Active power distribution network two-stage island division method and system considering flexible resource support

Abstract

The invention discloses an active power distribution network two-stage island division method and system considering flexible resource support. The method comprises the following steps: establishing a first resource allocation model considering energy storage and controllable load, the first resource allocation model comprises energy storage battery charging and discharging upper and lower limit constraints, an energy storage battery degradation cost model, a controllable load model and a controllable load related user protocol; obtaining parameter data of a target power distribution system, wherein the parameter data comprises a line parameter, a load level, a load level, a network topology connection relationship, a system operation voltage level and branch current limitation, a system fault position, a reference voltage and a reference power initial value; and according to the parameter data, establishing a mathematical model for two-stage island power supply recovery based on a first resource allocation model. The method for solving the island is simple and convenient, the island recovery amount can achieve the optimal recovery effect, meanwhile, the search time is greatly shortened, the solving efficiency is higher, and the rapid power supply recovery capacity of the power distribution network is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power supply restoration of distribution networks, and in particular to a two-stage islanding division method and system for active distribution networks taking flexible resource support into account. Background Art

[0002] With the high proportion of distributed generators (DG), the access of a large number of distributed energy storage and large-scale electricity substitution, the structural form and operation mode of the existing distribution network have been greatly affected.

[0003] At present, renewable energy is developing rapidly, and the capacity of some regions to accept a high proportion of DG is close to the limit. The distribution network has problems such as voltage over-limit, power impact, grid peak-shaving difficulties and wind and solar absorption. The development of a high proportion of distributed power sources has put forward higher requirements on the carrying capacity of the distribution network. At the same time, due to its volatility, intermittent and anti-peak characteristics, it has a huge impact on the structural form and operation mode of the traditional distribution network. In the context of frequent extreme disasters such as rain, snow, freezing, typhoons, and floods, the limitations of the "passivity" of the traditional fault recovery scheme of the distribution network have been further magnified, resulting in equipment overload, insufficient power supply capacity, unreliable power quality, and low power recovery level after faults in the distribution network, which has greatly affected the reliability and safety of the distribution network.

[0004] At the same time, the scale access of distributed power sources and energy storage also provides a feasible technical approach to use islands to ensure the continuity of local power supply when a distribution network fails. However, due to the volatility, intermittency and anti-peaking characteristics of renewable energy, the distribution network's power supply reserve capacity is unstable, and problems such as supply and demand imbalance and power shock will occur during island operation. In addition, due to the characteristics of source-load time sequence changes, the traditional static island recovery plan is no longer applicable, and the island operation plan should change dynamically over time. Summary of the invention

[0005] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0006] In view of the above existing problems, the present invention is proposed.

[0007] Therefore, the present invention provides a two-stage island partitioning method and system for an active distribution network taking into account flexible resource support, which can solve the problems mentioned in the background technology.

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

[0009] In a first aspect, the present invention provides a two-stage islanding method for an active distribution network taking into account flexible resource support, comprising:

[0010] Establishing a first resource allocation model that considers energy storage and controllable loads, wherein the first resource allocation model includes upper and lower limit constraints on energy storage battery charging and discharging, an energy storage battery degradation cost model, a controllable load model, and a controllable load-related user agreement;

[0011] Acquire parameter data of the target power distribution system, the parameter data including line parameters, load level, load grade, network topology connection relationship, system operating voltage level and branch current limit, system fault location, and reference voltage and reference power initial values;

[0012] According to the parameter data, a mathematical model of two-stage island power supply restoration based on the first resource allocation model is established.

[0013] As a preferred solution of the two-stage island partitioning method of the active distribution network considering flexible resource support described in the present invention, the mathematical model of the two-stage island power supply restoration based on the first resource allocation model includes: a prevention stage and an emergency stage;

[0014] In the prevention stage, island division is performed according to the predicted source load data, which is divided into a single-period island division model and a multi-period continuous island division model;

[0015] The single-period island division is performed by taking the maximum single-period equivalent recovery amount as the objective function to obtain a single-period discrete island set.

[0016] As a preferred solution of the two-stage islanding method of the active distribution network considering flexible resource support described in the present invention, the multi-period continuous islanding model includes:

[0017] The multi-period continuous islanding division participates in islanding optimization through energy storage and controllable loads, takes advantage of the electricity transfer characteristics of flexible resources in the previous and next periods, establishes a multi-period islanding division model with the maximum overall load recovery and the minimum battery degradation cost and controllable load compensation cost, and utilizes flexible resources to connect discrete islands in series to achieve multi-period continuous islanding division.

[0018] As a preferred scheme of the two-stage islanding division method of the active distribution network taking into account the support of flexible resources described in the present invention, the emergency stage includes: dynamically adjusting the multi-period continuous islanding scheme based on the actual wind and solar data with the single-period islanding division objective function as the target to obtain a single-period dynamic islanding scheme.

[0019] As a preferred scheme of the two-stage island partitioning method of the active distribution network taking into account flexible resource support described in the present invention, the mathematical model of the two-stage island power supply restoration based on the first resource allocation model also includes: power constraints within the island, branch capacity constraints, system operation constraints, power balance constraints, network topology constraints and radial topology constraints.

[0020] As a preferred solution of the two-stage islanding division method of the active distribution network considering flexible resource support described in the present invention, the islanding division is performed with the maximum equivalent recovery amount in a single period as the objective function to obtain a discrete island set in a single period, including:

[0021]

[0022] Where L is the number of load nodes in the island solution after the fault; x i,t is a 0-1 state variable, indicating the power supply status of node i, x i,t =1 means that the load is restored to power supply at time t, x i,t =0 means that the load has not restored power supply at time t; ω i represents the load weight of node i; P i,t is the active power of node i at time t.

[0023] As a preferred solution of the two-stage islanding division method of the active distribution network considering flexible resource support described in the present invention, the establishment of a multi-period islanding division model with the maximum overall load recovery amount and the minimum battery degradation cost and controllable load compensation cost includes:

[0024]

[0025] Where T represents the number of fault recovery time periods; ΔP load,t represents the equivalent recovery amount increased compared to the island in a single period; λ1, λ2 and λ3 represent the weight values ​​in the objective function, and λ1, λ2 and λ3 are taken as 0.6, 0.2 and 0.2 respectively; C B,t represents the battery degradation cost; C L,t Represents the controllable load compensation cost, which is determined based on the demand response contract.

[0026] In a second aspect, the present invention provides a two-stage island partitioning system for an active distribution network taking into account flexible resource support, comprising:

[0027] A resource allocation model establishment module, used to establish a first resource allocation model that takes into account energy storage and controllable loads, wherein the first resource allocation model includes upper and lower limit constraints on energy storage battery charging and discharging, an energy storage battery degradation cost model, a controllable load model, and a controllable load-related user agreement;

[0028] A data acquisition module is used to acquire parameter data of the target power distribution system, wherein the parameter data includes line parameters, load level, load grade, network topology connection relationship, system operating voltage level and branch current limit, system fault location, and reference voltage and reference power initial values;

[0029] The isolated island partition model establishment module is used to establish a two-stage isolated island power supply restoration mathematical model based on the first resource allocation model according to the parameter data.

[0030] In a third aspect, the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned method when executing the computer program.

[0031] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the method described above when executed by a processor.

[0032] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention proposes a two-stage island partitioning method and system for active distribution networks taking into account flexible resource support, establishes a first resource allocation model that takes into account energy storage and controllable loads, and the first resource allocation model includes upper and lower limit constraints on energy storage battery charging and discharging, energy storage battery degradation cost model, controllable load model, and controllable load-related user agreements; obtains parameter data of the target distribution system, and the parameter data includes line parameters, load levels, load grades, network topology connection relationships, system operating voltage levels and branch current limits, system fault locations, and reference voltage and reference power initial values; according to the parameter data, establishes a mathematical model for two-stage island power supply recovery based on the first resource allocation model. The present application is based on solving the problem of power supply recovery caused by distribution network failures, fully considering the impact of uncertainty in distributed power sources and the problems of power shock and voltage over-limit that may occur during the establishment of islands, and establishes a two-stage power supply recovery model for distribution networks based on islands. The Levy snake optimization algorithm is used to solve the problem and obtain a power supply recovery plan. The method for solving the island problem in the present invention is simple and convenient, and the island recovery capacity can achieve the optimal recovery effect. At the same time, the search time is greatly shortened, the solution efficiency is higher, and the rapid power supply recovery capability of the distribution network is improved. In addition, the two-stage island division method proposed in the present invention further reduces the impact of source-load uncertainty on the recovery plan, and avoids power shock and voltage over-limit during the operation of the island, thereby improving the safety of establishing the island after the disaster and improving the elasticity of the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor.

[0034] Figure 1 A method flow chart of a two-stage islanding method and system for active distribution network taking into account flexible resource support provided by one embodiment of the present invention;

[0035] Figure 2 A schematic diagram of a distribution network prevention-emergency dispatch framework of a two-stage islanding division method and system for an active distribution network taking into account flexible resource support provided by an embodiment of the present invention;

[0036] Figure 3 A schematic diagram of a distribution network preventive-emergency two-stage dynamic island partitioning strategy for a two-stage active distribution network island partitioning method and system taking into account flexible resource support provided by an embodiment of the present invention;

[0037] Figure 4 A flowchart of a two-stage island partitioning method and system for active distribution network taking into account flexible resource support and using Levy snake optimization algorithm for island partitioning provided by an embodiment of the present invention;

[0038] Figure 5 A two-stage island partitioning method and system for active distribution network taking into account flexible resource support provided by one embodiment of the present invention;

[0039] Figure 6 An improved IEEE33 node topology diagram of an example of a two-stage islanding method and system for active distribution network considering flexible resource support provided by an embodiment of the present invention;

[0040] Figure 7 A schematic diagram of a multi-period continuous islanding solution in the prevention phase of a two-stage islanding division method and system for an active distribution network taking into account flexible resource support provided by an embodiment of the present invention;

[0041] Figure 8 An internal structural diagram of a computer device of a two-stage islanding method and system for an active distribution network taking into account flexible resource support provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0042] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0043] Example 1

[0044] Reference Figure 1-Figure 8 , which is the first embodiment of the present invention, and provides a two-stage islanding method and system for active distribution network considering flexible resource support, including:

[0045] Before describing the embodiments of the present application in detail, some related concepts are first explained for the sake of clarity.

[0046] Island: "Island" means that when a main power grid fails, part of the distribution network is disconnected from the main grid and relies on its own internal distributed power generation devices (such as solar energy, wind power generation, etc.) to continue to supply power to part of the load, forming an independently operated small power grid system.

[0047] Predicted source and load data: "Predicted source and load data" refers to the data that estimates the generation capacity of distributed power sources (sources) and the demand for power load (load) in a certain period of time in the future. This prediction is based on historical data, weather forecasts and other factors to estimate future power generation and power consumption in order to plan the operation mode of the power grid in advance.

[0048] Single-period discrete island set: "Single-period discrete island set" means that in a specific time period, based on the predicted source and load data at that time, the part of the power grid that can operate independently is divided into small systems (i.e., islands) that can maintain their own power supply. These divisions are independent in time, that is, each period has its corresponding island division results.

[0049] Multi-period continuous islanding: "Multi-period continuous islanding" goes a step further. It not only considers the situation in a single period, but also considers the changes in the power generation and load of distributed power sources over time, and connects the islanding results of multiple periods in series to form a multi-period continuous islanding scheme. The goal of this scheme is to minimize the negative impact of source-load uncertainty, ensure safe and effective power restoration in different time periods, and take into account the energy transfer characteristics of energy storage devices and the management of controllable loads, in order to achieve the best power restoration effect throughout the entire period.

[0050] In related technologies, there is a common practice of simply matching the power generation capacity of distributed power sources with load demand, but this method often ignores the uncertainty of distributed power sources and loads, as well as the potential of energy storage devices and controllable loads. In addition, when dealing with island division, traditional methods also fail to fully consider the power impact and voltage limit problems during the island establishment process, resulting in poor power supply restoration effects and may even cause more serious power grid failures.

[0051] The present application provides a method that can effectively solve the above-mentioned problems. Next, multiple embodiments will be combined to explain in detail how to implement the two-stage island division method of the active distribution network taking into account the support of flexible resources;

[0052] Figure 1 A method flow chart of a two-stage islanding method and system for active distribution network considering flexible resource support is shown, including:

[0053] S101, establishing a first resource allocation model considering energy storage and controllable load, wherein the first resource allocation model includes upper and lower limit constraints of energy storage battery charging and discharging, an energy storage battery degradation cost model, a controllable load model, and a controllable load-related user agreement;

[0054] It should be noted that the two-stage island partitioning framework is as follows Figure 3 As shown. In the prevention stage, the possible location and duration of the fault are predicted. Before the fault occurs, the single-period islanding solution is solved according to the source-load prediction data and the priority of important loads. Then, flexible resources are considered to design a multi-period continuous islanding solution and a control strategy for energy storage and controllable loads to provide sufficient solution execution time for subsequent faults. In the emergency control stage, the designed energy storage charging and discharging and controllable load strategies are executed, and the single-period islanding objective function is dynamically adjusted every two hours based on the actual wind and solar output data to avoid power shocks and voltage over-limit problems, and the single-period dynamic adjustment solution is solved to achieve stable operation of the island.

[0055] In the embodiment of the present application, the energy storage battery charging and discharging model is designed as follows:

[0056] SoC (t) =SoC (t-1) -ΔP ess,t / E

[0057] Where E is the rated capacity of the battery; is the charge and discharge amount in time period t, ranging from Get the value.

[0058] If energy storage charging is required during time period t, the upper limit of charging is:

[0059]

[0060] If energy storage discharge is required during time period t, the upper limit of discharge is:

[0061]

[0062] in, Δ S t and SoC (t-1) The absolute value subtracted from the upper and lower limits of SoC respectively; is the single charge and discharge rated power; η in , η out is the charging efficiency and discharging efficiency.

[0063] In the embodiment of the present application, the energy storage battery degradation cost model is expressed as:

[0064] Specifically, the relationship between battery cycle life and DoD is shown in the following formula:

[0065]

[0066] Among them, β0, β1, and β2 represent curve fitting coefficients, which are determined by the battery type and experimental data provided by the manufacturer.

[0067] It should be noted that when energy storage performs a full cycle to a specific DoD, its cost is the battery capital divided by the cycle life corresponding to the DoD. When DoD = 1-SoC, the degradation cost of one cycle can be expressed as:

[0068]

[0069] Among them, C cap For the battery capital cost, two assumptions must be made in order to calculate the battery degradation cost.

[0070] First, it is assumed that discharge and charge operations for a certain DoD affect battery degradation uniformly until the maximum allowed cycles for that DoD are reached.

[0071] Second, the effect of charge-discharge cycling on degradation is independent of the previous cycles.

[0072] In the embodiment of the present application, the degradation cost function of the battery is as follows:

[0073]

[0074] Among them, C B,t Represents the battery degradation cost.

[0075] In the embodiment of the present application, the controllable load model includes:

[0076] a. Load that can be reduced. For this type of load, the maximum value of the power that can be reduced by load i within time period t can be expressed as.

[0077]

[0078] Among them, is a 0-1 state table, and takes 1 when the contract constraint is met. and represent the reduction factor and rated power of load i respectively.

[0079] b. Transposable load, the transposable power of load i in time period t is expressed as:

[0080]

[0081] Among them, is the set of time periods for the removal of load i; is the translation coefficient of load i; and is a 0-1 state variable.

[0082] In an optional embodiment, the specific data in Table 1 and Table 2 may be used for data determination;

[0083] Table 1 Controllable load user agreement

[0084]

[0085] Table 2 Basic information of energy storage battery

[0086] Energy storage number Location <![CDATA[β0]]> <![CDATA[β1]]> <![CDATA[β2]]> <![CDATA[C cap (Yuan)]]> 1、2 7、18 4901 1.98 0.016 6×105 3、4 21、31 3832 0.68 1.64 5×105

[0087] It should be noted that by comprehensively considering the resource allocation of energy storage and controllable loads, the potential of the load can be evaluated more accurately, so that these resources can be fully utilized in the process of island division and the effect of power supply restoration can be improved. Secondly, this step establishes detailed upper and lower limit constraints on energy storage battery charging and discharging, degradation cost models, and controllable load models. These models can more comprehensively reflect the complex situations in actual power grid operation, such as power shocks and voltage over-limit problems. Through the constraints and optimization of these models, these problems can be effectively avoided in the process of island division and the risk of power grid failure can be reduced. In addition, by introducing user agreements and specific data, the reduction and translation of loads can be controlled more accurately to ensure that the user's electricity demand is met during the process of island division, while reducing the cost of power grid operation.

[0088] S102, obtaining parameter data of the target power distribution system, wherein the parameter data includes line parameters, load level, load grade, network topology connection relationship, system operating voltage level and branch current limit, system fault location, and initial values ​​of reference voltage and reference power;

[0089] It should be noted that by comprehensively collecting various parameter data of the target distribution system, we can more accurately understand the actual operating status of the system and provide a solid data foundation for the subsequent island division. These data cover key information such as the physical characteristics of the line, the distribution and level of the load, the complexity of the network structure, and the voltage and current limits during system operation. At the same time, clarifying the specific location of the system fault will help avoid the fault area when dividing the island and ensure stable and reliable power supply within the island. In addition, setting the initial values ​​of the reference voltage and reference power will help unify the dimensions in the subsequent calculation process and improve the accuracy and comparability of the calculation results.

[0090] S103: Establishing a two-stage island power supply restoration mathematical model based on the first resource allocation model according to the parameter data.

[0091] In the embodiment of the present application, the mathematical model of the two-stage island power supply restoration based on the first resource allocation model includes: a prevention stage and an emergency stage;

[0092] In the prevention stage, island division is performed according to the predicted source load data, which is divided into a single-period island division model and a multi-period continuous island division model;

[0093] The single-period island division is performed by taking the maximum single-period equivalent recovery amount as the objective function to obtain a single-period discrete island set.

[0094] In an embodiment of the present application, the multi-period continuous island division model includes:

[0095] The multi-period continuous islanding division participates in islanding optimization through energy storage and controllable loads, takes advantage of the electricity transfer characteristics of flexible resources in the previous and next periods, establishes a multi-period islanding division model with the maximum overall load recovery and the minimum battery degradation cost and controllable load compensation cost, and utilizes flexible resources to connect discrete islands in series to achieve multi-period continuous islanding division.

[0096] In the embodiment of the present application, the island division is performed with the maximum equivalent recovery amount in a single period as the objective function to obtain a discrete island set in a single period, including:

[0097]

[0098] Where L is the number of load nodes in the island solution after the fault; x i,t is a 0-1 state variable, indicating the power supply status of node i, x i,t =1 means that the load is restored to power supply at time t, x i,t =0 means that the load has not restored power supply at time t; ω i represents the load weight of node i; P i,t is the active power of node i at time t.

[0099] In the embodiment of the present application, the establishment of a multi-period island partitioning model with the maximum overall load recovery amount and the minimum battery degradation cost and controllable load compensation cost includes:

[0100]

[0101] Where T represents the number of fault recovery time periods; ΔP load,t represents the equivalent recovery amount increased compared to the island in a single period; λ1, λ2 and λ3 represent the weight values ​​in the objective function, and λ1, λ2 and λ3 are taken as 0.6, 0.2 and 0.2 respectively; C B,t represents the battery degradation cost; C L,t Represents the controllable load compensation cost, which is determined based on the demand response contract.

[0102] In an embodiment of the present application, the emergency stage includes: dynamically adjusting the multi-period continuous islanding scheme based on actual wind and solar data with a single-period islanding division objective function as a target to obtain a single-period dynamic islanding scheme.

[0103] The mathematical model of the two-stage island power supply restoration based on the first resource allocation model also includes: power constraints within the island, branch capacity constraints, system operation constraints, power balance constraints, network topology constraints and radial topology constraints.

[0104] Specifically, the power constraint within the island is expressed as:

[0105]

[0106] Where n is the number of DGs in the distribution network; L is the number of nodes in the island; P y,t is the output of the nth DG at time t; P i,t is the active power of node i in the island at time t; P loss,t is the network loss within the island at time t.

[0107] Furthermore, the branch capacity constraint is expressed as:

[0108]

[0109] Among them, S j,t , is the power and transmission upper limit of branch j.

[0110] Furthermore, the system operates under the following constraints:

[0111] a. The node voltage constraint is expressed as:

[0112]

[0113] Among them, Ui,t represents the voltage of node i at time t; The upper and lower limits of the voltage amplitude.

[0114] b. The node current constraint is expressed as:

[0115]

[0116] Among them, I ij,t represents the actual current flowing through branch ij at time t; The upper and lower limits of the current amplitude.

[0117] Furthermore, the power balance constraint is expressed as:

[0118]

[0119] Among them, P i , Q i are the active power and reactive power injected into node i respectively; L is the total number of nodes; U i and U j are the voltage amplitudes of nodes i and j respectively; G ij , B ij , δ ij are the conductance, susceptance and voltage phase difference between nodes i and j respectively.

[0120] Furthermore, the network topology constraint is expressed as:

[0121] g t ∈G

[0122] Among them, g t represents the topological structure of the island at time t; G represents the set of network topological structures that satisfy connectivity.

[0123] Furthermore, the radial topology constraint is expressed as:

[0124] The radial topology of the distribution network is represented according to the spanning tree model in graph theory.

[0125]

[0126] Where L is the set of branches in the distribution network; Ω s represents the node set of distributed power sources; represents the state of branch ij at time t, Indicates that the branch is in closed state. Indicates that the line is disconnected; φ ij,t Represents the parent-child connection relationship between the nodes at both ends of branch ij at time t. When node j is the parent node of node i at time t, φ ij,t =1, otherwise φ ij,t =0.

[0127] In summary, the present application is based on solving the problem of power supply restoration caused by distribution network failures, fully considering the impact of uncertainty of distributed power sources and the problems of power shock and voltage over-limit that may occur during the establishment of isolated islands, and establishing a two-stage power supply restoration model for distribution networks based on isolated islands. The Levy snake optimization algorithm is used for solving the problem and obtaining a power supply restoration plan. The method for solving isolated islands in the present invention is simple and convenient, and the amount of island restoration can achieve the optimal restoration effect. At the same time, the search time is greatly shortened, the solution efficiency is higher, and the rapid power supply restoration capability of the distribution network is improved. In addition, the two-stage island division method proposed in the present application further reduces the impact of source-load uncertainty on the restoration plan, while avoiding power shock and voltage over-limit during the operation of isolated islands, improving the safety of establishing isolated islands after disasters, and improving the resilience of distribution networks.

[0128] This embodiment also provides a two-stage islanding system for active distribution network taking into account flexible resource support, including:

[0129] A resource allocation model establishment module, used to establish a first resource allocation model that takes into account energy storage and controllable loads, wherein the first resource allocation model includes upper and lower limit constraints on energy storage battery charging and discharging, an energy storage battery degradation cost model, a controllable load model, and a controllable load-related user agreement;

[0130] A data acquisition module is used to acquire parameter data of the target power distribution system, wherein the parameter data includes line parameters, load level, load grade, network topology connection relationship, system operating voltage level and branch current limit, system fault location, and reference voltage and reference power initial values;

[0131] The isolated island partition model establishment module is used to establish a two-stage isolated island power supply restoration mathematical model based on the first resource allocation model according to the parameter data.

[0132] The above-mentioned unit modules may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to the above-mentioned modules.

[0133] This embodiment also provides a computer device, which may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 8As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a two-stage island division method for an active distribution network taking into account flexible resource support is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0134] This embodiment further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0135] Establishing a first resource allocation model that considers energy storage and controllable loads, wherein the first resource allocation model includes upper and lower limit constraints on energy storage battery charging and discharging, an energy storage battery degradation cost model, a controllable load model, and a controllable load-related user agreement;

[0136] Acquire parameter data of the target power distribution system, the parameter data including line parameters, load level, load grade, network topology connection relationship, system operating voltage level and branch current limit, system fault location, and reference voltage and reference power initial values;

[0137] According to the parameter data, a mathematical model of two-stage island power supply restoration based on the first resource allocation model is established.

[0138] Example 2

[0139] Reference Figure 2-Figure 7 , which is an embodiment of the present invention, provides a two-stage islanding method and system for active distribution network considering flexible resource support;

[0140] Figure 2The invention discloses a distribution network prevention-emergency dispatch framework. The invention discloses that when a fault occurs, the distribution network executes the following three steps to achieve the safe establishment of an island. First, through the monitoring and data acquisition system (SCADA), feeder terminal unit (FTU) and other systems, the parameter information required for decision-making is collected and sent to the control center. This information includes the parameters of the distributed power unit, load weight, historical data, and the charge state of the energy storage system.

[0141] Secondly, the control center conducts rolling forecasts based on the historical data of distributed power sources and loads to provide data support for island division. The constraints considered when dividing islands include single-period island constraints such as power processing, backup capacity, load demand, grid topology and flow constraints, as well as energy storage capacity constraints and multi-period island constraints of controllable loads.

[0142] Finally, the control center will send instructions to the communication equipment of each switch to implement the island recovery plan. The dispatch plan in the prevention phase includes source-load forecast data, power backup capacity, load recovery priority, energy storage charging and discharging strategy, controllable load change strategy, and multi-period continuous island division plan; the emergency phase control instructions include wind and solar actual output data and single-period dynamic island adjustment plan.

[0143] Figure 3 This is a two-stage dynamic islanding division strategy for the distribution network of the present invention, which is prevention and emergency. In the prevention stage, according to the predicted location and duration of the fault, the initial islanding plan is solved according to the source-load prediction data and the priority of important loads before the disaster occurs. Then, flexible resources are considered to design a multi-period continuous islanding plan and a control strategy for energy storage and controllable loads, so as to provide sufficient plan execution time for subsequent faults. In the emergency control stage, the designed energy storage charging and discharging and controllable load strategies are executed, and the single-period islanding division objective function is used as the target to dynamically adjust the actual wind and solar output data every two hours to avoid problems such as power shocks and voltage over-limits, and solve the single-period dynamic adjustment plan to achieve stable operation of the island.

[0144] Figure 4 This is a flowchart of the invention using the Levy Snake optimization algorithm to divide the island. There are many nodes in the distribution network, which are used as optimization variables to search for the island range to restore the power outage area. In this stage, the Levy Snake optimization algorithm is used to search for the island node set in each time period. Taking a single DG as an example, the steps are as follows:

[0145] (1) 100 initialization settings, according to the problem setting dimension, upper and lower limits, snake population size, maximum number of iterations, current number of iterations, evaluation fitness function, node information, distribution network topology, DG access location, DG active power output and other data, the initial position of the population is the DG access location as the root node;

[0146] (2) 101 The population was divided equally into female and male groups;

[0147] (3) 102 evaluates the current population according to the fitness function and calculates the fitness of each individual;

[0148] (4) 103 determines whether the fitness has changed significantly for five consecutive times. If so, it goes to 104 to calculate the parameters according to the Levy flight strategy and replace the parameters of the stage in SO (105, 106); otherwise, it goes to 107 and 108 to find the best individuals in the female group and the male group respectively, according to the defined temperature and food quantity;

[0149] (5) Choose to enter the exploration phase or development phase according to the temperature and the amount of food. In the exploration phase, the snake enters the random foraging process and finds a location far away from the current location, that is, randomly searches for nodes to enter the island node set; in the development phase, the snake expands the current island range and enters the foraging mode, fighting mode or mating mode according to the temperature and random numbers to find new nodes to enter the set (109, 110, 111);

[0150] (6) Perform constraint check 116 on the snake individual with updated position. If the constraint is not satisfied, proceed to step (5);

[0151] (7) After the constraints are met, the population positions of the male and female groups are updated 117;

[0152] (8) After reaching the maximum number of iterations, the best individual, i.e., the best island range 118, 119, is output.

[0153] Figure 5 200 and 201 are the steps of island fusion in the present invention. If the number of distributed power sources is greater than 1, the island node set divided by the node where a single DG is located as the root node is obtained in sequence, and then it is determined whether island fusion processing is required, that is, 200 and 201. The process is as follows Figure 5 As shown, the steps are:

[0154] (1) If there is an overlapping island 202, the load nodes in the overlapping part of the island are merged and shrunk into a point to form a new topological structure 204, and the smallest node in the island node set is used as the access position of the new DG.

[0155] (2) The new DG position is used as the root node, and the sum of the active power of the overlapping nodes and the amount of power abandoned on the island is used as the power radius 205. The depth-first search traversal method and the exhaustive method 206 are used to search for the largest power supply area of ​​the island 207, list all possible combinations of restoration nodes outside the island, and screen out the restoration plan with the largest equivalent restoration amount 208.

[0156] (3) Restore the node topology structure and the newly searched island node set, and update the island range 209.

[0157] (4) When all overlapping islands are merged, check whether there are still connected islands. If so, merge the islands with connected edges until there is no overlap between all island node sets. If not, end the island fusion.

[0158] Figure 6 The improved IEEE33 node topology diagram used in the examples of the present invention.

[0159] Example analysis:

[0160] Figure 7 This is the multi-period continuous islanding solution in the prevention stage of the present invention. According to the prediction, a three-phase short circuit fault will occur in branch 1-2 at 10 o'clock, resulting in a complete power outage in the downstream area of ​​the feeder. The fault will last for 6 hours. The prevention solution is solved in a cycle of every 2 hours.

[0161] The island division is performed according to the above steps.

[0162] (1) Prevention

[0163] First, the source-load prediction data is applied to the island division to restore power to the power-lost load, and the island schemes in the prevention stage are divided. The Levy snake optimization algorithm described in Chapter 3 is used to solve the island schemes for each single period through the source-load data. As shown in Table 3, the islands divided by the three schemes can restore the power-lost load of 3450.13kW, accounting for 32.66% of the total power-lost load to be restored.

[0164] Table 3 Comparison of single-period island division results

[0165]

[0166] The results of single-period island division show that the effect of island recovery is not ideal at this time, and the ability to prioritize the restoration of important loads is weak. At this time, the reserve capacity is adjusted to optimize the island range, and the timing characteristics of energy storage and load are considered. The discrete islands in each period are connected in series to achieve multi-period continuous islands. The order of power adjustment is: energy storage first, then load.

[0167] Secondly, the multi-period continuous islanding scheme is as follows Figure 7 The specific data are shown in Table 4:

[0168] Table 4 Effect of multi-period continuous island recovery solution

[0169]

[0170]

[0171] (2) Emergency stage

[0172] Keep the energy storage charging and discharging strategy and the controllable load change strategy unchanged, adjust the island according to the actual wind and solar power output, and realize dynamic island adjustment in a single period.

[0173] The dynamic adjustment results in the emergency stage are shown in Table 5:

[0174] Table 5 Dynamic adjustment results in the emergency stage

[0175]

[0176] Due to the characteristics of the volatility of distributed power output, the system's adjustable spare capacity is highly random, resulting in unstable load recovery during faults. Table 5 shows that in the emergency fault stage, the reserve plan is dynamically adjusted based on the actual data of wind and solar output. After adjustment, the load recovery in the first period is reduced by 150kW, and the load recovery in the third period is increased by 133kW. Minor adjustments are made to adapt to the actual situation. Dynamic islands can flexibly adjust the boundaries of islands according to the dynamic changes in the output of distributed power sources, so that limited resources can be allocated to more important loads as much as possible. In contrast, the distribution network in fixed island mode can only allocate resources within the predetermined island range.

[0177] The two-stage islanding method for active distribution network taking into account flexible resource support provided by the present invention has the following effects:

[0178] Prevention stage: In view of the problem that the solution efficiency is low and the global optimal cannot be guaranteed during the island division process, it is proposed to use the improved Levy snake optimization algorithm to solve the static island solution for each single period. Compared with the traditional heuristic algorithm and exhaustive method, the island recovery capacity of the method proposed in this paper can achieve the optimal recovery effect, and the search time is greatly shortened, and the solution efficiency is higher, which verifies the correctness of the method proposed in this invention and improves the power supply recovery capability of the distribution network;

[0179] In view of the fact that the single-period plan divided by the above-mentioned island division model is a static island, the flexible resource optimization island of energy storage and controllable load is considered, and the single-period islands are connected in series to realize multi-period continuous island division. With the goal of maximizing the new equivalent recovery amount and minimizing the battery degradation cost and controllable load compensation cost, the power-off load is further restored, and the load with high importance is restored first. The scope of the island is expanded, which solves the problem of imbalance between supply and demand of the island and improves the power supply reliability on the user side of the distribution network.

[0180] Emergency stage: In response to the power shock and voltage over-limit problems that may occur during the operation of the isolated island, this paper establishes a two-stage dynamic island division strategy for the distribution network based on the fault time: prevention and emergency. In the prevention stage, the source and load day-ahead forecast data is used to design a continuous island prevention plan for multiple periods in the future to improve the distribution network's response capability when a fault occurs. Secondly, in the emergency stage, the prevention plan is dynamically adjusted based on the actual wind and solar output data, further reducing the impact of source and load uncertainty on the recovery plan. At the same time, power shock and voltage over-limit are avoided during the operation of the isolated island, thereby improving the safety of establishing an isolated island after a disaster and improving the resilience of the distribution network.

[0181] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0182] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0183] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0184] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0185] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0186] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0187] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A two-stage islanding method for active distribution network considering flexible resource support, characterized in that: include: Establishing a first resource allocation model that considers energy storage and controllable loads, wherein the first resource allocation model includes upper and lower limit constraints on energy storage battery charging and discharging, an energy storage battery degradation cost model, a controllable load model, and a controllable load-related user agreement; Acquire parameter data of the target power distribution system, the parameter data including line parameters, load level, load grade, network topology connection relationship, system operating voltage level and branch current limit, system fault location, and reference voltage and reference power initial values; According to the parameter data, a mathematical model of two-stage island power supply restoration based on the first resource allocation model is established.

2. The two-stage islanding method for active distribution network considering flexible resource support as claimed in claim 1, characterized in that: The mathematical model of the two-stage island power supply restoration based on the first resource allocation model includes: a prevention stage and an emergency stage; In the prevention stage, island division is performed according to the predicted source load data, which is divided into a single-period island division model and a multi-period continuous island division model; The single-period island division is performed by taking the maximum single-period equivalent recovery amount as the objective function to obtain a single-period discrete island set.

3. The two-stage islanding method for active distribution network considering flexible resource support as claimed in claim 2, characterized in that: The multi-period continuous island partitioning model includes: The multi-period continuous islanding division participates in islanding optimization through energy storage and controllable loads, takes advantage of the electricity transfer characteristics of flexible resources in the previous and next periods, establishes a multi-period islanding division model with the maximum overall load recovery and the minimum battery degradation cost and controllable load compensation cost, and utilizes flexible resources to connect discrete islands in series to achieve multi-period continuous islanding division.

4. The two-stage islanding method for active distribution network considering flexible resource support as claimed in claim 3, characterized in that: The emergency stage includes: dynamically adjusting the multi-period continuous islanding scheme based on actual wind and solar data with the single-period islanding division objective function as the target, and obtaining a single-period dynamic islanding scheme.

5. The two-stage islanding method for active distribution network considering flexible resource support as claimed in claim 4, characterized in that: The mathematical model of the two-stage island power supply restoration based on the first resource allocation model also includes: power constraints within the island, branch capacity constraints, system operation constraints, power balance constraints, network topology constraints and radial topology constraints.

6. The two-stage islanding method for active distribution network considering flexible resource support as claimed in claim 5, characterized in that: The island division is performed by taking the maximum equivalent recovery amount in a single period as the objective function to obtain a discrete island set in a single period, which includes: Where L is the number of load nodes in the island solution after the fault; x i,t is a 0-1 state variable, indicating the power supply status of node i, x i,t =1 means that the load is restored to power supply at time t, x i,t =0 means that the load has not restored power supply at time t; ω i represents the load weight of node i; P i,t is the active power of node i at time t.

7. The two-stage islanding method for active distribution network considering flexible resource support as claimed in claim 6, characterized in that: The multi-period island partitioning model established to maximize the overall load recovery amount and minimize the battery degradation cost and controllable load compensation cost includes: Where T represents the number of fault recovery time periods; ΔP load,t represents the equivalent recovery amount increased compared to the island in a single period; λ1, λ2 and λ3 represent the weight values ​​in the objective function, and λ1, λ2 and λ3 are taken as 0.6, 0.2 and 0.2 respectively; C B,t represents the battery degradation cost; C L,t Represents the controllable load compensation cost, which is determined based on the demand response contract.

8. A two-stage islanding system for active distribution network taking into account flexible resource support, characterized in that: include: A resource allocation model establishment module, used to establish a first resource allocation model that takes into account energy storage and controllable loads, wherein the first resource allocation model includes upper and lower limit constraints on energy storage battery charging and discharging, an energy storage battery degradation cost model, a controllable load model, and a controllable load-related user agreement; A data acquisition module is used to acquire parameter data of the target power distribution system, wherein the parameter data includes line parameters, load level, load grade, network topology connection relationship, system operating voltage level and branch current limit, system fault location, and reference voltage and reference power initial values; The isolated island partition model establishment module is used to establish a two-stage isolated island power supply restoration mathematical model based on the first resource allocation model according to the parameter data.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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