CN112231923A - Site selection method for 'multi-station integration' data center station - Google Patents
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Abstract
The invention discloses a multi-station fusion data center station site selection method, which comprises the following steps: determining a site selection scheme of a multi-station fusion data center station; determining influence factors of the addressing scheme according to the addressing scheme and acquiring specific information of the influence factors; respectively scoring the influence factors of each addressing scheme according to the specific information of the influence factors to obtain influence factor scores; determining the weight of each influencing factor through an analytic hierarchy process; and calculating the comprehensive score of each site selection scheme according to the weight and the influence factor scores, and selecting the site with the highest comprehensive score as the final address of the multi-station fusion data center station. The station building address selected by the multi-station fusion data center station site selection method can give consideration to the influence factors such as user composition, node scale, municipal planning, population density and the like, so that the built multi-station fusion data center station can better serve the public, service society and regional development.
Description
Technical Field
The invention relates to the field of power supply system construction, in particular to a multi-station integration data center station site selection method.
Background
With the deepening and rapid development of the strategic deployment of the national 'new capital construction', the construction work of the 'multi-station fusion' data center station is widely developed. The multi-station fusion data center station is a basic guarantee for supporting the construction of the power Internet of things.
In order to ensure that the 'multi-station fusion' data center station can fully exert the effect and quickly carry out operation after being built and put into operation, the 'multi-station fusion' data center station is often required to be located in a parcel with developed economy, convenient transportation and dense population. In the prior art, research on site selection of a multi-station fusion data center station involves a few, the site selection defect of the site selection often exists, and factors in the aspects of user distribution density, user properties, economic development conditions, development potential, traffic conditions, population density and the like cannot be considered. The multi-station fusion data center station constructed by site selection often cannot fully play a service role. The research objective of the site selection evaluation subject of the data center station by using the multi-station fusion of the multi-metadata is to decompose the site selection problem of the data center station into several relatively independent and associated criteria of user composition, node scale, municipal planning and population density, determine the weight of each criterion by an analytic hierarchy process, carry out score normalization conversion on the determined site to be selected one by one according to the corresponding criteria, and finally judge the optimal site selection point by comprehensive scoring. The multi-station fusion data center station can fully play a role through site selection.
Disclosure of Invention
In order to solve the above problems, the present invention provides a method for selecting a site of a multi-station fusion data center station, comprising:
determining a site selection scheme of a multi-station fusion data center station; determining influence factors of the addressing scheme according to the addressing scheme and acquiring specific information of the influence factors;
scoring the influence factors of each addressing scheme according to the specific information of the influence factors;
determining the weight of each influencing factor through an analytic hierarchy process;
and calculating the comprehensive score of each site selection scheme according to the weight and the influence factor scores, and selecting the site with the highest comprehensive score as the final address of the multi-station fusion data center station.
Preferably, the influencing factors include user composition, node size, municipal planning and population density.
Preferably, the scoring the influence factors of each addressing scheme according to the specific information of the influence factors comprises: scoring the user composition of the site selection scheme according to the electricity consumption in a period of time in the administrative region where the 'multi-station integration' data center station is located in each site selection scheme; scoring the node scale of the addressing scheme according to the area of the 'multi-station fusion' data center station in the addressing scheme; grading the administrative planning of the site selection scheme according to a relevant policy of an administrative region where a 'multi-station integration' data center station is located in the site selection scheme; and scoring the population density of the site selection scheme according to the population density of an administrative area in which the multi-station fusion data center station is located in the site selection scheme.
Preferably, the scoring of the user composition of the site selection scheme according to the power consumption in a period of time in the administrative area where the 'multi-station integration' data center station is located in each site selection scheme comprises:
counting the electricity consumption in a period of time in an administrative area where a 'multi-station integration' data center station is located in the site selection scheme;
and normalizing the electricity consumption to obtain a user composition score S1.
Preferably, the scoring the size of the nodes of the addressing scheme according to the area of the 'multi-station fusion' data center station in the addressing scheme comprises:
formulating a node scale scoring standard of which the area is mapped to the node scale scoring;
and scoring and normalizing according to the node scale scoring standard to obtain a node scale score S2.
Preferably, the scoring of the administrative plan of the site selection scheme according to the policy related to the administrative region in which the "multi-station fusion" data center station is located in the site selection scheme includes:
acquiring policy files related to a multi-station fusion data center station;
setting an administrative planning scoring standard for mapping the content of the policy file to the administrative planning scoring;
and scoring and normalizing according to the administrative planning scoring standard to obtain an administrative planning score S3.
Preferably, the scoring the population density of the site selection scheme according to the population density of the administrative region in which the "multi-station fusion" data center station is located in the site selection scheme includes:
counting the latest population density data in administrative regions where 'multi-station fusion' data center stations are located in the site selection scheme;
the population density data is normalized to obtain a population density score S4.
Preferably, determining the weight of each of the influencing factors by analytic hierarchy process comprises:
constructing a decision matrix of the influence factors by using a pairwise comparison method and a quantization scale of 1-9, wherein the decision matrix is a positive reciprocal matrix;
row-column normalization of the decision matrix
Sum by row
Determining feature vectors
Normalizing the elements of the feature vector
Obtaining a weight W ═ W for the influencing factor1，W2，……Wn]；
The reasonableness of the weight is detected according to the consistency ratio.
Preferably, detecting the reasonableness of the weight according to the conformity ratio includes:
computing maximum feature root
Calculating a consistency index
Calculating a consistency ratio
If CR is less than 0.1, the weight is reasonable, otherwise, the quantization scale is adjusted to determine the weight again, wherein RI is a random consistency index obtained by looking up a random consistency index table.
Preferably, a total score S1 × W of each site selection scheme is calculated according to the weight and the influence factor score1+S2×W2+S3×W3+S4W4。
The multi-station fusion data center station site selection method provided by the application has the following beneficial effects:
the site selection method of the multi-station fusion data center station provided by the invention obtains scoring weights of user composition, node scale, municipal planning and population density through an analytic hierarchy process, and evaluates each site selection scheme according to user composition scoring, node scale scoring, municipal planning scoring, population density scoring and scoring weights. The site selection scheme obtained through evaluation can take influence factors such as user composition, node scale, municipal planning, population density and the like into consideration, so that the constructed multi-station fusion data center station can better serve the public, service society and regional development.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.
FIG. 1 is a table of quantized scale comparison data of relative importance of influencing factors in an embodiment of the present invention;
FIG. 2 is a table of relative importance versus quantization scale in an embodiment of the present invention;
FIG. 3 is a table of user-formed ratings according to an embodiment of the present invention;
FIG. 4 is a table of node size scores in an embodiment of the present invention;
FIG. 5 is a municipal planning scoring table in an embodiment of the invention;
FIG. 6 is a table of population density ratings in an embodiment of the present invention;
FIG. 7 is a table of random consistency indicators in an embodiment of the present invention;
FIG. 8 is a table of composite score data in an embodiment of the present invention;
fig. 9 is a flowchart of a "multi-station fusion" data center station site selection method in an embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention is described with reference to the accompanying drawings, wherein fig. 1 is a table of quantized scale comparison data of relative importance of influencing factors in the embodiment of the invention; FIG. 2 is a table of relative importance versus quantization scale in an embodiment of the present invention; FIG. 3 is a table of user-formed ratings according to an embodiment of the present invention; FIG. 4 is a table of node size scores in an embodiment of the present invention; FIG. 5 is a municipal planning scoring table in an embodiment of the invention; FIG. 6 is a table of population density ratings in an embodiment of the present invention; FIG. 7 is a table of random consistency indicators in an embodiment of the present invention; FIG. 8 is a table of composite score data in an embodiment of the present invention; fig. 9 is a flowchart of a "multi-station fusion" data center station site selection method in an embodiment of the present invention.
Referring to fig. 9, the present invention provides a method for selecting an address of a "multi-station fusion" data center station, including:
s100, determining a site selection scheme of a plurality of 'multi-station fusion' data center stations to be selected.
S200, determining influence factors of the addressing scheme according to the addressing scheme and acquiring specific information of the influence factors; specifically, a plurality of the influencing factors are independent of each other. One possible such influencing factor includes user composition, node size, municipal planning, and population density. The user configuration is determined by the power consumption of an administrative area where the 'multi-station fusion' data center station is located in the site selection scheme within a period of time, the node size is determined by the area of the 'multi-station fusion' data center station in the site selection scheme, the municipal planning is determined by the policy planning of the administrative area where the 'multi-station fusion' data center station is located in the site selection scheme, and the population density is determined by the population density of the administrative area where the 'multi-station fusion' data center station is located in the site selection scheme.
S300, respectively scoring the influence factors of each addressing scheme according to the specific information of the influence factors to obtain influence factor scores; specifically, the scoring the influence factors of each address selection scheme according to the specific information of the influence factors includes: scoring the user composition of the site selection scheme according to the electricity consumption in a period of time in the administrative region where the 'multi-station integration' data center station is located in each site selection scheme; scoring the node scale of the addressing scheme according to the area of the 'multi-station fusion' data center station in the addressing scheme; grading the administrative planning of the site selection scheme according to a relevant policy of an administrative region where a 'multi-station integration' data center station is located in the site selection scheme; and scoring the population density of the site selection scheme according to the population density of an administrative area in which the multi-station fusion data center station is located in the site selection scheme.
In a specific implementation process, referring to fig. 3, scoring the user composition of the site selection scheme according to the power consumption in a period of time in the administrative area where the "multi-station fusion" data center station is located in each site selection scheme includes:
counting the electricity consumption in a period of time in an administrative area where a 'multi-station integration' data center station is located in the site selection scheme; as shown in fig. 3, 169912,7850, 11747 and 9063 represent the power usage of the selected areas of the four addressing schemes,
normalizing the electricity consumption to obtain a user composition score S1, wherein the electricity consumption normalization process comprises the following steps: and summing the four power consumptions to obtain power consumption sums, and calculating the ratio of each power consumption sum to serve as a user composition score. In fig. 3, the user composition scores of area 1, area 2, area 3, and area 4 are 0.371, 0.172, 0.258, and 0.199, respectively.
In a specific implementation process, referring to fig. 4, scoring the size of the nodes of the addressing scheme according to the area of the "multi-station fusion" data center station in the addressing scheme includes:
formulating a node scale scoring standard of which the area is mapped to the node scale scoring; one possible node scale scoring criterion is: the area of the multi-station fusion data center station is not more than 20 square meters and can be 1 minute, the area of the 20 square meters and the multi-station fusion data center station is not more than 40 square meters and can be 2 minutes, the area of the 40 square meters and the multi-station fusion data center station is not more than 100 square meters and can be 3 minutes, and the area of the multi-station fusion data center station is more than 100 square meters and can be 4 minutes.
Scoring and normalizing according to the node scale scoring standard to obtain a node scale score S2, wherein the node scale normalization process comprises the following steps: and summing the four node scales to obtain a node scale sum, and calculating the ratio of each node scale to the node scale sum as a node scale score.
In a specific implementation process, referring to fig. 5, scoring the administrative plan of the addressing scheme according to the policy related to the administrative region where the "multi-station fusion" data center station is located in the addressing scheme includes:
acquiring policy files related to a multi-station fusion data center station; specifically, selecting policy documents of governments on aspects of promoting new capital construction, new state development, industry poverty alleviation and the like;
setting an administrative planning scoring standard for mapping the content of the policy file to the administrative planning scoring; one possible administrative plan scoring criteria is: no area planned in the aspect is rated 0 in the last 5 years, the area with a district-county level project plan or an urban level project in the last 5 years is rated 1, the area with an urban level project or a provincial level project in the last 5 years is rated 2, and the area with a provincial level project or the provincial level project is rated 3 in the last 5 years.
And scoring and normalizing according to the administrative planning scoring standard to obtain an administrative planning score S3. The administrative planning normalization process comprises the following steps: and summing the four administrative plan divisions to obtain administrative plan sums, and calculating the ratio of each administrative plan to the administrative plan sums to serve as an administrative plan score.
In a specific implementation process, referring to fig. 6, scoring the population density of the site selection scheme according to the population density of the administrative area where the "multi-station fusion" data center station is located in the site selection scheme includes:
counting the latest population density data in administrative regions where 'multi-station fusion' data center stations are located in the site selection scheme;
the population density data is normalized to obtain a population density score S4. The population density normalization process includes: and summing the four population densities to obtain population density sums, and taking the ratio of each population density to the population density sum as a population density score.
S400, determining the weight of each influence factor through an analytic hierarchy process; in a specific implementation process, determining the weight of each influence factor by an analytic hierarchy process comprises the following steps:
constructing a decision matrix of the influence factors by using a pairwise comparison method and a quantization scale of 1-9, wherein the decision matrix is a positive reciprocal matrix; specifically, two influence factors are arbitrarily taken, the two influence factors are compared by a pairwise comparison method, and the relative importance degree of the two influence factors is evaluated by using a quantization scale of 1-9, so that a judgment matrix is constructed;
specifically, as shown in fig. 2, any two influencing factors, namely an influencing factor i and an influencing factor j, are selected; wherein, the quantization scale of relative importance degree is 1, which indicates that the influence factor i is equally important compared with the influence factor j; the quantization scale of the relative importance degree is 3, which indicates that the influence factor i is slightly more important than the influence factor j; the quantization scale of the relative importance degree is 2, which means that the relative importance degree of the influence factor i compared with the influence factor j is between equal importance and slightly important; the quantization scale of the relative importance degree is 5, which indicates that the relative importance degree of the influence factor i is more important than that of the influence factor j; similarly, the quantization scale of relative importance is 4, indicating that the relative importance of the influencing factor i compared to the influencing factor j is between slightly important and more important; the quantization scale of the relative importance degree is 7, which indicates that the relative importance degree of the influence factor i is more important than that of the influence factor j; the same quantization scale for relative importance is 6, tableIndicating that the relative importance degree of the influencing factor i compared with the influencing factor j is between stronger importance and stronger importance; the quantization scale of the relative importance degree is 9, which indicates that the relative importance degree of the influence factor i to the influence factor j is extremely important; similarly, the quantization scale for the relative importance level is 8, indicating that the relative importance level of the influencing factor i compared to the influencing factor j is between strongly important and extremely important; referring to fig. 1, the first row and the first column of fig. 1 represent the kind of the influencing factor; the second column is that the data indicates a relative degree of importance of the user composition to the user composition as A11The relative importance degree of the node scale relative to the user constitution is A21The relative importance of municipal planning to the user profile is A31The relative importance of population density to user composition is A41(ii) a The third column of data shows that the relative degree of importance of the user to form the relative node size is A12The relative importance of the node scale to the node scale is A22The relative importance degree of municipal planning to the node scale is A32The relative importance of population density to node size is A42(ii) a The fourth column of data indicates that the relative degree of importance of the user to the municipal planning is A13The relative importance degree of the node scale to the municipal planning is A23The relative importance degree of municipal planning to municipal planning is A33The relative importance of population density to municipal planning is A43(ii) a The fifth column of data indicates that the relative importance of the user to the relative population density is A14The relative importance degree of the node scale to the population density is A24The relative importance of municipal planning to population density is A34The relative importance of population density to population density is A44. The decision matrix is denoted by a as follows:
row-column normalization of the decision matrix
Sum by row
Determining feature vectors
Normalizing the elements of the feature vector
Obtaining a weight W ═ W for the influencing factor1，W2，……Wn]；
The reasonableness of the weight is detected according to the consistency ratio. The concrete rationality of detecting the weight according to the consistency ratio includes:
computing maximum feature root
Calculating a consistency index
Calculating a consistency ratio
If CR is less than 0.1, the weight is reasonable, otherwise, the quantization scale is adjusted to determine the weight again, wherein RI is a random consistency index, and referring to FIG. 7, RI is obtained by looking up a random consistency index table.
And S500, calculating the comprehensive score of each site selection scheme according to the weight and the influence factor scores, and selecting the site with the highest comprehensive score as the final address of the multi-station fusion data center station. Referring to fig. 8, a composite score S of each site selection scheme is calculated based on the weight and the influence score, wherein S is 1 × W1+S2×W2+S3×W3+S4W4. In FIG. 8, 0.3787>0.2796>0.2250>0.0987, therefore, building a "multi-station fusion" data center station in selected area 3。
The site selection method of the multi-station fusion data center station provided by the invention obtains scoring weights of user composition, node scale, municipal planning and population density through an analytic hierarchy process, and evaluates each site selection scheme according to user composition scoring, node scale scoring, municipal planning scoring, population density scoring and scoring weights. The site selection scheme obtained through evaluation can give consideration to influence factors such as user composition, node scale, municipal planning, population density and the like, so that the constructed multi-station fusion data center station can better serve the public, service society and regional development.
It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A multi-station fusion data center station site selection method is characterized by comprising the following steps:
determining a site selection scheme of a multi-station fusion data center station; determining influence factors of the addressing scheme according to the addressing scheme and acquiring specific information of the influence factors;
respectively scoring the influence factors of each addressing scheme according to the specific information of the influence factors to obtain influence factor scores;
determining the weight of each influencing factor through an analytic hierarchy process;
and calculating the comprehensive score of each site selection scheme according to the weight and the influence factor scores, and selecting the site with the highest comprehensive score as the final address of the multi-station fusion data center station.
2. The method of claim 1, wherein the influencing factors include user composition, node size, municipal planning, and population density.
3. The method of claim 2, wherein the step of scoring the influence factors of each addressing scheme according to the specific information of the influence factors comprises: scoring the user composition of the site selection scheme according to the electricity consumption in a period of time in the administrative region where the 'multi-station integration' data center station is located in each site selection scheme; scoring the node scale of the addressing scheme according to the area of the 'multi-station fusion' data center station in the addressing scheme; grading the administrative planning of the site selection scheme according to a relevant policy of an administrative region where a 'multi-station integration' data center station is located in the site selection scheme; and scoring the population density of the site selection scheme according to the population density of an administrative area in which the multi-station fusion data center station is located in the site selection scheme.
4. The method for site selection of a multi-station fusion data center station according to claim 3, wherein scoring the user configuration of the site selection scheme according to the power consumption of the multi-station fusion data center station in each site selection scheme in a period of time in the administrative area in which the multi-station fusion data center station is located comprises:
counting the electricity consumption in a period of time in an administrative area where a 'multi-station integration' data center station is located in the site selection scheme;
and normalizing the electricity consumption to obtain a user composition score S1.
5. The method of claim 3, wherein scoring the size of the nodes of the addressing scheme based on the area of the multi-station fusion data center station in the addressing scheme comprises:
formulating a node scale scoring standard of which the area is mapped to the node scale scoring;
and scoring and normalizing according to the node scale scoring standard to obtain a node scale score S2.
6. The method for site selection of a multi-station fusion data center station according to claim 3, wherein scoring the administrative plan of the site selection scheme according to the policy related to the administrative domain in which the multi-station fusion data center station is located in the site selection scheme comprises:
acquiring policy files related to a multi-station fusion data center station;
setting an administrative planning scoring standard for mapping the content of the policy file to the administrative planning scoring;
and scoring and normalizing according to the administrative planning scoring standard to obtain an administrative planning score S3.
7. The method of claim 3, wherein scoring the population density of the siting plan based on the population density of an administrative area in the siting plan in which the multi-station fusion data center station is located comprises:
counting the latest population density data in administrative regions where 'multi-station fusion' data center stations are located in the site selection scheme;
the population density data is normalized to obtain a population density score S4.
8. The method of claim 1, wherein determining the weight of each of the influencing factors by analytic hierarchy process comprises:
constructing a decision matrix of the influence factors by using a pairwise comparison method and a quantization scale of 1-9, wherein the decision matrix is a positive reciprocal matrix;
row-column normalization of the decision matrix
Sum by row
Determining feature vectors
Normalizing the elements of the feature vector
Obtaining a weight W ═ W for the influencing factor1，W2，……Wn]；
The reasonableness of the weight is detected according to the consistency ratio.
9. The method of claim 8, wherein detecting the reasonableness of the weights based on the consistency ratio comprises:
computing maximum feature root
Calculating a consistency index
Calculating a consistency ratio
If CR is less than 0.1, the weight is reasonable, otherwise, the quantization scale is adjusted to determine the weight again, wherein RI is a random consistency index obtained by looking up a random consistency index table.
10. The method of claim 1, wherein a composite score S1 xw is calculated for each site selection scheme based on the weights and the influence scores1+S2×W2+S3×W3+S4W4。
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN103632203A (en) * | 2013-09-23 | 2014-03-12 | 国家电网公司 | Distribution network power supply area division method based on comprehensive evaluation |
| CN104463548A (en) * | 2014-12-25 | 2015-03-25 | 南京大学 | Carriage quantitative selection method influenced by multiple factors |
| CN106228403A (en) * | 2016-07-20 | 2016-12-14 | 武汉斗鱼网络科技有限公司 | A kind of user based on step analysis algorithm is worth methods of marking and system |
| CN109767042A (en) * | 2019-01-17 | 2019-05-17 | 中国人民解放军陆军工程大学 | Works of service team for civil air defence's site selecting method based on land used assessment |
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2020
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| CN103632203A (en) * | 2013-09-23 | 2014-03-12 | 国家电网公司 | Distribution network power supply area division method based on comprehensive evaluation |
| CN104463548A (en) * | 2014-12-25 | 2015-03-25 | 南京大学 | Carriage quantitative selection method influenced by multiple factors |
| CN106228403A (en) * | 2016-07-20 | 2016-12-14 | 武汉斗鱼网络科技有限公司 | A kind of user based on step analysis algorithm is worth methods of marking and system |
| CN109767042A (en) * | 2019-01-17 | 2019-05-17 | 中国人民解放军陆军工程大学 | Works of service team for civil air defence's site selecting method based on land used assessment |
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| CN113657709A (en) * | 2021-07-06 | 2021-11-16 | 南京嘉环科技股份有限公司 | Site selection method and site selection device |
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