Modeling investment decisions from heterogeneous firms under imperfect information and risk in wholesale electricity markets
Not Available
Anwar, Muhammad Bashar (ORCID:0000000291846700)↗
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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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Climate impacts on hydropower and consequences for global electricity supply investment needs
Recent progress in global scale hydrological and dam modeling has allowed for the study of climate change impacts on global hydropower production. Here we explore the possible consequences of these impacts for the electricity supply sector. Regional hydropower projections are developed for two emissions scenarios by forcing a coupled global hydrological and dam model with downscaled, bias-corrected climate realizations derived from sixteen general circulation models. Consequent impacts on power sector composition and associated emissions and investment costs are explored using the Global Change Assessment Model (GCAM). Changes in hydropower generation resulting from climate change can shift power demands onto and away from carbon intensive technologies, resulting in significant impacts on power sector CO2 emissions for certain world regions—primarily those located in Latin America, as well as Canada and parts of Europe. Reduced impacts of climate change on hydropower production under a low emissions scenario coincide with increased costs of marginal power generating capacity—meaning impacts on power sector investment costs are similar for high and low emissions scenarios. Individual countries where impacts on investment costs imply significant risks or opportunities are identified.
Turner, Sean W. D. (ORCID:0000000344009800)↗
Investment Optimization to Improve Power Distribution System Reliability Metrics.
Abstract not provided.
Pierre, Brian Joseph↗
Basic Research Needs in The Science of Scientific Software Development and Use: Investment in Software is Investment in Science
Increasingly powerful and affordable computing has revolutionized scientific and scholarly discovery across a broad range of fields. Computing relies on software, which has been rapidly growing in scope, diversity, and complexity. At the same time, the methods, processes, and tools used to produce and utilize this essential software are often ad hoc, and the study and improvement of them are often done without the benefit of direct funding or prioritization. Consequently, concerns are growing about the productivity of the developers and users of scientific software, its sustainability, and the trustworthiness of the results that it produces. Increased investment, especially in the characterization and improvement of how scientific software is developed and used, is important for sustaining and improving the impact of software as the scope and complexity of scientific efforts expand. Without this investment, we face the risk of diminishing returns on our software investments because the demands for increased functionality, usability, reliability, and more will not be sufficiently met. The US Department of Energy Office of Science (DOE/SC) is at the forefront of modern software-enabled scientific discovery across numerous areas of computational, experimental, and observational science, including major investments in national user facilities that support these activities. For many years, DOE/SC software investments have provided tremendous value to the scientific community. We want to continue and further improve the value of DOE/SC software efforts by using a scientific approach to understanding and improving how scientific software is developed and used. In December 2021, the DOE/SC Office of Advanced Scientific Computing Research (ASCR) convened a workshop on basic research needs for the Science of Scientific-Software Development and Use (SSSDU). Through keynote presentations, lightning talks, and breakout groups, which built on insights from 124 pre-workshop position papers, participants discussed the current practice of software development, maintenance, evolution, and use, and considered how the scientific method could be used to examine these practices and develop more evidence-based approaches to enhance the impact of software and computing on all areas of science. Workshop participants identified three priority research directions (PRDs) and three important crosscutting themes that center on the following overarching insight: Software has become an essential part of modern science, impacting discoveries, policy, and technological development. To maintain and improve confidence in science delivered via software, we must improve the processes and tools that help us create and use software, and this enhancement requires a deep understanding of the diverse array of teams and individuals doing the work.
97 MATHEMATICS AND COMPUTING↗
InVEST Urban Development: Incorporating Earth Observation Data into the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation Model Python API
Urban flooding poses as one of the biggest issues for cities today, as its impacts are amplified by both climate change and urbanization. The Natural Capital Project’s Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation (UFRM) model, which benefits from its simplicity and robustness, is commonly used in NASA DEVELOP projects for disaster mitigation, urban planning, and environmental justice issues. While InVEST UFRM model was able to produce the surface water runoff and retention map sufficient for the scopes of past projects, the model accuracy and spatial variability need improvement. Since the current InVEST UFRM model employs constant rainfall depth for all pixels in the area of interest (AOI), the model suffers from inaccurately estimating rainfall depth, runoff volume, and flood depth. Therefore, we adapted the model so that satellite-based precipitation raster datasets (i.e., Integrated Multi-satellitE Retrievals for Global Precipitation Measurement [GPM IMERG]) can be used instead of a single constant value. We simulated the flood events on August 21st and August 22nd, 2017 in Wyandotte County, Kansas using both our modified and the original InVEST UFRM model and then compared the results after incorporating the rainfall raster into the model. Areas with developed land on the land use map predicted moderate to high flood volume in the original volume regardless of the actual amount of precipitation. The modified model considered the rainfall depth’s spatial variation achieving less overestimation of flood runoff and volume at low-to-moderate rainfall area.
Son Do↗
InVEST Urban Development: Incorporating Earth Observation Data into the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation Model Python API
Urban flooding poses as one of the biggest issues for cities today as its impacts are amplified by both climate change and urbanization. The Natural Capital Project’s Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation (UFRM) model, which benefits from its simplicity and robustness, is commonly used in NASA DEVELOP projects for disaster mitigation, urban planning, and environmental justice issues. While the InVEST UFRM model was able to produce the surface water runoff and retention map sufficient for the scopes of past projects, the model’s accuracy and spatial variability need improvement. Since the current InVEST UFRM model employs constant rainfall depth for all pixels in the area of interest (AOI), the model suffers from inaccurately estimating rainfall depth, runoff volume, and flood depth. Therefore, we adapted the model so that satellite-based precipitation raster datasets (i.e., Integrated Multi-satellitE Retrievals for Global Precipitation Measurement [GPM IMERG]) can be used instead of a single constant value. We simulated the flood events on August 21st and August 22nd, 2017, in Wyandotte County, Kansas using both our modified and the original InVEST UFRM model and then compared the results after incorporating rainfall raster into the model. Areas with developed land on the land use map predicted moderate to high flood volume in the original volume regardless of the actual amount of precipitation. The modified model considered the rainfall depth’s spatial variation achieving less overestimation of flood runoff and volume at low-to-moderate rainfall area.
Urban flooding↗
Intersections of Disadvantaged Communities and Renewable Energy Potential: Data Set and Analysis to Inform Equitable Investment Prioritization in the United States
Renewable energy development can bolster local economies through job creation, local tax revenues, and reduced energy costs; however, communities most in need of economic development and employment opportunities often see lower levels of renewable energy deployment. We sought to identify areas where disadvantaged community indicators and high generation potential from cost-effective renewable energy opportunities intersect and deployment could lead to economic development and job creation. This presentation will highlight several of our findings. This research and the associated county-level data set are intended to inform national- and state-level energy-related assistance programs, economic development efforts, and infrastructure programs seeking to prioritize investments in disadvantaged communities.
community energy planning↗
EVAL: A methodological approach to identify NPP total capital investment cost drivers and sensitivities
Not Available
Maronati, Giovanni↗
Investment Optimization to Improve Power System Resilience.
Abstract not provided.
Pierre, Brian Joseph↗
InVEST Urban Development: Incorporating Earth Observation Data into the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation Model Python API
Explore the source record for details and available documents.
Son Do↗
Performance Metrics to Evaluate Utility Resilience Investments
In 2019, Sandia National Laboratories (Sandia) contracted Synapse Energy Economics (Synapse) to research the integration of community and electric grid resilience investment planning as part of the Designing Resilient Communities (DRC): A Consequence-Based Approach for Grid Investment project. Synapse produced a series of reports to explore the challenges and opportunities in several key areas, including benefit-cost analysis (BCA), performance metrics, microgrids, and regulatory mechanisms. This report focuses on BCA. BCA is an approach that electric utilities, electric utility regulators, and communities can use to evaluate the costs and benefits of a wide range of grid resilience investments in a comprehensive and consistent way. While BCA is regularly applied to some types of grid investments, application of BCA to grid resilience investments is in the early stages of development. Though resilience is increasingly cited in connection with grid investment proposals and plans, the resilience- related costs and benefits of grid resilience investments are typically not fully identified, infrequently quantified, and almost never monetized. Without complete assessments of costs and benefits, regulators can be hesitant to approve some types of grid resilience investments. This report provides the first application of the framework developed in the 2020 National Standard Practice Manual for Benefit-Cost Analysis of Distributed Energy Resources (NSPM for DERs) to grid resilience investments. We provide guidance on next steps for implementation to enable grid resilience investments to receive due consideration. We suggest developing BCA principles and standards for jurisdiction-specific BCA tests. We also recommend identifying the resilience impacts of the investments and quantification of these impacts by establishing utility performance metrics for resilience. Proactive integration of grid resilience investments into existing regulatory processes and practices can increase the capacity of jurisdictions to respond to and recover from the consequences of extreme events. 1 National Energy Screening Project. 2020. National Standard Practice Manual for Benefit-Cost Analysis of Distributed Energy Resources.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Applying Value at Risk Analysis towards Energy Efficiency Investments
Value at Risk (VaR) is a measure of risk for potential losses within a portfolio of investments. Investments in energy efficiency in a manufacturing environment compete in terms of payback period, ease of investment, and transaction costs with other investments (production, safety, engineering, etc.). Because manufacturers have limited amounts of capital to allocate, investments in productivity tend to be prioritized over energy efficiency projects that offer similar paybacks. Value at Risk (VaR) can be used to quantify how risk-weighted expenditures change over time. Energy efficiency investments are often believed to offer relatively stable payoffs compared to changes in production and other assets, particularly when evaluated using methodologies such as simple payback. Incorporating methodologies such as VaR can provide a stronger business case for energy efficiency investments by quantifying value beyond what is captured in other Return on Investment calculations.In this paper we outline a methodology for applying VaR in the context of the variety of investments made by manufacturing organizations. Additionally, we profile the stability of energy efficiency (EE) and renewable energy (RE) investments compared to other types of investments made in manufacturing. By applying VaR to these investments, energy managers can better translate the financial benefits of energy-related capital projects in a way that is more compelling to Corporate Finance and Treasury departments. This common language also allows Corporate Finance and Treasury departments to support large, strategic deployments of capital for such projects based on a targeted objective – the management of financial risk for the organization’s shareholders.
Levine, Eli↗
Regulatory Incentives and Disincentives for Utility Investments in Grid Modernization
Electric power is America's most capital-intensive industry, with more than $100 billion invested each year in energy infrastructure. Investment needs are likely to grow as electric utilities make power systems more reliable and resilient, deploy advanced digital technologies, and facilitate new services to meet some consumers' expectations for greater choice and control. But do current regulatory approaches provide the appropriate incentives for grid modernization investments? This report presents three perspectives: -Financial analyst Steve Kihm begins by explaining that any major investor-owned electric utility that wants to raise capital today can do so at a reasonable cost. The question is whether utility managers want to raise capital for grid modernization. Specifically, they look for investments that create the most value for their existing shareholders. In cases where grid modernization investments are not the best choice in terms of shareholder value, Kihm describes shareholder incentive mechanisms that regulators could consider to encourage such investments when they are in the public interest. -From an institutional perspective, Dr. Janice Beecher finds that the traditional rate-base/rate of return regulatory model provides powerful incentives for utilities to pursue investments, cost control, efficiency and even innovation, and it is well suited to the policy objectives of grid modernization. Prudence of grid modernization investments (fair returns) depends on careful evaluation of the specific asset, and any special incentives (bonus returns) should be used only if they promote economic efficiency consistent with the core goals of economic regulation. According to Beecher, realizing the promises of grid modernization depends on effective implementation of the traditional regulatory model and ratemaking tools to serve the public interest. -Conversely, former commissioner and clean energy consultant Ron Lehr says that rapid electric industry changes require a better alignment of utility investment incentives with changes challenging the electricity sector, emerging grid modernization options and benefits, and public policies. For example, investor-owned utilities typically have an incentive to make capital investments, but rarely to employ expense-based solutions, since utilities do not earn profits on expenses. Further, Lehr cites a variety of factors that stand in the way of creating well targeted and well aligned utility incentives, including litigated regulatory processes. These may be a poor choice for finding the right balance among competing interests, establishing rules of prospective application, justifying demonstrations of new technologies and approaches to meeting emerging consumer demands, and keeping pace with rapid change.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Design and impact assessment of watershed investments: An approach based on ecosystem services and boundary work
Watershed investments, whose main aim is to secure water for cities, represent a promising opportunity for large-scale sustainability transitions in the near future. If properly designed, they promote activities in the watershed that enhance ecosystem services while protecting nature and biodiversity, as well as achieving other societal goals. In this paper, we build on the concepts of ecosystem services and boundary work, to develop and test an operative approach for designing and assessing the impact of watershed investments. The approach is structured to facilitate negotiations among stakeholders. Its strategic component includes setting the agenda; defining investment scenarios; and assessing the performance of watershed investments as well as planning for a follow-up. Its technical component concerns data processing; tailoring spatially explicit ecosystem service models; hence their application to design a set of “investment portfolios”, generate future land use scenarios, and model impacts on selected ecosystem services. A case study illustrates how the technical component can be developed in a data scarce context in sub-Saharan Africa in a way that is functional to support the steps of the strategic component. The case study addresses soil erosion and water scarcity-related challenges affecting Asmara, a medium-sized city in Eritrea, and considers urban water security and rural poverty alleviation as two illustrative objectives, within a ten-year planning horizon. The case study results consist in spatially explicit data (investment portfolio, land use scenario, impact on ecosystem services), which were aggregated to quantitatively assess the performance of different watershed investments scenarios, in terms of changes in soil erosion control. By addressing stakeholders' concerns of credibility, saliency, and legitimacy, the approach is expected to facilitate negotiation of objectives, definition of scenarios, and assessment of alternative watershed investments, ultimately, to contribute to implementing an adaptive watershed management.
54 ENVIRONMENTAL SCIENCES↗
Optimal investment strategies for distributed generation in distribution networks with real option analysis
Efficient and well‐timed investment in distributed generation (DG) in distribution networks in the electricity market environment presents a big challenge for distribution companies. In this study, a real option valuation framework is proposed to determine the optimal investment strategies for DG including the investment location, size, and timing. Within the proposed framework, the profit from investing in DG is modelled, where the benefits include the operation cost savings and capacity update deferral benefit compared with a no‐DG‐investment scenario over the study period. Future power demands and electricity prices are modelled as stochastic variables. The candidate DG investment plans are considered as multiple mutually exclusive options, and the corresponding managerial flexibility for seizing opportunities and mitigating risk of loss upon an unfavourable unfolding of future uncertainties is assessed with real option analysis using the extended least square Monte Carlo method. The distribution of future investment strategies and optimal initial investment threshold levels under various scenarios are analysed in a case study to demonstrate the characteristics of the proposed framework and methodology.
Zou, Bo↗
Regulatory Mechanisms to Enable Investments in Electric Utility Resilience
In 2019, Sandia National Laboratories contracted Synapse Energy Economics (Synapse) to research the integration of community and electric utility resilience investment planning as part of the Designing Resilient Communities: A Consequence-Based Approach for Grid Investment (DRC) project. Synapse produced a series of reports to explore the challenges and opportunities in several key areas, including benefit-cost analysis, performance metrics, microgrids, and regulatory mechanisms to promote investments in electric system resilience. This report focuses on regulatory mechanisms to improve resilience. Regulatory mechanisms that improve resilience are approaches that electric utility regulators can use to align utility, customer, and third-party investments with regulatory, ratepayer, community, and other important stakeholder interests and priorities for resilience. Cost-of-service regulation may fail to provide utilities with adequate guidance or incentives regarding community priorities for infrastructure hardening and disaster recovery. The application of other types of regulatory mechanisms to resilience investments can help. This report: characterizes regulatory objective as they apply to resilience; identifies several regulatory mechanisms that are used or can be adapted to improve the resilience of the electric system--including performance-based regulation, integrated planning, tariffs and programs to leverage private investment, alternative lines of business for utilities, enhanced cost recovery, and securitization; provides a case study of each regulatory mechanism; summarizes findings across the case studies; and suggests how these regulatory mechanisms might be improved and applied to resilience moving forward. In this report, we assess the effectiveness of a range of utility regulatory mechanisms at evaluating and prioritizing utility investments in grid resilience. First, we characterize regulatory objectives which underly all regulatory mechanisms. We then describe seven types of regulatory mechanisms that can be used to improve resilience--including performance-based regulation, integrated planning, tariffs and programs to leverage private investment, alternative lines of business for utilities, enhanced cost recovery, and securitization--and provide a case study for each one. We summarize our findings on the extent to which these regulatory mechanisms have supported resilience to date. We conclude with suggestions on how these regulatory mechanisms might be improved and applied to resilience moving forward.
24 POWER TRANSMISSION AND DISTRIBUTION↗