Energy storage site selection method and system for improving absorption capability of active power distribution network

Abstract

The invention discloses an energy storage site selection method and system based on improvement of the absorption capability of an active power distribution network, and relates to the technical field of active power distribution network planning. Comprising the steps of determining a key branch based on a consumption capability curve; determining a preliminary site selection position of the access point based on the key branch; solving a consumption capability curve and an index thereof after each preliminary site selection position is accessed to the stored energy; and comparing the absorption capacity curves and indexes of different preliminary site selection positions, and determining an optimal energy storage access position. According to the invention, through defining the key branch and optimizing the energy storage access position, the overall consumption capability of the active power distribution network is effectively improved. The method not only considers the maximum absorption capacity, but also introduces the concept of an absorption capacity curve, and comprehensively quantifies the absorption capacity range of the active power distribution network under the participation of energy storage under various load / DG distribution conditions. By comparing the absorption capacity curves and the indexes of the absorption capacity curves after energy storage is accessed to different positions, the method can determine the optimal energy storage access position with the best absorption capacity improvement effect.

Description

Technical Field

[0001] The present invention relates to the technical field of active power distribution network planning, and in particular to an energy storage site selection method and system for improving the absorption capacity of an active power distribution network. Background Art

[0002] Energy storage is an important flexible component of smart distribution networks. Reasonable access to energy storage can realize the consumption of new energy represented by distributed generation (DG)[1,2], load peak shifting[3] and optimized operation of distribution networks[4]. Therefore, it is of great significance and value to study the site selection planning of energy storage access to active distribution networks.

[0003] In the planning research of energy storage access to distribution networks for improving absorption capacity, reasonable access to energy storage can effectively improve the system's maximum absorption capacity for DG. However, the complete absorption capacity of the active distribution network under various load / DG distributions is not a single indicator of maximum absorption capacity, but an absorption capacity curve, and the maximum absorption capacity only constitutes a small part of the curve. However, the research on the absorption capacity curve of the active distribution network taking into account energy storage has not been reported, and it is not possible to quantify the complete absorption capacity range of the active distribution network under various load / DG distributions with the participation of energy storage. On the other hand, there is no research on the site selection planning of energy storage access to active distribution networks based on the absorption capacity curve, and it is not possible to effectively determine the location of energy storage access to the distribution network based on the absorption capacity curve to improve the absorption capacity of the system.

[0004] In terms of planning research on energy storage access to distribution networks for improving absorption capacity, existing research has not reported on site selection planning for energy storage access to active distribution networks based on absorption capacity curves, and it is still not possible to effectively determine the optimal location of energy storage access to distribution networks based on absorption capacity curves to fully improve the absorption capacity of the system. At the same time, the absorption capacity curve of active distribution networks with energy storage has not been studied, and it is impossible to effectively quantify the absorption capacity range of active distribution networks with energy storage participation under various load / DG distributions.

[0005] In view of the above problems, the present invention proposes a method for selecting an energy storage site to improve the absorption capacity of an active distribution network. The method can effectively determine the site selection for energy storage access to the active distribution network, solve the absorption capacity curve of the active distribution network containing energy storage, quantify the absorption capacity range of the active distribution network with the participation of energy storage, and completely improve the absorption capacity of the active distribution network. Summary of the invention

[0006] In view of the problems existing in the prior art, the present invention is proposed.

[0007] Therefore, the problem to be solved by the present invention is how to effectively determine the optimal location for energy storage to be connected to the active distribution network based on the absorption capacity curve to fully improve the absorption capacity of the system, and how to quantify the complete absorption capacity range of the active distribution network under various load / DG distributions with the participation of energy storage, rather than just the single indicator of maximum absorption capacity.

[0008] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0009] In a first aspect, an embodiment of the present invention provides a method for selecting an energy storage site for improving the absorption capacity of an active distribution network, which includes determining a key branch based on an absorption capacity curve;

[0010] Determine the preliminary site location of the access point based on the key branches;

[0011] Solve the absorption capacity curve and its index of each preliminary site after connecting to energy storage;

[0012] Compare the absorption capacity curves and indicators of different preliminary site selection locations to determine the optimal energy storage access location.

[0013] 3. As a preferred solution of the energy storage site selection method for improving the absorption capacity of the active distribution network of the present invention, the step of determining the key branch is specifically to calculate the absorption capacity curve expression of the active distribution network:

[0014]

[0015] Among them, L TAC is the absorption capacity curve, Val(W DGB,i ) is the absorption capacity of the operating point, i is the sorting number of the sampling point;

[0016] Where st(1) represents the operating point absorption capacity Val(W DB,i ) is equal to the sum of the apparent powers of all DG nodes, that is, the sum of the DG outputs;

[0017] Where st(2) represents the operating point W B,i On the DG boundary, W B,i is the DG boundary point, and the apparent power vector W of the load node LB,i and the DG node apparent power vector W DGB,i Composition, W LB,i S LB,h is the outflow power of the hth load node, W DGB,i S DGB,n Inject power into the nth DG node, For all DG boundaries, is the jth DG boundary;

[0018] Among them, st(3) is the DG growth criticality constraint, which means that the reverse power flow equality constraint covers all DG variables, so that all DG variables are subject to equality constraints, and any DG output growth will cause the reverse power flow to exceed the limit;

[0019] The criticality of DG growth is determined by the sum of the DG variable coefficients constrained by the reverse power flow equation being greater than 0 (i.e., a 1k +a 2k +...+a lk >0,k=1,2,...,n)guarantee;

[0020] The left constraint in st(3) is the reverse flow constraint, and the right constraint is the forward flow constraint. In the formula, l is the number of equality constraints, m is the number of equality and inequality constraints, and a is the number of ln Indicates whether the nth element is in the lth constraint, if yes, it takes 1, if no, it takes 0, r is the network loss coefficient, indicating that the network loss is taken into account, cl is the capacity of the lth element (branch), the equality constraint indicates that the reverse flow of the element reaches the upper capacity limit, and the inequality constraint indicates that the flow of the element does not exceed the upper capacity limit;

[0021] The critical branch is the branch in the active distribution network where the reverse flow reaches the component capacity first;

[0022] Calculate the absorption capacity curve expression of the active distribution network and find the reverse power flow equation constraint covering all DG variables in the absorption capacity curve expression:

[0023] -c l =(1+r)(a l1 S DGB,1 +...+a ln S DGB,n +a l(n+1) S LB,1 +...+a l(n+h) S LB,h )

[0024] If the reverse flow of the branch (branch l) corresponding to the reverse flow equation constraint reaches its capacity first, then the branch (branch l) is the critical branch.

[0025] As a preferred solution of the energy storage site selection method for improving the absorption capacity of the active distribution network of the present invention, the preliminary site selection position of the access point is determined based on the key branch as follows:

[0026] The active distribution network nodes are divided into the key branch downstream nodes NX = {Nk+1, ..., Nq} and the upstream branch NS = {N1, ..., Nk};

[0027] Among them, k is the location of the key branch, q is the total number of nodes, and the downstream node of the key branch NX = {Nk+1,…,Nq} is selected as the preliminary site selection location.

[0028] As a preferred solution of the energy storage site selection method for improving the absorption capacity of the active distribution network of the present invention, the steps of solving the absorption capacity curve and its index after the energy storage is connected to each preliminary site selection location are as follows:

[0029] Calculate the absorption capacity curve expression of the active distribution network with energy storage;

[0030] Uniform sampling generates operating points;

[0031] Screening DG boundary points that meet the DG growth criticality constraints;

[0032] Calculate and sort the sum of DG outputs at DG boundary points and draw the absorption capacity curve;

[0033] Calculate the absorption capacity curve index.

[0034] As a preferred solution of the energy storage site selection method for improving the absorption capacity of the active distribution network of the present invention, the uniform sampling and generation of the operating point is specifically:

[0035] With step size b in the load node power range DG node power range And energy storage power range Uniform sampling is performed to generate X operating points W i ;

[0036] The specific indicators for calculating the absorption capacity curve are:

[0037] The maximum absorption capacity TAC is the absorption capacity value at the highest point of the absorption capacity curve of the active distribution network including energy storage;

[0038] Average absorption capacity is the average absorptive capacity of all DG boundary points constituting the absorptive capacity curve;

[0039] Minimum absorption capacity TAC min It is the absorption capacity value at the lowest point of the absorption capacity curve.

[0040] As a preferred solution of the energy storage site selection method for improving the absorption capacity of the active distribution network of the present invention,

[0041] Chinese: The mathematical model of the absorption capacity curve of the active distribution network with energy storage is:

[0042]

[0043] Among them, S ESSB,kis the power of the energy storage connected to node k, β is a 0-1 variable, S ESS,d is the energy storage discharge power, S ESS,c The charging power for energy storage, and are the maximum charging and discharging powers constrained by PCS, C ESS,N is the energy capacity of energy storage, and are the maximum and minimum values ​​of energy storage SOC, Δt is the charge and discharge time, η ESS,c and η ESS,d are the charging and discharging efficiency of energy storage, ESS is the grid-connected power factor of the energy storage.

[0044] As a preferred solution of the energy storage site selection method for improving the absorption capacity of the active distribution network of the present invention, the absorption capacity curves and indicators of different preliminary site selection locations are compared to determine the optimal energy storage access location:

[0045] Draw the absorption capacity curves of the active distribution network after connecting to energy storage at different locations in the same graph;

[0046] The absorption capacity curve indicators of the active distribution network after connecting to energy storage at different locations are listed in the same table;

[0047] By comparing the height of the absorption capacity curve and the size of the index after connecting to energy storage at different locations;

[0048] The energy storage access location with the highest absorption capacity curve position and the largest curve index is preferably determined as the optimal location for energy storage access to the distribution network with the best absorption capacity improvement effect.

[0049] In a second aspect, an embodiment of the present invention provides an energy storage site selection system for improving the absorption capacity of an active distribution network, which includes a key branch determination module, a preliminary site selection module, and an optimal location determination module;

[0050] The key branch determination module is used to collect the topological structure of the active distribution network, the power range data of the load nodes and the DG nodes, calculate the absorption capacity curve expression of the active distribution network, and determine the key branches;

[0051] The preliminary site selection module is used to divide the active distribution network nodes into downstream nodes and upstream nodes based on key branches, and determine the preliminary site selection location for energy storage access;

[0052] The optimal location determination module is used to solve the absorption capacity curve and its indicators after each preliminary site selection location is connected to energy storage, compare the absorption capacity curves and their indicators of different preliminary site selection locations, determine the optimal energy storage access location, and regularly update and optimize the energy storage access plan.

[0053] In a third aspect, an embodiment of the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, the steps of the energy storage site selection method for improving the absorption capacity of the active distribution network as in the first aspect of the present invention are implemented.

[0054] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, the steps of the energy storage site selection method for improving the absorption capacity of an active distribution network as in the first aspect of the present invention are implemented.

[0055] The beneficial effects of the present invention are as follows: by defining key branches and optimizing energy storage access locations, the overall absorption capacity of the active distribution network is effectively improved. This method not only takes into account the maximum absorption capacity, but also introduces the concept of absorption capacity curve, and comprehensively quantifies the absorption capacity range of the active distribution network under various load / DG distribution conditions with the participation of energy storage. By comparing the absorption capacity curves and their indicators after energy storage is connected at different locations, this method can determine the optimal energy storage access location with the best absorption capacity improvement effect. This method overcomes the limitation of traditional methods that only focus on a single maximum absorption capacity indicator, and provides more comprehensive and effective guidance for the planning and operation of active distribution networks, which helps to improve the distribution network's ability to accept distributed power sources and promote the efficient use of renewable energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0057] Figure 1 Flowchart of energy storage site selection method for improving the absorption capacity of active distribution network;

[0058] Figure 2 Schematic diagram of an active distribution network example of energy storage site selection method to improve the absorption capacity of active distribution network;

[0059] Figure 3 The energy storage site selection method for improving the absorption capacity of active distribution network is the key branch B 2 Downstream Node N 2 An example of active distribution network connected to energy storage;

[0060] Figure 4 Key branch B of the energy storage site selection method for improving the absorption capacity of active distribution networks 2 Downstream Node N 3 An example of active distribution network connected to energy storage;

[0061] Figure 5 Key branch B of the energy storage site selection method for improving the absorption capacity of active distribution networks 2 Downstream Node N 4 An example of active distribution network connected to energy storage;

[0062] Figure 6 Key branch B of the energy storage site selection method for improving the absorption capacity of active distribution networks 2 Downstream Node N 1 An example of active distribution network connected to energy storage;

[0063] Figure 7 Schematic diagram of the absorption capacity curve of the active distribution network with energy storage, which is a method for selecting energy storage sites to improve the absorption capacity of the active distribution network. DETAILED DESCRIPTION

[0064] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0065] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0066] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0067] Example 1

[0068] Reference Figure 1 , which is the first embodiment of the present invention, and provides a method for selecting an energy storage site for improving the absorption capacity of an active distribution network, comprising:

[0069] S1: Determine the key branches based on the absorption capacity curve;

[0070] The absorption capacity curve expression of a given active distribution network is calculated. According to the reverse power flow equation constraint in the absorption capacity curve expression that can cover all DG variables, the branch where the reverse power flow reaches the component capacity first is determined as the key branch.

[0071] The absorption capacity curve of the active distribution network is a curve composed of all DG boundary points that meet the safety constraints, sorted from small to large according to the sum of DG output. The sorted sequence number is the horizontal coordinate of the curve, and the sum of DG output is the vertical coordinate of the curve. The DG boundary point is the operating point with DG growth criticality, and all DG boundary points constitute the DG boundary. DG growth criticality refers to a certain safe operating point. Any increase in DG output will cause the reverse flow to exceed the limit, causing insecurity.

[0072] Furthermore, the step of determining the key branch is to calculate the absorption capacity curve expression of the active distribution network:

[0073]

[0074] Among them, L TAC is the absorption capacity curve, Val(W DGB,i ) is the absorption capacity of the operating point, i is the sorting number of the sampling point;

[0075] Where st(1) represents the operating point absorption capacity Val(W DB,i ) is equal to the sum of the apparent powers of all DG nodes, that is, the sum of the DG outputs;

[0076] Where st(2) represents the operating point W B,i On the DG boundary, W B,i is the DG boundary point, and the apparent power vector W of the load node LB,i and the DG node apparent power vector W DGB,i Composition, W LB,i S LB,h is the outflow power of the hth load node, W DGB,i S DGB,n Inject power into the nth DG node, For all DG boundaries, is the jth DG boundary;

[0077] Among them, st(3) is the DG growth criticality constraint, which means that the reverse power flow equality constraint covers all DG variables, so that all DG variables are subject to equality constraints, and any DG output growth will cause the reverse power flow to exceed the limit;

[0078] The criticality of DG growth is determined by the sum of the DG variable coefficients constrained by the reverse power flow equation being greater than 0 (i.e., a 1k +a 2k +...+a lk >0,k=1,2,...,n)guarantee;

[0079] The left constraint in st(3) is the reverse flow constraint, and the right constraint is the forward flow constraint. In the formula, l is the number of equality constraints, m is the number of equality and inequality constraints, and a is the number of ln Indicates whether the nth element is in the lth constraint, if yes, it takes 1, if no, it takes 0, r is the network loss coefficient, indicating that the network loss is taken into account, cl is the capacity of the lth element (branch), the equality constraint indicates that the reverse flow of the element reaches the upper capacity limit, and the inequality constraint indicates that the flow of the element does not exceed the upper capacity limit;

[0080] The critical branch is the branch in the active distribution network where the reverse flow reaches the component capacity first;

[0081] Calculate the absorption capacity curve expression of the active distribution network and find the reverse power flow equation constraint covering all DG variables in the absorption capacity curve expression:

[0082] -c l =(1+r)(a l1 S DGB,1 +...+a ln S DGB,n +a l(n+1) S LB,1 +...+a l(n+h) S LB,h )

[0083] If the reverse flow of the branch (branch l) corresponding to the reverse flow equation constraint reaches its capacity first, then the branch (branch l) is the critical branch.

[0084] S2: Determine the preliminary site location of the access point based on the key branches;

[0085] According to the position of the critical branch in the active distribution network, the nodes of the active distribution network are divided into critical branch downstream nodes and critical branch upstream nodes. The critical branch downstream nodes and critical branch upstream nodes refer to the nodes located downstream and upstream of the critical branch, respectively. Downstream refers to the direction from the substation transformer to the feeder terminal, and upstream refers to the direction from the feeder terminal to the substation transformer.

[0086] Furthermore, the preliminary site selection location of the access point based on the key branch is specifically:

[0087] The active distribution network nodes are divided into the key branch downstream nodes NX = {Nk+1, ..., Nq} and the upstream branch NS = {N1, ..., Nk};

[0088] Among them, k is the location of the key branch, q is the total number of nodes, and the downstream node of the key branch NX = {Nk+1,…,Nq} is selected as the preliminary site selection location.

[0089] S3: Solve the absorption capacity curve and its index of each preliminary site after connecting to energy storage;

[0090] Furthermore, the steps to solve the absorption capacity curve and its index after the energy storage is connected to each preliminary site selection are as follows:

[0091] Calculate the absorption capacity curve expression of the active distribution network with energy storage;

[0092] Uniform sampling generates operating points;

[0093] Screening DG boundary points that meet the DG growth criticality constraint, and screening DG boundary points that meet the DG growth criticality constraint from the uniformly sampled operating points according to st(3) in the expression of the absorption capacity curve of the active distribution network with energy storage;

[0094] Calculate and sort the sum of the DG outputs at the DG boundary points, draw the absorption capacity curve, and calculate the sum of the DG outputs Val (W) at the DG boundary points according to st (1) in the absorption capacity curve expression of the active distribution network with energy storage. DGB,i ), sort them from small to large and draw the absorption capacity curve;

[0095] Calculate the absorption capacity curve index.

[0096] Furthermore, the uniform sampling generates the operating points as follows:

[0097] With step size b in the load node power range DG node power range And energy storage power range Uniform sampling is performed to generate X operating points W i ;

[0098] The specific indicators for calculating the absorption capacity curve are:

[0099] The maximum absorption capacity TAC is the absorption capacity value at the highest point of the absorption capacity curve of the active distribution network including energy storage;

[0100] Average absorption capacity is the average absorptive capacity of all DG boundary points constituting the absorptive capacity curve;

[0101] Minimum absorption capacity TAC min It is the absorption capacity value at the lowest point of the absorption capacity curve.

[0102] It should be noted that the absorption capacity curve is composed of the DG boundary points where the DG output growth reaches the reverse flow constraint. In order to balance the DG output and prevent the reverse flow in the distribution network from exceeding the limit, the energy storage should be operated in the charging state rather than the discharging state. Therefore, the sampling range of the energy storage is

[0103]

[0104] in, and L i , DG i and energy storage ESS i The power limit of

[0105] S4: Compare the absorption capacity curves and indicators of different preliminary site selection locations to determine the optimal energy storage access location;

[0106] After determining the preliminary site selection for energy storage access to the distribution network, it is necessary to solve the absorption capacity curve and indicators of the active distribution network containing energy storage, compare the effect of energy storage access at different locations on the absorption capacity improvement, and thus select the optimal location for energy storage access to the distribution network with the best absorption capacity improvement effect.

[0107] Furthermore, the mathematical model of the absorption capacity curve of the active distribution network with energy storage is:

[0108]

[0109] Among them, S ESSB,k is the power of the energy storage connected to node k, β is a 0-1 variable, S ESS,d is the energy storage discharge power, S ESS,c The charging power for energy storage, and are the maximum charging and discharging powers constrained by PCS, C ESS,N is the energy capacity of energy storage, and are the maximum and minimum values ​​of energy storage SOC, Δt is the charge and discharge time, η ESS,c and η ESS,d are the charging and discharging efficiency of energy storage, ESS is the grid-connected power factor of the energy storage.

[0110] Where st(4) is the energy storage power constraint, sub-equation 1

[0111] (S ESSB,k =βS ESS,d +(1-β)S ESS,c β=0or1)

[0112] The minimum of the beam power and the SOC constraint power is used. The two quantities on the right side of Sub-Equation 2 are both non-positive numbers, and max is the quantity with the smallest absolute value between the two.

[0114] Furthermore, this embodiment also provides an energy storage site selection system for improving the absorption capacity of an active distribution network, including a key branch determination module, a preliminary site selection module and an optimal location determination module;

[0115] The key branch determination module is used to collect the topological structure of the active distribution network, the power range data of the load nodes and the DG nodes, calculate the absorption capacity curve expression of the active distribution network, and determine the key branches;

[0116] The preliminary site selection module is used to divide the active distribution network nodes into downstream nodes and upstream nodes based on key branches, and determine the preliminary site selection location for energy storage access;

[0117] The optimal location determination module is used to solve the absorption capacity curve and its indicators after each preliminary site selection location is connected to energy storage, compare the absorption capacity curves and their indicators of different preliminary site selection locations, determine the optimal energy storage access location, and regularly update and optimize the energy storage access plan.

[0118] This embodiment also provides a computer device, which is suitable for the case of a method for selecting a site for energy storage that improves the absorption capacity of an active distribution network, and includes a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the method for selecting a site for energy storage that improves the absorption capacity of an active distribution network as proposed in the above embodiment.

[0119] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0120] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the energy storage site selection method for improving the absorption capacity of the active distribution network as proposed in the above embodiment is implemented.

[0121] In summary, by defining key branches and optimizing energy storage access locations, the overall absorption capacity of the active distribution network is effectively improved. This method not only takes into account the maximum absorption capacity, but also introduces the concept of absorption capacity curve, and comprehensively quantifies the absorption capacity range of the active distribution network under various load / DG distribution conditions with the participation of energy storage. By comparing the absorption capacity curves and their indicators after energy storage is connected at different locations, this method can determine the optimal energy storage access location with the best absorption capacity improvement effect. This method overcomes the limitation of traditional methods that only focus on a single maximum absorption capacity indicator, and provides more comprehensive and effective guidance for the planning and operation of active distribution networks, which helps to improve the distribution network's acceptance capacity for distributed power sources and promote the efficient use of renewable energy.

[0122] Example 2

[0123] Reference Figure 2-Figure 7 , which is the second embodiment of the present invention, and this embodiment provides a method for selecting an energy storage site to improve the absorption capacity of an active distribution network. In order to verify the beneficial effects of the present invention, a scientific demonstration is carried out through a specific example.

[0124] Basic situation of the calculation example: the feeder capacity is 1.00MVA, the power ranges of a single load node and a single DG node are [0, 1.00]MVA and [-1.50, 0]MVA respectively, and the network loss coefficient r is 5%. The energy capacity of the energy storage to be connected is 4.00MWh, the PCS power range of the energy storage is [-1.00, 1.00]MVA, and the charge state of the energy storage is Q soc The range is [20%, 100%], the charging and discharging time Δt of the energy storage is 1.00 hour, the grid-connected power factor of the energy storage is 0.90, and the charging and discharging efficiency of the energy storage is 0.95.

[0125] Based on the absorption capacity curve of the active distribution network, the key branches are determined. Figure 2 The active distribution network can calculate its absorption capacity curve expression according to formula (1), as shown in formula (4):

[0126]

[0127] From formula (4), we can see that Figure 2 The distribution network has only one DG boundary There is only one reverse power flow equation constraint in equation (4) (-1 = (1 + r) (S DGB,1 +S DGB,2 +S LB,2 )) covers all DG variables, and the equality constraints correspond to Figure 2 The reverse flow of the middle branch B2 reaches its capacity of 1.00MVA first. Therefore, branch B2 is the key branch, and the other branches (B1, B3 and B4) are not key branches.

[0128] Determine the preliminary site selection for energy storage access to the distribution network based on key branches:

[0129] For a given Figure 2 Active distribution network, according to the location of key branch B2, Figure 2 The four nodes in the active distribution network are divided as follows:

[0130] The upstream node of the key branch B2 is N s = {N 1}, the downstream node of the key branch B2 is N X = {N 2 ,N 3 ,N 4};

[0131] In order to effectively improve the active distribution network's ability to absorb DG, the initial site selection for energy storage access to the active distribution network is determined as the downstream node N of the key branch. X = {N 2 ,N 3 ,N 4}, rather than the key branch upstream node N s = {N 1};

[0132] The energy storage to be connected can be connected from the downstream node N of the key branch. X = {N 2 ,N 3 ,N 4} Select node N2 or node N3 or node N4 for access. After access, the absorption capacity of the active distribution network can be fully improved, but the improvement effect is not exactly the same. The present invention connects the energy storage to be connected to the key branch downstream node N2, node N3 and node N4 in the preliminary site selection location respectively, so as to select the energy storage access location with the best absorption capacity improvement effect. The active distribution network after energy storage access is shown in FIG. Figure 3 , Figure 4 and Figure 5 shown.

[0133] In order to verify the effectiveness and advantages of the energy storage site selection method for improving the absorption capacity of the active distribution network proposed in the present invention, as well as the effect of improving the complete absorption capacity, a method is designed to connect the energy storage to be connected to the upstream node N of the key branch. s = {N 1} scenes, such as Figure 6 shown.

[0134] The uniform sampling algorithm is used to solve the absorption capacity curve and its index of the active distribution network after the energy storage is connected to each location, and the optimal location of the energy storage connected to the distribution network with the best absorption capacity improvement effect is determined:

[0135] Calculate the absorption capacity curve expression of the active distribution network with energy storage:

[0136] right Figure 3 The distribution network with active energy storage (energy storage connected to the downstream node N2 of the key branch B2) calculates its absorption capacity curve expression according to formula (2), as shown in formula (5):

[0137]

[0138] It should be noted that the energy storage power of st(4) in formula (5) only takes the charging power, and the range is [0, 1.00] MVA. This is because the absorption capacity curve in the present invention is composed of the DG boundary points where the DG output growth reaches the reverse flow constraint. In order to balance the DG output and prevent the reverse flow in the distribution network from exceeding the limit, the energy storage should be operated in the charging state rather than the discharging state, and the calculated charging power range of the energy storage is [0, 1.00] MVA.

[0139] right Figure 4 Active distribution network with energy storage (energy storage access key branch B 2 Downstream node N 3 ), and calculate its absorption capacity curve expression according to formula (2), as shown in formula (6):

[0140]

[0141] right Figure 5 The energy storage active distribution network (energy storage connected to the downstream node N4 of the key branch B2) is calculated according to formula (2) as shown in formula (7):

[0142]

[0143] It should be noted that the different locations of the downstream nodes N2, N3 and N4 of the key branch B2 where the energy storage is connected result in different st(3) in equations (5) to (7).

[0144] right Figure 6 For the active distribution network with energy storage (the upstream node N1 of the key branch B2 connected to the energy storage), the absorption capacity curve expression is calculated according to formula (2), as shown in formula (8):

[0145]

[0146] Uniform sampling generates operating points:

[0147] Assuming the step size b is 0.05, according to formula (5), the load node power range [0, 1.00] MVA, the DG node power range [-1.00, 0] MVA and the energy storage power range [0, 1.00] MVA are uniformly sampled with a step size of 0.05. Figure 3 to Figure 6 The distribution networks in all generate 4,084,101 operating points Wi;

[0148] Find the DG boundary points:

[0149] According to st(3) in equations (5) to (8), the 4,084,101 sampling operation points are judged one by one whether they meet the DG growth criticality constraint. If they do, they are respectively: Figure 3 to Figure 6 DG boundary points of active distribution network with energy storage. Figure 3 to Figure 6 The DG boundary point results of the active distribution network with energy storage are shown in Tables 1 to 4 respectively:

[0150] Table 1 Figure 3 DG boundary point of active distribution network with energy storage (energy storage access key branch B 2 Downstream Node N 2 )

[0151]

[0152] Table 2 Figure 4 DG boundary point of active distribution network with energy storage (energy storage access key branch B 2 Downstream Node N 3 )

[0153]

[0154]

[0155] Table 3 Figure 5 DG boundary point of active distribution network with energy storage (energy storage access key branch B 2 Downstream Node N 4 )

[0156]

[0157] Table 4 Figure 6 DG boundary point of active distribution network with energy storage (energy storage access key branch B 2 Upstream node N 1 )

[0158]

[0159] Draw the absorption capacity curve:

[0160] According to st(1) in formula (5), Figure 3 The sum of the DG outputs at the DG boundary points (Table 1) is Val (W DGB,i ) The results are shown in the last column of Table 1. The absorption capacity curve is drawn by sorting them from small to large, such as Figure 7 shown.

[0161] According to st(1) in equations (6) to (8), we can calculate Figures 4 to 6 The sum of the DG outputs of the DG boundary points (Table 2 to Table 4) is Val (W DGB,i ), the results are shown in the last column of Table 2 to Table 4, and the absorption capacity curve is drawn from small to large, such as Figure 7 It should be pointed out that due to Figure 3 to Figure 6 The number of DG boundary points in the active distribution network with energy storage is not exactly the same. For the convenience of comparison, Figure 3 , Figure 4 and Figure 6 The DG boundary point number of the distribution network absorption capacity curve is expanded to Figure 5 The 71900 DG boundary points of the distribution network are numbered and plotted in the same coordinate system.

[0162] Depend on Figure 7 see:

[0163] The complete absorption capacity of the active distribution network under various load / DG distributions with the participation of energy storage can be represented by an absorption capacity curve rather than a single value of the maximum absorption capacity;

[0164] Energy storage access to key branch B 2 Downstream active distribution network ( Figure 3 to Figure 5 ) is higher than the overall absorption capacity curve of the key branch B connected to energy storage 2 Upstream active distribution network ( Figure 6 ), indicating that compared with connecting energy storage upstream of key branches, connecting energy storage downstream of key branches can effectively and completely improve the system's absorption capacity;

[0165] Compare energy storage access to key branch B 2 Downstream Node N X = {N 2 ,N 3 ,N 4} of the active distribution network ( Figure 3 to Figure 5 ) can be seen from the absorption capacity curve that energy storage is connected to the key branch B 2 Downstream Node N 2 and N 3 Active distribution network ( Figure 3 and Figure 4 ) completely overlaps with the absorption capacity curve, indicating Figure 3 and Figure 4 The active distribution network has the same absorption capacity (the data in Table 1 and Table 2 are exactly the same, which also verifies this point); however, the energy storage is connected to the key branch B 2 Downstream Node N 4 Active distribution network ( Figure 5 ) is at the highest position in the absorption capacity curve, indicating that energy storage is connected to the downstream node N of the key branch.4 Active distribution network ( Figure 5 ) compared to Figure 3 and Figure 4 The active distribution network has a greater complete absorption capacity. Therefore, in the initial site selection, the key branch B 2 Downstream Node N X = {N 2 ,N 3 ,N 4 When energy storage is connected, the optimal location for energy storage to improve the absorption capacity is the downstream node N of the key branch. 4 .

[0166] Calculate the absorption capacity curve index:

[0167] Figure 3 to Figure 6 The absorption capacity curve indicators of the active distribution network containing energy storage are shown in Table 5.

[0168] Table 5 Figure 3 to Figure 6 The absorption capacity curve index of the active distribution network containing energy storage

[0169]

[0170]

[0171] Table 5 specifically quantifies the complete absorption capacity of the active distribution network under various load / DG distributions with the participation of energy storage as an interval value, rather than a single maximum absorption capacity TAC value. For example, Figure 3 Active distribution network (energy storage access to key branch downstream node N 2 )'s complete absorption capacity is between [0.95, 2.40] MVA, Figure 5 Active distribution network (energy storage access to key branch downstream node N 4 )’s complete absorption capacity is between [0.95, 2.95] MVA.

[0172] As shown in Table 5, except for the minimum absorption capacity TAC min In addition to the same Figure 3 to Figure 5 Active distribution network (energy storage access to key branch downstream nodes {N 2 ,N 3 ,N 4 The maximum and average absorption capacity of Figure 6 The size of the active distribution network (node ​​N1 upstream of the key branch connected to energy storage) indicates that connecting energy storage downstream of the key branch can more completely improve the system's comprehensive absorption capacity than connecting energy storage upstream of the key branch. Therefore, the method proposed in the present invention for determining the preliminary site selection location of energy storage connected to the distribution network based on the key branch is effective and feasible.

[0173] Preferably, in comparison table 5 Figure 3 to Figure 5 Active distribution network (energy storage access to key branch downstream nodes {N 2 ,N 3 ,N 4}, except for TAC min In addition to the same Figure 5 Active distribution network (energy storage access to key branch downstream node N 4 )'s maximum and average absorption capacity are higher than Figure 3 and Figure 4 Active distribution network (energy storage access to key branch upstream node N 2 and N 3 ) is large, indicating Figure 5 Active distribution network compared Figure 3 and Figure 4 The distribution network has a greater comprehensive absorption capacity. 2 Downstream Node N X = {N 2 ,N 3 ,N 4 When energy storage is connected, the optimal location for energy storage to improve the absorption capacity is the downstream node N of the key branch. 4 Therefore, the present invention can effectively determine the optimal location for energy storage to be connected to the distribution network with the best absorption capacity improvement effect.

[0174] In summary, the feasibility and effectiveness of the method of the present invention have been verified through specific examples. By comparing the absorption capacity curves and indicators of different energy storage access locations (critical branch downstream nodes N2, N3, N4 and upstream node N1), the results show that connecting energy storage to the critical branch downstream node can more effectively improve the comprehensive absorption capacity of the system. In particular, when the energy storage is connected to the critical branch downstream node N4, the maximum absorption capacity of the system reaches 2.95MVA, and the average absorption capacity is 1.87MVA, both higher than other access locations. The correctness of the method for determining the preliminary site selection based on the critical branch is verified, and it is also proved that the method can effectively determine the optimal energy storage access location with the best absorption capacity improvement effect. At the same time, the complete absorption capacity of the active distribution network under various load / DG distributions with the participation of energy storage is fully quantified in the form of absorption capacity curves and range values, providing a more comprehensive and accurate reference for system planning and operation.

[0175] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for selecting a site for energy storage to improve the absorption capacity of an active distribution network, characterized in that: include, Determine the key branches based on the absorption capacity curve; Determine the preliminary site location of the access point based on the key branches; Solve the absorption capacity curve and its index of each preliminary site after connecting to energy storage; Compare the absorption capacity curves and indicators of different preliminary site selection locations to determine the optimal energy storage access location.

2. The energy storage site selection method for improving the absorption capacity of the active distribution network according to claim 1, characterized in that: The step of determining the key branch is specifically to calculate the absorption capacity curve expression of the active distribution network: Among them, L TAC is the absorption capacity curve, Val(W DGB,i ) is the absorption capacity of the operating point, i is the sorting number of the sampling point; Where st(1) represents the operating point absorption capacity Val(W DB,i ) is equal to the sum of the apparent powers of all DG nodes, that is, the sum of the DG outputs; Where st(2) represents the operating point W B,i On the DG boundary, W B,i is the DG boundary point, and the apparent power vector W of the load node LB,i and the DG node apparent power vector W DGB,i Composition, W LB,i S LB,h is the outflow power of the hth load node, W DGB,i S DGB,n Inject power into the nth DG node, Ω DG+ For all DG boundaries, β DG+,j is the jth DG boundary; Among them, st(3) is the DG growth criticality constraint, which means that the reverse power flow equality constraint covers all DG variables, so that all DG variables are subject to equality constraints, and any DG output growth will cause the reverse power flow to exceed the limit; The criticality of DG growth is determined by the sum of the DG variable coefficients constrained by the reverse power flow equation being greater than 0 (i.e., a 1k +a 2k +...+a lk >0,k=1,2,...,n)guarantee; The left constraint in st(3) is the reverse flow constraint, and the right constraint is the forward flow constraint. In the formula, l is the number of equality constraints, m is the number of equality and inequality constraints, and a is the number of ln Indicates whether the nth element is in the lth constraint, if yes, it takes 1, if no, it takes 0, r is the network loss coefficient, indicating that the network loss is taken into account, cl is the capacity of the lth element (branch), the equality constraint indicates that the reverse flow of the element reaches the upper capacity limit, and the inequality constraint indicates that the flow of the element does not exceed the upper capacity limit; The critical branch is the branch in the active distribution network where the reverse power flow reaches the component capacity first; Calculate the absorption capacity curve expression of the active distribution network and find the reverse power flow equation constraint covering all DG variables in the absorption capacity curve expression: -c l =(1+r)(a l1 S DGB,1 +...+a ln S DGB,n +a l(n+1) S LB,1 +...+a l(n+h) S LB,h ) If the reverse flow of the branch (branch l) corresponding to the reverse flow equation constraint reaches its capacity first, then the branch (branch l) is the critical branch.

3. The energy storage site selection method for improving the absorption capacity of the active distribution network as claimed in claim 2, characterized in that: The preliminary site selection of the access point based on the key branch is specifically as follows: The active distribution network nodes are divided into the key branch downstream nodes NX = {Nk+1, ..., Nq} and the upstream branch NS = {N1, ..., Nk}; Among them, k is the location of the key branch, q is the total number of nodes, and the downstream node of the key branch NX = {Nk+1,…,Nq} is selected as the preliminary site selection location.

4. The energy storage site selection method for improving the absorption capacity of the active distribution network as claimed in claim 3 is characterized by: The steps for solving the absorption capacity curve and its index after each preliminary site selection location is connected to energy storage are: Calculate the absorption capacity curve expression of the active distribution network with energy storage; Uniform sampling generates operating points; Screening DG boundary points that meet the DG growth criticality constraints; Calculate and sort the sum of DG outputs at DG boundary points and draw the absorption capacity curve; Calculate the absorption capacity curve index.

5. The method for selecting a site for energy storage to improve the absorption capacity of an active distribution network as claimed in claim 4, characterized in that: The uniform sampling generates the operating point specifically as follows: With step size b in the load node power range DG node power range And energy storage power range Uniform sampling is performed to generate X operating points W i ; The calculation of the absorption capacity curve index is specifically: The maximum absorption capacity TAC is the absorption capacity value at the highest point of the absorption capacity curve of the active distribution network including energy storage; Average absorption capacity is the average absorptive capacity of all DG boundary points constituting the absorptive capacity curve; Minimum absorption capacity TAC min It is the absorption capacity value at the lowest point of the absorption capacity curve.

6. The method for selecting a site for energy storage to improve the absorption capacity of an active distribution network as claimed in claim 5, characterized in that: The mathematical model of the absorption capacity curve of the active distribution network with energy storage is: Among them, S ESSB,k is the power of the energy storage connected to node k, β is a 0-1 variable, S ESS,d is the energy storage discharge power, S ESS,c The charging power for energy storage, and are the maximum charging and discharging powers constrained by PCS, C ESS,N is the energy capacity of energy storage, and are the maximum and minimum values ​​of energy storage SOC, Δt is the charge and discharge time, η ESS,c and η ESS,d are the charging and discharging efficiency of energy storage, ESS is the grid-connected power factor of the energy storage.

7. The method for selecting a site for energy storage to improve the absorption capacity of an active distribution network according to claim 6, characterized in that: The comparison of the absorption capacity curves and indicators of different preliminary site selection locations to determine the optimal energy storage access location is specifically as follows: Draw the absorption capacity curves of the active distribution network after connecting to energy storage at different locations in the same graph; The absorption capacity curve indicators of the active distribution network after connecting to energy storage at different locations are listed in the same table; By comparing the height of the absorption capacity curve and the size of the index after connecting to energy storage at different locations; The energy storage access location with the highest absorption capacity curve position and the largest curve index is preferably determined as the optimal location for energy storage access to the distribution network with the best absorption capacity improvement effect.

8. A multi-resource inertia and primary frequency regulation auxiliary service sequential acquisition system, based on the energy storage site selection method for improving the absorption capacity of the active distribution network according to any one of claims 1 to 7, characterized in that: It also includes a key branch determination module, a preliminary site selection module and an optimal location determination module; The key branch determination module is used to collect the topological structure of the active distribution network, the power range data of the load nodes and the DG nodes, calculate the absorption capacity curve expression of the active distribution network, and determine the key branches; The preliminary site selection module is used to divide the active distribution network nodes into downstream nodes and upstream nodes based on key branches, and determine the preliminary site selection location for energy storage access; The optimal location determination module is used to solve the absorption capacity curve and its index after each preliminary site selection location is connected to the energy storage, compare the absorption capacity curves and their indexes of different preliminary site selection locations, determine the optimal energy storage access location, and regularly update and optimize the energy storage access plan.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the energy storage site selection method for improving the absorption capacity of the active distribution network as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the energy storage site selection method for improving the absorption capacity of an active distribution network as described in any one of claims 1 to 7 are implemented.

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