Active power distribution network dynamic scheduling method and device based on fully distributed algorithm

Abstract

The invention discloses an active power distribution network dynamic scheduling method and device based on a fully distributed algorithm, and relates to the technical field of power distribution networks. The method comprises the following steps: acquiring the power generation cost and the solar energy abandoned electric quantity of a power distribution network; constructing an active power distribution network dispatching model according to the constraint condition of the power distribution network, the power generation cost and the solar energy abandoned electric quantity; dividing the power distribution network into N line areas according to tie lines in the power distribution network; respectively calculating a target parameter of each line area in the N line areas through a fully distributed algorithm and an active power distribution network scheduling model; and performing dynamic scheduling on the power distribution network according to the target parameter of each line area. According to the method and the device, the technical problem of overlarge communication pressure caused by excessive distributed power supplies during dynamic scheduling of the power distribution network in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the technical field of distribution network, and in particular to a method and device for dynamic scheduling of active distribution network based on a fully distributed algorithm. Background Art

[0002] The new power system with new energy as the main body has become the development direction of the contemporary power system. Distributed power sources such as distributed photovoltaics are widely connected to the distribution network, and are coupled with traditional micro gas turbines, flexible loads, distributed energy storage systems, etc., which makes the energy flow of the distribution network complicated and has a certain adverse impact on the economic dispatch of the distribution network.

[0003] In addition, the distribution network contains subsystems divided by geography or administrative regions. The market players of various types of distributed power sources are not the same. Due to the need for confidentiality of commercial information, the information exchange between each player is limited. Moreover, the large number of distributed power sources in the distribution network will bring heavy communication and data burdens to traditional centralized optimization scheduling.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present application provide a method and device for dynamic scheduling of an active distribution network based on a fully distributed algorithm, so as to at least solve the technical problem in the prior art of excessive communication pressure caused by an excessive number of distributed power sources when dynamically scheduling the distribution network.

[0006] According to one aspect of an embodiment of the present application, a method for dynamic scheduling of an active distribution network based on a fully distributed algorithm is provided, comprising: obtaining the power generation cost and solar energy curtailment of the distribution network, wherein the solar energy curtailment represents the amount of electricity that is discarded because the solar power generation cannot be fully absorbed by the distribution network; constructing an active distribution network scheduling model according to the constraints, power generation cost and solar energy curtailment of the distribution network, wherein the active distribution network scheduling model is used to reduce the power generation cost and solar energy curtailment by adjusting parameters of different line areas of the distribution network under the condition of satisfying the constraints, and the constraints are used to ensure the normal operation of the distribution network; according to the interconnection lines in the distribution network, the distribution network is divided into N line areas, wherein N is an integer greater than 1; by using the fully distributed algorithm and the active distribution network scheduling model, the target parameters of each line area in the N line areas are calculated respectively, wherein the target parameters of each line area are used to reduce the power generation cost and solar energy curtailment of the line area; and the distribution network is dynamically scheduled according to the target parameters of each line area.

[0007] Optionally, in the active distribution network dynamic scheduling method based on a fully distributed algorithm provided in the present application, the constraints of the distribution network include at least the following conditions: a first condition, used to constrain the power change rate of the distributed power sources of the distribution network to be between a first value and a second value, the first value being the maximum value of the output change rate of the distributed power sources of the distribution network, and the second value being the opposite of the first value; a second condition, used to constrain the power generation capacity of the generators of the distribution network; a third condition, used to constrain the power generation power of each branch of the distribution network; and a fourth condition, used to constrain the power flow balance information of the distribution network, wherein the power flow balance information represents the balance information between the power generation and power consumption of the distribution network.

[0008] Optionally, in the active distribution network dynamic scheduling method based on a fully distributed algorithm provided in the present application, before obtaining the power generation cost and solar energy curtailment of the distribution network, a first function and a second function are constructed according to the active power and predicted power of the distributed power sources of the distribution network, wherein the first function is used to calculate the solar energy curtailment and the second function is used to calculate the power generation cost of the distributed power sources of the distribution network; a third function is constructed according to the second function and the number of distributed power sources in the distribution network, wherein the third function is used to calculate the power generation cost of the distribution network.

[0009] Optionally, in the active distribution network dynamic scheduling method based on a fully distributed algorithm provided in the present application, an active distribution network scheduling model is constructed according to the constraints of the distribution network, the power generation cost and the amount of solar energy abandoned, including: determining the fourth function according to the third function and the first function, wherein the fourth function is used to calculate the minimum value of the weighted sum of the power generation cost of the distribution network and the amount of solar energy abandoned; expressing the constraints through the fifth function, and by introducing a branch node matrix, characterizing the balance information between the power generation and power consumption of the distribution network through an augmented matrix; and constructing the active distribution network scheduling model according to the fourth function, the fifth function and the augmented matrix.

[0010] Optionally, in the active distribution network dynamic scheduling method based on a fully distributed algorithm provided in the present application, the target parameters of each of the N line areas are calculated respectively through the fully distributed algorithm and the active distribution network scheduling model, including: splitting N augmented association matrices according to the augmented matrix, wherein the sum of the N augmented association matrices is equal to the augmented matrix, and the N augmented association matrices correspond one-to-one to the N line areas; calculating the target parameters of the Jth line area according to the augmented association matrix corresponding to the Jth line area and the active distribution network scheduling model, wherein J is a positive integer less than or equal to N.

[0011] Optionally, in the active distribution network dynamic scheduling method based on a fully distributed algorithm provided in the present application, the target parameters of the Jth line area are calculated according to the augmented association matrix corresponding to the Jth line area and the active distribution network scheduling model, including: converting the active distribution network scheduling model into a target model, wherein the target model is used to convert the fourth function, the fifth function and the augmented matrix into an inequality constraint function based on the Lagrange principle; using the augmented association matrix corresponding to the Jth line area to replace the augmented matrix in the target model, solving the target model, and obtaining the correct solution of the unknowns in the target model; and using the correct solution of the unknowns in the target model as the target parameters of the Jth line area.

[0012] Optionally, in the active distribution network dynamic scheduling method based on a fully distributed algorithm provided in the present application, the distribution network is dynamically scheduled according to the target parameters of each line area, including: adjusting the active power generation power and reactive power generation power of each line area according to the target parameters of the line area, wherein the target parameters of different line areas are transmitted independently; by adjusting the active power generation power and reactive power generation power of each line area, the power supply load of each line area is dynamically scheduled.

[0013] According to another aspect of the present application, there is also provided an active distribution network dynamic scheduling device based on a fully distributed algorithm, comprising: a first processing unit, used to obtain the power generation cost and solar energy abandonment of the distribution network, wherein the solar energy abandonment represents the amount of electricity abandoned because the solar power generation cannot be fully absorbed by the distribution network; a second processing unit, used to construct an active distribution network scheduling model according to the constraints, power generation cost and solar energy abandonment of the distribution network, wherein the active distribution network scheduling model is used to reduce the power generation cost and solar energy abandonment by adjusting the parameters of different line areas of the distribution network under the condition of satisfying the constraints, and the constraints are used to ensure the normal operation of the distribution network; a third processing unit, used to divide the distribution network into N line areas according to the interconnection lines in the distribution network, wherein N is an integer greater than 1; a fourth processing unit, used to calculate the target parameters of each line area in the N line areas respectively through the fully distributed algorithm and the active distribution network scheduling model, wherein the target parameters of each line area are used to reduce the power generation cost and solar energy abandonment of the line area; a fifth processing unit, used to dynamically schedule the distribution network according to the target parameters of each line area.

[0014] According to another aspect of the present application, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer-readable storage medium, wherein when the computer program is executed, the device where the computer-readable storage medium is located executes the above-mentioned active distribution network dynamic scheduling method based on a fully distributed algorithm.

[0015] According to another aspect of the present application, an electronic device is also provided, wherein the electronic device includes one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by one or more processors, the one or more processors execute the above-mentioned active distribution network dynamic scheduling method based on a fully distributed algorithm.

[0016] In the present application, the power generation cost and the amount of solar energy abandoned of the distribution network are first obtained, wherein the amount of solar energy abandoned represents the amount of electricity abandoned because the solar power generation cannot be fully absorbed by the distribution network. Then, according to the constraints of the distribution network, the power generation cost and the amount of solar energy abandoned, an active distribution network scheduling model is constructed, wherein the active distribution network scheduling model is used to reduce the power generation cost and the amount of solar energy abandoned by adjusting the parameters of different line areas of the distribution network under the condition of satisfying the constraints, and the constraints are used to ensure the normal operation of the distribution network. Subsequently, according to the interconnection lines in the distribution network, the distribution network is divided into N line areas, wherein N is an integer greater than 1; the target parameters of each line area in the N line areas are calculated respectively through the fully distributed algorithm and the active distribution network scheduling model, wherein the target parameters of each line area are used to reduce the power generation cost and the amount of solar energy abandoned in the line area. Finally, the distribution network is dynamically scheduled according to the target parameters of each line area.

[0017] It can be seen from the above content that the present application first constructs an active distribution network scheduling model according to the constraints of the distribution network, the power generation cost and the amount of solar energy abandoned, and then divides the distribution network into N line areas according to the interconnection lines in the distribution network. Finally, the target parameters of each line area in the N line areas are calculated respectively through the fully distributed algorithm and the active distribution network scheduling model; the distribution network is dynamically scheduled according to the target parameters of each line area. When the technical solution of the present application is used for distribution network scheduling, each line area only needs to exchange limited information with adjacent areas to optimize the output power of distributed power sources, which can not only ensure information security, but also the solution does not need to use a central coordinator for data processing. Each line area independently calculates the target parameters, thereby effectively reducing the overall communication pressure, thereby solving the technical problem of excessive communication pressure caused by too many distributed power sources when dynamically scheduling the distribution network in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0019] Figure 1is a flow chart of an optional active distribution network dynamic scheduling method based on a fully distributed algorithm according to an embodiment of the present application;

[0020] Figure 2 is a schematic diagram of an optional three-area distribution network structure according to an embodiment of the present application;

[0021] Figure 3 It is a schematic diagram of an optional simulation circuit according to an embodiment of the present application.

[0022] Figure 4 It is a schematic diagram of an active distribution network dynamic scheduling device based on a fully distributed algorithm according to an embodiment of the present application. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0024] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0025] It should also be noted that the information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) collected by this application are information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of relevant data are in compliance with the relevant laws, regulations and standards of the relevant regions, necessary confidentiality measures are taken, and public order and good customs are not violated, and corresponding operation portals are provided for users to choose to authorize or refuse. For example, an interface is set up between this system and relevant users or organizations. Before obtaining relevant information, it is necessary to send an acquisition request to the aforementioned user or organization through the interface, and obtain relevant information after receiving the consent information fed back by the aforementioned user or organization.

[0026] According to an embodiment of the present application, an embodiment of a method for dynamic scheduling of an active distribution network based on a fully distributed algorithm is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0027] Figure 1 is a flow chart of an optional active distribution network dynamic scheduling method based on a fully distributed algorithm according to an embodiment of the present application, such as Figure 1 As shown, the method comprises the following steps:

[0028] Step S101, obtaining the power generation cost and solar energy curtailment amount of the distribution network.

[0029] In step S101, the solar energy curtailment represents the amount of electricity that is abandoned because the solar energy generated cannot be fully absorbed by the distribution network.

[0030] Optionally, the goal of active distribution network economic dispatch is to minimize the power generation cost F1 of all traditional distributed power sources and minimize the amount of solar energy curtailment F2.

[0031] Step S102: construct an active distribution network scheduling model according to the constraints of the distribution network, the power generation cost and the amount of solar energy curtailment.

[0032] Optionally, the active distribution network dispatching model is used to reduce the power generation cost and the amount of solar energy curtailment by adjusting parameters of different line areas of the distribution network while satisfying constraint conditions, and the constraint conditions are used to ensure the normal operation of the distribution network.

[0033] Optionally, there may be multiple constraints, which are used to constrain the dispatching process of the distribution network from multiple dimensions to ensure that the distribution network always operates normally during the dispatching process without any abnormal conditions.

[0034] Step S103, dividing the distribution network into N line areas according to the tie lines in the distribution network.

[0035] In step S103, N is an integer greater than 1.

[0036] Optionally, there are fewer connecting lines between different line areas, so dynamic scheduling can be performed for different line areas. For example, the distribution network is divided into N line areas according to the principle that the number of connecting lines between any two line areas is less than a preset number, where the preset number can be customized. For example, the preset number is set to 3, and if the number of connecting lines between the Z1 area and the Z2 area of ​​the distribution network is less than 3, the two areas are determined as two areas of the N line areas; if the number of connecting lines between the Z1 area and the Z2 area of ​​the distribution network is greater than 3, the two areas are merged into one area.

[0037] Step S104, calculating the target parameters of each of the N line areas respectively by using a fully distributed algorithm and an active distribution network scheduling model.

[0038] In step S104, the target parameters of each line area are used to reduce the power generation cost and the amount of solar energy curtailment in the line area.

[0039] Optionally, the target parameter of each line area is a parameter that can determine the output power of the line area, and the fully distributed algorithm in the present application can be a fully distributed PDIP (Parallel and Decentralized Inverse Power) algorithm.

[0040] Alternatively, the fully distributed PDIP algorithm is an algorithm for distributed optimization and network synchronization. It is mainly used to solve the problem that in a distributed system, each node needs to work together to achieve a common goal. This algorithm has applications in many fields, such as power systems, communication networks, and multi-agent systems. The core idea of ​​the PDIP algorithm is to use the local information of each node, update the state of the node by iteration, and finally make the entire network reach a synchronized or optimized state. The main steps of the algorithm are as follows:

[0041] 1. Initialization: Each node is initialized according to its own initial state and goal.

[0042] 2. Iterative update: In each iteration, each node updates its own state based on the current state of its neighbors and its own current state. This process can be regarded as a local decision-making process based on neighbor information.

[0043] 3. Convergence judgment: After each iteration, the algorithm will check whether the convergence condition is met. If it is met, the algorithm stops iterating; otherwise, it continues to the next iteration.

[0044] 4. Result output: When the algorithm converges, the final state of each node is output, and these states together constitute the synchronization or optimization result of the entire network.

[0045] The advantages of the PDIP algorithm include:

[0046] 1. Distributed: The algorithm does not require a centralized control center. Each node only needs to make decisions based on its own local information and the information of its neighbors.

[0047] 2. Scalability: The algorithm can be easily expanded to large-scale networks because the processing process of each node is independent.

[0048] 3. Robustness: The algorithm is robust to changes in the network topology and node status.

[0049] 4. Convergence: Under certain conditions, the PDIP algorithm can be guaranteed to converge to the global optimal solution.

[0050] Step S105: Dynamically dispatch the distribution network according to the target parameters of each line area.

[0051] Optionally, the dispatching system can adjust the active power generation power and reactive power generation power of each line area according to the target parameters of each line area, wherein the target parameters of different line areas are transmitted independently; by adjusting the active power generation power and reactive power generation power of each line area, the power supply load of each line area is dynamically dispatched.

[0052] Based on the contents of the above steps S101 to S105, it can be known that in the present application, the power generation cost and the amount of solar energy abandoned of the distribution network are first obtained, wherein the amount of solar energy abandoned represents the amount of electricity abandoned because the solar power generation cannot be fully absorbed by the distribution network. Then, according to the constraints of the distribution network, the power generation cost and the amount of solar energy abandoned, an active distribution network scheduling model is constructed, wherein the active distribution network scheduling model is used to reduce the power generation cost and the amount of solar energy abandoned by adjusting the parameters of different line areas of the distribution network under the condition of satisfying the constraints, and the constraints are used to ensure the normal operation of the distribution network. Subsequently, according to the interconnection lines in the distribution network, the distribution network is divided into N line areas, wherein N is an integer greater than 1; the target parameters of each line area in the N line areas are calculated respectively by a fully distributed algorithm and an active distribution network scheduling model, wherein the target parameters of each line area are used to reduce the power generation cost and the amount of solar energy abandoned in the line area. Finally, the distribution network is dynamically scheduled according to the target parameters of each line area.

[0053] It can be seen from the above content that the present application first constructs an active distribution network scheduling model according to the constraints of the distribution network, the power generation cost and the amount of solar energy abandoned, and then divides the distribution network into N line areas according to the interconnection lines in the distribution network. Finally, the target parameters of each line area in the N line areas are calculated respectively through the fully distributed algorithm and the active distribution network scheduling model; the distribution network is dynamically scheduled according to the target parameters of each line area. When the technical solution of the present application is used for distribution network scheduling, each line area only needs to exchange limited information with adjacent areas to optimize the output power of distributed power sources, which can not only ensure information security, but also the solution does not need to use a central coordinator for data processing. Each line area independently calculates the target parameters, thereby effectively reducing the overall communication pressure, thereby solving the technical problem of excessive communication pressure caused by too many distributed power sources when dynamically scheduling the distribution network in the prior art.

[0054] In an optional embodiment, before obtaining the power generation cost and solar energy curtailment of the distribution network, a first function and a second function are first constructed according to the active power and predicted power of the distributed power sources of the distribution network, wherein the first function is used to calculate the solar energy curtailment, and the second function is used to calculate the power generation cost of the distributed power sources of the distribution network. Then, a third function is constructed according to the second function and the number of distributed power sources in the distribution network, wherein the third function is used to calculate the power generation cost of the distribution network.

[0055] Optionally, a fourth function may be determined according to the third function and the first function, wherein the fourth function is used to calculate the minimum value of a weighted sum of the power generation cost of the distribution network and the amount of solar energy curtailment.

[0056] Optionally, the goal of the active distribution network economic dispatch is to minimize the generation cost F1 of all traditional distributed power sources and minimize the solar energy curtailment F2, which can be expressed as the following formula (1):

[0057] minF=ω1F1+ω2F2

[0058]

[0059] Wherein, the above formula (1) corresponds to the above fourth function, ω1 and ω2 are two weight coefficients respectively; Ω T ,Ω S They are respectively a set consisting of traditional distributed power sources and a set consisting of photovoltaic power stations; are the active power and predicted power of distributed generation j respectively; is the power generation cost function of the traditional distributed power source (ie, the second function).

[0060] It is easy to notice that formula (1) includes a third function for calculating the power generation cost F1 of the distribution network and a second function for calculating the solar energy curtailment amount F2 of the distribution network.

[0061] in addition, The calculation formula is as follows:

[0062]

[0063] Optionally, a in formula (2) i 、b i 、c i represent the coefficients of the quadratic equation respectively.

[0064] In an optional embodiment, the constraints of the distribution network include at least the following conditions:

[0065] The first condition is used to constrain the power change rate of the distributed power source of the distribution network to be between a first value and a second value, the first value is the maximum value of the output change rate of the distributed power source of the distribution network, and the second value is the opposite of the first value;

[0066] The second condition is used to constrain the power generation capacity of the generators in the distribution network;

[0067] The third condition is used to constrain the power generation of each branch of the distribution network;

[0068] The fourth condition is used to constrain the power flow balance information of the distribution network, wherein the power flow balance information represents the balance information between the power generation and power consumption of the distribution network.

[0069] Optionally, the constraints for economic dispatch of the distribution network mainly include the ramp limit of distributed power sources (corresponding to the first condition mentioned above), the generator power generation capacity constraint (corresponding to the second condition mentioned above), the branch power constraint (corresponding to the third condition mentioned above) and the flow balance constraint (corresponding to the fourth condition mentioned above).

[0070] Optionally, for the ramp limit of distributed power sources, the power change rate of traditional distributed power sources (such as micro gas turbines) should meet certain restrictions. In this application, the first condition can be set as formula (3):

[0071]

[0072] in, is the output change rate limit of distributed generation i.

[0073] Optionally, for the generator capacity constraint and branch power constraint, the capacity constraint of the traditional distributed power source can be expressed as formula (4):

[0074]

[0075] The capacity constraint of photovoltaic power source can be expressed as formula (5):

[0076]

[0077] The branch power constraint can be expressed as formula (6):

[0078]

[0079] in, is the active power of branch ij.

[0080] For the power flow balance constraint, for node i, its power flow balance equation can be written as formula (7):

[0081]

[0082] Among them, u:u→i means that node u is associated with node i, and power flows to node i.

[0083] In an optional embodiment, an active distribution network scheduling model is constructed according to the constraints of the distribution network, the power generation cost and the amount of solar energy abandoned, including: determining a fourth function according to the third function and the first function, wherein the fourth function is used to calculate the minimum value of the weighted sum of the power generation cost of the distribution network and the amount of solar energy abandoned; expressing the constraints through a fifth function, and by introducing a branch node matrix, characterizing the balance information between the power generation and power consumption of the distribution network through an augmented matrix; and constructing an active distribution network scheduling model according to the fourth function, the fifth function and the augmented matrix.

[0084] Optionally, for the convenience of expression, the branch node matrix B is introduced to rewrite formula (7) to obtain formula (8):

[0085]

[0086] Optionally, in formula (8): the element in B is ij , which means:

[0087]

[0088] in, It can be written as formula (9):

[0089]

[0090] in, is the load of node i.

[0091] Optionally, in the model solution, In order to solve the variables, it is necessary to transform formula (8) for the convenience of solving. First, determine formula (10):

[0092]

[0093] Then substitute formula (10) into formula (8) to obtain formula (11):

[0094]

[0095] make Formula (11) can be simplified to formula (12):

[0096] B s x=b (12)

[0097] Among them, B s It is called the augmented matrix.

[0098] Finally, the above formulas (1), (3)-(6), and (12) constitute the active distribution network dispatching model. Among them, formulas (3)-(6) are collectively referred to as the fifth function.

[0099] In an optional embodiment, the target parameters of each of the N line areas are calculated respectively through a fully distributed algorithm and an active distribution network scheduling model, including: splitting N augmented association matrices according to the augmented matrix, wherein the sum of the N augmented association matrices is equal to the augmented matrix, and the N augmented association matrices correspond one-to-one to the N line areas; calculating the target parameters of the Jth line area according to the augmented association matrix corresponding to the Jth line area and the active distribution network scheduling model, wherein J is a positive integer less than or equal to N.

[0100] Optionally, since the distribution network mostly operates in a radial manner and there are fewer interconnection lines connecting adjacent areas, its augmented association matrix is ​​very sparse, and it is the only factor reflecting regional interconnection. Therefore, in order to simplify the communication process and reduce the overall communication pressure of the distribution network, the present application splits N augmented association matrices according to the augmented matrix, and uses the augmented association matrix corresponding to each line area to schedule each line area.

[0101] In an optional embodiment, the target parameters of the J-th line area are calculated according to the augmented correlation matrix and the active distribution network dispatching model corresponding to the J-th line area, including: converting the active distribution network dispatching model into a target model, wherein the target model is used to convert the fourth function, the fifth function and the augmented matrix into an inequality constraint function based on the Lagrange principle; using the augmented correlation matrix corresponding to the J-th line area to replace the augmented matrix in the target model, solving the target model, and obtaining the positive solution of the unknowns in the target model; and using the positive solution of the unknowns in the target model as the target parameter of the J-th line area.

[0102] Optionally, in order to facilitate the solution, the distribution network economic dispatch model is first converted into a standard target model, such as formula (13):

[0103] f

[0104] st

[0105]

[0106] Alternatively, the PDIP method can be used to effectively solve the optimization problem. The traditional centralized PDIP requires writing the Karush-Kuhn-Tucker (KKT) equation of formula (14) as follows:

[0107]

[0108] in,

[0109] Let y = (x, λ, v), Δy = (Δx, Δλ, Δv), and give the linearized approximate equation of the Newton method search direction (Formula 15):

[0110]

[0111] Combining equations (14) and (15), the search direction of the decision variable can be obtained as equation (16):

[0112]

[0113] in:

[0114]

[0115] However, the centralized solution method has too high requirements on data communication, and when applied to distribution network scheduling, the matrix dimension is too high and the amount of calculation is very large. Therefore, this application proposes a fully distributed solution method.

[0116] Alternatively, assuming that the distribution network is divided into N line areas, the variables x, λ, and v are also divided into N areas, expressed as y i =(x i ,λ i , v i ), i = 1, ..., N, for the convenience of analysis, Figure 2 An optional schematic diagram of a three-area distribution network structure is shown, including areas A, B, and C.

[0117] Alternatively, since the distribution network mostly operates in a radial manner, there are fewer tie lines connecting adjacent areas, and its augmented correlation matrix is ​​very sparse, and it is the only factor reflecting regional interconnection. As can be seen from formula (14), it involves rdual 、r pri , Δv and Δx, the other calculation steps can be solved locally in each region.

[0118] Optionally, r dual The distributed computing method is as follows:

[0119] According to formula (14), any region, for example, the r dual The calculation formula is updated to formula (18):

[0120]

[0121] in, is the augmented correlation matrix of the Nth region. This matrix ignores the connection lines between regions. Since there are few connection lines between regions, B s Highly sparse, B s and The relationship approximately satisfies equation (19), which is also the theoretical basis of the fully distributed PDIP algorithm.

[0122]

[0123] In formula (18), M r dual N To make up for The additional items introduced by ignoring the tie line are assigned values ​​only to the nodes at one end of the area N in the tie line, and the rest of the nodes are 0. The calculation of the elements is as follows:

[0124]

[0125] Optionally, r pr i The distributed computing method is as follows:

[0126] Similarly, according to formula (14), the r of the Nth region is pri The calculation formula is updated to:

[0127]

[0128] Among them, M r priN is a column vector that is almost zero, and its element calculation is as follows:

[0129]

[0130] Optionally, a distributed calculation method of Δv is as follows:

[0131] From formula (16), we can know that the calculation design of Δv is Y -1 ,because is a diagonal matrix, is an n×n matrix reflecting the network topology. The structure of Y can be as shown in formula (21):

[0132]

[0133] Since there are few connections between different areas in the distribution network, Y is almost a block diagonal matrix. Therefore, the inverse matrix of Y can be expressed as formula (22):

[0134]

[0135] From formula (22), we can know that each area can also be calculated separately, so we can get formula (23):

[0136]

[0137] Optionally, the distributed calculation method of Δx is as follows:

[0138] Optionally, according to formula (16) and formula (22), Δx of the Nth region can be calculated as N The calculation formula is formula (24):

[0139]

[0140] in:

[0141]

[0142] In summary, this application takes advantage of the fact that there are few interconnection lines between distribution networks. s Due to its highly sparse characteristics, the centralized iterative steps are improved to obtain its distributed computing form. Each region performs independent calculations with limited information exchange between them. This can not only improve computing efficiency but also protect each region’s privacy. Compared with centralized algorithms, it has greater advantages in the economic dispatch of distribution networks.

[0143] In an optional embodiment, the distribution network is dynamically scheduled according to the target parameters of each line area, including: adjusting the active power generation power and reactive power generation power of each line area according to the target parameters of the line area, wherein the target parameters of different line areas are transmitted independently; and dynamically scheduling the power supply load of each line area by adjusting the active power generation power and reactive power generation power of each line area.

[0144] Optionally, an improved IEEE33 node system can be used for simulation analysis, and its network structure and partitioning are as follows: Figure 3 As shown, it is divided into three areas, where area A contains three distributed power sources, and area B and area C each contain two distributed power sources.

[0145] Optionally, Figure 3 The 7 distributed power sources in the system are all micro gas turbines, and their cost coefficient is set to a i ~U(0.01,1),b i ~U(20,20.5),c i ~U(600,1530), the scheduling results based on the fully distributed PDIP algorithm of the present application are shown in Table 1.

[0146] Table 1

[0147]

[0148]

[0149] It can be seen from Table 1 that each region can achieve self-optimization and coordinate with adjacent regions to finally obtain a complete solution.

[0150] According to another aspect of the embodiment of the present application, there is also provided an active distribution network dynamic scheduling device based on a fully distributed algorithm, wherein: Figure 4 is a schematic diagram of an active distribution network dynamic dispatching device based on a fully distributed algorithm according to an embodiment of the present application, such as Figure 4 As shown, the active distribution network dynamic dispatching device based on the fully distributed algorithm includes: a first processing unit 401, a second processing unit 402, a third processing unit 403, a fourth processing unit 404, and a fifth processing unit 405.

[0151] Optionally, a first processing unit 401 is used to obtain the power generation cost and solar energy abandonment of the distribution network, wherein the solar energy abandonment represents the amount of electricity abandoned because the solar power generation cannot be fully absorbed by the distribution network; a second processing unit 402 is used to construct an active distribution network scheduling model according to the constraints, power generation cost and solar energy abandonment of the distribution network, wherein the active distribution network scheduling model is used to reduce the power generation cost and solar energy abandonment by adjusting the parameters of different line areas of the distribution network under the condition of satisfying the constraints, and the constraints are used to ensure the normal operation of the distribution network; a third processing unit 403 is used to divide the distribution network into N line areas according to the interconnection lines in the distribution network, wherein N is an integer greater than 1; a fourth processing unit 404 is used to calculate the target parameters of each line area in the N line areas respectively through a fully distributed algorithm and an active distribution network scheduling model, wherein the target parameters of each line area are used to reduce the power generation cost and solar energy abandonment of the line area; a fifth processing unit 405 is used to dynamically schedule the distribution network according to the target parameters of each line area.

[0152] Optionally, the constraints of the distribution network include at least the following conditions:

[0153] The first condition is used to constrain the power change rate of the distributed power source of the distribution network to be between a first value and a second value, the first value is the maximum value of the output change rate of the distributed power source of the distribution network, and the second value is the opposite of the first value;

[0154] The second condition is used to constrain the power generation capacity of the generators in the distribution network;

[0155] The third condition is used to constrain the power generation of each branch of the distribution network;

[0156] The fourth condition is used to constrain the power flow balance information of the distribution network, wherein the power flow balance information represents the balance information between the power generation and power consumption of the distribution network.

[0157] Optionally, the active distribution network dynamic dispatching device based on the fully distributed algorithm includes: a sixth processing unit and a seventh processing unit. The sixth processing unit is used to construct a first function and a second function according to the active power and predicted power of the distributed power sources of the distribution network, wherein the first function is used to calculate the amount of solar energy abandoned, and the second function is used to calculate the power generation cost of the distributed power sources of the distribution network; the seventh processing unit is used to construct a third function according to the second function and the number of distributed power sources in the distribution network, wherein the third function is used to calculate the power generation cost of the distribution network.

[0158] Optionally, the second processing unit 402 includes: a first determining subunit, a first processing subunit, and a second processing subunit. The first determining subunit is used to determine the fourth function according to the third function and the first function, wherein the fourth function is used to calculate the minimum value of the weighted sum of the power generation cost of the distribution network and the amount of solar energy abandoned; the first processing subunit is used to represent the constraint condition through the fifth function, and by introducing the branch node matrix, the balance information between the power generation and the power consumption of the distribution network is represented through the augmented matrix; the second processing subunit is used to construct an active distribution network scheduling model according to the fourth function, the fifth function and the augmented matrix.

[0159] Optionally, the fourth processing unit 404 includes: a third processing subunit and a fourth processing subunit. The third processing subunit is used to split N augmented correlation matrices according to the augmented matrix, wherein the sum of the N augmented correlation matrices is equal to the augmented matrix, and the N augmented correlation matrices correspond to the N line areas one by one; the fourth processing subunit is used to calculate the target parameters of the J-th line area according to the augmented correlation matrix corresponding to the J-th line area and the active distribution network scheduling model, wherein J is a positive integer less than or equal to N.

[0160] Optionally, the fourth processing subunit includes: a first processing module, a second processing module and a third processing module. The first processing module is used to convert the active distribution network dispatching model into a target model, wherein the target model is used to convert the fourth function, the fifth function and the augmented matrix into an inequality constraint function based on the Lagrange principle; the second processing module is used to replace the augmented matrix in the target model with the augmented correlation matrix corresponding to the Jth line area, solve the target model, and obtain the correct solution of the unknown number in the target model; the third processing module is used to use the correct solution of the unknown number in the target model as the target parameter of the Jth line area.

[0161] Optionally, the fifth processing unit 405 includes: an adjustment subunit and a scheduling subunit. The adjustment subunit is used to adjust the active power generation and reactive power generation of each line area according to the target parameters of each line area, wherein the target parameters of different line areas are transmitted independently; the scheduling subunit is used to dynamically schedule the power supply load of each line area by adjusting the active power generation and reactive power generation of each line area.

[0162] According to another aspect of the present application, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer-readable storage medium, wherein when the computer program is executed, the device where the computer-readable storage medium is located executes the above-mentioned active distribution network dynamic scheduling method based on a fully distributed algorithm.

[0163] According to another aspect of the present application, an electronic device is also provided, wherein the electronic device includes one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by one or more processors, the one or more processors execute the above-mentioned active distribution network dynamic scheduling method based on a fully distributed algorithm.

[0164] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0165] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0166] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0167] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0168] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0169] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0170] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for dynamic dispatching of active distribution network based on fully distributed algorithm, characterized in that: include: Obtaining the power generation cost and the solar energy curtailment amount of the distribution network, wherein the solar energy curtailment amount represents the amount of electricity that is discarded because the solar power generation cannot be fully absorbed by the distribution network; An active distribution network scheduling model is constructed according to the constraints of the distribution network, the power generation cost and the amount of solar energy abandoned, wherein the active distribution network scheduling model is used to reduce the power generation cost and the amount of solar energy abandoned by adjusting the parameters of different line areas of the distribution network when the constraints are met, and the constraints are used to ensure the normal operation of the distribution network; According to the tie lines in the distribution network, the distribution network is divided into N line areas, where N is an integer greater than 1; Calculate the target parameters of each of the N line areas respectively by using a fully distributed algorithm and the active distribution network dispatching model, wherein the target parameters of each line area are used to reduce the power generation cost and the amount of solar energy abandoned in the line area; The distribution network is dynamically dispatched according to the target parameters of each line area.

2. The method for dynamic dispatching of active distribution network based on fully distributed algorithm according to claim 1, characterized in that: The constraints of the distribution network include at least the following conditions: A first condition is used to constrain the power change rate of the distributed power source of the distribution network to be between a first value and a second value, wherein the first value is the maximum value of the output change rate of the distributed power source of the distribution network, and the second value is the opposite of the first value; A second condition is used to constrain the power generation capacity of the generator of the power distribution network; A third condition is used to constrain the power generation of each branch of the distribution network; The fourth condition is used to constrain the power flow balance information of the distribution network, wherein the power flow balance information represents the balance information between the power generation and power consumption of the distribution network.

3. The method for dynamic dispatching of active distribution network based on fully distributed algorithm according to claim 1, characterized in that: Before obtaining the power generation cost of the distribution network and the amount of solar energy curtailment, the method further includes: Constructing a first function and a second function according to the active power and the predicted power of the distributed power sources of the distribution network, wherein the first function is used to calculate the amount of solar energy abandoned power, and the second function is used to calculate the power generation cost of the distributed power sources of the distribution network; A third function is constructed according to the second function and the number of distributed power sources in the distribution network, wherein the third function is used to calculate the power generation cost of the distribution network.

4. The method for dynamic dispatching of active distribution network based on fully distributed algorithm according to claim 3 is characterized in that: According to the constraints of the distribution network, the power generation cost and the amount of solar energy abandoned, an active distribution network scheduling model is constructed, including: Determine a fourth function according to the third function and the first function, wherein the fourth function is used to calculate the minimum value of a weighted sum of the power generation cost of the distribution network and the amount of solar energy abandoned power; The constraint condition is represented by a fifth function, and the balance information between the power generation and the power consumption of the distribution network is represented by an augmented matrix by introducing a branch node matrix; The active distribution network scheduling model is constructed according to the fourth function, the fifth function and the augmented matrix.

5. The method for dynamic dispatching of active distribution network based on fully distributed algorithm according to claim 4 is characterized in that: By using a fully distributed algorithm and the active distribution network dispatching model, target parameters of each of the N line areas are calculated respectively, including: Splitting N augmented correlation matrices according to the augmented matrix, wherein a sum of the N augmented correlation matrices is equal to the augmented matrix, and the N augmented correlation matrices correspond one-to-one to the N line areas; According to the augmented correlation matrix corresponding to the J-th line area and the active distribution network scheduling model, the target parameter of the J-th line area is calculated, wherein J is a positive integer less than or equal to N.

6. The method for dynamic dispatching of active distribution network based on fully distributed algorithm according to claim 5, characterized in that: Calculating target parameters of the J-th line area according to the augmented correlation matrix corresponding to the J-th line area and the active distribution network dispatching model, including: Converting the active distribution network dispatching model into a target model, wherein the target model is used to convert the fourth function, the fifth function and the augmented matrix into an inequality constraint function based on the Lagrange principle; Using the augmented correlation matrix corresponding to the J-th line area to replace the augmented matrix in the target model, solving the target model, and obtaining a positive solution to the unknown number in the target model; The correct solutions of the unknowns in the target model are used as the target parameters of the J-th line area.

7. The method for dynamic dispatching of active distribution network based on fully distributed algorithm according to claim 1, characterized in that: Dynamically dispatching the distribution network according to the target parameters of each line area includes: adjusting the active power generation and reactive power generation of each line area according to the target parameters of each line area, wherein the target parameters of different line areas are transmitted independently; By adjusting the active power generation and reactive power generation of each line area, the power supply load of each line area is dynamically scheduled.

8. An active distribution network dynamic dispatching device based on a fully distributed algorithm, characterized in that: include: A first processing unit is used to obtain the power generation cost and the solar energy curtailment amount of the distribution network, wherein the solar energy curtailment amount represents the amount of electricity that is discarded because the solar power generation cannot be fully absorbed by the distribution network; A second processing unit is used to construct an active distribution network scheduling model according to the constraints of the distribution network, the power generation cost and the amount of solar energy abandoned, wherein the active distribution network scheduling model is used to reduce the power generation cost and the amount of solar energy abandoned by adjusting parameters of different line areas of the distribution network when the constraints are met, and the constraints are used to ensure the normal operation of the distribution network; A third processing unit, configured to divide the distribution network into N line areas according to the tie lines in the distribution network, wherein N is an integer greater than 1; a fourth processing unit, configured to calculate target parameters of each of the N line areas respectively by using a fully distributed algorithm and the active distribution network scheduling model, wherein the target parameters of each line area are used to reduce the power generation cost and the amount of solar energy abandoned in the line area; A fifth processing unit is used to dynamically dispatch the distribution network according to the target parameters of each line area.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located executes the active distribution network dynamic scheduling method based on a fully distributed algorithm as described in any one of claims 1 to 7.

10. An electronic device, characterized in that: It includes one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the active distribution network dynamic scheduling method based on a fully distributed algorithm as described in any one of claims 1 to 7.

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