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DOE OSTI2024

Integrated modeling for assessing climate change impacts on water resources and hydropower potential in the Himalayas

Regional hydroclimatic variability and change can affect water resources and hydropower generation. It is essential to assess hydropower potential under current and future climatic conditions to inform the design and operation of hydropower infrastructures. Here, we employ an integrated modeling framework to assess the impact of projected hydroclimatic conditions on water resource systems and hydropower generation. The integrated framework samples climate model outputs under different scenarios to force a hydrologic model and produces streamflow projections. The projected streamflows are inputs for the future hydropower potential assessment. We implement the framework in the central Himalayan river basin. Our results demonstrate substantial spatiotemporal variability in different water balance components (precipitation, evapotranspiration, and water yield) under current and future climatic conditions. For the Himalayan Tila river basin, the annual average energy production is expected to increase under future hydroclimatic conditions (up to 39% in Tila-2 hydropower project, suggested by ensemble mean). Furthermore, this increase in energy is driven mainly by the increased streamflow projections, particularly during the dry season and in the late century. Our results highlight the impacts of hydroclimatic variability in hydropower productions and are of practical use to provide decision-relevant information for designing and operating hydropower infrastructures. The integrated modeling framework presented here is region-specific; however, the approach is reproducible, and the overall insights are generalizable across the Himalayan region.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Endogenous Assessment of the Capacity Value of Solar PV in Generation Investment Planning Studies

There exist several different reliability-and approximation-based methods to determine the contribution of solar resources toward resource adequacy. However, most of these approaches require knowing in advance the installed capacities of both conventional and solar generators. This is a complication since generator capacities are actually decision variables in capacity planning studies. In this paper, we study the effect of time resolution and solar PV penetration using a planning model that accounts for the full distribution of generator outages and solar resource variability. We also describe a modification of a standard deterministic planning model that enforces a resource adequacy target through a reserve margin constraint. Our numerical experiments show that at least 50 days worth of data are necessary to approximate the results of the full-resolution model with a maximum error of 2.5% on costs and capacity. We also show that the amount of displaced capacity of conventional generation decreases rapidly as the penetration of solar PV increases. We find that using an exogenously defined and constant capacity value based on time-series data can yield relatively accurate results for small penetration levels. For higher penetration levels, the modified deterministic planning model better captures avoided costs and the decreasing value of solar PV.

14 SOLAR ENERGY↗

DOE OSTI2015

Balancing Area Coordination: Efficiently Integrating Renewable Energy Into the Grid, Greening the Grid

Greening the Grid provides technical assistance to energy system planners, regulators, and grid operators to overcome challenges associated with integrating variable renewable energy into the grid. Coordinating balancing area operation can promote more cost and resource efficient integration of variable renewable energy, such as wind and solar, into power systems. This efficiency is achieved by sharing or coordinating balancing resources and operating reserves across larger geographic boundaries.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2014

Endogenous Assessment of the Capacity Value of Solar PV in Generation Investment Planning Studies. Draft

There exist several different reliability- and approximation-based methods to determine the capacity contribution of solar resources towards resource adequacy. However, most of these approaches require knowing in advance the installed capacities of both conventional and solar generators. This is a complication since generator capacities are actually decision variables in capacity planning studies. In this article we study the effect of time resolution and solar PV penetration using a capacity planning model that accounts for the full distribution of generator outages and solar resource variability. We also describe a modification of a standard deterministic planning model that enforces a resource adequacy target through a reserve margin constraint. Our numerical experiments show that at least 50 days worth of data are necessary to approximate the results of the full-resolution model with a maximum error of 2.5% on costs and capacity. We also show that the amount of displaced capacity of conventional generation decreases rapidly as the penetration of solar PV increases. We find that using an exogenously defined and constant capacity factor based on time-series data can yield relatively accurate results for small penetration levels (less than 5%). For higher penetration levels (up to 20%), the modified deterministic planning model better captures avoided costs and the decreasing value of solar PV. Although our results are not general, they highlight the importance of accounting for the variation in both energy and capacity value of solar resources endogenously in capacity planning models. A11 numerical experiments are performed using the IEEE Reliability Test System and 7 years worth of demand and solar data from a utility in Arizona.

14 SOLAR ENERGY↗

DOE OSTI2026

Development of an Unbiased Future Solar Dataset for Solar Resource Adequacy Research Over CONUS

A high-resolution, long-term solar dataset is essential for capturing the variability of solar energy resources and informing strategies to ensure grid reliability and resilience in systems with high levels of solar energy integration. This study focuses on generating unbiased, high-resolution projections of solar irradiance through a statistical downscaling framework, using Earth system model (ESM) simulations obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX). The National Solar Radiation Database (NSRDB) is used to calibrate statistical downscaling models. The newly developed dataset provides solar irradiance, surface air temperature, and surface wind speed at 4-km and hourly resolutions across the contiguous United States (CONUS), based on two future scenarios (RCP4.5 and RCP8.5). This study outlines key steps in developing the high-resolution future solar dataset, including (1) regridding ESM data to a common 20-km resolution grid, (2) correcting ESM biases using the NSRDB, and (3) applying temporal and spatial downscaling methods to generate high-resolution (4-km, hourly) solar projections. Preliminary results indicate that downscaled projections (4-km) captured reasonable spatial patterns when compared to observations across CONUS for four variables. On average across all pixels, 4-km daily-total GHI and DNI projections showed normalized bias (nBias) less than 1% and 6% for GHI and DNI against NSRDB, respectively (nBias less than 1% and 5% for daily-average surface air temperature and surface wind speed). In terms of long-term trend for GHI and DNI, there was no strong increasing or decreasing trend (when compared to surface air temperature), but it showed a very weak decreasing trend.

14 SOLAR ENERGY↗

NASA NTRS2022

Western Sonoran Desert Water Resources: Evaluating Rock Pool Hydroperiod Fluctuation using Climate Variables to Inform Habitat Monitoring and Protection in the Western Sonoran Desert

Ephemeral freshwater rock pools, known as tinajas, have great biologic and cultural importance as sources of surface water in the western Sonoran Desert (WSD). Tinaja flooding and drying cycles, known as hydroperiods, vary based on meteorologic and climatologic conditions; however, a lack of extensive research relating climatic impacts to tinajas puts these critical ecosystems further at risk. The National Park Service (NPS) and the University of Arizona monitor the physical and ecological condition of tinajas in Organ Pipe Cactus National Monument (OPCNM), AZ, using resource-intensive strategies: in situ trail cameras and direct measurements. To aid monitoring efforts, the NASA DEVELOP team aimed to incorporate remote sensing into NPS strategies by analyzing spatiotemporal climate data and tinaja hydroperiods in OPCNM between 1979–2022. Using Aqua and Terra Moderate Resolution Imaging Spectroradiometers (MODIS), University of Idaho Gridded Surface Meteorological Dataset (gridMET), and OpenET data, the team generated climatology maps and time series for OPCNM. The team compared these data to daily in situ hydroperiod observations from the University of Arizona between 2019–2022. Climate maps and time series showed increases in temperature and solar radiation (p<0.05), while analyses of in situ data showed correlations of hydroperiods with precipitation and evapotranspiration. End products identified high-risk tinajas and demonstrated that Earth observations can successfully be correlated with in situ hydroperiod observations. These results will support NPS efforts to prioritize water resource management and inform protocols driving the conservation of tinajas in OPCNM.

Anne Britton↗

DOE OSTI2012

Impact of Transmission on Resource Adequacy in Systems with Wind and Solar Power: Preprint

Variable generation is on track to become a significant contributor to electric power systems worldwide. Thus, it is important to analyze the effect that renewables will have on the reliability of systems. In this paper we present a new tool being implemented at the National Renewable Energy Laboratory, which allows the inclusion of variable generation in the power system resource adequacy. Thetool is used to quantify the potential contribution of transmission to reliability in highly interconnected systems and an example is provided using the Western Interconnection footprint.

14 SOLAR ENERGY↗

DOE OSTI2018

Modeling I/O Performance Variability Using Conditional Variational Auto Encoders

Storage system performance modeling is crucial for efficient use of heterogeneous shared resources on leadership class computers. Variability in application performance, particularly variability arising from concurrent applications sharing I/O resources, is a major hurdle in the development of accurate performance models. We adopt a deep learning approach based on conditional variational auto encoders (CVAE) for I/O performance modeling, and use it to quantify performance variability. We illustrate our approach using the data collected on Edison, a production supercomputing system at the National Energy Research Scientific Computing Center (NERSC). The CVAE approach is investigated by comparing it to a previously proposed sensitivity-based Gaussian process (GP) model. We find that the CVAE model performs slightly better than the GP model in cases where training and testing data come from different applications, since CVAE can inherently leverage the whole data from multiple applications whereas GP partitions the data and builds separate models for each partition. Hence, the CVAE offers an alternative modeling approach that does not need preprocessing; it has enough flexibility to handle data from a wide variety of applications without changing the inference approach.

I/O perfornance variability↗

DOE OSTI2023

New Tool Evaluates the Financial Viability of Pumped Storage Hydropower

The rapidly evolving electricity system with increasing variable renewable energy (VRE) resources provides both opportunities and challenges for the power sector. With the significant ramps and intermittency associated with VRE resources, the requirements and need for additional flexible resources increase. Pumped storage hydropower (PSH) provides flexibility to the electricity grid to replace fossil fuel plants, which are responsible for 25% of U.S. emissions. PSH projects support various aspects of power system operations, including flexibility, ramping capability, energy, ancillary service, black start, and others. The significant potential of hydropower requires understanding the different value drivers to the electricity system specific to the location of a project and then optimizing the plant for the different system values. Thus, determining the value of PSH projects and their many services and contributions to the electricity system can be a challenge for potential developers, system owners, regulators, policy makers, and consultants.

13 HYDRO ENERGY↗

DOE OSTI2014

Comparing Resource Adequacy Metrics: Preprint

As the penetration of variable generation (wind and solar) increases around the world, there is an accompanying growing interest and importance in accurately assessing the contribution that these resources can make toward planning reserve. This contribution, also known as the capacity credit or capacity value of the resource, is best quantified by using a probabilistic measure of overall resource adequacy. In recognizing the variable nature of these renewable resources, there has been interest in exploring the use of reliability metrics other than loss of load expectation. In this paper, we undertake some comparisons using data from the Western Electricity Coordinating Council in the western United States.

14 SOLAR ENERGY↗

DOE OSTI2016

Wind and Solar on the Power Grid: Myths and Misperceptions, Greening the Grid (Spanish Version)

This is the Spanish version of the 'Greening the Grid - Wind and Solar on the Power Grid: Myths and Misperceptions'. Wind and solar are inherently more variable and uncertain than the traditional dispatchable thermal and hydro generators that have historically provided a majority of grid-supplied electricity. The unique characteristics of variable renewable energy (VRE) resources have resulted in many misperceptions regarding their contribution to a low-cost and reliable power grid. Common areas of concern include: 1) The potential need for increased operating reserves, 2) The impact of variability and uncertainty on operating costs and pollutant emissions of thermal plants, and 3) The technical limits of VRE penetration rates to maintain grid stability and reliability. This fact sheet corrects misperceptions in these areas.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2015

Methodology for Clustering High-Resolution Spatiotemporal Solar Resource Data

In this report, we introduce a methodology to achieve multiple levels of spatial resolution reduction of solar resource data, with minimal impact on data variability, for use in energy systems modeling. The selection of an appropriate clustering algorithm, parameter selection including cluster size, methods of temporal data segmentation, and methods of cluster evaluation are explored in the context of a repeatable process. In describing this process, we illustrate the steps in creating a reduced resolution, but still viable, dataset to support energy systems modeling, e.g. capacity expansion or production cost modeling. This process is demonstrated through the use of a solar resource dataset; however, the methods are applicable to other resource data represented through spatiotemporal grids, including wind data. In addition to energy modeling, the techniques demonstrated in this paper can be used in a novel top-down approach to assess renewable resources within many other contexts that leverage variability in resource data but require reduction in spatial resolution to accommodate modeling or computing constraints.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2006

Generic Environment for Simulating Launch Operations

GEM-FLO (A Generic Simulation Environment for Modeling Future Launch Operations) is a computer program that facilitates creation of discrete-event simulation models of ground processes in which reusable or expendable launch vehicles (RLVs) are prepared for flight. GEM-FLO includes a component, developed in Visual Basic, that generates a graphical user interface (GUI) and a component, developed in the Arena simulation language, that creates a generic discrete-event simulation model. Through the GUI, GEM-FLO elicits RLV design information from the user. The design information can include information on flight hardware elements, resources, and ground processes. GEM-FLO translates the user s responses into mathematical variables and expressions that populate the generic simulation model. The variables and expressions can represent processing times, resource capacities, status variables, and other process parameters needed to configure a simulation model that reflects the ground processing flow and requirements of a specific RLV. Upon execution of the model, GEMFLO puts out data on many measures of performance, including the flight rate, turnaround time, and utilization of resources. This information can serve as the basis for determining whether design goals can be met, and for comparing characteristics of competing RLV designs

Steele, Martin↗

DOE OSTI2017

An assessment of flexibility reserves in stochastic modeling at multiple timescales

Due to recent technological achievements, stochastic optimization, which inherently captures the uncertainty of intermittent resources, is being used to capture the variability and uncertainty of wind and solar resources. However, due to persistent computational limitations, it is not practical to consider all possible variable generation scenarios. As a result, a reduced number of most likely scenarios is usually considered. While this helps reduce the computational burden, it also leaves the system operator vulnerable to some risk. In order to address this issue, this paper aims at providing insight into using an explicit reserve requirement in a stochastic modeling framework in order to provide system operators with greater confidence in stochastic dispatch solutions. This is accomplished by simulating a modified version of the IEEE 118 bus system in a fully stochastic, multi-timescale framework with flexibility reserve requirements. Results show that utilizing a stochastic flexibility reserve requirement within the stochastic modeling framework offers the most reliability benefit.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2014

Commercial Building Loads Providing Ancillary Services in PJM

The adoption of low carbon energy technologies such as variable renewable energy and electric vehicles, coupled with the efficacy of energy efficiency to reduce traditional base load has increased the uncertainty inherent in the net load shape. Handling this variability with slower, traditional resources leads to inefficient system dispatch, and in some cases may compromise reliability. Grid operators are looking to future energy technologies, such as automated demand response (DR), to provide capacity-based reliability services as the need for these services increase. While DR resources are expected to have the flexibility characteristics operators are looking for, demonstrations are necessary to build confidence in their capabilities. Additionally, building owners are uncertain of the monetary value and operational burden of providing these services. To address this, the present study demonstrates the ability of demand response resources providing two ancillary services in the PJM territory, synchronous reserve and regulation, using an OpenADR 2.0b signaling architecture. The loads under control include HVAC and lighting at a big box retail store and variable frequency fan loads. The study examines performance characteristics of the resource: the speed of response, communications latencies in the architecture, and accuracy of response. It also examines the frequency and duration of events and the value in the marketplace which can be used to examine if the opportunity is sufficient to entice building owners to participate.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Commercial building loads providing ancillary services In PJM

MacDonald, Jason↗

DOE OSTI2020

Variability in Wind Energy Generation across the Contiguous United States

ERA5 provides high-resolution, high-quality hourly wind speeds at 100 m and is a unique resource for quantifying temporal variability in likely wind-derived power production across the United States. Gross capacity factors (CF) in seven independent system operators (ISOs) are estimated using the location and rated power of each wind turbine, a simplified power curve, and ERA5 output from 1979 to 2018. Excluding the California ISO, the marginal probability of a calm (zero power production) is less than 0.1 in any ERA5 grid cell. When a calm occurs, the mean co-occurrence across wind-turbine-containing grid cells ranges from 0.38 to 0.39 for ISOs in the Midwest and central plains [Midcontinent (or Midwest) ISO (MISO), Southwest Power Pool (SPP), and the Electric Reliability Council of Texas (ERCOT) region], increasing to 0.54–0.58 for ISOs in the eastern United States [Pennsylvania–New Jersey–Maryland interconnection (PJM), New York ISO (NYISO), and New England ISO (NEISO)]. Periods with low gross CF have a median duration of ≤6 h, except in California, and are most likely during summer. Additionally, gross CF exhibit highest variance at periods of 1 day in ERCOT and SPP; on synoptic scales in MISO, NEISO, and NYISO; and on interannual time scales in PJM. This implies differences in optimal strategies for ensuring resilience of supply. Theoretical scenarios show adding wind energy capacity near existing wind farms is advantageous even in areas with high existing installed capacity (IC), while expanding into areas with lower IC is more beneficial to reducing ramps and the probability of gross CF falling below 20%. These results emphasize the benefits of large balancing areas and aggregation in reducing wind power variability and the likelihood of wind droughts.

17 WIND ENERGY↗

DOE OSTI2013

Distributed Smart Grid Asset Control Strategies for Providing Ancillary Services

With large-scale plans to integrate renewable generation driven mainly by state-level renewable portfolio requirements, more resources will be needed to compensate for the uncertainty and variability associated with intermittent generation resources. Distributed assets can be used to mitigate the concerns associated with renewable energy resources and to keep costs down. Under such conditions, performing primary frequency control using only supply-side resources becomes not only prohibitively expensive but also technically difficult. It is therefore important to explore how a sufficient proportion of the loads could assume a routine role in primary frequency control to maintain the stability of the system at an acceptable cost. The main objective of this project is to develop a novel hierarchical distributed framework for frequency based load control. The framework involves two decision layers. The top decision layer determines the optimal gain for aggregated loads for each load bus. The gains are computed using decentralized robust control methods, and will be broadcast to the corresponding participating loads every control period. The second layer consists of a large number of heterogeneous devices, which switch probabilistically during contingencies so that aggregated power change matches the desired amount according to the most recently received gains. The simulation results show great potential to enable systematic design of demand-side primary frequency control with stability guarantees on the overall power system. The proposed design systematically accounts for the interactions between the total load response and bulk power system frequency dynamics. It also guarantees frequency stability under a wide range of time varying operating conditions. The local device-level load response rules fully respect the device constraints (such as temperature setpoint, compressor time delays of HVACs, or arrival and departure of the deferrable loads), which are crucial for implementing real load control programs. The promise of autonomous, Grid Friendly™ response by smart appliances in the form of under-frequency load shedding was demonstrated in the GridWise Olympic Peninsula Demonstration in 2006. Each controller monitored the power grid voltage signal and requested that electrical load be shed by its appliance whenever electric power-grid frequency fell below 59.95 Hz. The controllers and their appliances responded reliably to each shallow under-frequency event, which was an average of one event per day and shed their loads for the durations of these events. Another objective of this project was to perform extensive simulation studies to investigate the impact of a population of Grid Friendly™ Appliances (GFAs) on the bulk power system frequency stability. The GFAs considered in this report are represented as demonstration units with water heaters individually modeled.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗