DOE OSTI2019
Introduction: Solar soft costs can account for 60% of the cost of an installed solar system, thus cost reductions for solar hinge on reducing soft costs. Soft costs are most frequently defined as non-hardware costs. Defining something by what it isn’t makes it inherently difficult to identify what exactly it is, which in turn makes it difficult to study. Our goal is to develop an ontology that identifies 1) a consistent and defined soft cost vocabulary, 2) who creates, shares and acquires soft cost knowledge, and 3) the learning processes used to facilitate knowledge flows. Ultimately, identifying these aspects of solar soft costs will provide a pathway for public policy and market interventions to reduce soft costs. Methods: To build the solar soft cost ontology (SSCO) we built a corpus of solar soft cost literature (through keyword search), then coded the corpus for all concepts related to or influencing costs, barriers, or time. Finally, we organized the concepts into taxonomies, including soft costs and network actors, and developed the properties (i.e., attributes and relationships) that link the concepts. In phase two, we will code a set of solar installer case studies and complimentary solar sector (e.g., distributors, software providers, trade organizations) firm case studies to update the SSCO, documenting changes and additions resulting from the use of practitioner feedback. Results and Discussion: The resulting SSCO includes concepts, attributes, and relationships that provide a rich and deep knowledge base that merges academic and practitioner expertise to create a shared and exhaustive vocabulary related to soft costs, a network of actors that impact those soft costs, and the attributes and relationships that connect them. The applications of the SSCO extend to a diverse group of stakeholders, including researchers, policy makers, and practitioners, engaged in reducing solar soft costs.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗