Comprehensive Assessment and Empirical Research on Green and Low-Carbon Technologies in the Steel Industry

Abstract

The iron and steel industry is the leading industry supporting China’s industrial sector. Currently, there is less assessment work on green and low-carbon technologies for the iron and steel industry. This study clarifies the overall strategy of technology assessment by researching the relevant theories and methods of technology assessment. The study further establishes a scientific and reasonable comprehensive assessment index system of green and low-carbon technologies for the iron and steel industry from the aspects of technology index, economy and promotion, and application, including factors such as 11 indexes, the amount of energy saving, carbon dioxide emission reduction, and the resource recovery rate by utilising analytical and comprehensive methods and combining with the characteristics of the technologies. By analysing and comparing the advantages and disadvantages of the commonly used assessment methods, the entropy weighting method, grey correlation analysis method, and TOPSIS (technique for order preference by similarity to an ideal solution) method are combined and optimised to construct a comprehensive assessment model. The Latin hypercube sampling method is also introduced to analyse the technical parameters in combination with the evaluation model. Finally, fourteen iron and steel green and low-carbon technologies were selected for case assessment and uncertainty analysis of technical parameters, and it was found that the comprehensive assessment result of gas combined cycle power generation technology was optimal. After determining the weights of each assessment indicator through the entropy weighting method, it is concluded that the technical performance indicator > economic indicator > promotional indicator. A comparative analysis of the results under the three preference decisions concludes that technical performance is the main obstacle to improving the comprehensive assessment score of the technology, followed by the economics of the technology. Finally, the uncertainty analysis of the technical parameters shows that the fluctuation of the technical parameters not only affects the performance of the technology, but also affects the weights of the indicators and the comprehensive evaluation results of the technology.