Reliability calculation method for diamond-type distribution network with large-scale photovoltaic energy storage access

Abstract

The application discloses a diamond type power distribution network reliability calculation method considering large-scale photovoltaic energy storage access, relates to the power distribution technology field of a power system, and specifically comprises the following steps: firstly, a diamond type power distribution network framework structure model is constructed; secondly, a photovoltaic energy storage microgrid system operation model is constructed; and finally, the reliability of the diamond type power distribution network under large-scale photovoltaic energy storage access is calculated based on sequential Monte Carlo simulation. The application aims at the difficulty in reliability calculation caused by unstable new energy output after large-scale photovoltaic energy storage access of the current power distribution system, realizes the reliability calculation of the diamond type power distribution network based on sequential Monte Carlo simulation and aiming at the typical framework structure of the diamond type power distribution network.

Description

Technical Field

[0001] This invention relates to a reliability calculation method for diamond-shaped distribution networks considering large-scale photovoltaic energy storage integration, and belongs to the field of power system distribution technology. Background Technology

[0002] The power distribution system is the core component of power supply to users and a crucial infrastructure for energy conversion and utilization. The distribution network is a vital platform supporting demand-side response management and carrying a large amount of renewable and distributed energy resources. With the trend towards a power system dominated by new energy sources, the economic efficiency, flexibility, and reliability of the distribution system are becoming increasingly correlated with its system architecture. The continuous development of smart distribution networks is driving more and more renewable and clean energy sources into the grid. While distributed power sources alleviate energy pressure, protect the environment, and provide flexible power generation, they also pose challenges to the safe and stable operation of the distribution network.

[0003] Urban power distribution networks are characterized by high electricity consumption, high load density, high safety and reliability requirements, and high power quality standards. With the continuous development of smart grids and the application of new technologies, urban power distribution networks are transforming into intelligent grids that accommodate a large number of distributed power sources, microgrids, and other user-side loads. Recently, Shanghai, based on its own urban power distribution network development, summarized the structure of a diamond-shaped power distribution network. A diamond-shaped power distribution network is a user-centric distribution network. Through inter-station load transfer, faults can be quickly isolated and power restored, ensuring reliable power quality for medium and low-voltage users.

[0004] Currently, the instability of renewable energy output after large-scale integration into distribution systems poses the greatest challenge in calculating the reliability of diamond-shaped distribution networks. While traditional analytical methods offer high accuracy, they suffer from long computation times as the system scales up, and often fail to provide accurate calculations after the integration of renewable energy. This paper proposes a reliability analysis and calculation method for diamond-shaped distribution networks that considers large-scale photovoltaic energy storage integration. Summary of the Invention

[0005] The technical problem to be solved by this invention is: a reliability calculation method for diamond-shaped distribution networks considering large-scale photovoltaic energy storage access, which ensures the accuracy of reliability calculation while taking into account the efficiency of the algorithm, thus solving the problem of inaccurate reliability calculation in existing methods.

[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: a reliability calculation method for diamond-shaped distribution networks considering large-scale photovoltaic energy storage access, characterized by comprising the following steps:

[0007] Step 1: Construct a diamond-shaped distribution network structure model and formulate a fault analysis strategy;

[0008] Step 2: Construct an operational model of the photovoltaic energy storage microgrid system when a fault occurs;

[0009] Step 3: Perform reliability calculations based on sequential Monte Carlo simulations.

[0010] As a further aspect of the present invention, the diamond-shaped distribution network structure model constructed in step 1 includes a two-layer structure of a main network and a secondary network. Four K-type substations are connected in series between the substations on both sides. During normal operation, it operates in an open loop. The tie line between the second and third K-type substations is disconnected. After a fault occurs, the load between the substations can be transferred and power supply restored through the tie line.

[0011] The main network takes the K-type station, in which all incoming and outgoing lines are equipped with circuit breakers, as the core node. It adopts a dual-side power supply with four circuits for local power supply. All lines form a double-ring network structure with ring network connection, open-loop operation and self-healing function.

[0012] The secondary trunk network uses P-type substations, where all incoming and outgoing lines are equipped with ring network switches, as its core nodes, and load points are connected to the secondary trunk network P-type substations.

[0013] Loads within the area can be connected to secondary trunk network P-type substations or main trunk network switching stations according to their capacity; distributed energy resources can be connected to K-type or P-type substations according to their capacity.

[0014] As a further aspect of the present invention, the fault analysis strategy described in step 1 is as follows: considering the fault states of the K-type station bus, transmission lines, and distribution transformer components, a fault consequence analysis matrix is ​​generated based on the impact of each component's fault on the load points. It is assumed that the network has m components and n load points, where a ij This represents the impact of the failure of the i-th component on the j-th load point. If a ij =0 indicates no effect; if a ij =1 indicates that there is an impact, and the generated failure consequence analysis matrix D is:

[0015]

[0016] Based on this failure consequence analysis matrix, the impact of different components on the load point can be obtained when sequential Monte Carlo simulation of component failure, and then the system reliability index can be calculated.

[0017] As a further aspect of the present invention, in step 2,

[0018] When a fault occurs, if the upstream power grid cannot supply power to the microgrid, the microgrid will operate in islanded mode. In this case, ignoring the failure of photovoltaic and energy storage systems, we consider whether the output of photovoltaic and energy storage can meet the load demand within the microgrid. During islanded operation, we calculate the average outage time and average number of outages for load users through iterative calculations as follows.

[0019] Step 2.1, Initialization: Set the island running time to the shortest simulation duration to obtain the time when the upstream power grid fault occurs, and obtain the maximum island running time from the upstream power grid fault repair time;

[0020] Step 2.2, read the photovoltaic output power at time k Load demand Energy storage remaining power SOC k ;

[0021] Step 2.2, determine if Energy storage charging power Energy storage remaining power SOC k+1 =SOC k +P charge t. If Calculate the maximum output of the microgrid at this time. like P loss =0, if Point-of-load power loss

[0022] Step 2.4, calculate the number of users whose load points are cut off. Where N i Let i be the number of users at load point i. After a user is disconnected, that user will no longer be connected to the grid during this islanded operation. Calculate the average outage time for users at load point i.

[0023] Step 2.5, update the fault time k = k + 1, t s =t s +1. If t s ≥t s,max Exit islanded operation and calculate the average power outage time t for users at load points. e Average number of power outages at load points N i Let i be the number of users at load point i. If the maximum number of users to be cut is reached, otherwise return to step 2.2 to continue the simulation calculation.

[0024] As a further aspect of the present invention, step 3, which involves reliability calculation based on sequential Monte Carlo simulation, is as follows:

[0025] The sampling formulas for component fault-free operation time (TTF) and component repair time (TTR) are as follows, where λ is the component failure rate and μ is the component repair rate:

[0026]

[0027]

[0028] By sampling TTF and TTR alternately, and sampling the state of each component in the distribution network, the state change of the entire system over time can be obtained.

[0029] The system component status is sampled to obtain the system fault status. It is determined whether the affected load points can be restored to power supply through transfer. If power supply can be restored through transfer, the islanding operation time is the transfer time; otherwise, it is the component repair time. For the load points affected by the fault, the output of photovoltaic energy storage during islanding operation is simulated. The average power outage time and average number of power outages for users at the load points are calculated. Finally, the system reliability index is obtained.

[0030] As a further aspect of the present invention, the specific reliability assessment steps for a diamond-shaped power distribution network with m components are as follows:

[0031] Step 3.1: Initialize clock t=0, read in component parameters, load parameters, and network parameters;

[0032] Step 3.2: Randomly generate m random numbers uniformly distributed between [0,1]. Based on the failure rate λ and repair rate μ of different components, obtain the fault-free operating time (TTF) of the components.

[0033] Step 3.3: Obtain the minimum TTF, determine the fault type and impact based on the faulty component, and obtain the component repair time (TTR) by taking a random number based on the component repair rate and substituting it into the component status sampling formula.

[0034] Step 3.4: Obtain the area affected by this fault, the affected load points are operating in islanded mode, and collect information such as the power outage time and number of power outages for each load point;

[0035] Step 3.5: Update time t = t + TTR + TTF, and determine if time t has reached the simulation lifespan T. If not, return to step 3.2. If it has, calculate the reliability indicators for each load point and the system.

[0036] Compared with the prior art, the present invention, employing the above technical solution, has the following technical effects:

[0037] 1. Existing methods for power system reliability calculation lack effective means to handle large-scale renewable energy integration. While traditional analytical methods are highly accurate when renewable energy is not integrated, they often fail to provide accurate calculations after renewable energy is added. This invention considers the diamond-shaped distribution network structure and employs a calculation method based on sequential Monte Carlo simulation. By simulating the time series of renewable energy output and system faults, the accuracy of reliability calculations is ensured.

[0038] 2. Existing research on power system reliability calculation methods often requires analytical methods to ensure rapid calculation of reliability indicators. However, this method becomes inefficient as the system size increases, making it unsuitable for large-scale power system reliability calculations. The sequential Monte Carlo simulation method proposed in this invention generates a fault analysis matrix before calculation to accelerate efficiency. After a fault occurs, it simulates islanded operation of load points based on the consequences of the fault. Therefore, it balances the accuracy of the solution with the speed of calculation. Attached Figure Description

[0039] Figure 1 This is a flowchart of the diamond-shaped power distribution network reliability analysis and calculation method of the present invention;

[0040] Figure 2 This is a schematic diagram of a typical diamond-shaped power distribution network structure according to the present invention;

[0041] Figure 3 These are the load curves and photovoltaic output curves for two typical daily load points in summer and winter, as described in this embodiment of the invention. Detailed Implementation

[0042] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0043] like Figure 1 The flowchart shown is a process for calculating the reliability of a diamond-shaped distribution network considering large-scale photovoltaic energy storage integration, as described in this invention. The process includes the following steps:

[0044] Step 1: Construct the diamond-shaped distribution network structure model as follows.

[0045] A diamond-shaped urban distribution network is a hierarchical distribution network with a switching station at its core. A typical diamond-shaped distribution network structure is as follows: Figure 2 As shown. From the user's power supply perspective, the diamond-shaped urban distribution network constructs a "user-centric" distribution network. Whether it is the secondary trunk network 10kV ring substation providing power to low-voltage users or the main trunk network 10kV switching station providing power to medium-voltage users, any fault in any 10kV or higher public power grid line can be promptly transferred to ensure reliable power supply to users.

[0046] The diamond-shaped distribution network backbone uses a switch station (K-type station) with circuit breakers on all incoming and outgoing lines as its core node. It adopts a dual-power supply with four circuits for local power supply, and all lines form a double-ring network structure with ring network connection, open-loop operation, and self-healing function. The secondary backbone uses a ring station (P-type station) with ring network switches on all incoming and outgoing lines as its core node, and the load points are connected to the secondary backbone P-type station.

[0047] The network model considers components such as switchyard buses, transmission lines, and distribution transformers. A fault consequence analysis matrix is ​​generated based on the impact of each component's failure on the load points. Assume the network has m components and n load points, where a... ij This represents the impact of the failure of the i-th component on the j-th load point. If a ij =0 indicates no effect; if a ij =1 indicates that there is an impact, and the generated failure consequence analysis matrix D is:

[0048]

[0049] Based on this failure consequence analysis matrix, the impact of different components on the load point can be obtained when sequential Monte Carlo simulation of component failure, and then the system reliability index can be calculated.

[0050] Step 2: Construct the operating model of the photovoltaic energy storage microgrid system when a fault occurs, as follows.

[0051] When a fault occurs, if the upstream power grid cannot supply power to the microgrid, the microgrid will operate in islanded mode. In this case, we ignore the possibility of faults in the photovoltaic (PV) and energy storage systems, and only consider whether the output of the PV and energy storage can meet the load demand within the microgrid. During islanded operation, the average outage time and average number of outages for each load user are calculated using the following algorithm:

[0052] Step 2.1, Initialization: Set the islanding operation time and the shortest simulation duration to obtain the time when the upstream power grid fault occurs. Then, obtain the maximum islanding operation time from the upstream power grid fault repair time.

[0053] Step 2.2, read the photovoltaic output power at time k Load demand Energy storage remaining power SOC k

[0054] Step 2.3, determine if Energy storage charging power Energy storage remaining power SOC k+1 =SOC k +P charge t. If Calculate the maximum output of the microgrid at this time. like P loss =0, if Point-of-load power loss

[0055] Step 2.4, calculate the number of users whose load points are cut off. Where N iLet i be the number of users at load point i. After a user is disconnected, that user will no longer be connected to the grid during this islanded operation. Calculate the average outage time for users at load point i.

[0056] Step 2.5, update the fault time k = k + 1, t s =t s +1. If t s ≥t s,max Exit islanded operation and calculate the average power outage time t for users at load points. e Average number of power outages at load points N i Let i be the number of users at load point i. If the maximum number of users to be cut is reached, otherwise return to step 2.2 to continue the simulation calculation.

[0057] Step 3, reliability calculation based on sequential Monte Carlo simulation, is performed as follows:

[0058] The sampling formulas for component fault-free operation time (TTF) and component repair time (TTR) are as follows, where λ is the component failure rate and μ is the component repair rate:

[0059]

[0060]

[0061] By sampling TTF and TTR alternately, the cyclic process of the component state can be obtained as shown in the figure. Sampling the state of each component in the distribution network can obtain the state change of the entire system over time.

[0062] The system component states are sampled to obtain the system fault states. It is determined whether the affected load points can be restored to power through transfer. If power can be restored through transfer, the islanding operation time is the transfer time; otherwise, it is the component repair time. For the loads affected by the fault, the output of photovoltaic energy storage during islanding operation is simulated to calculate the average outage time and average number of outages for users at the load points. Finally, the system reliability index is obtained. The flowchart of the diamond-shaped distribution network reliability algorithm based on Monte Carlo simulation is shown in the figure.

[0063] For a diamond-shaped power distribution network with m components, the specific reliability assessment process is as follows:

[0064] Step 3.1: Initialize clock t=0, read in component parameters, load parameters, and network parameters.

[0065] Step 3.2: Randomly generate m random numbers uniformly distributed between [0,1]. Based on the failure rate λ and repair rate μ of different components, obtain the fault-free operating time (TTF) of the components.

[0066] Step 3.3: Obtain the minimum TTF, determine the fault type and impact based on the faulty component, and obtain the component repair time (TTR) by taking a random number based on the component repair rate and substituting it into the component status sampling formula.

[0067] Step 3.4: Obtain the area affected by this fault, the affected load points operating in islanded mode, and statistically analyze the outage time and number of outages for each load point.

[0068] Step 3.5: Update time t = t + TTR + TTF, and determine if time t has reached the simulation lifespan T. If not, return to step 3.2. If it has, calculate the reliability indicators for each load point and the system.

[0069] The following table, Table 1 to Table 2, shows the system parameters of a typical diamond-shaped distribution network structure.

[0070] Table 1 Component Failure Parameters

[0071] parameter Parameter value Cable failure rate (times / 100km) 0.84 Cable repair time (h) 8 Distribution transformer failure rate (times / year·unit) 0.00135 Transformer repair time (h) 36 Busbar failure rate (times / year) 0.0005 Busbar repair time (h) 36

[0072] Table 2 Automated power transfer time for different power distribution systems

[0073]

[0074]

[0075] Taking the aforementioned typical diamond-shaped distribution network structure as an example, it is assumed that each load point L in the system is equipped with a certain capacity of photovoltaic energy storage to maintain continuous power supply to users within the load point when a system failure occurs and power cannot be supplied to the load point. The time scale is set to 1 hour, and the total simulation period is set to 10,000 years. Typical load curves for summer and winter are considered, along with photovoltaic output as follows: Figure 3 As shown, when the maximum output of the photovoltaic system is equal to the maximum load on a typical summer day at that load point, it is said to be 100% capacity. Otherwise, the capacity is determined by the ratio of the maximum output of the photovoltaic system to the maximum load demand. The main technical indicators for reliability calculation are shown in Tables 3 and 4.

[0076] Table 3. Calculation results of reliability of one-hour isolation and power supply.

[0077] ASAI SAIDI SAIFI 0% capacity 99.99904％ 0.08352 0.01624 25% capacity 99.99918％ 0.07187 0.01339 50% capacity 99.99923％ 0.06729 0.01108 75% capacity 99.99934％ 0.05765 0.00762 100% capacity 99.99944％ 0.04912 0.00552

[0078] Table 4. Calculation results of 3-minute isolation and supply reliability

[0079] ASAI SAIDI SAIFI 0% capacity 99.99918％ 0.07105 0.01616 25% capacity 99.99931％ 0.06038 0.00165 50% capacity 99.99933％ 0.05803 0.00158 75% capacity 99.99941％ 0.05202 0.00142 100% capacity 99.99949％ 0.04436 0.00121

[0080] Calculation results show that after photovoltaic (PV) and energy storage are connected to the load points, the microgrid at the load points can operate in islanded mode during faults, ensuring power supply to users and reducing the average number and duration of power outages for users at the load points. Compared to the case without PV and energy storage, the system reliability indicators are improved. Furthermore, as PV capacity continues to increase, power supply reliability also improves, and the average power outage time and number of outages for users gradually decrease. The level of automation in different power distribution systems also affects system reliability.

[0081] The above embodiments are merely illustrative of the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solutions based on the technical concept proposed in this invention shall fall within the scope of protection of this invention.

Claims

1. A reliability calculation method for diamond-shaped distribution networks considering large-scale photovoltaic energy storage integration, characterized in that, Includes the following steps: Step 1: Construct a diamond-shaped distribution network structure model and formulate a fault analysis strategy; Step 2: Construct an operational model of the photovoltaic energy storage microgrid system when a fault occurs; Step 3: Perform reliability calculations based on sequential Monte Carlo simulations; The fault analysis strategy described in step 1 is as follows: Considering the fault states of the K-type substation bus, transmission lines, and distribution transformer components, a fault consequence analysis matrix is ​​generated based on the impact of each component's fault on the load points. It is assumed that the power grid has m components and n load points. This represents the impact of the failure of the i-th component on the j-th load point. Indicates no impact, if This indicates an impact; the generated failure consequence analysis matrix D is: Based on this failure consequence analysis matrix, the impact of different components on the load point can be obtained when sequential Monte Carlo simulation of component failure, and then the system reliability index can be calculated. In step 2, when a fault occurs, if the upstream power grid cannot supply power to the microgrid, the microgrid will operate in islanded mode. At this time, the failure of photovoltaic and energy storage is ignored, and the output of photovoltaic energy storage is considered to meet the load demand within the microgrid. During islanded operation, the average outage time and average number of outages for load users are calculated. The iterative calculation is as follows: Step 2.1, Initialization: Set the island running time to the shortest simulation duration to obtain the time when the upstream power grid fault occurs, and obtain the maximum island running time from the upstream power grid fault repair time; Step 2.2, Read the time Photovoltaic output power Load demand Remaining energy storage capacity ; Step 2.3, determine if Energy storage charging power Remaining energy storage capacity , like Calculate the maximum output of the microgrid at this time. ,like , ,like Load point power loss ; Step 2.4, calculate the number of users whose load points are cut off. ,in Let i be the number of users at load point i. After a user is disconnected, that user will no longer be connected to the grid during this islanded operation. Calculate the average outage time for users at load point i. ; Step 2.5, Update Fault Time , , like Exit islanded operation and calculate the average power outage time for users at load points. Average number of power outages at load points , Let i be the number of users at load point i. If the maximum number of users to be cut is reached, otherwise return to step 2.2 to continue the simulation calculation.

2. The reliability calculation method for a diamond-shaped distribution network considering large-scale photovoltaic energy storage access according to claim 1, characterized in that, The diamond-shaped distribution network structure model described in step 1 includes a two-layer structure of main network and secondary network. Four K-type substations are connected in series between the substations on both sides. During normal operation, it operates in an open loop. The tie line between the second and third K-type substations is disconnected. After a fault occurs, the load between the substations can be transferred and the power supply can be restored through the tie line. The main trunk network uses K-type substations with circuit breakers on all incoming and outgoing lines as the core node, adopts a dual-side power supply with four circuits for local power supply, and forms a double-ring network structure with ring network connection, open-loop operation and self-healing function for all lines; the secondary trunk network uses P-type substations with ring network switches on all incoming and outgoing lines as the core node, is connected by a single ring network, and is equipped with power distribution automation. Loads within the region can be connected to secondary trunk network P-type substations or main trunk network switching stations according to their capacity, and distributed energy resources can be connected to K-type substations or P-type substations according to their capacity.

3. The reliability calculation method for a diamond-shaped distribution network considering large-scale photovoltaic energy storage access according to claim 1, characterized in that, The reliability calculation method based on sequential Monte Carlo simulation in step 3 is as follows: The sampling formulas for component fault-free operation time (TTF) and component repair time (TTR) are as follows: For the failure rate of components, The component repair rate: By sampling TTF and TTR alternately, and sampling the state of each component in the distribution network, the state change of the entire system over time can be obtained. The system component states are sampled to obtain the system fault state. It is determined whether the affected load points can be restored to power supply through transfer. If power supply can be restored through transfer, the islanding operation time is the transfer time; otherwise, it is the component repair time. For the load points affected by the fault, the output of photovoltaic energy storage during islanding operation is simulated. The average power outage time and average number of power outages for users at the load points are calculated. Finally, the system reliability index is obtained.

4. The reliability calculation method for a diamond-shaped distribution network considering large-scale photovoltaic energy storage access according to claim 3, characterized in that, For a diamond-shaped power distribution network with m components, the specific reliability assessment steps are as follows: Step 3.1, Initialize the clock Read in component parameters, load parameters, and network parameters; Step 3.2: Randomly generate m random numbers uniformly distributed between [0,1], based on the failure rate of different components. With repair rate The TTF (Time To Failure) of the component is obtained. Step 3.3: Obtain the minimum TTF, determine the fault type and impact based on the faulty component, and obtain the component repair time (TTR) by taking a random number based on the component repair rate and substituting it into the component status sampling formula. Step 3.4: Obtain the area affected by this fault, the affected load points are operating in islanded mode, and collect information on the outage time and number of outages for each load point; Step 3.5, Update Time Determine if the simulation lifespan T has been reached within a certain time period. If not, return to step 3.

2. If it has, calculate the reliability indicators of each load point and the system.

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