Decision Support Systems for Improved Construction and Maintenance of Non-­Electrical Infrastructure for Energy

Stories about this project:

• Using artificial intelligence and fuzzy logic to help plan the future of energy

In order to effectively harness energy sources, we must design and construct facilities to extract, process, and deliver energy to end users. The construction, operation, and maintenance of such facilities require proper planning and execution in order to reduce risks and uncertainty, and to allow for rigorous efficiency, cost-effectiveness, and safety during each of these stages. Since future energy systems involve new technologies and have far-reaching social, economic, and political impacts, the development, operation, and upkeep of the associated infrastructure poses unique challenges for practitioners. The processes of constructing, operating, and maintaining long-life energy infrastructure assets, in comparison with other aspects of development such as design, pose many complex risks, including weather-related challenges, unproven technology, and unknown stakeholder interactions and interests. Therefore, risks that are not common to the construction and maintenance of other types of infrastructure may arise, and decision making will occur in an environment of considerable uncertainty. Data on such future energy infrastructure projects may be limited, of low quality, or not exist, and in such contexts, expert knowledge will be required in addition to project data for effective modeling and decision making. To address these issues, innovative modeling and decision-making approaches will be developed to address the unique characteristics of such projects, deal with new types of risks, and address data limitations in developing and validating models and decision-support tools.