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Potential State Regulatory Pathways to Facilitate Low-Carbon Fuels

States and the federal government are increasingly engaged in the challenges around decarbonizing the electric grid. In particular, regulators, consumers, stakeholders, and utilities recognize the need to carefully consider the role natural gas will play in a decarbonized future. A variety of technology and policy options to reduce greenhouse gas emissions associated with natural gas use are available, including energy efficiency programs, demand reduction tools, strategic electrification, and strategies to reduce emissions from natural gas production, transportation, and consumption. Low-carbon fuels – mainly renewable natural gas (RNG) and clean hydrogen – are being considered an important component of decarbonization goals. RNG and hydrogen may be able to meaningfully reduce emissions from processes independent of geologic natural gas, displacing emissions of methane, a powerful greenhouse gas. Although RNG and hydrogen are not cost-competitive today with geologic natural gas and are smaller in scale and potential than other decarbonization options, they can be explored as potential critical tools to decarbonize sectors that are difficult to electrify or shift off of natural gas entirely, such as air travel, industrial processes, maritime transport, long-distance trucking, space heating on cold days, and railroads (Nadel, 2022). The role of this report is to provide informational context for state utility regulators to understand the impacts of and challenges associated with broader integration of low-carbon fuels, followed by examples of state regulatory actions taken to date to facilitate the development of low-carbon fuels. Setting clear guidance to calculate the environmental benefits of low-carbon fuels and continuing federal and state investments in research and development to reduce costs relative to fossil fuels will be important steps to take to signal the desire to grow the market for these fuels. State public utility commissions may play a key role in setting regulatory frameworks for low-carbon fuels and ensuring that ratepayer funds, if utilized, are done so to further the public interest. This report is intended to summarize decisions that states have made to date on low-carbon fuels. In the spirit of understanding the current market and sharing information, this report provides success stories, and lessons learned across states as regulators implement varying strategies to achieve decarbonization objectives while maintaining their focus on affordability, safety, and reliability of the energy system. The report begins with an introduction of the role of natural gas in the U.S. economy (Section I) and background information on natural gas use, decarbonization, and low-carbon fuels (Section II). Next, the report describes the current market by discussing the scale of current production, emissions intensity, resource potential, and costs of low-carbon fuels compared to geologic natural gas (Section III). Following these sections, the report describes four strategies states have employed to facilitate low-carbon fuels: opening exploratory dockets, approving voluntary tariffs for customers, approving interconnection tariffs for producers, and considering portfolio-wide procurement targets (Section IV). This section lists states that have taken actions in each category, citing utility filings, commission decisions, stakeholder comments, and other relevant sources. Finally, the report concludes with suggested questions regulators may wish to consider regarding low-carbon fuels, in the interest of preparing to make decisions in the future (Section V). These questions include: Are there existing regulatory or technical barriers to voluntary purchases of low-carbon fuels? Can customers work with utilities to procure low-carbon fuels; are producers able to interconnect projects without significant barriers to entry? Should the infrastructure and/or commodity costs of low-carbon fuels be socialized among all ratepayers, or borne solely by the large commercial and industrial (C&I) customers currently driving the market? Should regulated natural gas and/or electric utilities own and operate low-carbon fuel production? How should regulators consider the unique decarbonization potential of low-carbon fuels, particularly for hard-to-abate sectors, in decision-making? Is additional direction or clarity from state policymakers needed? What no-regrets approaches can help facilitate both near-term RNG development and long-term development of hydrogen and other zero-carbon fuels? We collectively wish to express our gratitude to the U.S. Department of Energy, Office of Fossil Energy and Carbon Management, for supporting this report and other technical assistance resources for state regulators on natural gas topics. State regulators operate under a variety of policy environments, and states have vastly different types of energy resources, infrastructure, and customers. While there is no optimal regulatory, policy, or technological solution that will be successful in every state, state regulators can benefit by exchanging lessons learned with their peers across the country. We look forward to continued engagement with our fellow commissioners, commission staff, NARUC, the U.S. Department of Energy, and other stakeholders to develop sound regulation in the public interest.

03 NATURAL GAS↗

Nuclear Smuggling Detection and Deterrence (FY 2018 Data Analysis Annual Report)

The National Nuclear Security Administration’s Office of Nuclear Smuggling Detection and Deterrence (NSDD) has facilitated the installation of more than 3,728 radiation portal monitors (RPMs) at 660 sites in 63 countries. This collection of RPMs represents the world’s largest network of radiation detectors and provides one element of the defense-in-depth approach that supports the Global Nuclear Detection Architecture. These systems support NSDD’s mission to build partner country capability to deter, detect, and interdict the illicit transport of radiological and fissile material through strategic points of entry and exit at seaports, airports, and border crossings.NSDD works collaboratively with partner countries and international organizations to optimize the operation of these RPMs. The large amount of data provided by NSDD partner countries (summarized in the banner to the right) highlights the close cooperation and partnerships NSDD has built with 63 countries around the world. Thirty-two of these countries shared at least some RPM-related data with NSDD in fiscal year (FY) 2018. This significant level of data sharing is a key element that distinguishes the NSDD office as unique among nuclear nonproliferation programs and initiatives: NSDD can provide specific, objective, data-driven decisions and support for sustaining the radiation detection systems it helped deploy. This data analysis report summarizes and aggregates the RPM data provided to the NSDD office for analysis and review in FY 2018.The data can be used to describe RPM performance and characterize the wide diversity of NSDD deployment sites. For example, NSDD deploys detector systems across sites with natural background radiation levels that can vary by a factor of up to nine from site to site. Some RPM lanes have few occupancies, whereas others have up to approximately 8,000 occupancies per day, and the different types of cargo traveling through a site can result in site-wide alarm rates that range from near 0% at some sites to above 3% at others. Based on the data received, the global average uptime for NSDD RPMs was 97% for FY 2018. NSDD takes all these factors into account in making recommendations to partner countries on how to most effectively manage and maintain site operations. NSDD utilizes reports and other information products created by ORNL Radiation Inspection Systems Team (RIST) data analysts to efficiently allocate the resources needed to detect and ultimately interdict illicit nuclear and radiological material.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Orion SysML Model, Digital Twin, and Lessons Learned for Artemis I

In 2015 it was recognized by NASA’s Orion Chief Engineer that NASA’s design insight into the Orion subsystems for Artemis I were not sufficient to provide traditional engineering support to flight operations. To address these concerns and provide an opportunity to apply emerging model-based systems engineering and digital twin methodologies and provide opportunities for employees across NASA to get hands-on training, an Orion digital twin pilot project was initiated in 2020. With the increase in complexities of spacecraft, and decreased time to made decisions during missions in critical or emergency situations, digital modeling and integration of design can reduce the time to answer questions by days and required human resources by an order of magnitude over historical approaches and was identified to be critical capability for NASA’s future. This paper describes the genesis of this digital twin pilot project, efforts undertaken, a reproducible methodology to take available system information from a mature program to create an executable SysML model that supports a link to unit-specific data, thus forming a connection to the physical asset, and associated lessons learned and project deliverables.

MBSE↗

Quantification of functional impact classification on the current U.S. nuclear fleet

Currently, nuclear power generates only a small fraction of the world's electricity, though it does have the potential to meet the needs of the world as long as its production can compete with the alternative energy base load producers. In U.S the commercial nuclear fleet comprises of Light Water Reactors (LWRs), consisting of Pressurized Water Reactors (PWRs) and Boiling Water Reactors (BWRs). Many plants experience multiple events each year, which lead to reactor trips or scrams. This subsequently leads to plants being off the grid, which is not an economically favorable situation in the current energy markets. This study helps identify functional impact (FI) event categories for both PWR's and BWR's. Understanding that not all events and their causes can be anticipated, current industry best practices implement lessons learned to provide challenges and issues identification. In turn these are studied to achieve improved operational practices, and design modifications. This leads to overall enhanced resiliency. FI groups are the categories of initiating events (IE). IEs are unplanned events that occur while a nuclear plant is in critical operation, and requires that the plant be shut down to achieve a stable state. When a risk cannot be eliminated, IEs are identified and studied to reduce the risk and contribute to the identification of mitigations, safer designs and operational practices. Breaking IE events into groups' results in the classification of FI groups. A FI group is a risk-significant event category that could impact the ability of a NPP to remove decay heat from the reactor. Inability to remove decay heat from the reactor has the potential to lead to core damage. For an event to be considered a FI, it must be associated with a manual or automatic reactor trip, irrespective of the order of events. In addition, the plant must be at or above the point of adding heat and the event must happen before or shortly after a reactor trip. One or more FIs may be identified in any individual reactor trip sequence. The relationship between FI sequence, and/or frequency per a plant event is outside the scope of this paper. For example, the loss of offsite power (LOOP) can occur from eternal events (i.e. weather, human, wildlife etc.). This results in an event that requires a transfer of power to an emergency source, such as a generator, which produces a reactor trip and then a closure of main steam isolation valves (MSIVS). The FI applicable to this reactor trip sequence would be LOOP and closure of at least one MSIV in each main steam line. The results presented herein are focused on the analysis and evaluation of FI event categories. Only FI categories that can be found in IE studies, Initialing Events Spreadsheet and are recorded in a historical review of Licensee Event Reports (LERs) from 1988 through 2013. The results of this analysis can support plant decisions, design, procedures, and identify weakness.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Inferred inflow forecast horizons guiding reservoir release decisions across the United States

Abstract. Medium- to long-range forecasts often guide reservoir release decisions to support water management objectives, including mitigating flood and drought risks. While there is a burgeoning field of science targeted at improving forecast products and associated decision support models, data describing how and when forecasts are applied in practice remain undeveloped. This lack of knowledge may prevent hydrological modelers from developing accurate reservoir release schemes for large-scale, distributed hydrology models that are increasingly used to assess the vulnerabilities of large regions to hydrological stress. We address this issue by estimating seasonally varying, regulated inflow forecast horizons used in the operations of more than 300 dams throughout the conterminous United States (CONUS). For each dam, we take actual forward observed inflows (perfect foresight) as a proxy for forecasted flows available to the operator and then identify for each week of the year the forward horizon that best explains the release decisions taken. Resulting “horizon curves” specify for each dam the inferred inflow forecast horizon as a function of the week of the water year. These curves are analyzed for strength of evidence for contribution of medium- to long-range forecasts in decision making. We use random forest classification to estimate that approximately 80 % of large dams and reservoirs in the US (1553±50 out of 1927 dams with at least 10 Mm3 storage capacity) adopt medium- to long-range inflow forecasts to inform release decisions during at least part of the water year. Long-range forecast horizons (more than 6 weeks ahead) are detected in the operations of reservoirs located in high-elevation regions of the western US, where snowpack information likely guides the release. A simulation exercise conducted on four key western US reservoirs indicates that forecast-informed models of reservoir operations may outperform models that neglect the horizon curve – including during flood and drought conditions.

54 ENVIRONMENTAL SCIENCES↗

Projected Operational Energy Life Cycle Data Development: 2025 Update

This report documents the data sources and methods used to develop the energy life cycle data for use by the National Institute of Standards and Technology (NIST) Engineering Laboratory (EL) to be used for the development of measurement science and incorporation into decision-support tools for evaluating building and facility capital investments. The data are posted separately under DOI 10.18141/2575194.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA/SPoRT's GOES-R Activities in Support of Product Development, Management, and Training

The NASA Short-term Prediction Research and Transition (SPoRT) Center supports many activities within the GOES-R Proving Grounds (PG). These include the development of imagery from existing instrumentation as a proxy to future Advanced Baseline Imager (ABI) capabilities on GOES-R. The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible/Infrared Imager/Radiometer Suite (VIIRS) instruments are used to provide a glimpse of the multi-spectral capabilities that will become the norm as the number of channels and data rate dramatically increase with GOES-R. The NOAA/NWS has plans to provide operational users with all ABI channels at the highest resolution. Data fusion of individual channels into composite red, green, and blue imagery products will assist the end user with this future wave of information. While increasing the efficiency in the operational use of ABI channels, these composites provide only qualitative information. Within the GOES-R PG, SPoRT and other partners are exploring ways to include quantitative information as part of the composite imagery. However, limitations in local hardware processing and/or data bandwidth for users of the GOES-R data stream are challenges to overcome. This presentation will discuss the creation of these composite images as well as possible solutions to address these processing challenges. In a similar manner the Geostationary Lightning Mapper (GLM) to be launched on GOES-R presents several data management challenges. The GLM is a pioneering instrument to quantify total lightning from a geostationary platform. The expected data frequency from the GLM is to be at a sub-minute interval. Users of such a data set may have little experience in handling such a rapid update of information. To assist users, SPoRT is working with the NWS to develop tools within the user fs decision support system to allow tracking and analysis of total lightning from a storm-based perspective. This presentation will discuss the challenges and progress of this tool development work. With new data and products comes the need for user Training. Within the GOES-R PG SPoRT is supporting the demonstration of these future products by providing various training materials to end users. A summary of training provided to operational users will be discussed.

Fuell, Kevin K.↗

Rapid Evaluation and Response to Impacts on Critical End-Use Loads Following Natural Hazard-Driven Power Outages: A Modular and Responsive Geospatial Technology

The disparate nature of data for electric power utilities complicates the emergency recovery and response process. The reduced efficiency of response to natural hazards and disasters can extend the time that electrical service is not available for critical end-use loads, and in extreme events, leave the public without power for extended periods. This article presents a methodology for the development of a semantic data model for power systems and the integration of electrical grid topology, population, and electric distribution line reliability indices into a unified, cloud-based, serverless framework that supports power system operations in response to extreme events. An iterative and pragmatic approach to working with large and disparate datasets of different formats and types resulted in improved application runtime and efficiency, which is important to consider in real time decision-making processes during hurricanes and similar catastrophic events. This technology was developed initially for Puerto Rico, following extreme hurricane and earthquake events in 2017 and 2020, but is applicable to utilities around the world. Given the highly abstract and modular design approach, this technology is equally applicable to any geographic region and similar natural hazard events. In addition to a review of the requirements, development, and deployment of this framework, technical aspects related to application performance and response time are highlighted.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Distributed water desalination and purification systems: perspective and future directions

Distributed water treatment and desalination (DWTD) systems are critical for the development of a diverse water portfolio of the desired quality and intended use at the target location. Widespread adoption of DWTD has been hampered given the need for round-the-clock monitoring and the lack of local technical expertise for system management. However, self-adaptive operation, real-time remote monitoring, supervisory control, and asset management of DWTD systems are now feasible with the implementation of advanced local system control, cyberinfrastructure that facilitates real-time cloud-based analytics, data management, and artificial intelligence–powered decision support. Such an approach will introduce transformative virtual networks of DWTD systems to provide needed water to locations that are not served by centralized and satellite water treatment and desalination systems.

Cohen, Yoram [University of California, Los Angele↗

Technical Evaluation of Temporal Groundwater Monitoring Variability in MW66 and Nearby Wells, Paducah Gaseous Diffusion Plant

Evaluation of disposal records, soil data, and spatial/temporal groundwater data from the Paducah Gaseous Diffusion Plant (PGDP) Solid Waste Management Unit (SWMU) 7 indicate that the peak contaminant concentrations measured in monitoring well (MW) 66 result from the influence of the regional PGDP NW Plume, and does not support the presence of significant vertical transport from local contaminant sources in SWMU 7. This updated evaluation supports the 2006 conceptualization which suggested the high and low concentrations in MW66 represent different flow conditions (i.e., local versus regional influences). Incorporation of the additional lines of evidence from data collected since 2006 provide the basis to link high contaminant concentrations in MW66 (peaks) to the regional 'Northwest Plume' and to the upgradient source, specifically, the C400 Building Area. The conceptual model was further refined to demonstrate that groundwater and the various contaminant plumes respond to complex site conditions in predictable ways. This type of conceptualization bounds the expected system behavior and supports development of environmental cleanup strategies, providing a basis to support decisions even if it is not feasible to completely characterize all of the 'complexities' present in the system. We recommend that the site carefully consider the potential impacts to groundwater and contaminant plume migration as they plan and implement onsite production operations, remediation efforts, and reconfiguration activities. For example, this conceptual model suggests that rerouting drainage water, constructing ponds or basin, reconfiguring cooling water systems, capping sites, decommissioning buildings, fixing (or not fixing) water leaks, and other similar actions will potentially have a 'direct' impact on the groundwater contaminant plumes. Our conclusion that the peak concentrations in MW66 are linked to the regional PGDP NW Plume does not imply that there TCE is not present in SWMU 7. The available soil and groundwater data indicate that the some of the waste disposed in this facility contacted and/or were contaminated by TCE. In our assessment, the relatively small amount of TCE associated with SWMU 7 is not contributing detectable TCE to the groundwater and does not represent a significant threat to the environment, particularly in an area where remediation and/or management of TCE in the NW plume will be required for an extended timeframe. If determined to be necessary by the PGDP team and regulators, additional TCE characterization or cleanup activities could be performed. Consistent with the limited quantity of TCE in SWMU 7, we identify a range of low cost approaches for such activities (e.g., soil gas surveys for characterization or SVE for remediation). We hope that this information is useful to the Paducah team and to their regulators and stakeholders to develop a robust environmental management path to address the groundwater and soil contamination associated with the burial ground areas.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Safety Analytics Forecasting and Evaluation Reporting (SAFER)

The SAFER Sandbox is a web application for testing various types of data visualization tools that analyze safety data across national laboratories. By enabling the user to visualize this data through visual and textual analyses, the SAFER Sandbox helps to facilitate the research and support for the National Nuclear Security Administration (NNSA) Office of Safety, Infrastructure and Operations (NA-50). Safety data across the national laboratory complex is not currently analyzed in one location. This prohibits administrators from viewing safety data trends and making large scale decisions based on a holistic view of the data. By implementing data analytics web services such as representative text summary, noun phrase extraction and graph exploration, users can view and explore safety data based on search queries. The data visualizations in the SAFER Sandbox reveal trends and point to items of concern based on safety data. The SAFER Sandbox is a testing ground for these visualizations.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Machine Learning-Based Anomaly Detection for PMT Data Quality Monitoring in the SBN and DUNE

Maintaining high-quality detector data is essential for achieving the scientific objectives of the Short-Baseline Neutrino (SBN) Program at Fermilab. Current data quality monitoring (DQM) procedures rely primarily on threshold-based metrics and manual inspection of detector monitoring plots, making the detection of subtle or gradually developing anomalies both time-consuming and dependent on expert interpretation. This project developed and evaluated a machine-learning workflow for automatically identifying anomalous photomultiplier tube (PMT) channels in the Short-Baseline Near Detector (SBND) using optical-hit amplitude data. A Python-based analysis program was developed to process ROOT files, extract statistical features describing individual PMT amplitude distributions, and generate feature vectors for anomaly detection. These features were used to train an Isolation Forest model using data representing normal detector operation. The trained model was subsequently applied to independent detector runs to identify channels exhibiting statistically unusual behavior relative to the learned reference response. To support expert interpretation, the workflow generated complementary diagnostic products, including anomaly score distributions, normalized amplitude comparisons, decision-tree visualizations, and principal component analysis (PCA) projections. This project demonstrated the feasibility of integrating unsupervised machine learning into detector data-quality monitoring and developed a complete workflow for automated PMT performance assessment to aid expert-driven review. Beyond its technical contributions, the VFP appointment fostered a research collaboration between Aurora University and Fermilab and provided direct workforce development benefits by training the visiting faculty member in detector-scale machine-learning methods that are now being incorporated into undergraduate coursework and research. The methodology developed here provides a foundation for future applications to ProtoDUNE and other liquid argon time projection chamber (LArTPC) detectors, contributing to ongoing efforts to improve detector reliability, reduce manual monitoring requirements, and enable scalable data quality monitoring for future large-scale neutrino experiments, including the Deep Underground Neutrino Experiment (DUNE).

Colón Santana, Juan A. [Unlisted, US, IL]↗

PC4CAST: A tool for DSN load forecasting and capacity planning

Effectively planning the use and evolution of the Deep Space Network (DSN) is a complex problem involving many parameters. The tool that models many of these complexities, yet requires simple structured inputs and provides concise easy-to-understand metrics to aid in the planning process is discussed. The tool, PC4CAST, is used for both load forecasting (predicting how well planned that DSN resources meet expected demand) and as a decision support tool in the capacity-planning process (determining the relative benefits of capacity expansion options). It is now in use in the TDA Planning Office, has been used in numerous studies, and is also being used by the JPL Multimission Operations System Office (MOSO) as an integral part of Resource Allocation Team activities. Experience using the tool has helped to identify additional requirements that will further improve the planning process, which can be met by future PC4CAST versions.

Loyola, S. J.↗

JESNET Expert Assistant

The Johnson Space Center Engineering and Science Network (JESNET) supports the JSC Engineering and Space and Life Sciences Directorates by providing a network of interconnected ETHERNETS with a wide diversity of processing and routing nodes throughout the Johnson Space Center and off-site contractor locations. The JESNET provides the primary method of communication between the various computers that support the Directorates. Lockheed Engineering and Sciences Co. (LESC) is tasked with the operation and maintenance of certain primary portions of this network. Since maintenance of this network depends on the timely identification and subsequent repair of problems on the network, the decision was made to develop a JESNET Expert Assistant (JEA) to assist LESC personnel in the operation and maintenance of the JESNET. The JEA is being implemented in CLIPS, DEC Graphical Kernal System (GKS(TM)) and C on a DEC MicroVAX(TM) with VMS(TM).

Hansen, Roger F.↗

A Method for Making Cross-Comparable Estimates of the Benefits of Decision Support Technologies for Air Traffic Management

We present a general method for making cross comparable estimates of the benefits of NASA-developed decision support technologies for air traffic management, and we apply a specific implementation of the method to estimate benefits of three decision support tools (DSTs) under development in NASA's advanced Air Transportation Technologies Program: Active Final Approach Spacing Tool (A-FAST), Expedite Departure Path (EDP), and Conflict Probe and Trial Planning Tool (CPTP). The report also reviews data about the present operation of the national airspace system (NAS) to identify opportunities for DST's to reduce delays and inefficiencies.

Lee, David↗

Quantifying Pilot Contribution to Flight Safety During Dual Generator Failure

Accident statistics cite flight crew error in over 60% of accidents involving transport category aircraft. Yet, a well-trained and well-qualified pilot is acknowledged as the critical center point of aircraft systems safety and an integral safety component of the entire commercial aviation system. No data currently exists that quantifies the contribution of the flight crew in this role. Neither does data exist for how often the flight crew handles non-normal procedures or system failures on a daily basis in the National Airspace System. A pilot-in-the-loop high fidelity motion simulation study was conducted by the NASA Langley Research Center in partnership with the Federal Aviation Administration (FAA) to evaluate the pilot's contribution to flight safety during normal flight and in response to aircraft system failures. Eighteen crews flew various normal and non-normal procedures over a two-day period and their actions were recorded in response to failures. To quantify the human's contribution, crew complement was used as the experiment independent variable in a between-subjects design. Pilot actions and performance when one of the flight crew was unavailable were also recorded for comparison against the nominal two-crew operations. This paper details diversion decisions, perceived safety of flight, workload, time to complete pertinent checklists, and approach and landing results while dealing with a complete loss of electrical generators. Loss of electrical power requires pilots to complete the flight without automation support of autopilots, flight directors, or auto throttles. For reduced crew complements, the additional workload and perceived safety of flight was considered unacceptable.

Etherington, Timothy J.↗

IMPACT Concept of Operations

NASA’s future exploration missions mandate a significant paradigm change for mission planning, spacecraft design, human systems integration, and in-flight medical care due to constraints on mass, volume, power, resupply missions, and medical evacuation capabilities. These constraints require further development of the human health and performance system, which includes the medical, task performance, wellness, data, human and other systems necessary to keep the crew healthy and functioning optimally. The human health and performance system will be tightly integrated with mission and habitat design to provide a sufficient human health and performance infrastructure to enable mission success. A suite of systems engineering tools will aid in the decision making process for the development of such a human health and performance system. This Concept of Operations provides a vision for a tool suite to conduct evaluations of human health and performance system options, inform research prioritization, and provide trade study support, based on evidence, risks, and systems engineering principles. The integrated tool suite under development is IMPACT.

Lumpkins, Sara↗

Fast Determination of Distribution-Connected PV Impacts Using a Variable Time-Step Quasi-Static Time-Series Approach: Preprint

The increasing deployment of distribution-connected photovoltaic (DPV) systems requires utilities to complete complex interconnection studies. Relatively simple interconnection study methods worked well for low penetrations of photovoltaic systems, but more complicated quasi-static time-series (QSTS) analysis is required to make better interconnection decisions as DPV penetration levels increase. Tools and methods must be developed to support this. This paper presents a variable-time-step solver for QSTS analysis that significantly shortens the computational time and effort to complete a detailed analysis of the operation of a distribution circuit with many DPV systems. Specifically, it demonstrates that the proposed variable-time-step solver can reduce the required computational time by as much as 84% without introducing any important errors to metrics, such as the highest and lowest voltage occurring on the feeder, number of voltage regulator tap operations, and total amount of losses realized in the distribution circuit during a 1-yr period. Further improvement in computational speed is possible with the introduction of only modest errors in these metrics, such as a 91 percent reduction with less than 5 percent error when predicting voltage regulator operations.

14 SOLAR ENERGY↗