Method for analyzing adaptability of power service based on terminal characteristics and convergence communication technology

Abstract

The application discloses a kind of based on terminal feature electric power service and fusion communication technology adaptability analysis method, this method includes: obtaining the performance requirement of electric power service and service terminal, according to the performance requirement of electric power service and service terminal determines the index weight of each communication technology for each service terminal;Obtain the time feature and space feature of service terminal, according to time feature and space feature determine the space-time factor of service terminal;According to index weight and space-time factor determine adaptability analysis result;According to adaptability analysis result determines the best communication mode of electric power service.The application solves the problem that prior art does not combine service terminal space-time distribution situation to carry out adaptability analysis of electric power service and fusion communication technology.

Description

Technical Field

[0001] This invention relates to the field of communications, and in particular to a method for analyzing the compatibility of power services with converged communication technologies based on terminal characteristics. Background Technology

[0002] With the accelerated construction of the energy internet, the demand for information collection, network control, and operation monitoring across all aspects of power generation, grid, load, and storage is experiencing explosive growth. Building a new power system primarily based on new energy sources, addressing the large-scale, high-proportion grid connection of new energy sources, distributed power sources, and microgrid access, and creating a multi-energy complementary, two-way interactive energy internet, communication is fundamental and crucial. Traditional fiber optic communication methods, constrained by economic and flexibility factors, struggle to provide flexible and effective support for the direct acquisition of massive distributed power source information and the coordinated dispatch of power generation, grid, and load. The new requirements for communication technology and operation and maintenance management arising from the deployment of the new power system necessitate the promotion of advanced communication technologies and the improvement and optimization of power communication network technology. Currently, the power industry offers a wide variety of services with diverse communication needs; a single network cannot meet the industrialized service quality requirements of different services. Therefore, there is an urgent need to provide secure, reliable, and real-time communication services to the power grid by integrating various heterogeneous network resources.

[0003] Adaptability analysis of power services and communication technologies is a method to assess the interaction between the power industry and communication technologies, and to determine the degree of suitability and synergistic development between the two. By analyzing the adaptability of power services and communication technologies, we can gain a deeper understanding of the extent, effectiveness, and potential optimization space of communication technology adoption in the power industry, thereby providing guidance and decision-making basis for the modernization, intelligentization, and sustainable development of the power industry. However, there are relatively few existing adaptability analysis methods that analyze the compatibility of power services and 5G converged communication technologies, and the impact of characteristics such as service interruption types and spatiotemporal distribution patterns on the accuracy of adaptability analysis results is also less considered. Summary of the Invention

[0004] This invention provides a method for adaptability analysis of power services and converged communication technologies based on terminal characteristics, which solves the problem that existing technologies do not take into account the spatiotemporal distribution of service terminals when conducting adaptability analysis of power services and converged communication technologies.

[0005] A method for adaptability analysis of power services and converged communication technologies based on terminal characteristics, comprising:

[0006] Obtain the performance requirements of power services and service terminals, and determine the indicator weights of each communication technology for each service terminal based on the performance requirements of power services and service terminals;

[0007] Acquire the temporal and spatial characteristics of the service terminal, and determine the spatiotemporal factors of the service terminal based on the temporal and spatial characteristics;

[0008] The suitability analysis results are determined based on the index weights and the spatiotemporal factors.

[0009] The optimal communication method for the power service is determined based on the adaptability analysis results.

[0010] In one embodiment of the present invention, determining the index weights of each communication technology for each service terminal based on the performance requirements of the power service and the service terminal specifically includes: establishing a multi-layer evaluation index model based on the technical parameters of the performance requirements; starting from the second layer of the multi-layer evaluation index model, constructing a judgment matrix based on the pairwise comparison method and the importance scaling table for elements of the same layer belonging to each factor of the previous layer, up to the bottom layer; and calculating the weights of each layer's indexes based on the judgment matrix.

[0011] In one embodiment of the present invention, the step of acquiring the temporal and spatial characteristics of the service terminals and determining the spatiotemporal factors of the service terminals based on the temporal and spatial characteristics specifically includes: classifying the service terminals according to their deployment areas to determine the areas to which each service terminal belongs; dividing the deployment areas into multiple grid areas of uniform size; acquiring the spatial distribution and usage frequency information of power service-related service terminals from a Geographic Information System (GIS) database; evaluating the service terminals based on the usage frequency information using a time series analysis method based on an ARIMA model to obtain the temporal factors of the service terminals; and obtaining the spatial factors of the service terminals based on the spatial distribution of the service terminals using a geographic weighted regression model.

[0012] In one embodiment of the present invention, determining the adaptability analysis result based on the index weights and the spatiotemporal factors specifically includes: determining the final weights of each communication technology based on the index weights; and determining the adaptability analysis result based on the final weights and the spatiotemporal factors.

[0013] In one embodiment of the present invention, determining the final weight of each communication technology based on the index weight specifically includes: normalizing each attribute index of the communication technology and converting it into a dimensionless proportional value; obtaining the maximum and minimum values ​​of each attribute index, and determining the positive ideal solution and negative ideal solution of each attribute index based on the maximum and minimum values; calculating the first distance between the communication technology and the positive ideal solution and the second distance between the communication technology and the negative ideal solution in each attribute index according to the attribute index weight; determining the score of each communication technology based on the first distance, the second distance, and the proportional value, and using the score as the final weight of the communication technology.

[0014] In one embodiment of the present invention, determining the adaptability analysis result based on the final weight and the spatiotemporal factors specifically includes: the spatiotemporal factors including time factors and space factors; determining the sum of the time factors and the space factors; and determining the product of the sum of the time factors and the space factors and the final weight as the adaptability analysis result for power services, service terminals, and communication technologies.

[0015] In one embodiment of the present invention, the step of calculating the weights of each level index according to the judgment matrix specifically includes: determining the product of each element in the judgment matrix, determining the weight value of the evaluation index according to the product; normalizing the weight value to obtain the evaluation index weight; performing consistency verification on the evaluation index weights of each communication technology, and determining that the consistency ratio reaches a preset standard, then the verification passes.

[0016] A device for analyzing the compatibility of power services and converged communication technologies based on terminal characteristics, comprising:

[0017] The weight calculation module is used to obtain the performance requirements of power services and service terminals, and determine the index weight of each communication technology for each service terminal based on the performance requirements of power services and service terminals.

[0018] The spatiotemporal factor calculation module is used to acquire the temporal and spatial characteristics of the service terminal, and determine the spatiotemporal factor of the service terminal based on the temporal and spatial characteristics.

[0019] The adaptability analysis module is used to determine the adaptability analysis results based on the indicator weights and the spatiotemporal factors; and to determine the optimal communication method for the power service based on the adaptability analysis results.

[0020] In one embodiment of the present invention, the weight calculation module is specifically used for: establishing a multi-layer evaluation index model based on the technical parameters of the performance requirements; starting from the second layer of the multi-layer evaluation index model, constructing a judgment matrix based on the pairwise comparison method and the importance scaling table for elements of the same layer that belong to each factor of the previous layer, up to the bottom layer; and calculating the weight of each layer index based on the judgment matrix.

[0021] In one embodiment of the present invention, the spatiotemporal factor calculation module is specifically used for: classifying business terminals according to their deployment areas to determine the area to which each business terminal belongs; dividing the deployment area into multiple grid areas of uniform size; obtaining spatial distribution and usage frequency information of power business-related business terminals from a Geographic Information System (GIS) database; evaluating the business terminals based on the usage frequency information using a time series analysis method based on an ARIMA model to obtain the time factor of the business terminals; and obtaining the spatial factor of the business terminals based on the spatial distribution of the business terminals using a geographic weighted regression model.

[0022] In one embodiment of the present invention, the adaptability analysis module is specifically used to: determine the final weight of each communication technology according to the index weight; and determine the adaptability analysis result according to the final weight and the spatiotemporal factor.

[0023] In one embodiment of the present invention, the adaptability analysis module further includes a final weight determination unit;

[0024] The final weight determination unit is used to normalize each attribute index of the communication technology and convert it into a dimensionless ratio value; obtain the maximum and minimum values ​​of each attribute index, and determine the positive ideal solution and negative ideal solution of each attribute index based on the maximum and minimum values; calculate the first distance between the communication technology and the positive ideal solution and the second distance between the communication technology and the negative ideal solution in each attribute index according to the attribute index weight; determine the score of each communication technology based on the first distance, the second distance and the ratio value, and use the score as the final weight of the communication technology.

[0025] In one embodiment of the present invention, the adaptability analysis module further includes an adaptability analysis result determination unit;

[0026] The spatiotemporal factors include time factors and spatial factors; the adaptability analysis result determination unit is used to determine the sum of the time factors and the spatial factors; and to determine the product of the sum of the time factors and the spatial factors and the final weight as the adaptability analysis result of power services, service terminals and communication technologies.

[0027] In one embodiment of the present invention, the weight calculation module further includes an index weight calculation unit;

[0028] The indicator weight calculation unit is used to determine the product of each element in the judgment matrix, determine the weight value of the evaluation indicator based on the product, normalize the weight value to obtain the evaluation indicator weight, and perform consistency verification on the evaluation indicator weights of each communication technology. If the consistency ratio reaches the preset standard, the verification is passed.

[0029] A device for analyzing the compatibility of power services and converged communication technologies based on terminal characteristics, comprising:

[0030] At least one processor; and,

[0031] The memory is communicatively connected to the at least one processor via a bus; wherein,

[0032] The memory stores instructions that can be executed by the at least one processor to implement the method as described in any of the above embodiments.

[0033] A non-volatile storage medium storing computer-executable instructions, which are executed by a processor to implement the method as described in any of the above embodiments.

[0034] This invention provides a method for adaptability analysis of power services and converged communication technologies based on terminal characteristics, which has at least the following beneficial effects: By analyzing existing adaptability analysis methods for power services and converged communication technologies, this invention focuses on the impact of the type and spatiotemporal distribution of service terminals on the adaptability analysis of power services and 5G converged communication technologies. Compared with previous methods, the adaptability analysis results of this invention not only use an adaptability analysis method for converged communication technologies, but also have more accurate results. It can more accurately identify the most suitable converged communication technology for power services, improve the accuracy and utilization efficiency of converged communication technology access, and reduce the cost of power services. Attached Figure Description

[0035] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings:

[0036] Figure 1 The compatibility analysis architecture for power services, service terminals, and communication technologies provided in the embodiments of the present invention;

[0037] Figure 2 A schematic diagram illustrating the steps of a method for adaptability analysis of power services and converged communication technologies based on terminal characteristics, provided in an embodiment of the present invention;

[0038] Figure 3 This invention provides an adaptation analysis model for power services and converged communication technologies.

[0039] Figure 4 A grid diagram of the deployment area provided in an embodiment of the present invention;

[0040] Figure 5A schematic diagram of a power service and converged communication technology compatibility analysis device based on terminal characteristics provided in an embodiment of the present invention;

[0041] Figure 6 This is a schematic diagram of a device for analyzing the compatibility of power services and converged communication technologies based on terminal characteristics, provided in an embodiment of the present invention. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be described clearly and completely below in conjunction with specific embodiments. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0043] It should be noted that those skilled in the art will understand, explicitly and implicitly, that the embodiments described in this invention can be combined with other embodiments without conflict. Unless otherwise defined, the technical or scientific terms used in this invention should be understood in their ordinary sense by those skilled in the art. The terms "a," "an," "an," "the," etc., used in this invention do not indicate quantity limitation and can represent singular or plural. The terms "comprising," "including," "having," and any variations thereof used in this invention are intended to cover non-exclusive inclusion; the terms "first," "second," "third," etc., used in this invention are merely to distinguish similar objects and do not represent a specific ordering of objects.

[0044] This invention proposes a method for adaptability analysis of power services and converged communication technologies based on terminal characteristics. This invention focuses on the impact of terminal type and spatiotemporal distribution on the adaptability analysis of power services and 5G converged communication technologies. It calculates the spatiotemporal factors of terminal distribution within the deployment area of ​​the power service, and uses the TOPSIS method to calculate the comprehensive adaptability score of various converged communication technologies for a specified service under given terminal type and spatiotemporal distribution. Based on the calculations in the above steps, the adaptability analysis results of power services and converged communication technologies are finally obtained, thereby identifying the most suitable converged communication technology for the power service, improving the accuracy of converged communication technology adaptation and reducing costs. A detailed explanation follows.

[0045] This invention relates to a method for analyzing the compatibility of power services with converged communication technologies based on terminal characteristics. This method can analyze the compatibility of power services with available converged communication technologies and identify the most suitable converged communication technology for the power service.

[0046] To understand the current state of development of compatibility analysis between power services and communication technologies, existing papers and patents were searched, compared, and analyzed, and the following technical information with high relevance to this invention was selected:

[0047] Technical Solution 1: The patent CN107222350B, "Matching Method and Apparatus for Power Distribution Services and Communication Modes," proposes a matching method and apparatus, computer equipment, and storage medium for power distribution services and communication modes, belonging to the field of communication technology. The method involves: acquiring power distribution service terminal information and available communication mode information within a region; obtaining power distribution service performance requirements; calculating the technical matching degree between each power distribution service terminal and each available communication mode within the region based on the communication technology value of the available communication technology used when the power distribution service terminal carries the corresponding service type and the power distribution service performance requirements; calculating the cost based on the cost of the power distribution service terminal and the cost of the available communication modes; and determining the most suitable communication mode for the region based on the technical matching degree of each available communication mode and the required cost. This method fully considers the technical matching degree and cost of available communication modes within the region, enabling reliable selection of the power distribution network communication mode.

[0048] Technical Solution 2: The paper titled "Research on Terminal Communication Access Technology for Power Internet of Things" designs a matching model between power grid services and terminal communication access networks. This matching model starts from the daily business application scenarios carried by the terminal communication access network in the power grid, such as precise load control and distribution automation, and extends comprehensively. Currently, power grid production and operation also consider new business application scenarios such as distributed power generation and energy storage, integrated energy services, and electric vehicle charging piles (stations). It analyzes the technical indicators and communication requirements of various business scenarios, summarizes and extracts universally applicable business data attributes, and predicts the load density of power grid services. This matching model establishes a matching model between communication technologies and power grid services based on an optimal matching method under multiple constraints. It derives the communication technologies used in 11 local business scenarios, such as general scenario sensing and data acquisition, and 12 wide-area access scenarios, such as distribution automation. It calculates the communication technology matching score from 13 dimensions, including bandwidth, latency, reliability, and industry maturity, and recommends one or more communication technologies based on the score.

[0049] Technical Solution 3: The paper titled "Research on Service Adaptation and Application Scenarios of Wireless Private Networks for Power Internet of Things" proposes a service quality evaluation model based on an improved analytic hierarchy process (AHP). This paper first analyzes the key technologies and spectrum characteristics of power wireless private networks based on the current and future power service requirements for power grid control, data acquisition, and mobile applications. Combining latency, bandwidth, packet loss rate, security, and economic indicators, it proposes a service quality evaluation model based on an improved AHP, which can improve the operational quality of power services.

[0050] The shortcomings of the above three solutions are:

[0051] Technical Solution 1 designs a matching method and apparatus, computer equipment, and storage medium for power distribution services and communication methods. This matching method obtains the performance requirements of power distribution services and the technical characteristics of available communication methods, calculates the technical compatibility degree between each power distribution service terminal and each available communication method within a region, calculates the corresponding cost, and determines the most suitable communication method for the region based on the technical compatibility degree and required cost of each available communication method. This method fully considers the technical compatibility degree and required cost of each available communication method within a region, and can reliably select the communication method for the power distribution network. However, this solution only considers the static performance requirements of the services and does not consider that the performance requirements of power services in real life are dynamically changing. The communication technology for adaptability analysis only considers a single communication technology, lacking an analysis of converged communication technologies. Furthermore, this matching method does not consider the impact of the spatiotemporal distribution of service terminals on the adaptability analysis results.

[0052] In Technical Solution 2, this paper establishes a matching model between communication technologies and power grid services using an optimal matching method under multiple constraints. This model identifies suitable communication technologies for 11 local business scenarios, such as general scenario sensing and data acquisition, and 12 wide-area access scenarios, such as distribution automation. A matching score for communication technologies is calculated based on 13 dimensions, including bandwidth, latency, reliability, and industry maturity. One or more communication technologies are recommended based on the score. This matching model covers existing power grid business scenarios and can also address the communication technology selection needs of potential future business scenarios. Starting from the daily business application scenarios of precise load control and distribution automation carried by the terminal communication access network in the power grid, this paper comprehensively extends to current power grid production and operation, while also considering emerging business application scenarios such as distributed power sources and energy storage, integrated energy services, and electric vehicle charging stations (piles). It analyzes the technical indicators and communication requirements of various business scenarios, summarizes and extracts universally applicable business data attributes, and predicts the load density of power grid services. However, this solution only considers the direct compatibility analysis between power services and communication methods, without taking into account the impact of the spatiotemporal distribution of business terminals on the compatibility analysis results.

[0053] Technical Solution 3 proposes an improved analytic hierarchy process (AHP) model for Quality of Service (QoS). This paper studies the characteristics and needs of power services, constructs a demand indicator system for various services, and improves upon the traditional AHP by using a three-scale method (0, 0.5, 1) to determine the comparison matrix of influencing factors. This reduces the number of comparisons between indicators and the ambiguity in judging indicator importance, thus ensuring the rationality of the comparison matrix. The comparison matrix is ​​then optimized through mathematical transformations, converting it into a judgment matrix that meets consistency requirements. Finally, the largest eigenvalue of the consistency matrix and its corresponding eigenvector are calculated to directly obtain the weights of each service indicator for multi-objective decision analysis. Although this QoS evaluation model improves the evaluation accuracy by proposing the three-scale method, it only considers a single communication method and cannot reflect the compatibility analysis process between power services and converged communication technologies. Furthermore, the evaluation indicator system is relatively incomplete.

[0054] Since the above technical solutions directly perform compatibility analysis between power services and converged communication technologies, they cannot reflect the internal relationship between power services and service terminals, or between service terminals and communication technologies, nor can they accurately analyze the most suitable converged communication technology for power services. Therefore, this invention designs a compatibility analysis architecture between power services and converged communication technologies.

[0055] The proposed solution mainly consists of two parts: an analysis architecture for the compatibility of power services and converged communication technologies, and a comprehensive calculation method for the compatibility of power services and converged communication technologies based on terminal characteristics.

[0056] This architecture consists of three layers. The top layer is the service layer, representing various types of power services. The middle layer is the terminal layer, displaying the types of service terminals used. Terminal distribution density, the number of terminals, and terminal usage frequency are factors influencing the calculation of the terminal's spatiotemporal factor. The bottom layer is the converged communication technology layer, representing various converged communication technologies in the communication network. This includes not only individual communication technologies but also converged communication technologies that combine multiple technologies. The final architecture is as follows: Figure 1 As shown, it includes a service layer, a terminal layer, and a communication technology layer; the service layer is for power services, the terminal layer is for the various service terminals used in power services, and the communication technology layer is for the converged communication technologies that may be used, including WIFI, LoRa, 5G, satellite communication, and power wireless private networks.

[0057] When analyzing the compatibility between a specific power service and various converged communication technologies, the first step is to calculate the spatiotemporal situation of the power service and its corresponding set of terminals within the power service cluster, obtaining the spatiotemporal factors of the service terminals. Then, the converged communication technologies are evaluated. Given the requirements of the power service and service terminals for converged communication technologies, the weights of each evaluation index are calculated using the analytic hierarchy process (AHP), and the TOPSIS method is used to obtain the evaluation scores for each converged communication technology. Finally, the two calculation results are combined to obtain the suitability analysis results between the service and the converged communication technologies.

[0058] Figure 2 A schematic diagram illustrating the steps of a method for adaptability analysis of power services and converged communication technologies based on terminal characteristics, provided in an embodiment of the present invention, may include the following steps:

[0059] S210: Obtain the performance requirements of power services and service terminals, and determine the indicator weights of each communication technology for each service terminal based on the performance requirements of power services and service terminals.

[0060] Specifically, an adaptation model for power services and converged communication technologies will be established.

[0061] like Figure 3 As shown, the target layer is the method for analyzing the compatibility between power services and converged communication technologies, the indicator layer is the multi-level evaluation indicators of communication technologies, and the technology layer is a variety of available communication technologies, including WIFI, LoRa, 5G, satellite communication, and power private networks. Each communication technology can be analyzed for compatibility with power services individually, or multiple technologies can be combined to form converged communication technologies for compatibility analysis with power services.

[0062] Establish a multi-layered adaptability evaluation index model.

[0063] In the evaluation index system for the compatibility of converged communication technologies, each index reflects the compatibility of communication technologies from different perspectives, but their relative importance varies. Therefore, after establishing the evaluation index system, it is necessary to determine the degree of influence of each index on the evaluation of the compatibility of communication technologies. Based on the technical parameters of power business requirements, a multi-layered evaluation index model is established, resulting in a multi-layered adaptability evaluation index model for converged communication technologies, as shown in Table 1.

[0064]

[0065] Table 1

[0066] Terminal type-based compatibility weight decision.

[0067] Each power service has specific requirements for communication technology latency and bandwidth when using a particular service terminal. For example, differential protection services use DTU terminals to transmit distribution current information, requiring a latency of <20ms and a channel bandwidth of 3Mbps. Based on service requirements, services can be classified according to their performance requirements for converged communication technologies. If power service b requires a latency of <20ms when using service terminal t, then (service b, terminal t) is set to latency requirement type 4, and its classification criteria are shown in Table 2.

[0068]

[0069] Table 2

[0070] Similarly, the requirements for technical elements such as bandwidth in the combination of (service b, terminal t) can also be classified according to the requirements.

[0071] In one embodiment of the present invention, the indicator weights of each communication technology for each service terminal are determined according to the performance requirements of power services and service terminals. Specifically, this includes: establishing a multi-layer evaluation indicator model based on the technical parameters of the performance requirements; starting from the second layer of the multi-layer evaluation indicator model, constructing a judgment matrix for elements of the same layer that belong to each factor of the previous layer based on the pairwise comparison method and the importance scaling table, up to the bottom layer; and calculating the weights of each layer's indicators based on the judgment matrix.

[0072] Specifically, starting from the second level of the hierarchical model structure of the evaluation indicators, for each element belonging to the same level as each factor in the previous level, a judgment matrix is ​​constructed using pairwise comparison and an importance scaling table, up to the lowest level. The judgment matrix A for evaluating the first-level indicators is A = (a ij The formula is shown below:

[0073]

[0074] In one embodiment of the present invention, the weights of each level of indicators are calculated based on the judgment matrix, specifically including: determining the product of each element in the judgment matrix, determining the weight value of the evaluation indicator based on the product; normalizing the weight value to obtain the weight of the evaluation indicator; performing consistency verification on the weights of the evaluation indicators of each communication technology, and determining that the consistency ratio reaches the preset standard, then the verification passes.

[0075] Where a ij The comparison results of the importance of technical element i and technical element j at the same level have the following properties: a ij =1 / a ji Determine the matrix element a ij The scaling methods are shown in Table 3.

[0076]

[0077] Table 3

[0078] The weight values ​​of the primary evaluation indicators for each communication technology in the communication technology set c under the combination of (service b, terminal t) can be calculated. Then normalize it according to the following formula: Therefore, based on the judgment matrix, the weight matrix of the first-level indicator can be obtained as follows:

[0079] ω=[w A1 w A2 ]

[0080] The weight matrix of the first-level index of the communication technology set c is as follows:

[0081] ωc=[wc A1 wc A2 ]

[0082] After calculating the weights of each terminal and each communication technology, the results must be checked for consistency. If the calculated consistency ratio (CR) meets the standard, the check is passed.

[0083] Similarly, the judgment matrix and weights of each secondary evaluation indicator can be derived sequentially. Then, using the results of single-level sorting across all levels within the same hierarchy, the weights of the importance of all factors at this level relative to the evaluation target M can be calculated. For example, the weight of bandwidth B1 in the secondary evaluation indicator relative to the evaluation target M is calculated as w... A1 w B1 And so on. That is, under the condition of (service b, terminal t), the weight Wbt of the communication technology c. c =w A1 w B1 .

[0084] S220: Obtain the time and space characteristics of the service terminal, and determine the spatiotemporal factors of the service terminal based on the time and space characteristics.

[0085] In one embodiment of the present invention, the acquisition of the temporal and spatial characteristics of the service terminals, and the determination of the spatiotemporal factors of the service terminals based on the temporal and spatial characteristics, specifically includes: classifying the service terminals according to their deployment areas to determine the areas to which each service terminal belongs; dividing the terminal deployment areas into multiple grid areas of uniform size; acquiring the spatial distribution and usage frequency information of power service-related service terminals from a Geographic Information System (GIS) database; evaluating the service terminals based on the usage frequency information using a time series analysis method based on an ARIMA model to obtain the temporal factors of the service terminals; and obtaining the spatial factors of the service terminals based on the spatial distribution of the service terminals using a geographic weighted regression model.

[0086] Specifically, the service terminals are categorized according to their deployment areas. Terminals deployed in power distribution facilities include DTUs, low-voltage monitoring units, environmental sensors, and various monitoring sensors; terminals deployed on the load side include precision control terminals, user meters, and low-voltage smart switches; and terminals deployed on photovoltaic inverters include integrated photovoltaic controllers and charging piles. All data used in the calculation process comes from a Geographic Information System (GIS) database.

[0087] When business B is to be deployed in a certain area, the spatiotemporal factors of the terminals can be calculated based on the spatiotemporal situation of each business terminal device in the area. The spatiotemporal factors include time factors and spatial factors. The results of abstracting each area into a mathematical form are shown in Table 4 below:

[0088] Area code 1 2 3

[0089] Table 4

[0090] Within each region, it can be divided into multiple grids of uniform size. By calculating the spatiotemporal status of service terminals within a single grid, the spatiotemporal factor of that service terminal is comprehensively derived. The grid diagram can be shown as follows: Figure 4 As shown.

[0091] 1) Calculate the time factor of the business terminal using the time series analysis method of fitting the ARIMA model.

[0092] Using a GIS system to provide data on the usage frequency of a specific service (b) using terminal (t), the ARIMA model's time series analysis method is used to evaluate the service terminal. After cleaning and smoothing the collected information, it is input into the ARIMA model. The ACF and PACF plots can be used to determine the differencing order (d) and autoregressive order (p), and then methods such as least squares or maximum likelihood estimation are used to estimate the parameters. Assuming an ARIMA(1,1,0) model is obtained, i.e., differencing order is 1, autoregressive order is 1, and moving average order is 0, then the model formula is:

[0093] (1-B)S t =c+(1-φ1B)(1-B)u t

[0094] Where B is the time lag operator, φ1 is the autoregressive coefficient, and u t It is white noise error, and c is a constant.

[0095] Based on data collected from GIS, the ARIMA(1,1,0) model is used to evaluate the temporal characteristics of the business terminal, resulting in:

[0096] (1-B)Sn =c+(1-φ1B)(1-B)u n-1

[0097] S n =S n-1 +(S n-2 -S n-1 )+u n-1 -φ(u n-2 -u n-3 )

[0098] Finally, based on the usage frequency data from the previous period, the current evaluation of the service terminal t is derived, and the final result can be written as Sb. t .

[0099] 2) Calculate spatial factors using a business terminal spatial situation calculation model based on geographic weighted regression.

[0100] Geographically weighted regression (GWR) is a statistical analysis model for local parameter estimation. Its model structure and calculation formula are as follows:

[0101]

[0102] In the formula, i represents the region code (i = 1, 2, 3), j represents the j-th grid within the region, and β k (u ij ,v ij ) is a continuous function β k In region i, the k-th regression function of grid j, ε ij Let be the random error of grid j within the i-th region.

[0103] By adopting a model that divides terminal equipment deployment areas, and using the actual operational status data of business terminals as the dependent variable, and the number of terminals used by the business in the area (NOT) and the terminal density (TD) in the area as two business terminal usage factors with typical spatial attributes, a regression analysis model is constructed to analyze the factors of business terminal usage in the area in detail.

[0104] First, the relationship between the independent and dependent variables is tested using ordinary least squares (OLS) regression. Standardization is performed using the natural logarithm method to transform the discrete data into a linear relationship, while also reducing the impact of heteroscedasticity on the parameter estimation of the linear model. An OLS regression model is established with the spatial factor (SF) of the business terminal as the dependent variable, as follows:

[0105] log(SF)=β0+β1log(NOT)+β2(TD)

[0106] In the formula, β0, β1, and β2 are the weights of their respective terms. NOT t s represents the number of terminals t distributed within region i. i s represents the area of ​​region i. A This represents the area of ​​region A.

[0107] Based on OLS, the following business terminal grid geographic weighted evaluation model is constructed by selecting indicators for model validation:

[0108] y(SF) i =β0+β1x i1 (NOT)+β2x i2 (TD)

[0109] In the above formula, y(SF) i x represents the spatial factor of the service terminal within region i. i1 (NOT) represents the number of service terminals t distributed within region i, x i2 (TD) represents the distribution density of service terminal t within region i, where β0, β1, and β2 are the weights of their respective terms. Therefore, when service b is about to be deployed in region i, the spatial factor of service terminal t can be written as Yb. t .

[0110] S230: Determine the fit analysis results based on indicator weights and spatiotemporal factors.

[0111] In one embodiment of the present invention, the adaptation analysis result is determined based on the index weights and spatiotemporal factors, specifically including: determining the final weights of each communication technology based on the index weights; and determining the adaptation analysis result based on the final weights and spatiotemporal factors.

[0112] Furthermore, the final weights of each communication technology are determined based on the indicator weights. Specifically, this includes: normalizing each attribute indicator of the communication technology and converting it into a dimensionless proportional value; obtaining the maximum and minimum values ​​of each attribute indicator, and determining the positive and negative ideal solutions for each attribute indicator based on the maximum and minimum values; calculating the first distance between the communication technology and the positive ideal solution and the second distance between the communication technology and the negative ideal solution in each attribute indicator according to the attribute indicator weights; determining the score of each communication technology based on the first distance, the second distance, and the proportional value, and using the score as the final weight of the communication technology.

[0113] Specifically, a calculation method for the compatibility of power services and converged communication technologies based on TOPSIS.

[0114] 1) Calculate the overall score of each communication technology under the condition of (service b, terminal t) using the TOPSIS method. Let the latency of the communication technology i (for readability, i represents the communication technology here) be D. i The bandwidth of communication technology i is B. i The security of communication technology i is St i The reliability of communication technology i is Rt i The attribute values ​​of each communication technology are shown in Table 5.

[0115]

[0116] Table 5

[0117] 2) Normalize each attribute indicator, converting it into a dimensionless proportional value. Here, a minimal normalization method is used, that is, for each attribute value x... i Subtract the minimum value of this attribute (min) i x i Then divide by the range of that attribute (maximum value). i x i min i x i The calculation formula is as follows:

[0118]

[0119] The final calculation results are as follows:

[0120] The latency of this communication technology i is YD i The bandwidth of communication technology i is YB i The security of communication technology i is YS i The reliability of communication technology i is YR i .

[0121] 3) Calculate the positive and negative ideal solutions: Find the maximum and minimum values ​​of each index to obtain the positive and negative ideal solutions. The maximum and minimum values ​​of the time delay are D. max and D min The maximum and minimum bandwidth values ​​are B respectively. max and B min The maximum and minimum values ​​of security are S respectively. max and S min The maximum and minimum reliability values ​​are R0 and R0, respectively. max and R min The positive and negative ideal solutions are shown below:

[0122] (D max B max ,S max ,Rmax )

[0123] (D min B min ,S min ,R min )

[0124] 4) Calculate the distances of communication technology i to the positive ideal solution and the negative ideal solution in terms of various evaluation indicators, taking time delay as an example:

[0125]

[0126] In the formula, wc represents the distance between communication technology i and the positive ideal solution in each evaluation index. j The weight of index j (derived by the analytic hierarchy process), x ij This represents the score of alternative solution (communication technology) i on index j. This represents the score of the positive ideal solution on index j.

[0127]

[0128] In the formula, wc represents the distance between communication technology i and the negative ideal solution in terms of various evaluation metrics. j The weight of index j (derived by the analytic hierarchy process), x ij This represents the score of alternative solution (communication technology) i on index j. This represents the score of the negative ideal solution on index j.

[0129] 5) Calculate the score for each alternative (communication technology):

[0130] Divide the distance of each alternative to the positive ideal solution by the sum of the distances between that alternative and the negative ideal solution to obtain the score of each communication technology under the combination condition of (service b, terminal t).

[0131]

[0132] Therefore, when service b chooses service terminal t to access communication technology i, its final weight result is as follows:

[0133] F(service b, service terminal t, communication technology i) = f i

[0134] Furthermore, the adaptability analysis results are determined based on the final weights and spatiotemporal factors, specifically including: the spatiotemporal factors include time factors and space factors; the sum of time factors and space factors is determined; the product of the sum of time factors and space factors and the final weights is determined as the adaptability analysis results for power services, service terminals, and communication technologies.

[0135] Specifically, taking into account the spatiotemporal distribution factor of the terminal in the compatibility analysis results of power services and converged communication technologies, the compatibility analysis results of service b with service terminal t and communication technology i are as follows:

[0136] P bt =(Sb t +Yb t )*F(b,i,t)

[0137] S240: Determine the optimal communication method for power services based on the adaptability analysis results.

[0138] In summary, this invention designs a compatibility analysis architecture for power services and converged communication technologies, focusing on the impact of the type and spatiotemporal distribution of service terminals on the compatibility analysis of power services and 5G converged communication technologies. It abandons the approach of directly performing compatibility analysis between power services and converged communication technologies, instead employing a method that first calculates the spatiotemporal factors of terminals within the power service deployment area, and then uses the TOPSIS method to calculate the comprehensive score of various converged communication technologies for a specified service under a specific terminal spatiotemporal distribution. This allows for the calculation of the compatibility analysis results between the service and the communication technologies. This approach supports the selection of the converged communication technology with the highest compatibility for power services.

[0139] This solution designs a comprehensive calculation method for the compatibility of power services and converged communication technologies based on terminal characteristics. It uses the analytic hierarchy process (AHP) to determine the weights of each evaluation index under specific services and terminals. Then, it calculates the time factors of each service terminal in the power service deployment area through time series analysis and calculates the spatial factors of the terminal using the geographic weighted regression method. Finally, it uses the TOPSIS method to calculate the comprehensive score of each converged communication technology under specific services and specific terminals, thereby calculating the compatibility between the service terminal and each available converged communication technology.

[0140] The above describes a method for analyzing the compatibility of power services and converged communication technologies based on terminal characteristics, as provided in an embodiment of the present invention. Based on the same inventive concept, this invention also provides a corresponding device for analyzing the compatibility of power services and converged communication technologies based on terminal characteristics, such as... Figure 5 As shown, it includes:

[0141] The weight calculation module 502 is used to obtain the performance requirements of power services and service terminals, and determine the index weights of each communication technology for each service terminal based on the performance requirements of power services and service terminals.

[0142] The spatiotemporal factor calculation module 504 is used to obtain the temporal and spatial characteristics of the service terminal and determine the spatiotemporal factor of the service terminal based on the temporal and spatial characteristics.

[0143] The adaptability analysis module 506 is used to determine the adaptability analysis results based on the indicator weights and spatiotemporal factors; and to determine the optimal communication method for power services based on the adaptability analysis results.

[0144] In one embodiment of the present invention, the weight calculation module 502 is specifically used for: establishing a multi-layer evaluation index model based on the technical parameters of the performance requirements; starting from the second layer of the multi-layer evaluation index model, constructing a judgment matrix based on the pairwise comparison method and the importance scale table for elements of the same layer that belong to each factor of the previous layer, up to the bottom layer; and calculating the weight of each layer index based on the judgment matrix.

[0145] In one embodiment of the present invention, the spatiotemporal factor calculation module 504 is specifically used for: classifying business terminals according to their deployment areas to determine the area to which each business terminal belongs; dividing the deployment area of ​​the terminals into multiple grid areas of uniform size; obtaining spatial distribution and usage frequency information of power business-related business terminals from a Geographic Information System (GIS) database; evaluating the business terminals based on the usage frequency information using a time series analysis method based on an ARIMA model to obtain the time factor of the business terminals; and obtaining the spatial factor of the business terminals based on the spatial distribution of the business terminals using a geographic weighted regression model.

[0146] In one embodiment of the present invention, the adaptability analysis module 506 is specifically used to: determine the final weight of each communication technology according to the index weight; and determine the adaptability analysis result according to the final weight and the spatiotemporal factor.

[0147] In one embodiment of the present invention, the adaptability analysis module 506 further includes a final weight determination unit 5061; the final weight determination unit 5061 is used to normalize each attribute index of the communication technology and convert it into a dimensionless proportional value; obtain the maximum and minimum values ​​of each attribute index, and determine the positive ideal solution and negative ideal solution of each attribute index based on the maximum and minimum values; calculate the first distance between the communication technology and the positive ideal solution and the second distance between the communication technology and the negative ideal solution in each attribute index according to the attribute index weight; determine the score of each communication technology based on the first distance, the second distance and the proportional value, and use the score as the final weight of the communication technology.

[0148] In one embodiment of the present invention, the adaptability analysis module further includes an adaptability analysis result determination unit 5062; the spatiotemporal factors include time factors and spatial factors; the adaptability analysis result determination unit 5062 is used to determine the sum of the time factors and the spatial factors; and to determine the product of the sum of the time factors and the spatial factors and the final weight as the adaptability analysis result of power services, service terminals and communication technologies.

[0149] In one embodiment of the present invention, the weight calculation module 502 further includes an index weight calculation unit 5021; the index weight calculation unit 5021 is used to determine the product of each element in the judgment matrix, determine the weight value of the evaluation index based on the product; normalize the weight value to obtain the evaluation index weight; perform consistency verification on the evaluation index weights of each communication technology, and if the consistency ratio reaches a preset standard, the verification passes.

[0150] This invention also provides a corresponding device for analyzing the compatibility of power services and converged communication technologies based on terminal characteristics, such as... Figure 6 As shown, it includes:

[0151] The system includes at least one processor 602, a communication interface 604, a memory 606, and a communication bus 608; wherein the processor 602, the communication interface 604, and the memory 606 communicate with each other through the communication bus 608; the processor 602 can call the logical instructions stored in the memory 606 to cause at least one processor 602 to execute any step of the above embodiments.

[0152] Based on the same idea, some embodiments of the present invention also provide media corresponding to the above methods.

[0153] Some embodiments of the present invention provide a storage medium storing computer-executable instructions, which are executed by a processor to implement any of the steps in the above embodiments.

[0154] The various embodiments in this invention are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the device and medium embodiments are relatively simple in description because they are fundamentally similar to the method embodiments; relevant parts can be referred to the descriptions in the method embodiments.

[0155] The devices, media, and methods provided in the embodiments of the present invention are one-to-one correspondences. Therefore, the devices and media also have similar beneficial technical effects as their corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be repeated here.

[0156] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process method or product 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 or product. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process method or product that includes that element.

[0157] The above are merely embodiments of the present invention and are not intended to limit the invention. Although the present invention has been described in detail above with general descriptions and specific embodiments, modifications or improvements can be made to it, which will be obvious to those skilled in the art. Therefore, all such modifications or improvements made without departing from the spirit of the present invention fall within the scope of protection claimed by the present invention.

Claims

1. A method for adaptability analysis of power services and converged communication technologies based on terminal characteristics, characterized in that, include: Obtain the performance requirements of power services and service terminals, and determine the indicator weights of each communication technology for each service terminal based on the performance requirements of power services and service terminals; The process of acquiring the temporal and spatial characteristics of service terminals and determining their spatiotemporal factors based on these characteristics includes: classifying service terminals according to their deployment areas to determine the area to which each service terminal belongs; dividing the deployment areas into multiple uniformly sized grid areas; acquiring spatial distribution and usage frequency information of power service-related service terminals from a Geographic Information System (GIS) database; evaluating the service terminals based on the usage frequency information using a time series analysis method based on an ARIMA model to obtain their temporal factors; and obtaining their spatial factors based on their spatial distribution using a geographic weighted regression model. The adaptability analysis results are determined based on the indicator weights and the spatiotemporal factors, specifically including: determining the final weights of each communication technology based on the indicator weights; the spatiotemporal factors include time factors and space factors; determining the sum of the time factors and the space factors; and determining the product of the sum of the time factors and the space factors and the final weights as the adaptability analysis results for power services, service terminals, and communication technologies. The optimal communication method for the power service is determined based on the adaptability analysis results.

2. The method according to claim 1, characterized in that, The determination of the indicator weights of each communication technology for each service terminal based on the performance requirements of the power service and the service terminal specifically includes: Establish a multi-layered evaluation index model based on the technical parameters of the performance requirements; Starting from the second layer of the multi-layer evaluation index model, for each element in the same layer that belongs to each factor in the previous layer, a judgment matrix is ​​constructed based on the pairwise comparison method and the importance scale table, until the bottom layer. The weights of each level's indicators are calculated based on the judgment matrix.

3. The method according to claim 1, characterized in that, The final weights of each communication technology are determined based on the aforementioned index weights, specifically including: Each attribute index of the communication technology is normalized and converted into a dimensionless proportional value; Obtain the maximum and minimum values ​​of each attribute indicator, and determine the positive and negative ideal solutions for each attribute indicator based on the maximum and minimum values; Calculate the first distance between the communication technology and the positive ideal solution and the second distance between the communication technology and the negative ideal solution in terms of each attribute index weight; A score for each communication technology is determined based on the first distance, the second distance, and the ratio value, and the score is used as the final weight of the communication technology.

4. The method according to claim 2, characterized in that, The calculation of the weights of each level's indicators based on the judgment matrix specifically includes: Determine the product of each element in the judgment matrix, and determine the weight value of the evaluation index based on the product; The weight values ​​are normalized to obtain the evaluation index weights; The consistency of the evaluation index weights for each communication technology is verified. If the consistency ratio reaches the preset standard, the verification is successful.

5. A device for analyzing the compatibility of power services and converged communication technologies based on terminal characteristics, characterized in that, include: The weight calculation module is used to obtain the performance requirements of power services and service terminals, and determine the index weight of each communication technology for each service terminal based on the performance requirements of power services and service terminals. The spatiotemporal factor calculation module is used to acquire the temporal and spatial characteristics of service terminals, and determine the spatiotemporal factors of service terminals based on the temporal and spatial characteristics. Specifically, this includes: classifying service terminals according to their deployment areas to determine the area to which each service terminal belongs; dividing the deployment areas into multiple uniformly sized grid areas; acquiring spatial distribution and usage frequency information of power service-related service terminals from a Geographic Information System (GIS) database; evaluating the service terminals based on the usage frequency information using a time series analysis method based on an ARIMA model to obtain the temporal factors of the service terminals; and obtaining the spatial factors of the service terminals based on their spatial distribution using a geographic weighted regression model. The adaptability analysis module is used to determine the adaptability analysis result based on the indicator weights and the spatiotemporal factors. Specifically, it includes: determining the final weight of each communication technology based on the indicator weights; the spatiotemporal factors include time factors and space factors; determining the sum of the time factors and the space factors; determining the product of the sum of the time factors and the space factors and the final weights as the adaptability analysis result of the power service, service terminal and communication technology; and determining the optimal communication method for the power service based on the adaptability analysis result.

6. A device for analyzing the compatibility of power services and converged communication technologies based on terminal characteristics, characterized in that, include: At least one processor; as well as, The memory is communicatively connected to the at least one processor via a bus; wherein, The memory stores instructions executable by the at least one processor, which are executed to implement the method as described in any one of claims 1-4.

7. A non-volatile storage medium storing computer-executable instructions, characterized in that, The computer-executable instructions are executed by a processor to implement the method as described in any one of claims 1-4.

Images