Capacity configuration evaluation method for offshore wind power direct current collection system

Abstract

The invention provides an offshore wind power direct current collection system capacity configuration evaluation method, device and equipment, and belongs to the field of power system planning. According to the embodiment of the invention, the planning scheme of the offshore wind power direct current collection system is evaluated from multiple dimensions of efficiency, economy and reliability, and the defect that only a single index is focused in the prior art is overcome; meanwhile, establishing a standardized evaluation process, converting each evaluation index into a quantifiable score according to a preset relationship between each evaluation index and the score, determining a weight corresponding to each evaluation index by adopting an analytic hierarchy process, and obtaining a comprehensive score of the planning scheme through weighted summation; finally, the target planning scheme is screened out from the multiple planning schemes according to the comprehensive score, interference of human subjective factors on the evaluation result is avoided, the comparison of the multiple planning schemes has a unified benchmark, the evaluation result has higher credibility, repeatability and comparability, and a scientific basis is provided for engineering decision making.

Description

Technical Field

[0001] This application belongs to the field of power system planning, and in particular relates to a method, apparatus and equipment for capacity configuration assessment of offshore wind power DC collection systems. Background Technology

[0002] In recent years, with the increasing global demand for clean energy and the comprehensive development and utilization of marine resources, offshore wind power, as an important form of renewable energy, has seen rapid expansion in its construction scale. Against this backdrop, the planning of offshore wind power DC collection systems, as well as the selection and optimization of planning schemes, have become crucial steps before the implementation of wind farm projects.

[0003] In related technologies, the evaluation of planning schemes for offshore wind power DC collection systems often relies on the empirical threshold method. The core defect of this method is that it does not fully couple the multi-dimensional constraints of the power system, focuses only on economic evaluation indicators for decision-making, and the evaluation results are highly subjective. It is difficult to adapt to the differentiated engineering needs of deep-sea wind power, thus restricting the large-scale and high-quality development of offshore wind power DC collection systems. Summary of the Invention

[0004] This application provides a method, apparatus, and equipment for evaluating the capacity configuration of offshore wind power DC collection systems. It can evaluate the planning schemes of offshore wind power DC collection systems from multiple dimensions such as efficiency, economy, and reliability. At the same time, it adopts a standardized evaluation process to select the target planning scheme from multiple planning schemes, avoiding the interference of human subjective factors on the evaluation results. This makes the comparison of multiple planning schemes have a unified benchmark, and the evaluation results are more credible, repeatable, and comparable, providing a scientific basis for engineering decision-making.

[0005] In a first aspect, embodiments of this application provide a method for evaluating the capacity configuration of an offshore wind power DC collection system, the screening method comprising: Obtain the target parameters corresponding to each of the multiple offshore wind power DC aggregation system planning schemes. The target parameters include the rated capacity, topology, equipment parameters, fault parameters, and cost parameters of the offshore wind power DC aggregation system. For each offshore wind power DC collection system planning scheme, the evaluation indicators of the offshore wind power DC collection system planning scheme are determined according to the target parameters. The evaluation indicators include efficiency evaluation indicators, economic evaluation indicators and reliability evaluation indicators. Based on each evaluation indicator and the pre-defined relationship between each evaluation indicator and the score, the first score corresponding to the efficiency evaluation indicator, the second score corresponding to the economic evaluation indicator, and the third score corresponding to the reliability evaluation indicator are determined. The Analytic Hierarchy Process (AHP) was used to determine the first weight of the efficiency evaluation index, the second weight of the economic evaluation index, and the third weight of the reliability evaluation index. Based on the first weight, the second weight, and the third weight, the first score, the second score, and the third score are weighted and summed to obtain the comprehensive score of the offshore wind power DC collection system planning scheme. Based on the comprehensive scores of various offshore wind power DC collection system planning schemes, the target offshore wind power DC collection system planning scheme is selected from multiple offshore wind power DC collection system planning schemes.

[0006] In some embodiments, the efficiency evaluation index includes the total power loss rate, and the equipment parameters include cable parameters and wind turbine parameters. Accordingly, based on the target parameters, the efficiency evaluation index of the offshore wind power DC collection system planning scheme is determined, including: Based on the topology, determine the number of target cables, the number of fans gathered on each target cable, and the spacing between the fans; The network power loss is determined based on the number of target cables, cable parameters, the number of wind turbines connected to each target cable, and the spacing between the wind turbines. In addition, the power loss of the fans is determined based on the number of fans and the parameters of the fans gathered on each target cable; The total power loss is obtained based on the network power loss and the wind turbine power loss; Determine the total power loss rate based on the total power loss and rated capacity.

[0007] In some embodiments, cable parameters include the number of cables and cable resistivity, and fan parameters include the fan output current value. Accordingly, based on the number of target cables, cable parameters, the number of fans connected to each target cable, and fan spacing, the network power loss is determined, including: The current and resistance values ​​flowing through the target cables are determined based on the number of fans gathered on each target cable, the fan spacing, the fan output current value, and the cable resistivity. Determine the power loss of the target cable based on its current and resistance values; Based on the number of target cables, the power loss of each target cable is summed to obtain the network power loss.

[0008] In some embodiments, the topology includes a chain topology. Accordingly, the current and resistance values ​​flowing through the target cables are determined based on the number of fans gathered on each target cable, the fan spacing, the output current value, and the cable resistivity, including: Based on the number of fans and the output current of each fan on each target cable, determine the number of segments of the target cable and the current value of each segment. In addition, the resistance value of each section is determined based on the fan spacing and cable resistivity; Based on the current and resistance values ​​of the target cable, determine the power loss of the target cable, including: The power loss of the target cable is determined by the number of segments, the current value and resistance value of each segment.

[0009] In some embodiments, the power loss of the target cable is determined by the number of segments, the current value on each segment, and the resistance value, including: The power loss of the target cable is calculated using the following formula: in, This indicates the power loss of the target cable. Indicates the first The resistance values ​​of the segments, Indicates the flow through the first The segmented current values, Indicates the number of segments in the target cable.

[0010] In some embodiments, reliability evaluation indicators include utilization rate, equipment parameters further include equipment type and the number of devices of each type, and failure parameters include the annual average failure rate and average repair time of each type of equipment. Accordingly, based on the target parameters, reliability evaluation indicators for the offshore wind power DC collection system planning scheme are determined, including: The minimum cut set method is used to calculate the annual average failure rate, average repair time and number of devices for each type of equipment by multiplication, so as to obtain the annual power outage time of the corresponding type of equipment. The annual power outage time of various equipment is summed up to obtain the total annual power outage time of the offshore wind power DC collection system. The utilization rate is determined based on the total annual power outage time and total annual operating time of the offshore wind power DC collection system.

[0011] In some embodiments, determining the utilization rate based on the annual total power outage time and annual total operating time of the offshore wind power DC collection system includes: The utilization rate is calculated using the following formula: in, This indicates the utilization rate. Indicates the first The number of devices of this type Indicates the first The average annual power outage time for a single device in this category of equipment. Indicates the first Annual power outage time for this type of equipment This represents the total annual power outage time of the offshore wind power DC collection system. This indicates the total number of all types of equipment. This indicates the total annual working time of a single device. This indicates the total annual operating time of the offshore wind power DC collection system.

[0012] In some embodiments, the analytic hierarchy process (AHP) is used to determine the first weight corresponding to the efficiency evaluation index, the second weight corresponding to the economic evaluation index, and the third weight corresponding to the reliability evaluation index, including: Obtain scale values ​​for efficiency evaluation indicators, economic evaluation indicators, and reliability evaluation indicators. The scale values ​​are determined based on the relative importance of the efficiency evaluation indicators, economic evaluation indicators, and reliability evaluation indicators. Based on the scale values, construct a judgment matrix; Based on the judgment matrix, the preliminary weight vector is calculated using the geometric mean method. The preliminary weight vector includes the first preliminary weight, the second preliminary weight, and the third preliminary weight. If the judgment matrix passes the consistency test, the first preliminary weight is determined as the first weight, the second preliminary weight is determined as the second weight, and the third preliminary weight is determined as the third weight.

[0013] Secondly, embodiments of this application also provide a screening device for planning schemes of offshore wind power DC collection systems, the device comprising: The acquisition module is used to acquire the target parameters corresponding to each of the multiple offshore wind power DC aggregation system planning schemes. The target parameters include the rated capacity, topology, equipment parameters, fault parameters and cost parameters of the offshore wind power DC aggregation system. The first determining module is used to determine the evaluation indicators of each offshore wind power DC collection system planning scheme based on the target parameters. The evaluation indicators include efficiency evaluation indicators, economic evaluation indicators and reliability evaluation indicators. The second determining module is used to determine the first score corresponding to the efficiency evaluation index, the second score corresponding to the economic evaluation index, and the third score corresponding to the reliability evaluation index based on each evaluation index and the preset relationship between each evaluation index and the score. The third determination module is used to determine the first weight corresponding to the efficiency evaluation index, the second weight corresponding to the economic evaluation index, and the third weight corresponding to the reliability evaluation index using the analytic hierarchy process. The fourth determination module is used to perform a weighted summation of the first score, the second score, and the third score based on the first weight, the second weight, and the third weight to obtain a comprehensive score for the offshore wind power DC collection system planning scheme. The fifth determination module is used to select the target offshore wind power DC collection system planning scheme from multiple offshore wind power DC collection system planning schemes based on the comprehensive score of each offshore wind power DC collection system planning scheme.

[0014] Thirdly, embodiments of this application also provide an electronic device, which includes: a processor and a memory storing computer program instructions; When the processor executes computer program instructions, it implements any of the above-mentioned methods for evaluating the capacity configuration of offshore wind power DC collection systems.

[0015] Fourthly, embodiments of this application also provide a computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement any of the above-described methods for evaluating the capacity configuration of offshore wind power DC collection systems.

[0016] Fifthly, embodiments of this application also provide a computer program product, wherein the instructions in the computer program product, when executed by the processor of an electronic device, enable the electronic device to execute any of the above-described offshore wind power DC collection system capacity configuration evaluation methods.

[0017] This application provides a method, apparatus, and equipment for evaluating the capacity configuration of offshore wind power DC collection systems. It evaluates planning schemes for offshore wind power DC collection systems from multiple dimensions, including efficiency, economy, and reliability, overcoming the shortcomings of related technologies that focus only on a single indicator. Simultaneously, it establishes a standardized evaluation process. Based on the preset relationship between each evaluation indicator and its score, it transforms each evaluation indicator into a quantifiable score and uses the analytic hierarchy process (AHP) to determine the weights of each indicator. A weighted summation is then used to obtain a comprehensive score for the planning scheme. Finally, based on the comprehensive score, a target planning scheme is selected from multiple planning schemes. This avoids interference from subjective human factors in the evaluation results, provides a unified benchmark for comparing multiple planning schemes, and makes the evaluation results more credible, repeatable, and comparable, providing a scientific basis for engineering decisions. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating a method for evaluating the capacity configuration of an offshore wind power DC collection system provided in an embodiment of this application. Figure 2 This is a flowchart illustrating "determining the efficiency evaluation index of the offshore wind power DC collection system planning scheme based on target parameters" provided in an embodiment of this application. Figure 3 yes Figure 2 The diagram shows a detailed process flow diagram of S122; Figure 4This is a schematic diagram of the structure of a target cable provided in an embodiment of this application; Figure 5 This is a flowchart illustrating "determining the reliability evaluation index of the offshore wind power DC collection system planning scheme based on target parameters" provided in an embodiment of this application. Figure 6 yes Figure 1 A detailed flowchart of S140 in the screening method for offshore wind power DC collection system planning schemes is shown. Figure 7 This is a schematic diagram of the structure of a screening device for a planning scheme of an offshore wind power DC collection system provided in an embodiment of this application; Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0020] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0021] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0022] As the global energy structure accelerates its transition to a low-carbon model, offshore wind power is becoming a core growth engine in the renewable energy sector at an unexpected pace. However, as development extends to the deep sea, more than 80 kilometers offshore, the technological bottlenecks of traditional AC transmission systems are becoming increasingly apparent. Theoretical studies show that when the transmission distance exceeds 100 kilometers, the capacitive charging power of AC cables will account for more than 15% of the total system capacity, leading to a significant decrease in line transmission efficiency and a significant increase in the risk of transient overvoltage. Even more challenging is the fact that the output characteristics of deep-sea wind farms differ significantly from those of near-shore wind farms. The power fluctuations of deep-sea wind farms are much greater than those of near-shore wind farms, and the range of power fluctuations also varies considerably across different sea areas. These spatiotemporal heterogeneities impose differentiated requirements on the capacity margin design of offshore wind power aggregation systems.

[0023] In related technologies, the planning schemes for offshore wind power DC collection systems mostly rely on the empirical threshold method. The core defect of this method is that it does not fully couple the multi-dimensional constraints of the power system, focuses only on a single indicator for decision-making, and the evaluation results are highly subjective. It is difficult to adapt to the differentiated engineering needs of deep-sea wind power, thus restricting the large-scale and high-quality development of offshore wind power DC collection systems.

[0024] Currently, the high cost of engineering investment has become a key factor restricting the promotion and application of flexible DC wind power grid connection technology in my country. Moreover, with the development of offshore wind power in deep-sea and far-sea areas, the impedance characteristics are complex, and stability problems such as broadband harmonic oscillations are prone to occur between wind farms and converter stations, increasing the probability of system instability and endangering the safety and stability of the grid connection system and even the onshore AC main grid. With the large-scale development and centralized access of offshore wind power, this problem will become increasingly serious.

[0025] To address the aforementioned technical issues, this application provides a method, apparatus, and equipment for evaluating the capacity configuration of offshore wind power DC collection systems. This method evaluates planning schemes for offshore wind power DC collection systems from multiple dimensions, including efficiency, economy, and reliability, overcoming the shortcomings of related technologies that focus only on a single indicator. Furthermore, it establishes a standardized evaluation process, transforming each evaluation indicator into a quantifiable score based on a pre-defined relationship between the indicator and the score. The analytic hierarchy process (AHP) is used to determine the weights of each indicator, and a weighted summation is used to obtain a comprehensive score for the planning scheme. Finally, the target planning scheme is selected from multiple schemes based on the comprehensive score. This avoids interference from subjective human factors in the evaluation results, ensuring a unified benchmark for comparing multiple planning schemes. The evaluation results are more credible, repeatable, and comparable, providing a scientific basis for engineering decisions.

[0026] The following describes the selection method for the planning scheme of offshore wind power DC collection system provided in the embodiments of this application.

[0027] Figure 1This application illustrates a method for evaluating the capacity configuration of an offshore wind power DC collection system, as provided in an embodiment of this application. (Refer to...) Figure 1 The capacity configuration assessment method for offshore wind power DC collection systems may include the following steps: S110~S160.

[0028] S110. Obtain the target parameters corresponding to each of the multiple offshore wind power DC collection system planning schemes.

[0029] The target parameters may include the rated capacity, topology, equipment parameters, fault parameters, and cost parameters of the offshore wind power DC collection system. The rated capacity can be measured in megawatts (MW) or gigawatts (GW).

[0030] The rated capacities of different offshore wind power DC collection system planning schemes (hereinafter referred to as "planning schemes") may be equal or unequal, and this is not limited here.

[0031] The topology can include a topology diagram and a layout diagram, which can be used to determine information such as cable connection methods, cable lengths, and equipment spacing.

[0032] Equipment parameters can include parameters of various devices in the system (such as electrical and physical parameters). For example, equipment parameters can include cable parameters and fan parameters. Cable parameters include physical parameters such as cable grade, cable length, and cross-sectional area. Fan parameters can include electrical parameters such as fan input power, fan output power, fan output current, and bus output voltage, and can also include physical parameters such as the number of fans and fan spacing.

[0033] Fault parameters may include the annual average failure rate and average repair time for each type of equipment in the system.

[0034] Cost parameters may include the expected investment cost for each year, the discount rate, and the evaluation period.

[0035] For example, taking a planning scheme with a rated capacity of 2016MW as an example, the rated output power of a single wind turbine is 14MW, requiring 144 wind turbines. Taking a planning scheme with a rated capacity of 2000MW as an example, the rated output power of a single wind turbine is 10MW, requiring 200 wind turbines. The rated capacities of the two schemes are different, as are the rated output power of a single wind turbine and the number of wind turbines. Consequently, there will be differences in the topology, equipment parameters, fault parameters, and cost parameters of the two planning schemes. Even two planning schemes with the same rated capacity may have differences in their topology, equipment parameters, fault parameters, and cost parameters.

[0036] S120. For each offshore wind power DC collection system planning scheme, the evaluation indicators of the offshore wind power DC collection system planning scheme shall be determined according to the target parameters. The evaluation indicators include efficiency evaluation indicators, economic evaluation indicators and reliability evaluation indicators.

[0037] In this step, the evaluation index for each planning scheme is determined based on the target parameters such as rated capacity, topology, equipment parameters, fault parameters, and cost parameters obtained from S110.

[0038] S130. Based on each evaluation indicator and the preset relationship between each evaluation indicator and the score, determine the first score corresponding to the efficiency evaluation indicator, the second score corresponding to the economic evaluation indicator, and the third score corresponding to the reliability evaluation indicator.

[0039] Taking efficiency evaluation indicators as an example, the efficiency level can be determined based on the specific value of the efficiency evaluation indicator and the preset relationship between the efficiency evaluation indicator and the efficiency level. Furthermore, based on the preset relationship between the efficiency level and the first score, the third score corresponding to the efficiency evaluation indicator can be determined. Alternatively, a preset relationship between the efficiency evaluation indicator and the first score can be established in advance; based on the specific value of the efficiency evaluation indicator, the first score corresponding to the efficiency evaluation indicator can be obtained.

[0040] For example, the efficiency evaluation index may include the total power loss rate, and the efficiency evaluation index is set to include five levels: poor, poor, average, good, and good. The value ranges of the index corresponding to the five levels are: [>11%, 11%), [11%, 10%), [10%, 8.5%), [8.5%, 6.5%), [6.5%, <5%]}.

[0041] Taking economic evaluation indicators as an example, the economic level can be determined based on the specific values ​​of the economic evaluation indicators and the preset relationship between the economic evaluation indicators and the economic levels. Furthermore, based on the preset relationship between the economic level and the second score, the third score corresponding to the economic evaluation indicator can be determined. Alternatively, a preset relationship between the economic evaluation indicators and the second score can be established in advance; based on the specific values ​​of the efficiency evaluation indicators, the second score corresponding to the economic evaluation indicators can be obtained.

[0042] For example, the economic evaluation index may include the investment cost per unit capacity (unit: RMB 10,000 per megawatt). The economic evaluation index is set to include five levels: {poor, relatively poor, average, relatively good, good}. The value ranges of the index corresponding to the five levels are: [<350, 350), [350, 300), [300, 250), [250, 200), [200, <200).

[0043] Taking reliability evaluation indicators as an example, the reliability level can be determined based on the specific values ​​of the reliability evaluation indicators and the preset relationship between the reliability evaluation indicators and the reliability levels. Furthermore, the third score corresponding to the reliability evaluation indicator can be determined based on the preset relationship between the reliability level and the third score. Alternatively, a preset relationship between the reliability evaluation indicators and the third score can be established in advance; based on the specific values ​​of the reliability evaluation indicators, the third score corresponding to the reliability evaluation indicators can be obtained.

[0044] For example, the reliability evaluation index includes utilization rate. The reliability evaluation index is set to include five levels: poor, poor, average, good, and good. The value ranges of the index corresponding to the five levels are: (<96.7%, 96.7%), (96.7%, 96.72%), (96.72%, 96.74%), (96.74%, 96.76%), and (96.76%, >96.76%).

[0045] In this step, each evaluation indicator is converted into a quantifiable score based on the preset relationship between each evaluation indicator and the score.

[0046] S140. Using the analytic hierarchy process (AHP), determine the first weight corresponding to the efficiency evaluation index, the second weight corresponding to the economic evaluation index, and the third weight corresponding to the reliability evaluation index.

[0047] In this step, the weights of efficiency evaluation indicators, economic rating indicators, and reliability evaluation indicators are determined using the analytic hierarchy process (AHP). Compared with traditional weight determination methods such as experience-based allocation and subjective scoring, this approach ensures that the weight allocation not only meets the actual needs of offshore wind power projects but also has repeatable quantitative support, thus avoiding the interference of experience bias on the comprehensive evaluation results.

[0048] Furthermore, different offshore wind power projects have different requirements for the three evaluation indicators. For example, deep-sea projects have higher reliability requirements, while areas with scarce wind resources have higher efficiency requirements. The Analytic Hierarchy Process (AHP) can generate weights that are suitable for offshore wind power projects by adjusting the scaling values ​​of pairwise comparisons, thus solving the problem of detailed requirements for different offshore wind power projects and matching the weight allocation with project needs.

[0049] S150 calculates a weighted sum of the first, second, and third scores based on the first, second, and third weights to obtain a comprehensive score for the offshore wind power DC collection system planning scheme.

[0050] In this step, for each planning scheme, the first product of the first score and the first weight, the second score and the second weight, and the third product of the third score and the third weight are calculated. Then, the first, second, and third products are summed to determine the comprehensive score for each planning scheme. The comprehensive scores of multiple planning schemes are obtained through the same standardized scoring process, ensuring a unified benchmark for comparing multiple planning schemes.

[0051] Based on the comprehensive scores of various offshore wind power DC collection system planning schemes, S160 selects the target offshore wind power DC collection system planning scheme from multiple offshore wind power DC collection system planning schemes.

[0052] This application adopts a standardized evaluation process during the project planning stage to evaluate multiple planning schemes from multiple dimensions such as efficiency, reliability, and economics, and selects the optimal scheme from multiple planning schemes as the target offshore wind power DC collection system planning scheme, so as to propose a more efficient, economical, safe and reliable grid connection scheme to promote the rapid development of offshore wind power.

[0053] The capacity configuration evaluation method for offshore wind power DC collection systems provided in this application evaluates planning schemes for offshore wind power DC collection systems from multiple dimensions, including efficiency, economy, and reliability, thus overcoming the shortcomings of related technologies that focus only on a single indicator. Simultaneously, a standardized evaluation process is established. Based on the preset relationship between each evaluation indicator and its score, each evaluation indicator is transformed into a quantifiable score. The analytic hierarchy process (AHP) is used to determine the weights corresponding to each evaluation indicator. A weighted summation is then used to obtain a comprehensive score for the planning scheme. Finally, based on the comprehensive score, the target planning scheme is selected from multiple planning schemes. This avoids interference from subjective human factors in the evaluation results, provides a unified benchmark for comparing multiple planning schemes, and makes the evaluation results more credible, repeatable, and comparable, thus providing a scientific basis for engineering decisions.

[0054] In one embodiment, the efficiency evaluation index includes the total power loss rate, and the equipment parameters include cable parameters and wind turbine parameters. Accordingly, "determining the efficiency evaluation index of the offshore wind power DC collection system planning scheme based on the target parameters" may include the following steps: S121~S125, such as... Figure 2 As shown.

[0055] S121 determines the number of target cables, the number of fans gathered on each target cable, and the fan spacing based on the topology.

[0056] The topology can be represented in the form of a topology diagram, a layout diagram, or connection relationships. Network power loss is mainly affected by the system topology. Based on the topology diagram or connection relationships, it is necessary to determine the number of target cables in the DC collection system and the number of wind turbines collected on each target cable. Combined with the layout diagram, the spacing between two adjacent wind turbines (i.e., the wind turbine spacing) can be obtained.

[0057] S122. Determine the network power loss based on the number of target cables, cable parameters, the number of fans gathered on each target cable, and the fan spacing.

[0058] Among them, network power loss can refer to the transmission loss generated by cables in a DC collection system during the power transmission process.

[0059] In this step, the length of each target cable can be obtained based on the number of fans gathered on each target cable and the spacing between the fans. Then, the resistance value of each target cable can be determined by combining the cable parameters (such as cable resistivity). Based on the resistance value and current value of each target cable, the power loss of each target cable can be obtained. By superimposing the power losses of all target cables, the network power loss can be obtained.

[0060] S123. Determine the fan power loss based on the number of fans and fan parameters gathered on each target cable.

[0061] The fan parameters may include the fan's rated power and efficiency. The fan efficiency can be calculated based on the parameters provided in the equipment manufacturer's manual. The fan parameters may also include the number of fans in the DC collection system, or the number of fans in the DC collection system can be determined based on the number of fans collected on each target cable and the number of target cables.

[0062] In this step, the power loss of a single fan is calculated based on the rated power and efficiency of the fan. Combined with the number of fans in the DC collection system, the power loss of the fans is obtained.

[0063] S124. Based on the network power loss and the wind turbine power loss, the total power loss is obtained.

[0064] In this step, the sum of the network power loss and the wind turbine power loss is calculated. The sum can be directly determined as the total power loss, or the product of the sum and a preset coefficient can be used as the total power loss.

[0065] S125. Determine the total power loss rate based on the total power loss and rated capacity.

[0066] In this step, the ratio of total power loss to rated capacity is calculated, and this ratio is determined as the total power loss rate.

[0067] The capacity configuration evaluation method for offshore wind power DC collection systems provided in this application uses the total power loss rate as an efficiency evaluation index. Based on the core parameters of the planning scheme (such as rated capacity, topology and equipment parameters), the grid power loss and wind turbine power loss are calculated respectively to obtain the total power loss. The total power loss is then normalized by combining the rated capacity, which enables the comparison of cross-capacity schemes and makes the efficiency evaluation more scientific.

[0068] In one embodiment, cable parameters include the number of cables and cable resistivity, and fan parameters include the fan output current value; accordingly, Figure 2 S122 may include the following steps: S1221~S1223, such as Figure 3 As shown.

[0069] S1221. Determine the current and resistance values ​​flowing through the target cable based on the number of fans gathered on each target cable, the fan spacing, the fan output current value, and the cable resistivity.

[0070] In this step, the length of each target cable can be obtained based on the number of fans collected on each target cable and the spacing between the fans. Then, combined with the cable resistivity, the resistance value of each target cable can be determined. Based on the number of fans collected on each target cable and the output current value of the fans, the current value flowing through the target cable can be determined.

[0071] S1222. Determine the power loss of the target cable based on its current and resistance values.

[0072] In this step, the power loss of each target cable is calculated according to the current and resistance values ​​of the target cable and the preset power calculation formula.

[0073] S1223. Based on the number of target cables, sum the power losses of each target cable to obtain the network power loss.

[0074] The number of target cables is less than or equal to the number of cables. All cables in the DC bundling system can be identified as target cables, or only the cables in the main trunk line can be identified as target cables.

[0075] In this step, the power losses of all target cables are weighted and summed to obtain the network power loss.

[0076] The capacity configuration evaluation method for offshore wind power DC collection systems provided in this application calculates the grid power loss based on the core parameters of the target cable and wind turbine, so that the efficiency evaluation index can truly reflect the operating efficiency of the system, and at the same time improve the reliability of the calculation of grid power loss.

[0077] In one embodiment, the topology includes a chain topology, and accordingly, S1221 may include the following steps: determining the number of segments of the target cable and the current value on each segment based on the number of fans gathered on each target cable and the fan output current value; and determining the resistance value of each segment based on the fan spacing and the cable resistivity.

[0078] The number of segments in the target cable is equal to the number of wind turbines connected to it. Along the direction of power transmission, the current value in each segment of the target cable gradually increases. For example, such as... Figure 4 As shown, the target cable 2 adopts a chain topology, which gathers 8 wind turbines 1. The target cable 2 is divided into eight segments 21. Along the direction of power transmission (from left to right), the current values ​​of each segment 21 on the target cable 2 are i, 2i, 3i, 4i, 5i, 6i, 7i and 8i, respectively.

[0079] The distance between two adjacent wind turbines is approximately equal to the length of the segment between them. Therefore, the length of each segment can be determined based on the turbine distance, and then the resistance value of each segment can be obtained based on its length and the cable resistivity. The resistance value of each segment is positively correlated with its length; the longer the segment, the greater the resistance value.

[0080] It should be noted that, Figure 4 This illustration merely demonstrates that the output current of each wind turbine 1 is i, and does not constitute a limitation on the screening method for the offshore wind power DC collection system planning scheme provided in this application embodiment. In other embodiments, the output current of each wind turbine 1 may be equal or unequal, and the lengths of each segment 21 may be equal or unequal, which are not limited here.

[0081] S1222 may include the following steps: determining the number of segments of the target cable, the current value and resistance value of each segment, and determining the power loss of the target cable.

[0082] Due to the influence of the topology, the current intensity flowing through different segments is different, that is, the current value is different, and therefore the power loss of each segment is also different. First, the power loss of each segment is obtained based on the current value and resistance value of each segment. Then, the power loss of all segments is superimposed to obtain the power loss of the target cable.

[0083] In this embodiment, considering the characteristics of current gradient distribution in a chain topology, the target cable is divided into multiple segments based on the number of wind turbines and the spacing between them. The current and resistance values ​​of each segment are determined, and the power loss of each segment is accurately calculated based on the current and resistance values. By summing the power losses of each segment, the power loss of the target cable is obtained, which helps to improve the accuracy of loss calculation for the chain topology.

[0084] As an example, the number of segments in the target cable, the current value and resistance value on each segment, determine the power loss of the target cable, including: The power loss of the target cable is calculated using formula (1): (1) in, This indicates the power loss of the target cable. Indicates the first The resistance values ​​of the segments, Indicates the flow through the first The segmented current values, Indicates the number of segments in the target cable.

[0085] In this embodiment, the differences in current and resistance values ​​of each segment of the chain topology are fully considered to affect the power loss of the target cable, thereby improving the accuracy of the calculation results and enabling the calculation structure to accurately reflect the true efficiency level of the chain system.

[0086] For example, such as Figure 4 As shown, eight fans 1 are gathered on the target cable. The output current value of each fan 1 is equal to i. Accordingly, the target cable 1 is divided into eight segments. Along the direction of power transmission (from left to right), the current values ​​of each segment 21 are i, 2i, 3i, 4i, 5i, 6i, 7i and 8i, respectively. The power loss of the target cable can be calculated using formula (2).

[0087] (2) in, , ... These represent the resistance values ​​of each segment 21.

[0088] In one embodiment, reliability evaluation indicators include utilization rate, equipment parameters also include equipment type and the number of devices of each type, and fault parameters include the annual average failure rate and average repair time of each type of equipment. Accordingly, "determining the reliability evaluation indicators of the offshore wind power DC collection system planning scheme based on the target parameters" may include the following steps: S126~S128, such as... Figure 5 As shown.

[0089] S126. Using the minimum cut set method, the annual average failure rate, average repair time and number of devices for each type of equipment are multiplied to obtain the annual power outage time for the corresponding type of equipment.

[0090] Among them, the minimal cut set method refers to a method that identifies all minimal cut sets in a DC collection system, quantifies the risk of system failure caused by each cut set, and finally obtains a comprehensive system reliability evaluation index.

[0091] Annual average failure rate refers to the average number of failures that occur per unit of equipment per year. Mean time to repair (MTBT) refers to the average time it takes for equipment to return to normal operation after a failure. Both annual average failure rate and MTBT can be obtained through at least one of the following methods: industry data, manufacturer information, and practical operation and maintenance experience.

[0092] In this step, the average annual power outage time for a single device within a certain type of equipment is obtained by multiplying the average annual failure rate by the average repair time. Multiplying this by the number of devices in that type gives the annual power outage time for that type of equipment. This step calculates the annual power outage time for each type of equipment separately.

[0093] S127. The annual power outage time of various types of equipment is summed to obtain the total annual power outage time of the offshore wind power DC collection system.

[0094] In this step, the annual power outage time of each type of equipment obtained in step S126 is summed to obtain the total annual power outage time of the offshore wind power DC collection system.

[0095] S128. Determine the utilization rate based on the total annual power outage time and total annual operating time of the offshore wind power DC collection system.

[0096] In this step, the ratio of the total annual power outage time to the total annual working time can be calculated first to obtain the failure rate of the offshore wind power DC collection system, and then the utilization rate of the offshore wind power DC collection system can be obtained.

[0097] In this embodiment, the utilization rate is calculated using the minimum cut set method based on the annual average failure rate, average repair time, and number of devices. This method is closely related to the devices in the DC aggregation system and closely combines the system operation characteristics with actual engineering needs. It can accurately identify the combination of key failed devices (i.e., the minimum cut set) in the DC aggregation system and, to a certain extent, reflect the coupling failure risk of the DC aggregation system.

[0098] As an example, utilization is determined based on total annual power outage time and total annual operating time, including: The utilization rate is calculated using formula (3): (3) in, This indicates the utilization rate. Indicates the first The number of devices of this type Indicates the first The average annual power outage time for a single device in this category of equipment. Indicates the first Annual power outage time for this type of equipment This represents the total annual power outage time of the offshore wind power DC collection system. This indicates the total number of all types of equipment. This indicates the total annual working time of a single device. This indicates the total annual operating time of the offshore wind power DC collection system.

[0099] As an example, the total annual working hours of a single device It is 8760 hours, which means continuous work throughout the year.

[0100] This embodiment provides a unified formula for calculating utilization rate, making the utilization rate calculation process traceable and preventing subjective factors from interfering with reliability evaluation indicators.

[0101] In one embodiment, the economic evaluation index includes the total discounted value of investment, and the cost parameters include the expected investment cost, discount rate, and evaluation period for each year. Accordingly, "determining the economic evaluation index of the candidate planning scheme based on the target parameters" may include the following steps: using the discount method, discounting the expected investment cost for each year to the investment year at a certain discount rate to obtain the discounted value of investment for each year; and summing the discounted values ​​of investment for each year to obtain the total discounted value of investment.

[0102] The economic evaluation indicator can use the full life-cycle cost of the project, which includes initial costs and future costs. Initial costs refer to the costs that will be incurred before the project is operational, i.e., construction costs, which include capital investment costs, purchase and installation costs. Future costs refer to the costs incurred from the start of operation of the project until its dismantling, including energy costs, operating costs, maintenance and repair costs, replacement costs, and residual value (including any resale, salvage, or disposal costs).

[0103] In this embodiment, the present value method is used for evaluation. Future costs are discounted to the investment year according to a certain discount rate, and the total present value of the investment years is used to evaluate the overall cost of the project.

[0104] As an example, the total discounted value of the investment can be calculated using formula (4).

[0105] (4) in: Represents the total discounted value of the investment. Indicates the first The expected investment cost for the year Indicates the discount rate. Indicates the evaluation period. As an example, the discount rate... The value is 8%.

[0106] In one embodiment, Figure 1 S140 may include the following steps: S141~S144, such as Figure 6As shown.

[0107] S141. Obtain the scale values ​​of efficiency evaluation indicators, economic evaluation indicators, and reliability evaluation indicators. The scale values ​​are determined based on the relative importance of the efficiency evaluation indicators, economic evaluation indicators, and reliability evaluation indicators.

[0108] In this step, the three evaluation indicators are compared pairwise, and the scale values ​​of the two indicators are determined according to their relative importance. For example, the reliability of a deep-sea project is more important than its economics, so the scale value of the reliability evaluation indicator relative to the economics evaluation indicator can be determined to be 3, while the scale value of the economics evaluation indicator relative to the reliability evaluation indicator can be 1 / 3.

[0109] S142. Based on the scaling values, establish a judgment matrix.

[0110] In this step, a judgment matrix is ​​constructed based on the scaling values ​​of each evaluation indicator.

[0111] For example, this application uses three evaluation indicators to construct a 3×3 judgment matrix, where all diagonal elements of the judgment matrix are 1. The element in the first row and second column is the scale value of the first evaluation indicator relative to the second evaluation indicator, and the element in the second row and first column is the scale value of the second evaluation indicator relative to the first indicator. The two scale values ​​are reciprocals of each other. The element in the first row and third column is the scale value of the first evaluation indicator relative to the third evaluation indicator, and the element in the third row and first column is the scale value of the third evaluation indicator relative to the first indicator. The two scale values ​​are reciprocals of each other. The element in the second row and third column is the scale value of the second evaluation indicator relative to the third evaluation indicator, and the element in the third row and second column is the scale value of the third evaluation indicator relative to the second indicator. The two scale values ​​are reciprocals of each other.

[0112] S143. Based on the judgment matrix, the preliminary weight vector is calculated using the geometric mean method. The preliminary weight vector includes the first preliminary weight, the second preliminary weight, and the third preliminary weight.

[0113] In this step, the product of the elements in each row of the judgment matrix is ​​calculated first, and then the geometric mean of the product of the elements in each row is calculated. For example, if this application uses three evaluation indicators, the cube root of the product of the elements in each row is calculated. Finally, the geometric mean of the elements in each row is normalized to obtain the preliminary weight vector.

[0114] S144. If the judgment matrix passes the consistency test, the first preliminary weight is determined as the first weight, the second preliminary weight is determined as the second weight, and the third preliminary weight is determined as the third weight.

[0115] In this step, the largest eigenvalue of the judgment matrix is ​​first determined based on the judgment matrix and the preliminary weight vector. Then, based on the largest eigenvalue and the number of evaluation indicators, a consistency index is determined. Next, the ratio of the consistency index to the average random consistency index is calculated. If the ratio is less than or equal to the consistency ratio, the judgment matrix passes the consistency test, and the weight allocation logic is consistent. The first preliminary weight is then determined as the first weight, the second preliminary weight as the second weight, and the third preliminary weight as the third weight. If the ratio is greater than a preset threshold, the judgment matrix fails the consistency test. The scale values ​​of each evaluation indicator need to be adjusted, a new judgment matrix is ​​constructed, and the preliminary weight vector is recalculated until the judgment matrix passes the consistency test. The first preliminary weight corresponding to this judgment matrix is ​​then determined as the first weight, the second preliminary weight as the second weight, and the third preliminary weight as the third weight.

[0116] As an example, "determining the largest eigenvalue of the judgment matrix based on the judgment matrix and the initial weight vector" may include the following steps: multiply the judgment matrix and the initial weight vector to obtain the product corresponding to each element, then calculate the ratio of the product of each element to the corresponding element, and the average of the three ratios is the largest eigenvalue of the judgment matrix.

[0117] In other implementations, the judgment matrix can be first subjected to a consistency check, and the weight vector can be calculated based on the judgment matrix that satisfies the consistency check. The weight vector includes a first weight, a second weight, and a third weight.

[0118] For example, a consistency test is performed on the judgment matrix A, and the test results are shown in Table 1. The maximum eigenvalue λmax of the judgment matrix is ​​3.06, the consistency index CI is 0.0324, the average random consistency index RI is 0.58, and the ratio of the consistency index CI to the average random consistency index RI is 0.055, which is less than the consistency ratio CR. Therefore, the judgment matrix is ​​determined to satisfy the consistency test.

[0119] The eigenvector V corresponding to the largest eigenvalue λmax of the judgment matrix A that satisfies the consistency test is normalized and standardized to obtain the weight vector W=[0.6491, 0.0719, 0.2790] (reliability, efficiency, economy) of the three evaluation indicators.

[0120] Table 1. Results of the consistency test of the judgment matrix In this embodiment, the qualitative judgment of the relative importance of indicators is transformed into quantitative weights, clarifying the weights corresponding to each evaluation indicator. This ensures that the weight allocation not only aligns with the actual needs of offshore wind power projects but also has repeatable quantitative support, avoiding the interference of experience biases on the comprehensive evaluation results. Furthermore, by introducing a consistency verification mechanism, the determined first, second, and third weights are ensured to be logically consistent, thereby improving the accuracy of the screening results.

[0121] Based on the offshore wind power DC collection system capacity configuration evaluation method provided in the above embodiments, this application also provides a specific implementation of the offshore wind power DC collection system capacity configuration evaluation device. Please refer to the following embodiments.

[0122] First see Figure 7 This application provides a capacity configuration evaluation device for an offshore wind power DC collection system. The device includes: an acquisition module 201, a first determination module 202, a second determination module 203, a third determination module 204, a fourth determination module 205, and a fifth determination module 206.

[0123] The acquisition module 201 is used to acquire the target parameters corresponding to each of the multiple offshore wind power DC collection system planning schemes. The target parameters include the topology, equipment parameters, fault parameters and cost parameters of the offshore wind power DC collection system; each offshore wind power DC collection system planning scheme corresponds to a different rated capacity.

[0124] The first determining module 202 is used to determine the evaluation indicators of each offshore wind power DC collection system planning scheme based on the target parameters. The evaluation indicators include efficiency evaluation indicators, economic evaluation indicators and reliability evaluation indicators. The second determining module 203 is used to determine the first score corresponding to the efficiency evaluation index, the second score corresponding to the economic evaluation index, and the third score corresponding to the reliability evaluation index based on each evaluation index and the preset relationship between each evaluation index and the score. The third determination module 204 is used to determine the first weight corresponding to the efficiency evaluation index, the second weight corresponding to the economic evaluation index, and the third weight corresponding to the reliability evaluation index using the analytic hierarchy process. The fourth determining module 205 is used to perform a weighted summation of the first score, the second score, and the third score based on the first weight, the second weight, and the third weight to obtain a comprehensive score for the offshore wind power DC collection system planning scheme. The fifth determination module 206 is used to select the target offshore wind power DC collection system planning scheme from multiple offshore wind power DC collection system planning schemes based on the comprehensive score of each offshore wind power DC collection system planning scheme.

[0125] In one embodiment, the efficiency evaluation index includes the total power loss rate, and the equipment parameters include cable parameters and fan parameters. Accordingly, the first determining module is further configured to: determine the number of target cables, the number of fans gathered on each target cable, and the fan spacing based on the topology; determine the network power loss based on the number of target cables, cable parameters, the number of fans gathered on each target cable, and fan spacing; determine the fan power loss based on the number of fans gathered on each target cable and fan parameters; obtain the total power loss based on the network power loss and fan power loss; and determine the total power loss rate based on the total power loss and rated capacity.

[0126] In one embodiment, the cable parameters include the number of cables and the cable resistivity, and the fan parameters include the fan output current value. Accordingly, the first determining module is further configured to: determine the current value and resistance value flowing through the target cable based on the number of fans gathered on each target cable, the fan spacing, the fan output current value, and the cable resistivity; determine the power loss of the target cable based on the current value and resistance value of the target cable; and sum and calculate the power loss of each target cable based on the number of target cables to obtain the network power loss.

[0127] In one embodiment, the topology includes a chain topology, and accordingly, the first determining module is further configured to: determine the number of segments of the target cable and the current value on each segment based on the number of fans gathered on each target cable and the fan output current value; and determine the resistance value of each segment based on the fan spacing and the cable resistivity.

[0128] The first determining module is also used to: determine the number of segments in the target cable, the current value and resistance value on each segment, and determine the power loss of the target cable.

[0129] In one embodiment, the first determining module is further configured to calculate the power loss of the target cable using formula (1): (1) in, This indicates the power loss of the target cable. Indicates the first The resistance values ​​of the segments, Indicates the flow through the first The segmented current values, Indicates the number of segments in the target cable.

[0130] In one embodiment, the reliability evaluation index includes utilization rate, and the equipment parameters also include equipment type and the number of equipment in each type. The fault parameters include the annual average failure rate and average repair time of each type of equipment. Accordingly, the first determining module is further configured to: use the minimum cut set method to multiply the annual average failure rate, average repair time and number of equipment in each type of equipment to obtain the annual power outage time of the corresponding type of equipment; sum up the annual power outage times of all types of equipment to obtain the total annual power outage time of the offshore wind power DC collection system; and determine the utilization rate based on the total annual power outage time and total annual working time of the offshore wind power DC collection system.

[0131] In one embodiment, the first determining module is also used to calculate the utilization rate using formula (3): (3) in, This indicates the utilization rate. Indicates the first The number of devices of this type Indicates the first The average annual power outage time for a single device in this category of equipment. Indicates the first Annual power outage time for this type of equipment This represents the total annual power outage time of the offshore wind power DC collection system. This indicates the total number of all types of equipment. This indicates the total annual working time of a single device. This indicates the total annual operating time of the offshore wind power DC collection system.

[0132] In one embodiment, the third determining module is further configured to: obtain scale values ​​of efficiency evaluation indicators, economic evaluation indicators, and reliability evaluation indicators, wherein the scale values ​​are determined based on the relative importance of the efficiency evaluation indicators, economic evaluation indicators, and reliability evaluation indicators; establish a judgment matrix based on the scale values; calculate a preliminary weight vector using the geometric mean method based on the judgment matrix, wherein the preliminary weight vector includes a first preliminary weight, a second preliminary weight, and a third preliminary weight; and, if the judgment matrix passes the consistency test, determine the first preliminary weight as the first weight, the second preliminary weight as the second weight, and the third preliminary weight as the third weight.

[0133] Figure 8 A schematic diagram of the hardware structure of the electronic device provided in an embodiment of this application is shown.

[0134] An electronic device may include a processor 301 and a memory 302 storing computer program instructions.

[0135] Specifically, the processor 301 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0136] Memory 302 may include mass storage for data or instructions. For example, and not limitingly, memory 302 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 302 may include removable or non-removable (or fixed) media. Where appropriate, memory 302 may be internal or external to an electronic device. In a particular embodiment, memory 302 is a non-volatile solid-state memory.

[0137] Memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Therefore, typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the methods according to one aspect of this disclosure.

[0138] The processor 301 reads and executes computer program instructions stored in the memory 302 to implement any of the offshore wind power DC collection system capacity configuration evaluation methods in the above embodiments.

[0139] In one example, the electronic device may also include a communication interface 303 and a bus 304. For example, Figure 8 As shown, the processor 301, memory 302, and communication interface 303 are connected through bus 304 and complete communication with each other.

[0140] The communication interface 303 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0141] Bus 304 includes hardware, software, or both, that couples components of an electronic device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hypertext Transfer (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VESA Local Bus, VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, bus 304 may include one or more buses. Although specific buses are described and illustrated in the embodiments of this application, this application considers any suitable bus or interconnection.

[0142] Furthermore, in conjunction with the screening method for offshore wind power DC aggregation system planning schemes in the above embodiments, this application embodiment can provide a computer storage medium for implementation. This computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the offshore wind power DC aggregation system capacity configuration evaluation methods in the above embodiments.

[0143] This application also provides a computer program product, including a computer program that, when executed by a processor, implements any of the offshore wind power DC collection system capacity configuration evaluation methods described in the above embodiments.

[0144] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0145] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable-ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0146] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0147] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0148] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for evaluating the capacity configuration of an offshore wind power DC collection system, characterized in that, The screening method includes: Obtain the target parameters corresponding to each of the multiple offshore wind power DC aggregation system planning schemes. The target parameters include the rated capacity, topology, equipment parameters, fault parameters, and cost parameters of the offshore wind power DC aggregation system. For each of the offshore wind power DC collection system planning schemes, evaluation indicators for the offshore wind power DC collection system planning schemes are determined based on the target parameters. The evaluation indicators include efficiency evaluation indicators, economic evaluation indicators, and reliability evaluation indicators. Based on each evaluation indicator and the preset relationship between each evaluation indicator and the score, the first score corresponding to the efficiency evaluation indicator, the second score corresponding to the economic evaluation indicator, and the third score corresponding to the reliability evaluation indicator are determined. The Analytic Hierarchy Process (AHP) is used to determine the first weight corresponding to the efficiency evaluation index, the second weight corresponding to the economic evaluation index, and the third weight corresponding to the reliability evaluation index. Based on the first weight, the second weight, and the third weight, the first score, the second score, and the third score are weighted and summed to obtain the comprehensive score of the offshore wind power DC collection system planning scheme. Based on the comprehensive score of each offshore wind power DC collection system planning scheme, the target offshore wind power DC collection system planning scheme is selected from the multiple offshore wind power DC collection system planning schemes.

2. The method according to claim 1, characterized in that, The efficiency evaluation index includes the total power loss rate, and the equipment parameters include cable parameters and wind turbine parameters. Accordingly, determining the efficiency evaluation index of the offshore wind power DC collection system planning scheme based on the target parameters includes: Based on the topology, determine the number of target cables, the number of fans gathered on each target cable, and the fan spacing. The network power loss is determined based on the number of target cables, the cable parameters, the number of wind turbines connected to each target cable, and the spacing between the wind turbines. In addition, the power loss of the fans is determined based on the number of fans gathered on each of the target cables and the fan parameters. The total power loss is obtained based on the network power loss and the wind turbine power loss; The total power loss rate is determined based on the total power loss and the rated capacity.

3. The method according to claim 2, characterized in that, The cable parameters include the number of cables and the cable resistivity, and the fan parameters include the fan output current value. Accordingly, based on the number of target cables, the cable parameters, the number of fans connected to each target cable, and the fan spacing, the network power loss is determined, including: The current and resistance values ​​flowing through the target cable are determined based on the number of fans gathered on each target cable, the spacing between the fans, the output current value of the fans, and the resistivity of the cable. The power loss of the target cable is determined based on its current and resistance values. Based on the number of target cables, the power loss of each target cable is summed to obtain the network power loss.

4. The method according to claim 3, characterized in that, The topology includes a chain topology. Accordingly, determining the current and resistance values ​​flowing through the target cable based on the number of fans gathered on each target cable, the fan spacing, the output current value, and the cable resistivity includes: Based on the number of fans gathered on each target cable and the output current value of the fans, determine the number of segments of the target cable and the current value on each segment; Furthermore, the resistance value of each segment is determined based on the fan spacing and the cable resistivity; Based on the current and resistance values ​​of the target cable, determine the power loss of the target cable, including: The power loss of the target cable is determined by the number of segments, the current value and resistance value of each segment.

5. The method according to claim 4, characterized in that, The power loss of the target cable is determined by the number of segments, the current value and resistance value of each segment, including: The power loss of the target cable is calculated using the following formula: ， in, This indicates the power loss of the target cable. Indicates the first The resistance values ​​of the segments, Indicates the flow through the first The segmented current values, This indicates the number of segments in the target cable.

6. The method according to any one of claims 1-5, characterized in that, The reliability evaluation indicators include utilization rate, and the equipment parameters also include equipment type and the number of devices of each type. The failure parameters include the annual average failure rate and average repair time of each type of equipment. Accordingly, based on the target parameters, the reliability evaluation indicators for the offshore wind power DC collection system planning scheme are determined, including: The minimum cut set method is used to calculate the annual average failure rate, average repair time and number of devices for each type of equipment by multiplication, so as to obtain the annual power outage time of the corresponding type of equipment. The annual power outage time of the various types of equipment is summed to obtain the total annual power outage time of the offshore wind power DC collection system. The utilization rate is determined based on the total annual power outage time and total annual operating time of the offshore wind power DC collection system.

7. The method according to claim 6, characterized in that, The determination of the utilization rate based on the annual total power outage time and annual total operating time of the offshore wind power DC collection system includes: The utilization rate is calculated using the following formula: ， in, This indicates the utilization rate. Indicates the first Number of devices of this type Indicates the first The average annual power outage time for a single device in this category of equipment. Indicates the first Annual power outage time for this type of equipment This represents the total annual power outage time of the offshore wind power DC collection system. This indicates the total number of all types of equipment. This indicates the total annual working time of a single device. This indicates the total annual operating time of the offshore wind power DC collection system.

8. The method according to claim 1, characterized in that, The step of using the analytic hierarchy process (AHP) to determine the first weight corresponding to the efficiency evaluation index, the second weight corresponding to the economic evaluation index, and the third weight corresponding to the reliability evaluation index includes: Obtain the scale values ​​of the efficiency evaluation index, the economic evaluation index, and the reliability evaluation index, wherein the scale values ​​are determined based on the relative importance of the efficiency evaluation index, the economic evaluation index, and the reliability evaluation index; Based on the scale values, establish a judgment matrix; Based on the judgment matrix, a preliminary weight vector is calculated using the geometric mean method. The preliminary weight vector includes a first preliminary weight, a second preliminary weight, and a third preliminary weight. If the judgment matrix passes the consistency test, the first preliminary weight is determined as the first weight, the second preliminary weight is determined as the second weight, and the third preliminary weight is determined as the third weight.

9. A capacity configuration assessment device for an offshore wind power DC collection system, characterized in that, The device includes: The acquisition module is used to acquire the target parameters corresponding to each of the multiple offshore wind power DC aggregation system planning schemes. The target parameters include the rated capacity, topology, equipment parameters, fault parameters and cost parameters of the offshore wind power DC aggregation system. The first determining module is used to determine the evaluation index of each offshore wind power DC collection system planning scheme according to the target parameters. The evaluation index includes efficiency evaluation index, economic evaluation index and reliability evaluation index. The second determining module is used to determine the first score corresponding to the efficiency evaluation index, the second score corresponding to the economic evaluation index, and the third score corresponding to the reliability evaluation index based on each evaluation index and the preset relationship between each evaluation index and the score. The third determining module is used to determine the first weight corresponding to the efficiency evaluation index, the second weight corresponding to the economic evaluation index, and the third weight corresponding to the reliability evaluation index using the analytic hierarchy process. The fourth determining module is used to perform a weighted summation of the first score, the second score, and the third score based on the first weight, the second weight, and the third weight to obtain a comprehensive score for the offshore wind power DC collection system planning scheme. The fifth determining module is used to select the target offshore wind power DC collection system planning scheme from the multiple offshore wind power DC collection system planning schemes based on the comprehensive score of each offshore wind power DC collection system planning scheme.

10. An electronic device, characterized in that, The electronic device includes: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, it implements the capacity configuration evaluation method for offshore wind power DC collection systems as described in any one of claims 1-8.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions, which, when executed by a processor, implement the capacity configuration evaluation method for offshore wind power DC collection systems as described in any one of claims 1-8.

12. A computer program product, characterized in that, When the instructions in the computer program product are executed by the processor of the electronic device, the electronic device is able to perform the capacity configuration assessment method for offshore wind power DC collection systems as described in any one of claims 1-8.

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