Risk Control Of Coal-Acceptance Smart Management System In Implement Stage On Coal-Fired Power Plant

Coal is the main fuel source of Coal-Fired Power Plants (CPP), accounting for 70%-80% of the total costs. Many problems have been exposed in traditional coal management, such as backward technology, too many involved departments, inefficient management, and human disturbance. Nowadays, with highly development and continuous integration of Internet of Things (IOT) and Information Technology (IT), how to integrate the modern management ideas, methods, technologies and equipments into coal managements of CPP has become an urgent problem for power generation groups to be solved. At present, the project of Coal-acceptance Smart Management System of Coal-Fired Power Plant (CSMSCPP) has attracted a large amount of investments from the major power generation groups. However, by investigating the projects of IMSCPP been established and being under construction, there are many problems, such as construction progress delays. There are many reasons involved. On the one hand, the modern project has become increasingly complex. On the other hand, the poor risk management awareness and risk control ability of the participations are responsible, especially the contractor.To effectively control the risk of IMSCPP, the ISM method, vague sets and the theory of risk control are used in this paper, and focus on the stages of implementation of CSMSCPP from perspective of the contractor. Firstly, the original risk list was built, and the Interpretative Structural Modeling (ISM) method was introduced to analyze the logical and hierarchical relationship of the main risk factors, to build the hierarchic model, to determine the risk transfer relations. And the risk control index system was built on the results of ISM. Secondly, the vague sets method was used to quantitatively analyze the main risk factors of CSMSCPP to confirm the risk level of risk factors and CSMSCPP project. Then, according to risk control theory and risk transfer relations, different risk control strategies are applied to reduce the risk level to ensure the smooth implementation of the IMSCPP project. Finally, a project case was employed to verify the model and the results showed that the model is reasonable and effective. Moreover, it can provide reference and guidance for similar IMSCPP project.