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DOE OSTI2023

Uncertainty Quantification of PV Annual Energy Estimates in the System Advisor Model

This work will detail a proposed uncertainty quantification method for PV annual energy estimates. Motivations behind the proposed methodology will be discussed, including the frequent underperformance of installed PV systems to calculated probability of exceedance values being seen in industry. A methodology in which uncertainty factors correlated to different parts of the PV annual energy model chain are applied to annual energy estimates in conjunction with uncertainty from inter-annual solar resource variability will be described. The application of this methodology in the System Advisor Model (SAM) will also be discussed with example cases and graphical outputs of the probability of exceedance data calculated for the PV annual energy estimates.

energy modeling↗

DOE OSTI2020

The hidden value of large-rotor, tall-tower wind turbines in the United States

The significant upscaling of wind turbine size (nameplate capacity, rotor diameter, and tower height) has, to date, been driven primarily by a goal of minimizing the levelized cost of energy. But with wind’s levelized cost of energy now comparable with that of other generating resources, other design considerations besides cost-minimization have grown in importance—particularly as wind’s increasing market penetration begins to impose challenges on the electric grid. We find that taller towers and larger rotors (relative to nameplate capacity) can enhance the value of wind energy to the electricity system and provide other “hidden” benefits. Specifically, in regions where wind penetration has reached around 20%, we find a boost in wholesale market value of US$2–US$3/MWh. This is augmented by transmission, balancing, and financing benefits that sum to roughly US$2/MWh. The aggregate potential value enhancement of US$4–US$5/MWh is comparable with a 10%–15% reduction in levelized costs.

17 WIND ENERGY↗

DOE OSTI2024

A Strategic Condition Framework for Energy Innovation

Building upon previous work in innovation, technology, and economic fields, we propose a conceptual framework to address the interplay dynamics of public policy and the value chains of clean energy technology innovation systems, by focusing on market structural and strategic conditions in relation to the rate and direction of knowledge diffusion within activity-based value chains. Our framework extends beyond socio-technical transition models by considering such nuances as: 1) the implications of geography, 2) the locus of knowledge types, 3) the dynamics of financial and knowledge flow, and 4) emphasizing the importance of both market structure and institutional conditions. At the firm level, we consider dynamics of interactions between suppliers and customers, innovation activities, the competitive environment, and the firm’s broader strategic relationship to governance activities and structures; we allow for the fact that each of these aspects of a firm’s identity may have a strategically relevant geographic dimension (e.g., service territories, locational concentration of input resources, etc.). We provide a proof-of-concept application of the U.S. utility-scale solar photovoltaic (PV) and onshore wind sectors, including their interactions with the U.S. power market, which we in present in a web-based information platform (Energy I-SPARK, ei-spark.lbl.gov).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Lighting controls: not just for lighting anymore!

For the last few years, networked lighting controls (NLCs) have promised significant energy savings beyond what is achieved through a basic LED retrofit. At the same time, NLCs can substantially increase the cost and complexity of the lighting retrofit. And as lighting system wattage declines because of the increasing efficiency of LEDs, advanced controls have less lighting energy to save and the cost-effectiveness of the NLC investment decreases. But NLCs can be leveraged to achieve significant energy savings and value by enhancing control of other building systems. Integrating NLC with control of heating, ventilation and air conditioning (HVAC), plug load control, space utilization, and grid services all enhance the value of your NLC investment. There are already a few NLC products on the market that are capable of providing these enhanced benefits. Manufacturers and entrepreneurs are working hard to expand the impact of these products. But does system interoperability work? Can it be deployed at scale? Slipstream, NEEA and Pacific Northwest National Laboratory (PNNL) have all been attempting to answer these questions in recent pilot projects and describe the outcomes in this paper.

Hackel, Scott↗

DOE OSTI2022

Multistage Surface-Heated Vacuum Membrane Distillation Process Enables High Water Recovery and Excellent Heat Utilization: A Modeling Study

Surface-heated membrane distillation (MD) enhances the energy efficiency of desalination by mitigating temperature polarization (TP). However, systematic investigations of larger scale, multistage, surface-heated MD system with high water recovery and heat recycling are limited. Here, we explore the design and performance of a multistage surface-heated vacuum MD (SHVMD) with heat recovery through a comprehensive finite difference model. In this process, the latent heat of condensation is recovered through an internal heat exchanger (HX) using the retentate from one stage as the condensing fluid for the next stage and an external HX using the feed as the condensing fluid. Model results show that surface heating enhances the performance compared to conventional vacuum MD (VMD). Specifically, in a six-stage SHVMD process, 54.44% water recovery and a gained output ratio (GOR) of 3.28 are achieved with a surface heat density of 2000 W m –2 , whereas a similar six-stage VMD process only reaches 18.19% water recovery and a GOR of 2.15. Mass and energy balances suggest that by mitigating TP, surface heating increases the latent heat trapped in vapor. The internal and external HXs capture and reuse the additional heat, which enhances the GOR values. We show for SHVMD that the hybrid internal/external heat recovery design can have GOR value 1.44 times higher than that of systems with only internal or external heat recovery. Furthermore, by only increasing six stages to eight stages, a GOR value as high as 4.35 is achieved. The results further show that surface heating can reduce the energy consumption of MD for brine concentration. As a result, the multistage SHVMD technology exhibits a promising potential for the management of brine from industrial plants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

On the role of Battery Energy Storage Systems in the day-ahead Contingency-Constrained Unit Commitment problem under renewable penetration

The integration of variable Renewable Energy Sources (vRES) to alleviate greenhouse gas emissions has introduced significant challenges for power systems operations. These challenges include high levels of uncertainty due to the intermittence associated with vRES and therefore impose the need to devise a reliable and cost-effective day-ahead unit commitment and power and reserves scheduling for real-time operations. Also, this increasing penetration of vRES requires higher ramping capabilities from units originally designed for other purposes (e.g., base-load generation), which might be exacerbated during contingency states. Hence, in this work, we propose a methodology to address the day-ahead Contingency-Constrained Unit Commitment (CCUC) problem that leverages the participation of Battery Energy Storage Systems (BESSs) to address load-following and post-contingency management, therefore alleviating the ramping burden on conventional thermal generators. To do so, we formulate a three-level optimization problem that represents the decision-making process of obtaining the least-cost commitment, generation and reserves scheduling, while restricting the Conditional Value-at-Risk (CVaR) of the system imbalance at real-time operations to user-defined tolerance levels. In addition, we devise a computationally efficient solution approach for the proposed problem based on the Column-and Constraint Generation (CCG) algorithmic framework. Two numerical experiments are conducted to empirically illustrate the benefits of the proposed methodology. Key results indicate a reduction in real-time ramping needs and a better usage of the system resources, with a reduction in the overall system commitment levels and reserve scheduling costs when compared to a benchmark case in which storage is not available.

Moreira, Alexandre↗

DOE OSTI2021

A Bayesian Framework for Milling Stability Prediction and Reverse Parameter Identification

This paper describes a physics-guided Bayesian framework for identifying the milling stability boundary and system parameters through iterative testing. Prior uncertainties for the parameters are identified through physical simulation and literature reviews, without physical testing of the actual milling system. Those uncertainties are then propagated to the stability map using a physics-based stability model, which is used to suggest a test point. The uncertainties are updated based on the new information acquired from the cutting test to form a new probability distribution, called the posterior. Finally, the posterior are compared to measured values for the stability boundary and system parameters to evaluate the approach. Based on experimental observations, the advantages and disadvantages of using a physics-guided model are discussed.

Cornelius, Aaron↗

DOE OSTI2020

Engineered Barrier System R&D and International Collaborations – LANL (FY20): Spent Fuel and Waste Disposition

The United States Department of Energy’s Spent Fuel and Waste Disposition (SFWD) program is investigating the design and safety function of generic nuclear geologic repositories in a variety of geologic settings (salt, argillite, and crystalline rock). Different configurations and loadings of spent nuclear fuel and waste within disposal canisters are also being investigated, some of which have the potential to generate repository temperatures higher than previously considered (i.e., temperatures >100ºC) by foreign and domestic concepts. This report expands on engineered barrier material stability in a high temperature crystalline rock repository through high temperature hydrothermal experiments. Experiments were designed to develop engineered barrier system (EBS) concepts in a hightemperature crystalline environment in 1) bentonite-Grimsel Granodiorite interactions, 2) bentonite-cement reactions, and 3) interaction between waste canister materials and bentonite. Experiment results are applied to understanding long-term repository performance in terms of radionuclide isolation. One hydrothermal experiment was completed in the rocking autoclaves at LANL in FY-20: IEBS-6 (Grimsel Granodiorite + Wyoming bentonite + cured ordinary Portland cement + Grimsel Granodiorite synthetic groundwater, 250ºC/150 bar, 8 weeks). Several other experiments were planned but were delayed due to the COVID-19 pause in laboratory work. In addition, some characterization of the reaction products of experiments conducted in FY-20 was prevented by COVID-19. Mineral phase chemistry was not measured via electron microprobe analyses for IEBS-6. Quantitative X-ray diffraction results from IEBS-6 and HBT-1 were not completed. The missing analyses and discussion of the results will be included in next year’s report. New characterization that was completed includes scanning electron microscopy of reaction products from IEBS-6, quantitative X-ray diffraction results are presented from IEBS-1 through IBES-5, preliminary scanning electron microscope images and chemical analyses for IEBS-6, X-ray diffraction of the clay fraction from all experiments, measurement/imaging of mineral growth on the surface of steel coupons. Major observations pertaining to bentonite stability in a Grimsel Granodiorite environment include the stability of Na-montmorillonite at 250°C, the formation of trace CSH phases, and the formation of bentonite colloids on experiment cooling. The addition of a cured chip of Portland cement to the bentonite-Grimsel system results in slightly higher pH values and the formation of diverse secondary mineral phases that were not observed in the previous experiments (e.g., analcime, garronite, CSH phases). The new characterization efforts related to the interaction of stainless-steel coupons and bentonite clay focused on thickness and mineralogy of phases that formed at the steel surface. In Wyoming bentonite + Grimsel Granodiorite systems, newly formed minerals at the bentonitesteel coupon interface included alteration of the outermost steel edge to Fe,Cr-oxide phases, followed by Fe-rich phyllosilicates (Fe-saponite, chlorite) and interbedded Fe,Cr,Ni-sulfide phases (pentlandite). Hydrothermal experiments were completed to assess uranium-carbonate complexation at conditions relevant to high-temperature disposal. Autoclave solubility experiments were conducted at 150 to 250ºC with a range of carbonate and uranium concentrations. The experiment results were characterized via situ UV-Visible spectroscopy and synchrotron-based in situ XAS techniques. Results show a significant decrease in the stability of uranyl-carbonate complexes at temperatures above 100ºC along with the precipitation of uranium oxides. Further, at T > 200ºC, results show that uranyl-hydroxyl complexes control solubility of uranium instead of the previously predicted uranyl-carbonate species. These results are significant for understanding the mobility of uranium in the EBS, which will likely contain carbonate-rich fluids. International research efforts focused on three main areas: 1) participation in international conferences, 2) building collaborations with foreign repository programs, and 3) the initiation of an experimental program to complement the full-scale HotBENT test at the Grimsel test site. This experiment included Wyoming bentonite + low carbon steel + Grimsel Granodiorite synthetic groundwater and was run at the planned maximum temperature of the HotBENT test (200°C). Complete characterization of reaction products was hindered by disruptions to laboratory work but will be reported in the next FY. The experimental results obtained in FY-20 continue to document the wide-ranging effects of bulk composition and pressure-temperature conditions in the mineralogical and geochemical evolution of a high-temperature repository environment. Concepts developed will be used to inform models of long-term material stability in a generic crystalline rock-hosted repository.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Effect of H 2 O on the ethylene glycol/alkali dismantling of bagasse for high-value conversion

Using a high-boiling alcohol system to dismantle main components of biomass is a feasible technology. Reducing dismantle operating costs and improving dismantle efficiency are essential for promoting the green, economical, and sustainable development of biomass refining. Therefore, based on the low cost and chemical properties of H 2 O at high temperature, the effects of different H 2 O dosages in NaOH-catalyzed ethylene glycol (HBAA) system on the dismantling efficiency of bagasse, surface lignin coverage, recovered-lignin activity and enzymatic hydrolysis efficiency were investigated. Compared with the HBAA dismantling system without H 2 O, the HBAA system with 60% w/v H 2 O can obviously increase the removal rates of lignin and hemicellulose, while recovering up to 99% of cellulose and significantly declining surface lignin coverage, thus enhancing the enzymatic hydrolysis efficiency. Additionally, the results of density functional theory calculations and 2D HSQC NMR analysis prove that the synergy between H 2 O and ethylene glycol can promote the esterification reaction occurrence at the α-C carbon cation in β-O-4 structure of lignin, thereby protecting the β-O-4 aromatic ether bond. Simultaneously, when the H 2 O dosage increase from 0% to 60%, the enzymatic yield increases from 84.51% to 93.74% with an enzyme load of 10 FPU/g. Based on experimental results, this study conducted a techno-economic analysis of bagasse dismantling for ethanol and co-production of lignin, achieving a minimum ethanol selling price of $\$$1.07 per kg. Here, in this study, a green and economical solution for dismantling the main components of bagasse is developed, which is important for the high-value conversion of bagasse.

Ethylene glycol↗

DOE OSTI2024

Saturation and Recurrence of Quantum Complexity in Random Local Quantum Dynamics

Quantum complexity is a measure of the minimal number of elementary operations required to approximately prepare a given state or unitary channel. Recently, this concept has found applications beyond quantum computing—in studying the dynamics of quantum many-body systems and the long-time properties of anti–de Sitter black holes. In this context, Brown and Susskind [] conjectured that the complexity of a chaotic quantum system grows linearly in time up to times exponential in the system size, saturating at a maximal value, and remaining maximally complex until undergoing recurrences at doubly exponential times. In this work, we prove the saturation and recurrence of complexity in two models of chaotic time evolutions based on (i) random local quantum circuits and (ii) stochastic local Hamiltonian evolution. Our results advance an understanding of the long-time behavior of chaotic quantum systems and could shed light on the physics of black-hole interiors. From a technical perspective, our results are based on establishing new quantitative connections between the Haar measure and high-degree approximate designs, as well as the fact that random quantum circuits of sufficiently high depth converge to approximate designs. Published by the American Physical Society 2024

Oszmaniec, Michał (ORCID:0000000249466835)↗

DOE OSTI2023

Investigation of Theoretical Solutions to a Bottom-Raised Oscillating Surge Wave Energy Converter (OSWEC) Through Experimental and Parametric Studies

Experiments were conducted on a wave tank model of a bottom raised oscillating surge wave energy converter (OSWEC) model in regular waves. The OSWEC model shape was a thin rectangular flap, which was allowed to pitch in response to incident waves about a hinge located at the intersection of the flap and the top of the supporting foundation. Torsion springs were added to the hinge in order to position the pitch natural frequency at the center of the wave frequency range of the wave maker. The flap motion as well as the loads at the base of the foundation were measured. The OSWEC was modeled analytically using elliptic functions in order to obtain closed form expressions for added mass and radiation damping coefficients, along with the excitation force and torque. These formulations were derived and reported in a previous publication by the authors. While analytical predictions of the foundation loads agree very well with experiments, large discrepancies are seen in the pitch response close to resonance. These differences are analyzed by conducting a sensitivity study, in which system parameters, including damping and added mass values, are varied. The likely contributors to the differences between predictions and experiments are attributed to tank reflections, standing waves that can occur in long, narrow wave tanks, as well as the thin plate assumption employed in the analytical approach.

analytical↗

DOE OSTI2025

Benchmarking thermal energy storage cost for industrial process heat

Process heat accounts for roughly half of industrial energy demand, and currently 95% of process heat is derived from the combustion of natural gas, oil, and coal. Electrification of industrial heating could be an alternative, potentially expanding locations suitable for manufacturing; however, industrial facility owners may desire energy storage to stabilize energy costs. In this work, the economic benefits of pairing thermal storage with electrified process heat to reduce the average price paid for energy are analyzed. Cost savings focus on energy arbitrage, or leveraging flexible energy pricing schemes, alone. The cost of natural gas combustion across decades (2019-2060) is compared to the costs of electricity and thermal energy storage in four United States Independent System Operator (ISO) regions. Systems installed today may not yield positive net present value (NPV) compared to the use of natural gas. However, using estimated electricity prices, systems installed in 2030 using arbitrage alone could be profitable when compared to natural gas in some regions of the U.S. Furthermore, if capital expenditures could be reduced by 50% for sensible thermal storage systems by 2030, profitable systems are found across all regions. This implies that electrification of industrial process heat, when paired with inexpensive thermal energy storage systems, could be less expensive than brownfield natural gas systems, using arbitrage as the only source of revenue and without a dependency on any future policy drivers such as pricing externalities that could further incentivize the electrification of industrial process heat.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Matrix Completion Using Alternating Minimization for Distribution System State Estimation

This paper examines the problem of state estimation in power distribution systems under low-observability conditions. The recently proposed constrained matrix completion method which combines the standard matrix completion method and power flow constraints has been shown to be effective in estimating voltage phasors under low-observability conditions using single-snapshot information. However, the method requires solving a semidefinite programming (SDP) problem, which becomes computationally infeasible for large systems and if multiple-snapshot (time-series) information is used. This paper proposes an efficient algorithm to solve the constrained matrix completion problem with time-series data. This algorithm is based on reformulating the matrix completion problem as a bilinear (non-convex) optimization problem, and applying the alternating minimization algorithm to solve this problem. This paper proves the summable convergence of the proposed algorithm, and demonstrates its efficacy and scalability via IEEE 123-bus system and a real utility feeder system. This paper also explores the value of adding more data from the history in terms of computation time and estimation accuracy.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2020

Remote Hardware-in-the-Loop Approach for Microgrid Controller Evaluation: Preprint

Utilities have been installing microgrids due to the advancements in the distributed energy resources technologies. Microgrids also improve the resiliency of the system due to their capability to isolate themselves from the grid and run in islanded mode of operation. Microgrid controllers are management systems that can run the microgrids under varied operating condition and enable the smooth operation of microgrids under various system conditions. It is of high value to de-risk the installation of such controllers. Hardware-in-the-loop evaluation is used by controller developers and utilities to evaluate the controllers under stressful conditions to understand the performance and to understand the necessary improvements to the microgrid controller. In this research work, the team has leveraged the existing infrastructure of real-time simulation at the Energy Systems Integration Facility (ESIF) and the capability of the microgrid controller to control assets over the Internet Protocol (IP) to evaluate a university developed microgrid controller in an efficient and cost-effective manner. The full paper will provide the complete setup, the experimental use cases and the results. In this abstract, one use case will be expalined, and the results from the use case is provided.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Matrix Completion Using Alternating Minimization for Distribution System State Estimation: Preprint

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2021

Cyber-attack detection, localization, and neutralization for unmanned aerial vehicles

In some embodiments, an Unmanned Aerial Vehicle (“UAV”) system may be associated with a plurality of monitoring nodes, each monitoring node generating a series of monitoring node values over time that represent operation of the UAV system. An attack detection computer platform may receive the series of current monitoring node values and generate a set of current feature vectors. The attack detection computer platform may access an attack detection model having at least one decision boundary (e.g., created using a set of normal feature vectors a set of attacked feature vectors). The attack detection model may then be executed and the platform may transmit an attack alert signal based on the set of current feature vectors and the at least one decision boundary. According to some embodiments, attack localization and/or neutralization functions may also be provided.

Mestha, Lalit Keshav↗

DOE OSTI2020

Learning-Accelerated ADMM for Distributed DC Optimal Power Flow

We suggest a novel data-driven method to accelerate the convergence of Alternating Direction Method of Multipliers (ADMM) for solving distributed DC optimal power flow (DC-OPF) where lines are shared between independent network partitions. Using previous observations of ADMM trajectories for a given system under varying load, the method trains a recurrent neural network (RNN) to predict the converged values of dual and consensus variables. Given a new realization of system load, a small number of initial ADMM iterations is taken as input to infer the converged values and directly inject them into the iteration. We empirically demonstrate that the online injection of these values into the ADMM iteration accelerates convergence by a significant factor for partitioned 14-, 118-and 2848-bus test systems under differing load scenarios. The proposed method has several advantages: it maintains the security of private decision variables inherent in consensus ADMM; inference is fast and so may be used in online settings; RNN-generated predictions can dramatically improve time to convergence but, by construction, can never result in infeasible ADMM subproblems; it can be easily integrated into existing software implementations. While we focus on the ADMM formulation of distributed DC-OPF in this paper, the ideas presented are naturally extended to other distributed optimization problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Learning-Accelerated ADMM for Distributed DC Optimal Power Flow

We propose a novel data-driven method to accelerate the convergence of Alternating Direction Method of Multipliers (ADMM) for solving distributed DC optimal power flow (DC-OPF) where lines are shared between independent network partitions. Using previous observations of ADMM trajectories for a given system under varying load, the method trains a recurrent neural network (RNN) to predict the converged values of dual and consensus variables. Given a new realization of system load, a small number of initial ADMM iterations is taken as input to infer the converged values and directly inject them into the iteration. We empirically demonstrate that the online injection of these values into the ADMM iteration accelerates convergence by a significant factor for partitioned 14-, 118- and 2848-bus test systems under differing load scenarios. The proposed method has several advantages: it maintains the security of private decision variables inherent in consensus ADMM; inference is fast and so may be used in online settings; RNN-generated predictions can dramatically improve time to convergence but, by construction, can never result in infeasible ADMM subproblems; it can be easily integrated into existing software implementations. While we focus on the ADMM formulation of distributed DC-OPF in this paper, the ideas presented are naturally extended to other distributed optimization problems.

alternating direction method of multipliers↗