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Cost-Effectiveness of Distributed Generation Technologies

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Cost-Effectiveness of Distributed Generation Technologies ( cost-effectiveness-distributed-generation-technologies )

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Appendix A Examined DG Technologies A.1 Introduction The technical foundation of the cost-effectiveness model is a set of technology-specific workbooks on the different distributed generation (DG) technologies investigated in this study. The workbooks represent compiled performance and cost data from a variety of sources, including the CPUC‘s Self-Generation Incentive Program (SGIP). Secondary sources of information come from the combined heat and power industry, as well as academic institutions, national labs, federal or state energy programs, or other energy research organizations. This appendix explains the methods used for estimating and forecasting costs. It also identifies the sources, assumptions, and results for each individual DG technology. DG technologies examined in the study include fuel cells, small gas turbines; internal combustion (IC) engines, microturbines, wind energy systems; organic rankine cycle systems; and storage batteries. The appendix begins with a discussion of learning curves and how learning curves are used to project future capital costs of DG technologies. Following the discussion on learning curves, we present a discussion on biogas collection and processing costs. A number of DG combustion technologies can be powered by natural gas or by biogas derived from anaerobic digestion processes (e.g., dairy digesters, landfill gas collection systems, and wastewater treatment facilities). Biogas collection and processing costs are treated collectively as they cut across the different DG technologies. A.1.1 Treatment of DG Learning Curves and Costs The overarching concept behind learning curves is that companies operating in competitive markets can ―learn‖ to manufacture goods more efficiently as they gain experience in the manufacturing and production of the goods. As a company sells more units of some technology or product ―X,‖ it learns ways to decrease production costs. These lower production costs can be transferred to the consumer as lower prices. The level of learning is quantified by a reduction in costs while the metric for gained experience is the total number of units sold. Itron, Inc. Appendix A-1 DG Technologies

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