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To support NYPA's efforts in delivering a feasibility study to advise PANYNJ on future distributed energy resource (DER) deployments at their facilities.
We examine the UV/X-ray properties of 1378 quasars in order to link empirical correlations to theoretical models of the physical mechanisms dominating quasars as a function of mass and accretion rate. The clarity of these correlations is improved when (1) using C IV broad emission line equivalent width (EQW) and blueshift (relative to systemic) values calculated from high signal-to-noise ratio reconstructions of optical/UV spectra and (2) removing quasars expected to be absorbed based on their UV/X-ray spectral slopes. In addition to using the traditional C IV parameter space measures of C IV EQW and blueshift, we define a "C IV ∥ distance" along a best-fit polynomial curve that incorporates information from both C IV parameters. We find that the C IV ∥ distance is linearly correlated with both the optical-to-X-ray slope, α ox , and broad-line He II EQW, which are known spectral energy distribution indicators, but does not require X-ray or high spectral resolution UV observations to compute. The C IV ∥ distance may be a better indicator of the mass-weighted accretion rate, parameterized by L/L Edd , than the C iv EQW or blueshift alone, as those relationships are known to break down at the extrema. Conversely, there is only a weak correlation with the X-ray energy index (Γ), an alternate L/L Edd indicator. We find no X-ray or optical trends in the direction perpendicular to the C IV distance that could be used to reveal differences in accretion disk, wind, or corona structure that could be widening the C IV EQW–blueshift distribution. A different parameter (such as metallicity) not traced by these data must come into play.
This report documents the design and evaluation of an integrated online-learning pipeline developed within the AdCyDER project for Distributed Energy Resource (DER) cybersecurity. The pipeline couples a Reinforcement Learning (RL) attack classifier — which produces an attack-type probability distribution — with a Stackelberg game-theoretic (GT) defense selector that consumes those distributions alongside SME-encoded priors over (defense, attack) effectiveness pairings and perdefense costs to choose grid-health-preserving defenses. The objective is not attack classification per se but production of distributions that drive effective defense selection through the Stackelberg layer, learned from delayed grid-health feedback rather than labeled attack data. AdCyDER as a whole is broader than the work presented here; this report covers the specific RL/GT loop integration and its evaluation. We present the integrated pipeline (SCADA telemetry with Fronius inverter physics, Suricata IDS, time-windowed aggregation, per-facility LSTM classifier, Stackelberg optimizer, OpenC2 actuators), an experimental campaign of 28 eight-hour iterations across three baseline modes, and a pipeline-ordered diagnostic protocol. The protocol identifies two distinct failure modes within the loop: paired supervised ceilings on the same features establish that the deployed online RL classifier (macro F1 ≈ 0.07) sits at least 4.7× below a same-architecture supervised LSTM (≈ 0.34) and 10–11× below a linear feature-signal ceiling (≈ 0.70–0.79 depending on per-facility isolation), localizing the dominant failure to the training procedure; and the reward signal driving online updates carries weak directional coupling with classifier correctness in the methodology-expected direction (multi-lens convergent: top-decile P(true) records produce more frequent state changes and slightly larger improvements, top-vs-bot Cohen’s 𝑑 ≈ −0.19), but at effect magnitudes too small to drive gradient-based learning at the campaign sample size. The original learning hypothesis is not supported by the data. The primary contributions are the diagnostic methodology — proposed as a transferable falsification protocol for online RL/GT defense pipelines learning from delayed environmental reward — and the open, reproducible experimental infrastructure. We outline reward reformulation as the highest-priority aspirational next step given the underpowered-but-aligned Q6 reading, with hardware-in-the-loop evaluation as the broadest scope-expansion option.
While computer systems, software applications, and operational technology (OT)/Industrial Control System (ICS) devices are regularly updated through automated and manual processes, there are several unique challenges associated with distributed energy resource (DER) patching. Millions of DER devices from dozens of vendors have been deployed in home, corporate, and utility network environments that may or may not be internet-connected. These devices make up a growing portion of the electric power critical infrastructure system and are expected to operate for decades. During that operational period, it is anticipated that critical and noncritical firmware patches will be regularly created to improve DER functional capabilities or repair security deficiencies in the equipment. The SunSpec/Sandia DER Cybersecurity Workgroup created a Patching Subgroup to investigate appropriate recommendations for the DER patching, holding fortnightly meetings for more than nine months. The group focused on DER equipment, but the observations and recommendations contained in this report also apply to DERMS tools and other OT equipment used in the end-to-end DER communication environment. The group found there were many standards and guides that discuss firmware lifecycles, patch and asset management, and code-signing implementations, but did not singularly cover the needs of the DER industry. This report collates best practices from these standards organizations and establishes a set of best practices that may be used as a basis for future national or international patching guides or standards.
Climate change has resulted in increasingly impactful and more frequent occurrences of extreme weather events. This trend poses a significant challenge for distribution utilities and system operators to ensure that there is uninterrupted power supply to critical loads in their networks under fault scenarios; however, currently, utilities deploying the automated fault location, isolation and restoration (FLISR) function in their advanced distribution management system (ADMS) do not take into account the available generation and load-modification capabilities of distributed energy resources present in the disconnected network due to an upstream isolated fault. This results in the network reconfiguration and restoration to result in sub-optimal load restoration. Therefore, this paper presents two approaches that can upgrade the existing FLISR capabilities of distribution utilities to significantly increase the restoration of critical loads. The performance of the proposed approaches is evaluated on a numerical model of a real distribution feeder in Georgia, USA.
Climate change has resulted in increasingly impactful and more frequent occurrences of extreme weather events. This trend poses a significant challenge for distribution utilities and system operators to ensure that there is uninterrupted power supply to critical loads in their networks under fault scenarios; however, currently, utilities deploying the automated fault location, isolation and restoration (FLISR) function in their advanced distribution management system (ADMS) do not take into account the available generation and load-modification capabilities of distributed energy resources present in the disconnected network due to an upstream isolated fault. This results in the network reconfiguration and restoration to result in sub-optimal load restoration. Therefore, this paper presents two approaches that can upgrade the existing FLISR capabilities of distribution utilities to significantly increase the restoration of critical loads. The performance of the proposed approaches is evaluated on a numerical model of a real distribution feeder in Georgia, USA.
Equitable and automated bottoms-up power restoration following an extreme event will be demonstrated at a site in Puerto Rico. To do so, the team will develop enhanced grid situational awareness techniques integrating behind-the-meter (BTM) distributed energy resources (DER) discovery, impedance sweeping based outage boundary detection, and feasible restoration path identification algorithms. Resilience metric will be developed and incorporated along with situational awareness information in a distributed Model Predictive Control (MPC)-based restoration optimization algorithm to control and mobilize grid assets. These algorithms will be validated through power hardware-in-the-loop experiments and ultimately, a site demonstration to show that outage recovery time and total recovered load could be improved by >20% over the baseline.
Hospitals, emergency services, military bases, ports, airports, industries, commercial facilities, and others rely on backup power systems to provide electricity for their critical loads during grid outages. The purpose of this report it to provide accurate reliability information on commonly deployed distributed energy resources (DERs) to improve quantitative estimates for the reliability of these backup power systems during a grid outage. A backup power system consists of DERs, an electric distribution system with its associated switches and other devices, and mechanisms to control and manage the flow of electricity. Too often, facilities and campuses fail to properly quantify the reliability of their backup power systems. DERs are assumed to be 100% reliable, with the only concern being the availability of fuel. Such assumptions can lead to gross errors in the backup system's reliability estimates, particularly for long-duration outages. This report provides a set of estimates for reliability of emergency diesel generators (EDGs), natural gas prime generators and combined heat and power (CHP) prime movers, solar photovoltaics (PV), wind turbines, and Li-ion battery energy storage systems (BESS). The estimates are derived from empirical data when available and supplemented by modeling results when needed. These reliability estimates are for the DERs ability to provide power during a grid outage, ranging from an hour to 2 weeks.
This document is a technical report based on a large-scale DOE-funded project conducted between 2019 and 2022. The project, called SOLAr Critical infrastructure Energization (SOLACE), is aimed at leveraging distributed energy resources (DERs) to provide local power to communities, feeders, or other regions. The project included a particular focus on high-value critical loads such as municipal water supply, telecommunication hubs, and disaster shelters. The key developments of the project were: (1) A comprehensive pre-event power system analysis methodology that identifies and characterizes the viable local power options. (2) A DMS-based example control system for activating and operating the local power solution during a time of crisis. (3) Grid-forming inverter technology to enable isolated local power operation and black-starting. (4) Cyber-security considerations for isolated systems when wider-area communication may be offline. This report describes the overall process that identifies and assesses the viable DER-based local power solutions for a given facility, region, or community. The report documents the process, including the key analysis steps, tools required, data requirements, and recommended pass/fail criteria for each step. It also provides a sample implementation of this process through a test case. Finally, it provides details of how a viable pre-event plan can be selected and activated at go-time when an event has occurred.
Portland International Airport (PDX), Oregon, operated by the Port of Portland (Port) is exploring the possibility of operating a fleet of 28 fuel cell electric buses and developing a distributed energy system to support airport operations during various operating modes including large-scale power outages. This study investigates the compatibility of these two missions, which will be key to resilience management at PDX. This study also investigated the risks associated with deploying a hydrogen system that could support bus operations and be utilized during an emergency to ensure continued operation of the airport. This will be a key innovation for the deployment of hydrogen systems at airports. Utilizing the unique benefits of hydrogen infrastructure for multiple roles will aid adopters in justifying new projects and serve to demonstrate the versatility of hydrogen as an energy-carrier to a wider market.
To unravel the dominant cause of the weak emission line in a subset of optically selected radio-quiet ‘weak emission line quasars’ (WLQs), we have investigated the possibility of an underdeveloped broad line region (BLR). For this, we have modelled spectral energy distributions (SED) of 61 WLQs by using their optical and infrared (IR) photometric observations from Sloan Digital Sky Survey (SDSS) and WISE, respectively. SED fit consists of various emission components, including the luminosity from the dusty torus (L tor ). For comparison with the normal quasar, we have used a control sample of 55 Quasi-Stellar Objects (QSOs) for each WLQ matching in emission redshift and SDSS r-band. Based on our measurement of L tor , we found a decrement of 42 ± 2 per cent in IR luminosity in WLQs with respect to the control sample of normal QSOs. Using L tor /L bol as the measure of torus covering factor (CF tor ), we found a similar decrement in WLQ covering factor, with their CF tor distribution being significantly different with respect to the normal QSOs with a KS test P null of 4.27 × 10 −14 . As dusty torus and BLR covering factors are expected to be of a similar order in active galactic nucleus (AGN), our results suggest that the BLR in the WLQs is underdeveloped and could be a dominant cause of the weakness of their emission line. As a result, our analysis gives support to the models of WLQs based on the evolution scenario being in an early stage of AGNs.
Integrated planning holds the promise of unlocking lower total system cost solutions by connecting previously siloed planning processes. This article summarizes the state of bulk and local grid planning today and details multiple new analytical approaches that can enable more holistic planning methods to develop comprehensive solutions to generation, transmission, distribution, and distributed energy resource needs. These include both iterative approaches as well as cooptimization techniques. In addition to the benefits of these methods, the technical and institutional challenges and associated solutions are also discussed.
We describe a new instrument, the Argonne Auger Radioisotope Microscope (ARM), capable of characterizing the Auger electron (AE) emission of radionuclides, including candidates relevant in nuclear medicine. Our approach relies on event-by-event ion–electron coincidence, time-of-flight, and spatial readout measurement to determine correlated electron multiplicity and energy distributions of Auger decays. We present a proof-of-principle measurement with the ARM using x-ray photoionization of stable krypton beyond the K-edge and identify a bifurcation in the electron multiplicity distribution depending on the emission of K-LX electrons. Extension of the ARM to the characterization of radioactive sources of AE emissions is enabled by the combination of two recent developments: (1) cryogenic buffer gas beam technology to introduce Auger emitters into the detection region with well-defined initial conditions, and (2) large-area micro-channel plate detectors with multi-hit detection capabilities to simultaneously detect multiple electrons emitted in a single decay.
The combination of increased electric load growth across all sectors, deferred electrical infrastructure investment, and other factors resulting in variable electric power supply, has created technical challenges to maintaining a resilient and reliable grid. Many federal, regional, and local efforts are in play to modernize the electric grid, including advancing building technologies and distributed energy resources (DERs) that are utilizing smarter controls to become responsive to both occupant and grid needs. This report reviews ten pilot projects demonstrating how groups of buildings combined with behind-the-meter (BTM) DERs such as electric vehicle (EV) charging, battery storage, flexible HVAC and domestic hot water systems, and photovoltaic systems can reliably and cost effectively provide grid services. Each of the ten pilot projects aim to deliver both energy efficiency and demand flexibility (DF) while supporting load growth. The ten demonstration teams are piloting flexible DER packages across diverse communities of residential and commercial buildings to address a variety of regional grid needs. The outcomes of these pilot projects will be used to inform future scaling through utility program development. This paper characterizes the ten teams, showcasing the decision-making process used by each group to develop their packages (Section 2), the grid services they plan to deliver (Section 3), the types of DER packages selected for deployment within building sectors (Section 4) and trends between building sector, DER types, and grid services In order to achieve community scale benefits, the pilot projects must utilize aggregated control mechanisms for coordinating buildings and DERs together. Several types of coordinated control architectures have evolved amongst the teams, influenced by use type, existing market conditions, and integration type. Three coordinated controls architectures have been characterized, highlighting their use cases, benefits, challenges, and tradeoffs in their design. These insights can aid utilities, control vendors, and developers in scaling community-level energy systems (Paul, 2024). Ultimately, the technology packages selected by the ten teams will be coordinated to provide power system services, also known as grid services. Insights from these demonstrations will be useful for grid operators, regulators, aggregators and other stakeholders as they look to deploy demand flexible resources as grid services in the future. The grid services that each team is targeting for demonstration are described in Section 3 and Section 4. Methods for evaluating the grid services have been described in the paper Metrics for Evaluating Grid Service Provision from Communities of Grid-interactive and Efficient Buildings and other DER (MacDonald, 2023). To identify technology packages for demonstration, Section 2 shows that project teams used a range of analysis approaches, including building energy modeling, AMI data analysis, cost-benefit frameworks, and utility pilot data. Some teams emphasized technical modeling to quantify grid impacts and demand reduction potential, while others prioritized economic evaluations, stakeholder input, or exploratory pilots to inform deployment decisions. This diversity reflects the need to tailor selection methods to project goals, available data, and organizational context. Section 5 discusses trends between the DER technologies deployed and the grid service provisions from each team. Residential buildings (multifamily and single family) lean towards technologies that enhance energy efficiency (e.g. weatherization upgrades, smart thermostats) and onsite power generation integration (e.g. solar PV). Commercial building demonstrations prioritize technologies that ensure operational reliability (e.g. battery storage) and centralized energy management systems and optimization solutions. Teams that are deploying controllable storage-based technologies are more likely to provide grid services that require a near real-time response. Teams incorporating load shifting technologies like smart thermostats with HEMs are likely to include energy markets participation and customer bill management offerings. Campus demonstrations are adopting diverse sets of DERs to emphasize renewable generation, paired with centralized control. This section also describes technologies that were considered during project planning but ultimately excluded from final deployment. These demonstrations reveal that effective DER package design should be tailored to building type, customer segment, and construction vintage. Multifamily buildings benefit from centralized HVAC upgrades and supervisory controls, while single-family homes are well-suited for individualized technologies like solar, storage, and smart home energy monitors. Commercial and campus settings prioritize EMIS integration and load optimization. New construction enables cost-effective integration of DER-ready infrastructure, whereas retrofits require deployments aligned with owner and tenant value streams. For utility program planners, early coordination with developers and building owners, paired with segmented and modular program offerings, can improve adoption, scalability, and grid impact.
As the number of connected devices in the energy grid increase exponentially, so too are the cybersecurity risks. With the development of modern communications standards such as 5G and beyond the extent to which devices will continue to connect will continue to increase exponentially along with the inherent risks. However, 5G also includes features to help address cybersecurity concerns and therefore helping to mitigate many of these risks. This paper proposes a new service-based network architecture implementing network-slicing capabilities for connected systems and devices to improve performance, availability, security, and reliability of the grid devices and services. This paper considers the quality of service requirements and criticality of services needed for securely monitoring, operating, and securing Distributed Energy Resource (DER) devices. From developed use cases, network slicing is implemented based on these requirements and resource allocations. This work then highlights examples of how slicing can help prevent standard existing attack methods such as a denial-of-service or similar attack which limits resource availability and network bandwidth to the service and thus limiting its ability to affect other services by misbehaving. The designed network architecture use case will be further tested on a local virtualized testbed to verify secure operation and availability of services. Using hardware-in-the-loop devices and systems on this local testbed, this fully segmented, secure network may be realized and evaluated. Finally, this paper presents the results of this testing.
Active galactic nuclei (AGN) are typically identified through their distinctive X-ray or radio emissions, mid-infrared (MIR) colors, or emission lines. However, each method captures different subsets of AGN due to signal-to-noise (S/N) limitations, redshift coverage, and extinction effects, underscoring the necessity for a multiwavelength approach for comprehensive AGN samples. This study explores the effectiveness of spectral energy distribution (SED) fitting as a robust method for AGN identification. Using CIGALE optical-MIR SED fits on DESI Early Data Release galaxies, we compare SED-based AGN selection (AGNFRAC ≥ 0.1) with traditional methods including BPT diagrams, WISE colors, X-ray, and radio diagnostics. The SED fitting identifies ∼70% of narrow- and broad-line AGN and 87% of WISE-selected AGN. Incorporating high S/N WISE photometry reduces star-forming galaxy contamination from 62% to 15%. Initially, ∼50% of SED-AGN candidates are undetected by standard methods, but additional diagnostics classify ∼85% of these sources, revealing low-ionization nuclear emission-line regions and retired galaxies potentially representing evolved systems with weak AGN activity. Further spectroscopic and multiwavelength analysis will be essential to determine the true AGN nature of these sources. SED fitting provides complementary AGN identification, unifying multiwavelength AGN selections. This approach enables more complete – albeit somewhat contaminated – AGN samples, which are essential for upcoming large-scale surveys where spectroscopic diagnostics may be limited.
Recent advances in the chemical process industry have allowed for the intensification of reactors and unit operations, by enhancing heat and mass transfer or combining multiple unit operations. Process intensification can enable chemical plants to be constructed in a more compact, modular fashion, offering improvements over conventional on-site approaches to capital construction, operations and maintenance. This modular chemical process intensification (MCPI) offers several benefits over conventional stick-built (CSB) plant construction in terms of reduced footprint, reduced energy consumption, lower cost, less waste and improved safety and quality control. However, acceptance of MCPI over CSB construction practices within the chemical industry can be impeded by the uncertain risks associated with investing in new technology. Furthermore, the work here documents a case study during the development of a modular chemical plant for capturing distributed energy resources within chemical production. This MCPI approach to plant construction is contrasted with a CSB approach for producing the same chemical product. Data collection tools were developed, based on a literature review, and data was collected from the technology developer to understand the process technology. Sensitivity analysis was then conducted to analyze the business rationale for the application of MCPI over CSB across several market scenarios. It was found that MCPI would be better suited for capacities up to 150 000 metric tons per year, but that improvement in payback period was needed. Additionally, for MCPI approach to achieve acceptable payback periods, efforts are needed to reduce the cost of capital equipment and compress the schedule for ramping up modular production.
Direct dynamics calculations have been performed for three reactions: C 3 H 8 + H → i-C 3 H 7 + H 2 , C 3 H 8 + H → n-C 3 H 7 + H 2 , and C 2 H 3 + O 2 → HCO + CH 2 O. The fraction of the population for the radical products that promptly dissociates is computed. Here the results for C 3 H 8 + H are qualitatively similar to previous results for C 3 H 8 + OH, but the new results exhibit a slightly higher branching fraction for prompt dissociation products, owing to the fact that a greater fraction of the internal energy in the transition state ends up in the radical. For C 2 H 3 + O 2 → HCO + CH 2 O, the fraction of HCO that promptly dissociates is in excess of 99%. Consequently, the main product for C 2 H 3 + O 2 at lower temperatures should be written as H + CO + CH 2 O and not HCO + CH 2 O. These results are then compared with four previous systems: CH 2 O + H → HCO + H 2 , CH 2 O + OH → HCO + H 2 O, C 3 H 8 + OH → i-C 3 H 7 + H 2 O, and C 3 H 8 + OH → n-C 3 H 7 + H 2 O. Based upon these seven system, several statistical models are presented. The goal of these statistical models is to predict the fraction of the transition state energy that ends up in the rovibrationally excited radical. On average, these statistical models provide an excellent prediction of product energy distribution. Consequently, these models can be used instead of costly trajectory simulations for predicting prompt radical dissociation for larger species.