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At least 1,063 records · Page 59

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DOE OSTI2021

A Multi-Site Networked Hardware-in-Loop Platform for Evaluation of Interoperability and Distributed Intelligence at Grid-Edge

Electric power systems have experienced large increases in the number of intelligent, connected and controllable devices being deployed, leading to a high degree of distributed intelligence at the grid-edge. These devices, both utility-owned and consumer-owned, include but are not limited to: renewable generation sources, energy storage, remote switches, voltage regulators, and smart controllable loads such as electric vehicles. These new devices provide significant potential for increased operational flexibility that can be leveraged to achieve system reconfiguration, resiliency improvements, power quality improvements, and distribution system automation. However, there are two significant challenges that must be addressed before these assets can be leveraged for operations: interoperability and system level validation prior to deployment. Because of the complexity of distributed control systems, and their interactions with legacy centralized controls, a purely simulations-based approach for pre-deployment validation is not sufficient. It requires hardware-in-loop testing to emulate the operational hardware devices and evaluate their performance. Additionally, securely integrating multiple test facilities at utility operators and vendors might enable rapid scale-up of evaluation platforms, and remove the need for multiple expensive standalone installations. Presented in this paper, is the development of a multi-site evaluation platform that employs Advanced Distribution Management Systems (ADMS), distributed control devices, real-time hardware-in-loop assets, secure communication links, and protocol adapters. This platform uses standards-based approaches and open-source tools, and hence can serve as a template for other researchers and institutions to implement their multi-site evaluation frameworks for pre-deployment testing.

Essakiappan, Somasundaram↗

DOE OSTI2023

Continuum Damage Mechanics Modeling of High-Temperature Flaw Propagation: Application to Creep Crack Growth In 316H Standardized Specimens and Nuclear Reactor Components

Predicting creep crack growth (CCG) of flaws found during operation in high-temperature alloy components is essential for assessing the remaining lifetime of those components. While defect assessment procedures are available for this purpose in design codes, these are limited in their range of applicability. This study assesses the application of a local damage-based finite-element methodology as a more general technique for the prediction of CCG at high temperatures on a variety of structural configurations. Numerical results for stainless steel 316H, which are validated against experimental data, show the promise of this approach. This integration of continuum damage mechanics (CDM) based methodologies, together with adequate inelastic models, into assessment procedures can therefore inform the characterization of CCG under complex operating conditions, while avoiding excessive conservatism. This article shows that such modeling frameworks can be calibrated to experimental data and used to demonstrate that the degree of tri-axiality ahead of a growing creep crack affects its rate of growth. The framework is also successfully employed in characterizing CCG in a realistic reactor pressure vessel geometry under an arbitrary loading condition. These results are particularly relevant to the nuclear power industry for defect assessment and inspections as part of codified practices of structural components with flaws in high-temperature reactors.

42 ENGINEERING↗

DOE OSTI2021

One‐Pot Synthesis of Xanthone by Carbonylative Suzuki Coupling Reaction

Abstract Xanthone derivatives have a dibenzo‐y‐pyrone scaffold which has gained great interest in Medicinal Chemistry due to their diverse biological activities. Usually, its synthesis requires multi‐step synthetic routes using harsh conditions and high catalyst loadings. In this communication, we report for the first time a one‐pot synthesis of the xanthone scaffold based on a carbonylative Suzuki coupling. Iodophenol and (2‐methoxyphenyl)boronic acid were coupled under carbon monoxide, generated from a carbon monoxide surrogate. An experimental data‐based model was built to guide the reaction optimization. The optimized conditions were 1 mol% of a pincer complex as palladium catalyst, 5 equivalents of K 2 CO 3 as base, and DMF:water (7 : 3) as solvent. The robustness of the synthetic method, namely in terms of the reactants scope, was also evaluated. This approach provided the xanthone scaffold in high yields and provided a deep insight into the carbonylative Suzuki couplings.

Loureiro, Daniela R. P.↗

DOE OSTI2021

Stochastic pre-event preparation for enhancing resilience of distribution systems

Extreme weather events are the common causes for power supply interruptions and power outages in electrical distribution systems. Improving the distribution system and enhancing its resilience is becoming crucial due to the increased frequency of extreme weather events. Preparation and allocation of multiple flexible resources, such as mobile resources, fuel resources, and labor resources before extreme weather events can mitigate the effects of extreme weather events and enhance the resilience of power distribution systems. Here, in this paper, a two-stage stochastic mixed-integer linear programming (SMILP) is proposed to optimize the preparation and resource allocation process for upcoming extreme weather events, which leads to faster and more efficient post-event restoration. The objective of the proposed two-stage SMILP is to maximize the served load and minimize the operating cost of flexible resources. The first stage in the optimization problem selects the amounts and locations of different resources. The second stage considers the operational constraints of the distribution system and repair crew scheduling constraints. The proposed stochastic pre-event preparation model is solved by a scenario decomposition method, Progressive Hedging (PH), to ease the computational complexity introduced by a large number of scenarios. Furthermore, to show the impact of solar photovoltaic (PV) generation on system resilience, three types of PV systems are considered during a power outage and the resilience improvements with different PV penetration levels are compared. Numerical results from simulations on a large-scale (more than 10,000 nodes) distribution feeder have been used to validate the effectiveness and scalability of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

Pd-Catalyzed Aerobic Oxidation Reactions: Strategies To Increase Catalyst Lifetimes

Not provided.

Chemistry↗

DOE OSTI2025

Analytical Identification Method of Generalized Short‐Circuit Ratio Using Phasor Measurement Units

This paper introduces a novel analytical approach for the identification of the admittance matrix and the generalized short-circuit ratio (gSCR) in power systems integrated with renewable energy sources. The proposed method leverages voltage and current measurements from phasor measurement units (PMUs) to construct a least squares objective function, which is then solved using matrix calculus and partial derivatives. Unlike conventional optimization algorithms, this approach provides an analytical solution that substantially reduces data requirements, enabling the efficient and accurate identification of the gSCR with smaller datasets. Additionally, its fixed computational complexity allows for real-time updates as new data are collected, ensuring continuous refinement of the system of equations and enabling rapid, precise gSCR calculations. The method also exhibits strong robustness against measurement noise, making it well-suited for practical applications in dynamic power systems. The combination of reduced data requirements, real-time adaptability, noise robustness and fixed computational load establishes this method as a highly efficient and reliable tool for real-time power system stability analysis. Case studies on an EPRI 36-bus system demonstrate the method's effectiveness, highlighting its accuracy in closely matching true gSCR values, even under diverse disturbances and noisy conditions.

Han, Zelei [Hohai University, Nanjing (China)] (OR↗

DOE OSTI2021

Field validation of an actuated convergent-beam acoustic Doppler profiler for high resolution flow mapping

Abstract Energetic river and tidal flow environments feature complex hydrodynamic conditions. Conventional acoustic Doppler profiling instrumentation typically requires assumptions of flow homogeneity over the spatial scales of the divergent beam separation. This removes the ability to measure spatio-temporal variability within the flow. However, velocity variability within these spatial scales is often important in the design of structures and devices exposed to such flow, informing dynamic and peak hydrodynamic load predictions. The research presented outlines the development and testing of a flow measurement instrument consisting of multiple spatially-separated single beam acoustic Doppler profilers converging on a remote focal point, the location of which can be programmatically adjusted through actuation. This increases the spatial resolution at which remote field measurements can be made in energetic flow environments. Field testing of the instrument was conducted in a tidal channel at Sequim Bay Inlet, WA, USA. Results are compared with independent reference measurements made by a co-located, motion-corrected acoustic Doppler velocimeter. This comparison, across tidal velocities of 0.4–0.7 m s −1 , showed a mean velocity error of 0.5%–13.2% across nine sample locations within a 3.00 m × 2.25 m plane. To the authors’ knowledge, this is the first publication of flow velocity results from non-intrusive acoustic measurements at an off-axis, focal point location that features 3D positional control.

13 HYDRO ENERGY↗

DOE OSTI2020

A Novel AC to AC Wireless Power Transfer System for EV Charging Applications

In this paper, a novel ac to ac wireless power transfer (WPT) system is introduced for electric vehicle (EV) charging applications to reduce cost and design complexity. The presented wireless power transfer concept achieves unity power factor (UPF) on the grid-side by using a hybrid frequency ac / ac converter without an additional converter stage and closed loop control compared to the conventional systems. Due to inherent merit of the proposed ac / ac converter, ac input with 60 Hz grid frequency can be directly transferred to the load by superimposing with high frequency switching signal through the wireless coils. To validate the theoretical analysis of the proposed WPT system, the experimental results of the proposed converter are provided for 650 W output power by using 6 inches air gap between the couplers with the input of 110 VRMS ac source. The system overall efficiency is measured 89 % achieving 0.99 power factor (PF) and 1.5 % current total harmonic distortion (THD).

Asa, Erdem↗

DOE OSTI2019

A Distributed Energy Management Approach for Residential Demand Response

The implementation of large-scale optimization and control of residential appliances to support demand response (DR) programs comes with the challenges of coordinated communication, privacy, and consideration of customer preferences. Solving this complexity is best suited through a distributed optimization and control approach at the residential level by leveraging the availability and intelligence of a home energy management systems (HEMS). In this paper, a hierarchical control scheme to coordinate large-scale residential demand response through coordination of HEMs is proposed. This scheme is based on the exchange of a reward price and aggregated load information between utility system and HEMS. Numerical results on a one hundred-house model demonstrate the computational efficiency of the proposed approach.

Kou, Xiao↗

DOE OSTI2024

Biochar-compost-based controlled-release nitrogen fertilizer intended for an active microbial community

Nitrogen (N) fertilizers in agriculture suffer losses by volatilization of N to the air, surface runoff and leaching into the soil, resulting in low N use efficiency (NUE) (< 50%) and raising severe environmental pollutions. Controlled- release nitrogen fertilizers (CRNFs) can control the release of N nutrients to NUE in crop production. Different methods were used to develop new CRNFs. However, different CRNF technologies are still underdeveloped due to inadequate controlling on N releasing time and/or unsustainable diffusion. The study on the influences of CRNF processing parameters on microbial conditions are lacking when the CRNFs composed of various bio-ingredients such as biochar, composts, and biowaste. The complexity of processing methods, material biodegradability, and other physical properties make current CRNFs of questionable value in agricultural production. This research aims to develop a novel biochar-compost-based controlled-release urea fertilizer (BCRUF) to preserve microbial properties carried by the compost. The BCRUF was synthesized by pelletizing the 50:50 (dry, wt/wt) mixture of biochar and compost. BCRUF was loaded with urea and then spray-coated with polylactic acid (PLA). The releasing time of two types of BCRUFs, coated and uncoated with PLA, for 80% of N release in water was up to 6 h at three different temperatures (4, 23, and 40 °C), compared to conventional urea fertilizer and commercial environmentally smart N (ESN) fertilizer. The releasing time of coated BCRUF for 80% N release in soil was up to 192 h (8 days). Fourier-transform infrared spectroscopy (FTIR) analysis revealed that no new functional groups were found in the release solution, indicating no new chemical hazards generated. The differential scanning calorimetry (DSC) tests also verified that its thermal stability could be up to 160 °C. The microbe populations in the BCRUF pellets were reduced after the pelleting and drying processes in BCRUF fabrication, but a few bacteria can endure in the air-drying process. BCRUF pellets soaked in water for 4 days retained some bacteria. The BCRUF showed very promising characteristics to improve NUE and sustainability in agricultural production.

58 GEOSCIENCES↗

DOE OSTI2025

HP-FLEX: Field demonstration of the semantics-driven configuration of a Model Predictive Control system to make heat pumps flexible

Model Predictive Control (MPC) has demonstrated significant potential for optimizing building operations and enabling demand flexibility. However, the widespread adoption of MPC is hindered by complex manual configuration and commissioning processes that must be conducted by control experts working alongside building operators. These challenges drive up costs and reduce scalability, particularly when technical human resources and building automation systems are limited, such as in small and medium commercial buildings (SMCBs). This paper demonstrates how semantic standards, specifically ASHRAE 223P, can accelerate the adoption of MPC applications for load flexibility in SMCBs. The authors present a replicable control framework, titled “HP-FLEX” that leverages a building’s semantic model to bootstrap the required data configuration for an MPC controller developed for optimizing heat pump systems as flexible grid resources. The semantic model helps streamline the deployment workflow, particularly for site setup, data/control commissioning, and model setup. This integration enhances portability, transferability, and scalability of the HP-FLEX MPC, which has been developed to support MPC-based supervisory HVAC controllers in SMCBs. Additionally, the paper details the required building and thermostat metadata information to enable the HP-FLEX MPC based on field demonstrations. The new workflow was tested in a small commercial building located in California, U.S., and demonstrated a load shifting performance of 9% based on a dynamic pricing signal that varies by the hour. This work provides a practical pathway for transitioning sophisticated building applications from custom to standardized semantic representations, supporting the broader adoption of advanced control strategies like MPC. The framework also establishes a foundation for evolving metadata requirements as applications mature while maintaining compatibility with industry standards.

Paul, Lazlo↗

DOE OSTI2015

Investigation of the Effect of In-Plane Fiber Waviness in Composite Materials through Multiple Scales of Testing and Finite Element Modeling

Defects in materials can reduce strengths and lifetimes of manufactured parts. The number of possible defects increases with the complexity inherent in composite materials. The wind industry uses composite wind turbine blades in which the manufacturing process induces a number of defects. In order for the wind industry to continue sustainable expansion, the effects of defects must be better understood. In-plane (IP) fiber waviness is the focus of this work. The three main parts of this work include testing on the coupon level, modeling on the coupon level, and testing of beams in four-point bending (with and without defects). The coupon level testing includes partial IP waves, similar to those in manufactured parts, rather than full width IP waves. This allows investigation into complex interactions and varying failure mechanisms caused by the fiber misalignment gradient. Partial waves are also modeled to both validate testing as well as to increase robustness of a previously developed progressive damage modeling method. Lastly, a sandwich beam test specimen for testing in 4-point bending is developed to investigate the effects of fiber waviness in both tension and compression when loaded in flexure.

36 MATERIALS SCIENCE↗

DOE OSTI2025

HP-FLEX: Field Demonstration of the Semantics-Driven Configuration of a Model Predictive Control System to Make Heat Pumps Flexible

Paul, Lazlo↗

DOE OSTI2017

Radiological Shielding Design for the Neutron Backscattering Spectrometer EMU

In this paper we present modelling and design of compact radiation shielding required for operation of the EMU instrument, located at Australia's OPAL nuclear reactor. The acceptance criteria for the shielding design were (i) safety - dose rate ≤ 3 μSv/h at external surfaces of the instrument's experimental area, (ii) floor load limit < 20 tons/m{sup 2}, (iii) low cost and (iv) for maintenance purposes 'easy access' to components of the instruments. The EMU instrument is a cold neutron backscattering spectrometer designed to measure inelastic neutron scattering. Its distinctive feature is that it has a tight elastic energy transfer resolution, of about 1 μeV. The instrument provides unique opportunities to study diffusion in complex materials, e.g. water molecules in confinement, polymers or biological molecules, particularly in the Asia-Oceania region. EMU is the first instrument located on the CG3 neutron beam line of the OPAL Neutron Guide Hall (NGH). A pre-existing evacuated neutron guide of dimensions 200 mm (height) x 50 mm (width) feeds into the shared EMU/KOOKABURRA pre-monochromator bunker shielding assembly, and its bottom cross section will be intercepted ∼200 mm further in air by the highly orientated pyrolytic graphite (HOPG) EMU pre-monochromator (take-off angles from 125.4 deg. to 148 deg.). The bunker shielding assembly for EMU also contains a beryllium filter and Focusing Guide Section D (FGD, 170 mm (height) x 50 mm (width)). To accommodate the range of take-off angles Pb cylindrical shielding blocks of radius 140 mm and 500 mm height have been designed. These blocks will be located at the section of the bunker where the neutron beam will exit towards the experimental area and they will reside on top of a hollow steel base (sides 10 mm thick), on which they move by sliding and are integrated with the tertiary shutter. The experimental area is enclosed by a concrete wall of 2.5 m height and 300 mm thickness, shared with the KOOKABURRA instrument, Gyprock Plasterboard panels with viewing windows, a wall from the Out-of-Pile Bunker and the CG3 shielding. The neutron beam enters the experimental area via the tertiary shutter, into the Focusing Guide Section C (FGC), which has an entrance guide cross-section of 158 mm (height) x 79 mm (width) and exit guide cross-section of 149 mm (height) x 85 mm (width) and is of length 816 mm. The vacuum chamber of FGC will be connected to the vacuum chamber of the Background Chopper (BC, disc of outer radius 350 mm). Focusing Guide Section B (FGB) is aligned with FGC and its vacuum shared with the BC vacuum. The FGB has an exit guide cross section of 50 mm (height) x 49 mm (width) and is of length 4046 mm, which will focus the neutron beam vertically and horizontally towards the Al window entrance (0.82 mm thickness, labelled N16) of the Scattering Tank assembly (constructed from 20 mm - 40 mm thickness stainless steel and will be under vacuum < 1 x 10{sup -3} mbar). Inside the Scattering Tank there is another section of Focusing Guide (FGA), with an exit guide cross-section of 30 mm (height) 30 mm (width) and of length 417 mm. The neutron beam exiting the FGA will be reflected by the HOPG crystal pieces of the Graphite Chopper (GC) towards the Backscattering Monochromator (BM). The reflected neutron beam will first pass through the other Al window (0.82 mm thickness, labelled N17) of the Scattering Tank and then enter into a flight tube (steel of 10 mm thickness). The BM is formed in an 1800 mm spherical radius array of Si crystal elements (0.87 mm thickness) and is oscillated by the linear motor Doppler Drive. The neutron beam will be reflected back at 180 deg. from, and focussed by the BM to reenter the Scattering Tank through the N17 Al window. It will then pass through the GC (HOPG crystals are rotated out of the way) and will reach the scattering sample of interest to the instrument end user. Also, inside the Scattering Tank there will be {sup 3}He linear position-sensitive detectors, and Analyser Arrays formed in an 1800 mm radius spherical arrays of Si crystal elements (0.87 mm thickness) glued on aluminium support frames (10 mm thickness) and span ∼160 deg. arc.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Super Resolving Unrolled Neural Networks for Remote Sensing

In remote sensing systems, the capabilities of the system are constrained by the complex interactions between size, weight, and power (SWAP) of potential designs. In electro-optical (EO) systems, examples of these critical parameters include the system’s sensitivity and resolution. Those parameters can be increased by ever larger optical apertures and focal planes but at the cost of more SWAP. Multi-image super resolution (MISR) techniques allow resolution to be enhanced via computation rather than more sophisticated optical hardware. These algorithms combine multiple images together into a single, higher resolution image, trading temporal resolution and computation for spatial resolution. Fielded MISR techniques, such as Drizzle, can require several hundred images to create a single super resolved image, implying reduced temporal resolution, increased data acquisition load, and limiting mission applications. Iterative techniques, such as model-based image reconstruction and compressive sensing, have been shown to create super resolved images using fewer images than Drizzle. They do this by posing an optimization problem that balances accuracy between a highly accurate physical model and an image model. In the case of super resolution, the physical model is defined by the relation between low resolution input images and the desired high resolution output image. The image model encodes some assumptions about the super resolved image. These assumptions are meant to suppress reconstruction artifacts that arise due to deterministic physical model error, stochastic measurement noise, and potential undersampling. In practice, the performance of iterative methods are limited by imaging models compatible with optimization. Deep learning-based methods can effectively learn image models of arbitrary complexity, but lack the theoretical explainability and robustness of iterative techniques. Consensus equilibrium (CE) generalizes the iterative techniques beyond optimization, enabling blackbox algorithms such as traditional and neural image denoisers to be used as the image model. CE-based approaches retain much of the explainability and robustness of iterative techniques while allowing the expressiveness of machine learning image models to be used. Additionally, by unrolling iterations of CE with an embedded image denoiser, the image denoiser can be further trained and specialized to the specific application with potentially higher quality reconstructions. Under this project, we demonstrated the feasibility of training an unrolled neural network based upon CE. While we didn’t train one, we showed that the CE process is differentiable and its gradient can be tractably computed. We also explored the usage of a variants of CE akin to generative neural works. Most importantly, we applied the CE framework to a number of problems including non-blind deconvolution, upsampling, single-image super resolution, MISR, event-based sensing, and saturated deconvolution. Our MISR prototype creates high quality reconstructions with an order of magnitude fewer images than previous approaches and, critically, produces these reconstructions fast enough for practical usage.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Elastic wave suppression through additively manufactured petal lattice metamaterials

Lattice-core sandwich structure metamaterials are lightweight alternatives to monolithic materials that can present better mechanical, thermal, and energy dampening performance. Manufacturing lattice metamaterials to follow curved surfaces can pose a challenge, as the lattices rely on their geometric orientation to the substrate for their mechanical properties. This work rationally designed a lattice structure where the surface is broken up into “petals” connected to the underlying lattice, which localizes the petals’ impact response. This design opens a pathway for implementation of lattice-core sandwich structures onto complex surface geometries. These petal structures were evaluated for their energy absorption efficiency experimentally by utilizing pressure waves generated with nanosecond lasers and computationally via finite element modeling. The lattice structures exhibited a two-orders-of-magnitude decrease in transmitted pressure compared to their constituent steel at equivalent mass. Furthermore, localizing energy absorption into petal structures provided a 44% reduction in peak load compared to a continuous “single-petal” design.

Sarracino, Alex↗

DOE OSTI2014

Improving large-scale storage system performance via topology-aware and balanced data placement

With the advent of big data, the I/O subsystems of large-scale compute clusters are becoming a center of focus. More applications are putting greater demands on end-to-end I/O performance. These subsystems are often complex in design. They comprise of multiple hardware and software layers to cope with the increasing capacity, capability, and scalability requirements of data intensive applications. However, the sharing nature of storage resources and the intrinsic interactions across these layers make it a great challenge to realize end-to-end performance gains. This paper proposes a topology-aware strategy to balance the load across resources, to improve the per-application I/O performance. We demonstrate the effectiveness of our algorithm on an extreme-scale compute cluster, Titan, at the Oak Ridge Leadership Computing Facility (OLCF). Our experiments with both synthetic benchmarks and a real-world application show that, even under congestion, our proposed algorithm can improve large-scale application I/O performance significantly, resulting in both a reduction in application run time as well as a higher resolution of simulation run.

Wang, Feiyi↗

DOE OSTI2021

A Technical and Economic Assessment of LWR Flexible Operation for Generation and Demand Balancing to Optimize Plant Revenue

With increased penetration of subsidized variable renewable energy (VRE) resources and competition from low natural gas prices, existing light water reactor (LWR) nuclear power plants (NPPs) are struggling to remain economically competitive. This work examines the potential economic competitiveness of various thermal energy storage (TES) technologies when coupled directly or indirectly with a NPP. To highlight their relative economic competitiveness, we contrast several energy storage solutions in stochastic dispatch optimization. We leverage data from recent work analyzing a range of TES technologies with varying capital costs, performance, and technology readiness level (TRL) to establish our case. We explore inserting these technologies into an electricity market with existing nuclear generation and large projected variable renewable energy (VRE) penetration. Although these technologies' projected capital costs may make them unlikely candidates in their current state, this analysis demonstrates a high-fidelity techno-economic analysis of energy storage. Furthermore, as the projected cost of energy storage technologies evolves, this analysis sets a precedent for similar future investigations. One region with projected trends that may be unfavorable for existing nuclear capacity is the New York Independent System Operator (NYISO) market. New York state’s baseload generation has been historically provided by fossil-fired and nuclear assets. However, amid economic pressures from subsidized VREs and low natural gas prices, the state has recently deactivated Indian Point nuclear power plant units 2 and 3. Furthermore, the state plans to meet its zero-emission generation target by 2040 by replacing fossil-fired capacity with significant investments in VRE resources like wind and solar photovoltaic (PV) and battery storage. Increased intermittent resource penetration lowers the baseload power requirement, adding further economic pressure to the state’s three remaining NPPs still in operation. With three NPPs still in operation in New York, this work analyzes potential economic benefits to NPPs on the New York grid when directly or indirectly coupled with various TES technologies. This work requires two modeling steps to analyze the potential economic benefits of various system configurations of the TES directly or indirectly coupled with nuclear. First, this analysis leverages capacity expansion modeling by experts at the Electric Power Research Institute (EPRI). Using their deterministic capacity expansion model, U.S. Regional Economy, Greenhouse Gas, and Energy (US-REGEN), EPRI analysts evaluated the capacity and generation evolution of the New York state energy market under four projection scenarios. These four projection scenarios were developed to represent the potential evolution of the capacity and generation in NYISO from 2015 to 2050 under various economic, technology, and policy constraints. The results from these capacity expansion models are then used as boundary conditions in the second modeling step. The second modeling step uses the Holistic Energy Resource Optimization Network (HERON) for a set of stochastic techno-economic analyses (STEAs) to investigate the potential increase in the economic viability of various configurations of the TES. With no current capacity expansion capabilities, HERON takes the data generated from US-REGEN for 2050 to generate synthetic load, solar, and wind data. Then HERON economically optimizes the capacity and dispatch of the various TES configurations. The potential economic benefit is the differential net present value (NPV) of the TES configurations from the no-TES baseline. As a stochastic techno-economic analysis package, HERON introduces uncertainty into the economic metrics, while US-REGEN trades resolution for reduced computational complexity. Using HERON also allows the modeling of direct thermal coupling, a feature not common in capacity and dispatch models. As expected, with high capital costs, the costs of introducing energy storage for all the technologies considered outweighed the potential economic benefit of this strategy for flexible plant operation. The benefit of this analysis is primarily in demonstrating a workflow that examines innovative solutions to increase NPP revenue via TES coupling. HERON’s stochastic capacity and dispatch optimization process used in this work has proven an effective tool in observing and evaluating the impact of introducing storage technologies in a grid energy system.

25 ENERGY STORAGE↗