Flexible aggregation method, device and equipment of adjustable resources in power distribution network and medium

Abstract

The application relates to the technical field of flexible resource aggregation, in particular to a flexible aggregation method and device for adjustable resources in a power distribution network, equipment and a medium, wherein the method comprises the following steps: determining flexible resources on each node in the power distribution network; constructing a feasible region aggregation model of the power distribution network according to preset safety constraint conditions of the power distribution network and the flexible resources on each node; calculating at least one safety constraint parameter of the feasible region aggregation model according to an expected target of linear flow constraint, and optimizing the feasible region aggregation model based on the at least one safety constraint parameter, so as to perform linear flow safety constraint on the power distribution network by using the optimized feasible region aggregation model. Therefore, the problems that the related art cannot comprehensively consider the aggregation feasible region of the flexible resources in the power distribution network and cannot maximize the flexibility of the flexible resources, and the economy and safety of the whole network operation are reduced are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of flexible resource aggregation, and in particular to a flexible aggregation method and device for adjustable resources in a power distribution network, equipment and a medium. BACKGROUND

[0002] The high penetration of intermittent renewable energy sources such as wind and photovoltaic increases the demand for grid regulation. In this context, the grid can no longer rely solely on the regulation of traditional units, and it is imperative to utilize the regulation capacity of demand-side flexible resources. Some typical demand-side flexible resources include distributed generation, electric vehicles, distributed energy storage, and thermal control loads. The participation of demand-side flexible resources in grid regulation can ensure the safe and stable operation of the grid, promote new energy consumption, and reduce user electricity costs. However, due to the complexity of considering all demand-side resource parameters in grid dispatching and the need to protect the privacy of power users, demand-side flexible resources need to be aggregated before participating in grid regulation. In this mode, the flexible resource aggregator first submits the feasible region of the total power to the distribution network operator, who considers the feasible regions reported by all aggregators within its jurisdiction and the safety constraints of the distribution network to calculate the total power feasible region of the distribution network and report it to the main grid operator. After the clearing or dispatching calculation is completed, the total power of each distribution network is determined, and this total power is distributed to each flexible resource layer by layer for execution. Therefore, it is necessary to accurately construct the aggregation flexibility model of flexible resources in the distribution network to ensure smooth distribution and not to cause excessive computational complexity.

[0003] The current market rules consider the aggregation feasible region of flexible resources in the distribution network relatively simply. For example, the PJM power line market only considers the upper and lower adjustment boundaries of power. The North China market considers power and energy capacity for energy storage and V2G charging piles, and only considers power regulation capacity for ordinary charging piles, electric heating, and other controllable loads. The feasible region described by these methods generally has a large gap from the actual aggregation feasible region. There is a consensus in existing literature that calculating the aggregation feasible region of flexible resources in the distribution network is a problem of seeking the Minkowski sum of high-dimensional space polyhedrons or projecting the high-dimensional space feasible region. Generally, there is no efficient algorithm. The research of existing literature often focuses on approximating this feasible region from the inside or outside, and there is no accurate modeling and calculation method for the aggregation feasible region. SUMMARY

[0004] The present application provides a flexible aggregation method, device, equipment and medium for adjustable resources in a power distribution network to solve the problem that the current market rules do not comprehensively consider the aggregation feasible region of flexible resources in the distribution network, which cannot maximize the flexibility of flexible resources and reduces the economy and safety of the entire network operation.

[0005] The first aspect embodiment of the present application provides a flexible aggregation method of adjustable resources in a power distribution network, comprising the following steps: determining flexible resources on each node in the power distribution network; constructing a feasible region aggregation model of the power distribution network according to preset safety constraint conditions of the power distribution network and the flexible resources on the nodes; calculating at least one safety constraint parameter of the feasible region aggregation model according to an expected target of linear flow constraint, and optimizing the feasible region aggregation model based on the at least one safety constraint parameter, so as to perform linear flow safety constraint on the power distribution network by using the optimized feasible region aggregation model.

[0006] Optionally, in an embodiment of the present application, the step of constructing the feasible region aggregation model of the power distribution network according to the preset safety constraint conditions of the power distribution network and the flexible resources on the nodes comprises: dividing a preset time window into a plurality of time periods according to a preset time interval; constructing an aggregated feasible region of the flexible resources on each node according to boundary parameters of the flexible resources on each node in each time period; and aggregating the aggregated feasible regions of the flexible resources on each node according to preset power distribution network safety constraints and a preset linear power distribution network flow equation, to obtain the feasible region aggregation model of the power distribution network.

[0007] Optionally, in an embodiment of the present application, the expression formula of the feasible region aggregation model is:

[0008]

[0009] wherein X0 represents the feasible region aggregation model, t is a time period index, represents a set of all time periods, T represents a total number of time periods, represents active power at a root node, is an arbitrary subset of and respectively represent upper and lower bounds of power integrated on a time period set , and a superscript n represents node power, represents a T-dimensional column vector composed of .

[0010] Optionally, in an embodiment of the present application, the expected target of the linear flow constraint comprises a first linear flow constraint target and a second linear flow constraint target.

[0011] Optionally, in an embodiment of the present application, when the expected target of the linear flow constraint is the first linear flow constraint target, the step of calculating at least one safety constraint parameter of the feasible region aggregation model according to the expected target of the linear flow constraint, and optimizing the feasible region aggregation model based on the at least one safety constraint parameter comprises:

[0012] The feasible region of all variables in the network is converted into where n is the number of variables, x n,t is the value of the nth variable in the power flow equation at time period t, x n represents a T-dimensional column vector composed of x n,t ;

[0013] For a non-empty subset of the objective set such that satisfies the constraints: and the power flow constraints where m is the number of equations, a m,n is the coefficient of x n,t in the mth equation;

[0014] According to the first optimization formula, the safety constraint parameters and are calculated, and the first optimization formula is: where is the minimum value of , is the maximum value of , and s.t. represents the constraint condition;

[0015] According to the safety constraint parameters and , the feasible region aggregation model is optimized.

[0016] Optionally, in an embodiment of the present application, when the expected target of the linear power flow constraint is the second linear power flow constraint target, the at least one safety constraint parameter of the feasible region aggregation model is calculated according to the expected target of the linear power flow constraint, and the feasible region aggregation model is optimized based on the at least one safety constraint parameter, which includes:

[0017] The power flow transfer distribution factor described in the power flow constraint of the network is calculated according to the following formula:

[0018]

[0019]

[0020]

[0021]

[0022]

[0023] where is the active power increment of branch l at time period t, is the active power increment of node i, is the reference power of branch l, is the reference power of node i, s l,i is the power flow shift distribution factor of branch l with respect to node i, meaning that an increase of 1 unit of power at node i results in an increase of is the set of all nodes in the distribution network, is the set of nodes after removing the balanced nodes, is the set of nodes containing flexible resource aggregators, is the set of branches in the distribution network, and are T-dimensional column vectors composed of and represents the power feasible region at the flexible resource aggregator node;

[0024] According to the power flow shift distribution factor, the power flow constraint of the distribution network is described from the leaf node to the root node along the road, and the feasible region is continuously corrected according to the transmission capacity of the branch until the root node, to obtain a safety constraint parameter, wherein each correction is performed by comparison and summation operation; and the feasible region aggregation model is optimized based on the safety constraint parameter.

[0025] The second aspect of the application provides a flexible aggregation device of adjustable resources in a distribution network, comprising: a determination module configured to determine flexible resources on each node in the distribution network; a construction module configured to construct a feasible region aggregation model of the distribution network according to preset safety constraint conditions of the distribution network and the flexible resources on each node; and a constraint module configured to calculate at least one safety constraint parameter of the feasible region aggregation model according to an expected target of linear power flow constraint, and optimize the feasible region aggregation model based on the at least one safety constraint parameter, so as to perform linear power flow safety constraint on the distribution network by using the optimized feasible region aggregation model.

[0026] Optionally, in an embodiment of the application, the construction module is further configured to divide a preset time window into a plurality of time periods according to a preset time interval, construct an aggregated feasible region of the flexible resources on each node according to boundary parameters of the flexible resources on each node in each time period, and aggregate the aggregated feasible regions of the flexible resources on each node according to preset distribution network safety constraints and a preset linear distribution network power flow equation, to obtain the feasible region aggregation model of the distribution network.

[0027] Optionally, in an embodiment of the application, the expression formula of the feasible region aggregation model is:

[0028]

[0029] wherein X0 represents the feasible region aggregation model, t is a time period index,​ denotes a set of all time periods, T denotes the total number of time periods, denotes the active power at the root node, is an arbitrary subset of and denote the power upper and lower bounds of the integration over the set of time periods , and the superscript n denotes the node power, denotes a T-dimensional column vector composed of .

[0030] Optionally, in an embodiment of the present application, the expected target of the linear power flow constraint includes a first linear power flow constraint target and a second linear power flow constraint target.

[0031] Optionally, in an embodiment of the present application, when the expected target of the linear power flow constraint is the first linear power flow constraint target, the constraint module is further configured to convert the feasible region of all variables in the distribution network into where x n,t is the value of the nth variable in the power flow equation at time period t, x n denotes a T-dimensional column vector composed of x n,t ;

[0032] for a non-empty subset of the target set such that satisfy the constraints: and the power flow constraint where m is the number of equations, a m,n is the coefficient of x n,t in the mth equation;

[0033] According to a first optimization formula, the safety constraint parameters and are calculated, and the first optimization formula is: where is the minimum value of , is the maximum value of , and s.t. denotes the constraint condition.

[0034] According to the safety constraint parameters and , the feasible region aggregation model is optimized.

[0035] Optionally, in one embodiment of the present application, when the expected target of the linear flow constraint is the second linear flow constraint target, the constraint module is further configured to calculate the distribution factor of the distribution network flow constraint described by the flow transfer according to the following formula:

[0036]

[0037]

[0038]

[0039]

[0040]

[0041] wherein, is the active power increment of branch l at time period t, is the active power increment of node i, is the reference power of branch l, is the reference power of node i, l,i is the distribution factor of the flow transfer of branch l with respect to node i, meaning that the power of branch l is increased by one unit when the power of node i is increased by one unit, is the set of all nodes in the distribution network, is the set of nodes after removing the balance nodes, is the set of nodes containing the flexible resource aggregators, is the set of branches in the distribution network, and are T-dimensional column vectors composed of and represents the power feasible region at the flexible resource aggregator node;

[0042] According to the distribution factor of the flow transfer described by the distribution network flow constraint, the feasible region is continuously corrected along the road from the leaf node to the root node until the root node, and the safety constraint parameter is obtained, wherein each correction is performed by comparison and summation operation; and the feasible region aggregation model is optimized based on the safety constraint parameter.

[0043] The third aspect of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the flexible aggregation method of adjustable resources in the power distribution network as described in the above embodiments.

[0044] ​The fourth aspect of the application provides a computer readable storage medium, which stores a computer program, and the program is executed by a processor to implement the flexible aggregation method of adjustable resources in a power distribution network.

[0045] Therefore, the application has at least the following beneficial effects:

[0046] According to the flexible resource aggregation feasible region model on each node, the power distribution network flexible resource aggregation feasible region considering the power distribution network power flow safety constraint is calculated, power flexibility of the flexible resource can be maximized on the premise of guaranteeing the power distribution network power flow safety and power distribution feasibility. Therefore, the related art cannot comprehensively consider the flexible resource aggregation feasible region in the power distribution network, and the flexibility of the flexible resource cannot be maximized, and the economy and safety of the whole network operation are reduced.

[0047] Additional aspects and advantages of the application will be described in part below, some will become apparent from the following description, or will be understood by those skilled in the art through practice of the application. BRIEF DESCRIPTION OF DRAWINGS

[0048] The above and / or additional aspects and advantages of the application will become apparent and more readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:

[0049] Figure 1 A flow chart of a flexible aggregation method of adjustable resources in a power distribution network according to an embodiment of the application is provided.

[0050] Figure 2 A block schematic diagram of a flexible aggregation device of adjustable resources in a power distribution network according to an embodiment of the application is provided.

[0051] Figure 3 A structural schematic diagram of an electronic device according to an embodiment of the application is provided.

[0052] Explanation of reference signs: determination module-100, construction module-200, constraint module-300, memory-301, processor-302, communication interface-303. DETAILED DESCRIPTION

[0053] The embodiments of the application are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference signs represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are intended to explain the application, and cannot be understood as a limitation of the application.

[0054] A method for flexible aggregation of adjustable resources in a power distribution network, an apparatus, an electronic device, and a storage medium are described below with reference to the accompanying drawings. In view of the problems mentioned in the foregoing background art, the present application provides a method for flexible aggregation of adjustable resources in a power distribution network. In the method, flexible resources at each node in the power distribution network are determined. A feasible region aggregation model of the power distribution network is constructed according to preset safety constraint conditions of the power distribution network and the flexible resources at each node. At least one safety constraint parameter of the feasible region aggregation model is calculated according to a desired target of linear flow constraints, and the feasible region aggregation model is optimized based on the at least one safety constraint parameter, so as to perform linear flow safety constraint on the power distribution network by using the optimized feasible region aggregation model. Thus, the problem that the current market rules do not comprehensively consider the aggregation feasible region of the flexible resources in the power distribution network and cannot maximize the flexibility of the flexible resources is solved, and the economy and safety of the overall network operation are improved.

[0055] Specifically, Figure 1 A flowchart of a method for flexible aggregation of adjustable resources in a power distribution network is provided in the embodiments of the present application.

[0056] As Figure 1 shown, the method for flexible aggregation of adjustable resources in a power distribution network includes the following steps:

[0057] In step S101, the flexible resources at each node in the power distribution network are determined.

[0058] It can be understood that the participation of demand-side flexible resources in grid regulation can ensure the safe and stable operation of the power grid, promote new energy consumption, and reduce user electricity costs. Since the parameters of all demand-side resources considered in grid dispatching are too complex and are not conducive to protecting the privacy of power users, demand-side flexible resources need to be aggregated before participating in grid regulation. Therefore, the flexible resources at each node in the power distribution network need to be determined first in the embodiments of the present application.

[0059] In step S102, a feasible region aggregation model of the power distribution network is constructed according to preset safety constraint conditions of the power distribution network and the flexible resources at each node.

[0060] In the embodiments of the present application, the feasible region aggregation model of the flexible resources in the power distribution network can be calculated by considering the power flow safety constraint of the power distribution network on the premise that the flexible resource aggregation feasible region of each node in the power distribution network is known. It can be ensured that any power curve in the feasible region can be allocated to the feasible region of each flexible resource without error on the premise of meeting the power flow safety constraint. The power curve that is not in the accurate feasible region cannot be allocated to the feasible region of each flexible resource without error on the premise of meeting the power flow safety constraint. The model basis is provided for the decision of the economic dispatching or market clearing of the flexible resources participating in the large power grid, the flexibility of the flexible resources is maximized, and the economy and safety of the overall network operation are improved.

[0061] In an embodiment of the present application, the feasible region aggregation model of the power distribution network is constructed according to preset safety constraints of the power distribution network and flexible resources at each node, comprising: dividing a preset time window into a plurality of time periods according to preset time intervals; constructing an aggregated feasible region of the flexible resource at each node according to boundary parameters of the flexible resource at each node in each time period; and aggregating the aggregated feasible region of the flexible resource at each node according to preset power distribution network safety constraints and preset linear power distribution network flow equations to obtain the feasible region aggregation model of the power distribution network.

[0062] Specifically, the embodiment of the present application can construct the flexible resource feasible region aggregation model considering the power distribution network safety constraints, comprising the following steps:

[0063] 1) Discretize the time, divide the time window considered for optimization into T time periods according to the time interval of ΔT, and the set of all time periods is represented by .

[0064] 2) The accurate aggregated feasible region of the flexible resource at each node in the power distribution network is uniformly represented as:

[0065]

[0066] wherein X A represents the accurate aggregated feasible region of the flexible resource at a single node, P t A represents the total power of the flexible resource at the single node in the time period t, P A is a T-dimensional column vector composed of all P t A (from t = 1 to t = T), the bold letters shown subsequently in the present application are all T-dimensional column vectors composed of corresponding variables, is an arbitrary subset of , and are boundary parameters related to .

[0067] x t is used to generally refer to all variables, then the feasible region in the form of X A can be generalized, that is, the following set is defined:

[0068]

[0069] Let all the feasible regions that can be defined in the above form constitute a set

[0070] 3) Transform the power distribution network safety constraints and the linear power distribution network flow equations, and the feasible region determined by the transmission capacity constraints and the upper and lower voltage constraints in the safety constraints can be uniformly written as:

[0071]

[0072] The feasible region of this form belongs to Because

[0073] The feasible region determined by the fixed load constraint and the bus voltage phase angle constraint in the security constraint can be written as:

[0074]

[0075] The feasible region of this form also belongs to Because

[0076] Each equation of the linear distribution network power flow equation can be uniformly expressed as:

[0077]

[0078] where x n,t is the value of the nth variable in the power flow equation at time period t, m is the number of the equation, a m,n is the coefficient of x n,t in the mth equation, which is independent of t, and the above power flow equation can also be equivalently written as:

[0079]

[0080] 4) Considering a general radial distribution network, the accurate aggregation model of the distribution network flexible resource feasible region is the active power feasible region of the distribution network balance node (i.e. the root node). Let the active power at the root node be the variable After considering the feasible region of the flexible resource in the distribution network and the feasible region determined by the power flow security constraint, the feasible region accurate model of

[0081]

[0082] where the calculation method of the parameters and is given in the subsequent steps 2) and 3) combined with specific power flow equations. X0 represents the feasible region aggregation model, t is the time period subscript, T represents the set of all time periods, T represents the total number of time periods, P0 represents the active power at the root node, is any subset of , and represent the power at the time period set upper and lower bounds of the integral, the superscript n denotes the node power, represents a T-dimensional column vector composed of

[0083] In the exact model, Any non-empty subset of corresponds to a pair of valid upper and lower bound constraints. When T is large, the model is complex. Here, a kind of approximate model is given, named second-order approximate feasible region, which can be expressed as:

[0084]

[0085] It can be seen that the second-order approximate feasible region corresponds to a set composed of all time periods between any two time periods t1 and t2, which is a small part of the subset of The parameters and are also the part of and corresponding to the above subset.

[0086] It should be noted that the embodiments of the present application can also construct an approximate model by selecting other parts of the subset Here, the details are not described again, but as long as the way of constructing an approximate model by selecting a part of the subset is within the scope of the claims of the present application.

[0087] In step S103, at least one security constraint parameter of the feasible region aggregation model is calculated according to the expected target of the linear flow constraint, and the feasible region aggregation model is optimized based on the at least one security constraint parameter, so as to perform linear flow security constraint on the distribution network by using the optimized feasible region aggregation model.

[0088] In an embodiment of the present application, the expected target of the linear flow constraint includes a first linear flow constraint target and a second linear flow constraint target.

[0089] The first linear flow constraint target can be applicable to any linear distribution network flow security constraint, and the second linear flow constraint target can be applicable to the linear flow security constraint described by the flow transfer distribution factor.

[0090] The embodiments of the present application can accurately calculate the security constraint parameter of the flexible resource feasible region aggregation model in the linear distribution network flow constraint, optimize the model, and perform linear flow security constraint on the distribution network by using the optimized linear flow security constraint, so as to maximize the flexibility of the flexible resource while ensuring the flow security and power distribution feasibility of the distribution network, and improve the economy and safety of the whole network operation.

[0091] ​In one embodiment of this application, when the desired objective of the linear power flow constraint is a first linear power flow constraint objective, at least one safety constraint parameter of the feasible region aggregation model is calculated based on the desired objective of the linear power flow constraint, and the feasible region aggregation model is optimized based on the at least one safety constraint parameter, including:

[0092] Transform the feasible domain of all variables in the distribution network into Where n is the variable number, x n,t x is the value of the nth variable in the power flow equation during time period t. n Indicates by x n,t The T-dimensional column vector formed; for the target set non-empty subset Make Satisfy constraints: and trend constraints Where m is the equation number, a m,n It is x n,t The coefficient in the m-th equation;

[0093] Calculate the safety constraint parameters according to the first optimization formula. and The first optimization formula is:

[0094]

[0095]

[0096]

[0097]

[0098]

[0099]

[0100] in, yes The minimum value, yes The maximum value, st represents the constraint condition; according to the safety constraint parameters and Optimize the feasible region aggregation model.

[0101] In the embodiments of this application, for any given Solving the above optimization problem determines and Then after 2(2 T After -1) optimization calculations, all of them can be determined. and This method of calculating the optimal solution by solving an optimization problem and is called the flexibility optimization method. For and the above selection is not arbitrary, but only T(T+1) / 2, similarly using the flexibility optimization method, after T(T+1) optimization calculation can determine all and

[0102] For ease of understanding, the embodiments of the present application are described in detail through a specific linear flow equation and safety constraints, as follows:

[0103]

[0104]

[0105]

[0106]

[0107]

[0108]

[0109]

[0110]

[0111]

[0112]

[0113] V 0,t =1, θ 0,t =0

[0114]

[0115] Wherein, i, j is the number of nodes, 0 represents the root node, representing all nodes, representing the node set excluding the balanced node, representing the node set containing flexible resources, ij represents the branch starting from node i to node j, is the set of all branches, and represent the active and reactive power of branch ij in period t, V i,t represent the voltage of node i, θ i,t represent the phase angle of node i, Gij and B ij denote the real and imaginary parts of the (i, j)th element of the nodal admittance matrix, and denote the real and imaginary parts of the (i, j)th element of the nodal admittance matrix, i is the power factor angle of node i, denote the real and imaginary parts of the (i, j)th element of the nodal admittance matrix, V i and denote the real and imaginary parts of the (i, j)th element of the nodal admittance matrix, and denote the real and imaginary parts of the (i, j)th element of the nodal admittance matrix,

[0116] The first five constraints correspond to The sixth and seventh constraints correspond to The eighth, ninth and tenth constraints correspond to The last constraint corresponds to Therefore, the power flow equation, the security constraint and the resource flexibility constraint in the embodiment of the application fully meet the conditions for using the flexibility optimization method, and the aggregated feasible region of the flexible resource in the distribution network can be calculated by the flexibility optimization method.

[0117] In one embodiment of the application, when the expected target of the linear power flow constraint is a second linear power flow constraint target, at least one security constraint parameter of the feasible region aggregation model is calculated according to the expected target of the linear power flow constraint, and the feasible region aggregation model is optimized based on the at least one security constraint parameter, including:

[0118] The distribution network power flow constraint described by the power flow transfer distribution factor is calculated according to the following formula:

[0119]

[0120]

[0121]

[0122]

[0123] wherein, is the active power increment of branch l at time period t, is the active power increment of node i, is the reference power of branch l, is the reference power of node i, l,i is the power flow transfer distribution factor of branch l with respect to node i, that is, the power of branch l is increased by an increment when the power of node i is increased by 1 unit, is the set of all nodes in the distribution network, is the set of nodes after removing the balance nodes, is a set of nodes containing flexible resource aggregators, is a set of distribution network branches, and are T-dimensional column vectors composed of and respectively, represents the power feasible region at the flexible resource aggregator node;

[0124] The distribution network power flow constraints described by the power flow transfer distribution factor are continuously corrected along the road from the leaf node to the root node according to the transmission capacity of the branch, and the safety constraint parameters are obtained, wherein each correction is compared and summed; the feasible region aggregation model is optimized based on the safety constraint parameters.

[0125] In the embodiments of the present application, it is recorded that The matrix composed of S is in a radial distribution network, assuming that all power imbalances are provided by the balancing node (i.e. the root node), then S is equivalent to the branch-road association matrix of the radial power grid, and the physical meaning of this conclusion is that when the load of a node increases by 1, only the power of the branch on its road increases by 1.

[0126] Let the feasible region of be Let the feasible region of

[0127] The aggregation feasible region of the flexible resource in the distribution network is to find the feasible region of Under the linear power flow constraints of the distribution network described by the power flow transfer distribution factor, the parameters in the accurate feasible region model can be calculated using backtracking elimination method, including the following steps:

[0128] Input: node set branch set power feasible region of each node power feasible region Y of each branch l Δ ;

[0129] Output: feasible region of

[0130] 1、while do

[0131] 2、find a leaf node i, and its branch l and its parent node j

[0132] 3、for do

[0133] 4. assignment

[0134] 5. end for

[0135] 6. remove node i from , remove branch I from

[0136] 7. end while

[0137] 8. return

[0138] The power flow constraint described by the power flow transfer distribution factor in the embodiments of the application is continuously corrected according to the transmission capacity limit of the branch along the road from the leaf node to the root node, and each correction only needs to perform comparison and summation operation, without the need of calculating the optimization problem, so that the calculation complexity is greatly simplified.

[0139] According to the flexible resource flexibility aggregation method of the distribution network proposed in the embodiments of the application, the distribution network flexible resource aggregation feasible region considering the distribution network power flow safety constraint is calculated according to the aggregation feasible region model of the flexible resource at each node, so that the power flexibility of the flexible resource is maximally utilized under the premise of guaranteeing the distribution network power flow safety and power distribution feasibility. Therefore, the problems in the related art that the aggregation feasible region of the flexible resource in the distribution network is not considered comprehensively and the flexibility of the flexible resource cannot be maximally utilized, and the economy and safety of the whole network operation are reduced are solved.

[0140] Secondly, a flexible resource flexibility aggregation device in a distribution network according to the embodiments of the application is described with reference to the accompanying drawings.

[0141] Figure 2 is a block schematic diagram of the flexible resource flexibility aggregation device in a distribution network according to the embodiments of the application.

[0142] As shown in Figure 2 , the flexible resource flexibility aggregation device 10 in a distribution network includes a determination module 100, a construction module 200 and a constraint module 300.

[0143] The determination module 100 is configured to determine the flexible resource at each node in the distribution network, the construction module 200 is configured to construct a feasible region aggregation model of the distribution network according to a preset safety constraint condition of the distribution network and the flexible resource at each node, and the constraint module 300 is configured to calculate at least one safety constraint parameter of the feasible region aggregation model according to a desired target of the linear power flow constraint, and optimize the feasible region aggregation model based on the at least one safety constraint parameter, so as to perform linear power flow safety constraint on the distribution network by using the optimized feasible region aggregation model.

[0144] ​Optionally, in an embodiment of the present application, the constructing module 200 is further configured to divide a preset time window into a plurality of time periods according to a preset time interval, construct an aggregated feasible region of the flexible resource on each node according to a boundary parameter of the flexible resource on each node in each time period, and aggregate the aggregated feasible region of the flexible resource on each node according to a preset network security constraint and a preset linear network flow equation to obtain an aggregated model of the feasible region of the distribution network.

[0145] Optionally, in an embodiment of the present application, an expression formula of the aggregated model of the feasible region is as follows:

[0146]

[0147] wherein X0 represents the aggregated model of the feasible region, t is a time period index, denotes a set of all time periods, T represents a total number of time periods, denotes active power at a root node, is an arbitrary subset of , and respectively represent upper and lower bounds of power integrated on a set of time periods , and a superscript n represents node power, denotes a T-dimensional column vector composed of .

[0148] Optionally, in an embodiment of the present application, the expected target of the linear flow constraint includes a first linear flow constraint target and a second linear flow constraint target.

[0149] Optionally, in an embodiment of the present application, when the expected target of the linear flow constraint is the first linear flow constraint target, the constraining module 300 is further configured to convert the feasible region of all variables in the network into wherein x n,t is a value of the nth variable in the flow equation in the time period t, x n denotes a T-dimensional column vector composed of x n,t ;

[0150] for a non-empty subset of the target set , so that satisfy the constraints: and the flow constraint wherein m is a number of equations, a m,n is a coefficient of x n,t in the mth equation;

[0151] the safety constraint parameters and The first optimization formula is: in, yes The minimum value, yes The maximum value of , where st represents the constraint condition;

[0152] According to safety constraint parameters and Optimize the feasible region aggregation model.

[0153] Optionally, in one embodiment of this application, when the desired objective of the linear power flow constraint is the second linear power flow constraint objective, the constraint module 300 is further configured to calculate the distribution network power flow constraint described by the power flow transfer distribution factor according to the following formula:

[0154]

[0155]

[0156]

[0157]

[0158]

[0159] in, It is the active power increment of branch l in time period t. It is the active power increment of node i. It is the reference power of branch l. s is the reference power of node i. l,i It is the power flow transfer distribution factor of branch l with respect to node i, meaning the increase in power of branch l caused by a one-unit increase in the power of node i. It is the set of all nodes in the distribution network. It is the set of nodes after removing the balancing nodes. It is a collection of nodes that include flexible resource aggregators. It is a collection of distribution network branches. and They are respectively by and The T-dimensional column vector formed This represents the power feasible region at the flexible resource aggregator node.

[0160] Based on the power flow distribution factor, the power flow constraints of the distribution network are continuously modified from the leaf node along the road according to the transmission capacity of the branch until the root node, so as to obtain the safety constraint parameters. Each modification involves comparison and summation operations. The feasible region aggregation model is optimized based on the safety constraint parameters.

[0161] It should be noted that the foregoing explanation of the embodiment of the flexible aggregation method of adjustable resources in a power distribution network also applies to the flexible aggregation device of adjustable resources in a power distribution network of the embodiment, which will not be described here again.

[0162] The flexible aggregation device of adjustable resources in a power distribution network provided by the embodiment of the present application can calculate the flexible resource aggregation feasible region of the power distribution network considering the power flow safety constraint of the power distribution network according to the aggregation feasible region model of the flexible resources at each node, and can maximize the power flexibility of the flexible resources on the premise of ensuring the power flow safety and power distribution feasibility of the power distribution network. Thus, the related art problem that the aggregation feasible region of the flexible resources in the power distribution network is not considered comprehensively and the flexibility of the flexible resources cannot be maximized, and the problems of reducing the economy and safety of the whole network operation are solved.

[0163] Figure 3 The structure schematic diagram of the electronic device provided by the embodiment of the present application is shown. The electronic device can include:

[0164] The memory 301, the processor 302, and the computer program stored in the memory 301 and executable on the processor 302.

[0165] The processor 302 implements the flexible aggregation method of adjustable resources in a power distribution network provided in the above embodiments when executing the program.

[0166] Further, the electronic device further includes:

[0167] The communication interface 303 is used for communication between the memory 301 and the processor 302.

[0168] The memory 301 is used to store the computer program executable on the processor 302.

[0169] The memory 301 can include a high-speed RAM (Random Access Memory, Random Access Memory) memory, and can also include a non-volatile memory, such as at least one disk memory.

[0170] If the memory 301, the processor 302 and the communication interface 303 are implemented independently, the communication interface 303, the memory 301 and the processor 302 can be connected with each other through a bus and complete communication between each other. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, Figure 3 Only one thick line is used in the figure to represent the bus, but it does not mean that there is only one bus or only one type of bus.

[0171] Optionally, in a specific implementation, if the memory 301, the processor 302 and the communication interface 303 are integrated on a chip, the memory 301, the processor 302 and the communication interface 303 can complete communication between each other through an internal interface.

[0172] The processor 302 can be a CPU (Central Processing Unit), or an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present application.

[0173] The embodiments of the present application also provide a computer readable storage medium, which stores a computer program, and the program is executed by a processor to implement the power distribution network flexible aggregation method of adjustable resources as described above.

[0174] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example" or "some examples" means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms is not necessarily for the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, the skilled in the art can combine and combine the different embodiments or examples described in the present specification and the features of the different embodiments or examples without contradiction.

[0175] Moreover, the terms "first", "second", etc. are used herein only to describe different steps or features and do not imply a relative importance or a specific order of steps or features. Thus, features defined with "first", "second" etc. can include at least one of the features implicitly or explicitly. In the description of the application, the meaning of "N" is at least two, such as two, three, etc., unless otherwise expressly specified.

[0176] Any process or method descriptions or blocks in flow charts described herein and elsewhere can be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps in the process. Alternate implementations are included within the scope of the preferred embodiments of the present application in which the functions performed by the various processes described herein and elsewhere are allocated differently among more than one processing element, not only for purposes of speed but also for purposes of achieving parallelism in the uses of the various processing elements.

[0177] It should be understood that aspects of the application can be implemented in hardware, software, firmware or combinations thereof. In the above embodiments, the steps or methods can be implemented in software or firmware which is stored in memory and executed by a suitable instruction execution system. As with a purely hardware as in another embodiment, any of the following technologies can be used to implement the hardware or firmware, or their combinations: discrete logic circuitry having logic gates for implementing logic functions upon data signals, application specific integrated circuits having appropriate combinational logic gates, programmable gate arrays, field programmable gate arrays, and the like.

[0178] Those of skill in the art would understand that information and signals can be represented using any of a variety of technologies and techniques. Further, those of skill in the art could appreciate that the preferred embodiments of the present application can produce information and signals using any of a variety of technologies and techniques.

Claims

1. A method for flexibility aggregation of adjustable resources in a power distribution network, characterized in that, The method comprises the following steps: determining flexible resources on each node in a power distribution network; constructing a feasible region aggregation model of the power distribution network according to preset safety constraint conditions of the power distribution network and the flexible resources on the each node; calculating at least one safety constraint parameter of the feasible region aggregation model according to an expected target of linear flow constraint, and optimizing the feasible region aggregation model based on the at least one safety constraint parameter, so as to perform linear flow safety constraint on the power distribution network by using the optimized feasible region aggregation model; the step of constructing the feasible region aggregation model of the power distribution network according to the preset safety constraint conditions of the power distribution network and the flexible resources on the each node comprises: dividing a preset time window into a plurality of time periods according to a preset time interval; constructing an aggregated feasible region of the flexible resources on each node according to boundary parameters of the flexible resources on each node in each time period; and aggregating the aggregated feasible region of the flexible resources on each node according to preset power distribution network safety constraints and a preset linear power distribution network flow equation, to obtain the feasible region aggregation model of the power distribution network; wherein the preset power distribution network safety constraints comprise at least one of transmission capacity constraints, upper and lower voltage constraints, fixed load constraints and balance node voltage phase angle constraints; and an expression formula of the preset linear power distribution network flow equation is: wherein, is the value of the n th variable in the tidal flow equation at time period t , m is the number of the equation, is the coefficient in the m th equation; the expected target of the linear flow constraint comprises a first linear flow constraint target and a second linear flow constraint target; when the expected target of the linear flow constraint is the second linear flow constraint target, the step of calculating at least one safety constraint parameter of the feasible region aggregation model according to the expected target of linear flow constraint, and optimizing the feasible region aggregation model based on the at least one safety constraint parameter, comprises: calculating a power distribution network flow constraint described by a flow transfer distribution factor according to the following formula: wherein, is the branch l active power increment, t is the active power increment of node is the active power increment of node i is the reference power of branch is the reference power of node l is the reference power of node is the reference power of branch i is the reference power of branch is the reference power of branch l is the power flow shift distribution factor of node i with respect to branch i is the power increment of branch l when the power of node increases by 1 unit, is the set of all nodes in the distribution network, is the set of nodes excluding the slack node, is the set of branches in the distribution network, and are T-dimensional column vectors composed of and respectively, denotes the power feasible region at the flexible resource aggregator node; modifying the feasible region according to the power distribution network flow constraint described by the flow transfer distribution factor from a leaf node along a road until a root node, to obtain a safety constraint parameter, wherein each modification is accompanied by comparison and summation operations; optimizing the feasible region aggregation model based on the safety constraint parameter.

2. The method of claim 1, wherein, an expression formula of the feasible region aggregation model is: wherein, denotes the feasible region aggregation model, t is a time period index, denotes the set of all time periods, T denotes the total number of time periods, denotes the active power at the root node, is an arbitrary subset of and denote the power upper and lower bounds of the integral over the set of time periods with the upper index n denoting the node power, denotes the dimensional column vector consisting of T the active power at the root node.

3. The method of claim 1, wherein, when the expected target of the linear flow constraint is the first linear flow constraint target, the step of calculating at least one safety constraint parameter of the feasible region aggregation model according to the expected target of linear flow constraint, and optimizing the feasible region aggregation model based on the at least one safety constraint parameter, comprises: The feasible region of all variables in network configuration is converted into where, n is the number of variables, is the value of the n th variable in the power flow equation at the time period t , represents an -dimensional column vector composed of T ​ For a non-empty subset of the target set such that , , satisfies the constraints: and the power flow constraints where m is the number of equations, is the coefficient in the m th equation; calculating the security constraint parameter according to a first optimization formula and , the first optimization formula is: , wherein, is the minimum value of , is the maximum value of , represents a constraint condition; According to the security constraint parameters and optimizing the feasible region aggregation model.

4. A flexible aggregation device of adjustable resources in a power distribution network, characterized in that, comprising: a determination module configured to determine flexible resources on each node in a power distribution network; a construction module configured to construct a feasible region aggregation model of the power distribution network according to preset safety constraint conditions of the power distribution network and the flexible resources on the each node; a constraint module configured to calculate at least one safety constraint parameter of the feasible region aggregation model according to an expected target of linear flow constraint, and optimize the feasible region aggregation model based on the at least one safety constraint parameter, so as to perform linear flow safety constraint on the power distribution network by using the optimized feasible region aggregation model; The construction module is further used for: dividing a preset time window into a plurality of time periods according to a preset time interval, constructing an aggregated feasible region of flexible resources on each node according to boundary parameters of the flexible resources on the each node in each time period; and aggregating the aggregated feasible region of the flexible resources on the each node according to a preset network security constraint and a preset linear network flow equation to obtain an aggregated model of a feasible region of the distribution network. The expected target of the linear flow constraint includes a first linear flow constraint target and a second linear flow constraint target, and when the expected target of the linear flow constraint is the second linear flow constraint target, the constraint module is further used for: The distribution factor of the flow transfer is calculated according to the following formula: wherein, is the branch l active power increment, t is the active power increment of node is the active power increment of node i is the reference power of branch is the reference power of node l is the reference power of node is the reference power of branch i is the reference power of branch is the reference power of branch l is the power flow transfer distribution factor of node i with respect to branch i , which means that a power increase of 1 unit at node l results in an increment of power of branch is the set of all nodes in the distribution network, is the set of nodes after removing the slack node, is the set of nodes containing the flexible resource aggregators, is the set of branches in the distribution network, and are T-dimensional column vectors composed of and , respectively, denotes the power feasible region at the flexible resource aggregator nodes; The distribution factor of the flow transfer is used to continuously correct the feasible region according to the transmission capacity of the branch from the leaf node to the root node, and the security constraint parameter is obtained, wherein, each correction is performed by comparison and summation operation; The aggregated model of the feasible region is optimized based on the security constraint parameter.

5. An electronic device, comprising: The computer program is stored in the memory and executable on the processor, and the processor executes the program to implement the flexible aggregation method of adjustable resources in the distribution network according to any one of claims 1-3. The program is executed by the processor to implement the flexible aggregation method of adjustable resources in the distribution network according to any one of claims 1-3.

6. A computer-readable storage medium having stored thereon a computer program, characterized in that, ​

Images