California Energy Commission. The Energy Commission expressed an interest in identifying how its modeling results could be used to support a robust decision making process. Prior to joining Aspen the director of the Integrated Energy Policy and Analysis department was selected to coordinate and conduct interviews with Western Interconnection Assessment Methodology (WIAM) team members, prepare a report, and make recommendations regarding the potential contribution of the RAND Corporation Exploratory Modeling (EM) and Robust Decision Making (RDM) methodologies to the Commission's analytical capabilities. The WIAM investigation of modeling alternatives found that traditional quantitative decision tools tend to seek single best estimates of the future or optimal solutions. EM is characterized by intuitive models, transparent data and cross functional collaboration. As an alternative to traditional modeling approaches, EM offers greater internal and external transparency, it synthesizes and leverages existing knowledge from each area of expertise within the organization, and it facilitates building internal consensus around solutions. Since complex models do not process a large number of futures quickly or reliably, RAND develops meta-models that can run more quickly to develop many representations of uncertain future conditions. The RAND Corporation's RDM methodology is an EM methodology that was developed over the last decade to address the prevalence of "deep uncertainties" in policy decisions. Deep uncertainty exists when analysts do not know, or the parties to a decision cannot agree on the appropriate models to describe the interactions among system variables, the probability distributions to represent uncertainty about the values of key variables and parameters in the models, and/or how to value the desirability of alternative outcomes. Explicit representations of deep uncertainties offer the opportunities of testing the vulnerability of policies to a large variety of futures. In doing so, the decision makers may ask questions such as, "Which policy performs well in many futures?" or "Which policy avoids unacceptable outcomes under the largest set of plausible futures?" Aspen's report identifies numerous potential applications of RDM at the Energy Commission. For example, the Energy Commission seeks to ensure that the State meets its resource portfolio goals. The CEC must balance these goals with other outcome metrics related to ensuring reliability, minimizing ratepayer and taxpayer cost impacts, and limiting greenhouse gas emissions. Several sources of deep uncertainty impinge the outcome metrics: the rate of technological change of resource technology alternatives, the infrastructure development path, future federal regulations and subsidy policies, and climate change impacts on the hydro supply and average and peak temperatures. This is a problem where there are several objectives that cannot be consolidated to a single outcome metric and there are several sources of uncertainty that cannot be captured by a number of variables with known probability distributions.