Joan E. Haysom

Multijunction Solar Cell Designs Using Silicon Bottom Subcell and Porous Silicon Compliant Membrane

A novel approach to the design of multijunction solar cells on silicon substrates for 1-sun applications is described. Models for device simulation, including porous silicon layers, are presented. A silicon bottom subcell is formed by diffusion of dopants into a silicon wafer. The top of the wafer is porosified to create a compliant layer, and a III-V buffer layer is then grown epitaxially, followed by middle and top subcells. Because of the resistivity of the porous material, these designs are best suited to high-efficiency 1-sun applications. Numerical simulations of a multijunction solar cell that incorporates a porous silicon-compliant membrane indicate an efficiency of 30.7% under AM1.5G, 1-sun for low-threading dislocation density, decreasing to 23.7% for a TDD of 107 cm-2.

Concentrated photovoltaics system costs and learning curve analysis

An extensive set of costs in

Analysis of Present and Future Financial Viability of High-Concentrating Photovoltaic Projects

/W for the installed costs of CPV systems has been amassed from a range of public sources, including both individual company prices and market reports. Cost reductions over time are very evident, with current prices for 2012 in the range of 3.0 ± 0.7

Reconstruction of solar spectral resource using limited spectral sampling for concentrating photovoltaic systems

/W and a predicted cost of 1.5

A novel instrument for cost-effective and reliable measurement of Solar Spectral Irradiance

/W for 2020. Cost data is combined with deployment volumes in a learning curve analysis, providing a fitted learning rate of either 18.5% or 22.3% depending on the methodology. This learning rate is compared to that of PV modules and PV installed systems, and the influence of soft costs is discussed. Finally, if an annual growth rate of 39% is assumed for deployed volumes, then, using the learning rate of 20%, this would predict the achievement of a cost point of 1.5

Collection and storage of direct spectral irradiance and DNI datasets with high temporal resolution for CPV energy yield assessments

/W by 2016.

The down-to-earth future of Si substrate multi-junction concentrator photovoltaics

Three metrics for the financial analysis of high-concentrating photovoltaic (HCPV) systems are assessed: capital costs for fully installed systems (in

Solar resource assessment with a solar spectral irradiance meter

/W), the levelized cost of electricity [in

Design of a multiplexer to characterize individual optics at a concentrating photovoltaic test site

/kilowatt-hours (kWh)], and the net present value [NPV (in

Multi-year ground-based irradiance dataset in a northern urban climate

)]. First, capital costs for HCPV systems are shown to have fallen at a steady rate and are characterised by a learning rate of 18 % with a 90 % confidence interval of 14–22 %. The analysis further combines this learning rate with future scenarios for volume growth rates to provide “lower,” “middle,” and “upper” projections for future capital costs of HCPV systems. These capital cost projections are used as inputs to the LCOE and NPV calculations, from which present and future project viability is assessed for a number of different project conditions. A case study for an HCPV deployment in Las Vegas exhibited an LCOE of