A method and system for optimizing source-grid-load-storage coordinated dispatching for post-disaster recovery of power distribution system

Abstract

The present invention discloses a method and system for optimizing coordinated dispatching of sources, networks, loads and storage for post-disaster recovery of a distribution system, which relates to the technical field of electric power systems and operations research, and comprises: obtaining network topology constraint data of a distribution system, wherein the network topology constraint of the distribution system comprises virtual network topology constraint of the distribution system, geometric network topology constraint of the distribution system and electrical network topology constraint of the distribution system; generating equipment operation characteristic constraint data of the distribution system according to the fault conditions of power supply equipment, load equipment and energy storage equipment caused by disasters, wherein the equipment operation characteristic constraint data of the distribution system comprises operation characteristic constraint of power supply equipment, load equipment and energy storage equipment; inputting the network topology constraint data of the distribution system and the equipment operation characteristic constraint data of the distribution system into a pre-established coordinated dispatching optimization model of sources, networks, loads and storages for a distribution system oriented to post-disaster recovery scenarios, and outputting a coordinated dispatching optimization result.

Description

Technical Field

[0001] The present invention relates to the technical field of power system and operations research, and specifically to a source-grid-load-storage coordinated dispatch optimization method and system for post-disaster recovery of a distribution system. Background Art

[0002] There are two main problems with the existing distribution system post-disaster recovery scheduling methods: on the one hand, the modern distribution system is an organic whole composed of power grid topology, power supply equipment, load equipment and energy storage equipment. However, most of the existing methods only focus on one or several types of controllable equipment, and it is difficult to fully mobilize all power resources in the distribution system to promote power recovery of important loads; on the other hand, traditional distribution system topology control optimization technologies are mostly oriented to normal operating scenarios. When applied to post-disaster recovery scenarios with many equipment failures, loops that violate safety operation requirements may be generated. The new topology control optimization technologies proposed for post-disaster recovery scenarios mostly assume that there are no passive islands in the distribution system. This simplification will result in the model used in the existing technology being unable to provide a feasible scheduling solution once passive islands are generated due to line disconnection and equipment failure in real scenarios. Summary of the invention

[0003] To address the deficiencies mentioned in the above background technology, the purpose of the present invention is to provide a method and system for optimizing the coordinated dispatch of sources, networks, loads and storage for post-disaster recovery of a distribution system, thereby reducing the economic losses caused by disasters by coordinating and regulating the grid topology, power supply equipment, load equipment and energy storage equipment in the distribution system until all faults in the distribution system are repaired and the power supply capacity of the distribution system is restored to the pre-disaster level.

[0004] In a first aspect, the purpose of the present invention can be achieved by the following technical solution: a method for optimizing source-grid-load-storage coordinated scheduling for post-disaster recovery of a distribution system, the method comprising the following steps:

[0005] Acquire network topology constraint data of the power distribution system, wherein the network topology constraint of the power distribution system includes virtual network topology constraint of the power distribution system, geometric network topology constraint of the power distribution system and electrical network topology constraint of the power distribution system;

[0006] Generate distribution system equipment operation characteristic constraint data according to the fault conditions of power supply equipment, load equipment and energy storage equipment caused by the disaster, wherein the distribution system equipment operation characteristic constraint data includes the operation characteristic constraints of power supply equipment, load equipment and energy storage equipment;

[0007] The network topology constraint data of the distribution system and the equipment operating characteristic constraint data of the distribution system are input into a pre-established distribution system source-grid-load-storage collaborative scheduling optimization model for post-disaster recovery scenarios, and the collaborative scheduling optimization results are output.

[0008] In combination with the first aspect, in some implementations of the first aspect, the method further includes: the process of acquiring the network topology constraints of the power distribution system is as follows: receiving the connectivity constraints and the radiation constraints that the network topology needs to satisfy when the power distribution system operates normally, and generating a virtual network topology constraint of the power distribution system according to the connectivity constraints and the radiation constraints;

[0009] The connectivity constraints of the virtual topology of the distribution system are relaxed to generate the geometric network topology constraints of the distribution system. The electrical network topology constraints of the distribution system are generated by receiving the electrical constraints that the grid voltage, current and power in the distribution system need to satisfy. Thus, the virtual network topology constraints of the distribution system, the geometric network topology constraints of the distribution system and the electrical network topology constraints of the distribution system are integrated to generate the network topology constraints of the distribution system.

[0010] In combination with the first aspect, in some implementations of the first aspect, the method further includes: the connectivity constraint is constructed based on a virtual commodity flow model, wherein the formula of the connectivity constraint is as follows:

[0011]

[0012]

[0013]

[0014] Where i and j are node numbers in the power distribution system; I S is the collection of main grid substation nodes in the power distribution system; N is the set of nodes in the distribution system except the main grid substation nodes; t is the number of the decision moment; T is the total time steps of the decision; L is the set of lines in the distribution system, and each line is counted in L in the form of a two-dimensional vector composed of the node numbers at both ends, and the smaller number of the node numbers at both ends is the first dimension of the two-dimensional vector, and the larger number is the second dimension of the two-dimensional vector; f i,j,t is the virtual commodity flow from node i to node j on line (i, j) in the virtual network topology at time t; f j,i,t is the virtual commodity flow from node j to node i on line (j, i) in the virtual network topology at time t; d i,j,t is the on-off state variable of the virtual line (i, j) at time t; M is the linear relaxation coefficient, and its value is set to the number of nodes in the distribution system;

[0015] The formula for the radiation constraint is as follows:

[0016]

[0017] In the formula, |I N| is the number of nodes in the distribution system except the main grid substation nodes.

[0018] In combination with the first aspect, in some implementations of the first aspect, the method further includes: the connectivity constraints of the virtual topology of the power distribution system are relaxed, and the line fault conditions of the power distribution system after the disaster need to be considered when generating the geometric network topology constraints of the power distribution system, and the process is performed based on the principle of generating subgraphs, wherein the constraints constructed by considering the line fault conditions of the power distribution system after the disaster are as follows:

[0019]

[0020]

[0021] In the formula, c i,j,t is the on-off state variable of the physical line (i, j) at time t; is the period of time during which the physical line (i, j) is disconnected due to a fault; is the period during which the physical line (i, j) is not faulty or has been repaired and can work normally; L U A collection of lines that are not equipped with switchgear;

[0022] The geometric network topology constraints of the power distribution system are as follows:

[0023]

[0024] In combination with the first aspect, in some implementations of the first aspect, the method further includes: the electrical network topology constraint of the power distribution system is based on the DistFlow model and combined with the second-order cone relaxation technology and the large M relaxation technology to construct the electrical constraints that the grid voltage, current and power in the power distribution system need to satisfy, thereby forming the electrical network topology constraint of the power distribution system, wherein the electrical constraints that the grid voltage, current and power in the power distribution system need to satisfy are as follows:

[0025]

[0026]

[0027]

[0028]

[0029]

[0030] Where I is the node number set of the distribution system; p i,t is the net active power demand of the equipment connected to node i in the electrical network topology at time t; p i,j,tis the active power delivered from node i to node j by line (i, j) in the electrical network topology at time t; p j,i,t is the active power delivered from line (j,i) at node j to node i in the electrical network topology at time t; is the square of the current on line (j,i) in the electrical network topology at time t; r i,j is the resistance of line (i, j); q i,t is the net reactive power demand of the equipment connected to node i in the electrical network topology at time t; i,j,t is the reactive power delivered from node i to node j by line (i, j) in the electrical network topology at time t; q j,i,t is the reactive power delivered from line (j,i) at node j to node i in the electrical network topology at time t; i,j is the reactance of line (i, j); is the square of the voltage on node i in the electrical network topology at time t; is the square of the voltage on node j in the electrical network topology at time t; ||·||2 is the two-norm operator.

[0031] In combination with the first aspect, in some implementations of the first aspect, the method further includes: the distribution system equipment operation characteristic constraint is constructed for power supply equipment represented by a main grid substation, a distributed fossil fuel unit, and a distributed renewable energy unit in the distribution system, combined with equipment failure conditions caused by disasters, wherein the main grid substation operation characteristic constraint is as follows:

[0032]

[0033]

[0034]

[0035]

[0036] in, is the active power output of the main grid substation at node i at time t; is a binary variable representing the fault status of the main grid substation at node i at time t; is the upper limit of active power that can be output by the main grid substation at node i; is the reactive power output by the main grid substation at node i at time t; is the upper limit of reactive power that can be output by the main grid substation at node i;

[0037] The operating characteristic constraints of the constructed distributed fossil fuel units are as follows:

[0038]

[0039]

[0040]

[0041]

[0042] Among them, I DG A set of node numbers for a distribution system equipped with distributed fossil fuel units; is the active power output of the distributed fossil fuel unit at node i at time t; is a binary variable that characterizes the fault status of the distributed fossil fuel unit at node i at time t; is the upper limit of the active power that can be output by the distributed fossil fuel unit at node i; is the reactive power output of the distributed fossil fuel unit at node i at time t; is the upper limit of reactive power that can be output by the distributed fossil fuel unit at node i;

[0043] The operating characteristic constraints of the constructed distributed renewable energy units are as follows:

[0044]

[0045]

[0046] Among them, I RES A set of node numbers for a distribution system equipped with distributed renewable energy units; is the active power output of the distributed renewable energy unit at node i at time t; is a binary variable that characterizes the fault status of the distributed renewable energy unit at node i at time t; is the upper limit of active power that can be output by the distributed renewable energy unit at node i at time t.

[0047] In combination with the first aspect, in some implementations of the first aspect, the method further includes: constructing operation characteristic constraints of load devices in the power distribution system by using three different types of load devices, namely, removable loads, transferable loads, and non-adjustable loads, wherein the constructed removable load operation characteristic constraints are as follows:

[0048]

[0049]

[0050] in, is the active power absorbed by the removable load on node i at time t; is the upper limit of active power absorbed by the removable load at node i at time t; is the reactive power absorbed by the removable load at node i at time t; is the upper limit of reactive power absorbed by the removable load at node i at time t;

[0051] The constructed transferable load operation characteristic constraints are as follows:

[0052]

[0053]

[0054]

[0055]

[0056] in, is the active power regulation of the transferable load on node i at time t; is the adjustable upper limit of the active power of the transferable load on node i at time t; is the active power absorbed by the transferable load on node i at time t; is the original demand for the active power of the transferable load at node i at time t; is the reactive power absorbed by the transferable load at node i at time t; is the original demand for reactive power of transferable load at node i at time t;

[0057] The active power and reactive power absorbed by the non-adjustable load at the node i at time t are given as constants and are respectively and express.

[0058] In combination with the first aspect, in some implementations of the first aspect, the method further includes: the operating characteristic constraints of the energy storage device in the power distribution system are as follows:

[0059]

[0060]

[0061]

[0062]

[0063]

[0064] Among them, I ES A set of node numbers of a power distribution system equipped with energy storage equipment; is the active power output by the energy storage device at node i at time t; is a binary variable that characterizes the fault status of the energy storage device at node i at time t; is a binary variable that characterizes the charging and discharging state of the energy storage device at node i at time t; is the upper limit of active power output by the energy storage device at node i; is the active power absorbed by the energy storage device at node i at time t; is the upper limit of active power absorbed by the energy storage device at node i; is the remaining power of the energy storage device at node i after the decision at time t, and the initial remaining power of the energy storage device at node i at time 0 Given as a constant; and are the discharge efficiency and charging efficiency of the energy storage device at node i respectively; Δt is the decision time step; and are the upper and lower limits of the power storage capacity of the energy storage device at node i respectively.

[0065] In combination with the first aspect, in some implementations of the first aspect, the method further includes: the pre-established distribution system source-grid-load-storage coordinated dispatch optimization model for post-disaster recovery scenarios is constructed by minimizing the economic dispatch cost optimization objective, and constructing the coupled operation constraints of the distribution system source-grid-load-storage, wherein the minimization of the economic dispatch cost optimization objective is as follows:

[0066]

[0067] in, and They are the regulation prices of main grid substation, distributed fossil fuel units, removable loads and transferable loads;

[0068] The coupled operation constraints of the distribution system source, grid, load and storage are as follows:

[0069]

[0070]

[0071] In a second aspect, in order to achieve the above-mentioned purpose, the present invention discloses a distribution system post-disaster recovery source-grid-load-storage coordinated dispatch optimization system, comprising:

[0072] A data acquisition module, used to acquire network topology constraint data of a power distribution system, wherein the network topology constraint of the power distribution system includes a virtual network topology constraint of the power distribution system, a geometric network topology constraint of the power distribution system, and an electrical network topology constraint of the power distribution system;

[0073] A data generation module, used to generate distribution system equipment operation characteristic constraint data according to the fault conditions of power supply equipment, load equipment and energy storage equipment caused by disasters, wherein the distribution system equipment operation characteristic constraint data includes operation characteristic constraints of power supply equipment, load equipment and energy storage equipment;

[0074] The collaborative dispatch optimization module is used to input the network topology constraint data of the distribution system and the distribution system equipment operation characteristic constraint data into a pre-established distribution system source-grid-load-storage collaborative dispatch optimization model for post-disaster recovery scenarios, and output the collaborative dispatch optimization results.

[0075] Beneficial effects of the present invention:

[0076] On the one hand, the present invention comprehensively considers the adjustable potential and constraint characteristics of the power grid topology, power supply equipment, load equipment and energy storage equipment in the distribution system, and fully mobilizes all power resources in the distribution system to promote the power restoration of important loads; on the other hand, the adopted distribution system topology control optimization model can adapt to various complex post-disaster scenarios and give the optimal scheduling plan under the corresponding scenarios, with stronger robustness. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0078] Figure 1 It is a schematic flow chart of the method of the present invention;

[0079] Figure 2 It is a schematic diagram of the workflow of the present invention;

[0080] Figure 3 A schematic diagram of the normal operating state of the test system used in the specific implementation mode of the present invention;

[0081] Figure 4 This is a schematic diagram of the operating status of a power distribution system in a test scenario of a specific embodiment of the present invention;

[0082] Figure 5 This is a schematic diagram of the operating status of the power distribution system under the second test scenario of the specific implementation method of the present invention;

[0083] Figure 6 This is a schematic diagram of the operating status of the power distribution system under the third test scenario of the specific implementation mode of the present invention;

[0084] Figure 7 This is a schematic diagram of the operating status of the power distribution system under the test scenario 4 of the specific implementation mode of the present invention;

[0085] Figure 8 It is a schematic diagram of the system structure of the present invention. DETAILED DESCRIPTION

[0086] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0087] Embodiment 1:

[0088] The following is an introduction to the relevant terms involved in the embodiments of the present application:

[0089] Distribution system: The section of the power system from the step-down distribution substation (high-voltage distribution substation) to the user end is called the distribution system. The distribution system is a power network system composed of a variety of distribution equipment (or components) and distribution facilities that transforms voltage and directly distributes electric energy to end users.

[0090] Source, grid, load and storage mainly consists of three parts: source, grid and load (storage):

[0091] 1. The source of “source, grid, load and storage” corresponds to energy storage on the power generation side.

[0092] Energy storage on the power generation side mainly refers to the common photovoltaic, wind power and hydropower storage, which mainly operates in cooperation with thermal power plants and power grids to adjust peak and frequency and gain profits. It can greatly reduce the local abandoned solar and wind rates.

[0093] 2. The "source, grid, load and storage" network corresponds to grid-side energy storage.

[0094] Grid-side energy storage can be directly used in electrical appliances such as computers, mobile phones, and refrigerators. The representative of grid-side energy storage is pumped storage. The grid can balance the electricity price by itself. Compared with the power generation side, the grid side does not need to strive for additional compensation mechanisms for energy storage, such as electricity price discounts and subsidies.

[0095] 3. The load (storage) of “source, grid, load and storage” corresponds to the energy storage on the user side.

[0096] Usually we classify household storage, industrial and commercial storage, and energy storage charging piles as the user side, and the main target is electricity users.

[0097] like Figure 1 As shown, a method for optimizing source-grid-load-storage coordinated scheduling for post-disaster recovery of a distribution system is provided, characterized in that the method comprises the following steps:

[0098] Acquire network topology constraint data of the power distribution system, wherein the network topology constraint of the power distribution system includes virtual network topology constraint of the power distribution system, geometric network topology constraint of the power distribution system and electrical network topology constraint of the power distribution system;

[0099] The process of obtaining the network topology constraints of the distribution system is as follows: receiving the connectivity constraints and radiation constraints that the network topology needs to satisfy when the distribution system operates normally, and generating the virtual network topology constraints of the distribution system according to the connectivity constraints and radiation constraints;

[0100] The connectivity constraints of the virtual topology of the distribution system are relaxed to generate the geometric network topology constraints of the distribution system. The electrical network topology constraints of the distribution system are generated by receiving the electrical constraints that the grid voltage, current and power in the distribution system need to satisfy. Thus, the virtual network topology constraints of the distribution system, the geometric network topology constraints of the distribution system and the electrical network topology constraints of the distribution system are integrated to generate the network topology constraints of the distribution system.

[0101] Furthermore, the connectivity constraint is constructed based on the virtual commodity flow model, wherein the formula of the connectivity constraint is as follows:

[0102]

[0103]

[0104]

[0105] Where i and j are node numbers in the power distribution system; I S is the collection of main grid substation nodes in the power distribution system; N is the set of nodes in the distribution system except the main grid substation nodes; t is the number of the decision moment; T is the total time steps of the decision; L is the set of lines in the distribution system, and each line is counted in L in the form of a two-dimensional vector composed of the node numbers at both ends, and the smaller number of the node numbers at both ends is the first dimension of the two-dimensional vector, and the larger number is the second dimension of the two-dimensional vector; f i,j,t is the virtual commodity flow from node i to node j on line (i, j) in the virtual network topology at time t; f j,i,t is the virtual commodity flow from node j to node i on line (j, i) in the virtual network topology at time t; d i,j,t is the on-off state variable of the virtual line (i, j) at time t, which is 1 when the virtual line (i, j) is connected and 0 when the virtual line (i, j) is disconnected; M is the linear relaxation coefficient, and its value can generally be set to the number of nodes in the distribution system;

[0106] The formula for the radiation constraint is as follows:

[0107]

[0108] In the formula, |I N | is the number of nodes in the distribution system except the main grid substation nodes.

[0109] Among them, the connectivity constraints of the virtual topology of the distribution system are relaxed, and the line failure of the distribution system after the disaster needs to be considered when generating the geometric network topology constraints of the distribution system. This is based on the principle of generating subgraphs. Among them, the constraints constructed by considering the line failure of the distribution system after the disaster are as follows:

[0110]

[0111]

[0112] In the formula, c i,j,t is the on-off state variable of the physical line (i, j) at time t; is the period of time during which the physical line (i, j) is disconnected due to a fault; is the period during which the physical line (i, j) is not faulty or has been repaired and can work normally; L U A collection of lines that are not equipped with switchgear;

[0113] The geometric network topology constraints of the power distribution system are as follows:

[0114]

[0115] The electrical network topology constraints of the distribution system are based on the DistFlow model and combined with the second-order cone relaxation technology and the large M relaxation technology to construct the electrical constraints that the grid voltage, current and power in the distribution system need to satisfy, thereby forming the electrical network topology constraints of the distribution system. Among them, the electrical constraints that the grid voltage, current and power in the distribution system need to satisfy are as follows:

[0116]

[0117]

[0118]

[0119]

[0120]

[0121] Where I is the node number set of the distribution system; p i,t is the net active power demand of the equipment connected to node i in the electrical network topology at time t; p i,j,tis the active power delivered from node i to node j by line (i, j) in the electrical network topology at time t; p j,i,t is the active power delivered from line (j,i) at node j to node i in the electrical network topology at time t; is the square of the current on line (j,i) in the electrical network topology at time t; r i,j is the resistance of line (i, j); q i,t is the net reactive power demand of the equipment connected to node i in the electrical network topology at time t; i,j,t is the reactive power delivered from node i to node j by line (i, j) in the electrical network topology at time t; q j,i,t is the reactive power delivered from line (j,i) at node j to node i in the electrical network topology at time t; i,j is the reactance of line (i, j); is the square of the voltage on node i in the electrical network topology at time t; is the square of the voltage on node j in the electrical network topology at time t; ||·||2 is the two-norm operator.

[0122] Generate distribution system equipment operation characteristic constraint data according to the fault conditions of power supply equipment, load equipment and energy storage equipment caused by the disaster, wherein the distribution system equipment operation characteristic constraint data includes the operation characteristic constraints of power supply equipment, load equipment and energy storage equipment;

[0123] The operating characteristic constraints of the distribution system equipment are constructed for the power supply equipment represented by the main grid substation, distributed fossil fuel units, and distributed renewable energy units in the distribution system, combined with the equipment failure caused by disasters. Among them, the operating characteristic constraints of the main grid substation are as follows:

[0124]

[0125]

[0126]

[0127]

[0128] in, is the active power output of the main grid substation at node i at time t; is a binary variable that represents the fault status of the main grid substation at node i at time t. It takes 1 when the main grid substation can output power normally, otherwise it takes 0; is the upper limit of active power that can be output by the main grid substation at node i; is the reactive power output by the main grid substation at node i at time t; is the upper limit of reactive power that can be output by the main grid substation at node i;

[0129] The operating characteristic constraints of the constructed distributed fossil fuel units are as follows:

[0130]

[0131]

[0132]

[0133]

[0134] Among them, I DG A set of node numbers for a distribution system equipped with distributed fossil fuel units; is the active power output of the distributed fossil fuel unit at node i at time t; is a binary variable that represents the fault state of the distributed fossil fuel unit at node i at time t. It takes 1 when the distributed fossil fuel unit can output electricity normally, otherwise it takes 0; is the upper limit of the active power that can be output by the distributed fossil fuel unit at node i; is the reactive power output of the distributed fossil fuel unit at node i at time t; is the upper limit of reactive power that can be output by the distributed fossil fuel unit at node i;

[0135] The operating characteristic constraints of the constructed distributed renewable energy units are as follows:

[0136]

[0137]

[0138] Among them, I RES A set of node numbers for a distribution system equipped with distributed renewable energy units; is the active power output of the distributed renewable energy unit at node i at time t; is a binary variable that represents the fault state of the distributed renewable energy unit at node i at time t. It takes 1 when the distributed renewable energy unit can output power normally, otherwise it takes 0; is the upper limit of active power that can be output by the distributed renewable energy unit at node i at time t.

[0139] In the distribution system, three different types of load devices, namely, removable loads, transferable loads and non-adjustable loads, are used to construct the operating characteristic constraints of the load devices in the distribution system. The constructed removable load operating characteristic constraints are as follows:

[0140]

[0141]

[0142] in, is the active power absorbed by the removable load on node i at time t; is the upper limit of active power absorbed by the removable load at node i at time t; is the reactive power absorbed by the removable load at node i at time t; is the upper limit of reactive power absorbed by the removable load at node i at time t;

[0143] The constructed transferable load operation characteristic constraints are as follows:

[0144]

[0145]

[0146]

[0147]

[0148] in, is the active power regulation of the transferable load on node i at time t; is the adjustable upper limit of the active power of the transferable load on node i at time t; is the active power absorbed by the transferable load on node i at time t; is the original demand for the active power of the transferable load at node i at time t; is the reactive power absorbed by the transferable load at node i at time t; is the original demand for reactive power of transferable load at node i at time t;

[0149] The active power and reactive power absorbed by the non-adjustable load at the node i at time t are given as constants and are respectively and express.

[0150] The operating characteristics of energy storage equipment in the distribution system are constrained as follows:

[0151]

[0152]

[0153]

[0154]

[0155]

[0156] Among them, I ES A set of node numbers of a power distribution system equipped with energy storage equipment; is the active power output by the energy storage device at node i at time t; is a binary variable that represents the fault status of the energy storage device at node i at time t. It takes 1 when the energy storage device can charge and discharge normally, otherwise it takes 0; is a binary variable that represents the charging and discharging state of the energy storage device at node i at time t. It takes 1 when the energy storage device is in the charging state and takes 0 when it is in the discharging state. is the upper limit of active power output by the energy storage device at node i; is the active power absorbed by the energy storage device at node i at time t; is the upper limit of active power absorbed by the energy storage device at node i; is the remaining power of the energy storage device at node i after the decision at time t, and the initial remaining power of the energy storage device at node i at time 0 Given as a constant; and are the discharge efficiency and charging efficiency of the energy storage device at node i respectively; Δt is the decision time step; and are the upper and lower limits of the power storage capacity of the energy storage device at node i respectively.

[0157] The network topology constraint data of the distribution system and the equipment operating characteristic constraint data of the distribution system are input into a pre-established distribution system source-grid-load-storage collaborative scheduling optimization model for post-disaster recovery scenarios, and the collaborative scheduling optimization results are output.

[0158] The pre-established distribution system source-grid-load-storage coordinated dispatch optimization model for post-disaster recovery scenarios is constructed by minimizing the economic dispatch cost optimization objective, and constructing the coupled operation constraints of the distribution system source-grid-load-storage, wherein the minimization of the economic dispatch cost optimization objective is as follows:

[0159]

[0160] in, and They are the regulation prices of the main grid substation, distributed fossil fuel units, removable loads and transferable loads respectively. The regulation costs of distributed renewable energy units and energy storage equipment are negligible.

[0161] The coupled operation constraints of the distribution system source, grid, load and storage are as follows:

[0162]

[0163]

[0164] Specifically, the present invention is further described below by way of embodiments:

[0165] This implementation method uses a dual substation coupled distribution system for testing, and its normal operating state is as follows: Figure 3 Among them, important load nodes are equipped with distributed power sources or distributed energy storage devices, and the non-adjustable load on the node is not 0; the non-adjustable load on the secondary load node is 0, so passive islands are allowed to form in extreme scenarios.

[0166] The test scenario is the same as Figure 4 As shown, the main grid substation at node 1 cannot supply power normally due to a fault. After optimization by the method proposed in the present invention, the load originally supplied by the main grid substation at node 1 is transferred to the main grid substation at node 18 through the interconnection line (10, 19), thereby ensuring sufficient power supply to half of the load nodes in the distribution system.

[0167] Test scenario 2 Figure 5 As shown, based on the test scenario one, a fault also occurred in line (14, 15). After optimization by the method proposed in the present invention, in addition to connecting the line (10, 19) in the test scenario one, the line (7, 17) was also connected, thereby ensuring sufficient power supply to the loads on nodes 15, 16, and 17.

[0168] Test scenario three Figure 6 As shown, based on the test scenario 1, the lines (15, 16), (6, 7), and (8, 9) also failed. After optimization by the method proposed in the present invention, in addition to connecting the line (10, 19) in the test scenario 1, the line (7, 17) and the line (9, 26) were also connected, thereby forming an island consisting of nodes 6, 7, 16, and 17. The loads on the island are all powered by the distributed power supply on node 16. Since the distributed power supply is small in size, the loads on the island are slightly removed or shifted.

[0169] Test scenario 4 Figure 7 As shown in the figure, based on the test scenario 1, the lines (7,8) and (8,9) also failed. In addition to connecting the lines (10,19) in the test scenario 1, the lines (9,26) were also connected. At this time, node 8 formed a passive island alone, and its load was completely removed or shifted. It is worth mentioning that the existing technology usually cannot properly handle such scenarios that are bound to form passive islands, and will mistakenly believe that there is no feasible scheduling solution in this scenario.

[0170] Embodiment 2: In the second aspect, as Figure 8 As shown, in order to achieve the above-mentioned purpose, the present invention discloses a distribution system post-disaster recovery source-grid-load-storage coordinated dispatch optimization system, comprising:

[0171] A data acquisition module, used to acquire network topology constraint data of a power distribution system, wherein the network topology constraint of the power distribution system includes a virtual network topology constraint of the power distribution system, a geometric network topology constraint of the power distribution system, and an electrical network topology constraint of the power distribution system;

[0172] A data generation module, used to generate distribution system equipment operation characteristic constraint data according to the fault conditions of power supply equipment, load equipment and energy storage equipment caused by disasters, wherein the distribution system equipment operation characteristic constraint data includes operation characteristic constraints of power supply equipment, load equipment and energy storage equipment;

[0173] The collaborative dispatch optimization module is used to input the network topology constraint data of the distribution system and the distribution system equipment operation characteristic constraint data into a pre-established distribution system source-grid-load-storage collaborative dispatch optimization model for post-disaster recovery scenarios, and output the collaborative dispatch optimization results.

[0174] Based on the same inventive concept, the present invention also provides a computer device, which includes: one or more processors, and a memory for storing one or more computer programs; the program includes program instructions, and the processor is used to execute the program instructions stored in the memory. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is used to implement one or more instructions, specifically for loading and executing one or more instructions in a computer storage medium to implement the above method.

[0175] It needs to be further explained that, based on the same inventive concept, the present invention also provides a computer storage medium, on which a computer program is stored, and the computer program is executed by a processor to execute the above method. The storage medium can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electrical, magnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0176] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0177] The above shows and describes the basic principles, main features and advantages of the present disclosure. Those skilled in the art should understand that the present disclosure is not limited by the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present disclosure. Without departing from the spirit and scope of the present disclosure, the present disclosure may have various changes and improvements, and these changes and improvements fall within the scope of the present disclosure to be protected.

Claims

1. A method for optimizing source-grid-load-storage coordinated dispatching for post-disaster recovery of a distribution system, characterized in that: The method comprises the following steps: Acquire network topology constraint data of the power distribution system, wherein the network topology constraint of the power distribution system includes virtual network topology constraint of the power distribution system, geometric network topology constraint of the power distribution system and electrical network topology constraint of the power distribution system; Generate distribution system equipment operation characteristic constraint data according to the fault conditions of power supply equipment, load equipment and energy storage equipment caused by the disaster, wherein the distribution system equipment operation characteristic constraint data includes the operation characteristic constraints of power supply equipment, load equipment and energy storage equipment; The distribution system equipment operation characteristic constraints are constructed for power supply equipment represented by main grid substations, distributed fossil fuel units, and distributed renewable energy units in the distribution system, combined with equipment failures caused by disasters. The main grid substation operation characteristic constraints are as follows: in, is the active power output of the main grid substation at node i at time t; is a binary variable representing the fault status of the main grid substation at node i at time t; is the upper limit of active power that can be output by the main grid substation at node i; is the reactive power output by the main grid substation at node i at time t; is the upper limit of reactive power that the main grid substation can output at node i; I S is the set of main grid substation nodes in the distribution system, T is the total time steps of decision making, and I is the set of node numbers in the distribution system; The operating characteristic constraints of the constructed distributed fossil fuel units are as follows: Among them, I DG A set of node numbers for a distribution system equipped with distributed fossil fuel generating units; is the active power output of the distributed fossil fuel unit at node i at time t; is a binary variable that characterizes the fault status of the distributed fossil fuel unit at node i at time t; is the upper limit of the active power that can be output by the distributed fossil fuel unit at node i; is the reactive power output of the distributed fossil fuel unit at node i at time t; is the upper limit of reactive power that can be output by the distributed fossil fuel unit at node i; The operating characteristic constraints of the constructed distributed renewable energy units are as follows: Among them, I RES A set of node numbers for a distribution system equipped with distributed renewable energy units; is the active power output of the distributed renewable energy unit at node i at time t; is a binary variable that characterizes the fault status of the distributed renewable energy unit at node i at time t; is the upper limit of the active power that can be output by the distributed renewable energy unit at node i at time t; In the power distribution system, three different types of load devices, namely, removable load, transferable load and non-adjustable load, are used to construct the operating characteristic constraints of the load devices in the power distribution system, wherein the constructed removable load operating characteristic constraints are as follows: in, is the active power absorbed by the removable load on node i at time t; is the upper limit of active power absorbed by the removable load at node i at time t; is the reactive power absorbed by the removable load at node i at time t; is the upper limit of reactive power absorbed by the removable load at node i at time t; The constructed transferable load operation characteristic constraints are as follows: in, is the active power regulation of the transferable load on node i at time t; is the adjustable upper limit of the active power of the transferable load on node i at time t; is the active power absorbed by the transferable load on node i at time t; is the original demand for the active power of the transferable load at node i at time t; is the reactive power absorbed by the transferable load at node i at time t; is the original demand for reactive power of transferable load at node i at time t; The active power and reactive power absorbed by the non-adjustable load at the node i at time t are given as constants and are respectively and express; The operating characteristics of the energy storage device in the power distribution system are constrained as follows: Among them, I ES A set of node numbers of a power distribution system equipped with energy storage equipment; is the active power output by the energy storage device at node i at time t; is a binary variable that characterizes the fault status of the energy storage device at node i at time t; is a binary variable that characterizes the charging and discharging state of the energy storage device at node i at time t; is the upper limit of active power output by the energy storage device at node i; is the active power absorbed by the energy storage device at node i at time t; is the upper limit of active power absorbed by the energy storage device at node i; is the remaining power of the energy storage device at node i after the decision at time t, and the initial remaining power of the energy storage device at node i at time 0 Given as a constant; and are the discharge efficiency and charging efficiency of the energy storage device at node i respectively; Δt is the decision time step; and are the upper and lower limits of the power storage capacity of the energy storage device at node i respectively; The network topology constraint data of the distribution system and the operating characteristic constraint data of the distribution system equipment are input into the pre-established distribution system source-grid-load-storage coordinated dispatch optimization model for post-disaster recovery scenarios, and the coordinated dispatch optimization result is output; The pre-established distribution system source-grid-load-storage coordinated dispatch optimization model for post-disaster recovery scenarios is constructed by minimizing the economic dispatch cost optimization objective, and constructing the coupled operation constraints of the distribution system source-grid-load-storage, wherein the minimization of the economic dispatch cost optimization objective is as follows: in, and They are the regulation prices of main grid substation, distributed fossil fuel units, removable loads and transferable loads; The coupled operation constraints of the distribution system source, grid, load and storage are as follows:

2. According to claim 1, a method for optimizing source-grid-load-storage coordinated dispatching for post-disaster recovery of a power distribution system, characterized in that: The acquisition process of the network topology constraint of the power distribution system is as follows: receiving the connectivity constraint and the radiation constraint that the network topology needs to satisfy when the power distribution system operates normally, and generating the virtual network topology constraint of the power distribution system according to the connectivity constraint and the radiation constraint; The connectivity constraints of the virtual topology of the distribution system are relaxed to generate the geometric network topology constraints of the distribution system. The electrical network topology constraints of the distribution system are generated by receiving the electrical constraints that the grid voltage, current and power in the distribution system need to satisfy. Thus, the virtual network topology constraints of the distribution system, the geometric network topology constraints of the distribution system and the electrical network topology constraints of the distribution system are integrated to generate the network topology constraints of the distribution system.

3. According to claim 2, a method for optimizing source-grid-load-storage coordinated dispatching for post-disaster recovery of a power distribution system, characterized in that: The connectivity constraint is constructed based on the virtual commodity flow model, wherein the formula of the connectivity constraint is as follows: Where i and j are node numbers in the power distribution system; I S is the collection of main grid substation nodes in the power distribution system; N is the set of nodes in the distribution system except the main grid substation nodes; t is the number of the decision moment; T is the total time steps of the decision; L is the set of lines in the distribution system, and each line is counted in L in the form of a two-dimensional vector composed of the node numbers at both ends, and the smaller number of the node numbers at both ends is the first dimension of the two-dimensional vector, and the larger number is the second dimension of the two-dimensional vector; f i,j,t is the virtual commodity flow from node i to node j on line (i, j) in the virtual network topology at time t; f j,i,t is the virtual commodity flow from node j to node i on line (j, i) in the virtual network topology at time t; d i,j,t is the on-off state variable of the virtual line (i, j) at time t; M is the linear relaxation coefficient; The formula for the radiation constraint is as follows: In the formula, |I N | is the number of nodes in the distribution system except the main grid substation nodes.

4. A method for optimizing source-grid-load-storage coordinated dispatching for post-disaster recovery of a power distribution system according to claim 3, characterized in that: The connectivity constraints of the virtual topology of the power distribution system are relaxed, and the line failure of the power distribution system after the disaster needs to be considered when generating the geometric network topology constraints of the power distribution system, and the process is based on the principle of generating subgraphs, wherein the constraints constructed by considering the line failure of the power distribution system after the disaster are as follows: In the formula, c i,j,t is the on-off state variable of the physical line (i, j) at time t; is the period of time during which the physical line (i, j) is disconnected due to a fault; is the period during which the physical line (i, j) is not faulty or has been repaired and can work normally; L U A collection of lines that are not equipped with switchgear; The geometric network topology constraints of the power distribution system are as follows:

5. The method for optimizing source-grid-load-storage coordinated dispatching for post-disaster recovery of a power distribution system according to claim 2, characterized in that: The electrical network topology constraints of the distribution system are based on the DistFlow model and combined with the second-order cone relaxation technology and the large M relaxation technology to construct the electrical constraints that the grid voltage, current and power in the distribution system need to satisfy, thereby forming the electrical network topology constraints of the distribution system. The electrical constraints that the grid voltage, current and power in the distribution system need to satisfy are as follows: Where I is the node number set of the distribution system; p i,t is the net active power demand of the equipment connected to node i in the electrical network topology at time t; p i,j,t is the active power delivered from node i to node j by line (i, j) in the electrical network topology at time t; p j,i,t is the active power delivered from line (j,i) at node j to node i in the electrical network topology at time t; is the square of the current on line (j,i) in the electrical network topology at time t; r i,j is the resistance of line (i, j); q i,t is the net reactive power demand of the equipment connected to node i in the electrical network topology at time t; i,j,t is the reactive power delivered from node i to node j by line (i, j) in the electrical network topology at time t; q j,i,t is the reactive power delivered from line (j,i) at node j to node i in the electrical network topology at time t; i,j is the reactance of line (i, j); is the square of the voltage on node i in the electrical network topology at time t; is the square of the voltage on node j in the electrical network topology at time t; ||·||2 is the two-norm operator, T is the total number of time steps for decision making; L is the set of lines in the distribution system.

6. A distribution system post-disaster recovery source-grid-load-storage coordinated dispatch optimization system, characterized in that: include: A data acquisition module, used to acquire network topology constraint data of a power distribution system, wherein the network topology constraint of the power distribution system includes a virtual network topology constraint of the power distribution system, a geometric network topology constraint of the power distribution system, and an electrical network topology constraint of the power distribution system; A data generation module, used to generate distribution system equipment operation characteristic constraint data according to the fault conditions of power supply equipment, load equipment and energy storage equipment caused by disasters, wherein the distribution system equipment operation characteristic constraint data includes operation characteristic constraints of power supply equipment, load equipment and energy storage equipment; The collaborative scheduling optimization module is used to input the network topology constraint data of the distribution system and the distribution system equipment operation characteristic constraint data into a pre-established distribution system source-grid-load-storage collaborative scheduling optimization model for post-disaster recovery scenarios, and output the collaborative scheduling optimization results.

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