Substation local service and communication scheme adaptation method and related device

Abstract

The invention belongs to the field of electric power communication, and discloses a transformer substation local service and communication scheme adaptation method and related devices.The method comprises the steps that firstly, the demand weight of a local service for each communication index is obtained through a multi-dimensional index system, then linear normalization and vector normalization are adopted to process the index value of each alternative communication scheme in parallel; according to the method, the relative difference between indexes and data distribution characteristics are considered, the adaptation degree of each alternative communication scheme to the current local service is comprehensively evaluated from different decision dimensions based on a plurality of effect degree calculation models, and finally, the alternative communication scheme with the highest aggregation effect degree is selected as the communication scheme by aggregating a plurality of effect degree calculation results. The problem that local services and communication schemes are difficult to effectively adapt in a traditional method is effectively solved, diversified requirements of substation services for communication technologies can be accurately reflected, the most adaptive communication scheme is provided in a complex decision-making environment, the communication quality is effectively improved, and technical support is provided for intelligent operation and maintenance of a power transformation and distribution station.

Description

Technical Field

[0001] This invention belongs to the field of power communication and relates to a method and related devices for adapting local services and communication schemes in substations. Background Technology

[0002] With the deepening of the construction of new power systems, the intelligent transformation of substations has become an inevitable trend. To meet the core needs of intelligent operation and maintenance, lean management, and smart construction, a large number of new local services have emerged within the substations, such as high-definition video transmission from inspection robots, issuance of protection and control commands, and online monitoring of equipment status. These services exhibit significantly differentiated communication requirements in different scenarios, including production control, security management, and data acquisition. However, current research and practice largely focus on wide area network (WAN) or backbone network communication, lacking a systematic analysis and modeling of the local area network (LAN) level of substations, especially the business traffic characteristics and communication deterministic requirements under complex electromagnetic environments.

[0003] This ambiguity directly leads to blind spots in network planning and design, failing to provide accurate input for subsequent communication scheme selection, and becoming the primary bottleneck restricting the full-element digital sensing and intelligent application within the substation. Currently, regarding the adaptation of local substation services and communication schemes, the mapping relationship between the characteristics of local substation services and the key performance indicators of communication schemes is still imperfect. Traditional methods typically only use generalized indicators such as bandwidth, latency, and reliability for rough matching, failing to establish a refined quantitative mapping model.

[0004] Meanwhile, existing adaptability calculation methods often have limitations, either only performing simple technical indicator benchmarking and lacking comprehensive decision-making based on multiple criteria, failing to fully consider the dynamic impact of complex electromagnetic environments, equipment mobility, and multi-service concurrency in substations on communication performance. These limitations lead to biases in communication scheme selection, making it difficult to guarantee the quality of communication services and overall network efficiency for local substation operations. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method and related apparatus for adapting local services and communication schemes in substations.

[0006] To achieve the above objectives, the present invention employs the following technical solution: In a first aspect, the present invention provides a method for adapting local services and communication schemes in a substation, comprising: obtaining the demand weights of various communication indicators for the current local service; obtaining the indicator values ​​of various communication indicators for each candidate communication scheme, and performing linear normalization and vector normalization to obtain linearly normalized indicator values ​​and vector normalized indicator values; obtaining the effect degree of each candidate communication scheme for the current local service under several effect degree calculation models based on the linearly normalized indicator values ​​and vector normalized indicator values ​​of each communication indicator for each candidate communication scheme, combined with the demand weights of various communication indicators for the current local service; aggregating the effect degrees of each candidate communication scheme to obtain the aggregated effect degree of each candidate communication scheme, and selecting the candidate communication scheme with the highest aggregated effect degree as the communication scheme for the current local service.

[0007] Optionally, obtaining the required weights of each communication indicator of the current local service includes: obtaining the required weights of each communication indicator of the current local service using the best-worst method based on the importance analysis value of the current local service to each communication indicator.

[0008] Optionally, the communication metrics include at least two of the following: latency determinism, reliability, bandwidth capacity, coverage, connection density, deployment cost, energy efficiency ratio, data confidentiality, anti-interference capability, and identity authentication and access control.

[0009] Optionally, obtaining the index values ​​of each communication indicator for each candidate communication scheme and performing linear and vector normalization to obtain linearly normalized index values ​​and vector normalized index values ​​includes: assigning scores to the qualitative indicators in the communication indicators using a probabilistic language terminology set to obtain the probabilistic language terminology set for each qualitative indicator in the communication indicators, which serves as the index value of each qualitative indicator in the communication indicators; and linearly normalizing the index values ​​of each communication indicator for each candidate communication scheme using the following formula:

[0010]

[0011] in, For the first The first of the alternative communication schemes The linearly normalized index value of each communication indicator. For the first The first of the alternative communication schemes The range values ​​of a communication indicator. For the first The first of the alternative communication schemes The value of each communication metric. For the first The target value of each communication metric For all selected communication schemes, the first The maximum value of each communication indicator. For all alternative communication schemes, the first The minimum value of a communication indicator. for and distance, For the first The first of the alternative communication schemes A probabilistic linguistic terminology set for communication indicators. For the first A set of target probabilistic language terms for each communication indicator.

[0012] The values ​​of each communication metric for each alternative communication scheme are vector-normalized using the following formula:

[0013] in, For the first The first of the alternative communication schemes The vector-normalized index values ​​of a communication index. This represents the number of alternative communication schemes.

[0014] Optionally, the several effect calculation models include a complete compensation model, a non-compensation model, and an incomplete compensation model.

[0015] Optionally, the step of obtaining the effectiveness of each candidate communication scheme for the current local service under several effectiveness calculation models, based on the linearly normalized and vector-normalized index values ​​of each communication index of each candidate communication scheme and the demand weights of each communication index of the current local service, includes: obtaining the adjustment factor of the demand weights of each communication index through the following formula:

[0016] in, For the first Adjustment factors for the demand weights of each communication metric. For the first The first of the alternative communication schemes The value of each communication metric. For all alternative communication schemes, the first The maximum value of each communication indicator. The number of alternative communication schemes, for Expectations For the first The first of the alternative communication schemes A probabilistic linguistic terminology set for communication indicators. The largest among all alternative communication schemes .

[0017] Adjust the demand weights of each communication indicator using the following formula:

[0018]

[0019] in, For the first The weighting of adjustment requirements for each communication metric. For intermediate parameters, For the first The required weight of each communication metric This refers to the number of communication metrics.

[0020] The effectiveness of each alternative communication scheme for the current local service under the complete compensation model is obtained by the following formula:

[0021] in, For the first The effectiveness of each alternative communication scheme for the current local service under the complete compensation model. For the first The first of the alternative communication schemes The linearly normalized index value of each communication indicator.

[0022] The effectiveness of each alternative communication scheme for the current local service under the uncompensated model is obtained by the following formula:

[0023] in, For the first The effectiveness of each alternative communication scheme for the current local service under the non-compensated model. For all communication metrics The maximum value.

[0024] The effectiveness of each alternative communication scheme for the current local service under the incomplete compensation model is obtained by the following formula:

[0025] in, For the first The effectiveness of each alternative communication scheme for the current local service under the incomplete compensation model. For the first The first of the alternative communication schemes Vector-normalized index values ​​of each communication index.

[0026] Optionally, the aggregation of several effect degrees of each candidate communication scheme to obtain the aggregated effect degree of each candidate communication scheme includes: obtaining the preference weights of the current local service for each effect degree calculation model: The normalized effect size of each effect size of the alternative communication schemes is obtained by the following formula:

[0027] in, for The normalized effect degree.

[0028] The aggregation effect degree of each alternative communication scheme is obtained by the following formula:

[0029] in, For the first The aggregation effect degree of the alternative communication schemes The weights represent the current local business's preference for the complete compensation model. This represents the current local business's preference weights for the non-compensated model. The weights represent the current local business's preference for the incomplete compensation model. To adjust the parameters, For the first One alternative communication scheme is based on Ranking from largest to smallest, For the first One alternative communication scheme is based on Ranked from largest to smallest, For the first The alternative communication schemes are based on a ranking from largest to smallest. The ranking.

[0030] In a second aspect, the present invention provides a substation local service and communication scheme adaptation system, comprising: a demand weighting module for obtaining the demand weights of various communication indicators of the current local service; a normalization module for obtaining the indicator values ​​of various communication indicators of each candidate communication scheme, and performing linear normalization and vector normalization to obtain linearly normalized indicator values ​​and vector normalized indicator values; an effectiveness module for obtaining the effectiveness of each candidate communication scheme for the current local service under several effectiveness calculation models based on the linearly normalized indicator values ​​and vector normalized indicator values ​​of each communication indicator of each candidate communication scheme, combined with the demand weights of various communication indicators of the current local service; and an aggregation module for aggregating several effectiveness values ​​of each candidate communication scheme to obtain the aggregated effectiveness of each candidate communication scheme, and selecting the candidate communication scheme with the highest aggregated effectiveness as the communication scheme for the current local service.

[0031] In a third aspect, the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described substation local service and communication scheme adaptation method.

[0032] In a fourth aspect, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described substation local service and communication scheme adaptation method.

[0033] Compared with the prior art, the present invention has the following beneficial effects: This invention presents a method for adapting local services and communication schemes in substations. By constructing a multi-dimensional communication technology adaptability analysis index system, it first obtains the demand weights of each communication index for the current local service, effectively capturing the inherent correlation between service characteristics and communication performance. Then, it processes the index values ​​of each communication index for each candidate communication scheme using both linear normalization and vector normalization methods. This preserves the relative differences between indicators and maintains the distribution characteristics of the original data, laying a data foundation for subsequent accurate evaluation. Next, it employs a multi-effects calculation model aggregation mechanism to evaluate the adaptability of each communication scheme from different decision dimensions, effectively avoiding evaluation biases that may result from single-effects calculation methods and significantly improving the comprehensiveness and scientific rigor of adaptability calculation. Finally, it aggregates several effect degrees of each candidate communication scheme to obtain the aggregated effect degree of each scheme, and selects the candidate communication scheme with the highest aggregated effect degree as the communication scheme for the current local service. This method can not only accurately reflect the diversified needs of local substation services for communication technology, but also provide a stable and reliable adaptation solution in complex multi-attribute decision-making environments, ensuring the communication quality of local services and providing technical support for intelligent operation and maintenance, lean management and smart construction of substations. Attached Figure Description

[0034] Figure 1 This is a flowchart of the substation local service and communication scheme adaptation method according to an embodiment of the present invention.

[0035] Figure 2 This is a flowchart illustrating the effect size calculation in an embodiment of the present invention.

[0036] Figure 3 This is a block diagram of the substation local service and communication scheme adaptation system according to an embodiment of the present invention. Detailed Implementation

[0037] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0038] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0039] The present invention will now be described in further detail with reference to the accompanying drawings: See Figure 1 In one embodiment of the present invention, a method for adapting local services and communication schemes in a substation is provided, which can achieve accurate adaptation of local services and communication schemes in a substation and improve communication quality.

[0040] Specifically, the substation local service and communication scheme adaptation method of the present invention includes the following steps: S1: Obtain the required weights of various communication metrics for the current local business.

[0041] S2: Obtain the index values ​​of each communication index for each alternative communication scheme, and perform linear normalization and vector normalization to obtain the linearly normalized index value and the vector normalized index value.

[0042] S3: Based on the linearly normalized and vector-normalized index values ​​of each communication indicator of each candidate communication scheme, and combined with the demand weights of each communication indicator of the current local business, obtain the effect degree of each candidate communication scheme on the current local business under several effect degree calculation models.

[0043] S4: Aggregate several effectiveness values ​​of each candidate communication scheme to obtain the aggregate effectiveness value of each candidate communication scheme, and select the candidate communication scheme with the highest aggregate effectiveness value as the communication scheme for the current local business.

[0044] This invention presents a method for adapting local services and communication schemes in substations. By constructing a multi-dimensional communication technology adaptability analysis index system, it first obtains the demand weights of each communication index for the current local service, effectively capturing the inherent correlation between service characteristics and communication performance. Then, it processes the index values ​​of each communication index for each candidate communication scheme using both linear normalization and vector normalization methods. This preserves the relative differences between indicators and maintains the distribution characteristics of the original data, laying a data foundation for subsequent accurate evaluation. Next, it employs a multi-effects calculation model aggregation mechanism to evaluate the adaptability of each communication scheme from different decision dimensions, effectively avoiding evaluation biases that may result from single-effects calculation methods and significantly improving the comprehensiveness and scientific rigor of adaptability calculation. Finally, it aggregates several effect degrees of each candidate communication scheme to obtain the aggregated effect degree of each scheme, and selects the candidate communication scheme with the highest aggregated effect degree as the communication scheme for the current local service. This method can not only accurately reflect the diversified needs of local substation services for communication technology, but also provide a stable and reliable adaptation solution in complex multi-attribute decision-making environments, ensuring the communication quality of local services and providing technical support for intelligent operation and maintenance, lean management and smart construction of substations.

[0045] For illustrative purposes, the communication scheme is preferably a wireless communication scheme.

[0046] In one possible implementation, obtaining the demand weights of each communication indicator of the current local service includes: obtaining the demand weights of each communication indicator of the current local service using the best-worst method based on the importance analysis value of the current local service to each communication indicator.

[0047] For example, for different business characteristics of substation power services, the communication requirements are analyzed and the mapping relationship between them and communication indicators is obtained, thereby establishing a local business and communication indicator evaluation system for substations.

[0048] In this embodiment, the analysis focuses on three aspects: communication, economy, and security. The communication index evaluation system for the communication scheme of substation power business is determined. The secondary index includes communication index, economic index, and security index. The tertiary index is further subdivided into ten specific indicators, namely, latency determinism, reliability, bandwidth capacity, coverage and connection density under the communication index, deployment cost and energy efficiency ratio under the economic index, and data confidentiality, anti-interference ability and identity authentication and access control under the security index.

[0049] Interpretively, the best-worst method (BWM) is used to calculate the demand weights of various communication indicators for current local services. For example, ten indicators are used in the proposed multi-dimensional comprehensive evaluation system for substation power services in a new power system: The most important and optimal communication metrics were selected by experts. and the weakest and worst communication metric The remaining communication indicators were scored using a 1-9 scoring system. and The remaining communication metrics are scored, and the optimal comparison vector is obtained by comparing each of the remaining communication metrics with the optimal communication metric pairwise. The worst-case comparison vector is obtained by pairwise comparison of the remaining communication metrics and the worst-case communication metrics. .

[0050] Then, the demand weights for each communication indicator are solved using the following constraint optimization solution model:

[0051] in, For communication indicators Demand weight; For communication indicators Communication indicators Importance value; For communication indicators Communication indicators The importance value.

[0052] Finally, by calculating the consistency ratio To verify the weight of each requirement:

[0053] in, For different The maximum possible value value. The closer the value is to 0, the better the consistency. It is generally considered that... A value less than 0.1 is an acceptable level of consistency, at which point the demand weights are reliable.

[0054] In one possible implementation, obtaining the index values ​​of each communication index of each alternative communication scheme and performing linear normalization and vector normalization to obtain linearly normalized index values ​​and vector normalized index values ​​includes: assigning scores to the qualitative indexes in the communication indexes using a probabilistic language terminology set to obtain a probabilistic language terminology set for each qualitative index in the communication indexes, which serves as the index value of each qualitative index in the communication indexes.

[0055] The values ​​of each communication metric for each alternative communication scheme are linearly normalized using the following formula:

[0056]

[0057] in, For the first The first of the alternative communication schemes The linearly normalized index value of each communication indicator. For the first The first of the alternative communication schemes The range values ​​of a communication indicator. For the first The first of the alternative communication schemes The value of each communication metric. For the first The target value of each communication metric For all selected communication schemes, the first The maximum value of each communication indicator. For all alternative communication schemes, the first The minimum value of a communication indicator. for and distance, For the first The first of the alternative communication schemes A probabilistic linguistic terminology set for communication indicators. For the first A set of target probabilistic language terms for each communication indicator.

[0058] The values ​​of each communication metric for each alternative communication scheme are vector-normalized using the following formula:

[0059] in, For the first The first of the alternative communication schemes The vector-normalized index values ​​of a communication index. This represents the number of alternative communication schemes.

[0060] For interpretative, qualitative indicators within communication metrics, a probabilistic linguistic terminology set is used for scoring. In this set, each term is associated with a probability value representing its weight in the overall evaluation. This allows evaluators to more precisely express their assessment of an object or attribute and to handle uncertainty and biases in the evaluation process.

[0061] Specifically, the definition of the probabilistic language terminology set is as follows: 1): Let It is a set of linguistic terms, in which It is a positive integer. It is a linguistic term. and These are the upper and lower bounds for the evaluation of language terms.

[0062] 2): The probabilistic language terminology set is defined as follows: :

[0063] in, Representing language terms and their corresponding probabilities , yes Number of Chinese language terms.

[0064] 3): Define the probabilistic language terminology set and probability language terminology set The distance is:

[0065] in, and They are and The subscript (sorting).

[0066] 4) When multiple experts simultaneously describe and score the same quantitative indicator, the score for the quantitative indicator can be obtained by combining the opinions of multiple experts:

[0067] in, For the first The importance weight of each expert For the first Expert Selection exist The probability that it occupies.

[0068] For explanatory purposes, considering the differences in the order of magnitude of different index values, two normalization methods are used to normalize and quantize them before processing: target-based linear normalization and vector normalization.

[0069] Linear normalization eliminates the criterion unit by comparing the response to a maximum-minimum interval. The details are as follows:

[0070]

[0071] in, As the first For each communication metric, the target value should be the maximum for positive metrics and the minimum for negative metrics.

[0072] Since linear normalization loses the distribution of the original values, objective-based vector normalization is introduced to compensate for this deficiency. Vector normalization scales the length (or norm) of a vector to 1 while preserving its direction, resulting in a unit vector, as shown in the formula below:

[0073] Through the above processing, the linearly normalized index value and the vector normalized index value of each communication index of each candidate communication scheme are obtained, which provides a basis for the subsequent calculation of the effect degree of each candidate communication scheme.

[0074] In one possible implementation, the plurality of effect size calculation models include the complete compensation model (CCM), the uncompensated model (UCM), and the incomplete compensation model (ICM).

[0075] Interpretive methods are employed to calculate the effectiveness of different alternative communication schemes on local services using three different effectiveness calculation methods. Then, aggregation is used to avoid the shortcomings of a single method and effectively determine the optimal communication scheme.

[0076] In one possible implementation, see Figure 2 The step of obtaining the effectiveness of each candidate communication scheme for the current local service under several effectiveness calculation models, based on the linearly normalized and vector-normalized index values ​​of each communication indicator of each candidate communication scheme and the demand weights of each communication indicator of the current local service, includes: obtaining the adjustment factor of the demand weights of each communication indicator through the following formula:

[0077] in, For the first Adjustment factors for the demand weights of each communication metric. For the first The first of the alternative communication schemes The value of each communication metric. For all alternative communication schemes, the first The maximum value of each communication indicator. The number of alternative communication schemes, for Expectations For the first The first of the alternative communication schemes A probabilistic linguistic terminology set for communication indicators. The largest among all alternative communication schemes .

[0078] Adjust the demand weights of each communication indicator using the following formula:

[0079]

[0080] in, For the first The weighting of adjustment requirements for each communication metric. For intermediate parameters, For the first The required weight of each communication metric This refers to the number of communication metrics.

[0081] The effectiveness of each alternative communication scheme for the current local service under the complete compensation model is obtained by the following formula:

[0082] in, For the first The effectiveness of each alternative communication scheme for the current local service under the complete compensation model. For the first The first of the alternative communication schemes The linearly normalized index value of each communication indicator.

[0083] The effectiveness of each alternative communication scheme for the current local service under the uncompensated model is obtained by the following formula:

[0084] in, For the first The effectiveness of each alternative communication scheme for the current local service under the non-compensated model. For all communication metrics The maximum value.

[0085] The effectiveness of each alternative communication scheme for the current local service under the incomplete compensation model is obtained by the following formula:

[0086] in, For the first The effectiveness of each alternative communication scheme for the current local service under the incomplete compensation model. For the first The first of the alternative communication schemes Vector-normalized index values ​​of each communication index.

[0087] Interpretively, before calculating the effect size, the demand weights of communication indicators for the current local business are dynamically adjusted based on the indicator values ​​of each communication scheme. The static theoretical demand weights based on business needs are upgraded to dynamic, objective demand weights that combine the actual performance of the schemes, effectively solving the deficiency of insufficient decision-making sensitivity in traditional weight allocation. Specifically, when all candidate communication schemes perform very similarly on a communication indicator with a high demand weight, the actual distinguishing power of that indicator in communication scheme selection will decrease. Continuing to use the original high demand weight would weaken the effectiveness of the decision. By introducing the distribution characteristics of indicator values ​​for calculation, the demand weights of such communication indicators can be automatically identified and lowered, while the demand weights of those communication indicators that can significantly differentiate communication schemes can be increased. This data-driven weight adjustment mechanism ensures that the final demand weights reflect both the importance preferences of the business side and the technical characteristics of the supply side, thereby significantly improving the accuracy and scientific rigor of the suitability assessment and ensuring that the final communication scheme reflects actual differentiated advantages.

[0088] In one possible implementation, see Figure 2 The aggregation of several effect values ​​of each candidate communication scheme to obtain the aggregated effect value of each candidate communication scheme includes: obtaining the preference weights of the current local service for each effect value calculation model; and obtaining the normalized effect value of each effect value of each candidate communication scheme through the following formula:

[0089] in, for The normalized effect degree.

[0090] The aggregation effect degree of each alternative communication scheme is obtained by the following formula:

[0091] in, For the first The aggregation effect degree of the alternative communication schemes The weights represent the current local business's preference for the complete compensation model. This represents the current local business's preference weights for the non-compensated model. The weights represent the current local business's preference for the incomplete compensation model. To adjust the parameters, For the first One alternative communication scheme is based on Ranking from largest to smallest, For the first One alternative communication scheme is based on Ranked from largest to smallest, For the first The alternative communication schemes are based on a ranking from largest to smallest. The ranking.

[0092] For example, the preference weights of the current local business for each effect calculation model can be calculated using the best-worst (BWM) method described above.

[0093] Explanatoryly, when aggregating several effect sizes of various alternative communication schemes, the first step is to eliminate dimensional differences through normalization to ensure the comparability of different effect sizes.

[0094] The following are embodiments of the apparatus of the present invention, which can be used to execute embodiments of the method of the present invention. For details not disclosed in the apparatus embodiments, please refer to the embodiments of the method of the present invention.

[0095] See Figure 3 In another embodiment of the present invention, a substation local service and communication scheme adaptation system is provided, which can be used to implement the above-mentioned substation local service and communication scheme adaptation method. Specifically, the substation local service and communication scheme adaptation system includes a demand weighting module, a normalization module, an effect degree module, and an aggregation module.

[0096] The system comprises the following modules: a demand weighting module to obtain the demand weights of each communication indicator for the current local service; a normalization module to obtain the indicator values ​​of each communication indicator for each candidate communication scheme, and perform linear and vector normalization to obtain linearly normalized indicator values ​​and vector-normalized indicator values; an effectiveness module to obtain the effectiveness of each candidate communication scheme for the current local service under several effectiveness calculation models, based on the linearly normalized and vector-normalized indicator values ​​of each communication indicator for each candidate communication scheme, combined with the demand weights of each communication indicator for the current local service; and an aggregation module to aggregate the effectiveness of each candidate communication scheme to obtain the aggregate effectiveness of each candidate communication scheme, and select the candidate communication scheme with the highest aggregate effectiveness as the communication scheme for the current local service.

[0097] In one possible implementation, obtaining the demand weights of each communication indicator of the current local service includes: obtaining the demand weights of each communication indicator of the current local service using the best-worst method based on the importance analysis value of the current local service to each communication indicator.

[0098] In one possible implementation, the communication metrics include at least two of the following: latency determinism, reliability, bandwidth capacity, coverage, connection density, deployment cost, energy efficiency ratio, data confidentiality, anti-interference capability, and authentication and access control.

[0099] In one possible implementation, obtaining the index values ​​of each communication indicator for each candidate communication scheme and performing linear and vector normalization to obtain linearly normalized index values ​​and vector normalized index values ​​includes: assigning scores to the qualitative indicators in the communication indicators using a probabilistic language terminology set to obtain the probabilistic language terminology set for each qualitative indicator in the communication indicators, which serves as the index value of each qualitative indicator in the communication indicators; and linearly normalizing the index values ​​of each communication indicator for each candidate communication scheme using the following formula:

[0100]

[0101] in, For the first The first of the alternative communication schemes The linearly normalized index value of each communication indicator. For the first The first of the alternative communication schemes The range values ​​of a communication indicator. For the first The first of the alternative communication schemes The value of each communication metric. For the first The target value of each communication metric For all selected communication schemes, the first The maximum value of each communication indicator. For all alternative communication schemes, the first The minimum value of a communication indicator. for and distance, For the first The first of the alternative communication schemes A probabilistic linguistic terminology set for communication indicators. For the first A set of target probabilistic language terms for each communication indicator.

[0102] The values ​​of each communication metric for each alternative communication scheme are vector-normalized using the following formula:

[0103] in, For the first The first of the alternative communication schemes The vector-normalized index values ​​of a communication index. This represents the number of alternative communication schemes.

[0104] In one possible implementation, the plurality of effect calculation models include a complete compensation model, a non-compensation model, and an incomplete compensation model.

[0105] In one possible implementation, the step of obtaining the effectiveness of each candidate communication scheme for the current local service under several effectiveness calculation models, based on the linearly normalized and vector-normalized index values ​​of each communication index of each candidate communication scheme and the demand weights of each communication index of the current local service, includes: obtaining the adjustment factor of the demand weights of each communication index through the following formula:

[0106] in, For the first Adjustment factors for the demand weights of each communication metric. For the first The first of the alternative communication schemes The value of each communication metric. For all alternative communication schemes, the first The maximum value of each communication indicator. The number of alternative communication schemes, for Expectations For the first The first of the alternative communication schemes A probabilistic linguistic terminology set for communication indicators. The largest among all alternative communication schemes .

[0107] Adjust the demand weights of each communication indicator using the following formula:

[0108]

[0109] in, For the first The weighting of adjustment requirements for each communication metric. For intermediate parameters, For the first The required weight of each communication metric This refers to the number of communication metrics.

[0110] The effectiveness of each alternative communication scheme for the current local service under the complete compensation model is obtained by the following formula:

[0111] in, For the first The effectiveness of each alternative communication scheme for the current local service under the complete compensation model. For the first The first of the alternative communication schemes The linearly normalized index value of each communication indicator.

[0112] The effectiveness of each alternative communication scheme for the current local service under the uncompensated model is obtained by the following formula:

[0113] in, For the first The effectiveness of each alternative communication scheme for the current local service under the non-compensated model. For all communication metrics The maximum value.

[0114] The effectiveness of each alternative communication scheme for the current local service under the incomplete compensation model is obtained by the following formula:

[0115] in, For the first The effectiveness of each alternative communication scheme for the current local service under the incomplete compensation model. For the first The first of the alternative communication schemes Vector-normalized index values ​​of each communication index.

[0116] In one possible implementation, the aggregation of several effect values ​​of each candidate communication scheme to obtain the aggregated effect value of each candidate communication scheme includes: obtaining the preference weights of the current local service for each effect value calculation model; and obtaining the normalized effect value of each effect value of each candidate communication scheme using the following formula:

[0117] in, for The normalized effect degree.

[0118] The aggregation effect degree of each alternative communication scheme is obtained by the following formula:

[0119] in, For the first The aggregation effect degree of the alternative communication schemes The weights represent the current local business's preference for the complete compensation model. This represents the current local business's preference weights for the non-compensated model. The weights represent the current local business's preference for the incomplete compensation model. To adjust the parameters, For the first One alternative communication scheme is based on Ranking from largest to smallest, For the first One alternative communication scheme is based on Ranked from largest to smallest, For the first The alternative communication schemes are based on a ranking from largest to smallest. The ranking.

[0120] All relevant content of each step involved in the aforementioned embodiments of the substation local service and communication scheme adaptation method can be referenced to the functional description of the corresponding functional module of the substation local service and communication scheme adaptation system in the embodiments of the present invention, and will not be repeated here.

[0121] The module division in this embodiment of the invention is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in the various embodiments of the invention can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0122] In another embodiment of the present invention, a computer device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to achieve corresponding method flows or corresponding functions. The processor described in this embodiment of the present invention can be used for the operation of a substation local service and communication scheme adaptation method.

[0123] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the substation local service and communication scheme adaptation method in the above embodiments.

[0124] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0125] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of 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, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0126] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0127] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0128] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for adapting local services and communication schemes in a substation, characterized in that, include: Obtain the required weights of various communication metrics for the current local business; Obtain the index values ​​of each communication index for each alternative communication scheme, and perform linear normalization and vector normalization to obtain the linearly normalized index value and the vector normalized index value. Based on the linearly normalized and vector-normalized index values ​​of each communication indicator of each alternative communication scheme, and combined with the demand weights of each communication indicator of the current local business, the effectiveness of each alternative communication scheme for the current local business under several effectiveness calculation models is obtained. The aggregation effect of each candidate communication scheme is obtained by aggregating several effect values, and the candidate communication scheme with the highest aggregation effect value is selected as the communication scheme for the current local business.

2. The method for adapting local services and communication schemes in substations according to claim 1, characterized in that, The required weights for obtaining the various communication metrics of the current local service include: Based on the importance analysis values ​​of each communication indicator for the current local business, the demand weights of each communication indicator for the current local business are obtained using the best-worst method.

3. The method for adapting local services and communication schemes in substations according to claim 1, characterized in that, The communication metrics include at least two of the following: Deterministic latency, reliability, bandwidth capacity, coverage, connection density, deployment cost, energy efficiency, data confidentiality, anti-interference capability, and identity authentication and access control.

4. The method for adapting local services and communication schemes in substations according to claim 1, characterized in that, The process of obtaining the index values ​​of each communication index for each candidate communication scheme, and performing linear normalization and vector normalization to obtain the linearly normalized index value and the vector normalized index value includes: For the qualitative indicators in the communication indicators, a probabilistic language terminology set is used for scoring to obtain the probabilistic language terminology set of each qualitative indicator in the communication indicators, which serves as the indicator value of each qualitative indicator in the communication indicators. The values ​​of each communication metric for each alternative communication scheme are linearly normalized using the following formula: in, For the first The first of the alternative communication schemes The linearly normalized index value of each communication indicator. For the first The first of the alternative communication schemes The range values ​​of a communication indicator. For the first The first of the alternative communication schemes The value of each communication metric. For the first The target value of each communication metric For all selected communication schemes, the first The maximum value of each communication indicator. For all alternative communication schemes, the first The minimum value of a communication indicator. for and distance, For the first The first of the alternative communication schemes A probabilistic linguistic terminology set for communication indicators. For the first A set of target probabilistic language terms for each communication indicator; The values ​​of each communication metric for each alternative communication scheme are vector-normalized using the following formula: in, For the first The first of the alternative communication schemes The vector-normalized index values ​​of a communication index. This represents the number of alternative communication schemes.

5. The method for adapting local services and communication schemes in substations according to claim 1, characterized in that, The aforementioned effect calculation models include the complete compensation model, the non-compensation model, and the incomplete compensation model.

6. The method for adapting local services and communication schemes in substations according to claim 5, characterized in that, The process of obtaining the effectiveness of each alternative communication scheme for the current local service under several effectiveness calculation models, based on the linearly normalized and vector-normalized index values ​​of each communication index of each alternative communication scheme and the demand weights of each communication index of the current local service, includes: The adjustment factor for the demand weight of each communication indicator is obtained by the following formula: in, For the first Adjustment factors for the demand weights of each communication metric. For the first The first of the alternative communication schemes The value of each communication metric. For all alternative communication schemes, the first The maximum value of each communication indicator. The number of alternative communication schemes, for Expectations For the first The first of the alternative communication schemes A probabilistic linguistic terminology set for communication indicators. The largest among all alternative communication schemes ; Adjust the demand weights of each communication indicator using the following formula: in, For the first The weighting of adjustment requirements for each communication metric For intermediate parameters, For the first The required weight of each communication metric The number of communication indicators; The effectiveness of each alternative communication scheme for the current local service under the complete compensation model is obtained by the following formula: in, For the first The effectiveness of each alternative communication scheme for the current local service under the complete compensation model. For the first The first of the alternative communication schemes The linearly normalized index value of each communication indicator; The effectiveness of each alternative communication scheme for the current local service under the uncompensated model is obtained by the following formula: in, For the first The effectiveness of each alternative communication scheme for the current local service under the non-compensated model. For all communication metrics The maximum value; The effectiveness of each alternative communication scheme for the current local service under the incomplete compensation model is obtained by the following formula: in, For the first The effectiveness of each alternative communication scheme for the current local service under the incomplete compensation model. For the first The first of the alternative communication schemes Vector-normalized index values ​​of each communication index.

7. The substation local service and communication scheme adaptation method according to claim 6, characterized in that, The aggregated effectiveness of each alternative communication scheme is obtained by aggregating several effectiveness values, including: Obtain the current local business's preference weights for each effect calculation model; The normalized effect size of each effect size of the alternative communication schemes is obtained by the following formula: in, for Normalized effect degree; The aggregation effect degree of each alternative communication scheme is obtained by the following formula: in, For the first The aggregation effect degree of the alternative communication schemes The weights represent the current local business's preference for the complete compensation model. This represents the current local business's preference weights for the non-compensated model. The weights represent the current local business's preference for the incomplete compensation model. To adjust the parameters, For the first One alternative communication scheme is based on Ranking from largest to smallest, For the first One alternative communication scheme is based on Ranked from largest to smallest, For the first The alternative communication schemes are based on a ranking from largest to smallest. The ranking.

8. A substation local service and communication scheme adaptation system, characterized in that, include: The demand weighting module is used to obtain the demand weights of various communication metrics for the current local business. The normalization module is used to obtain the index values ​​of each communication index of each candidate communication scheme, and perform linear normalization and vector normalization to obtain linear normalized index values ​​and vector normalized index values. The effect degree module is used to obtain the effect degree of each candidate communication scheme for the current local service under several effect degree calculation models, based on the linear normalized index value and vector normalized index value of each communication index of each candidate communication scheme, combined with the demand weight of each communication index of the current local service. The aggregation module is used to aggregate several effectiveness values ​​of each candidate communication scheme to obtain the aggregate effectiveness value of each candidate communication scheme, and select the candidate communication scheme with the highest aggregate effectiveness value as the communication scheme for the current local business.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the substation local service and communication scheme adaptation method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the substation local service and communication scheme adaptation method as described in any one of claims 1 to 7.

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