Budget and Cost Contingency Cart Models for Power Plant Projects

Abstract

Cost overruns are a ubiquitous feature of construction projects, and realistic budgeting at the development stage plays a significant role in their control. However, the application of existing models to budgeting for power plant projects is restricted by the limited amount of project-specific cost data available. This study overcomes this by using a Classification and Regression Tree (CART) approach involving mixed methods of website visits, document study, and expert opinion to predict the amount of project cost (PC) and cost contingency (CC) needed to cover probable cost increases by the use of models containing readily available project attributes and national economic parameters at the project development stage. The modeling process is demonstrated and tested with a case study involving 58 Bangladeshi power plant projects – producing average absolute errors ranging from 0.7% to 1.7% and enabling project cost, inflation rate, and GDP to be identified as significant factors affecting PC and CC modeling. The approach can be applied to predict the PC during preliminary budgeting and selecting a project type and location aligned to the country’s economic status and policy-making strategies, thus facilitating further investment decisions.

Simulation of Carbon Emission Reduction in Power Construction Projects Using System Dynamics: A Chinese Empirical Study

“…For a long time, scholars have focused on the technical and economic aspects of PCPs. For example, improving the quality of PCPs in the construction stage [16,17], enhancing the risk control level of PCPs [7,18], and evaluating the cost and economic performance of PCPs [19,20]. In addition, Zhang et al evaluated the key characteristic indicators of PCPs, and the evaluation results are conducive to the investment decision for a PCP, and the research results show that the increase in PCPs is important for promoting economic growth [21].…”