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Virtual Trainings are the online version of the multi-day workshops known as In-Plants (INPLTs) offered by the DOE Better Plants program. ORNL has a 6-session weekly training on Renewable Energy Contracting Options and RECs starting August 5th 2025 (10 am ET) focused on options and resources for the manufacturing sector. This session is earmarked for Tuesday, August 26th, 10 AM ET.
This paper presents an overview of an ongoing project to develop and deliver a solar mapping processing system to the National Renewable Energy Laboratory (NREL) using the data sets that are planned for production at the National Climatic Data Center (NCDC). NCDC will be producing a long-term radiance and cloud property data set covering the globe every three hours at an approximate resolution of 10 x 10 km. NASA, the originators of the Surface meteorology and Solar Energy web portal are collaborating with SUNY-Albany to develop the production system and solar algorithms. The initial result will be a global long-term solar resource data set spanning over 25 years. The ultimate goal of the project is to also deliver this data set and production system to NREL for continual production. The project will also assess the impact of providing these new data to several NREL solar decision support tools.
Abnormal climates due to global warming have emerged as a big concern in the global community. To mitigate climate change and achieve sustainability, distributed energy resources (DERs), including solar and wind, have been recently deployed in power systems. As the penetration level of DERs has increased, however, it caused a multitude of issues in the power systems, such as voltage fluctuation in the distribution network limiting renewable hosting capacity. On the other hand, the electric vehicle (EV) industry is rapidly growing to facilitate the transition to a carbon-neutral community, illuminating the potential of EVs as a flexible grid asset to mitigate some of the issues and improve grid operation, if properly exploited. To explore the potential of EVs, this paper proposes an EV scheduling strategy. By using an optimal EV charging scheduling proposed, distribution system operators (DSOs) can minimize their operating costs and stably operate the system with a high level of DERs. To validate the method, a modified IEEE 33-bus system with DERs is developed. The case study shows the proposed scheduling strategizes EV charging to reduce the cost of PV curtailment. In the study, the method outperforms the renewable-only case with curtailment by 4.97% in DSO cost. It also demonstrates its potential to increase the renewable hosting capacity by harmonizing EV charging with renewables.
As the penetration level of power electronics-interfaced renewables such as photovoltaics (PV) and wind has surged in modern electric grids, new operational risks caused by the dynamics of those inverter-based resources (IBRs) are emerging in parallel. Lessons learned from various grid events include that the impact of IBRs on system-level grid stability will become prominent along with the increase of renewables and that the short-timescale dynamic impacts of IBRs on grid stability are not fully captured by current commercial dynamic simulation tools [1] [2]. For example, IBRs can be controlled to mitigate those destabilizing interactions, but conventional phasor-domain tools (e.g. PSS/E, PSLF) often cannot capture that; likewise, the existing electromagnetic transient (EMT) simulation tools (e.g. PSCAD, EMTP) can simulate detailed IBR controls, but for large power systems with many IBRs, slow simulation speeds severely impede the ability to study dynamic events [3] [4]. Massively paralleling simulations using high-performance computing (HPC) can help address this, especially now that cloud-based HPC capability is widely available, but today s EMT tools are not HPC-compatible, and parallelization of dynamic simulation solvers is not trivial because each region can dynamically affect the others. Thus, dynamic simulation of grids with very large numbers of IBRs potentially poses a barrier to the ongoing energy transition.
Wind energy is among the most mature renewable energy technologies, accounting for 11% of the current US electricity generation in 2024, with the lowest average levelized cost. While it is known that substantial opportunity exists for further development, a key question has been where wind energy is best suited compared to other technologies. This study leverages an immense dataset of parcel-resolved technoeconomic potential for the contiguous United States, focusing on distributed wind (DW) energy—a configuration where one or more turbines, typically 30–60 m in height are used to satisfy nearby energy needs. The analysis is conducted at multiple spatial scales and considers land use, crop land, census, and incentive program data to determine the most opportune areas for market development. The results show that rural, agricultural and residential areas are most suited to DW. Connection type (in front of, or behind the meter) and regulations determine the best application, while siting constraints, economics, demand and the wind resource determines the optimal size of turbine.
The Distributed Generation Market Demand (dGen) model simulates customer adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the United States or other countries through 2050. The dGen model can be used for identifying the sectors, locations, and customers for whom adopting DERs would have a high economic value, for generating forecasts as an input to estimate distribution hosting capacity analysis, integrated resource planning, and load forecasting, and for understanding the economic or policy conditions in which DER adoption becomes viable, and for illustrating sensitivity to market and policy changes such as retail electricity rate structures, net energy metering, and technology costs.
Current cybersecurity challenges for distributed energy resources (DERs) stem from the integration of various systems and the cyber-physical security concerns they bring. Although frameworks exist for industrial control systems and other energy systems, a simple guided tool that can prioritize recommended actions for controls specific to DERs is lacking. Additionally, the novelty of the field has made it difficult to create a standardized procedure for DERs with cybersecurity in mind. In response to this critical need to address cybersecurity risk management, the National Renewable Energy Laboratory (NREL) has developed a framework and accompanying web application known as the Distributed Energy Resources Cybersecurity Framework (DERCF) (Powell, 2019). A brief overview of the DERCF can be found in Section 1.2. This document provides a guide to cybersecurity best practices identified by technical research and site visits where the framework was used to assess the cybersecurity posture of DER systems.
End-use electrical loads in residential and commercial buildings are evolving into flexible and cost-effective resources to improve electric grid reliability, reduce costs, and support increased hosting of distributed renewable generation. This article reviews the simulation of utility services delivered by buildings for the purpose of electric grid operational modeling. We consider services delivered to (1) the high-voltage bulk power system through the coordinated action of many, distributed building loads working together, and (2) targeted support provided to the operation of low-voltage electric distribution grids. Although an exhaustive exploration is not possible, we emphasize the ancillary services and voltage management buildings can provide and summarize the gaps in our ability to simulate them with traditional building energy modeling (BEM) tools, suggesting pathways for future research and development.
Advanced distribution management systems (ADMS) integrate multiple enterprise-level functions into a single platform and offer advanced applications such as fault location, isolation, and service restoration (FLISR), to utilities to meet their operational needs for a modernized grid. These applications need to operate reliably even as distributed energy resource (DER) penetration increases on distribution systems. The ADMS test bed at the National Renewable Energy Laboratory offers utilities and vendors the opportunity to evaluate the performance of such advanced applications on distribution feeders of the future and to understand their potential benefits for a specific utility. This is done through defining use cases that address specific questions. This paper presents the definition of a use case on the performance of a commercially-available FLISR application on a feeder of an electric cooperative with DERs. After experiments are completed, results from this use case will be disseminated to the electric utility and research community to improve understanding of the challenges and benefits that DERs present to ADMS applications and the operation of a modernized grid.
Power system dynamics will be significantly changed by integrating wind farms and solar photovoltaic plants into power systems. This study investigates the effect of momentary cessation of inverter-based resources (IBRs) on transient stability and provides a recovery strategy for bulk IBRs in power systems. The theoretical analysis was initially carried out on a one-machine infinite-bus system, demonstrating the IBR impact in a critical group. The analysis was then expanded to a multimachine power system with IBRs using the single-machine equivalent method. The study found that IBRs in critical and noncritical groups exert contrasting effects on transient stability. Finally, a strategy for enhancing transient stability is proposed by controlling IBRs during power system recovery. The proposed strategy was verified by simulation on IEEE 9-bus and IEEE 39-bus power systems with the addition of IBRs. A 39-bus power system simulation demonstrates the scalability of the proposed method. Here, the proposed strategy provides effective and executable measures for improving system security in the presence of IBRs.
An increasing rate of material consumption and a growing population mean that the Earth's supply of natural resources is witnessing an unsustainable and unprecedented demand. This forces us to find solutions that ensure the availability of resources for sustenance of our society in the years to come. Actors from various backgrounds are addressing these challenges from their own perspectives: engineers are developing efficient manufacturing processes, designers are creating lightweight and durable products, educators are incorporating sustainable thinking in their curricula, policymakers are finding interdisciplinary solutions that benefit society at large, etc. Circular economy (CE) is one such approach to resource use that aims to move away from the linear material use framework of "take-make-waste" to a more circular and interdependent system where product, material and resource use is maximized to avoid unnecessary social, economic, and environmental costs. The purpose of this report is to explain how to approach evaluating the circular economy and to help researchers identify existing tools that can be used or that can serve as starting points for their research needs.
Energy storage technologies—including pumped storage hydropower (PSH), batteries, and other technologies—have been technically proven to be capable of providing transmission services by regulating power flows and providing voltage support. These technologies will potentially increase the flexibility of transmission infrastructure and may defer (or eliminate) the need for transmission upgrades or new investments. On the regulatory side, Congress and the Federal Energy Regulatory Commission (FERC) have issued several orders over decades that have established energy storage’s (ES) eligibility as a transmission asset. The orders have required transmission planning entities to provide a level playing field where ES can participate in the transmission planning process (TPP) without undue discrimination and preference of technology. These developments pave the way for ES to participate in transmission planning as a transmission asset. On the other hand, as a flexible resource, ES can play an important role in the electricity market to enable more renewable energy integration by providing energy and grid reliability services. This could bring more revenue in return.
On June 28–29, 2021, the US Department of Energy’s (DOE’s) Advanced Scientific Computing Research (ASCR) program in the Office of Science convened a workshop with the Energy Efficiency and Renew able Energy (EERE) program offices to assess the future need for advanced computing resources in the areas of clean energy and advanced manufacturing. In part, this discussion served as an update to earlier workshops and townhalls. ASCR is guided by DOE mission needs as it develops research programs, computers, and networks at the leading edge of technologies. As the exascale computing era dawns, technology changes are creating new opportunities for those who must use high-performance computing (HPC) and data systems effectively. The ASCR computing facilities are augmenting their strategy to adapt to changing science needs and emerging technologies and to leverage the utility of exascale computing across the federal government.
Integrated transmission-and-distribution (T&D) modeling is a new and developing method for simulating power systems. Interest in integrated T&D modeling is driven by the changes taking place in power systems worldwide that are resulting in more decentralized power systems with increasingly high levels of distributed energy resources. Additionally, the increasing role of the hitherto passive energy consumer in the management and operation of power systems requires more capable and detailed integrated T&D modeling to understand the interactions between T&D systems. Although integrated T&D modeling has not yet found widespread commercial application, its potential for changing the decades-old power system modeling approaches has led to several research efforts in the last few years that tried to (i) develop algorithms and software for steady-state and dynamic modeling of power systems and (ii) demonstrate the advantages of this modeling approach compared with traditional, separated T&D system modeling. In this paper, we provide a review of integrated T&D modeling research efforts and the methods employed for steady-state and dynamic modeling of power systems. We also discuss our current research in integrated T&D modeling and the potential directions for future research. This paper should be useful for power systems researchers and industry members because it will provide them with a critical summary of current research efforts and the potential topics where research efforts are needed to further advance and demonstrate the utility of integrated T&D modeling.
NASA’s Prediction of Worldwide Energy Resource (POWER) project facilitates the use of NASA Earth Science data holdings within the renewable energy, agricultural, and building heating/cooling design industries. POWER packages solar and meteorological data at various temporal levels from several NASA projects in a user friendly GIS-enabled web services system (https://power.larc.nasa.gov). Data users can access these data either through an intuitive data viewer, image services fully integrable with GIS analysis, connections in the cloud through an Amazon Web Services S3 Bucket, or fully customizable access through an API. Data provided by POWER has been successfully used by decision makers to support actions that address climate change. For example, POWER data has been used to remotely monitor solar array fields and integrated in a sizing tool for off-grid solar and storage systems. POWER data has also been coupled with key building decision tools to support design and retrofitting of building energy systems for energy efficiency and reduction of greenhouse gases. POWER is now developing climate services to provide time series of the projected future evolution of key quantities that interest our users, such as heating/cooling degree days, temperature, wind speed, and downwelling solar flux. We demonstrate the potential of the new climate services by presenting here a range of possible future changes in these quantities at different NASA centers across the continental United States. These data services are based on downscaled climate model data from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) data set. We highlight the important insights that new climate services can provide. Our climate services will help our user communities quantify the impacts of climate change to support their key decisions in planning for the future, both inside and outside the Federal Government, especially for decisions in renewable energy and in building heating and cooling.
In a future with higher penetrations of variable and energy-limited resources, the dominant sources of resource adequacy risk begin to shift from (assumed) independent thermal unit outages to spatially- and temporally-correlated weather-driven phenomena. Traditional resource adequacy assessment and planning methods can be ill-suited to such scenarios. This presentation will highlight aspects of NREL's work in adapting and developing new probabilistic methods and tools in anticipation of the needs of the power system planning exercises of tomorrow.
Advanced distribution management systems (ADMS) integrate multiple enterprise-level functions into a single platform and offer advanced applications such as fault location, isolation, and service restoration (FLISR), to utilities to meet their operational needs for a modernized grid. These applications need to operate reliably even as distributed energy resource (DER) penetration increases on distribution systems. The ADMS test bed at the National Renewable Energy Laboratory offers utilities and vendors the opportunity to evaluate the performance of such advanced applications on distribution feeders of the future and to understand their potential benefits for a specific utility. This is done through defining use cases that address specific questions. This paper presents the definition of a use case on the performance of a commercially-available FLISR application on a feeder of an electric cooperative with DERs. Results from this use case will be disseminated to the electric utility and research community to improve understanding of the challenges and benefits that DERs present to ADMS applications and the operation of a modernized grid.
Technological changes across energy systems are forcing utilities and operators to reconsider their methods for managing power delivery, but few operators have adopted advanced controls and operational software. Their challenge is that every system has peculiar requirements, and the available solutions are relatively new, untested, and difficult to integrate into an operational environment. Through extensive collaboration with utilities and cooperatives, the National Renewable Energy Laboratory has realized the need for autonomous and optimized management of energy resources, leading to the development of Autonomous Energy Systems, a packaged set of controls that is ready to be integrated into existing control rooms.