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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Envisioning the Future Renewable and Resilient Energy Grids—A Power Grid Revolution Enabled by Renewables, Energy Storage, and Energy Electronics

Today’s power grids are facing tremendous challenges because of the ever-increasing power demand, system complexity, infrastructure cost, knowledge base, and policy and regulatory issues to achieve supply–demand power balance and resiliency with respect to more frequent extreme weather events and cyberattacks. It is particularly challenging when the transition toward 100% intermittent renewable energy sources is considered. Many countries are calling for building up more transmission and distribution lines to increase power delivery capacities. This article is an attempt to answer two urgent questions: Is more transmission and distribution infrastructure really needed to meet the increasing power demand? What kind of future grid infrastructure should we envision and build? This article attempts to answer these questions and proposes the concept of community-centric asynchronous renewable and resilient energy grids. By clearly differentiating the concepts of grid resilience and reliability, the importance of building resilient power electronics’ devices and robust system-level control algorithms to achieve 100% renewable energy integrated resilient grids is presented. To identify the shortcomings and propose advancements, power electronics’ technologies are categorized using the proposed concepts of natural source frequencies (NSf), energy storage, direct energy conversion/control and fault protection (DeCaFp), and high-efficiency energy consumption and buffering (heECaB) technology. The ability of networked microgrids to greatly reduce power outages and power system restoration time is demonstrated by leveraging robust decentralized and centralized control algorithms, identified through a comprehensive literature review. Future research areas are proposed to further enhance grid stability, controllability, cybersecurity, and protection against faults in the presence of 100% renewable sources by leveraging the advanced capabilities of NSf, DeCaFp, and heECaB devices and system-level control algorithms.

14 SOLAR ENERGY↗
DOE OSTI2024

Inaugural Symposium of the Institute for Sustainable Energy and Environment, Virginia Commonwealth University

The Inaugural Symposium of the Institute for Sustainable Energy and Environment (ISEE) was held in Virginia Commonwealth University, Richmond, Virginia during April 26 – 28, 2023. The symposium addressed issues and challenges in energy and environment and highlighted the use of clean renewable energy to mitigate the adverse effects of fossil fuels and the greenhouse gases it produces. These issues are complex as the involve educating the public that the climate change is real, it is caused by the use of fossil fuels, it requires scientists and engineers to understand the fundamental science in the production and storage of renewable energy, it requires industries to manufacture and distribute the equipment necessary for commercial application of these technologies, it requires policy makers to put together policies and guidelines to make the transition from fossil fuels to renewable energies efficient, and it requires social scientists and educators to address environmental justice issues and create a workforce to sustain the transition. The symposium considered all the above issues with a diverse list of speakers from the federal and state government, industrial partners, and experts from science and technology to social sciences and public policy. Speakers from the White House Office of Science and Technology Policy, Department of Energy, universities, and non-governmental agencies discussed the challenges and solutions in Plenary as well as Panel sessions. The talks were recorded with permission from the speakers and the panelists and were put in the ISEE website. The participants included students, postdoctoral fellows, and professors from Virginia Commonwealth University and local area Historically Black College and Universities (HBCU) such as Virginia State University and Norfolk State University. The $5000 fund awarded by the Department of Energy were used to support the participation of students, postdoctoral fellows, and faculty from the HBCU institutions. The technical program the list of participants is provided later in the document.

08 HYDROGEN↗
DOE OSTI2025

Hybrid Power Plants for Energy Resilience: A Case Study

As renewable energy technologies are increasingly adopted, they pose an opportunity to improve the sustainability and resilience of distributed grids, especially when their design and operation is coordinated as a hybrid power plant. When included in hybrid power plants, distributed wind turbines in particular have the potential to enhance the resilience of distributed grids in areas with good wind resource, due to their ability to provide more consistent generation and ancillary services as compared to photo-voltaic (PV) solar panels. Despite this benefit, U.S. distributed wind adoption is lower than other comparable renewable energy technologies. In this study, we seek to demonstrate how hybrid power plants that include distributed wind turbines can contribute to distribution grid resilience by meeting loads (especially critical loads) more consistently, increasing reserve capacity, and providing value to customers during outages. To demonstrate these contributions, we integrate three separate frameworks and apply them to a case study in a rural electric cooperative in Iowa. Through this case study, we simulate and compare hybrid power plant design and operation during two hazard events: a tornado that causes a 48-hour distribution outage and a winter weather event that causes a 6-hour generation outage. The inclusion of a hybrid power plant that leverages 1) increased battery duration and 2) advanced forecasting and dispatch strategies that reserve capacity leading up to a hazard event best reduce lost loads as well as diesel consumption that would otherwise be used to meet those loads during short- and long-duration hazard events. Depending on the hybrid power plant capacity and operation, we find that the outage mitigation value of a hybrid power plant (measured in value to customers to avoid an outage and avoided lost revenues for the utility) is significant in both hazard events; adding wind, solar, and battery assets to the existing system adds about $50-$100M in avoided lost load and at least $4-$8k in utility value in the tornado hazard event, and $570k-$2.2M in avoided lost load and at least $220-$650 in utility value in the winter hazard scenario. In both the tornado and winter hazard scenarios, optimizing the operation of the hybrid system for resilience can lend similar value as increasing battery duration by 5 MWh for the lower capacity systems considered.

17 WIND ENERGY↗
DOE OSTI2025

An Integrated Paradigm for the Management of Delivery Risk in Electricity Markets: From Batteries to Insurance and Beyond

If power systems transition to integrate higher amounts of variable renewable energy sources, storage technologies, and distributed energy resources (DERs), new risk management frameworks are necessary to ensure cost-effective and reliable power system operations. Projects funded by the Advanced Research Projects Agency-Energy (ARPA-E) Performance-based Energy Resource Feedback, Optimization, and Risk Management (PERFORM) program aim to contribute new risk management frameworks by developing methods to quantify and manage risk at grid asset and system levels. The National Renewable Energy Laboratory (NREL) led a PERFORM project in collaboration with the Johns Hopkins University, the Electric Power Research Institute (EPRI), kWh Analytics, Packetized Energy, and Imperial Consultants (ICON). The project addressed two challenges related to risk management in electricity markets: managing net load imbalances and flexibility from DERs. This final technical report presents a list of project accomplishments, activities, and outputs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Cloud-based Testbed for Adaptive Under-Frequency Load Shedding with High DER Penetration

Increasing penetration of distributed energy resources and behind-the-meter renewables may soon disrupt the efficacy of critical protection schemes, such as under-frequency load shedding (UFLS). Improved data exchange and coordination across the transmission-distribution boundary will be required to maintain reliability of bulk electric system. Standards-based data integration platforms using agreed-upon semantic vocabularies, such as the Common Information Model, will be key to enabling adaptive protection schemes requiring synthesized data from both the bulk power system and behind-the-meter resources. This paper introduces a cloud-based open-source data integration environment and UFLS clustering algorithm being developed to enable adaptive relay coordination between transmission and distribution utilities in the state of Vermont.

Anderson, Alexander A.↗
DOE OSTI2020

A Hybrid Stochastic-Interval Operation Strategy for Multi-Energy Microgrids

Increasing deployment of distributed energy resources intensifies interactions among electric, gas, heating, and cooling systems. Inherent uncertainties ranging from internal parameters to external inputs also impose significant challenges on system operation. A coordinated scheduling method is, therefore, desired for facilitating efficient operation of multi-energy microgrids under multiple uncertainties. In this paper, a deterministic coordinated scheduling model is developed first with detailed modeling of system dynamics and device parameters to fully characterize complex interactions among multi-energy carriers. Then, a hybrid stochastic-interval method is proposed to account for heterogeneous uncertainties in decisions of operational strategies. Specifically, performance and efficiency uncertainties of distributed energy resources, and injection uncertainty of renewable sources and multienergy demands are characterized by interval-based uncertain operation regions and probability distributions, respectively. A scenario-based two-stage algorithm is developed to solve the problem so that multiple uncertainties are preserved in the entire decision-making process. Moreover, adjustable operational strategies are determined to hedge uncertainty by considering operators’ risk preferences. The validity of the proposed method is verified by comprehensive case studies on a test system.

hybrid stochastic-interval approach↗
DOE OSTI2023

Integration of DER Adoption Forecasting into Distribution Planning: Cooperative Research and Development Final Report, CRADA Number CRD-11-00430 (Project H)

The objective of this project is to improve distributed energy resources (DER) technology, time, and locational impact analysis by incorporating customer adoption intentions and preferences into distribution planning and operations. The National Renewable Energy Laboratory (NREL) shall collaborate with EPRI staff to contribute to the development of methodology, literature review, analysis, and write-up for two sections of a report "Identification and Overview of Methods for Mapping DER Adoption Forecasts” and “Comparative Analysis of Methods for Mapping DER Adoption Forecasts."

14 SOLAR ENERGY↗
DOE OSTI2021

Automation for Distributed Energy Resources Risk Manager Using OSCAL

The risk management framework (RMF) provides a well-organized and thorough approach to diagnose information technology (IT) system threats, to gather required materials to comply with industry standards, and to document a plan for achieving authority to operate (ATO). ATO is given by the operating authority with the awareness of vulnerabilities that arise when operating the IT system. The primary goal of the National Renewable Energy Laboratory’s (NREL’s) distributed energy resource (DER) RM application is to provide a user-friendly interface and in-depth guidance for generating the authorization package for the authorizing official to review. In other words, the application satisfies steps 1 through 7 of the RMF process with a focus on DERs.

cybersecurity↗
DOE OSTI2024

Short-term Electricity Price Forecasting with Constrained Regressors

The volatility of electricity price presents a challenge to market participants as their decision-making process are highly depend on the accuracy of price forecasts. However, there is growing empirical evidence of increasing price volatility and price spikes in electricity markets as a result of variable renewable energy generation, extreme weather events, and other factors. The distribution shift caused by spikes in electricity price data differentiates the forecasting tasks from other renewable energy sources. Moreover, the observations may be compromised by cyberattacks and thus not available in the testing phase. To this end, we propose a Similarity-Enhanced Electricity Decomposition Forecasting model (SEED-Forecaster) to address the missing response problem and spikes capturing in short-term electricity price forecasting. The effectiveness of the proposed framework is tested on real-world electricity price data from California Independent System Operator (CAISO). Numerical results of case studies show that the proposed SEED-Forecsater can enhance forecasting performance, particularly in capturing electricity spikes, even under conditions without regressors during testing stage.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Forecasting Commercial Building Electricity Consumption, Zone Airflow and Zone Temperature: Update - Development of a Generalized Machine Learning Approach

The U.S. power grid is being transformed to make it smarter, more efficient, and cleaner. This transformation is leading to the addition of a significant of energy generated by distributed, variable, and renewable resources. Because of the variable nature of renewable generation, the short- and long-term supply and demand imbalances are less predictable, and conventional approaches to mitigating the imbalances will be less efficient or cost effective. To address this challenge and to support the mission and the vision of the U.S. Department of Energy’s (DOE’s) Office of Energy Efficiency and Renewable Energy (EERE) Building Technologies Office has developed a Grid-Interactive Efficient Building Strategy. The strategy focuses on simultaneously improving building energy efficiency and supporting reliability and resilience of the electric grid more efficiently and at a lower cost. In addition, EERE and DOE’s Office of Electricity created an initiative led by DOE and supported by the national laboratories under the Grid Modernization Lab Consortium structure to enhance grid modernization. The work reported in this document is part of the first set of projects funded under the initiative to design, develop, and validate scalable transactive control technologies for the commercial buildings sector. Transactive controls requires the ability of individual end-use loads to express flexibility as a function of a transactive signal (e.g., price). Empirical grey- and black-box models have been widely used to express flexibility. Although this approach is generally easy to construct and simple to use, it does not capture non-linear behavior that some end-use loads represent. Therefore, Pacific Northwest National Laboratory (PNNL) with support from Western Washington University conducted this research to explore the use of deep machine learning (ML) techniques. The work reported in this document is limited to forecasting whole building electricity consumption, the zone airflow and the zone temperature predictions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Thermal Modeling and Simulation of the Packed-bed Thermal Energy Storage Combined with INL Thermal Energy Distribution System

Dynamic Energy Transport and Integration Lab (DETAIL) at Idaho National Laboratory is to support experimental demonstration and validation research on Nuclear-Renewable Hybrid Energy System [1]. The Thermal Energy Distribution System (TEDS) is a thermal-hydraulic flow loop in DETAIL with its own dedicated control system to support the integration of co-located multiple experimental systems, where a packed-bed thermal energy storage (TES) is installed as a thermal buffer and storage unit. Among various TES options, the packed-bed TES is adopted in TEDS because it offers a low-cost single-tank thermal storage option compared to the traditional two-tank TES. However, since the TES tank is filled with granular fillers having different thermophysical properties from those of TES tank wall, there is a potential thermo-mechanical issue to be carefully addressed like thermal ratcheting which may pose a significant design concern for the packed-bed TES tank. Thermal ratcheting is a thermomechanical process caused by the repeated rearrangement of granular filler inside a TES tank during continuous thermal cycling operation of the packed-bed TES system. If the thermally induced stress exceeds the yield strength of a TES tank wall, catastrophic consequences may happen like rupture of the TES tank. Thus, it is important to understand the phenomenon to ensure the robust operation of the packed-bed TES tank. Given that thermal ratcheting is caused by complex interaction of thermal transport in the porous bed and solid mechanics, the accurate prediction of transient thermal behavior of the packed-bed TES tank, which is the focus of this paper, is critical to the reliable thermal ratcheting analysis. This paper discusses the numerical modeling, simulation, and validation studies that are ongoing at INL to investigate the transient thermal behavior of the packed-bed TES. Of particular concern is the transient thermal process occurring in the packed-bed TES unit that is operated in conjunction with the INL TEDS. The main goal of this research is three-fold: (i) provide preliminary insights into the transient thermal behavior of the TEDS TES tank, (ii) support the thermal measurement and validation plan for TEDS experiment, and (iii) provide transient thermal boundary conditions to support the reliable thermal ratcheting analysis of the TEDS TES tank. For the transient thermal modeling and analysis, a CFD model was developed, and the validity of the modeling approach was examined via comparing the numerical simulation results with the experimental data obtained from various design characteristics of packed-bed TES tanks. Then, the present modeling method was applied for the transient thermal analysis of the TEDS TES tank, and the results are discussed along with the potential improvement of data acquisition strategy for the future TEDS experiments for more precise validation study.

25 ENERGY STORAGE↗
DOE OSTI2022

Renewables, Resource Adequacy, and Reliability

Presentation to the Legislative Energy Horizons Institute on grid reliability and renewable integration, including resource adequacy, flexibility, and distributed energy resource considerations.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗
DOE OSTI2022

Hexagonal Distributed Embedded Energy Converters (HexDEECs)

The HexDEEC is a small, characteristic length approximating a centimeter, energy transducer that converts the dynamic deformations of its elastomer housing into electricity through a variable capacitance charging-discharging cycle. This device is a type of Distributed Embedded Energy Converter Technology (DEEC-Tec), a new domain for marine renewable energy research that utilizes a conglomeration of small distributed embedded energy converters (DEECs) that, in aggregate, form larger metamaterial frameworks. These resulting DEEC-Tec metamaterials can then, in turn, be used to construct flexible ocean wave energy converters called flexWECs, which can utilize a broad band of ocean wave frequencies and lack highly loaded rigid bodies. These systems also provide new avenues of wave energy harvesting such as actively transforming topologies (e.g., shape and form) and morphologies (e.g., stiffness and damping throughout its entire structure) in real time. Presented, is one specific type of DEEC: the HexDEEC, which is currently being developed by the United States National Renewable Energy Laboratory. This transducer shows promise in aiding the adoption and further development of the DEEC-Tec domain. The following presentation focuses on the promise of this technology and current work being done to analyze the performance of an individual HexDEEC design. The HexDEEC is composed of a hyperelastic hexagonal housing, nominally silicon rubber, with six electrodes on its inner faces. The upper three electrodes share the same charge while the lower three electrodes oppose the upper electrode charges. Externally, the HexDEEC has two arms extending away from the middle vertices of the hexagon. Via principles governing the relationship between electrical capacitance and electrical potential (voltage and charge), electricity is generated when the HexDEEC's arms are dynamically pulled or released under tensile loading, as doing so causes the distance between the upper and lower sets of electrodes to change - varying the energy converter's overall capacitance. Analytical and numerical modeling is being used to evaluate the mechanics and electrical energy generated by the HexDEEC. Equations to describe the capacitance and electrostatic forces acting on this unique system have been developed and implemented into the numerical modeling software STAR-CCM+, along with models to describe its hyperelastic material, such as the Mooney-Rivlin 3-parameter model. So far, an initial design has been analyzed and we plan to further optimize it to increase power production. Individual HexDEECs have been fabricated by drawing uncured liquid silicon rubber into molds via vacuum pressure. To simplify manufacturing, HexDEEC sub-components - e.g., electrodes, wires - can be placed within those molds such that they are directly embedded into the hexagonal housing during the curing process. Furthermore, DEEC-Tec metamaterials can be created by interweaving or sequentially layering multiple HexDEEC strands together. The HexDEEC based metamaterial could then generate electricity through its gross deformations. Ultimately, HexDEECs represent a specific type of energy transducer that can be leveraged, by the DEEC-Tec domain, to create metamaterials used to construct novel flexWECs.

DEEC-Tec↗
DOE OSTI2025

Pricing Strategy of Electric Vehicle Aggregators Based on Locational Marginal Price to Minimize Photovoltaic (PV) Curtailment

The global climate crisis demands urgent action to mitigate global warming. Using renewable energy sources, such as solar and wind power, for electricity generation is crucial. This shift from centralized to distributed power systems, however, brings challenges, including voltage fluctuations and renewable energy curtailment. The rapid growth of the electric vehicle (EV) industry adds complexity, increasing overall electricity demand and straining the power supply during peak charging times. This paper proposes a scheduling strategy for EV aggregators to reduce renewable energy curtailment and stabilize grid operation by strategically scheduling EV charging. Using Multi -Agent Transport Simulation (MATSim), a traffic simulation tool, EV driving data in Denver, Colorado, USA, were modeled. The EV aggregator adjusts charging fees based on locational marginal prices, encouraging EVs to charge at different stations according to pricing. Simulations on an IEEE 33-bus system with distributed energy resources and EV charging stations validate the proposed algorithm, demonstrating its effectiveness in reducing curtailment by 12.55% and stabilizing grid operation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

ESPC ESA Training Series: Site-Specific/Stand-Alone Contract Vehicle

This webinar provides instructions and resources for financing distributed energy projects (e.g., on–site renewable energy, storage, and combined heat and power) using an energy savings performance contract (ESPC) energy sales agreement (ESA) through the site–specific/stand–alone contract vehicle. The site–specific/stand–alone contract vehicle is a procurement process using a request for proposal (RFP). Topics covered during the webinar include forming a strong project team, validating the feasibility of the distributed energy project at a site, acquisition planning, RFP development, procurement, proposal evaluation and contract award, and the construction and performance period. This webinar also provides an overview of the resources available in the ESPC ESA Toolkit, such as checklists and templates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Hexagonal Distributed Embedded Energy Converters (HexDEECs)

Distributed Embedded Energy Converter Technologies (DEEC-Tec) is a new domain for marine renewable energy research that utilizes a conglomeration of small distributed embedded energy converters (DEECs) that, in aggregate, form larger metamaterial frameworks. These resulting DEEC-Tec metamaterials can then, in turn, be used to construct flexible ocean wave energy converters called flexWECs. DEEC-Tec enables flexWECs: (i) to be inherently broad-banded ocean wave frequency energy converters and (ii) to have an inherent lack of highly loaded rigid bodies. The DEEC-Tec domain also benefits the marine renewable energy domain by inherently availing ways that marine energy can be harvested and converted that heretofore has not yet been considered possible: real-time execution of transforming topologies (e.g., actively changing a flexWEC's shape and form) and morphologies (e.g., actively changing a flexWEC's stiffness and damping throughout its entire structure). Presented, is one specific type of DEEC, a HexDEEC, that shows promise in aiding the adoption and further development of the DEEC-Tec domain - it is a small energy transducer being developed by the United States National Renewable Energy Laboratory. The HexDEEC is a small (characteristic length approximating a centimeter) energy transducer that converts the dynamic deformations of an elastomer into electricity through a charging-discharging cycle of a capacitor whose capacitance is varied by those elastic deformations. The HexDEEC is composed of a hyperelastic hexagonal housing (nominally silicon rubber) with six electrodes on its inner faces. The upper three electrodes share the same charge while the lower three electrodes oppose the upper electrode charges. Externally, the HexDEEC has two arms extending away from the middle vertices of the hexagon. Via principles governing the relationship between electrical capacitance and electrical potential (voltage and charge), electricity is generated when the HexDEEC's arms are dynamically pulled or released under tensile loading as doing so causes the distance between the upper and lower sets of electrodes to change - varying the energy converter's overall capacitance. Analytical and numerical modeling have already been used to estimate the electrical energy produced by a HexDEEC. The cursory models approximate the HexDEEC as a parallel plate variable capacitor - simplifying from six to two opposing plates with a constant dielectric volume between those two plates. To account for the elastic HexDEEC material properties, software such as SolidWorks and STAR-CCM+ have been used to generate hyperelastic models; notably, Mooney-Rivlin based models. Individual HexDEECs have been fabricated by drawing uncured liquid silicon rubber into molds via vacuum pressure. To simplify manufacturing, HexDEEC sub-components - e.g., electrodes, wires - can be placed within those molds such that they are directly embedded into the hexagonal housing during the curing process. Furthermore, DEEC-Tec metamaterials can be created by interweaving or sequentially layering multiple HexDEEC strands together. The HexDEEC based metamaterial could then generate electricity through its gross deformations. Ultimately, HexDEECs represent a specific type of energy transducer that can be leveraged, by the DEEC-Tec domain, to create metamaterials used to construct novel flexWECs.

DEEC-Tec↗
DOE OSTI2025

Using Artificial Intelligence to Improve Reliability and Operational Efficiency of Small-Scale Hydroelectric Distributed Generation

Reliability and resilience are critical concerns for distributed generation (DG) at the rural electric level. The integration of renewable energy sources, such as small-scale hydroelectric distributed generators (hydro DGs), introduces operational challenges, particularly regarding aging infrastructure and grid stability. Artificial Intelligence (AI)-driven Machine Learning (ML) models and applications of Large Language Models (LLMs) offer promising solutions for optimizing DG operations and enhancing resilience. This paper explores AI-based models for improving efficiency, fault resolution, and outage mitigation in small-scale hydro DGs. Furthermore, it highlights the development of a centralized, AI-powered information portal for rural electric cooperatives and municipalities. The research evaluates hydro DG plant models and discusses the applicability of AI-powered question-answering tools for real-time operations, focusing on statistical data, load flow, voltage regulation, and generation power. The findings demonstrate AI’s potential to transform DG management to ensure greater stability and resilience in rural electric grids.

Bhattacharyya, Arjun [ORNL] (ORCID:000900060976046↗
DOE OSTI2022

Applying the Risk Management Framework: The Distributed Energy Resource Risk Manager

As part of a multiyear effort, the National Renewable Energy Laboratory (NREL) has dedicated resources to understand and identify cybersecurity weaknesses in distributed energy resources (DERs) by performing assessments. Due to a lack of standardization and rapidly increasing adoption of DERs, there is a critical need to address cybersecurity needs for DER systems in an interactive way. Furthermore, federal agencies, which are required to obtain an authority to operate, are challenged by the complexities of including their DERs. To help meet this need, in early 2020, NREL released the Distributed Energy Resources Cybersecurity Framework (DERCF) and accompanying Web application. This process is supported by the Risk Management Framework (RMF) developed by the National Institute of Standards and Technology. This project, referred to as the DERCF RMF application, expands on the existing DERCF work to include methods that support walking a user through the seven RMF steps. The tool will be available for download at no cost from [link ]. The purpose of this paper is to describe the steps the DERCF team at NREL took to understand Steps 1-5 of the RMF process. Additionally, this document will identify future work on the first five steps as well as a plan for Steps 6 and 7.

24 POWER TRANSMISSION AND DISTRIBUTION↗