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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

14 SOLAR ENERGY↗

DOE OSTI2019

The Vineyard Wind Power Purchase Agreement: Insights for Estimating Costs of U.S. Offshore Wind Projects

This report analyzes the power purchase agreements (PPAs) between Massachusetts electric distribution utilities (EDC) and Vineyard Wind LLC filed on July 31, 2018, and derives insights for estimating cost of U.S. offshore wind systems and broader cost modeling activities. The documented price for delivery of offshore wind generation and renewable energy certificates under the Vineyard Wind/electric distribution utilities PPA is 74 $/megawatt-hour (MWh) (2022$) for facility 1 (400 MW) and 65 $/MWh (2023$) for facility 2 (400 MW). However, this PPA price does not comprise the complete set of expected revenue sources and tax benefits available to the Vineyard Wind LLC project. A comprehensive accounting of expected revenue sources inclusive of those that are exogenous to the reported PPA is conducted in this study to estimate the project's levelized revenue of energy (LROE). This allows for a more equivalent comparison of the PPA pricing with bottom-up modeled (unsubsidized) levelized cost of energy (LCOE) estimates. LROE from the Vineyard LLC/EDC PPA is estimated to be 98$/MWh (2018$). This LROE estimate for the first commercial-scale offshore wind project in the United States appears to be within the range of LROE estimated for offshore wind projects recently tendered in Northern Europe with a start of commercial operation by the early 2020s. This suggests that a cost and risk premium for the initial set of U.S. offshore wind projects may be less pronounced than anticipated by many industry observers and analysts.

17 WIND ENERGY↗

DOE OSTI2018

Prices in Frequency Regulation Markets: Impacts of Natural Gas Prices and Variable Renewable Energy

Increasing wind and solar penetration and low natural gas prices have reduced electricity prices in competitive power markets in recent years, while also increasing the relative importance of ancillary services in balancing short-term net load variability. As a result, ancillary service markets are providing a valuable alternative revenue stream for many market participants. Yet the price dynamics in these markets are still not very well understood. In this work, we incorporate unit-level ancillary service offer prices and quantities into a production cost model and examine how prices for frequency regulation are impacted by relatively extreme perturbations of several system parameters. Initial offers are first estimated on the basis of limited available public data and are then iteratively calibrated against historic market outcomes. Through a case study of the PJM Interconnection, we find that doubling the natural gas price increases the average annual regulation price by 36%, while replacing all coal generation with natural gas decreases the average price by 42%. Increasing the wind penetration from 2% to 30% in isolation increases the average regulation price by 32%, while further doubling the regulation requirement results in an 84% increase. These price increases can be mitigated by introducing additional battery storage capacity or by increasing offer quantities from hydro and thermal units. Finally, we discuss a number of modeling challenges that are faced when incorporating ancillary services into traditional production cost models. These include poor data availability, inconsistent product definitions across markets, and complex market rules.

02 PETROLEUM↗

DOE OSTI2026

Challenges and Opportunities for Electric Utility Modeling and Asset Valuation Frameworks: Case Study on Valuing New Pumped Storage Hydropower

Asset valuation by electric utilities is becoming increasingly difficult in the rapidly changing electric sector. Rapid deployment of variable generation and inverter-based storage systems along with uncertain demand growth, climate, policies, and other factors create a challenging environment for understanding the value proposition of a new potential asset. This report describes an effort between the Tennessee Valley Authority (TVA) and three U.S. Department of Energy laboratories to perform a detailed review of utility modeling and analysis practices for asset valuation and identify challenges and opportunities for advancing its methods into the future. It focuses on a case study of new potential pumped storage hydropower (PSH) because of growing interest in new PSH capacity to provide energy balancing, firm capacity, and a range of ancillary services. Staff from the DOE labs conducted systematic interviews about current practices in capacity expansion modeling, production-cost modeling, hydrological modeling, and transmission stability modeling while also discussing how scenario analysis is conducted and how models and data are integrated. The effort resulted in a set of model, integration, and scenario recommendations that could be valuable to TVA, other utilities, system operators, and other stakeholders conducting integrated grid analysis. Individual model recommendations suggest exploring computational tradeoffs with detail and resolution across spatiotemporal structure, supply- and demand-side details, transmission overlays, market interactions, and ancillary services. Automated processes to pass data between models and conduct larger scenario suites could also enhance valuation practices by enabling a more consistent study of asset value across a broader range of uncertain future grid conditions where PSH could be particularly valuable. TVA and other industry stakeholders can learn from and adapt applied research-grade methods developed by DOE laboratories and other research institutions to improve decision making and accelerate progress towards a reliable, economic, sustainable energy system.

13 HYDRO ENERGY↗

NASA NTRS1983

Satellite provided customer premises services: A forecast of potential domestic demand through the year 2000. Volume 1: Executive summary

Development of a forecast of the total domestic telecommunications demand, identification of that portion of the telecommunications demand suitable for transmission by satellite systems, identification of that portion of the satellite market addressable by CPS systems, identification of that portion of the satellite market addressable by Ka-band CPS system, and postulation of a Ka-band CPS network on a nationwide and local level were achieved. The approach employed included the use of a variety of forecasting models, a parametric cost model, a market distribution model and a network optimization model. Forecasts were developed for: 1980, 1990, 2000; voice, data and video services; terrestrial and satellite delivery modes; and C, Ku and Ka-bands.

Kratochvil, D.↗

NASA NTRS1984

Satellite provided customer promises services, a forecast of potential domestic demand through the year 2000. Volume 4: Sensitivity analysis

The overall purpose was to forecast the potential United States domestic telecommunications demand for satellite provided customer promises voice, data and video services through the year 2000, so that this information on service demand would be available to aid in NASA program planning. To accomplish this overall purpose the following objectives were achieved: (1) development of a forecast of the total domestic telecommunications demand; (2) identification of that portion of the telecommunications demand suitable for transmission by satellite systems; (3) identification of that portion of the satellite market addressable by consumer promises service (CPS) systems; (4) identification of that portion of the satellite market addressable by Ka-band CPS system; and (5) postulation of a Ka-band CPS network on a nationwide and local level. The approach employed included the use of a variety of forecasting models, a parametric cost model, a market distribution model and a network optimization model. Forecasts were developed for: 1980, 1990, and 2000; voice, data and video services; terrestrial and satellite delivery modes; and C, Ku and Ka-bands.

Kratochvil, D.↗

NASA NTRS1986

Cost Risk Analysis Based on Perception of the Engineering Process

In most cost estimating applications at the NASA Langley Research Center (LaRC), it is desirable to present predicted cost as a range of possible costs rather than a single predicted cost. A cost risk analysis generates a range of cost for a project and assigns a probability level to each cost value in the range. Constructing a cost risk curve requires a good estimate of the expected cost of a project. It must also include a good estimate of expected variance of the cost. Many cost risk analyses are based upon an expert's knowledge of the cost of similar projects in the past. In a common scenario, a manager or engineer, asked to estimate the cost of a project in his area of expertise, will gather historical cost data from a similar completed project. The cost of the completed project is adjusted using the perceived technical and economic differences between the two projects. This allows errors from at least three sources. The historical cost data may be in error by some unknown amount. The managers' evaluation of the new project and its similarity to the old project may be in error. The factors used to adjust the cost of the old project may not correctly reflect the differences. Some risk analyses are based on untested hypotheses about the form of the statistical distribution that underlies the distribution of possible cost. The usual problem is not just to come up with an estimate of the cost of a project, but to predict the range of values into which the cost may fall and with what level of confidence the prediction is made. Risk analysis techniques that assume the shape of the underlying cost distribution and derive the risk curve from a single estimate plus and minus some amount usually fail to take into account the actual magnitude of the uncertainty in cost due to technical factors in the project itself. This paper addresses a cost risk method that is based on parametric estimates of the technical factors involved in the project being costed. The engineering process parameters are elicited from the engineer/expert on the project and are based on that expert's technical knowledge. These are converted by a parametric cost model into a cost estimate. The method discussed makes no assumptions about the distribution underlying the distribution of possible costs, and is not tied to the analysis of previous projects, except through the expert calibrations performed by the parametric cost analyst.

Dean, Edwin B.↗

NASA NTRS2005

Advanced Technology Lifecycle Analysis System (ATLAS) Technology Tool Box (TTB)

The Advanced Technology Lifecycle Analysis System (ATLAS) is a decision support tool designed to aid program managers and strategic planners in determining how to invest technology research and development dollars. It is an Excel-based modeling package that allows a user to build complex space architectures and evaluate the impact of various technology choices. ATLAS contains system models, cost and operations models, a campaign timeline and a centralized technology database. Technology data for all system models is drawn from a common database, the ATLAS Technology Tool Box (TTB). The TTB provides a comprehensive, architecture-independent technology database that is keyed to current and future timeframes.

Doyle, Monica↗

DOE OSTI2014

Cost and Performance Model for Redox Flow Batteries

A cost model was developed for all vanadium and iron-vanadium redox flow batteries. Electrochemical performance modeling was done to estimate stack performance at various power densities as a function of state of charge. This was supplemented with a shunt current model and a pumping loss model to estimate actual system efficiency. The operating parameters such as power density, flow rates and design parameters such as electrode aspect ratio, electrolyte flow channel dimensions were adjusted to maximize efficiency and minimize capital costs. Detailed cost estimates were obtained from various vendors to calculate cost estimates for present, realistic and optimistic scenarios. The main drivers for cost reduction for various chemistries were identified as a function of the energy to power ratio of the storage system. Levelized cost analysis further guided suitability of various chemistries for different applications.

efficiency↗

DOE OSTI2016

Impact of Market Behavior, Fleet Composition, and Ancillary Services on Revenue Sufficiency

Revenue insufficiency, or the missing money problem, occurs when the revenues that generators earn from the market are not sufficient to cover both fixed and variable costs to remain in the market and/or justify investments in new capacity, which may be needed for reliability. The near-zero marginal cost of variable renewable generators further exacerbates these revenue challenges. Estimating the extent of the missing money problem in current electricity markets is an important, nontrivial task that requires representing both how the power system operates and how market participants behave. This paper explores the missing money problem using a production cost model that represented a simplified version of the Electric Reliability Council of Texas (ERCOT) energy-only market for the years 2012-2014. We evaluate how various market structures -- including market behavior, ancillary services, and changing fleet compositions -- affect net revenues in this ERCOT-like system. In most production cost modeling exercises, resources are assumed to offer their marginal capabilities at marginal costs. Although this assumption is reasonable for feasibility studies and long-term planning, it does not adequately consider the market behaviors that impact revenue sufficiency. In this work, we simulate a limited set of market participant strategic bidding behaviors by means of different sets of markups; these markups are applied to the true production costs of all gas generators, which are the most prominent generators in ERCOT. Results show that markups can help generators increase their net revenues overall, although net revenues may increase or decrease depending on the technology and the year under study. Results also confirm that conventional, variable-cost-based production cost simulations do not capture prices accurately, and this particular feature calls for proxies for strategic behaviors (e.g., markups) and more accurate representations of how electricity markets work. The analysis also shows that generators face revenue sufficiency challenges in this ERCOT-like energy-only market model; net revenues provided by the market in all base markup cases and sensitivity scenarios (except when a large fraction of the existing coal fleet is retired) are not sufficient to justify investments in new capacity for thermal and nuclear power units. Overall, the work described in this paper points to the need for improved behavioral models of electricity markets to more accurately study current and potential market design issues that could arise in systems with high penetrations of renewable generation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Assessment of the driving factors of CO 2 mitigation costs of household biogas systems in China: A LMDI decomposition with cost analysis model

China has been placing a substantial focus on biogas for reducing energy consumption and carbon dioxide (CO 2 ) emissions. The operation mode of biogas systems may make the CO 2 reduction target over-optimistic. There is limited research to investigate the influential factors that may be causing the gap between the actual and theoretical CO 2 reduction costs of biogas systems in China. In this research, by using field survey data of 209 biogas users and 489 non-biogas users from 19 villages in 2015, the gap between actual and theoretical unit CO 2 reduction cost is quantified at approximately 156 USD/t CO 2 . By employing the Logarithmic Mean Divisia Index I (LMDI) model, it is found that both the cost effect (48%) and the reduction effect (52%) contribute to the unit CO 2 reduction cost gap. Furthermore, four influential factors–household labor, accessibility to the energy resource, acceptance of biogas technology, and subsidy–significantly narrow the gap between actual and theoretical CO 2 reduction costs, while the levelized subsidy contributes to widening the gap. On average, biogas systems should be operated for at least four years and the substitution rate should be more than 67% in order to keep the gap between actual and theoretical CO 2 reduction costs under 50%.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2022

COMPACT KNN V2: Analogy-Based Cost Estimation Model for CubeSats

The CubeSat Or Microsat Probabilistic and AnalogiesCost Tool, or COMPACT, is a NASA Headquarters fundedeffort to fill the gap in cost estimating capabilities for CubeSats,as well as other microsat spacecraft. The COMPACT team hasfocused mainly on CubeSats to date, and has collected technical,programmatic and cost data on dozens of flown CubeSatsmissions led by NASA, research labs, and universities. In late2019, the team released the first tool prototype which uses a nonparametricregression technique, k-Nearest Neighbors (KNN),on actual data from historical CubeSat missions to produceearly ballpark analogy-based cost estimates for new CubeSatconcepts. Since the KNN prototype was first released, theCOMPACT team has normalized 17 new missions to be addedto the model in COMPACT V2. COMPACT V2 also featureschanges to the KNN tool algorithm including the introduction ofPrincipal Component Analysis (PCA) to the model developmentprocess and changes to the input parameters which have madethe analogy results more intuitive and have improved modelperformance. This paper describes the current COMPACTKNN dataset, improvements made to the model in COMPACTV2, an assessment of current model performance, and a forwardlook at COMPACT’s planned future enhancements.

Hooke, Melissa↗

DOE OSTI2016

Analysis of Fuel Cell Markets in Japan and the US: Experience Curve Development and Cost Reduction Disaggregation

Fuel cells are both a longstanding and emerging technology for stationary and transportation applications, and their future use will likely be critical for the deep decarbonization of global energy systems. As we look into future applications, a key challenge for policy-makers and technology market forecasters who seek to track and/or accelerate their market adoption is the ability to forecast market costs of the fuel cells as technology innovations are incorporated into market products. Specifically, there is a need to estimate technology learning rates, which are rates of cost reduction versus production volume. Unfortunately, no literature exists for forecasting future learning rates for fuel cells. In this paper, we look retrospectively to estimate learning rates for two fuel cell deployment programs: (1) the micro-combined heat and power (CHP) program in Japan, and (2) the Self-Generation Incentive Program (SGIP) in California. These two examples have a relatively broad set of historical market data and thus provide an informative and international comparison of distinct fuel cell technologies and government deployment programs. We develop a generalized procedure for disaggregating experience-curve cost-reductions in order to disaggregate the Japanese fuel cell micro-CHP market into its constituent components, and we derive and present a range of learning rates that may explain observed market trends. Finally, we explore the differences in the technology development ecosystem and market conditions that may have contributed to the observed differences in cost reduction and draw policy observations for the market adoption of future fuel cell technologies. The scientific and policy contributions of this paper are the first comparative experience curve analysis of past fuel cell technologies in two distinct markets, and the first quantitative comparison of a detailed cost model of fuel cell systems with actual market data. The resulting approach is applicable to analyzing other fuel cell markets and other energy-related technologies, and highlights the data needed for cost modeling and quantitative assessment of key cost reduction components.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2016

Experimental Determination of Demand Response Control Models and Cost of Control for Ensembles of Window-Mount Air Conditioners

Control of consumer electrical devices for providing electrical grid services is expanding in both the scope and the diversity of loads that are engaged in control, but there are few experimentally-based models of these devices suitable for control designs and for assessing the cost of control. A laboratory-scale test system is developed to experimentally evaluate the use of a simple window-mount air conditioner for electrical grid regulation services. The experimental test bed is a single, isolated air conditioner embedded in a test system that both emulates the thermodynamics of an air conditioned room and also isolates the air conditioner from the real-world external environmental and human variables that perturb the careful measurements required to capture a model that fully characterizes both the control response functions and the cost of control. The control response functions and cost of control are measured using harmonic perturbation of the temperature set point and a test protocol that further isolates the air conditioner from low frequency environmental variability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Western Interconnection Baseline Study

The purpose of the baseline study is to evaluate the degree to which current industry planning processes meet the national 2035 decarbonization goals for the Western Interconnection. This analysis serves as a comparative baseline for the scenario analysis conducted in the NTP Study using a Western Interconnection dataset that is readily available to industry. This baseline analysis differs from the production cost modeling analysis and power flow analysis in the main NTP Study report (forthcoming). In particular, the analysis presented in this report reflects a business-as-usual future with an optimistic build out of specific planned transmission projects and foreseeable generation. In contrast, the NTP Study models a future generation and transmission expansion based on optimization from a capacity expansion model. The analysis presented herein also reflects a 2030 timeframe, whereas the main NTP Study production cost modeling analysis and power flow analysis reflect a 2035 time frame. This baseline analysis utilizes industry’s most reliable data to account for future transmission projects across various stages of development, with a particular focus on those in the permitting stage. Additionally, it incorporates projections for changes in generation capacity (both additions and retirements). This baseline analysis outlines a probable trajectory, given current process and practice, for the future of the bulk power system with a horizon extending to 2030.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Enhanced Catalyst Durability and Sulfur Tolerance by Atomic Layer Deposition (CRADA Final Report)

This CRADA advanced the use of atomic layer deposition (ALD) catalyst coatings to improve sulfur tolerance and demonstrate improved catalyst durability for biomass conversion chemistries. This project leveraged National Laboratory and industry expertise for ALD catalyst coating development between NREL, ALD NanoSolutions, Inc. ("ALD NanoSolutions"), and Johnson Matthey PLC ("Johnson Matthey"). To better understand the role of ALD coatings on catalyst activity and durability, a joint experimental and computational effort combined bench-scale ALD catalyst synthesis, material characterization, catalyst testing, and modeling of catalyst surface energetics. In addition, to demonstrate the commercial relevance of this technology, scaled ALD coated catalysts were subjected to continuous testing and accelerated aging to validate performance gains. Results were used to inform ALD catalyst coating manufacturing cost models, as well as biobased chemical process cost models.

09 BIOMASS FUELS↗

NASA NTRS1992

Cost-estimating relationships for space programs

Cost-estimating relationships (CERs) are defined and discussed as they relate to the estimation of theoretical costs for space programs. The paper primarily addresses CERs based on analogous relationships between physical and performance parameters to estimate future costs. Analytical estimation principles are reviewed examining the sources of errors in cost models, and the use of CERs is shown to be affected by organizational culture. Two paradigms for cost estimation are set forth: (1) the Rand paradigm for single-culture single-system methods; and (2) the Price paradigms that incorporate a set of cultural variables. For space programs that are potentially subject to even small cultural changes, the Price paradigms are argued to be more effective. The derivation and use of accurate CERs is important for developing effective cost models to analyze the potential of a given space program.

Mandell, Humboldt C., Jr.↗