Optimization Method and System for Capacity Configuration of Network-Forming Distributed Energy Storage in Active Distribution Network

Abstract

An optimization method and system for the capacity configuration of grid-type distributed energy storage in an active distribution network is proposed. An index system for island division of the active distribution network within the duration of a fault outage is established. The capacity configuration range and load distribution of the grid-type energy storage in each island in the active distribution network are determined based on the island division index system. The objective function is to maximize the restored load, maximize the weighted sum of restored loads, minimize the system network loss, and minimize the number of switch operations. Connectivity constraints, current and voltage constraints, branch power constraints, grid-type energy storage constraints, and the island division index system are used to form joint constraints. Based on the 0 / 1 knapsack theory, an optimization model is established using the objective function and joint constraints. The determined capacity configuration range and load distribution of the grid-type energy storage in the island are used as input parameters, and the optimization model is iteratively solved to obtain an optimization solution for the capacity configuration of the grid-type distributed energy storage in the active distribution network, thereby solving the problem of the optimal access location and capacity allocation of the grid-type distributed power source in the distribution network.

Description

Technical Field

[0001] The present invention belongs to the technical field of grid-type distributed energy storage capacity configuration, and specifically relates to a method and system for optimizing the configuration of grid-type distributed energy storage capacity in an active distribution network. Background Art

[0002] With the rapid development of new energy technologies, integrating new energy into distribution networks is a future trend in smart grid development. However, when a distribution network system fails, the network loses power, creating a dead island. The introduction of grid-connected distributed power sources (DGs) into the system can enable the distribution network to enter an islanded state, maximizing power supply to critical loads while also responding to other serious emergencies. By rationally arranging the access locations of DGs, the power backup capacity can be maximized, enabling the network to better utilize its emergency power supply capabilities during islanded operation, thereby comprehensively improving the disaster prevention and mitigation capabilities of my country's distribution network system under the influence of extreme weather disasters.

[0003] Existing distributed power optimization configuration methods based on improved genetic algorithms start from system component failure factors, comprehensively consider the impact of component aging failure rate, line outage probability, and weather factors on component failure probability, as well as operational risk cost and potential risk cost factors, establish a probability model, and use genetic algorithms to determine the optimal configuration of distributed power sources. However, these methods only consider the economic efficiency of the site selection and sizing scheme, without separately considering multiple economic and risk factors, resulting in a lack of accuracy and flexibility. A distribution network operation risk assessment method containing distributed power sources calculates the failure probability of distribution lines under different weather types and the failure probability of distributed power sources under different weather types and operating lifespans. Based on the failure probabilities of distribution lines and distributed power sources, the operating status of the distribution network is simulated using a pre-built distributed power output model. The operational risk of the distribution network is assessed based on the simulation results. However, these methods do not consider the impact of operational cost risk and potential cost risk factors on the distribution network containing distributed power sources, and therefore cannot fully guarantee the accuracy of the distribution network operation risk assessment.

[0004] In summary, the existing technology only considers the operating characteristics of distributed power sources, ignores the safety of the grid-type distributed power sources themselves, and cannot meet the safety requirements of the grid-type power sources. Summary of the Invention

[0005] In order to address the deficiencies in the prior art, the present invention provides a method and system for optimizing the capacity configuration of distributed energy storage in an active distribution network. By establishing a capacity configuration optimization model for distributed power sources in a distribution network system, weighting different load nodes is performed based on the input-output method, and then an island partitioning MILP model is constructed under the constraints of island operation. This solves the problem of optimal access location and capacity allocation of distributed power sources in the distribution network.

[0006] The present invention adopts the following technical solutions.

[0007] The present invention proposes a method for optimizing the configuration of distributed energy storage capacity in an active distribution network, comprising:

[0008] In the event of a system failure, the duration of the power outage, the output power of each distributed power source, and the power demand of the power-off load in the system are obtained to determine the power and remaining capacity of the grid-connected energy storage;

[0009] Using the power and remaining capacity of the grid-forming energy storage, an index system for islanding the active distribution network during a fault outage is established, including: the grid-forming energy storage's discharge power duration index, discharge remaining capacity duration index, charging power duration index, charging remaining capacity duration index, power balance duration index, and energy balance duration index. Based on this islanding index system, the capacity configuration range and load distribution of the grid-forming energy storage within each island in the active distribution network are determined.

[0010] Taking the maximum restored load, the maximum weighted sum of restored loads, the minimum system network loss and the minimum number of switch operations as the objective function, the connectivity constraint, current and voltage constraint, branch power constraint, grid-type energy storage constraint and island division index system constitute the joint constraint conditions; based on the 0 / 1 knapsack theory, the objective function and the joint constraint conditions are used to establish an optimization model; with the determined capacity configuration range of the grid-type energy storage in the island and the load distribution as input parameters, the optimization model is iteratively solved to obtain the capacity configuration optimization scheme of the active distribution network grid-type distributed energy storage.

[0011] Preferably, the power outage duration satisfy , is the fault start time, Fault recovery time;

[0012] The power of grid-type energy storage satisfies the following relationship:

[0013]

[0014] Where, For the moment The power of grid-type energy storage, For the moment The output power of the distributed power supply, For the moment The power demand of the power-off load in the system, Power outage duration moments within;

[0015] when When When , the grid-type energy storage discharges.

[0016] The remaining power of the grid-type energy storage satisfies the following relationship:

[0017]

[0018] Where, For the moment The remaining power of the grid-type energy storage, Fault start time The amount of electricity used in grid-type energy storage.

[0019] Preferably, the discharge power duration index of the grid-type energy storage satisfies the following relationship:

[0020]

[0021] Where, It is the discharge power duration indicator of grid-type energy storage within the fault outage duration. is the charging and discharging power sampling time interval, is the discharge power indicator, The total number of sampling moments of charge and discharge power during the fault outage duration;

[0022] Satisfies the following relationship:

[0023]

[0024] Satisfies the following relationship:

[0025]

[0026] Where, is the discharge power sampling value, is the maximum discharge power.

[0027] Preferably, the discharge remaining capacity duration indicator of the grid-type energy storage satisfies the following relationship:

[0028]

[0029] Where, It is the discharge remaining capacity duration indicator of the grid-type energy storage within the fault outage duration. is the remaining power sampling time interval, It is the mark of the remaining discharge capacity. The total number of sampling times for the remaining charge and discharge power during the power outage duration;

[0030] Satisfies the following relationship:

[0031]

[0032] Satisfies the following relationship:

[0033]

[0034] Where, is the remaining power sampling value, The minimum value of remaining power.

[0035] Preferably, the charging power duration index of the grid-type energy storage satisfies the following relationship:

[0036]

[0037] Where, It is the charging power duration indicator of grid-type energy storage within the fault outage duration. It is the charging power identifier;

[0038] Satisfies the following relationship:

[0039]

[0040] Where, is the charging power sampling value, The maximum charging power.

[0041] Preferably, the charging remaining capacity time indicator of the grid-type energy storage satisfies the following relationship:

[0042]

[0043] Where, It is the charging remaining capacity duration indicator of the grid-type energy storage within the fault power outage duration. Indicates the remaining charge capacity.

[0044] Satisfies the following relationship:

[0045]

[0046] Where, is the remaining power sampling value, The maximum remaining power.

[0047] Preferably, the power balance duration indicator satisfies the following relationship:

[0048]

[0049] Where, It is an indicator of the power balance duration of grid-type energy storage within the duration of a fault power outage.

[0050] Preferably, the power balance duration indicator satisfies the following relationship:

[0051]

[0052] Where, It is an indicator of the power balance duration of grid-type energy storage within the duration of a fault power outage.

[0053] Preferably, when the discharge power duration index or the discharge residual capacity duration index of the grid-type energy storage reaches zero, the load with the largest weight is connected to the grid-type energy storage; after the connection, when the charging power duration index or the charging residual capacity duration index reaches the minimum value, the output of the distributed power source and the capacity configuration range of the grid-type energy storage are adjusted; with the goal of maximizing both the power balance duration index and the power balance duration index, the load distribution connected to the grid-type energy storage is determined according to the adjusted distributed power source output and the capacity configuration range of the grid-type energy storage.

[0054] Preferably, the weight of the load corresponding to the production and supply of electricity, heat and water is 1, and the input-output method is used to determine the weight of the load according to the industry to which the load belongs.

[0055] Preferably, the weighted sum of the restoration loads satisfies the following maximum relationship:

[0056]

[0057] Where, To restore the maximum value of the weighted sum of loads, For the The load collection of an island, For load The state variables, Indicates load In the isolated island, It indicates load Not on an island, For load The weight of For load Power;

[0058] The minimum system network loss satisfies the following relationship:

[0059]

[0060] Where, To minimize the system network loss, For connected A collection of branches, and Branch The active power and reactive power of For branch The resistance, For branch voltage;

[0061] The minimum number of switch operations must satisfy the following relationship:

[0062]

[0063] Where, To minimize the number of switching operations, In the failover area A set of switches, Switch before failure recovery The state of the switch is 1, which means the switch is closed, and 0, which means the switch is open. Switch after fault recovery The state of the switch is 1, which means the switch is closed, and 0, which means the switch is open.

[0064] Preferably, the island division index system is transformed into the following constraints:

[0065]

[0066] Where, For the The load collection of an island, For the The total charging and discharging power of the grid-type distributed energy storage in each island, For the load within an island The power, For the The total power of all loads in an island;

[0067]

[0068] Where, It is the power balance duration indicator of grid-type energy storage within the fault outage duration. For the The distributed storage system in the isolated island can The total charge and discharge power, For the The total capacity of the grid-type distributed energy storage within each island, It is the available state of charge of grid-type energy storage;

[0069]

[0070] Where, and are the maximum and minimum values of the available state of charge of the grid-type energy storage respectively;

[0071]

[0072] Where, For the The maximum total capacity of the distributed energy storage network within each island is: It is the electricity balance duration indicator of grid-type energy storage within the fault outage duration. For the Distributed power generation moment in an island Total output;

[0073]

[0074] Where, Provides margin for island safety operation.

[0075] Preferably, the 0 / 1 backpack theory is improved, including: taking integers for input parameters and restoring power supply according to load weights.

[0076] The present invention also proposes an active distribution network type distributed energy storage capacity configuration optimization system, comprising:

[0077] The data acquisition and processing module is used to obtain the duration of the power outage, the output power of each distributed power source, and the power demand of the power-off load in the system when a system failure occurs, so as to determine the power and remaining capacity of the grid-connected energy storage;

[0078] The islanding module is used to establish an islanding index system for the active distribution network during the duration of a fault outage, including: the discharge power duration index, discharge remaining capacity duration index, charging power duration index, charging remaining capacity duration index, power balance duration index, and power balance duration index of the grid-forming energy storage. Based on the islanding index system, the capacity configuration range and load distribution of the grid-forming energy storage within each island in the active distribution network are determined.

[0079] The capacity configuration optimization module is used to maximize the amount of restored load, maximize the weighted sum of restored loads, minimize system network losses, and minimize the number of switch operations as objective functions, and to form joint constraints based on connectivity constraints, current and voltage constraints, branch power constraints, grid-type energy storage constraints, and an island division index system. Based on the 0 / 1 knapsack theory, an optimization model is established using the objective function and joint constraints. Using the determined capacity configuration range of the grid-type energy storage within the island and the load distribution as input parameters, the optimization model is iteratively solved to obtain an optimization solution for the capacity configuration of the grid-type distributed energy storage in the active distribution network.

[0080] The present invention also provides a terminal, comprising a processor and a storage medium; the storage medium is used to store instructions; and the processor is used to operate according to the instructions to execute steps of the method.

[0081] The present invention also relates to a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method when the program is executed by a processor.

[0082] The beneficial effects of the present invention are that, compared with the prior art, at least the following are included: the present invention proposes a method for optimizing the capacity configuration of distributed power sources in a distribution network, which realizes the reasonable arrangement of the access locations of the distributed power sources in the distribution network by constructing an island partition MILP model that meets the island partitioning indicators and constraints, so as to maximize the utilization of the power backup capacity. By rationally configuring the access location and capacity of the power source, the power capacity is fully utilized, the island emergency power supply capability of the distributed power source in the distribution network is better utilized, and the disaster resistance and mitigation capability of the distribution network under extreme disasters and the resilience of the power system itself are comprehensively improved, with the characteristics of fast calculation time and strong applicability. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] Figure 1 This is a logic block diagram of a method for optimizing the configuration of distributed energy storage capacity in an active distribution network configuration proposed by the present invention;

[0084] Figure 2 Schematic diagram of distribution network line planning in an embodiment of the present invention;

[0085] Figure 3 This is the division scheme of DG25 & DG18 in the embodiment of the present invention;

[0086] Figure 4 This is the division scheme of DG25 & DG15 in the embodiment of the present invention;

[0087] Figure 5 This is the division scheme of DG25 & DG26 in the embodiment of the present invention;

[0088] Figure 6 This is the division scheme of DG25 & DG28 in the embodiment of the present invention. DETAILED DESCRIPTION

[0089] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. The embodiments described in this application are only part of the embodiments of the present invention, not all of them. Based on the spirit of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0090] The present invention proposes a method for optimizing the configuration of distributed energy storage capacity in an active distribution network. Figure 1 As shown, including:

[0091] Step 1: When a system fails, obtain the duration of the power outage, the output power of each distributed power source, and the power demand of the power-off load in the system to determine the discharge power and remaining power of the grid-connected energy storage.

[0092] Specifically, the duration of the power outage satisfy , is the fault start time, Fault recovery time;

[0093] Whether the active distribution network can operate in an isolated state under system failure, the charging and discharging power and remaining power of the grid-connected energy storage are key indicators. They can effectively reflect the actual operating status of the active distribution network in an isolated state and provide an important basis for evaluating the operating performance of the active distribution network during the off-grid period.

[0094] The power of grid-type energy storage satisfies the following relationship:

[0095]

[0096] Where, For the moment The power of grid-type energy storage, For the moment The output power of the distributed power supply, For the moment The power demand of the power-off load in the system, Power outage duration moments within;

[0097] when When the grid-type energy storage is charged; when When , the grid-type energy storage discharges.

[0098] The remaining power of the grid-type energy storage satisfies the following relationship:

[0099]

[0100] Where, For the moment The remaining power of the grid-type energy storage, Fault start time The amount of electricity used in grid-type energy storage.

[0101] Step 2: Establish an islanding index system for the active distribution network during the fault outage duration, including: the discharge power duration index, discharge remaining capacity duration index, charging power duration index, charging remaining capacity duration index, power balance duration index, and power balance duration index of the grid-connected energy storage; and perform islanding of the active distribution network based on the islanding index system.

[0102] After the active distribution network is divided into islands based on the island division index system, the grid-connected energy storage connected to the islands is used as the planning scheme for grid-connected distributed energy storage.

[0103] Specifically, the islanding index system for active distribution networks within the duration of a fault outage includes: the discharge power duration index, the discharge remaining capacity duration index, the charging power duration index, the charging remaining capacity duration index, the power balance duration index, and the power balance duration index of grid-connected energy storage;

[0104] Specifically, step 2 includes:

[0105] Step 2.1: During the fault outage duration, a discharge power identifier is set based on the relationship between the grid-type energy storage discharge power and the maximum discharge power, with the sum of all discharge power identifiers serving as the discharge power duration indicator. A discharge residual capacity identifier is set based on the relationship between the residual capacity of the grid-type energy storage and the minimum residual capacity, with the sum of all discharge residual capacity identifiers serving as the discharge residual capacity duration indicator.

[0106] In the embodiment, the power outage duration is (Unit: hour), if the grid-type energy storage is discharged, the discharge power of the grid-type energy storage in the island is detected every 1 minute, so the Discharge power sampling value ,when Discharge power indicator Set to 1, when Discharge power indicator Set to 0, Discharge power indicator The sum of is the discharge power duration index of the grid-type energy storage within the fault outage duration, which satisfies the following relationship:

[0107]

[0108] Where, It is the discharge power duration indicator of grid-type energy storage within the fault outage duration. is the charging and discharging power sampling time interval, which is 1 minute in the embodiment. is the discharge power indicator, The total number of sampling moments of charge and discharge power during the fault outage duration;

[0109] Satisfies the following relationship:

[0110]

[0111] In the formula, the duration of power outage is satisfy , is the fault start time, The fault recovery time; the unit of the fault outage duration is hours, 60 in the numerator represents 60 minutes, and 1 in the denominator represents 1 minute;

[0112] Satisfies the following relationship:

[0113]

[0114] Where, is the discharge power sampling value, is the maximum discharge power;

[0115] The discharge power duration index proposed in the present invention represents the statistical result of the duration that the discharge power exceeds the maximum value. When the discharge power duration index is zero, it means that the discharge power of the grid-type energy storage exceeds the maximum value within the fault power outage duration. The discharge power sampling time interval of 1 minute is a non-restrictive and preferred choice.

[0116] In the embodiment, the power outage duration is (Unit: hour), if the grid-type energy storage is discharged, the remaining power of the grid-type energy storage in the island must be detected every 15 minutes, so the Remaining power sampling value ,when Remaining power indicator Set to 1, when Remaining power indicator Set to 0, Remaining discharge capacity indicator The sum of is the discharge remaining capacity duration index of the grid-type energy storage within the fault outage duration, which satisfies the following relationship:

[0117]

[0118] Where, It is the discharge remaining capacity duration indicator of the grid-type energy storage within the fault outage duration. is the remaining power sampling interval, which is 15 minutes in the embodiment. It is the mark of the remaining discharge capacity. The total number of sampling times of the remaining discharged power during the fault power outage duration;

[0119] Satisfies the following relationship:

[0120]

[0121] In the formula, the duration of power outage is satisfy , is the fault start time, The fault recovery time; the unit of the fault power outage duration is hours, 60 in the numerator means 60 minutes, and 15 in the denominator means 15 minutes;

[0122] Satisfies the following relationship:

[0123]

[0124] Where, is the remaining power sampling value, is the minimum value of remaining power;

[0125] The discharge residual power index proposed in the present invention represents the statistical result of the duration during which the residual power is not less than the minimum value during discharge. When the discharge residual power index is zero, it means that the residual power of the grid-type energy storage does not fall below the minimum value within the duration of the fault power outage; the residual power sampling time interval of 15 minutes is a non-restrictive and preferred choice.

[0126] When the discharge power duration index and the discharge residual capacity duration index proposed in the present invention are both zero, they constitute the zero-value criterion for the island operation of the active distribution network. In the island operation state, if the discharge power of the grid-type energy storage in the island is lower than a certain limit, and the remaining power drops below the critical threshold, the system will lose its dynamic power balancing capability. At this time, it is necessary to implement a load reduction strategy based on the load priority ranking, and give priority to cutting off loads with lower weight levels to maintain safe and stable operation of the system. If control measures are not taken in time, the key parameters of the system (such as voltage amplitude) will deviate from the safety threshold range, which will not only expand the scope of the original power outage area, but may also cause chain power outage accidents, and even lead to complex faults such as deterioration of the system operation state and malfunction of multi-level protection devices. Therefore, the zero-value criterion is a safety indicator for island division.

[0127] Step 2.2: During the power outage duration, the grid-type energy storage is charged. The charging power identifier is set based on the relationship between the grid-type energy storage charging power and the maximum charging power. The sum of all charging power identifiers is used as the charging power duration indicator. The charging remaining capacity identifier is set based on the relationship between the remaining capacity of the grid-type energy storage and the maximum remaining capacity. The sum of all charging remaining capacity identifiers is used as the charging remaining capacity duration indicator.

[0128] In the embodiment, the power outage duration is (Unit: hour), if the grid-type energy storage is discharged, the charging power of the grid-type energy storage in the island must be detected every 1 minute, so the Charging power sampling value ,when Charging power indicator Set to 1, when Charging power indicator Set to 0, Charging power indicator The sum of is the charging power duration index of the grid-type energy storage within the fault outage duration, which satisfies the following relationship:

[0129]

[0130] Where, It is the charging power duration indicator of grid-type energy storage within the fault outage duration. is the charging and discharging power sampling time interval, which is 1 minute in the embodiment. It is the charging power indicator. The total number of sampling moments of charge and discharge power during the fault outage duration;

[0131] Satisfies the following relationship:

[0132]

[0133] Where, is the charging power sampling value, is the maximum charging power;

[0134] The charging power duration indicator proposed in the present invention represents the statistical result of the duration during which the charging power does not exceed the maximum value. The smaller the charging power duration indicator, the shorter the duration during which the charging power of the grid-type energy storage does not exceed the maximum value during the fault power outage. A charging power sampling time interval of 1 minute is a non-restrictive and preferred choice.

[0135] In the embodiment, the power outage duration is (Unit: hour), if the grid-type energy storage is charged, the remaining power of the grid-type energy storage in the island must be detected every 15 minutes, so the Remaining power sampling value ,when Remaining power indicator Set to 1, when Remaining power indicator Set to 0, Remaining charge indicator The sum of is the charging remaining capacity duration index of the grid-type energy storage within the fault outage duration, which satisfies the following relationship:

[0136]

[0137] Where, It is the charging remaining capacity duration indicator of the grid-type energy storage within the fault power outage duration. is the remaining power sampling interval, which is 15 minutes in the embodiment. It is the mark of the remaining charge capacity. The total number of sampling times of the remaining charging capacity during the power outage duration;

[0138] Satisfies the following relationship:

[0139]

[0140] Where, is the remaining power sampling value, The maximum value of remaining power;

[0141] The charging remaining capacity index proposed in the present invention represents the statistical result of the duration during which the charging remaining capacity does not exceed the maximum value. The smaller the charging remaining capacity index is, the shorter the duration during which the charging remaining capacity of the grid-type energy storage does not exceed the maximum value during the fault power outage. The charging remaining capacity sampling time interval of 15 minutes is a non-restrictive and preferred choice.

[0142] Distributed power sources are connected to the island, so when the island is operating, the grid-type energy storage must be in a charging state. The charging power duration indicator and the charging remaining capacity duration indicator proposed in this invention are both minimum values, which constitute the minimum criteria for the island operation of the active distribution network. If the charging power of the grid-type energy storage in the island exceeds the maximum charging power and the remaining power of the grid-type energy storage exceeds the limit, then effective measures must be taken to control the power generation of the DG. In order to effectively utilize energy, load power supply must be ensured as much as possible, and phenomena such as wind and solar power abandonment should be reduced, and the minimum criteria should be followed. Therefore, the minimum criteria is an economic indicator for island division.

[0143] Step 2.3: The difference between the fault outage duration and the discharge power duration indicator and the charging power duration indicator is used as the power balance duration indicator; the difference between the fault outage duration and the discharge remaining power duration indicator and the charging remaining power duration indicator is used as the power balance duration indicator;

[0144] Specifically, the power balance duration indicator satisfies the following relationship:

[0145]

[0146] Where, It is the power balance duration indicator of grid-type energy storage within the fault outage duration;

[0147] The power balance duration indicator satisfies the following relationship:

[0148]

[0149] Where, It is the electricity balance duration indicator of grid-type energy storage within the fault power outage duration;

[0150] When the zero-value and minimum-value criteria are met, the power balance duration and battery balance duration indicators proposed in this invention both reach their maximum values, constituting the maximum value criteria for islanding the active distribution network. When the island is operating effectively, both the grid-forming energy storage charging and discharging power and the remaining battery capacity must meet certain requirements. During islanding operation, the grid-forming energy storage should be kept within its effective adjustment range as much as possible, with a good balance between power and remaining battery capacity. Therefore, the maximum value criterion serves as a stability indicator for islanding.

[0151] The islanding index system for active distribution networks during fault outage duration also includes: load restoration priority index, distributed power supply parameter index, and active distribution network topology index;

[0152] In the prior art, islanding of active distribution networks is based on qualitative indicators or local, single quantitative indicators. However, the present invention not only proposes quantitative indicators that cover multiple aspects of safety, economy, and stability and are organically linked, but also proposes the following indicators:

[0153] 1) Load restoration power supply priority index

[0154] The load restoration priority index is the same as the load importance level;

[0155] Restoring critical loads should be the most crucial step in restoring power to a distribution network. Loads in a distribution network are categorized by their importance into primary, secondary, and tertiary loads. Therefore, when restoring power to a distribution network after a fault, critical loads must be restored first.

[0156] 2) Distributed power supply parameter indicators

[0157] Distributed power supply parameter indicators include but are not limited to: power supply voltage, power supply frequency;

[0158] Use highly reliable distributed power sources. In an isolated operating environment, distributed power sources must have stable supply voltage and frequency, and reduce intermittency and volatility. In this embodiment, energy storage and wind and photovoltaic power sources with grid-connected inverter interfaces are used.

[0159] 3) Active distribution network topology indicators

[0160] In the distribution system, radial topology usually adopts the "closed-loop design, open-loop operation" approach, which requires ensuring the radial structure of the distribution network system after an accident occurs.

[0161] The above indicators are actually a series of fixed prerequisite indicators and will not change significantly due to the fault state of the active distribution network. The discharge power duration indicator, discharge remaining capacity duration indicator, charging power duration indicator, charging remaining capacity duration indicator, power balance duration indicator, and power balance duration indicator are a set of dynamic a posteriori indicators. Changes in the fault state of the active distribution network will be clearly reflected in these indicators. Therefore, these indicators can not only serve as the basis for islanding the active distribution network, but also serve as indicators of the fault state of the active distribution network.

[0162] Step 2.4: Determine the capacity configuration range and load distribution of the grid-connected energy storage within each island in the active distribution network based on the island classification index system;

[0163] The island division index system proposed in the present invention does not directly divide the active distribution network into islands, nor does it configure the access location and capacity of the grid-forming energy storage. Instead, it uses the island division index system of the active distribution network to achieve multi-stage dynamic allocation of the grid-forming energy storage and load within the island. In fact, the specific situation of the grid-forming energy storage connected to the divided island is the preliminary planning scheme of the grid-forming distributed energy storage. This method avoids the existing energy storage planning scheme that only considers the economic and safety requirements of the active distribution network while ignoring the multiple impacts of the layout scheme of the grid-forming distributed energy storage on the safety, economy and stability of the active distribution network when it is declassified into an island and operates under a fault state. Moreover, based on the island division index system proposed in the present invention, the island division results are different when facing different fault states of the active distribution network, and the planning scheme of the grid-forming distributed energy storage can be adaptively adjusted.

[0164] In this embodiment, during the duration of a power outage, real-time data on the grid-connected energy storage's charge and discharge power, remaining capacity, distributed power generation output, and load demand is collected. A time series dataset is generated at preset sampling intervals (every 1 minute for power and every 15 minutes for capacity). Each indicator is calculated, and a determination is made as to whether a zero-value criterion (the discharge power duration indicator or the remaining charge capacity duration indicator is zero) or a minimum-value criterion (the charging power duration indicator or the remaining charge capacity duration indicator reaches a critical value) has been triggered. Existing technologies often use static thresholds (e.g., charge and discharge power ≤ maximum value, energy storage capacity ≥ minimum value) as constraints. However, this invention constructs dynamic indicators through high-frequency sampling statistics to quantify the operational time characteristics of the grid-connected energy storage, such as the duration of indicator exceeding a limit, more accurately reflecting changes in the energy storage state during a fault.

[0165] Specifically, when the discharge power duration index or the discharge remaining capacity duration index of the grid-type energy storage reaches zero, the load with the largest weight is connected to the grid-type energy storage; after the connection, when the charging power duration index or the charging remaining capacity duration index reaches the minimum value, the output of the distributed power source and the capacity configuration range of the grid-type energy storage are adjusted; with the goal of maximizing both the power balance duration index and the power balance duration index, the load distribution connected to the grid-type energy storage is determined according to the adjusted distributed power source output and the capacity configuration range of the grid-type energy storage;

[0166] In the embodiment, if the zero value criterion is triggered (discharge power or remaining capacity exceeds the limit), high-weight loads (such as primary loads) are preferentially connected directly to the grid-type energy storage to form an independent island to ensure power supply to critical loads; if the minimum value criterion is triggered (charging power or remaining capacity exceeds the limit), the output of distributed power sources is adjusted (such as reducing the wind and solar power curtailment rate), and the energy storage charging period is reallocated to optimize energy utilization; based on the principle of maximizing the power balance duration indicator and the power balance duration indicator, the island boundary is dynamically adjusted to ensure the timing matching of energy storage charging and discharging with load demand.

[0167] In the embodiment, topology connectivity verification is also performed to verify the connectivity between nodes in the island and the grid-type energy storage, ensuring that the island topology is a radial structure to avoid circulating current or voltage exceeding the limit problem.

[0168] The determined capacity configuration range and load distribution of the grid-type energy storage within each island are used as input parameters and initial conditions of the MILP optimization model to solve the optimal capacity configuration plan; and the relevant indicators are converted into dynamic constraints of the optimization model to ensure that the configuration plan matches the actual operation requirements.

[0169] The input-output method is used to determine the weight of each load, including:

[0170] The power loss load value model utilizes the input-output method. For the civilian power industry, generated electricity must first be transmitted through transformers and then distributed to various production departments via transmission equipment. The input-output method links the inputs and outputs of different production departments, thereby determining the value of electricity consumption. This value is then linked to load weights to determine their magnitude.

[0171] The value of electricity consumption includes the direct value generated by electricity and the indirect value generated by electricity, which satisfies the following relationship:

[0172]

[0173] Where, For the The total value of electricity production in each sector, For the The direct value of electricity generated by each sector, For the the indirect value of electricity generated by each sector;

[0174]

[0175] Where, For the The added value of output of each sector, For the The amount of electricity consumed by each department;

[0176]

[0177]

[0178] Where, is the total output of the electricity sector, For The corresponding total electricity output value is is the direct consumption coefficient, which indicates the direct consumption per unit output value of the power sector. The intermediate inputs of the sector, For the The value added rate of a sector means that the value added rate is the ratio of value added to gross output.

[0179] The electricity value and load weight of each industry are calculated, as shown in Table 1. The load weight is based on the production and supply of electricity, heat, and water, with the load weight set to 1. The load weights of the remaining industries are scaled down by this multiple to obtain the load weights of each industry.

[0180] Table 1 Production load power value and load weight

[0181]

[0182] In step 3, the objective function is to maximize the amount of restored load, maximize the weighted sum of restored loads, minimize the system network loss, and minimize the number of switch operations. The connectivity constraint, current and voltage constraint, branch power constraint, grid-type energy storage constraint, and island division index system are used to form a joint constraint condition. Based on the 0 / 1 knapsack theory, the objective function and the joint constraint condition are used to form an optimization model. The capacity configuration range of the grid-type energy storage in the determined island and the load distribution are used as input parameters. The optimization model is iteratively solved to obtain the capacity configuration optimization scheme of the active distribution network grid-type distributed energy storage.

[0183] From the perspective of economy and importance, important loads should be restored as much as possible after a disaster-induced accident. In the distribution network, due to the access of grid-connected energy storage, an islanded operating state is formed. The power outage area should be minimized to ensure the continuous power supply of key loads and minimize the impact of the disaster to achieve the purpose of optimizing the island division. The goals of distribution network fault reconstruction include maximizing load recovery, minimizing system network losses, and minimizing the number of switches; therefore, this paper proposes a MILP optimization model for island division based on the improved 0 / 1 knapsack theory.

[0184] Specifically, the restored load is the load whose power supply is restored after the island division. The maximum weighted sum of the restored loads satisfies the following relationship:

[0185]

[0186] Where, To restore the maximum value of the weighted sum of loads, For the The load collection of an island, For load The state variables, Indicates load In the isolated island, It indicates load Not on an island, For load The weight of For load Power;

[0187] In the embodiment, the weight of the load corresponding to the production and supply of electricity, heat and water is 1, and the input-output method is used to calculate the load. The industry to which the load belongs determines the load The weight of

[0188] Specifically, the minimum system network loss satisfies the following relationship:

[0189]

[0190] Where, To minimize the system network loss, For connected A collection of branches, and Branch The active power and reactive power of For branch The resistance, For branch voltage;

[0191] Specifically, the number of switch operations must at least satisfy the following relationship:

[0192]

[0193] Where, To minimize the number of switching operations, In the failover area A set of switches, Switch before failure recovery The state of the switch is 1, which means the switch is closed, and 0, which means the switch is open. Switch after fault recovery The state of the switch is 1, which means the switch is closed, and 0, which means the switch is open.

[0194] The joint constraints are composed of connectivity constraints, current and voltage constraints, branch power constraints, grid-type energy storage constraints, and island division index system, including:

[0195] 1) Connectivity Constraints: Based on the radial network structure of the distribution network system, from the perspective of energy and power balance, each island node must be connected to the distributed power generation node by at least one path. This connectivity is constrained by the power flow on the lines at both ends of the node. When the grid-type distributed power generation is connected to the island, its access point is the root node. To ensure successful power supply, all nodes included in it must be connected to the root node, satisfying the following relationship:

[0196]

[0197] 2) Current and voltage constraints: The divided islands must ensure that the actual current of the transformer and transmission line is less than the corresponding rated current, satisfying the following relationship:

[0198]

[0199] Where, is the maximum current on the line and transformer, is the rated current on the line and transformer;

[0200] The voltage fluctuation range is generally required to be ±5%. Voltage that is too high or too low will have a negative impact and satisfy the following relationship:

[0201]

[0202] Where, For the Real-time voltage of segment bus; is the busbar rated voltage.

[0203] 3) Branch power constraint:

[0204]

[0205] Where, For branch At the moment Active power; For branch The maximum active power.

[0206] 4) Convert the island division index system into the following constraints:

[0207]

[0208] Where, For the The load collection of an island, For the The total charging and discharging power of the grid-type distributed energy storage in each island, For the load within an island The power, For the The total power of all loads in an island;

[0209]

[0210] Where, It is the power balance duration indicator of grid-type energy storage within the fault outage duration. For the The distributed storage system in the isolated island can The total charge and discharge power, For the The total capacity of the grid-type distributed energy storage within each island, It is the available state of charge of grid-type energy storage;

[0211]

[0212] Where, and are the maximum and minimum values of the available state of charge of the grid-type energy storage respectively;

[0213]

[0214] Where, For the The maximum total capacity of the distributed energy storage network within each island is: It is the electricity balance duration indicator of grid-type energy storage within the fault outage duration. For the Distributed power generation moment in an island Total output;

[0215]

[0216] Where, Provides margin for island safety operation.

[0217] In the present invention, the constraints established based on the island partitioning index system take the charging and discharging capabilities of distributed grid-type energy storage as new constraints, and add charging and discharging power limits and energy storage capacity limits to the optimization model to achieve the purpose of optimizing the utilization rate of grid-type energy storage, reducing load losses and improving energy storage stability. In the prior art, charging and discharging power limits and energy storage capacity limits are usually static constraints (setting maximum charging and discharging power or capacity thresholds), and only focus on instantaneous values or total amount limits. The indicators proposed in this grid-type energy storage constraint are dynamic time series statistical indicators. These indicators dynamically capture the energy storage operating status through high-frequency sampling (power detection every minute, remaining power detection every 15 minutes) and quantify it as a constraint condition in the time dimension. This dynamic constraint can more accurately reflect the actual operating characteristics of the energy storage system during a fault, rather than simply relying on instantaneous values or total amount limits. This constitutive grid-type energy storage constraint further combines the above-mentioned indicators with the power balance duration indicator and the charge balance duration indicator to form a multi-dimensional constraint system. Safety: The discharge power duration indicator and the discharge residual capacity duration indicator ensure that the power and charge do not exceed the safety threshold during energy storage discharge. Economy: The charging power duration indicator and the charging residual capacity duration indicator avoid energy waste during charging. Stability: The power and charge balance duration indicators ensure the dynamic balance of energy storage charging and discharging during island operation. Stability constraint: The power and charge balance duration indicators ensure the dynamic balance of energy storage charging and discharging during island operation. This multi-indicator collaborative constraint mechanism solves the problem of one-sided optimization objectives caused by single constraints in existing technologies (such as considering only power or capacity), and achieves comprehensive optimization of safety, economy, and stability.

[0218] The 0 / 1 knapsack problem involves a limited-capacity knapsack and a series of items, each with a weight and value. The goal is to select items that maximize the total value without exceeding the knapsack's capacity. In island partitioning applications, the knapsack's capacity corresponds to the remaining charge or power of the grid-type energy storage. The items correspond to different loads, with their "weight" representing the load's power requirement and "value" indicating the load's priority or importance. In planning schemes for grid-type distributed energy storage based on islanding, the capacity and load power of the grid-type energy storage are not always integers; they often contain decimals. The 0 / 1 knapsack problem falls under the category of integer programming within dynamic programming and can yield integer solutions for the capacity configuration of the grid-type distributed energy storage. In planning schemes for grid-type distributed energy storage based on islanding, for any load assigned to an island, all loads and branches along the path from that load to the grid-type energy storage are also included in the island. This imposes connectivity constraints on the network within the island. Once a load is islanded, current must flow between all nodes within the entire island. However, the 0 / 1 knapsack theory fails to address this connectivity constraint. The 0 / 1 knapsack model primarily considers isolated "points," whereas the mathematical model for islanding must consider not only individual "points" but also the connections between them. Therefore, the traditional 0 / 1 knapsack problem cannot be applied to the islanding problem. Instead, it is necessary to adjust and improve the distribution network parameters and network structure containing distributed generation and grid-type energy storage based on the 0 / 1 knapsack theoretical model. The improvement strategy is as follows:

[0219] (1) Integering the input parameters: During the islanding process, since the grid-type energy storage capacity and load power may have decimal parts, the capacity dimension needs to be discretized when using dynamic programming. The load, load weight value, distributed power supply and grid-type energy storage capacity and other values are integerized. Because these power values are relatively large and have low sensitivity to decimals, integerization will not affect the final model solution and partitioning results; a suitable accuracy can be set. , multiply the capacity value by Convert to integer, perform calculation, and then convert the result back to real value.

[0220] (2) Restoring power supply according to load weight: Add automation devices between the nodes corresponding to the load to match the improved 0 / 1 backpack theoretical model. In the island, there is a tree-like line with nodes A, B, and C distributed on it in sequence. When performing the restoration operation, the improved 0 / 1 backpack theoretical method is used for analysis. The analysis results show that the loads connected to nodes A and C can meet the restoration conditions, but node B, which is in the middle position, fails to meet the restoration standard due to its low importance level coefficient. At this time, nodes A, B, and C are in the same line. When the current flows through node B, according to the established island division scheme, the distribution network automation device will receive the corresponding signal and block the switch between node B and the load connected to it. In this way, point B only serves as a path point for the current to pass through, ensuring that nodes A, C and other similar loads with high importance level coefficients can be restored to power first. Through this series of operations, the total weighted value of the load in the island is finally maximized according to the specific function.

[0221] By improving the 0 / 1 knapsack theory, it is convenient to adopt the mixed integer linear programming (MILP) method and establish an optimization model using the objective function and joint constraints; using the determined capacity configuration range of the grid-type energy storage within the island and the load distribution as input parameters, the optimization model is iteratively solved to obtain the capacity configuration optimization scheme of the active distribution network grid-type distributed energy storage.

[0222] The present invention also proposes an active distribution network type distributed energy storage capacity configuration optimization system, comprising:

[0223] The data acquisition and processing module is used to obtain the duration of the power outage, the output power of each distributed power source, and the power demand of the power-off load in the system when a system failure occurs, so as to determine the power and remaining capacity of the grid-connected energy storage;

[0224] The islanding module is used to establish an islanding index system for the active distribution network during the duration of a fault outage, including: the discharge power duration index, discharge remaining capacity duration index, charging power duration index, charging remaining capacity duration index, power balance duration index, and power balance duration index of the grid-forming energy storage. Based on the islanding index system, the capacity configuration range and load distribution of the grid-forming energy storage within each island in the active distribution network are determined.

[0225] The capacity configuration optimization module is used to maximize the amount of restored load, maximize the weighted sum of restored loads, minimize system network losses, and minimize the number of switch operations as objective functions, and to form joint constraints based on connectivity constraints, current and voltage constraints, branch power constraints, grid-type energy storage constraints, and an island division index system. Based on the 0 / 1 knapsack theory, an optimization model is established using the objective function and joint constraints. Using the determined capacity configuration range of the grid-type energy storage within the island and the load distribution as input parameters, the optimization model is iteratively solved to obtain an optimization solution for the capacity configuration of the grid-type distributed energy storage in the active distribution network.

[0226] The feasibility and effectiveness of the present invention were verified by MATLAB. Using IEEE 33-node power distribution system data, MATLAB software was used for modeling and analysis. The IEEE 33-node power distribution system parameters used for modeling are shown in Table 2. The distribution network line planning is shown in Table 2. Figure 2 shown.

[0227] Table 2 IEEE33 node distribution system parameters

[0228]

[0229] The load node sizes and weights obtained by the input-output method are shown in Table 3. According to Table 3, the total load capacity of the distribution network can be calculated to be 6.6 MVA. According to the constraints, the total capacity of the two grid-type distributed generation units should be 1.65 MVA.

[0230] Table 3 Distribution network load node types and their load weights

[0231]

[0232] The MILP model for optimizing the capacity configuration of distributed generation in the distribution network is used for calculation. The four DG recovery node division schemes are shown in Table 4. The simulation results of MATLAB are shown below:

[0233] Table 4 Results of four DG recovery node partitioning schemes

[0234]

[0235] Figure 3 This is the division scheme of DG25 & DG18 in the embodiment of the present invention. Figure 4 This is the division scheme of DG25 & DG15 in the embodiment of the present invention. Figure 5 This is the division scheme of DG25 & DG26 in the embodiment of the present invention. Figure 6 This is the division scheme of DG25 & DG28 in the embodiment of the present invention.

[0236] Table 5 shows the four optimized allocation schemes for distributed power capacity of network-based structures:

[0237] Table 5 Results of four DG capacity allocation schemes

[0238]

[0239] Analysis of Table 5 shows that, with Schemes 1 and 2, the combined capacity of the two grid-connected distributed generation units is 1.65 MVA; with Schemes 3 and 4, the combined capacity of the two grid-connected distributed generation units is 1.64 MVA. Regarding the sum of the load weights that the grid-connected distributed generation units can recover, Scheme 3 achieves the highest sum of the load node weights, 30.077, compared to the other three schemes. Furthermore, the total capacity of the power source is lower than that of Schemes 1 and 2. Finally, the analysis concludes that Scheme 3 is the optimal MILP optimization configuration scheme for grid-connected distributed generation units in the distribution network.

[0240] It can be seen that the method proposed in the present invention solves the problem of optimal access location and capacity allocation of distributed power sources in the distribution network. By rationally configuring the access location and capacity of the power source, the power capacity is fully utilized, the island emergency power supply capability of the distributed power source in the distribution network is better utilized, and the disaster resistance and mitigation capability of the distribution network under extreme disasters and the resilience of the power system itself are comprehensively improved. It has the characteristics of fast calculation time and strong applicability, as follows:

[0241] (1) Fast calculation time: The model of the present invention utilizes mixed integer linear programming, a mathematical model applied to optimization problems. The decision variables involved include both integer variables and continuous variables. It is particularly advantageous when solving problems with binary variables and some decision variables. It can quickly solve the model and derive island planning and grid-type distributed power planning solutions for distribution networks.

[0242] (2) Strong applicability: The model of the present invention can adapt to different scenario requirements through the input-output method. This method comprehensively considers the economic benefits and load levels of different load points, restores as many important loads as possible, narrows the scope of power outages in the distribution network, and reduces the losses caused by power outages. It has wide applicability.

[0243] The present disclosure may be a system, method and / or computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0244] A computer-readable storage medium can be a tangible device that can hold and store instructions for use by an instruction execution device. A computer-readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punched card or raised structure in a groove on which instructions are stored, and any suitable combination thereof. As used herein, a computer-readable storage medium is not to be construed as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse passing through a fiber optic cable), or an electrical signal transmitted through an electrical wire.

[0245] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions to be stored in the computer-readable storage medium in each computing / processing device.

[0246] The computer program instructions for performing the operations of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages such as Smalltalk, C++, and conventional procedural programming languages such as "C" or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, the state information of the computer-readable program instructions is used to personalize an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), so that the electronic circuit can execute the computer-readable program instructions, thereby implementing various aspects of the present disclosure.

[0247] Finally, 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 above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A method for optimizing the configuration of distributed energy storage capacity in an active distribution network, characterized in that: include: In the event of a system failure, the duration of the power outage, the output power of each distributed power source, and the power demand of the power-lost load in the system are obtained to determine the power and remaining capacity of the grid-forming energy storage. Using the power and remaining capacity of the grid-forming energy storage, an index system for islanding the active distribution network during the power outage duration is established. Based on this index system, the capacity configuration range and load distribution of the grid-forming energy storage within each island in the active distribution network are determined. The objective function is to maximize the amount of restored load, maximize the weighted sum of restored loads, minimize the system network loss and the number of switching operations. The joint constraints are composed of connectivity constraints, current and voltage constraints, branch power constraints, grid-type energy storage constraints and island division index system. Among them, the input-output method is used to determine the weight of the load according to the industry to which the load belongs to calculate the weighted sum of the restored load; the island division index system includes: power balance time index, electricity balance time index, and the power balance time index. , Power balance duration indicator Transformed into the following constraints: Where, For the The distributed storage system in the isolated island can The total charge and discharge power, For the The total capacity of the grid-type distributed energy storage within each island, It is the available state of charge of grid-type energy storage; Where, For the The maximum total capacity of the grid-type distributed energy storage within each island is: For the Distributed power generation moment in an island Total output; For the The load collection of an island, For the load within an island Power; Based on the 0 / 1 knapsack theory, an optimization model is established using the objective function and joint constraints. Taking the determined capacity configuration range of the grid-type energy storage within the island and the load distribution as input parameters, the power supply is restored according to the load weight, and the optimization model is iteratively solved to obtain the optimal configuration scheme of the distributed energy storage capacity in the active distribution network.

2. The method for optimizing the configuration of distributed energy storage capacity in an active distribution network according to claim 1, characterized in that: Fault power outage duration satisfy , is the fault start time, Fault recovery time; The power of grid-type energy storage satisfies the following relationship: Where, For the moment The power of grid-type energy storage, For the moment The output power of distributed power supply, For the moment The power demand of the power-off load in the system, Power outage duration moments within; when When When , the grid-type energy storage discharges; The remaining power of the grid-type energy storage satisfies the following relationship: Where, For the moment The remaining power of the grid-type energy storage, Fault start time The amount of electricity used in grid-type energy storage.

3. The method for optimizing the configuration of distributed energy storage capacity in an active distribution network according to claim 2, characterized in that: The island classification index system also includes: the discharge power duration index, the discharge remaining capacity duration index, the charging power duration index, and the charging remaining capacity duration index of the grid-type energy storage.

4. The method for optimizing the configuration of distributed energy storage capacity in an active distribution network according to claim 3, characterized in that: The discharge power duration index of grid-type energy storage satisfies the following relationship: Where, It is the discharge power duration indicator of grid-type energy storage within the fault outage duration. is the charging and discharging power sampling time interval, is the discharge power indicator, The total number of sampling moments of charge and discharge power during the fault outage duration; Satisfies the following relationship: Satisfies the following relationship: Where, is the discharge power sampling value, is the maximum discharge power.

5. The method for optimizing the configuration of distributed energy storage capacity in an active distribution network according to claim 4, characterized in that: The discharge residual capacity duration indicator of grid-type energy storage satisfies the following relationship: Where, It is the discharge remaining capacity duration indicator of the grid-type energy storage within the fault outage duration. is the remaining power sampling time interval, It is the mark of the remaining discharge capacity. The total number of sampling times for the remaining charge and discharge power during the power outage duration; Satisfies the following relationship: Satisfies the following relationship: Where, is the remaining power sampling value, The minimum value of remaining power.

6. The method for optimizing the configuration of distributed energy storage capacity in an active distribution network according to claim 5, characterized in that: The charging power duration index of grid-type energy storage satisfies the following relationship: Where, It is the charging power duration indicator of grid-type energy storage within the fault outage duration. It is the charging power identifier; Satisfies the following relationship: Where, is the charging power sampling value, The maximum charging power.

7. The method for optimizing the configuration of distributed energy storage capacity in an active distribution network according to claim 6, characterized in that: The remaining charging capacity time indicator of grid-type energy storage satisfies the following relationship: Where, It is the charging remaining capacity duration indicator of the grid-type energy storage within the fault power outage duration. Indicates the remaining charge capacity. Satisfies the following relationship: Where, is the remaining power sampling value, The maximum remaining power.

8. The method for optimizing the configuration of distributed energy storage capacity in an active distribution network according to claim 7, characterized in that: The power balance duration indicator satisfies the following relationship: Where, It is an indicator of the power balance duration of grid-type energy storage within the duration of a fault power outage.

9. The method for optimizing the configuration of distributed energy storage capacity in an active distribution network according to claim 8, characterized in that: The power balance duration indicator satisfies the following relationship: Where, It is an indicator of the power balance duration of grid-type energy storage within the duration of a fault power outage.

10. The method for optimizing the configuration of distributed energy storage capacity in an active distribution network according to claim 1, characterized in that: When the discharge power duration index or the discharge remaining capacity duration index of the grid-type energy storage reaches zero, the load with the largest weight is connected to the grid-type energy storage; after the connection, when the charging power duration index or the charging remaining capacity duration index reaches the minimum value, the output of the distributed power source and the capacity configuration range of the grid-type energy storage are adjusted; with the goal of maximizing both the power balance duration index and the power balance duration index, the load distribution connected to the grid-type energy storage is determined according to the adjusted distributed power source output and the capacity configuration range of the grid-type energy storage.

11. The method for optimizing the configuration of distributed energy storage capacity in an active distribution network according to claim 10, characterized in that: The weight of the load corresponding to the production and supply of electricity, heat and water is 1, and the input-output method is used to determine the weight of the load according to the industry to which the load belongs.

12. The method for optimizing the configuration of distributed energy storage capacity in an active distribution network according to claim 1, characterized in that: The maximum weighted sum of the restoration loads satisfies the following relationship: Where, To restore the maximum value of the weighted sum of loads, For the The load collection of an island, For load The state variables, Indicates load In the isolated island, It indicates load Not on an island, For load The weight of For load Power; The minimum system network loss satisfies the following relationship: Where, To minimize the system network loss, For connected A collection of branches, and Branch The active power and reactive power, For branch The resistance, For branch voltage; The minimum number of switch operations must satisfy the following relationship: Where, To minimize the number of switching operations, In the failover area A set of switches, Switch before failure recovery The state of the switch is 1, which means the switch is closed, and 0, which means the switch is open. Switch after fault recovery The state of the switch is 1, which means the switch is closed, and 0, which means the switch is open.

13. The method for optimizing the configuration of distributed energy storage capacity in an active distribution network according to claim 1, characterized in that: The island division indicator system is transformed into the following constraints: Where, For the The load collection of an island, For the The total charging and discharging power of the grid-type distributed energy storage in each island, For the load within an island Power, For the The total power of all loads in an island; Where, and are the maximum and minimum values of the available state of charge of the grid-type energy storage respectively; Where, Provides margin for island safety operation.

14. The method for optimizing the configuration of distributed energy storage capacity in an active distribution network according to claim 1, characterized in that: Improvements are made to the 0 / 1 backpack theory, including rounding input parameters to integers and restoring power supply according to load weights.

15. An active distribution network type distributed energy storage capacity configuration optimization system, characterized in that: include: The data acquisition and processing module is used to obtain the duration of the power outage, the output power of each distributed power source, and the power demand of the power-off load in the system when a system failure occurs, so as to determine the power and remaining capacity of the grid-connected energy storage; The islanding module is used to utilize the power and remaining capacity of the grid-forming energy storage to establish an islanding index system for the active distribution network during the fault outage duration, including: the grid-forming energy storage's discharge power duration index, discharge remaining capacity duration index, charging power duration index, charging remaining capacity duration index, power balance duration index, and power balance duration index. Based on the islanding index system, the capacity configuration range and load distribution of the grid-forming energy storage within each island in the active distribution network are determined. The capacity configuration optimization module is used to maximize the restored load, maximize the weighted sum of restored loads, minimize the system network loss and the number of switch operations as the objective function, and to form joint constraints with connectivity constraints, current and voltage constraints, branch power constraints, grid-type energy storage constraints and island division index system; among them, the input-output method is used to determine the weight of the load according to the industry to which the load belongs to calculate the weighted sum of the restored load; the power balance time index is used to calculate the power balance time. , Power balance duration indicator Transformed into the following constraints: Where, For the The distributed storage system in the isolated island can The total charge and discharge power, For the The total capacity of the grid-type distributed energy storage within each island, It is the available state of charge of grid-type energy storage; Where, For the The maximum total capacity of the grid-type distributed energy storage within each island is: For the Distributed power generation moment in an island Total output; For the The load collection of an island, For the load within an island Power; Based on the 0 / 1 knapsack theory, an optimization model is established using the objective function and joint constraints. Taking the determined capacity configuration range of the grid-type energy storage within the island and the load distribution as input parameters, the power supply is restored according to the load weight, and the optimization model is iteratively solved to obtain the optimal configuration scheme of the distributed energy storage capacity in the active distribution network.

16. A terminal comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1 to 14.

17. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 14 are implemented.

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