Abstract

Micro-tracked CPV, in which cells move relative to fixed concentrating optics, allows CPV to be deployed in the same manner as fixed PV modules. Behind-the-meter applications in locations where there is a land/roof area cost for the space occupied by the modules confers a cost advantage to CPV compared to PV. The primary objective of the present paper is to estimate target prices below which CPV has a competitive advantage over PV. We analyse PV and CPV microgrids, optimizing the scheduling of power into and out of the battery in order to achieve the maximum savings compared to purchasing grid power. We then choose the battery capacity that maximizes the internal rate of return (IRR) on the PV microgrid. The CPV target price is the price that gives a CPV IRR that matches the PV IRR. The analysis is performed for 3 battery prices and 3 load profiles, in 3 cities in southwestern USA with different irradiance profiles, different time-of-use commercial electricity prices together with different demand charges levied on peak hour consumption each month. Land prices from $0/m2 to $400/m2 are analysed, representing the range from the urban fringe to commercial office parks. The target CPV prices obtained are found to depend on the land price and on the ratio of CPV to PV annual energy yield (REY), but are insensitive to battery prices, load profiles, current electricity tariffs and future trends in electricity tariffs. Modesto, CA has a REY of 1.10 and an average target CPV price from $1.86/W at zero land price to $3.53/W at $400/m2. Lancaster, CA with a REY of 1.26 has corresponding target CPV prices from $2.14/W to $4.23/W. In Las Vegas, NV, (REY = 1.27) the target CPV price is $2.13/W at a land price of zero, but at higher land prices the IRR is insufficient for solar power to be deployed. These target CPV prices correspond with current estimates of pedestal-tracked CPV of $2.4/W to $3.3/W and indicate that it is realistic to expect micro-tracked CPV to be cost competitive with PV in some urban areas in southwestern USA.

Highlights

  • TRENDS IN CPV AND MICROGRID ECONOMICS Industry Trends Concentrator Photovoltaics (CPV) has been profitable in utility-scale deployments in high Direct Normal Irradiance (DNI) regions, its cost in US$/W has not declined as fast as expected in Haysom et al (2015) and deployment volumes have been very low since 2015, (Ekins-Daukes and Johnson, 2017; Gil et al, 2017)

  • We have given the major relevant references relating to CPV costs and micro-tracking; we focus on the literature on microgrid economics

  • In section Introduction: Trends in CPV and Microgrid Economics, we emphasized the importance of peak demand charges to medium sized business customers and how batteries can contribute to reducing peaks in consumption from the grid when the load profile extends to times at which solar power is not generating well

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Summary

Industry Trends

Concentrator Photovoltaics (CPV) has been profitable in utility-scale deployments in high Direct Normal Irradiance (DNI) regions, its cost in US$/W has not declined as fast as expected in Haysom et al (2015) and deployment volumes have been very low since 2015, (Ekins-Daukes and Johnson, 2017; Gil et al, 2017). We focus on urban deployment where the value of land or roof area is significant, in order to investigate situations in which CPV has a higher internal rate of return (IRR) than PV. This leads us to focus our research on behind-the-meter (BTM) applications on customer premises instead of utility-scale deployments. In the present paper we analyse CPV with microtrackers integrated into the modules, moving the cell in relation to fixed optics (Price et al, 2017) and resulting in a shape and size for CPV modules similar to that of PV modules. Microgrid economics has an established literature which we review in order to identify the contribution of the present paper

Microgrid Economics Literature Review
Objectives and Contributions of the Current Paper
ENERGY AND ECONOMIC MODELING
Energy Yield Models
Microgrid Economics Optimization Model
Lt aI eiQt
Monthly maximum
IRR Optimization
Internal rate of return
Sequence of Calculations
Scenarios and Corresponding Data Sources
Las Vegas
Impact of Land Prices
CONCLUSIONS
Findings
AUTHOR CONTRIBUTIONS
Full Text
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