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DOE Solar Energy Technologies Program

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DOE Solar Energy Technologies Program ( doe-solar-energy-technologies-program )

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environment; a system performance module, which simulates the hour-by-hour output of the selected system for the lifetime of a project; a cost input module for providing simple or detailed cost inputs for system components; and a financial analysis module for calculating system economics. The modules work in concert to generate the physical and financial figures of merit relevant to the particular user. Subcontracted work, listed in Table 6, includes a graphical user interface expert, Software Design Works, which was retained to aid in the development of the interface. Steven Janzou and the University of Wisconsin were retained to assist in model code development. 3. Results and Accomplishments 3.1 Analysis Improving our understanding of the long-term market potential for solar technologies is an important part of our analysis task. For example, SolarDS is being developed to examine sensitivity of PV market share to PV capital cost and performance, rate structures, competition with other DG technologies, tax and environmental policies, storage and load controls, and financing options and consumer choice Reviewing the program’s technical and economic targets and carrying out detailed value analysis of solar technologies are other impactive analysis activities. This year has seen quantification of how the value of solar energy to the end-user is influenced by rate structures, demand charges, and demand profile. In addition, best practices are being identified and documented for estimating benefits and cost of distributed PV technology. Information sharing is being enhanced through implementation of a Web-based clearinghouse on the value of distributed grid-tied PV, through incorporating best practices into a Web-based benefit-cost calculator, and through informing state-level policymaking groups. 3.2 Benchmarking Major results, as input to SDA models and the Multi-Year Program Plan, are shown in Table 2. Table 2. Key PV Benchmarking Parameters for Systems-Driven Approach Analyses System Units Element Res. Com Util. OffGrid Island Size Module Price Module eff. Inverter Price Inverter Size DC-AC eff. Inverter Life Other BOS Install Other Installed Sys. Price Lifetime kW $/Wdc % $/Wac kW % Years $/Wdc $/Wdc $/Wdc $/Wdc 4 150 4.00 3.50 13.5 13.5 0.90 0.60 4 150 90 92 5 10 0.61 0.54 1.66 0.55 1.30 1.10 8.47 6.29 30 30 1 1 0.5 0.45 10M 1.2 3.30 4.00 13.5 13.5 0.46 0.90 150 2.4 92 90 10 5 0.97 2.10 0.27 1.00 0.55 4.71 5.55 12.71 30 30 1 1 0.15 3.6 Years Degradation %/Yr O&M cost 3.3 Modeling % inst. price In the analyses specific to the MYPP, the model was populated with the 2005 benchmark parameters to calculate the 2005 reference LCOE. Sensitivity evaluations were made by changing one parameter at a time to the 2011 target, while leaving all others at the 2005 reference level. Overall impact was explored by changing all parameters to the 2011 targets. Figure 1 shows an example of the results; this example is of the TIO systems analysis for residential PV systems. Similar analyses have been performed for systems in the other reference applications as well. $0.350 $0.300 $0.250 $0.200 $0.150 $0.100 $0.050 $- Residential PV Reference System Total Energy Price ($/kWh) 151 Systems Integration and Coordination 2005 Benchmark 2011 Target 2020 Target Fig. 1. Residential PV reference system total energy price ($/kWh) for current and future years. O&M Other Costs Installation BOS Inverter Modules

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