side resource aggregation scheduling method in any one of claims 1-4.

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