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At least 379 records · Page 21

Risk-informed Graded Approach for Reliability and Performance Assessment of Sensor and Instrumentation Systems within Advanced Condition Monitoring Technologies

Advanced condition monitoring (ACM) technologies, such as digital twins, are innovative strategies designed to provide real-time health insights, including the remaining useful life of components. The primary goal of ACM is to predict and alert operators to potential functional failures before they occur. ACM systems achieve this by integrating predictive models with various sensor instrumentation, analog-to-digital converters, data warehouses, and data pre-processors. These sensor and instrumentation systems (SIS) are essential for forming a comprehensive understanding of component conditions and ensuring the predictive success of ACM programs. Introducing new technologies like ACM involves varying degrees of risk that can impact plant reliability. Therefore, risk mitigation should be commensurate with the performance and reliability of the developed technology, following a risk-informed graded approach (RIGA). Establishing a RIGA process requires a clear understanding of the hazards and reliability of all subsystems, including their interdependencies and potential impacts on the overall system. Given the critical role of SIS in ACM, this work reviews hazard identification and reliability quantification methods for SIS. It also considers these methods' implications when developing a RIGA process for ACM.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Appending High-Resolution Elevation Data to GPS Speed Traces for Vehicle Energy Modeling and Simulation

Accurate and reliable global positioning system (GPS)-based vehicle use data are highly valuable for many transportation, analysis, and automotive considerations. Model-based design, real-world fuel economy analysis, and the growing field of autonomous and connected technologies (including predictive powertrain control and self-driving cars) all have a vested interest in high-fidelity estimation of powertrain loads and vehicle usage profiles. Unfortunately, road grade can be a difficult property to extract from GPS data with consistency. In this report, we present a methodology for appending high-resolution elevation data to GPS speed traces via a static digital elevation model. Anomalous data points in the digital elevation model are addressed during a filtration/smoothing routine, resulting in an elevation profile that can be used to calculate road grade. This process is evaluated against a large, commercially available height/slope dataset from the Navteq/Nokia/HERE Advanced Driver Assistance Systems product. Results will show good agreement with the Advanced Driver Assistance Systems data in the ability to estimate road grade between any two consecutive points in the contiguous United States.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Emerging Technologies for Privacy Preservation in Energy Systems

This study explores the intersection of digitalization and privacy within the energy sector, focusing on the emerging challenges and opportunities presented by integrating Distributed Energy Resources (DERs) and advanced metering infrastructure. The need for robust digital privacy measures has become crucial as the energy industry evolves towards a more decentralized, digitalized, and decarbonized future. This study delves into four cutting-edge privacy-preserving technologies—Homomorphic Encryption (HE), Secure Multiparty Computation (SMPC), Differential Privacy (DP), and Federated Learning (FL)—each offering unique solutions to safeguard consumer data by increasing digital connectivity and data exchange. Through a detailed examination of these methods, the study explains how each technology operates, its applications within the energy sector, and the specific privacy challenges it addresses. Homomorphic Encryption allows for secure computations on encrypted data, enabling data analysis without compromising privacy. Secure Multiparty Computation enables collaborative data analysis across different entities while protecting the confidentiality of the inputs. Differential Privacy introduces randomness into the assembled data set, preventing the identification of individual records in statistical databases. Lastly, Federated Learning offers a paradigm shift in data analysis, where machine learning models are trained at the edge, minimizing the centralization of sensitive data. The research underscores the significance of implementing these privacy-enhancing technologies to comply with strict data protection regulations, foster consumer trust, and enhance the security of the energy infrastructure. By providing a comprehensive overview of these methodologies and their practical implications for the energy sector, this study aims to contribute to the ongoing discourse on digital privacy, offering insights into how the energy industry can navigate the complexities of data privacy in the digital age.

Cali, Umit↗

The Sloan Digital Sky Survey Quasar Catalog: Twelfth data release

In this paper, we present the Data Release 12 Quasar catalog (DR12Q) from the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey III. This catalog includes all SDSS-III/BOSS objects that were spectroscopically targeted as quasar candidates during the full survey and that are confirmed as quasars via visual inspection of the spectra, have luminosities M i [z = 2] < -20.5 (in a ΛCDM cosmology with H 0 = 70 km s -1 Mpc -1 , Ω M = 0.3, and Ω Λ = 0.7), and either display at least one emission line with a full width at half maximum (FWHM) larger than 500 km s -1 or, if not, have interesting/complex absorption features. The catalog also includes previously known quasars (mostly from SDSS-I and II) that were reobserved by BOSS. The catalog contains 297 301 quasars (272 026 are new discoveries since the beginning of SDSS-III) detected over 9376 deg 2 with robust identification and redshift measured by a combination of principal component eigenspectra. The number of quasars with z > 2.15 (184 101, of which 167 742 are new discoveries) is about an order of magnitude greater than the number of z > 2.15 quasars known prior to BOSS. Redshifts and FWHMs are provided for the strongest emission lines (C iv, C iii], Mg ii). The catalog identifies 29 580 broad absorption line quasars and lists their characteristics. For each object, the catalog presents five-band (u, g, r, i, z) CCD-based photometry with typical accuracy of 0.03 mag together with some information on the optical morphology and the selection criteria. When available, the catalog also provides information on the optical variability of quasars using SDSS and Palomar Transient Factory multi-epoch photometry. The catalog also contains X-ray, ultraviolet, near-infrared, and radio emission properties of the quasars, when available, from other large-area surveys. The calibrated digital spectra, covering the wavelength region 3600–10 500 Å at a spectral resolution in the range 1300 < R < 2500, can be retrieved from the SDSS Catalog Archive Server. Finally, we also provide a supplemental list of an additional 4841 quasars that have been identified serendipitously outside of the superset defined to derive the main quasar catalog.

79 ASTRONOMY AND ASTROPHYSICS↗

Systematic Analyzer Of Numeric Data

This system is meant to take large amounts of digital, automatically gathered data, and then organize it into a form that shows data integrity and plot, graph.

Lehmer, Jacob P.↗

DER Digital Supply Chain Gap Analysis

Solar photovoltaic (PV) cybersecurity is a growing field of research. As deployments of solar PV have increased, cyber risk has also increased. Utility solar PV installations, however, are not required to comply with the North American Electric Reliability Corporation (NERC) Critical Infrastructure Protection (CIP) plan unless they meet a minimum generation threshold of 75 MW. Individual residential-scale solar PV deployments will not meet that generation threshold and are therefore excluded from the NERC CIP requirements. With most solar installations less than 75 MW, solar PV has been deployed with minimal oversight and highly variable cybersecurity maturity. The resources that comprise the digital supply chain can include software, code, data, and other digital components. But as clean energy technologies advance, cybersecurity threats and vulnerabilities continue to evolve and grow in sophistication. Supply chain cybersecurity represents a critical area for ensuring safe operations as the U.S. moves toward a clean energy future.

cybersecurity↗

A digitizer based compact digital spectrometer for ion beam analysis using field programmable gate arrays and various energy algorithms

We report on the implementation of a compact multi-detector fully digital spectrometer and data acquisition system at a nuclear microprobe for ion beam analysis and imaging. The spectrometer design allows for system scalability with no restriction on the number of detectors. It consists of four-channel high-speed digitizer modules for detector signal acquisition and one low-speed digital-to-analog converter (DAC) module with two DAC channels and additional general purpose inputs/outputs to control ion beam scanning and data acquisition. Each digitizer module of the spectrometer provides its own Field Programmable Gate Array (FPGA) as digital signal processing unit to analyze detector signals as well as to synchronize the ion beam position in hard real-time. With the customized FPGA designs for all modules, all calculation intensive tasks are executed inside the modules, which reduces significantly the data stream to and CPU load on the control computer. To achieve an optimal energy resolution for all detector/preamplifier pulse shape characteristics, a user-definable infinite impulse response filter with high throughput for energy determination was implemented. The new spectrometer has an online data analysis feature, a compact size, and is able to process any type of detector signals such as particle induced x-ray emission, Rutherford backscattering spectrometry, or scanning transmission ion microscopy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Automatic Digitization and Orientation of Scanned Mesh Data for Floor Plan and 3D Model Generation

This paper describes a novel approach for generating accurate floor plans and 3D models of building interiors using scanned mesh data. Unlike previous methods, which begin with a high resolution point cloud from a laser range-finder, our approach begins with triangle mesh data, as from a Microsoft HoloLens. It generates two types of floor plans, a “pen-and-ink” style that preserves details and a drafting-style that reduces clutter. It processes the 3D model for use in applications by aligning it with coordinate axes, annotating important objects, dividing it into stories, and removing the ceiling. Its performance is evaluated on commercial and residential buildings, with experiments to assess quality and dimensional accuracy. Our approach demonstrates promising potential for automatic digitization and orientation of scanned mesh data, enabling floor plan and 3D model generation in various applications such as navigation, interior design, furniture placement, facilities management, building construction, and HVAC design.

Sharma, Ritesh↗

Development of a CO 2 Chemical Sensor for Downhole CO 2 Monitoring in Carbon Sequestration

Geologic storage of carbon dioxide (CO 2 ) has been proposed as a viable means for reducing anthropogenic CO 2 emissions. The means for geological sequestration of CO 2 is injection of supercritical CO 2 underground, which requires the CO 2 to remain either supercritical, or in solution in the water/brine present in the underground formation. However, there are aspects of geologic sequestration that need further study, particularly in regards to safety. To date, none of the geologic sequestration locations have been tested for storage integrity under the changing stress conditions that apply to the sequestration of very large amounts of CO 2 . Establishing environmental safety and addressing public concerns require widespread monitoring of the process in the deep subsurface. In addition, studies of subsurface carbon sequestration such as flow simulations, models of underground reactions and transports require a comprehensive monitoring process to accurately characterize and understand the storage process. Real-time information about underground CO 2 movement and concentration change is highly helpful for: (1) better understanding the uncertainties present in CO 2 geologic storage; (2) improvement of simulation models; and (3) evaluation of the feasibility of geologic CO 2 storage. Current methods to monitor underground CO 2 storage include seismic, geoelectric, isotope and tracer methods, and fluid sampling analysis. However, these methods commonly resulted low resolution, high cost, and the inability to monitor continuously over the long time scales of the CO 2 storage process. A preferred way of monitoring in-situ underground CO 2 migration is to continuous measure CO 2 concentration change in brine during the carbon storage process. An approach to obtain the real time information on CO 2 concentration change in formation solution is highly demanded in carbon storage to understand the CO 2 migration subsurface and to answer the public safety problem. The objective of the study is to develop a downhole CO 2 sensor that can in-situ, continuously monitor CO 2 concentration change in deep saline. The sensor is a Severinghaus-type CO 2 sensor with small size, which renders it can be embedded in monitoring well casing or integrated with pressure/temperature transducers, enabling the development of “smart” wells. The studies included: (1) prepare and characterize metal-oxide electrodes. Test the electrodes response to pH change. Investigate different ions and brine concentration effects on the electrode’s performance. Study the stability of the electrode in brine solution; (2) fabricate a downhole CO 2 sensor with the metal-oxide electrodes prepared in the laboratory. Test the performance of the CO 2 sensor in brine solutions. Study high pressure effects on the performance of the sensor; (3) design and conduct CO 2 /brine coreflooding experiments with the CO2 sensor. Monitor CO 2 movement along the core and test the performance of the sensor in coreflooding tests. Develop a data acquisition system that can digitize the sensor’s output voltage. Our completed research has resulted in deep understanding of downhole CO 2 sensor development and CO 2 monitoring in CO 2 storage process. The developed downhole CO 2 sensor included a metal-oxide electrode, a gas-permeable membrane, a porous steel cup, and a bicarbonate-based internal electrolyte solution. Iridium oxide-based electrode was prepared and used for preparation the CO 2 sensor. The prepared iridium oxide-based electrode displayed a linearly response to pH change. Different factors such as different ions and ions concentration, temperature, and pressure effects on the electrode performance on pH response were investigated. The results indicated that the electrode exhibited a good performance even in high salt concentration of produced water. To improve the electrode performance under high pressure, IrO 2 nanoparticles with the particle size in the range of 1-2 nm were prepared and electrodeposited on stainless steel substrate by cyclic voltammetry. It was observed that the thin film of iridium oxide was formed on the substrate surface and such iridium oxide-based electrode displayed excellent performance under high pressure for longer term. A downhole CO 2 sensor with the iridium oxide-based electrode was prepared. The working principle of the CO 2 sensor is based on the measurement of the pH change of the internal electrolyte solution caused by the hydrolysis of CO 2 and then determination of the CO 2 concentration in water. The prepared downhole CO 2 sensor had the size of diameter of 0.7 in. and length of 1.5 in. The sensor was tested under the pressures of 500 psi, 2,000 psi, and 3,000 psi. A linear correlation was observed between the sensor potential change and dissolved CO 2 concentration in water. The response time of the CO 2 sensor was in the range of 60-100 minutes. Further tests indicated that the CO 2 sensor exhibited good reproducibility under high pressure. A CO 2 /brine coreflooding system was constructed to simulate the real-world CO 2 storage process. The prepared downhole CO 2 sensor was loaded in the system to monitor CO 2 movement during CO 2 /brine coreflooding test. The results indicated that the sensor could detect CO 2 movement in the tests. Further studies showed that the sensor could be recovered by brine flooding after CO 2 /brine flushed the core. The results of the coreflooding tests demonstrated that the sensor had potential application for CO 2 monitoring in carbon sequestration. A data acquisition system for the downhoe CO 2 sensor was developed and coded. The system converted the sensor output signal into digital data and transported the data from downhole to wellhead surface. The data acquisition system was tested and evaluated in the laboratory with the prepared sensor for data collection.

36 MATERIALS SCIENCE↗

Transmission line relay mis-operation detection based on time-synchronized field data

In this paper, a real-time tool to detect transmission line relay mis-operation is implemented. The tool uses time-synchronized measurements obtained from both ends of the line during disturbances. The proposed fault analysis tool comes into the picture only after the protective device has operated and tripped the line. The proposed methodology is able not only to detect, classify, and locate transmission line faults, but also to accurately confirm whether the line was tripped due to a mis-operation of protective relays. The analysis report includes either detailed description of the fault type and location or detection of relay mis-operation. As such, it can be a source of very useful information to support the system restoration. The focus of the paper is on the implementation requirements that allow practical application of the methodology, which is illustrated using the field data obtained the real power system. Testing and validation is done using the field data recorded by digital fault recorders and protective relays. The test data included several hundreds of event records corresponding to both relay mis-operations and actual faults. The discussion of results addresses various challenges encountered during the implementation and validation of the presented methodology.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Properties of Spectrally Defined Red QSOs at z = 0.3–1.2

We investigated the properties of a sample of red Quasi-stellar Objects (QSOs) using optical, radio, and infrared data. These QSOs were selected from the Sloan Digital Sky Survey Data Release 7 quasar catalog. We only selected sources with sky coverage in the Very Large Array Faint Images of the Radio Sky at Twenty-centimeters survey, and searched for sources with Wide-field Infrared Survey Explorer counterparts. We defined the spectral color of the QSOs based on the flux ratio of the rest-frame 4000 to 3000 Å continuum emission to select red QSOs and typical QSOs. In accordance with this criterion, only QSOs with redshifts between 0.3 and 1.2 could be selected. We found that red QSOs have stronger infrared emission than typical QSOs. We noted that the number ratios of red QSOs to typical QSOs decrease with increasing redshifts, although the number of typical QSOs increase with redshifts. Furthermore, at high redshifts, the luminosity distributions of typical QSOs and red QSOs seem to have similar peaks; however, at low redshifts, the luminosities of red QSOs seem to be lower than those of typical QSOs. These findings suggest that there might be at least two types of red QSOs in our QSO samples.

79 ASTRONOMY AND ASTROPHYSICS↗

A DATA-DRIVEN MODEL FOR SPECTRA: FINDING DOUBLE REDSHIFTS IN THE SLOAN DIGITAL SKY SURVEY

We present a data-driven method-heteroscedastic matrix factorization, a kind of probabilistic factor analysis-for modeling or performing dimensionality reduction on observed spectra or other high-dimensional data with known but non-uniform observational uncertainties. The method uses an iterative inverse-variance-weighted least-squares minimization procedure to generate a best set of basis functions. The method is similar to principal components analysis (PCA), but with the substantial advantage that it uses measurement uncertainties in a responsible way and accounts naturally for poorly measured and missing data; it models the variance in the noise-deconvolved data space. A regularization can be applied, in the form of a smoothness prior (inspired by Gaussian processes) or a non-negative constraint, without making the method prohibitively slow. Because the method optimizes a justified scalar (related to the likelihood), the basis provides a better fit to the data in a probabilistic sense than any PCA basis. We test the method on Sloan Digital Sky Survey (SDSS) spectra, concentrating on spectra known to contain two redshift components: these are spectra of gravitational lens candidates and massive black hole binaries. We apply a hypothesis test to compare one-redshift and two-redshift models for these spectra, utilizing the data-driven model trained on a random subset of all SDSS spectra. This test confirms 129 of the 131 lens candidates in our sample and all of the known binary candidates, and turns up very few false positives.

79 ASTRONOMY AND ASTROPHYSICS↗

MEAN SPECTRAL ENERGY DISTRIBUTIONS AND BOLOMETRIC CORRECTIONS FOR LUMINOUS QUASARS

We explore the mid-infrared (mid-IR) through ultraviolet (UV) spectral energy distributions (SEDs) of 119,652 luminous broad-lined quasars with 0.064 < z < 5.46 using mid-IR data from Spitzer and WISE, near-infrared data from the Two Micron All Sky Survey and UKIDSS, optical data from the Sloan Digital Sky Survey, and UV data from the Galaxy Evolution Explorer. The mean SED requires a bolometric correction (relative to 2500 A) of BC{sub 2500A} =2.75 {+-} 0.40 using the integrated light from 1 {mu}m-2 keV, and we further explore the range of bolometric corrections exhibited by individual objects. In addition, we investigate the dependence of the mean SED on various parameters, particularly the UV luminosity for quasars with 0.5 {approx}< z {approx}< 3 and the properties of the UV emission lines for quasars with z {approx}> 1.6; the latter is a possible indicator of the strength of the accretion disk wind, which is expected to be SED-dependent. Luminosity-dependent mean SEDs show that, relative to the high-luminosity SED, low-luminosity SEDs exhibit a harder (bluer) far-UV spectral slope ({alpha}{sub UV}), a redder optical continuum, and less hot dust. Mean SEDs constructed instead as a function of UV emission line properties reveal changes that are consistent with known Principal Component Analysis trends. A potentially important contribution to the bolometric correction is the unseen extreme UV (EUV) continuum. Our work suggests that lower-luminosity quasars and/or quasars with disk-dominated broad emission lines may require an extra continuum component in the EUV that is not present (or much weaker) in high-luminosity quasars with strong accretion disk winds. As such, we consider four possible models and explore the resulting bolometric corrections. Understanding these various SED-dependent effects will be important for accurate determination of quasar accretion rates.

79 ASTRONOMY AND ASTROPHYSICS↗

Observing correlations between dark matter accretion and galaxy growth: II. testing the impact of galaxy mass, star formation indicator, and neighbour colours

A crucial question in galaxy formation is what role new accretion has in star formation. Theoretical models have predicted a wide range of correlation strengths between halo accretion and galaxy star formation. Previously, we presented a technique to observationally constrain this correlation strength for isolated Milky Way mass galaxies at z ~ 0.12, based on the correlation between halo accretion and the density profile of neighbouring galaxies. By applying this technique to both observational data from the Sloan Digital Sky Survey and simulation data from the UNIVERSEMACHINE , where we can test different correlation strengths, we ruled out positive correlations between dark matter accretion and recent star formation activity. In this work, we expand our analysis by (1) applying our technique separately to red and blue neighbouring galaxies, which trace different infall populations, (2) correlating dark matter accretion rates with D n 4000 measurements as a longer-term quiescence indicator than instantaneous star-formation rates, and (3) analysing higher-mass isolated central galaxies with 10 11.0 < M * /M ⊙ < 10 11.5 out to z ~ 0.18. Finally, in all cases, our results are consistent with non-positive correlation strengths with ≳ 85 percent confidence, which is most consistent with models where processes such as gas recycling dominate star formation in massive z = 0 galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

Reliable and redundant FPGA based read-out design in the ATLAS TileCal Demonstrator

The Tile Calorimeter at ATLAS [1] is a hadron calorimeter based on steel plates and scintillating tiles read out by PMTs. The current read-out system uses standard ADCs and custom ASICs to digitize and temporarily store the data on the detector. However, only a subset of the data is actually read out to the counting room. The on-detector electronics will be replaced around 2023. To achieve the required reliability the upgraded system will be highly redundant. Here the ASICs will be replaced with Kintex-7 FPGAs from Xilinx. This, in addition to the use of multiple 10 Gbps optical read-out links, will allow a full read-out of all detector data. Due to the higher radiation levels expected when the beam luminosity is increased, opportunities for repairs will be less frequent. The circuitry and firmware must therefore be designed for sufficiently high reliability using redundancy and radiation tolerant components. Within a year, a hybrid demonstrator including the new readout system will be installed in one slice of the ATLAS Tile Calorimeter. This will allow the proposed upgrade to be thoroughly evaluated well before the planned 2023 deployment in all slices, especially with regard to long term reliability. Different firmware strategies alongside with their integration in the demonstrator are presented in the context of high reliability protection against hardware malfunction and radiation induced errors.

ATLAS↗

THE EVOLUTION OF POST-STARBURST GALAXIES FROM z ∼ 1 TO THE PRESENT

Post-starburst galaxies are in the transitional stage between blue, star-forming galaxies and red, quiescent galaxies and therefore hold important clues for our understanding of galaxy evolution. In this paper, we systematically searched for and identified a large sample of post-starburst galaxies from the spectroscopic data set of the Sloan Digital Sky Survey (SDSS) Data Release 9. In total, we found more than 6000 objects with redshifts between z ∼ 0.05 and z ∼ 1.3, making this the largest sample of post-starburst galaxies in the literature. We calculated the luminosity function of the post-starburst galaxies using two uniformly selected subsamples: the SDSS main galaxy sample and the Baryon Oscillation Spectroscopic Survey CMASS sample. The luminosity functions are reasonably fit by half-Gaussian functions. The peak magnitudes shift as a function of redshift from M ∼ −23.5 at z ∼ 0.8 to M ∼ −20.3 at z ∼ 0.1. This is consistent with the downsizing trend, whereby more massive galaxies form earlier than low-mass galaxies. We compared the mass of the post-starburst stellar population found in our sample to the decline of the global star formation rate and found that only a small amount (∼1%) of all star formation quenching in the redshift range z = 0.2–0.7 results in post-starburst galaxies in the luminosity range our sample is sensitive to. Therefore, luminous post-starburst galaxies are not the place where most of the decline in the star formation rate of the universe is happening.

79 ASTRONOMY AND ASTROPHYSICS↗

Advanced Tritium Process Analytics and Optimization via a Digital Twin, SRNL-TR-2023-00550

Improving the process knowledge and understanding of TCAP can be achieved by incorporating advanced tools. This project addresses “Advanced analytics for modeling, forecasting, & optimization of the tritium refinement process” and is being applied to the TCAP process. The value of digitization and advanced analytics for TCAP data are tracking of gas mixtures & inventories is presently a manual effort that is rather cumbersome. Incorporating some automation into the data capture will reduce errors and storing data in an accessible database that can be used for tracking as well as process improvements. In addition, the database approach will enable longer term history to be maintained rather than the current practice of deleting data after six months. The digitized and automated data will allow for models to be developed for the process and will enable the forecasting and optimization.

Korinko, Paul S.↗

Adapting Grid Criticality for Data Centers

This presentation explores the evolving definition of “critical load” in the electric grid, emphasizing the growing importance of digital infrastructure—particularly data centers—in grid resilience, restoration, and modernization. As utilities increasingly rely on AI-driven analytics and software-defined control systems, data centers have shifted from passive electricity consumers to essential computational hubs that enable National Critical Functions (NCFs) and support real-time grid operations. The deck examines the scale and impact of digital loads, the need for grid modernization to manage rapid load growth, and the diverse computing paradigms required for AI deployment. It introduces a tiered taxonomy for classifying critical loads, highlights operational dependencies between the grid and digital infrastructure, and discusses policy implications for integrating data centers into emergency planning and restoration protocols. Through case studies and practical frameworks, the presentation provides actionable insights for utilities, regulators, and planners navigating the digital transformation of the power sector.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗