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At least 343 records · Page 19

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↗

A model for the cost of doing a cost estimate

A model for estimating the cost required to do a cost estimate for Deep Space Network (DSN) projects that range from $0.1 to $100 million is presented. The cost of the cost estimate in thousands of dollars, C(sub E), is found to be approximately given by C(sub E) = K((C(sub p))(sup 0.35)) where C(sub p) is the cost of the project being estimated in millions of dollars and K is a constant depending on the accuracy of the estimate. For an order-of-magnitude estimate, K = 24; for a budget estimate, K = 60; and for a definitive estimate, K = 115. That is, for a specific project, the cost of doing a budget estimate is about 2.5 times as much as that for an order-of-magnitude estimate, and a definitive estimate costs about twice as much as a budget estimate. Use of this model should help provide the level of resources required for doing cost estimates and, as a result, provide insights towards more accurate estimates with less potential for cost overruns.

Remer, D. S.↗

Civil Service Workforce Market Supply and the Effect on Cost Estimating Relationship (CERS) that May Effect the Productivity Factors for Future NASA Missions

The upcoming retirement of the Baby Boomers will leave a workforce age gap between the younger generation (the future NASA decision makers) and the gray beards. This paper will reflect on the average age of the workforce across NASA Centers, the Aerospace Industry and other Government Agencies, like DoD. This paper will dig into Productivity and Realization Factors and how they get applied to bi-monthly (payroll) data for true full-time equivalent (FTE) calculations that could be used at each of the NASA Centers and other business systems that are on the forefront in being implemented. This paper offers some comparative costs analysis/solutions, from simple FTE cost-estimating relationships (CERs) versus CERs for monthly time-phasing activities for small research projects that start and get completed within a government fiscal year. This paper will present the results of a parametric study investigating the cost-effectiveness of alternative performance-based CERs and how they get applied into the Center's forward pricing rate proposals (FPRP). True CERs based on the relationship of a younger aged workforce will have some effects on labor rates used in both commercial cost models and other internal home-grown cost models which may impact the productivity factors for future NASA missions.

Sterk, Steve↗

Renewable Energy Resources Portfolio Optimization in the Presence of Demand Response

In this paper we introduce a simple cost model of renewable integration and demand response that can be used to determine the optimal mix of generation and demand response resources. The model includes production cost, demand elasticity, uncertainty costs, capacity expansion costs, retirement and mothballing costs, and wind variability impacts to determine the hourly cost and revenue of electricity delivery. The model is tested on the 2024 planning case for British Columbia and we find that cost is minimized with about 31% renewable generation. We also find that demand responsive does not have a significant impact on cost at the hourly level. The results suggest that the optimal level of renewable resource is not sensitive to a carbon tax or demand elasticity, but it is highly sensitive to the renewable resource installation cost.

Behboodi, Sahand↗

Herbaceous Feedstock 2019 State of Technology Report

The U.S. Department of Energy (DOE) promotes the production of advanced liquid transportation fuels from lignocellulosic biomass by funding fundamental and applied research that advances the State of Technology (SOT). As part of its involvement with this mission, Idaho National Laboratory (INL) completes an annual SOT report for biomass feedstock logistics. This report summarizes supply system impacts of Bioenergy Technologies Office (BETO)-funded research and development efforts at INL and elsewhere (such as the High-Tonnage Feedstock Logistics projects (Webb et al. 2013a, Webb et al. 2013b, Webb et al. 2013c, Webb and Sokhansanj 2014, Sokhansanj et al. 2014)) that lead to improvements in feedstock supply systems. These include improvements to and observed performance of innovative harvest and collection methods, storage technologies, transportation and handling approaches, and advanced preprocessing technologies. Biomass quality and variability, and the interface between feedstock quality and conversion performance are key drivers in addition to delivered feedstock cost. In this report, we estimate the benefits of R&D improvements to individual supply system unit operations and present the status of feedstock logistics technology development for converting biomass into biofuels. These analyses are supported by experimental data where possible and help to align the SOT relative to the cost goals defined in the Multi-Year Program Plan. The 2019 Herbaceous SOT incorporates several technology changes in feedstock preprocessing and introduces opportunities from the integrated landscape management (ILM) strategy and increased grower participation to reduce biomass access costs, while maintaining or improving grower profitability. During FY18 uneven flow from the horizontal bale grinder was identified as a significant issue limiting preprocessing system throughput. Based on FSL-funded research at INL, the 2019 Herbaceous SOT replaces the horizontal bale grinder used in the first stage size reduction with a bale processor. The improved uniformity of biomass flow entering the PDU eliminated slugging flow from the first stage size reduction and improved the throughput of downstream operations. In order to achieve moisture reduction through frictional heating during grinding (which allowed elimination of the costly rotary drum dryer in previous SOTs), the second stage grinder was changed from a rotary shear, which does not remove moisture, back to a hammer mill. Finally, the 2019 Herbaceous SOT introduces modified three-pass and two-pass corn stover supply curves derived from the BT16 resource assessment, based on FY19 modeling results (WBS 4.2.1.20) quantifying economic benefits of ILM in the supply area, together with modeling results (WBS 1.2.1.5) identifying ILM strategies to increase grower participation. The 2019 Herbaceous SOT report documents the current modeled cost of an herbaceous feedstock supply system from harvest to the pretreatment reactor throat for hydrocarbon fuel production via biochemical conversion, based on equipment and processes now available or potentially available in the near term. The modeled cost also considers both the required quality and the availability of the biomass resources. The 2019 Herbaceous SOT predicts a modeled delivered feedstock cost of $81.37 /dry ton (2016$); this is a $2.30/dry ton (2016$) decrease from the 2018 Herbaceous SOT. Technology improvements that contributed to this modeled cost reduction include reduced cost for the new preprocessing design and quantification of the opportunities of the integrated landscape management (ILM) strategy and an increased grower participation rate to reduce the grower payment portion of biomass access costs, while maintaining or improving grower profitability. A greenhouse gas emissions (GHG) assessment was completed by Argonne National Laboratory using the 2019 Greenhouse Gases, Regulated Emissions, and Energy use in Transportation model, estimating an increase of 14.89 kg CO2e/ton from the 2018 SOT (69.27 kg CO2e/ton in 2018 to 84.16 kg CO2e/ton in 2019). The increase of energy consumption during preprocessing along with higher transportation distance to access low cost biomass from further distance contributed to the increase of GHG emissions in the 2019 Herbaceous SOT. The reason for the increased transportation distances was the cost tradeoff of going farther from the biorefinery to access the cheaper ILM-derived counties (the cheaper price outweighed the cost of increased supply radius).

09 BIOMASS FUELS↗

An additively-manufactured molten salt-to-supercritical carbon di-oxide primary heat exchanger for solar thermal power generation – Design and techno-economic performance

The design and techno-economic performance of a compact additively manufactured (AM) molten salt (MS)-to-supercritical carbon di-oxide (sCO2) primary heat exchanger (PHE) for solar thermal application is described. The PHE design consists of sCO2 flow through an array of microscale pin fins while the MS flows through mm-scale rectangular channels. Constraints imposed by AM using laser powder bed fusion method are considered in the design. Structural and fluid flow simulations are performed to arrive at a viable design of the core and headers. A simplified one-dimensional steady state model for the PHE is developed including the impact of surface roughness from the AM process. A process-based cost model is used to determine the tradeoff between thermofluidic design and manufacturing cost. A parametric study is performed using the thermo-fluidic and cost models to determine the set of geometrical and flow variables that result in high power density and low cost, while restricting the pressure drop on the sCO2 side to less than 2% of line pressure. Flow rates of MS and sCO2 were varied over heat capacity rate ratios ranging from 0.2 to 1. Results indicate that it is possible to design a low-pressure drop AM PHE with an effectiveness of 90% and a power density in excess of 10 MW/m3 (including headers). Fabrication of representative nickel superalloy specimens are shown to demonstrate that low-porosity parts with the requisite dimensional tolerance of PHE core can be generated.

14 SOLAR ENERGY↗

High Cost/High Risk Components to Chalcogenide Molded Lens Model: Molding Preforms and Mold Technology

FiveFocal outlined the major components to a cost model for isothermal compression molding of chalcogenide lenses in view of alternative methods of fabrication, such as single point diamond turning (SPDT) or conventional grinding and polishing. There is certainly a threshold for lens production volume that self-selects molding over SPDT or grinding/polishing, and it is the aim of the FiveFocal model to determine this inflection point. Of the many components of the cost model, two main items are those concerning lens preforms and molding tooling technology. These two areas are the focus of the remainder of this document.

Chalcogenide Lens Molding↗

Evaluating the Impacts of Coordination for Cascaded Hydropower Plants on the Mid-Columbia

The Mid-Columbia region in the U.S. Pacific Northwest includes seven large, cascaded hydropower plants with a combined nameplate capacity of nearly 14 GW. These plants have several different operators, and there is currently limited coordination among the operators. We develop a detailed model of the Mid-Columbia system that captures both river flow constraints and power system operations. We then place this detailed model within a production cost model of a 2030 system of the Western Interconnection to evaluate how coordination of the Mid-Columbia hydropower plants might impact operations throughout the interconnection. We find that coordination of the Mid-Columbia plants leads to more generation from the Mid-Columbia plants and increased revenues for the Mid-Columbia operators. This benefit is achieved primarily through better utilization of the storage reservoirs and decreased spill through the cascade. We also evaluate the impacts of look-ahead on production costs and find that longer look-ahead values result in lower system-wide production costs.

13 HYDRO ENERGY↗

A Comprehensive Comparison of Methods for Evaluating Dispatch of Long-Duration Energy Storage in Power Systems Models

Long-duration energy storage (LDES) could play a pivotal role in the transformation of electricity grids with high shares of variable renewable energy (VRE) such as solar and wind. However, the weather-dependent nature of VRE introduces challenges for grid balancing and stability, which LDES - along with short-duration energy storage (SDES) - can help address. However, modeling LDES in production cost models (PCMs) is particularly challenging due to the need for high temporal resolution over extended optimization windows while preserving chronology, which ensures the alignment of energy storage operations with VRE generation over multi-day periods. This report compares traditional dispatch methods with advanced LDES dispatch strategies, such as the extended horizon approach, across different PCM platforms and examines tradeoffs and scalability. The comparison reveals that the traditional 1-day optimization horizon within the PCM leads to inefficient utilization of LDES. In contrast, extending the optimization horizon as much as possible significantly reduces curtailment and improves storage dispatch, especially in renewable-dense systems. There is also promise in using state-of-charge or end volume targets set by an external model, however this requires an additional modeling set and generally increases computational burden. This paper presents a comparison of these various methods in a number of power systems, showing algorithms initially in small test systems and scaling up to large, country-wide simulations. Overall, the research presents the trade-offs of various computational methods and illustrates how LDES may play an essential role in power systems of the future.

14 SOLAR ENERGY↗

Research note: LED lighting – A global enterprise

There is considerable focus on technology manufacturing locations and the value in funding innovation when upstream products are not manufactured within a domestic economy. Light-emitting diodes (LEDs) are such an upstream product. Here, we evaluate the value added along the supply chain of luminaires, a product that utilizes LEDs, using bottom-up cost modelling. Coupling the results with analysis of shipping cost and time, this analysis examines how advances in LEDs can incentivize LED luminaire adoption leading to the potential for significant domestic manufacturing effects even if the upstream products are produced in other economies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Ultralight Door Design, Development and Demonstration Project (Final Scientific Report)

The project objectives associated with the Ultralight Door Project were to develop a lightweight driver's side door, 42.5% lighter than a current model year high-volume baseline door, at an incremental cost not to exceed $ \$ $ 5 per pound saved, while maintaining equivalent functionality, safety, corrosion, durability and sound transmission performance of the baseline vehicle. The project approach included the selection of a door architecture, development of a key performance target matrix and incremental cost model. Several unique door structures were developed and evaluated using computer-aided engineering (CAE) and cost modeling tools. The aluminum-intensive door structure was the only design capable of meeting both the performance and cost criteria objectives. The door module, glass, interior trim, latch and electrical subsystems were functionally integrated with the aluminum door structure, enabling additional mass reduction beyond material substitution. The lightweight door design was prototyped, integrated with baseline vehicles and tested to validate equivalent functionality and performance. The project results demonstrate a mass reduction of 15.2 kg (40%) at an incremental cost of $ \$ $2.81 per pound saved, while maintaining functionality and performance of the baseline door. The environmental benefit associated with the Ultralight Door enables a 6g CO 2 eq. per kilometer environmental benefit, for a 4-door vehicle powered by a downsized fuel injected gasoline combustion engine. The project results were presented and published in the 2018 SAE International Conference proceedings and in the Journal of Life Cycle Assessment.

36 MATERIALS SCIENCE↗

Analysis of Benefits of an Energy Imbalance Market in the NWPP

The Northwest Power Pool (NWPP) Market Assessment Committee (MC) Initiative, which was officially launched on March 19, 2012, set out to explore a range of alternatives that could help the Balancing Authorities and scheduling utilities in the NWPP area address growing operational and commercial challenges affecting the regional power system. The MC formed an Analytical Team with technical representatives from each of the member Balancing Areas in the NWPP and with staff of Pacific Northwest National Laboratory (PNNL). This Analytical Team was instructed to conduct extensive studies of intra-hour operation of the NWPP system in the year 2020 and of the NWPP region with 14,671 MW of wind penetration. The effort utilized a sub-hourly production cost model (the PLEXOS® computer model) that inputs data from the Western Electricity Coordinating Council (WECC)-wide Production Cost Model (PCM) to evaluate potential production cost savings. The Analytical Team was given two general options to evaluate: •Energy Imbalance Market (EIM): establishment of an automated, organized NWPP area market for economically supplying energy imbalance within the hour. •Enhanced Market-Operational Tools (EMT) that might augment or replace an EIM. The Analytical The Analytical Team built on the WECC-wide PCM data from prior work done in the WECC and carried forward the evolution of the original WECC Transmission Expansion Planning Policy Committee (TEPPC) 2020 PC0 data base. A large number of modifications and improvements were made to this case and the data were subjected to extensive review by the team members to improve the model representation of the Northwest (NW). MC meetings that were open to the public were held for interested parties to review and provide input to the study. Results for the test, base, and sensitivity case studies performed by the MC Initiative Analytical Team indicate that there are a wide range of benefits that could be obtained from the operation of an EIM in the NWPP depending on what assumptions are made. The instructions from the MC were to determine a "minimum high confidence" range of potential benefits. The results for the Base Case indicate that the EIM benefits ranged from approximately $40 million to $70 million in annual savings from the operation of an EIM in the NWPP footprint. A number of additional relevant sensitivity cases were performed, including low and high water conditions, low and high natural gas prices, and various flex reserve requirements, resource operations, and amounts of resource capability held back during the preschedule period. Along with the results for the Base Case, the results for these studies yielded EIM benefits that clustered within the range of $70 to $80 million dollars per year with potential benefits ranging from approximately $125 million to as little as $17 million per year. Because the design and operation of an EIM could enable participating Balancing Authorities (BAs) to collectively lower the quantity of resources they must carry to meet within-hour balancing needs, a sensitivity case was also performed to analyze the impact that such reductions might have on the benefits from an EIM. The results for this sensitivity case indicate that such reductions could increase the benefits from the operation of an EIM in the NWPP into the range of approximately $130 million to $160 million per year. Also, a sensitivity case for a WECC-wide EIM was performed with the results indicating that the potential benefits to the NWPP could increase into the range of $197 million to $233 million per year. While there may be potential reliability benefits from the coordinated dispatch process underlying the operation of an EIM, reliability benefits from an EIM were out of the scope of this study. The EIM benefit analyses that were performed by the Analytical Team are provided in this report.

Power markets, NWPP, Energy Imbalance, EIM, Renewa↗

Modelling Concentrating Solar Power with Thermal Energy Storage for Integration Studies (Presentation)

Concentrating solar power with thermal energy storage (CSP-TES) can provide multiple benefits to the grid, including low marginal cost energy and the ability to levelize load, provide operating reserves, and provide firm capacity. It is challenging to properly value the integration of CSP because of the complicated nature of this technology. Unlike completely dispatchable fossil sources, CSP is a limited energy resource, depending on the hourly and daily supply of solar energy. To optimize the use of this limited energy, CSP-TES must be implemented in a production cost model with multiple decision variables for the operation of the CSP-TES plant. We develop and implement a CSP-TES plant in a production cost model that accurately characterizes the three main components of the plant: solar field, storage tank, and power block. We show the effect of various modelling simplifications on the value of CSP, including: scheduled versus optimized dispatch from the storage tank and energy-only operation versus co-optimization with ancillary services.

14 SOLAR ENERGY↗

Modelling Concentrating Solar Power with Thermal Energy Storage for Integration Studies: Preprint

Concentrating solar power with thermal energy storage (CSP-TES) can provide multiple benefits to the grid, including low marginal cost energy and the ability to levelize load, provide operating reserves, and provide firm capacity. It is challenging to properly value the integration of CSP because of the complicated nature of this technology. Unlike completely dispatchable fossil sources, CSP is a limited energy resource, depending on the hourly and daily supply of solar energy. To optimize the use of this limited energy, CSP-TES must be implemented in a production cost model with multiple decision variables for the operation of the CSP-TES plant. We develop and implement a CSP-TES plant in a production cost model that accurately characterizes the three main components of the plant: solar field, storage tank, and power block. We show the effect of various modelling simplifications on the value of CSP, including: scheduled versus optimized dispatch from the storage tank and energy-only operation versus co-optimization with ancillary services.

14 SOLAR ENERGY↗

A generalized approximate control variate framework for multifidelity uncertainty quantification

We describe and analyze a variance reduction approach for Monte Carlo (MC) sampling that accelerates the estimation of statistics of computationally expensive simulation models using an ensemble of models with lower cost. These lower cost models — which are typically lower fidelity with unknown statistics — are used to reduce the variance in statistical estimators relative to a MC estimator with equivalent cost. We derive the conditions under which our proposed approximate control variate framework recovers existing multifidelity variance reduction schemes as special cases. We demonstrate that existing recursive/nested strategies are suboptimal because they use the additional low-fidelity models only to efficiently estimate the unknown mean of the first low-fidelity model. As a result, they cannot achieve variance reduction beyond that of a control variate estimator that uses a single low-fidelity model with known mean. However, there often exists about an order-of-magnitude gap between the maximum achievable variance reduction using all low-fidelity models and that achieved by a single low-fidelity model with known mean. We show that our proposed approach can exploit this gap to achieve greater variance reduction by using non-recursive sampling schemes. The proposed strategy reduces the total cost of accurately estimating statistics, especially in cases where only low-fidelity simulation models are accessible for additional evaluations. Several analytic examples and an example with a hyperbolic PDE describing elastic wave propagation in heterogeneous media are used to illustrate the main features of the methodology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗