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Cost-Effectiveness of Distributed Generation Technologies In the case of PV modules produced between 1976 and 1992, the progress ratio is 82%. This implies that the price of the technology is reduced to 0.82 of its previous level after a doubling of cumulative capacity sold. One would expect more mature technologies to have higher progress ratios (the upper limit is 100%) until the technology reaches a point where learning by experience no longer drives cost reductions. On the other hand, emerging technologies tend to have lower progress ratios and show larger cost reductions as more is learned about ways to improve production or lower material costs. Learning curves, because they are based on the demonstrated capability of companies to improve manufacturing or production processes, represent a powerful way to predict future costs of technologies. In this study, learning curves and progress ratios are used to predict future capital costs for the different DG technologies up through 2020. While this approach does not take into account all the economic factors affecting capital costs (such as commodity prices), the method has been implemented successfully in the past in energy policy applications. Itron used a series of data sources on DG technology production volumes and prices including historical SGIP cost data, literature surveys, and DG technology industry interviews. Based on the collected information, learning curve models were developed for each examined DG technology. The developed learning curves were then used to forecast possible future costs of the technologies out through 2020. Figure A-2 is a summary of the estimated installed costs of the examined DG technologies from 2008 through 2020 based on learning curve projections. Figure A-2: Summary of Learning Curve DG Technology Cost Projections Itron, Inc. Appendix A-3 DG TechnologiesPDF Image | Cost-Effectiveness of Distributed Generation Technologies
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