| Issue |
E3S Web Conf.
Volume 136, 2019
2019 International Conference on Building Energy Conservation, Thermal Safety and Environmental Pollution Control (ICBTE 2019)
|
|
|---|---|---|
| Article Number | 02018 | |
| Number of page(s) | 5 | |
| Section | Integrated Application of Renewable Energy in Buildings | |
| DOI | https://doi.org/10.1051/e3sconf/201913602018 | |
| Published online | 10 December 2019 | |
An interpretative structural model based on SPSS for the interaction analysis between risk factors of power grid
1 Economic and Technological Research Institute of Shanghai Power Grid, State Grid Shanghai Electric Power Company, 200122, Shanghai, China.
2 Energy Development Research Institute, Hunan University, State Grid Yiyang Electric Power Company Company, 413002, Yiyang, China
3 Key Laboratory of Intelligent Information Analysis and Comprehensive Optimization of Energy Internet in Hunan Province, Hunan University, 410082, Changsha, China
4 Economic and Technological Research Institute of Hunan Power Grid, State Grid Hunan Power Co., Ltd, 410007, Changsha, China
* Corresponding author’s e-mail: iheyuqing@163.com
The risk factors influencing the analysis of power grid investment are complicated and highly coupled. The analysis of the interaction of risk factors based on the traditional interpretative structural model, using the expert score to form correlation matrix, which is subjective. To increase the quantitative analysis and overcome the drawbacks of traditional model relying on experts’ experience, this paper proposes a new method to construct the interpretative structural model. Firstly, the evaluation index system of power grid investment is constructed, based on this, the collected history data of risk factors are processed and analysed through the correlation analysis of SPSS and the quantitative correlation matrix of risk factors is obtained, then the construction of interpretative structural model is finished. The constructed model provides the basis for the analysis and management of power grid investment.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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