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Grue, Nicholas

Publications and source records attributed to Grue, Nicholas.

Measuring and Valuing Resilience: A Literature Review for the Power Sector

The New York State Energy Research and Development Authority (NYSERDA) partnered with NREL to address some of the key research needs for New York State in advancing power sector resilience. NYSERDA requested a literature review specifically focused on measuring and valuing energy resilience to identify existing work and gaps in research to inform NYSERDA's energy resilience efforts. While the costs of resilience investments are relatively well known, it is also important to adequately convey the benefits of these investments. This often means assigning metrics and estimating the dollar value of potential advantages of resilience enhancements.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Applications of Measuring and Valuing Resilience in Energy Systems

The electricity sector is vulnerable to numerous hazards that are being exacerbated by climate change, which can cause an increase in the hazards' frequency and intensity. Consumers, system regulators, system operators, and communities are now preparing to mitigate the increased risks posed by climate change. New York State's energy infrastructure resilience can be increased with targeted investments including but not limited to installing emergency backup systems, integrating microgrid solutions, weatherizing buildings, increasing energy efficiency, adding redundancy, investing in restoration and recovery, and hardening critical components. Such investments can reduce the likelihood, impact, and consequences of disruptive events but can also increase capital and operating costs. A barrier to prioritizing investments in resilience is that there is no widely established method for quantifying and assigning the benefits of resilience investments across various stakeholders. Decision-makers need better information detailing the value of resilience improvements. Developing methods to quantify, value, and price resilience helps meet resilience needs in an effective manner that also supports broader societal welfare. This report lays out considerations for quantifying and valuing resilience, discusses the current state of resilience valuation tools, and provides case studies of resilience projects that demonstrate how resilience attributes could be measured while highlighting broader, project-specific challenges to increasing resilience. Further, we present insights into methods and challenges to measuring, valuing, and enacting resilience investments.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Complementarity of Renewable Energy-Based Hybrid Systems

Increased attention has focused on scenarios of rapid and deep decarbonization of the U.S. electricity supply, with least-cost solutions typically involving significant expansion of renewable energy, energy storage, and transmission assets. Strategies that enable the integration of renewable energy projects while minimizing transmission expansion could be especially valuable in the future. It is within this context that the concept of hybrid power plants (or hybrid energy systems) has gained prominence. One specific example is the FlexPower concept, which seeks to demonstrate how coupling variable renewable energy (VRE) and energy storage technologies can result in renewable-based hybrid power plants that provide full dispatchability and a full range of reliability and resiliency services, similar to or better than fuel-based power plants.

13 HYDRO ENERGY↗

Data on temporal complementarity of hybrid renewable energy systems [SWR-23-09]

These datasets describe multiple facets of the temporal complementarity of co-located hybrid renewable energy systems throughout the United States. Several metrics characterizing the complementarity of generation profiles are provided on an annual and monthly basis (for both hourly and daily aggregations). These generation profiles are underpinned by hourly resource data (e.g., the WIND Toolkit and National Solar Radiation Database (NSRDB)) spanning the multi-year period 2007-2013. The data include complementarity results for greater than 1.76 million individual locations within the continental United States (CONUS). The data are intended to accompany two publications on the topic of temporal complementarity: 1) Harrison-Atlas, Dylan, Caitlin Murphy, Anna Schleifer, and Nicholas Grue. "Temporal complementarity and value of wind-PV hybrid systems across the United States." Renewable Energy 201 (2022): 111-123, doi:10.1016/j.renene.2022.10.060; and 2) Murphy, Caitlin, Harrison-Atlas, Dylan, Nicholas Grue, Vahan Gevorgian, Juan Gallego-Calderon, Shiloh Elliot and Thomas Mosier. “A Resource Assessment for FlexPower”. NREL Technical Report.

Harrison-Atlas, Dylan↗

The Renewable Energy Potential (reV) Model: A Geospatial Platform for Technical Potential and Supply Curve Modeling

The Renewable Energy Potential (reV) model is a platform for detailed assessment of renewable energy (RE) resources and their geospatial intersection with grid infrastructure and land use characteristics. The reV model currently supports photovoltaic (PV), concentrating solar power (CSP) and land-based wind turbine technologies. Modules in the reV framework function at different spatial and temporal resolutions, allowing for assessment of resource potential, technical potential and supply curves at varying levels of detail. The platform runs on NREL's High Performance Computing system, providing scalable and efficient performance from a single location all the way up to continental scales, for a single year or decades of time series resource data. Coupled with NREL's System Advisor Model (SAM), reV supports resource assessment from 5-minute to hourly temporal resolution and provides for analysis of long-term (i.e., year-on-year) variability of RE generation (e.g., interannual variability and exceedance probabilities). Technical potential is measured as a function of resource potential and limitations put on developable land area defined by the user. For example, the user can limit development by land ownership, terrain, land use/cover, and urban areas, as well as custom inputs. Technology, grid interconnection and operation costs, based on the latest market data and future projections, are also embedded in the model. The supply curve module is a spatial sorting algorithm based on plant siting, grid interconnection cost, and regional competition, which provides a geographically discrete estimate of levelized cost of electricity (LCOE) and supply (i.e., capacity) for specific renewable technologies. The reV model currently provides broad coverage across North America, South and Central Asia, South America and South Africa to inform national- and international-scale analyses as well as regional infrastructure and deployment planning.

13 HYDRO ENERGY↗

After the hurricane: Validating a resilience assessment methodology

With increasing utility grid outages in the United States, there is growing interest in assessing risk and developing mitigation strategies to reduce the impact of grid outages. Working with the U.S. Air Force, the U.S. Department of Energy's National Renewable Energy Laboratory (NREL) developed a replicable energy resilience assessment methodology and investment decision tool to: (1) identify and score hazards and vulnerabilities at the site level; (2) analyze risks to energy infrastructure; and (3) identify and prioritize energy resilience investments. This work improves on existing resilience assessment methodologies and tools by combining a bottom-up, all-hazards assessment methodology with top-down geographic information system mapping capabilities to provide an innovative, dynamic tool for identifying and prioritizing actionable solutions. This process combines probabilistic forecasting with an iterative approach for continuously updating and reassessing risks to address temporal dynamism. Relationships among systems are modeled and visualized to estimate the effectiveness of resilience actions across multiple interdependent systems and inform financial priorities through cost-difficulty-impact trade-offs. The approach is validated in a case study at Tyndall Air Force Base (AFB) in Florida, which experienced a Category 5 hurricane in 2018. The risks and mitigation strategies identified pre-hurricane are compared with post-hurricane, realized impacts. The assessment effectively identifies risks and actions to increase site energy resilience, but the methodology can be enhanced though greater consideration of the interdependencies between the energy system and related systems like transportation, communication, and food/water systems, which impact the recovery of the energy system and the base.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

reV (The Renewable Energy Potential Model - Open Source) [SWR-21-59, SWR-20-20 and SWR-17-34]

The Renewable Energy Potential (reV) model is a platform for the detailed assessment of renewable energy resources and their geospatial intersection with grid infrastructure and land use characteristics. The reV model currently supports photovoltaic (PV), concentrating solar power (CSP), and land-based wind turbine technologies. Modules in the reV framework function at different spatial and temporal resolutions, allowing for the assessment of resource potential, technical potential, and supply curves at varying levels of detail. The platform runs on the National Renewable Energy Laboratory’s (NREL’s) high-performance computing system, providing scalable and efficient performance from a single location up to a continent, for a single year or decades of time-series resource data. Coupled with NREL’s System Advisor Model (SAM), reV supports resource assessments from 5-minute to hourly temporal resolutions and supports the analysis of long-term (i.e., year-on-year) variability of renewable generation (e.g., interannual variability and exceedance probabilities).

Maclaurin, Galen↗