Tyche: Technology Characterization and EvaluationΒΆ
Risk and uncertainty are core characteristics of research and development (R&D) programs. Attempting to do what has not been done before will sometimes end in failure, just as it will sometimes lead to extraordinary success. The challenge is to identify an optimal mix of R&D investments in pathways that provide the highest returns while reducing the costs of failure. The goal of the R&D Pathway and Portfolio Analysis and Evaluation project is to develop systematic, scalable pathway and portfolio analysis and evaluation methodologies and tools that provide high value to the U.S. Department of Energy (DOE) and its Office of Energy Efficiency & Renewable Energy (EERE). This work aims to inform decision-making across R&D projects and programs by assisting analysts and decision makers to identify and evaluate, quantify and monitor, manage, document, and communicate energy technology R&D pathway and portfolio risks and benefits. The project-level risks typically considered are technology cost and performance (e.g., efficiency and environmental impact), while the portfolio level risks generally include market factors (e.g., competitiveness and consumer preference).
Quick Start Guide covers how to set up an R&D decision context using Tyche by creating the necessary input datasets and writing the technology model. Technology Model Example provides a simple example of developing a technology model, and Analysis Example provides an analysis example of decision support analysis. High-level information on the approach behind Tyche is given in Approach and details on the mathematical formulation used to represent technologies and analyze investment impact is given in Mathematical Formulation. Optimization gives information on built-in optimization algorithms. The complete Python API for the Tyche codebase and the technology models provided with Tyche is in Python API.