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DOE OSTI2025

Basin-Scale Structural Features Database: Spatial Datasets to Support Carbon Storage Resource Assessments

Presentation slides on "Basin-Scale Structural Features Database: Spatial Datasets to Support Carbon Storage Resource Assessments" for CCUS 2025 Annual Meeting. The Basin-Scale Structural Features database contains a series of basin-scale spatial datasets representing structural features, including faults, fractures, folds, and earthquakes. Designed to support carbon storage feasibility and resources assessments for Carbon Capture and Storage (CCS) projects, the database leverages publicly available data resources from authoritative sources (e.g. US Geological Survey, State Geologic Surveys), and aims to help users better understand basin-scale structural features, as well as potential data gaps in areas with sparse information.

basin scale↗

DOE OSTI2017

Evaluation of the National Solar Radiation Database (NSRDB): 1998-2015

This paper validates the performance of the physics-based Physical Solar Model (PSM) data set in the National Solar Radiation Data Base (NSRDB) to quantify the accuracy of the magnitude and the spatial and temporal variability of the solar radiation data. Achieving higher penetrations of solar energy on the electric grid and reducing integration costs requires accurate knowledge of the available solar resource. Understanding the impacts of clouds and other meteorological constituents on the solar resource and quantifying intra-/inter-hour, seasonal, and interannual variability are essential for accurately designing utility-scale solar energy projects. Solar resource information can be obtained from ground-based measurement stations and/or from modeled data sets. The availability of measurements is scarce, both temporally and spatially, because it is expensive to maintain a high-density solar radiation measurement network that collects good quality data for long periods of time. On the other hand, high temporal and spatial resolution gridded satellite data can be used to estimate surface radiation for long periods of time and is extremely useful for solar energy development. Because of the advantages of satellite-based solar resource assessment, the National Renewable Energy Laboratory developed the PSM. The PSM produced gridded solar irradiance -- global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance -- for the NSRDB at a 4-km by 4-km spatial resolution and half-hourly temporal resolution covering the 18 years from 1998-2015. The NSRDB also contains additional ancillary meteorological data sets, such as temperature, relative humidity, surface pressure, dew point, and wind speed. Details of the model and data are available at https://nsrdb.nrel.gov. The results described in this paper show that the hourly-averaged satellite-derived data have a systematic (bias) error of approximately +5% for GHI and less than +10% for DNI; however, the scatter (root mean square error [RMSE]) difference is higher for the hourly averages.

14 SOLAR ENERGY↗

DOE OSTI2017

Evaluation of the National Solar Radiation Database (NSRDB): 1998-2015

14 SOLAR ENERGY↗

DOE OSTI2015

The diverse use of clouds by CMS

The resources CMS is using are increasingly being offered as clouds. In Run 2 of the LHC the majority of CMS CERN resources, both in Meyrin and at the Wigner Computing Centre, will be presented as cloud resources on which CMS will have to build its own infrastructure. This infrastructure will need to run all of the CMS workflows including: Tier 0, production and user analysis. In addition, the CMS High Level Trigger will provide a compute resource comparable in scale to the total offered by the CMS Tier 1 sites, when it is not running as part of the trigger system. During these periods a cloud infrastructure will be overlaid on this resource, making it accessible for general CMS use. Finally, CMS is starting to utilise cloud resources being offered by individual institutes and is gaining experience to facilitate the use of opportunistically available cloud resources. Lastly, we present a snap shot of this infrastructure and its operation at the time of the CHEP2015 conference.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Wind Energy Forecasting with the Weather Research and Forecasting Model

This was a collaborative effort between Lawrence Livermore National Security, LLC as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Siemens Energy, Inc. (Siemens) to develop a wind resource forecasting tool. LLNL was to develop an independent high-resolution mesoscale modeling capability forecasting tool that could be implemented in conjunction with existing wind farm control and monitoring software to provide forecasting of wind resources using local observations of winds and temperature. Research with LLNL’s state-of-the-art large-eddy simulation meteorological prediction model, based on the community WRF model and innovative turbulence parameterizations, would improve that model’s applicability to large wind farms offshore and in complex terrain. The modeling capability would include uncertainty quantification. Finally, the application of the modeling tool and existing global climate change predictions would enable the delineation of the likely effects of climate change on wind resources. Siemens was to provide high time resolution hub-height wind speed and other meteorological data streams, including temperature profiles from wind farms, for LLNL to incorporate into the modeling system, to validate and tune this forecasting model for their locations of interest. These data streams would also be used for longer-term studies of correlations of wind resources to climate oscillations to indicate how long-term climate change trends may affect the available wind resource. Siemens would also provide information and observations of turbine wakes for incorporation into the modeling tool. By implementing state-of-the-art turbulence parameterizations into a simulation model and/or ensembles of simulation models, and by integrating real-time hub height wind speed and other meteorological datastreams from wind farms into that model or ensemble of models, LLNL would develop a forecasting tool that could be implemented by Siemens as an add-on to existing wind farm control and monitoring software to provide owners with useful resource forecasting. The desired outcome was that the accuracy level of the output would be sufficient to substantiate power output commitments. The final deliverable for this work would consist of a document outlining the algorithms and software tools that could be integrated into Siemens Wind Park Supervisor.

17 WIND ENERGY↗

DOE OSTI2022

Mapping the Opportunity Space to Model the Circular Economy Using Tools Funded by the DOE Office of Energy Efficiency and Renewable Energy

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.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2012

GIS-and Web-based Water Resource Geospatial Infrastructure for Oil Shale Development

The Colorado School of Mines (CSM) was awarded a grant by the National Energy Technology Laboratory (NETL), Department of Energy (DOE) to conduct a research project en- titled GIS- and Web-based Water Resource Geospatial Infrastructure for Oil Shale Development in October of 2008. The ultimate goal of this research project is to develop a water resource geo-spatial infrastructure that serves as “baseline data” for creating solutions on water resource management and for supporting decisions making on oil shale resource development. The project came to the end on September 30, 2012. This final project report will report the key findings from the project activity, major accomplishments, and expected impacts of the research. At meantime, the gamma version (also known as Version 4.0) of the geodatabase as well as other various deliverables stored on digital storage media will be send to the program manager at NETL, DOE via express mail. The key findings from the project activity include the quantitative spatial and temporal distribution of the water resource throughout the Piceance Basin, water consumption with respect to oil shale production, and data gaps identified. Major accomplishments of this project include the creation of a relational geodatabase, automated data processing scripts (Matlab) for database link with surface water and geological model, ArcGIS Model for hydrogeologic data processing for groundwater model input, a 3D geological model, surface water/groundwater models, energy resource development systems model, as well as a web-based geo-spatial infrastructure for data exploration, visualization and dissemination. This research will have broad impacts of the devel- opment of the oil shale resources in the US. The geodatabase provides a “baseline” data for fur- ther study of the oil shale development and identification of further data collection needs. The 3D geological model provides better understanding through data interpolation and visualization techniques of the Piceance Basin structure spatial distribution of the oil shale resources. The sur- face water/groundwater models quantify the water shortage and better understanding the spatial distribution of the available water resources. The energy resource development systems model reveals the phase shift of water usage and the oil shale production, which will facilitate better planning for oil shale development. Detailed descriptions about the key findings from the project activity, major accomplishments, and expected impacts of the research will be given in the sec- tion of “ACCOMPLISHMENTS, RESULTS, AND DISCUSSION” of this report.

04 OIL SHALES AND TAR SANDS↗

DOE OSTI2019

Critical Load Restoration using Distributed Energy Resources for Resilient Power Distribution System

Extreme weather events have a significant impact on the aging and outdated power distribution infrastructures. These high-impact low-probability (HILP) events often result in extended outages and loss of critical services, thus, severely affecting customers' safety. This calls for the need to ensure resilience in distribution networks by quickly restoring the critical services during a disaster. This paper presents an advanced feeder restoration method to restore critical loads using distributed energy resources (DERs). A resilient restoration approach is proposed that jointly maximizes the amount of restored critical loads and optimizes the restoration times by optimally allocating grid's available DER resources. The restoration problem is modeled as a mixed-integer linear program with the objective of maximizing the resilience to post-restoration failures while simultaneously satisfying grid's critical connectivity and operational constraints and ensuring a radial operation for a given open-loop feeder configuration. Simulations are performed to demonstrate the effectiveness of the proposed approach using IEEE 123-node feeder with 5 DERs supplying 11 critical loads and IEEE 906-bus feeder with 3 DERs supplying 17 critical loads. The impacts of DER availability and fuel reserve on restored networks are assessed and it is shown that the proposed approach is successfully able to restore a maximum number of critical loads using available DERs.

resilience, microgrids, reactive power, energy res↗

DOE OSTI2023

Control coordination in inverter‐based microgrids using AoI‐based 5G schedulers

Abstract A coordinated set point automatic adjustment with correction enabled (C‐SPAACE) framework that uses 5G communication for real‐time control coordination between inverter‐based resources (IBR) in microgrids is proposed. Utilising slicing capability, 5G offers low‐latency communication to C‐SPAACE under normal conditions. However, given the multitude of power grid use cases, a certain 5G slice for C‐SPAACE may have access only to limited radio spectrum resources, which if not managed well, greatly undermines the communication needs of C‐SPAACE framework. Thus, optimally scheduling the available spectrum resources among IBRs in a sliced 5G network‐based C‐SPAACE framework becomes a critical problem. To address this issue, the authors utilise a novel age of information (AoI) metric and designs an AoI‐based 5G scheduler to provide low‐latency communication to C‐SPAACE. Following this, a co‐simulation environment is designed using PSCAD/EMTDC and Python to simulate a microgrid supported by 5G communication. Time‐domain simulation case studies are performed using the proposed co‐simulation environment to evaluate the performance of C‐SPAACE using 5G with both AoI‐based and other baseline (non‐AoI) schedulers.

Choudhury, Biplav↗

DOE OSTI2013

Nuclear power fleets and uranium resources recovered from phosphates

Current light water reactors (LWR) burn fissile uranium, whereas some future reactors, as Sodium fast reactors (SFR) will be capable of recycling their own plutonium and already-extracted depleted uranium. This makes them a feasible solution for the sustainable development of nuclear energy. Nonetheless, a sufficient quantity of plutonium is needed to start up an SFR, with the plutonium already being produced in light water reactors. The availability of natural uranium therefore has a direct impact on the capacity of the reactors (both LWR and SFR) that we can build. It is therefore important to have an accurate estimate of the available uranium resources in order to plan for the world's future nuclear reactor fleet. This paper discusses the correspondence between the resources (uranium and plutonium) and the nuclear power demand. Sodium fast reactors will be built in line with the availability of plutonium, including fast breeders when necessary. Different assumptions on the global uranium resources are taken into consideration. The largely quoted estimate of 22 Mt of uranium recovered for phosphate rocks can be seriously downscaled. Based on our current knowledge of phosphate resources, 4 Mt of recoverable uranium already seems to be an upper bound value. The impact of the downscaled estimate on the deployment of a nuclear fleet is assessed accordingly. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2018

Stochastic Programming Approach for Resource Selection under Demand Uncertainty

Cost-efficient selection and scheduling of a subset of geographically distributed resources to meet the demands of a scientific workflow is a challenging problem. The problem is exacerbated by uncertainties in demand and availability of resources. In this paper, we present a stochastic optimization based framework for robust decision making in the selection of distributed resources over a planning horizon under demand uncertainty. We present a novel two-stage stochastic programming model for resource selection, and implement an L-shaped decomposition algorithm to solve this model. A Sample Average Approximation algorithm is integrated to enable stochastic optimization to solve problems with a large number of scenarios. Using the metric of stochastic solution, we demonstrate up to 30% cost reduction relative to solutions without explicit consideration of demand uncertainty for a 24-month problem. We also demonstrate up to 54% cost reduction relative to a previously developed solution for a 36-month problem. We further argue that the composition of resources selected is superior to solutions computed without explicit consideration of uncertainties. Given the importance of resource selection and scheduling of complex scientific workflows, especially in the context of commercial cloud computing, we believe that our novel stochastic programming framework will benefit many researchers as well as users of distributed computing resources.

scientific workflows, task scheduling, optimizatio↗

DOE OSTI2024

Resources, Training, and Education Under the Heliostat Consortium: Industry Gap Analysis and Building a Resource Database

Concentrating solar power is not a widely deployed or known technology area, and the heliostat workforce community in the United States is currently small, with knowledge and expertise not widely available. The resource, training, and education (RTE) topic within the Heliostat Consortium (HelioCon) was established to address this. RTE encompasses resources, practices, and programs to ensure that (1) newcomers to the heliostat development community have an adequate knowledge base and training to conduct R&D efforts, (2) outsiders to the field are provided with resources and opportunities to join the workforce, and (3) the workforce community is a productive, healthy, and fulfilling environment for all workers. In the first year of the project, a roadmap study was conducted, in which the major gaps in RTE were identified by consulting experts in the industry, with the top gap being the lack of public accessibility to concentrating solar-thermal power (CSP) knowledge. Here, to address this, the HelioCon team has been developing a centralized web-based resource database, containing a reference library, educational videos, lists of components suppliers and software/metrology tools, a power tower plant database, and information on existing standards/guidelines.

14 SOLAR ENERGY↗

DOE OSTI2015

Adsorbent Alkali Conditioning for Uranium Adsorption from Seawater. Adsorbent Performance and Technology Cost Evaluation

The Fuel Resources program of the Fuel Cycle Research and Development program of the Office of Nuclear Energy (NE) is focused on identifying and implementing actions to assure that nuclear fuel resources are available in the United States. An immense source of uranium is seawater, which contains an estimated amount of 4.5 billion tonnes of dissolved uranium. This unconventional resource can provide a price cap and ensure centuries of uranium supply for future nuclear energy production. NE initiated a multidisciplinary program with participants from national laboratories, universities, and research institutes to enable technical breakthroughs related to uranium recovery from seawater. The goal is to develop advanced adsorbents to reduce the seawater uranium recovery technology cost and uncertainties. Under this program, Oak Ridge National Laboratory (ORNL) has developed a new amidoxime-based adsorbent of high surface area, which tripled the uranium capacity of leading Japanese adsorbents. Parallel efforts have been focused on the optimization of the physicochemical and operating parameters used during the preparation of the adsorbent for deployment. A set of parameters that need to be optimized are related to the conditioning of the adsorbent with alkali solution, which is necessary prior to adsorbent deployment. Previous work indicated that alkali-conditioning parameters significantly affect the adsorbent performance. Initiated in 2014, this study had as a goal to determine optimal parameters such as base type and concentration, temperature, and duration of conditioning that maximize the uranium adsorption performance of amidoxime functionalized adsorbent, while keeping the cost of uranium production low. After base-treatment at various conditions, samples of adsorbent developed at ORNL were tested in this study with batch simulated seawater solution of 8-ppm uranium concentration, batch seawater spiked with uranium nitrate at 75-100 ppb uranium, and continuous-flow natural seawater at the Pacific Northwest National Laboratory (PNNL). Fourier Transform Infrared (FTIR) spectroscopy, Nuclear Magnetic Resonance (NMR) spectroscopy, Scanning Electron Microscopy (SEM), and elemental analysis were used to characterize the adsorbent at different stages of adsorbent preparation and treatment. The study can be divided into two parts: (A) investigation of optimal parameters for KOH adsorbent conditioning and (B) investigation of other possible agents for alkali conditioning, including cost analysis on the basis of uranium production. In the first part of the study, tests with simulated seawater containing 8 ppm uranium showed that the uranium adsorption capacity increased with an increase in the KOH concentration and conditioning time and temperature at each of the KOH concentrations used. FTIR and solid state NMR studies indicated that KOH conditioning converts the amidoxime functional groups into more hydrophilic carboxylate. The longer the KOH conditioning time, up to three hours, the higher was the loading capacity from the simulated seawater solution which is composed of only uranyl, sodium, chloride, and carbonate ions. Marine testing with natural seawater, on the other hand, showed that the uranium adsorption capacity of the adsorbent increased with KOH conditioning temperature, and gradually decreased with increasing KOH conditioning time from one hour to three hours at 80 C. This behavior is due to the conversion of amidoxime to carboxylate. The carboxylate groups are needed to increase the hydrophilicity of the adsorbent; however, conversion of a significant amount of amidoxime to carboxylate leads to loss in selectivity toward uranyl ions. Thus, there is an optimum KOH conditioning time for each temperature at which an optimum ratio between amidoxime and carboxylate is reached. For the case of base conditioning with 0.44 M KOH at 80 C, the optimal conditioning time is 1 hour, with respect to the highest uranium loading capacity from natural seawater. Uptake of other metal ions such as V, Fe, and Cu follows the same trend as that of uranium. Also, the uptake of Ca, Mg, and Zn ions increased with increasing KOH conditioning time, probably due to formation of more carboxylates, which leads to conversion of uranium-selective binding sites to less selective sites. In the second part of the study, inorganic based reagents such as sodium hydroxide (NaOH), sodium carbonate (Na 2 CO 3 ), cesium hydroxide (CsOH), as well as organic based reagents such as ammonium hydroxide (AOH), tetramethylammonium hydroxide (TMAOH), tetraethylammonium hydroxide (TEAOH), triethylmethylammonium hydroxide (TEMAOH), tetrapropylammonium hydroxide (TPAOH) and tetrabutylammonium hydroxide (TBAOH), in addition to KOH, were used for alkaline conditioning. NaOH has emerged as a better reagent for alkaline conditioning of amidoxime-based adsorbent because of higher uranium uptake capacity, higher uranium uptake selectivity ...

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2015

2015 HPC Annual Report

Center 9300 is very proud to provide a wide range of computing and networking resources ranging from desktop support to high performance computing that enable Sandia’s national security mission needs. Our goal is to provide these services in the most efficient, secure, user friendly, and agile means necessary. High performance computing is one example of how we are delivering on this goal. Thanks to investments from NNSA’s Advanced Simulation and Computing program, coupled with Sandia’s Institutional Computing program, a wide variety of computing resources are available and used to support national security needs. This year we are expanding our high performance computing infrastructure with the procurement of institutional resources for information computing or analytics. Big data analytics has been the buzzword in the computing industry for over a decade now and industries in finance, food and drug, business, and security organizations have been leading the charge. Much like how scientific computing has changed the way science and engineering are performed, data analytics is changing just about every aspect of our lives and more especially our ability to contribute to the national security mission of Sandia. This third edition of our HPC Annual Report continues our commitment to communicate the details and impact of Sandia’s large-scale computing resources that support missions work across Sandia. The Laboratories’ and NNSA’s strategic investments in high performance computing demonstrate our commitment to keeping mission-related research on the cutting edge of science, at pace with technology advances, and at a scale that meets the toughest demands of the nation we so proudly serve.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Methodology to Establish Performance Targets for Building Energy Codes

This report explains the underlying development of the U.S. NZE building sector performance targets reported in Federal Register Notice XX. This document also includes NZE performance targets for U.S. states, which were developed following the same procedures used to develop the national values. These national and state targets are intended to support the establishment and attainment of NZE goals over time. Where residential and commercial building energy code compliance mechanisms apply to new buildings and major renovations and dictate performance requirements, these targets reflect the recommended, minimum levels of performance. Appendix A provides the performance values and targets by U.S. state for residential and commercial buildings. These include each state’s adopted energy code performance, current published MEC performance value, and a nominal NZE code compliance performance target. The current code and NZE values can be compared to the state adopted code value to indicate the level of advancement needed to move towards recommended NZE building performance levels. Additional supplemental resources are available to support states and local governments ready to move from setting NZE policy goals to adopting NZE codes. More information about these resources and the actions states can take to achieve NZE buildings with energy codes are provided in the body of this document.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2015

The Pacific Northwest National Laboratory library of bacterial and archaeal proteomic biodiversity

This dataset deposition announces the submission to public repositories of the PNNL Biodiversity Library, a large collection of global proteomics data for 112 bacterial and archaeal organisms. The data comprises 35,162 tandem mass spectrometry (MS/MS) datasets from ~10 years of research. All data has been searched, annotated and organized in a consistent manner to promote reuse by the community. Protein identifications were cross-referenced with KEGG functional annotations which allows for pathway oriented investigation. We present the data as a freely available community resource. A variety of data re-use options are described for computational modeling, proteomics assay design and bioengineering. Instrument data and analysis files are available at ProteomeXchange via the MassIVE partner repository under the identifiers PXD001860 and MSV000079053.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

2015 California Demand Response Potential Study - Charting California’s Demand Response Future. Interim Report on Phase 1 Results

Demand response (DR) is an important resource for keeping the electricity grid stable and efficient; deferring upgrades to generation, transmission, and distribution systems; and providing other customer economic benefits. This study estimates the potential size and cost of the available DR resource for California’s three investor-owned utilities (IOUs), as the California Public Utilities Commission (CPUC) evaluates how to enhance the role of DR in meeting California’s resource planning needs and operational requirements. As the state forges a clean energy future, the contributions of wind and solar electricity from centralized and distributed generation will fundamentally change the power grid’s operational dynamics. This transition requires careful planning to ensure sufficient capacity is available with the right characteristics – flexibility and fast response – to meet reliability needs. Illustrated is a snapshot of how net load (the difference between demand and intermittent renewables) is expected to shift. Increasing contributions from renewable generation introduces steeper ramps and a shift, into the evening, of the hours that drive capacity needs. These hours of peak capacity need are indicated by the black dots on the plots. Ultimately this study quantifies the ability and the cost of using DR resources to help meet the capacity need at these forecasted critical hours in the state.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2015

Significance of Dynamic and Transient Analysis in the Design and Operation of Hybrid Energy Systems

Energy systems were historically designed and operated with a specific energy conversion objective, while managing loads and resources. In the recent years, the increased utilization of non-dispatchable renewable sources such as wind and solar has played a role in power quality and the reliability of power systems. In order to mitigate the risk associated with the non-dispatchable resources an integrated approach, such as Hybrid Energy Systems (HES), has to be taken, integrating the loads and resource management between the traditional thermal power plants and the non-dispatchable resources. As our electric energy becomes more diverse in its generation resources, the HES with its operational control system, its real-time view and its dynamic decisions making will become an essential part of the integrated energy systems and improve the overall grid reliability. The operational constraints of the energy sources on both the thermal power plants and the non-dispatchable resources in HES, plays a vital role in the planning and design stage. It is an established fact that the choice of energy source depends on the available natural resources and possible infrastructure. A critical component of decision-making depends on the complementary nature and controllability of the energy sources to supply the load demands with high reliability. Controllability of complex HES to achieve desired performance and flexibility is implemented via coordinated control systems while simultaneously generating electricity and other useful products such as useful heat or hydrogen. These systems are based on instrumentation, signal processing, control theory, and engineering system design. The entire HES along with the control systems are characterized by widely varying time constants. Hence, for a well-coordinated control and operation, we propose physics based modeling of the subsystems to assist in a dynamic and transient analysis. Dynamic and transient analysis in real and non-real time domain of the potential sources is capable of providing satisfactory results at the feasibility analysis stage. A simplified HES consisting of complementary energy sources is used to demonstrate the proposed approach. Suitable real time simulations to perform dynamic and transient analysis will be performed to verify results from the non-real time analysis. The role of such analyses, especially the real time dynamic and transient analysis for manual controls is elaborated. It is also discussed that faster than real time simulation will pave the future for controller rooms and hence manual control procedures. Multiple tools such as Real Time Simulator, Matlab®, Simulink®, PSCAD®, MOOSE, etc. are expected to be used for the HES analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗