A data-mining-based system design for cost management and control of power transmission and transformation project

Monitoring, managing and controlling the cost of a power transmission and transformation project (PTTP) plays an essential role in meeting the growing power demand and achieving the sustainable power project construction development. A model of cost management and control system for PTTP on the basis of the data mining theory is addressed. Seven tiers are designed to collect cost information, compile and store data, analyze the project costs and correct their deviations. These tiers specifically generate topology diagrams between all the factors giving rise to a fluctuation of the cost, analyze the correlation of factors, predict the cost, and raise several deviation-corrected proposals to users. A 110kV substation project is employed to demonstrate the proposed approach, in terms of the data deduction in three periods, including the budgetary estimation (BE), settlement and post evaluation. This system demonstration consists of price forecast by means of the well-established back-propagation neural network, price fluctuation tracking and cost analysis.