CN108038572A - Method for predicting new situation load potential in rural area - Google Patents
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Abstract
The invention provides a method for predicting the potential of a new situation load in a rural area, which comprises the following steps: analyzing influence factors according to family characteristics, government input conditions, market characteristics and natural characteristics, and primarily constructing input-output indexes; screening input-output indexes by using SPSS analysis software; determining a final input-output index system according to the screening result; performing data processing on the input-output index vector; constructing a rural electric energy alternative short-term potential analysis model; and (4) predicting according to the rural electric energy alternative recent potential analysis model and an input-output index system by using a DEAP calculation tool. The method has the advantages that through the potential model research of electric energy substitution, the rural electric energy substitution work can be scientifically and accurately researched and analyzed; by combining the rural electric energy substitution potential values, a more reasonable rural electric energy substitution priority sequence of each region is designed, and the influence of urban haze on the life and production of residents can be quickly eliminated.
Description
Technical Field
The invention relates to a load potential prediction method, in particular to a new situation load potential prediction method in rural areas.
Background
Non-renewable energy sources in China are gradually reduced, and more people propose to replace the non-renewable energy sources by clean energy sources. With the continuous development of industry, on one hand, the economic development is restricted due to the energy shortage, and on the other hand, the problem of human living environment pollution, especially the haze problem frequently appearing in recent years, is caused by the large use of fossil energy and other traditional energy supply modes.
At present, severe haze frequency occurs in northern areas such as Jingjin Ji in winter, the living lives of numerous citizens are seriously influenced, and huge hidden dangers are buried for the health of the masses in the future. The amount of heating coal in winter in most areas in the north is greatly increased, so that the emission of atmospheric pollutants is sharply increased, the energy consumption in rural areas mainly comprises coal, straws, firewood and other energy sources, and the contribution to severe haze also accounts for a certain proportion.
In order to solve the urban haze problem, a scheme of replacing electric energy is developed in 2013, 8 months and 15 days, a new concept of energy consumption is proposed vigorously, namely 'electricity replaces coal, oil and electricity from a distance', the electric energy replacement work is started comprehensively in a company management area, the advantages of convenience, safety, cleanness, high efficiency and the like of electric energy of each unit to which the company belongs are required to be fully exerted, and the electric energy consumption proportion of the electric energy in the terminal energy consumption market is continuously improved, so that the social energy conservation and emission reduction are promoted, and the urban haze problem is solved.
Related people of the national grid company introduce the following: electric energy substitution is an important means for accelerating energy structure adjustment and is also an important measure for promoting the rise of the ratio of clean energy consumption. Many provinces make a lot of efforts aiming at the measure, and also obtain more remarkable results, for example, because Jilin province is located in northern high and cold areas, the heating period in winter reaches 5 months, and the heating mode is single, rural areas mostly use firewood and straw for heating, energy structure adjustment is imperative, the change of the heating mode in rural areas in winter needs to be emphatically promoted, after Jilin electric power company learns the situation through market research, the electric heating is actively promoted in the aspect of heating, so that the electric heating gradually enters the sight of new farmers in new rural areas.
By analyzing the progress and the effect of the electric energy replacement work completed by each provincial electric power company, the electric energy replacement work in rural areas can not only play a great role in promoting the environmental quality, the energy efficiency and the economic development, but also have great implementation potential, and can be carried out from multiple aspects of cooking, heating, traffic, production and the like.
However, domestic and foreign experts have few comprehensive and specific researches on electric energy substitution in rural areas, the researches on electric energy substitution are only limited to a certain part, and currently, few relevant policies and mechanisms beneficial to electric energy substitution are still available in China, especially for calculating the electric energy substitution amount of a specific main electric energy substitution mode in rural areas, researches in documents only stay in suggestions and suggestions on future development directions and policies, but no relevant researches on how to calculate potential values of rural electric energy substitution in various provinces exist in China.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a method for predicting the potential of a new situation load in a rural area, which can more scientifically and accurately research and analyze the rural electric energy substitution work.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows: a method for predicting the potential of a new situation load in a rural area comprises the following steps: analyzing influence factors according to family characteristics, government input conditions, market characteristics and natural characteristics, and primarily constructing input-output indexes; screening the input-output index by using SPSS analysis software; determining a final input-output index system according to the screening result; performing data processing on the input-output index vector; constructing a rural electric energy alternative short-term potential analysis model; and predicting according to the rural electric energy alternative recent potential analysis model and the input-output index system by using a DEAP calculation tool.
Further, the input-output index is constructed based on the following indexes: the income level of rural families, the population number of the rural families, the culture degree of rural residents, the investment of rural power grid infrastructure, the energy price, the storage amount of fossil energy and the planting area.
Further, the step of screening the input-output index by using the SPSS analysis software specifically includes: performing factor analysis on the input-output index by using SPSS analysis software; judging the effectiveness and the suitability of the factor analysis; and selecting the comprehensive index to replace the original index.
Further, the judgment conditions of the effectiveness and the suitability of the discriminant factor analysis are as follows: the KMO value is more than 0.5 factor and is analyzed effectively; the significance probability Sig is less than 0.01, which indicates that the method is suitable for factor analysis.
Further, the data processing is performed on the input-output index vector based on the following equation:
wherein n represents the number of rural areas, and the four values of j represent four indexes respectively.
Further, the step of constructing the rural electric energy alternative recent potential analysis model specifically comprises the following steps:
obtaining a DEA input and output expression based on rural electric energy substitution potential analysis according to a DEA model:
x j ＝(x 1j ，x 2j ，x 3j ) T >0 j＝1,2,…，n
y j ＝(y 1j ) T >0 j＝1,2，…,n
wherein j =1,2,n represents the number of selected provinces, x j And y j Respectively represents the numerical value of the corresponding input-output index of each provincial rural area;
constructing a rural electric energy replacement recent potential analysis model according to the input and output expressions and the input-output index system:
compared with the prior art, the invention has the advantages and positive effects that: through the potential model research of electric energy substitution, the rural electric energy substitution work can be researched and analyzed more scientifically and accurately, and the method has important practical significance; by combining the rural electric energy substitution potential value, a more reasonable rural electric energy substitution priority sequence of each region is designed, namely electric energy substitution work can be preferentially expanded when the electric energy substitution potential is large, and the influence of urban haze on the life and production of residents can be quickly eliminated.
Drawings
FIG. 1 is a flow chart of the present invention.
Detailed Description
In order that those skilled in the art will better understand the disclosure, the invention will be described in further detail with reference to the accompanying drawings and specific embodiments. It is to be understood that the described embodiments are merely some embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention. It should be noted that the figures and description omit representation and description of components and processes that are not relevant to the present invention and that are known to those of ordinary skill in the art for the sake of clarity.
In the description of the present invention, it is to be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", and the like indicate orientations or positional relationships based on orientations or positional relationships shown in the drawings, and are used merely for convenience of description and for simplicity of description, but do not indicate or imply that the devices or elements referred to must have specific orientations, be constructed in specific orientations, and be operated, and thus, are not to be construed as limiting the present invention.
As shown in fig. 1, the present embodiment provides a method for predicting new situation load potential in a rural area, which includes the following steps:
step 1: analyzing influence factors according to family characteristics, government input conditions, market characteristics and natural characteristics, and primarily constructing input-output indexes.
The influence factor that influences rural energy consumption is more, and every influence factor all can cause the influence to the in service behavior of future energy, and wherein comparatively main several points include: family features, government input, market features, and nature features.
The input-output index is constructed based on the following indexes: the income level of rural families, the population number of the rural families, the culture degree of rural residents, the investment of rural power grid infrastructure, the energy price, the storage amount of fossil energy and the planting area.
Step 2: and (4) screening the input-output index by using SPSS analysis software.
The steps of screening the input-output index by using SPSS analysis software specifically comprise:
1. performing factor analysis on the input-output index by using SPSS analysis software;
2. validity and suitability of discriminant factor analysis: the discrimination conditions of the effectiveness and the suitability of the discriminant factor analysis are as follows: the KMO value is more than 0.5, and the factor analysis is effective; the significance probability Sig is less than 0.01, which indicates that the method is suitable for factor analysis;
3. and selecting the comprehensive index to replace the original index.
And 3, step 3: and determining a final input-output index system according to the screening result.
By means of input data and factor analysis of related indexes and referring to related documents, rural village electric energy substitution potential analysis input and output indexes are obtained, and basically the indexes need to meet the selection principle of indexes in DEA analysis, such as the unity of data apertures, the comparability principle, the availability principle and the comprehensive principle.
And 4, step 4: and carrying out data processing on the input-output index vector.
Because the factor score has a negative number, in order to satisfy the non-negativity of the input and output data of the DEA method, the data is subjected to non-dimensionalization processing, and the data is controlled between 0 and 1. The specific calculation is shown in the formula:
wherein n represents the number of rural areas, and the four values of j represent four indexes respectively.
And 5: and constructing a rural electric energy alternative recent potential analysis model.
The steps of constructing the rural electric energy alternative recent potential analysis model specifically comprise:
1. and obtaining a DEA input and output expression based on rural electric energy substitution potential analysis according to the DEA model:
x j ＝(x 1j ，x 2j ，x 3j ) T >0 j＝1,2,…，n
y j ＝(y 1j ) T >0 j＝1,2，…,n
wherein j =1,2,n represents the number of selected provinces, x j And y j Respectively represents the numerical value of the corresponding input-output index of each provincial rural area;
2. constructing a rural electric energy alternative recent potential analysis model according to the input and output expression and the input-output index system
Wherein λ j For the maximum value of the electric energy utilization ratio under all the provincial existing power generation and power utilization technology levels, namely the optimal solution, s + And s - The method is the changeable quantity of input and output indexes in rural electric energy substitution potential analysis of each province. For the DEA analysis of the ineffective or weak effective provinces, the input-output index can be further adjusted to enable the rural electric energy consumption of the province to catch up with the optimal province, and the improvement target value of the rural input and output of the optimal province is changed.
Step 6: and predicting according to the rural electric energy alternative recent potential analysis model and the input-output index system by using a DEAP calculation tool.
The method for predicting the new situation load potential in the rural areas is further explained by taking the rural electric energy consumption characteristics of 26 provinces in the country as an example.
(1) The DEAP2.1 software is correctly downloaded and the SPSS software is correctly installed as explained.
(2) Establishment of input-output System
Specific analysis indexes influencing rural electric energy substitution are determined as follows:
(1) income level of rural families
(2) Number of rural family population
(3) Cultural degree of rural residents
(4) Rural power grid infrastructure investment
(5) Energy price
(6) Fossil energy storage capacity
(7) Area of planting
(3) Factor analysis using software
The practical significance of the extracted common factors can be reasonably explained, the factor load matrix is rotated according to the non-uniqueness of the factor load, and a rotation matrix is obtained, and the specific factor analysis result is shown as follows.
TABLE 1 examination of KMO and Bartlett
Total variance explained in Table 2
TABLE 3 rotating composition matrix
Firstly, the original indexes are analyzed, namely, the correlation test of the input indexes is carried out: the test value of KMO was 0.702, and the Butterworth sphere statistic Sig was 0.001, which was found to be suitable for factorial analysis based on the standard of KMO test. As can be seen from the total explained variance table obtained after the principal component analysis, more than 72.773% of the influence factors can be explained by the three principal components, and most information of the original data can be reflected, so that all the original indexes can be represented by the three comprehensive indexes. According to the rotating component matrix, the first comprehensive index has larger load on rural fuel energy price, rural electric appliance price and rural power grid investment, and is mostly related to the attraction of electric energy to rural users, so that the index can be called rural electric attraction index and is set as Y1; the second comprehensive index has larger load on rural employment proportion and rural per capita income, is mostly related to the economic conditions of rural families, can be called as the rural family economic level index and is set as Y2. The third comprehensive index has larger load on the fossil energy reserve and the biomass energy planting area, is mostly related to the storage amount of non-electric energy sources, can be called as a rural fossil energy storage amount index and is set as Y3.
(4) Establishment of input-output System
According to factor analysis, the rural electric energy is finally shown as the following table instead of recent potential analysis input-output index system:
table 4 rural electric energy alternative recent potential analysis input-output index system
(5) Prediction by DEAP2.1 software
According to the established analysis model and related data, DEAP2.1 software is used for calculating the Comprehensive Efficiency (CE), the pure technical efficiency value (PTE), the scale efficiency value (SE) and the relaxation value of the output variable of the electric energy utilization in each rural area.
Table 5 summary of efficiencies
TABLE 6 relaxation values of output variables
The electric energy substitution potential is a relative value rather than an absolute value, and the electric energy use ratio of 0 does not represent that the electric energy substitution in the region cannot be further implemented, but means that the possibility of further electric energy substitution is low in terms of the current optimal technical level of the region.
The sequence of electric energy substitution should be arranged according to the rural potential of each province.
According to the analysis and research results, the electric energy utilization proportion of all the rural areas is divided into three types:
1. the first is the effective DEA class. The DEA effectiveness is the optimum meaning, which means that in the data comparison of the decision unit, the consumption is the least, the output is the most, the capacity utilization rate is 100%, and the text indicates the full utilization of the electric energy. The rural power utilization mode of Hainan province is an effective DEA class, and can be used as a power utilization standard for other provincial rural imitations, the provincial rural electric energy utilization reaches the national optimum under the existing energy utilization scale and technical level, the electric energy utilization ratio does not have a space for improving, and further optimization is not needed.
2. The second type is a weak effective DEA effective type, and the weak effective indicates that the unit achieves the effect of scale, namely the unit is just invested, and is neither too large nor too small, and the scale reward is in the best state from the critical point between increasing to decreasing. The weak and effective province is the Qinghai province, the rural power utilization capacity of the province reaches the optimum under the energy utilization scale of the province, the scale reward is in the stage from increasing to decreasing, and no space is provided for improvement.
3. The third type is non-DEA effective, and specifically comprises the step of removing the residual provinces of the first type and the second type, rural electric energy utilization of the provinces does not reach the optimum under the province energy utilization scale, the optimum electric energy utilization proportion is not completely reached under the existing energy utilization technical level and scale, the rural electric energy utilization of the provinces has high electric energy utilization and improvement potential, particularly, the rural electric energy substitution potential of the two provinces of Shanxi and inner Mongolia is the maximum, the electric energy utilization proportion can be improved by more than 80% in proportion and is respectively 83.9% and 80.2%, so the two provinces are required to be placed at the head of electric energy substitution work in the category, the electric energy substitution potential of the rural areas of other provinces is small, and the rural electric energy substitution potential of the other provinces is also a substitution space.
(6) Calculating the final result
As can be seen from the calculation of the relaxation values of the output variables and the total energy consumption of the rural areas of the provinces in the table above, when the electric energy substitution project is carried out on the existing electric energy utilization scale, the electric energy consumption proportion of the rural areas of the provinces in China can be averagely improved by 28.8 percent, and the improvement space of the electric energy is totally 742.35 hundred million kilowatt-hours.
The invention has the beneficial effects that: through the potential model research of electric energy substitution, the research and the analysis of rural electric energy substitution work can be more scientifically and accurately carried out, and the method has important practical significance; by combining the rural electric energy substitution potential values, a more reasonable rural electric energy substitution priority sequence of each region is designed, namely electric energy substitution work can be preferentially developed when the electric energy substitution potential is large, and the influence of urban haze on the life and production of residents can be quickly eliminated.
While one or more embodiments of the present invention have been described in detail, the description is in the nature of preferred embodiments of the invention and is not intended to limit the scope of the invention. All equivalent changes and modifications made within the scope of the present invention should be covered by the appended claims.
Claims (6)
1. A method for predicting the potential of a new situation load in a rural area is characterized by comprising the following steps: the method comprises the following steps:
analyzing influence factors according to family characteristics, government input conditions, market characteristics and natural characteristics, and primarily constructing input-output indexes;
screening the input-output index by using SPSS analysis software;
determining a final input-output index system according to the screening result;
performing data processing on the input-output index vector;
constructing a rural electric energy alternative short-term potential analysis model;
and predicting according to the rural electric energy alternative recent potential analysis model and the input-output index system by using a DEAP calculation tool.
2. The method of predicting the new situation load potential in rural areas according to claim 1, wherein: the input-output index is constructed based on the following indexes: the income level of rural families, the population number of the rural families, the culture degree of rural residents, the investment of rural power grid infrastructure, the energy price, the storage amount of fossil energy and the planting area.
3. The method of predicting the new situation load potential in rural areas according to claim 1, wherein: the step of screening the input-output index by using the SPSS analysis software specifically comprises the following steps: performing factor analysis on the input-output index by using SPSS analysis software; the effectiveness and suitability of discriminant factor analysis; and selecting the comprehensive index to replace the original index.
4. The rural area new situation load potential prediction method of claim 3, characterized in that: the judgment conditions of the effectiveness and the suitability of the discriminant factor analysis are as follows: the KMO value is more than 0.5, and the factor analysis is effective; the significance probability Sig is less than 0.01, which indicates that the method is suitable for factor analysis.
5. The method of predicting the new situation load potential in rural areas according to claim 1, wherein: the data processing is performed on the input-output index vector based on the following equation:
wherein n represents the number of rural areas, and the four values of j represent four indexes respectively.
6. The method of predicting the new situation load potential in rural areas according to claim 1, wherein: the steps of constructing the rural electric energy alternative recent potential analysis model specifically comprise:
obtaining a DEA input and output expression based on rural electric energy substitution potential analysis according to a DEA model:
x j ＝(x 1j ，x 2j ，x 3j ) T >0 j＝1,2,…，n
y j ＝(y 1j ) T >0 j＝1,2，…,n
wherein j =1,2,n represents the number of selected provinces, x j And y j Respectively represents the numerical value of the corresponding input-output index of each provincial rural area;
constructing a rural electric energy alternative recent potential analysis model according to the input and output expressions and the input-output index system:
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108764584A (en) * | 2018-06-05 | 2018-11-06 | 国网浙江省电力有限公司 | A kind of enterprise electrical energy replacement potential evaluation method |
| CN115296424A (en) * | 2022-10-10 | 2022-11-04 | 北京智盟信通科技有限公司 | Distributed power supply comprehensive monitoring system and method based on fusion terminal |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108764584A (en) * | 2018-06-05 | 2018-11-06 | 国网浙江省电力有限公司 | A kind of enterprise electrical energy replacement potential evaluation method |
| CN108764584B (en) * | 2018-06-05 | 2021-04-09 | 国网浙江省电力有限公司 | Enterprise electric energy substitution potential evaluation method |
| CN115296424A (en) * | 2022-10-10 | 2022-11-04 | 北京智盟信通科技有限公司 | Distributed power supply comprehensive monitoring system and method based on fusion terminal |
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