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DOE OSTI2021

U.S. Solar Photovoltaic System and Energy Storage Cost Benchmark (Q1 2020)

This report benchmarks U.S. solar photovoltaic (PV) system installed costs as of the first quarter of 2020 (Q1 2020). We use a bottom-up method, accounting for all system and project-development costs incurred during the installation to model the costs for residential (with and without storage), commercial (with and without storage), and utility-scale systems (with and without storage). We also incorporate other system characteristics and performance factors, as well as ongoing costs, to benchmark LCOE for PV-standalone systems, and LCOSS for solar+storage.

14 SOLAR ENERGY↗

DOE OSTI2021

U.S. Solar Photovoltaic System and Energy Storage Cost Benchmark: Q1 2020 [PowerPoint]

NREL has been modeling U.S. photovoltaic (PV) system costs since 2009. This report benchmarks costs of U.S. solar PV for residential, commercial, and utility-scale systems, with and without storage, built in the first quarter of 2020 (Q1 2020). Our methodology includes bottom-up accounting for all system and project-development costs incurred when installing residential, commercial, and utility-scale systems, and it models the capital costs for such systems.

14 SOLAR ENERGY↗

DOE OSTI2020

The Effect of Photovoltaic Module Efficiency on Installed System Costs and Markets in Residential Rooftop Installations in the United States

In this report, we analyze how efficiencies influence residential PV system installed system costs and break-even module prices using a bottom-up cost model. We show that the cost savings associated with efficiency are much higher for area-constrained rooftop than those which are usage-constrained. We also show that simplified models of how efficiency impacts costs overestimate the value of efficiency compared to bottom-up models, particularly for usage-constrained scenarios. We also estimate the fraction of area-constrained residential rooftops in the United States today and explore how that fraction could change in future scenarios with high levels of electrification.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2019

The International Supply Chain and Manufacturing Costs for Photovoltaic Modules, and Project Economics of Systems Including Storage

This talk will highlight the most recent efforts from the National Renewable Energy Laboratory's (NREL) Strategic Energy Analysis Center (SEAC) to track solar PV manufacturing capacities and trade flows, bottom-up manufacturing costs, and project capital costs including storage. We will begin with an overview of the global PV supply chain and the 2019 benchmark input data used to inform NREL's crystalline silicon (c-Si) and thin film module manufacturing cost models. The accounting framework that we follow and that will be reviewed during this talk provides a methodology to prepare cost models in accordance with the Generally Accepted Accounting Principles (GAAP) and the International Financial Reporting Standards (IFRS). For the polysilicon, wafer, cell conversion, and module assembly steps of the c-Si supply chain, and for thin film modules, we will review input data and methods useful for calculating the costs of goods sold (COGS); research and development (R&D) expenses; and sales, general, and business administration (S, G, &A) expenses. This 2019 benchmark analysis is compiled for state-of-the-art polysilicon-to-module manufacturing across the globe. We will also provide an overview of opportunities for solar plus storage and show our 2018 benchmark bottom-up capital cost model results for utility-scale PV systems with battery storage.

14 SOLAR ENERGY↗

DOE OSTI2019

The Role of Reliability and Durability in Photovoltaic System Economics

This presentation was delivered as a webinar to members of the Durable Modules Materials Consortium (led by NREL) on February 11, 2019. We are now preparing it for posting to the DuraMAT website. The presentation offered an overview of how NREL's technoeconomic analysis helps to guide DuraMAT's work. Specifically, the presentation offers several examples of how analysis helps answer the question 'what is the value of solving a particular problem?'

14 SOLAR ENERGY↗

DOE OSTI2019

Cost Modelling for Energy Efficient Window Replacements

This paper detailed data collection and cost-modeling efforts to understand the hardware and non-hardware (soft) cost of residential, energy efficient window replacements. NREL created a bottom-up cost model that details costs associated with window materials, installation labor, company overhead, and administrative costs. NREL did not find a single cost area for improvement but observed several non-cost barriers to increased window replacements. The non-cost barriers associated with window replacements are consumer education, lack of communication of the value of window replacement to consumers, and difficulty for consumers to identify quality products and installation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2019

U.S. Solar Photovoltaic System Cost Benchmark Q1 2018

NREL has been modeling U.S. photovoltaic PV system costs since 2009. The U.S. Solar Photovoltaic System CostBenchmark Q1 2018 report benchmarks costs of U.S. solar PV for residential commercial and utility-scale systems built in the first quarter of 2018 Q1 2018. THE methodology includes bottom-up accounting for all system and project-development costs incurred when installing residential commercial and utility-scale systems and it models the capital costs for such systems.

14 SOLAR ENERGY↗

DOE OSTI2018

Evaluating the Cost Benefits of U.S. Utility-Scale Photovoltaics Plus Energy Storage Systems

Utility-scale photovoltaics (PV) system market growth has been rapid for several years. Today, with the cost reductions of energy storage technologies, the application of combing PV and energy storage has become feasible and beneficial, especially for the areas that only have PV standalone systems and need to shift the peak load to meet the evening electricity demand. Overall, the utility-scale PV plus energy storage systems can provide dispatchable energy and reliable capacity. This study details cost factors, including labor costs, material costs, overhead, and permitting costs using a systemlevel bottom-up cost modeling approach. We use this model to benchmark PV plus storage installation system cost and identify cost difference for AC and DC coupled systems and duration variation. Finally, we assess the cost reduction opportunities of co-locating PV system with energy storage system in order to indicate the possible economic impacts of PV plus storage configuration and help future research and development (R&D) effects in the context of U.S. energy storage policymaking.

14 SOLAR ENERGY↗

DOE OSTI2018

U.S. Solar Photovoltaic System Cost Benchmark: Q1 2018

NREL has been modeling U.S. photovoltaic (PV) system costs since 2009. This report benchmarks costs of U.S. solar PV for residential, commercial, and utility-scale systems built in the first quarter of 2018 (Q1 2018). Our methodology includes bottom-up accounting for all system and project-development costs incurred when installing residential, commercial, and utility-scale systems, and it models the capital costs for such systems.

14 SOLAR ENERGY↗

DOE OSTI2018

2018 U.S. Utility-Scale Photovoltaics-Plus-Energy Storage System Costs Benchmark

Market growth for utility-scale photovoltaic (PV) systems has been rapid for several years. Today, with the cost reductions of energy storage technologies, the combining PV and energy storage has become feasible and beneficial, especially for the areas that have only PV standalone systems and need to shift the peak load to meet electricity demand in the evening. Overall, utility-scale PV plus energy storage systems can provide dispatchable energy and reliable capacity. This study details cost factors, including labor costs, material costs, overhead, and permitting costs using a system-level bottom-up cost modeling approach. We use this model to benchmark PV-plus-storage installation system cost and identify the cost difference for AC- and DC-coupled systems and duration variation. Finally, we assess the cost reduction opportunities of colocating PV systems with energy storage systems in order to indicate the possible economic impacts of the PV-plus-storage configuration and help future research and development (R&D) effects in the context of U.S. energy storage policymaking.

14 SOLAR ENERGY↗

DOE OSTI2018

2018 U.S. Utility-Scale Photovoltaics-Plus-Energy Storage System Costs Benchmark

Market growth for utility-scale photovoltaic (PV) systems has been rapid for several years. Today, with the cost reductions of energy storage technologies, the combining PV and energy storage has become feasible and beneficial, especially for the areas that have only PV standalone systems and need to shift the peak load to meet electricity demand in the evening. Overall, utility-scale PV plus energy storage systems can provide dispatchable energy and reliable capacity. This study details cost factors, including labor costs, material costs, overhead, and permitting costs using a system-level bottom-up cost modeling approach. We use this model to benchmark PV-plus-storage installation system cost and identify the cost difference for AC- and DC-coupled systems and duration variation. Finally, we assess the cost reduction opportunities of colocating PV systems with energy storage systems in order to indicate the possible economic impacts of the PV-plus-storage configuration and help future research and development (R&D) effects in the context of U.S. energy storage policymaking.

14 SOLAR ENERGY↗

DOE OSTI2018

U.S. Solar Photovoltaic System Cost Benchmark: Q1 2018

NREL has been modeling U.S. photovoltaic (PV) system costs since 2009. This report benchmarks costs of U.S. solar PV for residential, commercial, and utility-scale systems built in the first quarter of 2018 (Q1 2018). Our methodology includes bottom-up accounting for all system and project-development costs incurred when installing residential, commercial, and utility-scale systems, and it models the capital costs for such systems.

14 SOLAR ENERGY↗

DOE OSTI2018

Estimating the Effects of Module Area on Thin-Film Photovoltaic System Costs

We investigate the potential effects of module area on the cost and performance of photovoltaic systems. Applying a bottom-up methodology, we analyzed the costs associated with thin-film modules and systems as a function of module area. We calculate a potential for savings of up to 0.10/Wand0.13/W in module manufacturing costs for CdTe and CIGS respectively, with large area modules. We also find that an additional 0.04/W savings in balance-of-systems costs may be achieved. Sensitivity of the /W cost savings to module efficiency, manufacturing yield, and other parameters is presented. Lifetime energy yield must also be maintained to realize reductions in the levelized cost of energy; the effects of module size on energy yield for monolithic thin-film modules are not yet well understood. Finally, we discuss possible non-cost barriers to adoption of large area modules.

14 SOLAR ENERGY↗

DOE OSTI2018

A New Model to Determine Installed System Cost and LCOE for ARPA-E's MOSAIC Micro-Concentrator PV Program: Preprint

The US Department of Energy's Advanced Research Projects Agency-Energy (ARPA-E) started a three-year program in December 2015 called Microscale Optimized Solar-cell Arrays with Integrated Concentration (MOSAIC). It consists of 11 teams from across the United States. Its goal is to have project teams leverage expertise from conventional flat-plate photovoltaic (PV) system configuration and concentrated photovoltaic (CPV) module technology to produce a new class of modules for residential, commercial, and utility-scale markets. The intent is to increase performance and facilitate cost-effective deployment of solar power systems across a wide range of geographical locations in part by concentrating both direct and diffuse components of the sun's irradiance. This paper describes a collaboration of ARPA-E and the National Renewable Energy Laboratory (NREL) to develop a bottom-up system cost model for MOSAIC research teams. The model includes an estimate of regional, all-in, CPV installed cost, and levelized cost of energy (LCOE) by using customized inputs parameters, such as module efficiency, cost, and physical dimensions. This techno-economic cost model can help researchers analyze tradeoffs among different design parameters and then prioritize their distinct research opportunities. Moreover, it establishes a standardized cost benchmarking for MOSAIC micro-CPV systems and a normalized comparison against traditional CPV and today's highly competitive flat-plate PV systems. The model is a valuable design tool within the program, helping validate the various technical approaches and compare future deployed system competitiveness versus incumbent technologies in the PV industry.

14 SOLAR ENERGY↗