Schedule Forecast Optimization for the Construction and Commissioning of Nuclear Power Plants

Abstract

The purpose of this work is to determine an appropriately accurate and descriptive regression utilized to express the construction and commissioning period of modern nuclear power plants. It specifically aims to provide this tool for use in countries seeking to establish their own nascent commercial nuclear programs. It also seeks to expand the breadth of centralized public information on historical build programs, as well as offering recommendations on optimal build strategies for future nuclear projects. Multiple regression based upon a range of variables delineated by both statistical measures and performance in a series of increasingly restrictive regressions is utilized. Technical and project background data were collected on each reactor contained within the IAEA’s Power Reactor Information System (PRIS) database and subjected to a range of statistical tests, whereafter this data was collapsed into discrete site-based projects that accumulated the overall characteristics of reactors constructed over the same period and of the same design. A seven-factor Gaussian Process Regression (GPR) utilizing Reference Unit Power, Pressurizer Use, Democracy Index, Regulatory Burden, Year of Construction Commencement, Standard UO2 Enrichment, and Standard Pressure was confirmed to provide greater accuracy than utility or vendor estimates and is appropriate for use when evaluating reactor construction bids, potentially saving billions of dollars over the life of the program.