Study On The Cost Monitoring And Feedback Control Strategy Of Power Grid Project Whole Procedure

As China’s economic growth, the power industry as an economic development leading industry, the rapid growth of grid investment has become a necessity. Grid construction projects usually are large scale, has technical complexity and the construction environment is variable, while from planning and design to put into operation, a large amount of investment is involved, and therefore investment management and control of the power grid is an important part of business management. With the deepening of China’s competitive electricity market reform, electricity intensified among enterprises, power companies will face huge competition and challenges, low investment efficiency cannot meet the state and society on the grid business requirements. Reduce costs and improve efficiency is the best way to deal with competition and challenges.Firstly, this paper focuses on the importance and difficulties of grid project cost control, then compares differences in terms of cost control projects at home and abroad to explain the whole process cost control strategies of grid project, and then discusses key steps of cost controlling. Secondly, this paper compares several common cost control optimization methods, and ultimately selects a combination of qualitative and quantitative research models, namely feedback theory and PSR project support review model, and fuzzy clustering analysis. This theory can solve the problem that our response to project management issue is not timely, in this way obtaining the result of bias control deviation, system stability, fast response, anti-interference ability enhancement and so on. Finally, use the example of Research Institute of State Grid of Liaoning Province by the "Grid project life-cycle investment monitoring and control optimization research" project as an example, using fuzzy clustering analysis to list the factors affecting expenses, then draw order of importance of factors affecting expenses and draw expert system recommendations. It is possible to effectively control feedback stage of grid project, improve the viability indicators and investment benefits of the project.