Improving Cost and Schedule Performance on Large Energy Infrastructure Deployment Projects: Establishment of Best Practices for Risk Management and Organizational Learning based on Nuclear Power Generation Project Assessments.

摘要

Improving the cost of energy generation projects is an objective of the various stakeholders partaking in the development and procurement of energy generation infrastructure. These projects have historically suffered from significant cost and schedule overruns, which are often caused by externalities or risks that are inadequately assessed prior to the project start, and hence ineffectively managed over the course of the project. This study uses nuclear power generation as a test-case to assess the causes of these externalities, and to develop potential improvements. The nuclear power industry has historically been plagued with considerable power plant deployment risks; project cost and schedule overruns present a significant risk to investors. The drivers to nuclear-power deployment risks over other technologies include the high cost of knowledge-workers in the nuclear field, the high cost of technology development, the highly specialized quality assurance process and the high level of regulation in the industry. All of these risk drivers are anticipated to continue to be significant issues, and with the recent events at the Fukushima Daiichi nuclear plant, the regulatory landscape is even more uncertain for nuclear power deployment. The nuclear industry has responded by employing risk management practices to reduce the uncertainty associated with nuclear power plant deployment. Although these risk management practices have been put in place, considerable cost and schedule excursions have continued to occur in the construction of recent nuclear power plant projects.;This paper proposes to improve risk management by identifying limitations within the existing standards of practice related to risk identification, assessment and organizational learning. For risk identification and assessment, a standard risk register and objective-driven methods are proposed. For organizational learning, a method of measuring learning relative to risk management is proposed, and a framework for institutional learning across the nuclear industry was proposed, and is presently being implemented.