Computational Aspects of the National Transmission Planning Study
Presentation on computational aspects of National Transmission Planning Study supporting a panel discussion.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
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Results for “Expansion Planning”
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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Regional Energy Deployment System (ReEDS) Model Documentation: 2025
The Regional Energy Deployment System (ReEDS) model is a capacity expansion and dispatch model that is primarily used for the contiguous U.S. electric power sector. The model relies on system-wide least cost optimization to estimate the type and location of future generation and transmission capacity. This document describes details of how the model is formulated, how it functions, and many of the key inputs.
15 GEOTHERMAL ENERGY↗
Powering Large Loads: Solutions Across Transmission, Utility, and Facility Scales
This report synthesizes current strategies for accommodating large load growth through a review of publicly available technical literature and media insights around the United States (U.S.). Solutions are organized across three implementation scales (transmission, utility, and facility) and categorized according to common implementation pathways (including structural expansion, operations and efficiency, upgrades, and planning and policy).
Valdez, Raquel Lynn [Sandia National Laboratories ↗
Modeling Market Interactions
This slide deck provides a high-level overview of wholesale electricity market design model development activities occurring at NREL. The motivation for this work, as well as the broader NREL modeling landscape in which it belongs, is first presented. Then the various model formulations and features are described.
agent-based simulation↗
Nuclear's Role in the U.S. Electricity System: A Multi-Model Inter-Comparison Analysis
A variety of US electric power sector capacity expansion models are used by decision makers and analysts to evaluate competition among generation, transmission, and storage technologies to meeting the demands of the system. CEMs use least-cost optimization to identify optimal portfolios of investments capable of satisfying all specified requirements. While CEMs are a useful tool to inform pathways to meet future needs, projections can differ significantly between tools for apparently similar scenario assumptions. Differences in model structure, scope, and input assumption contribute to this issue. This work compares model response with harmonization between four modeling teams on issues significant to the representation and development of nuclear energy.
capacity expansion model↗
Insights on Nuclear Energy from Long-Term System Models: Inter-Model Comparison Results
A variety of US electric power sector capacity expansion models are used by decision makers and analysts to evaluate competition among generation, transmission, and storage technologies to meeting the demands of the system. CEMs use least-cost optimization to identify optimal portfolios of investments capable of satisfying all specified requirements. While CEMs are a useful tool to inform pathways to meet future needs, projections can differ significantly between tools for apparently similar scenario assumptions. Differences in model structure, scope, and input assumption contribute to this issue. This work compares model response with harmonization between four modeling teams on issues significant to the representation and development of nuclear energy.
capacity expansion model↗
Advancing Understanding of Geothermal Representation in the Power Sector to Accelerate Deployment
Driven mostly by decarbonization goals, geothermal interest in the US power sector has grown considerably, gradually evolving from being considered a niche technology, to being recognized as a viable source of clean, baseload, grid-balancing power, and renewable electric power generation. Furthermore, recent technical advances that could greatly accelerate deployment in the near future, and US federal incentives for low-carbon generation technologies, including geothermal, can enable opportunities for integrating geothermal into utilities resource planning portfolios. However, in general, utilities do not have in-house expertise to evaluate geothermal technologies and its potential role in helping decarbonize the grid as well as help them achieve their individual decarbonization goals. To date, geothermal is rarely included in Capacity Expansion Models (CEM) which utilities use in their planning activities and resource/technologies prioritization. To this end, EPRI and NREL are working together in a DOE-GTO funded research project to improve geothermal understanding (opportunities, value, risks) among the power industry to help accelerate geothermal deployment. In the present paper we describe the approach and preliminary findings of this work, focused on two topics: 1) Expand the degree of understanding on the value, opportunity, and risk of geothermal technologies among utilities and related companies/groups, specifically around geothermal for power generation. 2) Improve representation of geothermal power technologies in capacity expansion models (CEM).
capacity expansion models↗
Effect of modeled time horizon on quantifying the need for long-duration storage
Long-Duration Energy Storage (LDES) has gained interest due to its key role in attaining a decarbonized, low-cost, and stable grid driven by variable renewable electricity (VRE). Currently, there is a wide range of LDES technologies being developed to provide electricity with 8+ hours of consecutive discharge. However, current capacity expansion models used in long-term planning processes rarely consider low cost LDES as a candidate technology. If they do, the storage balancing horizon (SBH) of the model usually only considers non-consecutive 1-day periods that do not capture the potential of LDES to shift energy across multiple days or even seasons. Addressing these limitations in existing models, this work explores the ways in which the optimal energy storage changes when increasing the number of consecutive days in the SBH and how these changes will impact planners who are determining the future roles of energy storage. Our analysis uses SWITCH, an open-source capacity expansion model with a high spatial resolution for the entire Western Electricity Coordinating Council (WECC) in a zero-carbon scenario in 2050. We find that the number of consecutive days in the SBH changes both the total selected power and energy capacity of LDES when storage energy and power capacity overnight costs are $\$$13 USD/kWh (or less) and $113 USD/kW, respectively. We also find that the amount of required energy in storage to drive a future VRE-driven WECC grid ranges from 2.5 TWh to 16.0 TWh depending on the length of the SBH. The optimal storage duration (energy to power ratio) we obtain ranges from 10 h to 620 h among all the scenarios. Furthermore, depending on the storage cost assumption, we observe different charge/discharge patterns when varying the length of the SBH. Given our results, we anticipate that as more LDES technologies become commercially available, it will be critical to increase the length of the SBH to fully capture the benefits of LDES assets in long-term planning processes of high VRE-driven grids.
42 ENGINEERING↗
Plans for Expanded Data Testing at ORNL [Slides]
VALID expansion is on-going and should provide coverage over a wider range of systems in the future. Adding additional application types beyond critical experiments can also be used in expanded data testing. Two other test suites have been developed at ORNL for other purposes, but never waste a good test suite. These suites are more likely to be relevant to testing differences in data as compared to assessing accuracy of evaluations.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Modeling the Water Systems of the Western US to Support Climate‐Resilient Electricity System Planning
Abstract Electricity and water systems in the Western US (WUS) are closely connected, with hydropower comprising 20% of total annual WUS generation, and electricity related to water comprising about 7% of total WUS electricity use. Because of these interdependencies, the threat of climate change to WUS resources will likely have compounding electricity impacts on the Western Interconnect grid. This study describes a WUS‐wide water system model with a particular emphasis on estimating climate impacts on hydropower generation and water‐related electricity use, which can be linked with a grid expansion model to support climate‐resilient electricity planning. The water system model combines climatically‐driven physical hydrology and management of both water supply and demand allocation, and is applied to an ensemble of 15 climate scenarios out to 2050. Model results show decreasing streamflow in key basins of the WUS under most scenarios. Annual water‐related electricity use increases up to 4%, and by up to 6% during the summer months, driven by growing agricultural demands met increasingly through a shift toward energy‐intensive groundwater to replace declining surface water. Total annual hydropower generation changes by +5% to −20% by mid‐century but declines in most scenarios, with decreases in summer generation by up to nearly −30%. Water‐related electricity use increases tend to coincide with hydropower generation declines, annually and seasonally, demonstrating the importance of concurrently evaluating the climate signal on both water‐for‐energy and energy‐for‐water to inform planning for grid reliability and decarbonization goals.
13 HYDRO ENERGY↗
2020 Standard Scenarios Report: A U.S. Electricity Sector Outlook
This report summarizes the results of 47 forward-looking 'standard scenarios' of the U.S. power sector simulated by the National Renewable Energy Laboratory (NREL) using the Regional Energy Deployment System (ReEDS) and Distributed Generation (dGen) capacity expansion models. The annual Standard Scenarios, which are now in their sixth year, have been designed to capture a range of possible power system futures considering a variety of factors that impact power sector evolution.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Regional Energy Deployment System (ReEDS) Model Documentation: Version 2019
The Regional Energy Deployment System (ReEDS) model is a capacity expansion and dispatch model that is primarily used for the contiguous U.S. electric power sector. The model relies on system-wide least cost optimization to estimate the type and location of future generation and transmission capacity. This document describes details of how the model is formulated, how it functions, and many of the key inputs.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Regional Energy Deployment System (ReEDS) Model Documentation (Version 2020)
The Regional Energy Deployment System (ReEDS) model is a capacity expansion and dispatch model that is primarily used for the contiguous U.S. electric power sector. The model relies on system-wide least cost optimization to estimate the type and location of future generation and transmission capacity. This document describes details of how the model is formulated, how it functions, and many of the key inputs.
24 POWER TRANSMISSION AND DISTRIBUTION↗
A data-driven operational model for traffic at the Dallas Fort Worth International Airport
Airports are on the front line of significant innovations, allowing the movement of more people and goods faster, cheaper, and with greater convenience. As air travel continues to grow, airports will face challenges in responding to increasing passenger vehicle traffic, which leads to lower operational efficiency, poor air quality, and security concerns. This paper evaluates methods for traffic demand forecasting combined with traffic microsimulation, which will allow airport operations staff to accurately predict traffic and congestion. Using two years of detailed data describing individual vehicle arrivals and departures, aircraft movements, and weather at Dallas-Fort Worth (DFW) International Airport, we evaluate multiple prediction methods including the Auto Regressive Integrated Moving Average (ARIMA) family of models, traditional machine learning models, and DeepAR, a modern recurrent neural network (RNN). We find that these algorithms are able to capture the diurnal trends in the surface traffic, and all do very well when predicting the next 30 minutes of demand. Longer forecast horizons are moderately effective, demonstrating the challenge of this problem and highlighting promising techniques as well as potential areas for improvement. Traffic demand is not the only factor that contributes to terminal congestion, because temporary changes to the road network, such as a lane closure, can make benign traffic demand highly congested. Combining a demand forecast with a traffic microsimulation framework provides a complete picture of traffic and its consequences. The result is an operational intelligence platform for exploring policy changes, as well as infrastructure expansion and disruption scenarios. To demonstrate the value of this approach, we present results from a case study at DFW Airport assessing the impact of a policy change for vehicle routing in high demand scenarios. This framework can assist airports like DFW as they tackle daily operational challenges, as well as explore the integration of emerging technology and expansion of their services into long term plans.
97 MATHEMATICS AND COMPUTING↗
Beyond Capacity Credits: Adaptive Stress Period Planning for Evolving Power Systems
This paper combines and applies concepts from several researchers to outline an alternative framework to plan power systems for resource adequacy needs, which we call Adaptive Stress Period Planning (ASPP). It first provides background information regarding least-cost planning objectives and the challenge of balancing an increasing need for model representation with computational intensity as power systems evolve in complexity. Next, it motivates the opportunity for a new paradigm by outlining challenges of frameworks in use today that rely on aggregate capacity heuristics (i.e., capacity credits and planning reserve margins). Subsequently, it lays out main process details of ASPP, which more directly represents spatial and temporal dynamics of power systems in a capacity expansion model with a process to adaptively select risk periods. The paper concludes with a summary of the approach, its benefits, and opportunities for future work.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Informing Transmission Supply Chain Needs from National Transmission Studies
Recent national studies indicate significant transmission expansion can provide the lowest-cost option to maintain grid reliability while meeting growing demand. However, constraints in domestic supply chains may limit grid expansion across the U.S., with higher costs and longer delays for required transmission equipment. Despite growing evidence of supply chain constraints for transmission components, transmission planning studies often assume transmission equipment is readily available for deployment or analyze future demand using historical trade and manufacturing data that may not capture evolving grid needs. This report aims to address this gap by demonstrating methods to quantify future demand for critical transmission components and input materials from national-scale planning models. These components include power transformers, generator step-up transformers, converter transformers, conductors, circuit breakers, and transmission towers and the materials include aluminum, steel, grain-oriented electrical steel (GOES), and copper. The analytical approach is applied to two nodal transmission expansion scenarios from the National Transmission Planning Study (NTP) to illustrate the methods. These scenarios represent different transmission expansion strategies for the contiguous U.S. to the year 2035: the Alternating Current (AC) scenario includes AC transmission expansion within each interconnection and the Multiterminal (MT) scenario includes interregional transmission expansion across the country using both AC and multiterminal HVDC options between neighboring zones. We also explore potential heuristics to derive transmission component demand from zonal capacity expansion models (CEMs) with coarse representation of the transmission grid.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Informing Transmission Supply Chain Needs from National Transmission Studies
Recent national studies indicate significant transmission expansion can provide the lowest-cost option to maintain grid reliability while meeting growing demand. However, constraints in domestic supply chains may limit grid expansion across the U.S., with higher costs and longer delays for required transmission equipment. Despite growing evidence of supply chain constraints for transmission components, transmission planning studies often assume transmission equipment is readily available for deployment or analyze future demand using historical trade and manufacturing data that may not capture evolving grid needs. This report aims to address this gap by demonstrating methods to quantify future demand for critical transmission components and input materials from national-scale planning models. These components include power transformers, generator step-up transformers, converter transformers, conductors, circuit breakers, and transmission towers and the materials include aluminum, steel, grain-oriented electrical steel (GOES), and copper. The analytical approach is applied to two nodal transmission expansion scenarios from the National Transmission Planning Study (NTP) to illustrate the methods. These scenarios represent different transmission expansion strategies for the contiguous U.S. to the year 2035: the Alternating Current (AC) scenario includes AC transmission expansion within each interconnection and the Multiterminal (MT) scenario includes interregional transmission expansion across the country using both AC and multiterminal HVDC options between neighboring zones. We also explore potential heuristics to derive transmission component demand from zonal capacity expansion models (CEMs) with coarse representation of the transmission grid.
24 POWER TRANSMISSION AND DISTRIBUTION↗
A Supply Chain Road Map for Offshore Wind Energy in the United States
"A Supply Chain Road Map for Offshore Wind Energy in the United States" identifies pathways to developing a domestic offshore wind supply chain that can manufacture and deploy the major components needed to set the United States on a pathway to installing 30 GW of offshore wind by 2030 and 110 GW by 2050. The report estimates that this supply chain could require an investment of at least $\$$22.7 billion this decade to meet an annual demand for components, ports, and vessels in 2030. Although this is a considerable investment, it could allow the industry to install around $\$$100 billion worth of offshore wind this decade by reducing risk of delays due to global supply chain bottlenecks and creating a robust network of assets that will continue to be effective well beyond 2030. The United States would need at least 34 manufacturing facilities employing 10,000 workers, 39,000 jobs in the supporting supply chain, 10 marshaling ports, 4-6 dedicated wind turbine installation vessels, 4-6 dedicated heavy-lift vessels, and 4-8 U.S.-flagged specialized feeder barges to come online this decade to support an average annual deployment of 4-6 gigawatts offshore wind capacity per year. This supply chain could be developed in 6-9 years, but would require near-term decision making and efficient permitting and planning to strategically develop these resources by 2030. Additional investment and expansion would be required in the 2030s as the sector expands into new regions (such as the Gulf of Mexico) and new technologies (such as larger wind turbines and floating wind energy projects). Furthermore, the planning process needs to meaningfully engage with communities that will be impacted by supply chain expansion to achieve just outcomes and maximize benefits to these stakeholders, which will result in a more equitable and sustainable supply chain. While U.S. offshore wind has made significant progress in recent years, remaining supply chain challenges include uncertainty surrounding deployment and procurement timelines; a lack of port and vessel infrastructure; and limitations in the available workforce, supporting supplier networks, and energy justice best practices. However, many of these problems can be addressed through improved communication between key stakeholder groups, support from federal and state governments, and forward-thinking designs of supply chain assets to accommodate future technology changes for fixed-bottom and floating offshore wind. Although it is a significant task, developing these domestic capabilities represents a once-in-a-generation opportunity to contribute to a decarbonized energy future and also create massive economic benefits that are distributed throughout the country.
17 WIND ENERGY↗