This paper describes a pragmatic method of searching for the key inputs to a system dynamics model. This analysis is known as screening. The goal is to learn which of the many uncertain inputs stand out as most influential. The method is implemented with readily available software and relies on the simple correlation coefficient to indicate the relative importance of model inputs at different times in the simulation. The screening is demonstrated with two examples with step-by-step instructions. The paper recommends that screening analysis be used in an iterative process of screening and model expansion to arrive at tolerance intervals on model results. The appendices compare screening analysis with analytical methods to identify the key inputs to system dynamics models.
Abstract:As states across the country struggle to increase local development of renewable energy, policymakers are turning to innovative program designs to meet their renewable electricity targets. Massachusetts recently adopted a unique, auction-based price support mechanism for the solar portion of its renewable portfolio standard. During the program development process, the Massachusetts Department of Energy Resources (DOER) used system dynamics to simulate potential solar renewable energy certificate market conditions under the proposed regulations. The modeling exercise resulted in several program design changes that will lead to a more stable certificate market. System dynamics can be a useful tool for developing and improving sustainability programs.
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