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Doubleday, Kate

Publications and source records attributed to Doubleday, Kate.

Illuminating Agrivoltaics at NREL

In this talk, we will provide an overview of the INSPIREing work being done in the agrivoltaics field at NREL. We will focus on the modeling aspects of agrivoltaics, discussing key assumptions and metrics that guide research, and main open concerns from the community. We will innovative solutions implement at NREL for modeling, and ongoing experiments for shading and irradiance modeling. We will conclude with a look at the future steps necessary to advance this particular area of agrivoltaics.

14 SOLAR ENERGY↗

Sienna Modeling Framework [Slides]

NREL's Sienna modeling framework effectively builds, solves, and analyzes the scheduling problems and dynamic simulations of quasi-static infrastructure systems. It uses a modular framework to answer different questions about future energy systems, fundamentally advancing the nation's ability to model individual and integrated infrastructure systems at a range of spatial and temporal scales. This presentation will include NREL power grid researcher Clayton Barrows.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Lithuania 100% Renewable Energy Study - Interim Results: Electricity System Scenarios for 2030 [Slides]

Lithuania's Energy Vision aims to achieve self-sufficiency in electricity generation by 2035 and transition to 100% renewable energy as soon as possible while maintaining affordability, reliability, and energy security. The Lithuania Energy Agency (LEA) is partnering with the National Renewable Energy Laboratory (NREL) to conduct the Lithuania 100% Renewable Energy Study (Lithuania 100) to provide evidence-based analysis for development of Lithuania's National Energy Independence Strategy. The Lithuania 100 Study leverages unique tools and capabilities of NREL to provide rigorous technical analysis of clean energy policies to achieve 100% renewable energy, and assess impacts on electricity grid operations, hydrogen system development, electricity distribution networks, air quality, and human health outcomes. The study is supported by a stakeholder committee chaired by the Ministry of Energy of Lithuania and implemented by four technical working groups. This report provides highlights of key interim results from modeling of Lithuania's near-term electricity grid through the year 2030. Results show that Lithuania has sufficient renewable energy potential, flexible generation capacity, and interconnection with neighboring European Union countries to reliably meet projected 2030 electricity demand with 100% renewable energy. A range of scenarios were modeled, each of which achieves at least 100% renewable energy in electricity, on average over the year, by 2030. Potential demands for hydrogen across industrial and transportation sectors were also evaluated, as well as the cost of hydrogen produced in Lithuania by 2030.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

County Land-Use Regulations for Solar Energy Development in Colorado

We present a survey of county-level policies on ground-mounted solar development across Colorado, including both solar-specific ordinances as well as general land-use code that might be applicable in counties without solar-specific policies. This report provides an accessible reference for stakeholders interested in identifying counties with particular regulations or in analyzing the diversity of regulations across Colorado. We defined a set of search criteria to find information on solar definitions and classifications, permitting processes, and use-specific requirements in each of Colorado's 64 counties. With those criteria, we reviewed relevant ordinances, land-use code, and comprehensive and master plans. If any uncertainties were identified, we contacted county officials for clarification. The findings are categorized and mapped to illustrate the distribution of key policies adopted across Colorado's counties on the following topics: solar definitions, solar siting policy documentation, categorization of PV systems for permitting, 1041 permitting, solar on agricultural land, panel height restrictions, fencing requirements, vegetation management, visual impacts, decommissioning plans, and financial assurance for decommissioning. Additionally, we identify and discuss policies that might impact the deployment of agrivoltaics, a dual land use combining both agriculture and solar on the same land, which might not fit neatly in existing zoning definitions and solar-specific regulations.

14 SOLAR ENERGY↗

Solar PV, Wind Generation, and Load Forecasting Dataset for ERCOT 2018: Performance-Based Energy Resource Feedback, Optimization, and Risk Management (P.E.R.F.O.R.M.)

This report describes the Advanced Research Projects Agency-Energy Performance-Based Energy Resource Feedback, Optimization, and Risk Management (PERFORM) Electric Reliability Council of Texas (ERCOT) dataset consisting of load, solar, and wind deterministic and probabilistic forecasts at three timescales. This dataset consists of 1 year of time-coincident load, wind, and solar actuals and probabilistic forecasts for a region similar to ERCOT. All the data are stored in Hierarchical Data Format 5 (HDF5) files and have been uploaded to an Amazon Web Services repository. The ERCOT data set has 2 years (2017, 2018) of actuals and 1 year (2018) of probabilistic forecasts. These data are provided at various spatial (i.e., site-level, zone-level, and system-level) and temporal scales (i.e., day-ahead, intraday, and intra-hour). Specifically, data are provided for 125 existing wind sites, 22 existing solar sites, 139 proposed wind sites, and 204 proposed solar sites.

14 SOLAR ENERGY↗

Solar Uncertainty Management and Mitigation for Exceptional Reliability in Grid Operations (SUMMER-GO): Project Final Report

The Solar Uncertainty Management and Mitigation for Exceptional Reliability in Grid Operation (SUMMER-GO) project was recently completed through a collaboration among the National Renewable Energy Laboratory, Maxar, the Electric Reliability Council of Texas (ERCOT), the University of Texas at Dallas, the University of California Berkeley, and the University of Colorado Boulder. The project made significant advances in probabilistic solar power forecasting, both through the development of Bayesian model averaging methods for ensemble forecasting and in bringing these and other advancements into practice with Maxar's delivery of operational forecasts to ERCOT. In addition to creating more reliable solar power forecasts, the project developed methods for their utilization in power system operations. These include the development of risk-aware unit commitment and economic dispatch algorithms and methods to reformulate probabilistic forecasts to be used in these power system operational models. Dynamic power system reserve methods were also developed, which have been shown in silico to create economic savings and reliability improvements on an ERCOT-like system as well as financial savings in the ERCOT system through more granular consideration of the uncertainty associated with solar power forecasts. Finally, a situational awareness tool to help grid operators better understand solar power forecast uncertainty in daily operations was developed and extensively vetted.

14 SOLAR ENERGY↗

ARPA-E PERFORM datasets

Time-coincident load, wind, and solar data including actual and probabilistic forecast datasets at 5-min resolution for ERCOT, MISO, NYISO, and SPP. Wind and solar profiles are supplied for existing sites as well as planned sites based on interconnection queue projects as of 2021. For ERCOT actuals are provided for 2017 and 2018 and forecasts for 2018, and for the remaining ISOs actuals are provided for 2018 and 2019 and forecasts for 2019. There datasets were produced by NREL as part of the ARPA-E PERFORM project, an ARPA-E funded program that aim to use time-coincident power and load seeks to develop innovative management systems that represent the relative delivery risk of each asset and balance the collective risk of all assets across the grid. For more information on the datasets and methods used to generate them see https://github.com/PERFORM-Forecasts/documentation.

5-min data↗

A Multi-Stage Stochastic Risk Assessment With Markovian Representation of Renewable Power

Probabilistic forecasts provide a distribution of possible outputs and so can capture the uncertainty and variability of Variable Renewable Energy (VRE). However, taking advantage of uncertainty information has practical challenges that make it difficult to integrate probabilistic forecasting into control room decision-making. This paper proposes a novel use-case for probabilistic forecasts by incorporating them into the hour-ahead operations for situational awareness via a risk-averse multi-stage stochastic program. We employ a Markovian representation of the probabilistic forecasts that enables the formulation of the multi-stage problem and avoids a scenario generation phase. We test the model on a realistically sized system to assess risk and showcase the capability of using probabilistic renewable forecast as input to produce probabilistic output forecasts of future system states. The results show that the model can capture time consistency in the reserves and Area Control Error (ACE) forecast. The solution times are adequate for risk profiling in hour-ahead timescales.

forecasting↗

Stability and control of power systems with high penetrations of inverter-based resources: An accessible review of current knowledge and open questions

As power system renewable energy penetrations increase, the ways in which key renewable technologies such as wind and solar photovoltaics (PV) differ from thermal generators become more apparent. Many studies have examined the variability and uncertainty of such generators and described how generation and load can be balanced for a wide variety of annual energy penetrations, at timescales from seconds to years. Another important characteristic of these resources is asynchronicity, the result of using inverters to interface the prime energy source with the power system as opposed to synchronous generators. Unlike synchronous generators, whose frequency of alternating current (AC) injection is physically coupled to the rotation of the machine itself, inverter based asynchronous generators do not share the same physical coupling with the generated frequency. These subtle differences impact the operations of power systems developed around the characteristics of synchronous generators. In this paper we review current knowledge and open research questions concerning the interplay between asynchronous inverter-based resources (IBRs) and cycle- to second-scale power system dynamics, with a focus on how stability and control may be impacted or need to be achieved differently when there are high instantaneous penetrations of IBRs across an interconnection. This work does not seek to provide a comprehensive review of the latest developments, but is instead intended to be accessible to any reader with an engineering background and an interest in power systems and renewable energy. As such, the paper includes basic material on power electronics, control schemes for IBRs, and power system stability; and uses this background material to describe potential impacts of IBRs on power system stability, operational challenges associated with large amounts of distributed IBR generation, and modern power system simulation trends driven by IBR characteristics.

14 SOLAR ENERGY↗

Benchmark probabilistic solar forecasts: Characteristics and recommendations

We illustrate and compare commonly used benchmark, or reference, methods for probabilistic solar forecasting that researchers use to measure the performance of their proposed techniques. A thorough review of the literature indicates wide variation in the benchmarks implemented in probabilistic solar forecast studies. To promote consistent and sensible methodological comparisons, we implement and compare ten variants from six common benchmark classes at two temporal scales: intra-hourly forecasts and hourly resolution forecasts. Using open-source Surface Radiation Budget Network (SURFRAD) data from 2018, these benchmark methods are compared using proper probabilistic metrics and common diagnostic tools. Practical implementation issues, such as the impact of missing data and applicability for operational forecasting, are also discussed. Furthermore, we make recommendations for practitioners on the appropriate selection of benchmark methods to properly showcase state-of-the-art improvements in forecast reliability and sharpness. All code and open-source data are available on Github for reproducibility and for other researchers to apply the same benchmark methods to their own data.

14 SOLAR ENERGY↗

Toward a subhourly net zero energy district design through integrated building and distribution system modeling

A modeling framework integrating both building energy modeling and power system modeling is introduced for the design of net zero energy (NZE) districts for the simultaneous selection of both demand-side efficiency measures and supply-side generation technologies. A novel district control scheme is proposed for pursuing NZE on a subhourly basis while mitigating potential grid impacts such as power backfeeding and voltage violations. As a case study, Pena Station NEXT, a new 100-building, mixed-use district on a 1200-node distribution feeder in Denver, Colorado, is modeled in the integrated framework. An exhaustive scenario analysis is conducted for sizing the district's distributed energy resources, considering multiple objectives such as capital cost, net energy import, and equipment violations. Here, when trying to achieve annual NZE, the district incurs frequent operating violations, and achieving NZE on a 15-min basis is also limited by seasonal fluctuations in photovoltaic output, illustrating the need for diverse generation or seasonal storage. As a practical compromise, both annual and 15-min district import can be reduced by ~78% without significant violations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Integrated distribution system and urban district planning with high renewable penetrations

Recent efforts to reduce energy consumption and greenhouse gas emissions have resulted in the development of sustainable, smart districts with highly energy efficient buildings, renewable distributed energy resources (DERs), and support for alternative modes of transportation. However, there is typically little if any coordination between the district developers and the local utility. Most attention is paid to the district's annual net load and generation without considering their instantaneous imbalance or the connecting network's state. This presents an opportunity to learn lessons from the design of distribution feeders for districts characterized by low loads and high penetrations of DERs that can be applied to the distribution grid at large. The aim of this overview is to summarize current practices in sustainable district planning as well as advances in modeling and design tools for incorporating the power distribution system into the district planning process. Recent developments in the modeling and optimization of district power systems, including their coordination with multi-energy systems and the impact of high penetration levels of renewable energy, are introduced. Sustainable districts in England and Japan are reviewed as case studies to illustrate the extent to which distribution system planning has been considered in practice. Finally, newly developed building-to-grid modeling tools that can facilitate coordinated district and power system design with utility involvement are introduced, along with suggestions for future research directions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Peña Station NEXT: Visualizing a net-zero energy district

Learn how NREL researchers are using advanced modeling and visualization tools to help create the planned net-zero energy district, Peña Station NEXT, near the Denver International Airport in Denver, Colorado. This project will result in tools for smart city design that can be applied across the country.

24 POWER TRANSMISSION AND DISTRIBUTION↗