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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Breakeven Prices for Photovoltaics on Supermarkets in the United States

The photovoltaic (PV) breakeven price is the PV system price at which the cost of PV-generated electricity equals the cost of electricity purchased from the grid. This point is also called 'grid parity' and can be expressed as dollars per watt ($\$$W) of installed PV system capacity. Achieving the PV breakeven price depends on many factors, including the solar resource, local electricity prices, customer load profile, PV incentives, and financing. In the United States, where these factors vary substantially across regions, breakeven prices vary substantially across regions as well. In this study, we estimate current and future breakeven prices for PV systems installed on supermarkets in the United States. We also evaluate key drivers of current and future commercial PV breakeven prices by region. The results suggest that breakeven prices for PV systems installed on supermarkets vary significantly across the United States. Non-technical factors -- including electricity rates, rate structures, incentives, and the availability of system financing -- drive break-even prices more than technical factors like solar resource or system orientation. In 2020 (where we assume higher electricity prices and lower PV incentives), under base-case assumptions, we estimate that about 17% of supermarkets will be in utility territories where breakeven conditions exist at a PV system price of $\$$3/W; this increases to 79% at $\$$1.25/W (the DOE SunShot Initiative's commercial PV price target for 2020). These percentages increase to 26% and 91%, respectively, when rate structures favorable to PV are used.

14 SOLAR ENERGY↗
DOE OSTI2026

Rewarding Grid-Friendly Behavior: Estimating the Potential Bill Reduction and Load Shifting Benefits of Dynamic Prices

Shifting electric load from times of peak demand can be a key strategy to slow price growth as reducing peak demand avoids the cost of upgrading generation, transmission and distribution infrastructure. Utilities are releasing time-varying prices, such as time of use rates or dynamic prices, to incentivize grid-friendly load shifting. New dynamic price programs provide insight into the true cost of operating electricity grids and the potential economic benefits of load shifting. Program developers and device manufacturers need to understand the economic opportunities in terms of 1) the variation in prices across hours, days, and seasons; 2) the change in utility bills for customers who don’t shift load; and 3) the potential load shifted and economic value of different technologies if manufacturers or aggregators deploy price-responsive controls. This paper estimates possible impacts of dynamic price adoption and load shifting controls if customers paid the dynamic rate from one pilot program. Statistical analysis of historical prices identified annual and seasonal metrics as well as representative price curves for each circuit in the pilot. Simulations for residential technologies with price-responsive controls including unitary heat pump water heaters, central multifamily heat pump water heaters, heating & cooling + storage systems, and pool pumps estimated the potential impacts of highly dynamic prices both with and without load shifting controls. Results showed the potential to reduce electricity costs on representative days by 42-94% and reduce consumption during times of high electricity prices by 63-100% compared to baseline operation for those flex-friendly devices.

Grant, Peter↗
DOE OSTI2018

The value of price transparency in residential solar photovoltaic markets

Installed prices for residential solar photovoltaic (PV) systems have declined significantly in recent years. However price dispersion and limited customer access to PV quotes prevents some prospective customers from obtaining low price offers. This study shows that improved customer access to prices - also known as price transparency - is a potential policy lever for further PV price reductions. We use customer search and strategic pricing theory to show that PV installation companies face incentives to offer lower prices in markets with more price transparency. We test this theoretical framework using a unique residential PV quote dataset. Our results show that installers offer lower prices to customers that are expected to receive more quotes. Our study provides a rationale for policies to improve price transparency in residential PV markets.

14 SOLAR ENERGY↗
DOE OSTI2023

Stochastic Price Generation for Evaluating Wholesale Electricity Market Bidding Strategies

This work presents a novel method for generating electricity price scenarios from statistical properties of past electricity prices using a hybrid statistical and reduced-form stochastic model. Previous work in applying stochastic differential equations (SDE) to model electricity prices has focused on daily average prices. To extend stochastic price generation methods to hourly or sub-hourly pricing, we address several weaknesses in the state-of-the-art: (1) we replace the mean-reversion component of the SDE with an ARIMA process that is better able to characterize the daily and weekly trends; (2) we extend the price-spike, or jump process to account for conditional probabilities of price spikes occurring in consecutive time steps by replacing the traditional Poisson process for modeling jumps with a generalized point process model inspired by brain neuron models; and (3) we replace the traditional method of estimating spike intensity with empirical variance with a Markov process based on observed price spike intensity transitions. The method is demonstrated with electricity prices from the US ERCOT market and a use-case example is provided for bidding an energy storage unit into the day-ahead and real-time energy markets of ERCOT using stochastic optimization methods. Results show that the the synthetic price model out performs a (naive) persistence forecast model by resulting in 24% to 47% more in profits over 168 simulated days.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

The relative influences of hydrologic information and dams’ hydropower scheduling decisions on electricity price forecasts

Price dynamics in wholesale electricity markets are driven by supply and demand. In markets with hydroelectric dams, the timing and amount of hydropower offered can influence prices in similar ways to wind and solar power. Unlike variable renewable energy, however, the supply of hydropower in wholesale markets is a function of both water availability and operational decisions at dams. Dam operators maximize revenues in wholesale markets by aligning generation with the periods of highest expected prices, and these scheduling decisions may in turn influence prices. Here, we examine the relative importance of two types of information in predicting forward electricity prices: a) water availability at dams, in the form of short-to-medium-range hydrological forecasts; and b) hourly scheduling decisions at dams. Using softly coupled hydrologic, hydropower scheduling, and power systems models spanning the U.S. Western Interconnection, we quantify the importance of hydrologic forecast accuracy in correctly predicting wholesale electricity prices and compare this with the influence of dam operators’ own hourly scheduling decisions on realized market prices. We find that aligning hydropower generation schedules with the periods of high forecasted prices causes larger, inadvertent price forecast errors than imperfect hydrologic forecasts. This suggests that knowledge of how water is managed by dam operators within the week is more important than weekly inflow forecast errors when predicting forward electricity prices. Our findings have implications for optimal hydropower scheduling by region. Specifically, accounting for price effects is critical in markets dominated by hydropower capacity.

Electricity markets↗
DOE OSTI2014

Financial derivative pricing under probability operator via Esscher transfomation

The problem of pricing contingent claims has been extensively studied for non-Gaussian models, and in particular, Black- Scholes formula has been derived for the NIG asset pricing model. This approach was first developed in insurance pricing{sup 9} where the original distortion function was defined in terms of the normal distribution. This approach was later studied6 where they compared the standard Black-Scholes contingent pricing and distortion based contingent pricing. So, in this paper, we aim at using distortion operators by Cauchy distribution under a simple transformation to price contingent claim. We also show that we can recuperate the Black-Sholes formula using the distribution. Similarly, in a financial market in which the asset price represented by a stochastic differential equation with respect to Brownian Motion, the price mechanism based on characteristic Esscher measure can generate approximate arbitrage free financial derivative prices. The price representation derived involves probability Esscher measure and Esscher Martingale measure and under a new complex valued measure φ (u) evaluated at the characteristic exponents φ{sub x}(u) of X{sub t} we recuperate the Black-Scholes formula for financial derivative prices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Price response of waste resources under demand shocks: four case studies

To quantify potential price changes of waste feedstocks that may be caused by increased demand, this study explored four case studies: 1) recyclable materials at local waste collection and recycling facilities in seven US states, 2) recyclable materials on internationally traded markets, 3) a wood-powered plant in Reading, PA, and 4) an MSW-powered plant in Tulsa, OK. The four case studies provided a total of ninety-one waste material price observations yielding twenty-seven price-supply relationships expressed as price elasticity of supply (PES) and unit price change with change in demand. For the two case studies related to recyclable materials with a global market shock, price changes vary widely from $0.08-$7.84 per ton with each percent change in demand. For the two case studies related to local market shocks in biomass used for energy, observed price changes range from $0.08-$0.23 per ton per percent change in demand. Based on these results, a base range of $0.10-$0.20 per ton per percent change in demand is recommended for local market shocks. I.e., for a facility that collects organic wastes on the order of 200,000-400,000 tons per year at price near zero, a doubling of demand could increase procurement prices by about $10.00-$20.00 per ton. Actual price changes with respect to change in demand may be non-linear. Shocks with broader geographic extent may increase price response due to a reduced opportunity for surrounding markets to mitigate localized market changes.

09 BIOMASS FUELS↗
NASA NTRS2011

New Local, National and Regional Cereal Price Indices for Improved Identification of Food Insecurity

Large price increases over a short time period can be indicative of a deteriorating food security situation. Food price indices developed by the United Nations Food and Agriculture Organization (FAO) are used to monitor food price trends at a global level, but largely reflect supply and demand conditions in export markets. However, reporting by the United States Agency for International Development (USAID)'s Famine Early Warning Systems Network (FEWS NET) indicates that staple cereal prices in many markets of the developing world, especially in surplus-producing areas, often have a delayed and variable response to international export market price trends. Here we present new price indices compiled for improved food security monitoring and assessment, and specifically for monitoring conditions of food access across diverse food insecure regions. We found that cereal price indices constructed using market prices within a food insecure region showed significant differences from the international cereals price, and had a variable price dispersion across markets within each marketshed. Using satellite-derived remote sensing information that estimates local production and the FAO Cereals Index as predictors, we were able to forecast movements of the local or national price indices in the remote, arid and semi-arid countries of the 38 countries examined. This work supports the need for improved decision-making about targeted aid and humanitarian relief, by providing earlier early warning of food security crises.

Brown, Molly E.↗
DOE OSTI2020

How Do Electricity Pricing Programs Impact the Selection of Energy Efficiency Measures? - A Case Study with U.S. Medium Office Buildings

Building owners usually select energy efficiency measures (EEMs) by referring to return on investment (ROI). Current studies tend to apply static energy price to estimate ROI. However, more and more buildings are adopting dynamic electricity pricing programs. To understand how electricity pricing programs impact the selection of EEMs, this paper presents an analysis of the ROIs of EEMs under different pricing programs using U.S. medium office buildings as an example. Eight EEMs in four typical cities are selected as case studies. Considering five electricity pricing programs scenarios (one static program and four dynamic programs), EEMs are selected based on their ROIs. The main findings are: (1) The ROIs of EEMs change under different pricing programs. (2) In Honolulu, Buffalo, and Denver, replacing interior fixtures with higher-efficiency fixtures has a significantly higher ROI than the rest EEMs under all five pricing programs. However, the ROI of this EEM in Honolulu ranges from 28% to 47% for different pricing programs. (3) Similarly, in Fairbanks, replace heating coil with higher-efficiency coil produce higher ROI than the rest under all five pricing programs. (4) For other EEMs, their ROI rankings vary according to electricity pricing programs.

demand response↗
DOE OSTI2018

Rules of the rooftop: Platform design and price reductions in an online solar photovoltaic marketplace in the United States

Residential solar photovoltaic (PV) customers typically obtain price quotes directly from installers, a process with high consumer search costs that enable price dispersion and can discourage adoption. Recently, however, customers are increasingly shopping for PV using third-party online platforms that make it easier to obtain and compare quotes from multiple installers. While early evidence indicates that these platforms make the PV market more transparent and lower prices, the literature suggests that market outcomes are critically linked to detailed aspects of platform design. In this study, we econometrically analyze a unique dataset of quotes offered in the online PV marketplace EnergySage to investigate how four changes to the platform design have influenced quote prices and transaction prices. We find that the largest reductions in quote prices ($0.11/ W) and transaction prices ($0.15/W) were associated with the introduction of a price guidance information feature for installers. While educating and informing customers has repeatedly emerged as a policy priority for bolstering PV markets, these results suggest that the same should be true on the supply side. We also find that customers are willing to pay higher transaction prices for systems with higher-quality panels, dispelling concerns that online PV marketplaces lead to a 'race to the bottom' phenomenon by emphasizing price at the expense of quality.

14 SOLAR ENERGY↗
DOE OSTI2014

Analyzing reliability of virtual machine instances with dynamic pricing in the public cloud

This study presents reliability analysis of virtual machine instances in public cloud environments in the face of dynamic pricing. Different from traditional fixed pricing, dynamic pricing allows price to dynamically fluctuate over arbitrary period of time according to external factors such as supply and demand, excess capacity, etc. This pricing option introduces a new type of fault: virtual machine instances may be unexpectedly terminated due to conflicts in the original bid price and the current offered price. This new class of fault under dynamic pricing may be more dominant than traditional faults in cloud computing environments, where resource availability associated with traditional faults is often above 99.9%. To address and understand this new type of fault, we translated two classic reliability metrics, mean time between failures and availability, to the Amazon Web Services spot market using historical price data. We also validated our findings by submitting actual bids in the spot market. We found that overall, our historical analysis and experimental validation lined up well. Based upon these experimental results, we also provided suggestions and techniques to maximize overall reliability of virtual machine instances under dynamic pricing.

Cloud computing↗
DOE OSTI2023

Water and Wastewater Annual Price Escalation Rates for Selected Cities Across the United States: 2023 Edition

This report builds on the 2016 Water and Wastewater Annual Price Escalation Rates for Selected Cities across the United States report prepared by Pacific Northwest National Laboratory (PNNL) for the U.S. Department of Energy’s (DOE) Federal Energy Management Program (FEMP). The 2017 report examined annual water and wastewater price escalation rate trends across the U.S. Annual water and wastewater price escalation rates are an important factor when conducting life-cycle cost analyses (LCCA) of water efficiency measures, which is required for Federal agencies. Following the framework of the 2017 report, PNNL used the American Water Works Association (AWWA) water and wastewater rate surveys to gather historical rate data for water and wastewater utilities in the US, which were used to calculate a sample set of water and wastewater annual price escalation rates (Figure E.1). An annual price escalation rate was calculated for 113 water utilities and 76 wastewater utilities that reported at least two AWWA surveys across the past 13 years (i.e., 2008 to 2021) and at least a five-year range between those two surveys. Statistical trends in the annual price escalation rates are also provided by the seven regions identified in Figure E.1. In the 2017 report, the average annual price escalation for the surveyed sample of water and wastewater rates were 3.0% and 3.2%, respectively. This report also calculated aggregate average annual price escalation rates for the surveyed sample of water and wastewater utilities to be 3.1% and 2.7%, respectively. These escalation rates were based on 87 water utilities and 46 wastewater utilities that reported data in at least two AWWA surveys with at least a five-year range between those two surveys and reported at least one AWWA survey in 2019 or 2021. Among water utilities, the highest average annual price escalation rate was 8.8%, and the highest average annual water de-escalation rate was -2.0%. And for wastewater utilities, the highest average annual wastewater price escalation rate was 10.2%, and the highest average annual wastewater de-escalation rate was -2.3%.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Dataset for: Price Controls for Scarcity Events in Real-Time and Transactive Energy Systems

Real time pricing (RTP) is often promoted as a mechanism to improve the economic efficiency of the electricity system. However, many regulators have been hesitant to adopt RTP due to concerns about exposing customers to extreme price swings. To balance these concerns, this paper proposes a methodology for establishing price controls, based on the supply of demand-side flexibility in the system. As an illustrative example, we measure price responsiveness using an agent-based simulation model that is representative of the ERCOT market. The model is composed of a distribution feeder that has 250 customers with active agents controlling their HVAC systems in response to the historical ERCOT RTP with an artificially added high-price event. These agents are subjected to increasing electricity prices during the event, which we then use to create a supply curve for demand-side resources in our modeled scarcity event. We set potential price caps at points on the supply curve where customers’ have exhausted their flexible capacity. Using historical prices, we examine the systemic costs of these price caps, and present regulatory options for recouping them. Utilities and regulators interested in limiting consumer risk from dynamic pricing can utilize these methods to develop rate structures and encourage conservation. The attached data upload allows for the duplication or modification of the analysis performed in this study.

Kerby, Jessica R↗
DOE OSTI2020

North American energy system responses to natural gas price shocks

As of 2020, North American natural gas extraction and use in the electricity sector have both reached all-time highs. The combination of North America's increased reliance on natural gas with a potential disruption to the natural gas market has several energy security implications. Additionally, policymakers interested in economic resiliency will find this study's results useful for informing the implications of the energy sectors' long-term planning and investment decisions. This paper evaluates how both the electricity and natural gas sectors could respond to hypothetical gas price shocks under different system configurations. We impose unforeseen natural gas price shocks under reference and alternative configurations resulting from a renewable generation mandate or variations to renewable capacity costs. Results from several different models are presented for the electricity and natural gas sectors separately for Canada, Mexico, and the United States. Generally, the US becomes more (less) reliant on electricity imports from Canada given a high (low) gas price shock but increases (decreases) exports to Mexico. The renewable mandate is shown to buffer electricity price increases under high price shocks but price reductions under the low price shocks are dampened given less flexibility to take advantage of the low-priced natural gas. The United States is demonstrated to reduce natural gas production and net exports with high natural gas price shocks given a reduction in demand.

03 NATURAL GAS↗
DOE OSTI2018

Solar Buyer's Markets: Unlocking Lower Photovoltaic and Battery Prices on Online Quote Platforms

In an online quote platform, a solar PV customer provides information about their home and desired system characteristics to a quote 'aggregator,' who conveys this information to a network of installers. Interested installers submit bids to the online quote platform, where the customer can then compare bids in a common format. In this report, we analyze the effects of quote platform use on PV prices using data from the Pick My Solar platform. The results of the our study corroborate results from a previous study based on a different quote platform, indicating that quote platforms are associated with reduced PV prices. By opting to use quote platforms rather than directly soliciting quotes from installers, PV customers might save roughly 20 cents/W - 40 cents/W, which is equivalent to 1,000-2,000 dollars in savings for a typical 5-kW residential PV system. For the first time, we also explore battery prices on quote platforms, and find evidence that quote platforms are associated with reduced battery prices. Despite the savings potential, only about 3 percent of residential PV sales currently occur through online platforms - though many more customers use platforms without adopting PV, and some customers may use platforms to learn about PV prices before accepting a quote received directly from an installer. Continued growth of platform use could yield PV price reductions for at least two reasons. First, it could push the average PV price point toward lower platform prices. Second, it could produce spillover effects by forcing reductions in quotes obtained outside of platforms. For instance, national-scale installers - which have not historically bid on quote platforms - may begin to offer lower prices if greater numbers of prospective customers begin to use the platforms.

14 SOLAR ENERGY↗
DOE OSTI2025

Factors influencing recent trends in retail electricity prices in the United States

This study analyzes the primary drivers of recent state-level trends in U.S. retail electricity prices. We summarize pricing trends, explore descriptive relationships, and employ regression models to quantify the influence of various factors. Although the recent national rise in retail prices has largely tracked inflation, state-level trends vary widely. We identify a number of factors that explain trends in subsets of states. States with the greatest price increases typically exhibited shrinking customer loads—partially linked to growth in net metered behind-the-meter solar—and had renewables portfolio standards (RPS) in concert with relatively costly incremental renewable energy supplies. By contrast, recent utility-scale wind and solar deployment that occurred outside RPS programs (but that benefited from tax incentives) had no discernible impact on increased retail prices. Hurricanes, storms and wildfires also contributed to sizable price increases in some states, most notably in California, where wildfire risk mitigation and liability insurance were major cost drivers. Fluctuations in natural gas prices—particularly following the onset of the Ukraine-Russia war—further contributed to sharp price increases through 2022–2023 in many states, with moderation in 2024. The relative influence of these factors varies across states and over time, and relationships may change in the future. Nonetheless, the findings underscore the diverse set of price determinants and highlight the need for continued research to inform effective policy and ensure customer affordability.

Customer load↗
DOE OSTI2017

Meta-Analysis of the Oil Price Elasticity of the GDP for Policy Analysis: Documentation

Given the important role of oil in economic activities, policy makers are interested in estimates of the potential damage to the economy from oil price shocks, particularly during periods of rapid and large increases that accompany severe shocks. Such estimates are needed to quantify the economic costs of oil price shocks, and to evaluate the potential benefits of alternative policy responses. Although research on the economic impacts of oil price shocks is extensive and has generally found that large increases in oil prices exert negative economic impacts, the range of estimates, summarized by the oil price elasticity of the GDP or other aggregate measure of economic activity, is very wide. There are also conditions under which the relationship between the oil price and the economy could be positive. The range of estimates of the oil price elasticity of the GDP for the United States is typified by averages from the studies of Hamilton (2005, 2012) and Kilian and Vigfusson (2014), in which the implied elasticities were -0.014 to - 0.069 and +0.004 to -0.052, respectively. We employ a meta-regression approach to systematically summarize available estimates of the oil price elasticity of the GDP for oil importing economies, and examine the role of key factors. The resulting regression model was used to estimate the oil price elasticity of the GDP for the United States. Based on this we estimate the mean elasticity for the United States at -0.0238, with a 68% confidence interval of -0.0075 to -0.0402, four quarters after a shock.

02 PETROLEUM↗
DOE OSTI2018

Impacts of High Variable Renewable Energy Futures on Wholesale Electricity Prices, and on Electric-Sector Decision Making

Increasing penetrations of variable renewable energy (VRE) can affect wholesale electricity price patterns and make them meaningfully different from past, traditional price patterns. Many long-lasting decisions for supply- and demand-side electricity infrastructure and programs are based on historical observations or assume a business-as-usual future with low shares of VRE. Our motivating question is whether certain electric-sector decisions that are made based on assumptions reflecting low VRE levels will still achieve their intended objective in a high VRE future. We qualitatively describe how various decisions may change with higher shares of VRE and outline an analytical framework for quantitatively evaluating the impacts of VRE on long-lasting decisions. We then present results from detailed electricity market simulations with capacity expansion and unit commitment models for multiple regions of the U.S. for low and high VRE futures. We find a general decrease in average annual hourly wholesale energy prices with more VRE penetration, increased price volatility and frequency of very low-priced hours, and changing diurnal price patterns. Ancillary service prices rise substantially and peak net-load hours with high capacity value are shifted increasingly into the evening, particularly for high solar futures. While in this report we only highlight qualitatively the possible impact of these altered price patterns on other demand- and supply-side electric sector decisions, the core set of electricity market prices derived here provides a foundation for later planned quantitative evaluations of these decisions in low and high VRE futures.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗