Reliability evaluation method for high-voltage direct-current power transmission system containing high-proportion new energy

Abstract

The invention discloses a reliability evaluation method for a high-voltage direct-current power transmission system containing high-proportion new energy, and relates to the technical field of high-voltage direct-current power transmission systems.The reliability evaluation method comprises the steps that firstly, a reliability block diagram of a multi-terminal high-voltage direct-current power transmission system is constructed, and a subsystem division method is used for decomposing a complex system into smaller manageable subsystems; then, the reliability of the subsystems is analyzed through a state enumeration technology and a cascade network method, and reliability equivalent parameters, including the failure rate, the failure frequency and the repair time, of each subsystem are calculated; then, based on the internal connection relation of the subsystems, generating a system reliability block diagram, and calculating the reliability index of the whole system; in addition, the output fluctuation of the new energy base at the sending end and all possible system states are considered, the forced energy unavailability index of the receiving end is comprehensively calculated, and the overall reliability index of the system is synthesized.

Description

Technical Field

[0001] The present invention relates to the technical field of high-voltage direct current transmission systems, and in particular to a reliability assessment method for a high-voltage direct current transmission system containing a high proportion of new energy. Background Art

[0002] Western China has abundant clean energy resources such as wind power and solar energy, but due to the limitations of its own consumption capacity, target market, transmission channels and many other factors, it is difficult to transmit and consume the remaining clean energy. Combined with the national power supply and demand pattern and the timing of power development. It is recommended that new energy bases in southeastern Tibet and Qinghai be put into operation to provide DC power to the southern region. With the increase in transmission capacity and layout optimization, higher requirements are placed on the reliability of large-scale transmission terminal systems that constitute a considerable part of the new energy power base. However, its main circuit structure is complex and there are many devices, which brings difficulties to reliability assessment.

[0003] The main renewable energy sources include solar and wind. Due to the unpredictability of their output, renewable energy bases exhibit irregularity, volatility, and intermittency. Therefore, the reliability of large-scale systems that rely heavily on renewable energy must be evaluated and analyzed. The problem of calculating the failure rate of renewable energy power generation bases is rarely involved in the reliability assessment of large-scale systems at the receiving end. At present, the Monte Carlo method is often used to study and calculate the reliability indicators of wind and solar energy storage power generation systems, but the reliability assessment of wind and solar energy storage renewable energy power sources has not yet been included in the reliability analysis.

[0004] In addition, compared with traditional direct current, the characteristics of cross-provincial and cross-regional transmission have changed significantly. In order to optimize the use of transmission corridor resources to transport clean energy, more and more direct current transmission stations will be equipped with multi-terminal converter stations. Current research mainly studies single-supply high-voltage direct current systems, and pays relatively little attention to the electrical structure, operation mode and evaluation method of hybrid multi-terminal high-voltage direct current transmission system (Hybrid Multi-Terminal High-Voltage Direct Current transmission system, referred to as H-MSTDC).

[0005] In view of this, a reliability assessment method for HVDC transmission systems with a high proportion of renewable energy is needed to combine the deficiencies of these two types of research and improve the accuracy of reliability modeling of large-scale systems with a high proportion of renewable energy. Summary of the invention

[0006] In view of this, the purpose of this application is to study the reliability assessment of large-scale systems that contain a large part of renewable energy, propose an enhanced K-means clustering algorithm, and use the cluster efficacy index to derive typical renewable energy output scenarios. Secondly, the output characteristics of the generator set and the traditional wiring and operation mode of the H-MSTDC system are considered, and a failure rate calculation model for a renewable energy power generation base is established. The failure rate calculation model obtains the reliability index of the system. The impact of the proportion of key equipment and renewable energy units on system reliability is clarified. Typical scenario analysis provides operating data and potential risk factors, laying the foundation for the construction and verification of the failure rate calculation model. In turn, the failure rate calculation model can predict and evaluate possible failures in these typical scenarios, help optimize the design and operation and maintenance of the power generation base, reduce the occurrence of failures, and improve power generation efficiency and reliability.

[0007] In order to achieve the above objectives, this application provides the following technical solutions:

[0008] The reliability block diagram of the multi-channel DC transmission system was constructed by using the subsystem division method. The state capacity of the system was analyzed by using the series-parallel network method and the state enumeration method. The reliability index of each receiver was calculated in combination with the capacity allocation coefficient.

[0009] Due to the complexity of hybrid multi-terminal HVDC systems, based on the idea of ​​subsystem division, Figure 1 The topology shown is transformed into Figure 2 Reliability block diagram shown. Figure 3 The results of converting it into capacity representation using a system reliability block diagram are shown. Figure 4 It is the series and parallel connection of each block diagram and represents the transmission capacity of the components in the reliability block diagram. The calculation formula is as follows:

[0010] C 31 =min(C 3 +C 4 ,C 23 )

[0011] C 32 =min(C 5 +C 6 ,C 24 )

[0012] C 33 =C 7 +C 8

[0013] C 34 =C 9 +C 10

[0014] C 35 =min(C11 ,C 13 +C 14 )

[0015] C 36 =min(C 12 ,C 15 +C 16 )

[0016] Among them C i express Figure 2 Reliability block diagram of the transmission capacity of the component, where i represents the component serial number.

[0017] The steps for reliability assessment of H-MSTDC system are as follows:

[0018] Step 1: Divide the HVDC system into multiple subsystems according to the subsystem division method.

[0019] Step 2: Using the state enumeration technology, analyze and calculate the reliability of the subsystem according to the connection relationship of the internal components of each subsystem, so as to determine the reliability equivalent characteristics of each subsystem.

[0020] Step 3: Consider the impact of the subsystem on the overall system reliability and generate a system reliability block diagram. In order to calculate the reliability equivalent parameters of the components described in the reliability block diagram, the series and parallel network method is used. Once the connection relationship of each subsystem is determined, the reliability index of the subsystem can be calculated using the series and parallel relationship, including failure rate, failure frequency and maintenance time. That is, the reliability equivalent parameters of each component in the reliability block diagram are calculated using the reliability equivalent parameters of the subsystem.

[0021] Step 4: According to the H-MSTDC reliability block diagram and the internal connection relationship of each subsystem, analyze the transmission capacity under this state and calculate the system reliability index.

[0022] According to the reliability equivalent parameters of each component in the reliability block diagram, such as the equivalent failure rate λ e and the equivalent repair time r e , the forced downtime rate of the component can be determined.

[0023]

[0024] λ e is the equivalent failure rate, r e Equivalent maintenance time

[0025] Step 5: Based on the state enumeration, considering the output fluctuation of the renewable energy power base at the sending end and all power outage events k, calculate the forced energy unavailability index of the receiving end 1 By combining all events, the forced energy unavailability ratio is calculated. As shown below.

[0026]

[0027] Q R1 (k) represents the probability that the receiving end 1 is in system state k, G R1 (k) represents the ratio of the available transmission capacity to the rated transmission capacity when the receiving end 1 is in system state k.

[0028] Step 6: In the ergodic system, for the receiver 1, the frequency f of the system entering state k is obtained according to the state space equation k , as shown below.

[0029]

[0030] λ i and r j represent the component failure rate and maintenance time of the component in failure event k respectively.

[0031] Step 7: By synthesizing all events with the same transmission capacity, the probability and frequency of the system state capacity are obtained. In addition, according to the operation mode of the multi-terminal system and the frequency of the corresponding event set in Table 1, indicators such as unipolar and bipolar forced outage rates can be obtained. MOT Take the following example to calculate the unipolar forced downtime rate index of receiving end 1: Therefore, the system's single-pole forced outage rate indicator system

[0032]

[0033] In the formula, and are the single-pole forced power outage rates of receiving end 1 and receiving end 2, respectively.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] This application provides a reliability assessment method for a high-voltage direct current transmission system containing a high proportion of renewable energy. First, by constructing a reliability block diagram of a multi-terminal high-voltage direct current transmission system, the subsystem partitioning method is used to decompose the complex system into smaller, manageable subsystems. Then, the reliability of these subsystems is analyzed using state enumeration technology and cascade network methods, and the reliability equivalent parameters of each subsystem, including failure rate, failure frequency, and repair time, are calculated. Next, based on the internal connection relationship of the subsystem, a system reliability block diagram is generated, and the reliability index of the entire system is calculated. In addition, this section also considers the output fluctuations of the new energy base at the transmitting end, as well as all possible system states, comprehensively calculates the forced energy unavailability index at the receiving end, and synthesizes the overall reliability index of the system. Finally, taking China's Qinggui DC transmission project as an example, the effectiveness of the proposed reliability assessment model is verified, and the impact of the proportion of new energy units and extreme geographical environment on system reliability is analyzed, providing a reference for actual projects. Through this method, a decision support tool can be provided for the reliability assessment of large-scale power systems that rely on renewable energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for the specific embodiments or the description of the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn according to the actual scale.

[0037] Figure 1 It is the line diagram of H-MSTDC system;

[0038] Figure 2 It is the reliability block diagram of H-MSTDC system;

[0039] Figure 3 Transmission capacity block diagram for H-MSTDC system;

[0040] Figure 4 This is a simplified HVDC system capacity block diagram. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0043] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0044] It should be further understood that the term "and / or" used in the present description and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0045] The technical solution of the present invention will be further described below in conjunction with the accompanying drawings of the present invention.

[0046] First, the key characteristics of wind power are selected. Large-scale wind power grid connection affects the power balance and peak balance of the system. In view of the large variability and strong unpredictability of wind power, according to the output characteristics of the wind power curve, the feature vector containing the following five wind power characteristic indicators is selected.

[0047] ① Maximum daily wind power output

[0048]

[0049] ②Average daily wind power generation

[0050]

[0051] ③ Daily peak output rate of wind power

[0052]

[0053] ④Daily peak-to-valley difference rate

[0054]

[0055] ⑤ Daily fluctuation range of wind power

[0056]

[0057] is the wind power output at each moment, T is the number of moments in a day, N w is the wind force curve number, L pis the number of time periods during which the output reaches 80% of the peak value, L z is the total number of time periods in a day.

[0058] Then the key characteristics of photovoltaic power generation are selected. Since the output of photovoltaic power generation is more regular and stable than that of wind power, only three indicators are selected as its characteristic indicators to participate in clustering.

[0059] ① Maximum daily photovoltaic power generation

[0060]

[0061] ②Average daily photovoltaic power generation

[0062]

[0063] ③ Daily peak photovoltaic output rate

[0064]

[0065] is the photovoltaic output at each moment.

[0066] After clarifying the wind and solar characteristic indicators, the key characteristic indicators are weighted based on the entropy weight method. When each dimension is regarded as a feature, the load and wind power statistics collected by the smart grid contain many redundant features. Analyzing all the features will increase the complexity of the model and prolong the operation time. Therefore, it is necessary to comprehensively evaluate the feature combination based on the power data, and then optimize the feature combination and delete the redundant features. The entropy weight calculation formula of the characteristic indicators used here is

[0067]

[0068] Among them, v i Represents the characteristic index information entropy value, and the total information E is based on Calculated.

[0069] After clarifying the characteristic indicators of wind and solar power and weighting the key indicators, the wind and solar output profiles were reduced in dimension according to the proposed characteristic indicators of the new energy power supply base. Subsequently, the K-means clustering algorithm was implemented. The specific steps are as follows.

[0070] Step 1: Input historical data of new energy power supply bases, especially wind power and photovoltaic output data.

[0071] Step 2: Use the wind and solar index calculation formula proposed above to calculate the characteristic values ​​of photovoltaic output and wind power output.

[0072] Step 3: Objectively assign attributes to wind power and photovoltaic power.

[0073] Step 4: Set the expected cluster number K and initialize the wind power and photovoltaic cluster numbers.

[0074] Step 5: Based on the K-means algorithm, the two classes with the closest distance are classified into one class, and the distance between the newly generated class and the old class is recalculated.

[0075] Step 6: Determine the number of wind power and photovoltaic clusters, K w ,K p Is it equal to the expected number of clusters K. If the number of clusters is equal to K, the cycle ends; otherwise, re-execute step 5.

[0076] Step 7: Output K w Typical wind power output scenarios and K p Typical photovoltaic output scenario.

[0077] Next, a failure rate model for a new energy power generation base is established. In traditional wind turbine reliability models, it is usually assumed that the failure rate of a wind turbine is not affected by external variables, so it is set to a constant value. But in fact, wind speed and wind load have a great impact on components such as wind turbine blades. A large part of all failures are caused by the failure of these components. Therefore, the impact of wind load on the failure rate must be considered.

[0078] The wind load is:

[0079] Where: w k is the measured wind load; v k is wind speed; z is the wind vibration coefficient; μ z is the coefficient of variation of wind pressure height; μ s is the shape coefficient, ρ is the air density. There is a linear relationship between the wind speed failure rate and the wind load as λ w =k f w k +b f , where the parameter k f ,b f They are:

[0080]

[0081] Among them, λ min represents the failure rate associated with the cut-off wind speed, λ max represents the failure rate associated with the cut-off wind speed, ν co and ν ci It is used to determine the working status of wind turbines at different wind speeds.

[0082] The failure rate model of photovoltaic power station is established taking into account the local failure of photovoltaic array components.2 State model. Currently, if the PV power station is in operation, the operation state will be transferred, and the number of states that may be reached is M 2 (including transition to its own state i). The probability of reaching state j is P ij It can be obtained by the following formula.

[0083]

[0084] λ ij represents the transition rate from the current state i to the next state j, n ij Represents the number of transitions from state i to state j.

[0085] Then the reliability indexes of each receiving end of the H-MSTDC system are proposed, among which the single-pole interruption time The calculation formula for partial unipolar interruption time is: Bipolar power-off time Partial bipolar power-off time Energy availability This indicator measures the energy level transmitted by the HVDC transmission system in a given period of time. Among them, the equivalent outage hours of derating operation is the number of outage hours converted according to the rated transmission capacity. The corresponding energy unavailable is P EU =1-P EA , the above is the reliability index of H-MSTDC system.

[0086] After obtaining the system reliability index, the system reliability evaluation will be carried out. The steps for the H-MSTDC system reliability evaluation are as follows:

[0087] Step 1: Divide the HVDC system into multiple subsystems according to the subsystem division method. The specific subsystem division steps are:

[0088] 1.1 Identify the main components: Identify all the main components in the system, such as converter stations, DC lines, AC side equipment, etc.

[0089] 1.2 Based on function division: Group the components according to their functions to form preliminary subsystems, such as converter station subsystem, line subsystem, etc.

[0090] 1.3 Consider physical connections: Further refine the subsystem based on the physical connections of the components to ensure that the components in the same subsystem are physically connected to each other.

[0091] 1.4 Evaluate interdependencies: Determine dependencies between subsystems and, if necessary, adjust subsystem boundaries to reflect these dependencies.

[0092] Step 2: Use the state enumeration technique to analyze and calculate the reliability of the subsystems based on the connection relationship between the internal components of each subsystem, so as to determine the reliability equivalent characteristics of each subsystem. The state enumeration technique is a system analysis method that involves identifying and listing all possible states in the system and then evaluating the reliability of each state. The main steps are:

[0093] 2.1: Define the system state and determine all possible operating and fault states in the subsystem. Each state represents a different combination of devices in the subsystem and their operating conditions.

[0094] 2.2: Use binary notation or other methods to list all possible states of the subsystem.

[0095] 2.3: Calculate the reliability of each state, which usually involves determining the product of the reliabilities of all the devices operating in that state. If the devices are in series, then the reliability of the state is the product of the reliabilities of all the devices operating. If the devices are in parallel, then the reliability of the state is 1 minus the probability that all devices fail.

[0096] 2.4: Determine which states are feasible, i.e., states in which the subsystem can perform its functions. Eliminate infeasible states in which the subsystem cannot operate.

[0097] 2.5: Add up the reliabilities of all feasible states to get the total reliability of the subsystem. If necessary, the average reliability of the subsystem can be calculated by considering the probability of each state occurring.

[0098] The above completes the calculation and analysis of system reliability by state enumeration technology. After the reliability analysis and calculation of the subsystems, the process of determining the equivalent characteristics of the reliability of each subsystem involves simplifying the complex structure of each subsystem into an equivalent single component that can represent the impact of the entire subsystem on the reliability of the entire system.

[0099] Step 3: Consider the impact of the subsystem on the overall system reliability and generate a system reliability block diagram. The specific steps are as follows:

[0100] First, based on the reliability analysis of the subsystems, the reliability parameters of each subsystem, such as failure rate, repair time, and availability, are determined. These parameters are obtained through the state enumeration in step 2. Next, the connection relationships between subsystems are identified, including whether they are connected in series or in parallel.

[0101] Then, these connections are used to construct the reliability block diagram of the system. In the block diagram, each subsystem is represented by a box, and its reliability parameters are marked in the box.

[0102] In order to calculate the reliability equivalent parameters of the components described in the reliability block diagram, the series and parallel network methods are used. The subsystems connected in series are connected by straight lines, indicating that their reliabilities are multiplied. If the subsystems are connected in series, the reliability of the overall system is the product of the reliabilities of the individual subsystems. Assume that there are three subsystems, and their reliabilities are R 1 ,R 2 ,R 3 , then the overall reliability calculation formula of the system is: R total,a =R 1 ×R 2 ×R 3 , R total,a Indicates the overall reliability of the series system.

[0103] Subsystems connected in parallel are represented by branch lines, indicating that their reliability is calculated by subtracting the failure probability of all subsystems from 1. Assume there are three subsystems, and their reliabilities are R 4 ,R 5 ,R 6 , then the overall reliability calculation formula of the system is: R total,b =1-(1-R 1 )×(1-R 2 )×(1-R 3 ), R total,b Indicates the overall reliability of the system.

[0104] Once the connection relationship of each subsystem is determined, the reliability index of the subsystem can be calculated using the series-parallel relationship, including the failure rate, failure frequency and maintenance time. That is, the reliability equivalent parameters of each component in the reliability block diagram are calculated using the reliability equivalent parameters of the subsystem.

[0105] Step 4: According to the H-MSTDC reliability block diagram and the internal connection relationship of each subsystem, analyze the transmission capacity under this state and calculate the system reliability index.

[0106] According to the reliability equivalent parameters of each component in the reliability block diagram, such as the equivalent failure rate λ e and the equivalent repair time r e , the forced downtime rate of the component can be determined.

[0107]

[0108] Taking receiving end 1 as an example, the probability of being in system state k is:

[0109]

[0110] Among them, k,up ,Ψ k,downare the sets of available and unavailable components corresponding to failure event k, respectively, and F i 、F j are the equivalent forced downtime rates of the available component set and the unavailable component set in failure event k, respectively.

[0111] Step 5: Based on the state enumeration, considering the output fluctuation of the renewable energy power base at the sending end and all power outage events k, calculate the forced energy unavailability index of the receiving end 1 By combining all events, the forced energy unavailability ratio is calculated. As shown below.

[0112]

[0113] Q R1 (k) represents the probability that the receiving end 1 is in system state k, G R1 (k) represents the ratio of the available transmission capacity to the rated transmission capacity when the receiving end 1 is in system state k

[0114] Step 6: In the ergodic system, for the receiver 1, the frequency f of the system entering state k is obtained according to the state space equation k , as shown below.

[0115]

[0116] λ i and r j represent the component failure rate and maintenance time of the component in failure event k respectively.

[0117] Step 7: By synthesizing all events with the same transmission capacity, the probability and frequency of the system state capacity are obtained. In addition, according to the operation mode of the multi-terminal system and the frequency of the corresponding event set in Table 1, indicators such as unipolar and bipolar forced outage rates can be obtained. MOT Take the following as an example to calculate the unipolar forced downtime rate index of receiving end 1: Therefore, the system's single-pole forced outage rate indicator system

[0118]

[0119] In the formula, and are the single-pole forced power outage rates of receiving end 1 and receiving end 2, respectively. Specifically, the formula involves the frequency f of the system entering different states k , which is a parameter based on the impact of the failure rate of key equipment and the proportion of new energy units on the system in the previous analysis. It reflects the impact of the proportion of key equipment and new energy units on system reliability, and is therefore used as a system reliability evaluation indicator.

[0120] Table 1 H-MSTDC system operation mode (partial)

[0121] Terminal converter station 1 Terminal converter station 2 System outage type System capacity (%) Bipolar power off Bipolar power off Bipolar power off 0 Bipolar power off 3 / 4 double pole power off Bipolar power off 12.5 Bipolar power off Single pole power off Bipolar power off 25 Bipolar power off 1 / 4 double pole power off Bipolar power off 25 Bipolar power off 1 / 4 single pole power off Bipolar power off 37.5 Bipolar power off normal Bipolar power off 50 … … … … normal Bipolar power off Bipolar power off 50 normal 3 / 4 poles power off Partial Bipolar Power Off 62.5 normal Single pole power off Single pole power outage 75 normal 1 / 4 double pole power off Partial Bipolar Power Off 75 normal 1 / 4 single pole power off Partial single-pole power outage 87.5 normal normal Normal operation 100

[0122] Since then, the reliability assessment of the DC transmission system containing a high proportion of renewable energy has been completed.

[0123] The reliability assessment method of the new energy direct current transmission system designed by the present invention takes into account the uncertainty of the output of new energy and the correlation between the actual output and the predicted output of new energy. Based on the actual historical output values ​​and predicted values, a conditional probability distribution model of the new energy output is established, which complements the traditional new energy output point prediction method. This method is of great significance for the planning, scheduling and energy storage capacity determination of power systems containing new energy. It can effectively evaluate the key restricted transmission channels of the new energy direct current transmission system under different extreme weather scenarios, and propose a coordinated scheduling strategy to improve the transmission capacity of the transmission channels.

[0124] Those of ordinary skill in the art will appreciate that the units of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition of each example has been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0125] In the embodiments provided by the present invention, it should be understood that the division of units is only a logical function division, and there may be other division methods in actual implementation, for example, multiple units can be combined into one unit, one unit can be split into multiple units, or some features can be ignored, etc.

[0126] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0127] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-0nly Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0128] 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 aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A reliability assessment method for a high-voltage direct current transmission system containing a high proportion of renewable energy, firstly establishing H-MSTDC system reliability indicators, including single-pole outage time and double-pole power outage time, characterized in that: The following steps are also included: According to the subsystem division method, the HVDC system is divided into multiple subsystems; Using state enumeration technology, the reliability of subsystems is calculated according to the connection relationship of the internal components of each subsystem; Considering the impact of subsystems on the overall system reliability, generate the system H-MSTDC reliability block diagram; According to the H-MSTDC reliability block diagram and the internal connection relationship of each subsystem, calculate the system reliability index; Based on the state enumeration, the output fluctuation of the renewable energy power base at the sending end and all power outage events k are comprehensively considered to calculate the forced energy unavailability index at the receiving end Then, by integrating all events, the forced energy unavailable ratio is calculated. By combining all events with the same transmission capacity, the probability and frequency of the system state capacity are obtained.

2. The reliability assessment method of a high-voltage direct current power transmission system containing a high proportion of renewable energy according to claim 1 is characterized in that: According to the subsystem division method, the specific steps of dividing the HVDC system into multiple subsystems are as follows: Identify all major components in the system, including converter stations, DC lines, and AC side equipment; Group the components according to their functions to form preliminary subsystems, including converter station subsystem and line subsystem; Further refine the subsystem based on the physical connections of the components to ensure that the components in the same subsystem are physically connected to each other; Identify dependencies between subsystems.

3. The reliability assessment method of a high-voltage direct current transmission system containing a high proportion of renewable energy according to claim 2 is characterized in that: Using the state enumeration technology, the specific steps for calculating the reliability of the subsystem according to the connection relationship of the internal components of each subsystem are as follows: Define system states and identify all possible operating and failure states in the subsystems; List all possible states of the subsystem using binary notation or other methods; Calculate the reliability of each state. If the devices are connected in series, then the reliability of the state is the product of the reliabilities of all running devices. If the devices are connected in parallel, then the reliability of the state is 1 minus the probability that all devices fail. Determine which states are feasible, that is, the states in which the subsystem can perform its functions, and exclude those infeasible states in which the subsystem cannot operate. The total reliability of the subsystem is obtained by adding up the reliabilities of all feasible states.

4. The reliability assessment method of a high-voltage direct current power transmission system containing a high proportion of renewable energy according to claim 3 is characterized in that: Considering the impact of subsystems on the overall system reliability, the steps to generate the system H-MSTDC reliability block diagram are as follows: Based on the reliability analysis of the subsystems, determine the reliability parameters of each subsystem, including failure rate, repair time and availability obtained through state enumeration; Identify the connections between subsystems, including whether they are connected in series or parallel; Use these connections to build a reliability block diagram of the system, in which each subsystem is represented by a box; Series and parallel network methods, series-connected subsystems are connected by straight lines, indicating that their reliabilities are multiplied, while parallel-connected subsystems are represented by branch lines, indicating that their reliabilities are calculated by subtracting the probability of failure of all subsystems from 1; The reliability indexes of the subsystem are calculated using the series-parallel relationship, including failure rate, failure frequency and maintenance time.

5. The reliability assessment method of a high-voltage direct current power transmission system containing a high proportion of renewable energy according to claim 4 is characterized in that: According to the H-MSTDC reliability block diagram and the internal connection relationship of each subsystem, the specific steps for calculating the system reliability index are as follows: According to the reliability equivalent parameters of each component in the reliability block diagram, including the equivalent failure rate λ e and the equivalent repair time r e , determine the forced outage rate of the component, as follows: Taking receiving end 1 as an example, the probability of being in system state k is: Among them, k,up , k,down are the sets of available and unavailable components corresponding to failure event k, respectively, and F i 、F j are the equivalent forced downtime rates of the available component set and the unavailable component set in failure event k, respectively.

6. The reliability assessment method of a high-voltage direct current power transmission system containing a high proportion of renewable energy according to claim 5 is characterized in that: Forced energy unavailable index of receiver 1 and forced energy unavailability ratio As follows: In the formula, Q R1 (k) represents the probability that the receiving end 1 is in system state k, G R1 (k) represents the ratio of the available transmission capacity to the rated transmission capacity when the receiving end 1 is in system state k.

7. The reliability assessment method of a high-voltage direct current power transmission system containing a high proportion of renewable energy according to claim 1 is characterized in that: The following steps are also included: According to the system operation mode and the frequency of the corresponding event set, the unipolar and bipolar forced shutdown rates are obtained, and the unipolar forced shutdown event set Ω MOT Take the following example to calculate the unipolar forced downtime rate index of receiving end 1: And the system's single-pole forced outage rate indicator system In the formula, and are the single-pole forced power outage rates of receiving end 1 and receiving end 2, respectively.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the reliability assessment method for a high-voltage direct current transmission system containing a high proportion of renewable energy as described in any one of claims 1 to 7.

9. A processor, characterized in that: The processor is used to run a program, wherein the program, when running, executes the reliability assessment method for a high-voltage direct current transmission system containing a high proportion of renewable energy as described in any one of claims 1 to 7.

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