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At least 541 records · Page 30

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DOE OSTI2019

Co-optimized trading of hybrid wind power plant with retired EV batteries in energy and reserve markets under uncertainties

To be competitive in the electricity markets, various technologies have been reported to increase profits of wind farm owners. Combining battery storage system, wind farms can be operated as conventional power plants which promotes the integration of wind power into the power grid. However, high expenses on batteries keep investors away. Retired EV batteries, fortunately, still have enough capacity to be reused and could be obtained at a low price. In this work, a two-stage optimization of a wind energy retired EV battery-storage system is proposed. The economic performance of the proposed system is examined concerning its participation in the frequency containment normal operation reserve (FCR-N) market and the spot market simultaneously. To account uncertainties in the wind farm output, various electricity market prices, and up/down regulation status, a scenario-based stochastic programming method is used. The sizing of the equipment is optimized on top of daily operations of the hybrid system which formulates a mixed-integer linear programming (MILP) problem. Scenarios are generated with the Monte Carlo simulation (MCS) and Roulette Wheel Mechanism (RWM), which are further reduced with the simultaneous backward method (SBM) to increase computational efficiency. A 21 MW wind farm is selected as a case study. Here, the optimization results show that by integrating with a retired EV battery-storage system (RESS) and a bi-directional inverter, the wind farm can increase its profits significantly when forwarding bids in both of the aforementioned electricity markets.

17 WIND ENERGY↗

DOE OSTI2010

Scenario Analysis of Peak Demand Savings for Commercial Buildings with Thermal Mass in California

This paper reports on the potential impact of demand response (DR) strategies in commercial buildings in California based on the Demand Response Quick Assessment Tool (DRQAT), which uses EnergyPlus simulation prototypes for office and retail buildings. The study describes the potential impact of building size, thermal mass, climate, and DR strategies on demand savings in commercial buildings. Sensitivity analyses are performed to evaluate how these factors influence the demand shift and shed during the peak period. The whole-building peak demand of a commercial building with high thermal mass in a hot climate zone can be reduced by 30percent using an optimized demand response strategy. Results are summarized for various simulation scenarios designed to help owners and managers understand the potential savings for demand response deployment. Simulated demand savings under various scenarios were compared to field-measured data in numerous climate zones, allowing calibration of the prototype models. The simulation results are compared to the peak demand data from the Commercial End-Use Survey for commercial buildings in California. On the economic side, a set of electricity rates are used to evaluate the impact of the DR strategies on economic savings for different thermal mass and climate conditions. Our comparison of recent simulation to field test results provides an understanding of the DR potential in commercial buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2009

Angle of Attack Modulation for Mars Entry Terminal State Optimization

From the perspective of atmospheric entry, descent, and landing (EDL), one of the most foreboding destinations in the solar system is Mars due in part to its exceedingly thin atmosphere. To benchmark best possible scenarios for evaluation of potential Mars EDL system designs, a study is conducted to optimize the entry-to-terminal-state portion of EDL for a variety of entry velocities and vehicle masses, focusing on the identification of potential benefits of enabling angle of attack modulation. The terminal state is envisioned as one appropriate for the initiation of terminal descent via parachute or other means. A particle swarm optimizer varies entry flight path angle, ten bank profile points, and ten angle of attack profile points to find maximum-final-altitude trajectories for a 10 30 m ellipsled at 180 different combinations of values for entry mass, entry velocity, terminal Mach number, and minimum allowable altitude. Parametric plots of maximum achievable altitude are shown, as are examples of optimized trajectories. It is shown that appreciable terminal state altitude gains (2.5-4.0 km) over pure bank angle control may be possible if angle of attack modulation is enabled for Mars entry vehicles. Gains of this magnitude could prove to be enabling for missions requiring high-altitude landing sites. Conclusions are also drawn regarding trends in the bank and angle of attack profiles that produce the optimal trajectories in this study, and directions for future work are identified.

Lafleur, Jarret M.↗

NASA NTRS1990

Evaluating scheduling algorithms for traffic with heterogeneous performance objectives

Two types of network traffic are considered: traffic with deadlines, for which the most important performance objective is based on loss rate, and packets without deadlines, for which the most important performance objective is based on mean delay. An optimal scheduling algorithm is presented to minimize weighted loss rate and weighted mean delay in the queues that form at the switches and at the network access points of a packet-switched network, where weights reflect the relative importance of packets. Although not practical for implementation, the algorithm is intended as a standard for the comparison of the performance of other scheduling algorithms. The algorithm is more general and lower computational complexity than previously published algorithms, enabling performance evaluation of some important scenarios that could not previously have been considered. Using the optimal performance results of this algorithm, the performance of the first-come-first-served, static priority, and earliest deadline first scheduling algorithms is evaluated. The results suggest that network efficiency could be improved by using a more sophisticated heuristic scheduling algorithm rather than one of the aforementioned algorithms.

Peha, Jon M.↗

DOE OSTI2019

Best Practices for Wake Model and Optimization Algorithm Selection in Wind Farm Layout Optimization: Preprint

This paper presents the results of two case studies regarding the wind farm layout optimization problem. We asked a general audience to take part in the studies that we designed, and nine individuals participated. Case study 1 considered variations in optimization strategies for a given simple Gaussian wake model. Participants were provided with a wake model that outputs annual energy production (AEP) for an input set of wind turbine locations. Participants used an optimization method of their choosing to find an optimal wind farm layout. Case study 2 looked at trade-offs in performance resulting from variation in both physics model and optimization strategy. For case study 2, participants calculated AEP using a wake model of their choice while also implementing their chosen optimization method. Participants then used their wake model to calculate the AEP all other participant submitted turbine configurations produce for cross-comparison results. for optimized turbine locations were then cross-compared by recalculating the AEP using every other participant's wake model. Results for case study 1 show that the best optimal wind farm layouts in this study were achieved by participants who used gradient-based optimization methods. A front-runner emerged with the Sparse Nonlinear OPTimizer plus Wake Expansion Continuation (SNOPTplusWEC) optimization method, which consistently discovered a higher AEP for each scenario. Results for case study 2 show that for small wind farms with few turbines, turbine placement on the wind farm boundary is superior. Conclusions for case study 2 were drawn from participant cross-comparison of results.

17 WIND ENERGY↗

DOE OSTI2019

Best Practices for Wake Model and Optimization Algorithm Selection in Wind Farm Layout Optimization

17 WIND ENERGY↗

DOE OSTI2025

Robust A-Optimal Experimental Design for Sensor Placement in Bayesian Linear Inverse Problems

Optimal design of experiments for Bayesian inverse problems has recently gained wide popularity and attracted much attention, especially in the computational science and Bayesian inversion communities. An optimal design maximizes a predefined utility function that is formulated in terms of the elements of an inverse problem, an example being optimal sensor placement for parameter identification. The state-of-the-art algorithmic approaches following this simple formulation generally overlook misspecification of the elements of the inverse problem, such as the prior or the measurement uncertainties. This work presents an efficient algorithmic approach for designing optimal experimental design schemes for Bayesian linear inverse problems such that the optimal design is robust to misspecification of elements of the inverse problem. Specifically, we consider a worst-case scenario approach for the uncertain or misspecified parameters, formulate robust objectives, and propose an algorithmic approach for optimizing such objectives. Furthermore, both relaxation and stochastic solution approaches are discussed with detailed analysis and insight into the interpretation of the problem and the proposed algorithmic approach. Extensive numerical experiments to validate and analyze the proposed approach are carried out for sensor placement in a parameter identification problem.

Bayesian inverse problems↗

DOE OSTI2018

Optimal Control of Connected and Automated Vehicles at Roundabouts: An Investigation in a Mixed-Traffic Environment

Connectivity and automation in vehicles provide the most intriguing opportunity for enabling users to better monitor transportation network conditions and make better operating decisions to improve safety and reduce pollution, energy consumption, and travel delays. This paper investigates the implications of optimally coordinating vehicles that are wirelessly connected to each other in roundabouts to achieve a smooth traffic flow. We apply an optimization framework and an analytical solution that allows optimal coordination of vehicles for merging in such traffic scenario. The effectiveness of the proposed approach is validated through simulation and it is shown that fully coordinated vehicles reduce total travel time by 51% and fuel consumption by 35%. Furthermore, we study the influence of vehicle coordination in a mixed-traffic environment and compare the network performance under different market penetration rates of connected and automated vehicles (CAVs). For this particular study with near-capacity demand, high penetration of CAVs is necessary to ensure an efficient and effective control, due to extremely unstable traffic.

Zhao, Liuhui↗

DOE OSTI2018

Search for gauge-mediated supersymmetry in events with at least one photon and missing transverse momentum in pp collisions at s = 13 TeV

A search for gauge-mediated supersymmetry (SUSY) in final states with photons and large missing transverse momentum is presented. The data sample of pp collisions at $\sqrt{s} = $ 13 TeV was collected with the CMS detector at the CERN LHC and corresponds to an integrated luminosity of 35.9 fb$^{-1}$. Data are compared with models in which the lightest neutralino has bino- or wino-like components, resulting in decays to photons and gravitinos, where the gravitinos escape detection. The event selection is optimized for both electroweak (EWK) and strong production SUSY scenarios. The observed data are consistent with standard model predictions, and limits are set in the context of a general gauge mediation model in which gaugino masses up to 980 GeV are excluded at 95% confidence level. Gaugino masses below 780 and 950 GeV are excluded in two simplified models with EWK production of mass-degenerate charginos and neutralinos. Stringent limits are set on simplified models based on gluino and squark pair production, excluding gluino (squark) masses up to 2100 (1750) GeV depending on the assumptions made for the decay modes and intermediate particle masses. This analysis sets the highest mass limits to date in the studied EWK models, and in the considered strong production models when the mass difference between the gauginos and the squarks or gluinos is small.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2016

Synergetic Effects of Alcohol/Water Mixing on the Catalytic Reductive Fractionation of Poplar Wood

One of the foremost challenges in lignocellulose conversion encompasses the integration of effective lignin valorization in current carbohydrate-oriented biorefinery schemes. Catalytic reductive fractionation (CRF) of lignocellulose offers a technology to simultaneously produce lignin-derived platform chemicals and a carbohydrate-enriched pulp via the combined action of lignin solvolysis and metal-catalyzed hydrogenolysis. Herein, the solvent (composition) plays a crucial role. In this contribution, we study the influence of alcohol/water mixtures by processing poplar sawdust in varying MeOH/water and EtOH/water blends. The results show particular effects that strongly depend on the applied water concentration. Low water concentrations enhance the removal of lignin from the biomass, while the majority of the carbohydrates are left untouched (scenario A). Contrarily, high water concentrations favor the solubilization of both hemicellulose and lignin, resulting in a more pure cellulosic residue (scenario B). For both scenarios, an evaluation was made to determine the most optimal solvent composition, based on two earlier introduced empirical efficiency descriptors (denoted LFDE and LFFE). According to these measures, 30 (A) and 70 vol % water (B) showed to be the optimal balance for both MeOH/water and EtOH/water mixtures. This successful implementation of alcohol/water mixtures allows operation under milder processing conditions in comparison to pure alcohol solvents, which is advantageous from an industrial point of view.

09 BIOMASS FUELS↗

DOE OSTI2022

Wetter California Projected by CMIP6 Models With Observational Constraints Under a High GHG Emission Scenario

As the world's fifth-largest economy entity, California (CA) is vulnerable to climate changes especially the magnitude of winter (wet season) precipitation that is closely linked to regional drought severity, vegetation growth, and wildfire activities. However, the fate of CA precipitation in the future remains highly uncertain, for example, the state-of-the-art Earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) projected –3% to +42% and –27% to +63% precipitation changes in northern and central-southern CA, respectively, under the high greenhouse gas (GHG) emission scenario (SSP585). In this work, we applied the Pareto optimality concept and used observed teleconnection patterns (causal relationships between ocean regions and CA precipitation) to mechanistically constrain CMIP6 projected CA precipitations. We estimated that precipitation will robustly increase by 0.4–1.3 mm d –1 (10–34%) over northern CA and increase by 0.1–0.5 mm d –1 (7–32%) over central-southern CA by the end of the 21st century compared with present-day. Up to 71% of ESM projection uncertainties were reduced mainly due to the strong and consistent causal relationship between North American west coast sea level pressure and CA precipitation in both observations and CMIP6 models. Our results suggest that teleconnection patterns are powerful mechanistic constraints that can help explain and reduce uncertainties in ESM projections.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Proactive Operations and Investment Planning via Stochastic Optimization to Enhance Power Systems’ Extreme Weather Resilience

We present scalable stochastic optimization approaches for improving power systems’ resilience to extreme weather events. We consider both proactive redispatch and transmission line hardening as alternatives for mitigating expected load shed due to extreme weather, resulting in large-scale stochastic linear programs (LPs) and mixed-integer linear programs (MILPs). We solve these stochastic optimization problems with progressive hedging (PH), a parallel, scenario-based decomposition algorithm. Our computational experiments indicate that our proposed method for enhancing power system resilience can provide high-quality solutions efficiently. With up to 128 scenarios on a 2,000-bus network, the operations (redispatch) and investment (hardening) resilience problems can be solved in approximately 6 min and 2 h of wall-clock time, respectively. Additionally, we solve the investment problems with up to 512 scenarios, demonstrating that the approach scales very well with the number of scenarios. Moreover, the method produces high quality solutions that result in statistically significant reductions in expected load shed. Our proposed approach can be augmented to incorporate a variety of other operational and investment resilience strategies, or a combination of such strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

System Design of Dynamic Wireless Power Transfer for Automated Highways

Dynamic wireless power transfer (DWPT) has been proposed as a solution to power electric vehicles (EVs)on future electrified highways. However, there has been little consideration of how the coordination of electric connected and automated vehicles (CAVs) could impact DWPT system designs in future scenarios. In this paper, a DWPT system design is optimized for a future highway where CAVs travel in coordinated groups, with each CAV in the group powered by the same DWPT section. As the distribution of smaller light-duty vehicles (LDVs) and larger heavy-duty vehicles (HDVs) in each group is varied, the DWPT system power level, transmitter length, and the equivalent receiver loads are adjusted to minimize the infrastructure requirements and energy losses of the DWPT system. The outputs from this analysis are used to determine the optimal groupings of vehicles for a given DWPT system. The analysis suggests that CAV coordination could aid the deployment of DWPT systems and reduce the overall infrastructure and energy losses of DWPT systems.

Foote, Andrew↗

DOE OSTI2014

SU-E-J-81: Interplay Effect in Non-Gated Dynamic Treatment Delivery of a Lung Phantom with Simulated Respiratory Motion

Purpose: To quantify the interplay effect in non-gated VMAT external beam delivery using realistic, clinically relevant 3D motion in an anthropomorphic lung phantom, and to determine if adding margins is sufficient to account for motion or if gating is required in all cases. Methods: A 4D motion stage was used to move a Virtual Water (VW) lung target containing a piece of radiochromic EBT3 film in an anthropomorphic chest phantom. A five-arc stereotactic body radiation therapy (SBRT) treatment was planned using a CT scan of the phantom in its stationary position, using planning parameters chosen to push the optimizer to achieve a highly-modulated plan. Two scenarios were delivered using a Varian TrueBeam: the first was delivered with the phantom and target both stationary and the second was delivered with the phantom stationary but the target moving in a realistic, irregular 3D elliptical pattern. A single piece of 4×4 cm{sup 2} film was used per fraction, located in the central coronal plane of the target. Film was calibrated on a 6 MV beam with dose values from 0.20 to 20 Gy. Results: Preliminary test films were analyzed in ImageJ and MatLab software. Dose maps were calculated on a central region of interest (ROI) delineated on both the motion-induced and stationary films. Both static and dynamic film dose maps agreed with planning values within acceptable uncertainty. Conclusion: Including a large number of arcs in a clinically realistic SBRT treatment could reduce the effect of motion interplay due to averaging. Because all clinics do not employ multiple arcs for SBRT lung treatments, it is still important to consider the effects of motion on treatment delivery. Further analysis on the treatment films, as well as a broader investigation other planning parameters, will be conducted.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

GreenThrift: Optimizing Carbon and Cost for Flexible Residential Loads

Reducing buildings’ carbon emissions is an important sustainability challenge. While scheduling flexible building loads has been previously used for a variety of grid and energy optimizations, carbon footprint reduction using such flexible loads poses new challenges since such methods need to balance both energy and carbon costs while also reducing user inconvenience from delaying such loads. This paper highlights the potential conflict between electricity prices and carbon emissions and the resulting trade-offs in carbon-aware and cost-aware load scheduling. To address this trade-off, we propose GreenThrift, a home automation system that leverages the scheduling capabilities of smart appliances and knowledge of future carbon intensity and cost to reduce both the carbon emissions and costs of flexible energy loads. At the heart of GreenThrift is an optimization technique that automatically computes schedules based on user configurations and preferences. We evaluate the effectiveness of GreenThrift using real-world carbon intensity data, electricity prices, and load traces from multiple locations and across different scenarios and objectives. Our results show that GreenThrift can replicate the offline optimal and retains 97% of the savings when optimizing the carbon emissions. Moreover, we show how GreenThrift can balance the conflict between carbon and cost and retain 95.3% and 85.5% of the potential carbon and cost savings, respectively.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2013

Studies of anisotropy of iron based superconductors

To study the electronic anisotropy in iron based superconductors, the temperature dependent London penetration depth, Δλ(T), have been measured in several compounds, along with the angular dependent upper critical field, H c2 (T). Study was undertaken on single crystals of Ba(Fe 1-x Co x ) 2 As 2 with x=0.108 and x=0.127, in the overdoped range of the doping phase diagram, characterized by notable modulation of the superconducting gap. Heavy ion irradiation with matching field doses of 6 T and 6.5 T respectively, were used to create columnar defects and to study their effect on the temperature Δλ(T). The variation of the low-temperature penetration depth in both pristine and irradiated samples was fitted with a power-law function Δλ(T) = AT n . Irradiation increases the magnitude of the pre-factor A and decreases the exponent n, similar to the effect on the optimally doped samples. This finding supports the universal s ± scenario for the whole doping range.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2018

Energy-Water Nexus Knowledge Discovery Framework, Experts’ Meeting Report

Energy and water generation and delivery systems are inherently interconnected. With worldwide demandfor energy growing, the energy sector is experiencing increasing competition for water. With increasingpopulation and changing environmental, socioeconomic, and demographic scenarios, new technology andinvestment decisions must be made for optimized and sustainable energy-water resource management. These decisions require novel scientific insights into the complex interdependencies of energy-water infrastructures across multiple space and time scales.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2016

Optimized Finite-Difference Coefficients for Acoustic Modeling.

Although using standard Taylor series coefficients for finite-difference operators is optimal in the sense that in the limit of infinitesimal space and time discretization, the solution approaches the correct analytic solution to the acousto-dynamic system of differential equations, other finite-difference operators may provide optimal computational run time given certain error bounds or source bandwidth constraints. This report describes the results of investigation of alternative optimal finite-difference coefficients based on several optimization/accuracy scenarios and provides recommendations for minimizing run time while retaining error within given error bounds.

58 GEOSCIENCES↗