Engineering topics

Jorgenson, Jennie

Publications and source records attributed to Jorgenson, Jennie.

25 records · Page 2

DOE OSTI2021

Methods for Representing Flexible, Energy-Constrained Technologies in Utility Planning Tools

Capacity expansion models are widely used by power system researchers, planners, and policy analysts to evaluate alternative power system investment scenarios. With the increasing deployment of wind and solar in the US, there has been much focus on improving the representations of variable generation (VG) technologies within capacity expansion models. Models that capture the variable net-load profiles and larger reserve requirements associated with high penetration VG systems represent an improvement to classic capacity expansion models, but fall short of capturing the complexities associated with storage technologies, such as battery energy storage (BES) and concentrating solar power with thermal energy storage (CSP with TES). While difficult to model in a capacity expansion setting, these technologies are potentially competitive sources of flexibility with the intriguing characteristics of being able to absorb VG that would otherwise be curtailed and directly contribute to renewable energy goals, respectively. In this paper we present methods for accurately representing these technologies in a large-scale capacity expansion model with high electrical and geospatial resolution. VG modeling techniques, including novel methods for capturing curtailment due to unit commitment and other hourly dispatch phenomena, are also reviewed. Modeling for a region in the southwestern United States demonstrates the economic relevance of being able to explicitly trade off the costs and capabilities of energy-constrained technologies, especially BES, against other resources in the near-term, in time to make plans for the coming decade

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

The Los Angeles 100% Renewable Energy Study (LA100): Executive Summary

The City of Los Angeles has set ambitious goals to transform its electricity supply, aiming to achieve a 100% renewable energy power system by 2045, along with aggressive electrification targets for buildings and vehicles. To reach these goals, and assess the implications for jobs, electricity rates, the environment, and environmental justice, the Los Angeles City Council passed a series of motions directing the Los Angeles Department of Water and Power (LADWP) to determine the technical feasibility and investment pathways of a 100% renewable energy portfolio standard. The Los Angeles 100% Renewable Energy Study (LA100) is a first-of-its-kind objective, rigorous, and science-based power systems analysis to determine what investments could be made to achieve these goals. The LA100 final report is presented as a collection of 12 chapters and an executive summary, each of which is available as an individual download.

100% renewable↗

DOE OSTI2021

The Los Angeles 100% Renewable Energy Study (LA100): Chapter 6. Renewable Energy Investments and Operations

100% Renewable↗

DOE OSTI2021

A systematic evaluation of wind's capacity credit in the Western United States

Abstract The degree to which wind energy can contribute to the capacity needed to meet resource adequacy requirements, also known as capacity credit (CC), can be impacted by many factors. The CC varies regionally with wind resource and correlation to net load and may also vary with wind technology (land‐based versus offshore) and turbine specifications. We use a probabilistic resource adequacy tool to systematically assess the CC of multiple technologies for near‐term wind deployment across the Western US power system to help inform planning decisions. We find that wind CC varies by weather year and location but averages 16% for land‐based turbines and 41% for offshore turbines, with large regional variations. The average wind CC increases to 20% for land‐based and 53% for offshore when considering only the sites in the top 25th percentile of capacity factor. The CC of land‐based wind is generally lower than its capacity factor, which indicates a low correlation of generation to system needs. However, offshore wind shows a substantially higher CC, which is driven by not only a higher capacity factor but also a greater correlation with system needs.

17 WIND ENERGY↗

DOE OSTI2021

Managing Solar Photovoltaic Integration in the Western United States Appendix: Reference and High Solar Photovoltaic Scenarios for Three Regions [Slides]

This slide deck is an appendix to a paper series that examines potential challenges related to planning future power systems with higher solar photovoltaic (PV) penetrations. The series uses the western U.S. power system for these investigations because it is a region the authors and their colleagues have already extensively studied. We are therefore well-suited to analyze even higher PV penetrations and then examine the results in multiple models to determine whether our current approaches are missing key details that only emerge at higher PV penetrations. This deck details the systems underlying those analyses and how they were modeled using the Resource Planning Model (RPM), a capacity expansion modeling tool. We examine both Western Interconnection-wide and regional results for three regions in the Western U.S. with significantly different existing power systems and connections to neighboring regions; this provides a more balanced picture as to how power systems with high PV penetration might emerge in different contexts and what the resulting grid challenges, if any, might be.

14 SOLAR ENERGY↗

DOE OSTI2020

Managing Solar Photovoltaic Integration in the Western United States: Power System Flexibility Requirements and Supply

As penetrations of variable renewable energy generation technologies such as wind and solar photovoltaics (PV) continue to increase across the United States, greater uncertainty and variability in the net load often lead to a concern about how power systems may adapt. Managing the system net load (i.e., load minus contribution from variable generation technologies) may become more challenging with increasing variable generation, as the magnitude and frequency of net ramps increase. However, there is inherent flexibility in power systems through the conventional generator fleet (under least-cost unit commitment and economic dispatch), less-conventional generation sources (e.g., storage, demand response, concentrating solar power with thermal energy storage), and imports and exports with neighbors. In this analysis, we create an open-source tool to analyze the flexibility of the results of a specific commercial unit commitment and economic dispatch tool (PLEXOS), but the code can be applied generically as well. The tool assesses the flexibility requirements (or demand) of a system through a net load analysis. The constraints and limitations of each generator are then considered to determine the availability (or supply) of flexibility. Then, the supply and demand of flexibility are compared to gain a more complete picture of potential flexibility concerns. We apply this open-source tool to high-penetration PV scenarios constructed for three focus regions in the western United States defined using the Resource Planning Model (RPM) capacity expansion modeling tool: RPM-OR, RPM-CO, and RPM-AZ. Generally, we find few flexibility concerns, as the western United States represents a large and interconnected power system with significant inherent flexibility. In addition, the PV scenarios we analyzed are overbuilt on capacity, leaving plenty of ramping ability on the system. We do find that for each focus region, the impact of imports on meeting ramping needs is essential. This means the PV integration in each focus region impacts the entire rest of the system. Each system has different dominant sources of flexibility. The conventional generator fleet (especially coal and gas combined-cycle technologies) as well as less-conventional sources such as storage are all shown to be important sources of flexibility. The scenarios evaluated here were designed to study the planning and operations impact of high solar penetration in each of three focus regions. However, none of the three focus regions likely will deploy PV in isolation, meaning the ability of imports and exports to provide flexibility may be considerably different in scenarios with strong PV deployment in every region. Overall, we intend that the framework we present here will be useful in future analysis of other system evolutions to identify whether and how flexibility may constrain the successful deployment of variable generation technologies.

14 SOLAR ENERGY↗

DOE OSTI2020

SAM™ (System Advisor Model™) [SWR-16-02, SWR-10-13]

See the SAM™ website to build a desktop version of the National Laboratory of the Rockies' (NLR's) System Advisor Model™ (SAM). https://sam.nlr.gov/ The System Advisor Model™ (SAM™) is a free techno-economic software model that facilitates decision-making for people in the renewable energy industry: -Project managers and engineers -Policy analysts -Technology developers -Researchers SAM can model many types of renewable energy systems: -Photovoltaic systems, from small residential rooftop to large utility-scale systems -Battery storage with Lithium ion, lead acid, or flow batteries for front-of-meter or behind-the-meter applications -Concentrating Solar Power systems for electric power generation, including parabolic trough, power tower, and linear Fresnel -Industrial process heat from parabolic trough and linear Fresnel systems -Wind power, from individual turbines to large wind farms -Marine energy wave and tidal systems -Solar water heating -Fuel cells -Geothermal power generation -Biomass combustion for power generation -High concentration photovoltaic systems SAM's financial models are for the following types of projects: -Residential and commercial projects where the renewable energy system is on the customer side of the electric utility meter (behind the meter), and power from the system is used to reduce the customer's electricity bill. -Power purchase agreement (PPA) projects where the system is connected to the grid at an interconnection point, and the project earns revenue through power sales. The project may be owned and operated by a single owner or by a partnership involving a flip or leaseback arrangement. -Third party ownership where the system is installed on the customer's (host) property and owned by a separate entity (developer), and the host is compensated for power generated by the system through either a PPA or lease agreement. For a more detailed description of SAM, see Blair et al. (2018), System Advisor Model (SAM) General Description (Version 2017.9.5), NREL/TP-6A20-70414. https://www.nrel.gov/docs/fy18osti/70414.pdf

Ryberg, David↗