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At least 451 records · Page 25

User-Preference-Driven Model Predictive Control of Residential Building Loads and Battery Storage for Demand Response: Preprint

This paper presents a user-preference-driven home energy management system (HEMS) for demand response (DR) with residential building loads and battery storage. The HEMS is based on a multi-objective model predictive control algorithm, where the objectives include energy cost, thermal comfort, and carbon emission. A multi-criterion decision making method originating from social science is used to quickly determine user preferences based on a brief survey and derive the weights of different objectives used in the optimization process. Besides the residential appliances used in the traditional DR programs, a home battery system is integrated into the HEMS to improve the flexibility and reliability of the DR resources. Simulation studies have been performed on field data from a residential building stock data set. Appliance models and usage patterns were learned from the data to predict the DR resource availability. Results indicate the HEMS was able to provide a significant amount of load reduction with less than 20% prediction error in both heating and cooling cases.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Implementation and Integration of a Finite Element Model into the Bone Remodeling Model to Characterize Skeletal Loading

NASA's Digital Astronaut Project is developing a bone physiology model to predict changes in bone mineral density over the course of a space mission. The model intends to predict bone loss due to exposure in microgravity as well as predicting bone maintenance due to mechanical stimulus generated by exercise countermeasures. These predictions will be used to inform exercise device efficacy and to help design exercise protocols that will maintain bone mineral density during long exposures to microgravity during spaceflight. The mechanical stimulus and the stresses that are exhibited on the bone are important factors for bone remodeling. These stresses are dependent on the types of exercise that are performed and vary throughout the bone due to the geometry. A primary area of focus for bone health is the proximal femur. This location is critical in transmitting loads between the upper and lower body and have been known to be a critical failure point in older individuals with conditions like osteoporosis.

bone mineral content↗

A Sample/Jitter Monte Carlo Technique for Main Parachute Loads Predictions

Models for Orion parachute performance are based on reconstructions of the Capsule Parachute Assembly System (CPAS) drop test campaign and were documented in the CPAS “Model Memo.” Experience with similar Commercial Crew Program (CCP) parachute systems resulted in some updates to the Orion models in preparation for Artemis missions. The reefing cutter dispersion model for the drogues and mains had been overly-conservative by producing wide timing differences within clusters. A higher-fidelity timing model was generated by separating out in-lot variation and temperature effects. The main parachute inflation model had accounted for some correlations between parameters using complicated 2-D geometric bounding, but the results tended to exaggerate individual peak loads from fast (leading) inflations and under-emphasize actual lagging experience. Several flight tests were reconstructed again with an emphasis on matching peak load magnitudes using a search algorithm. A simpler method for generating inflation parameters uses the 3-D correlated reconstructed “samples” with some random “jitter” applied. Dispersed Monte Carlo inputs are then checked against flight test data to evaluate whether they represent reality.

parachutes↗

SINDA-NASTRAN interfacing program theoretical description and user's manual

The task of converting SINDA finite difference thermal model temperature results into NASTRAN finite element model thermal loads can be very labor intensive if there is not one node-to-one element, or systematic node-to-element. correlation between models. This paper describes the SINDA-NASTRAN Interfacing Program (SNIP), a FORTRAN computer code that generates NASTRAN structural model thermal load cards given by SINDA (or similar thermal model) temperature results and thermal model geometric data. SNIP generates NASTRAN thermal load cards for NASTRAN plate, shell, bar, and beam elements. The paper describes the interfacing procedures used by SNIP, and discusses set-up and operation of the program. Sample cases are included to demonstrate use of the program and show its performance under a variety of conditions. SNIP can provide structural model thermal loads that accurately reflect thermal model results while reducing the time required to interface thermal and structural models when compared to other methods.

Winegar, Steven R.↗

How good are learning-based control v.s. model-based control for load shifting? Investigations on a single zone building energy system

Both model predictive control (MPC) and deep reinforcement learning control (DRL) have been presented as a way to approximate the true optimality of a dynamic programming problem, and these two have shown significant operational cost saving potentials for building energy systems. Furthermore, there is still a lack of in-depth quantitative studies on their approximation levels to the true optimality, especially in the building energy domain. To fill in the gap, this paper provides a numerical framework that enables the evaluation of the optimality levels of different controllers for building energy systems. This framework is then used to comprehensively compare the optimal control performance of both MPC and DRL controllers with given computation budgets for a single zone fan coil unit system. Note the optimality is estimated based on a user-specific selection of trade-off weights among energy costs, thermal comfort and control slew rates. Compared with the best optimality we can find through expensive optimization simulations, the best DRL agent can maximally approximate the optimality by 96.54%, which outperforms the best MPC whose optimality level is 90.11%. However, due to the stochasticity, the DRL agent is only expected to approximate the optimality by 90.42%, which is almost equivalent to the best MPC. Except for Proximal Policy Optimization (PPO), all DRL agents can have a better approximation to the optimality than the best MPC, and are expected to have better approximation than the MPC with a prediction horizon of 32 steps (15 min per step). In terms of reducing energy cost and thermal discomfort, MPC can outperform the rule-based control (RBC) by 18.47%–25.44%. DRL can be expected to outperform RBC by 18.95%–25.65% ,and the best DRL control policy can outperform RBC by 20.29%–29.72%. Although the comparison of the optimality level is performed in a perfect setting, e.g., MPC assumes perfect models, and DRL assumes a perfect offline training process and online deployment process, this can shed insight on their capabilities of approximating to the original dynamic programming problem.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Reliability-Based Design Optimization of a Composite Airframe Component

A stochastic design optimization methodology (SDO) has been developed to design components of an airframe structure that can be made of metallic and composite materials. The design is obtained as a function of the risk level, or reliability, p. The design method treats uncertainties in load, strength, and material properties as distribution functions, which are defined with mean values and standard deviations. A design constraint or a failure mode is specified as a function of reliability p. Solution to stochastic optimization yields the weight of a structure as a function of reliability p. Optimum weight versus reliability p traced out an inverted-S-shaped graph. The center of the inverted-S graph corresponded to 50 percent (p = 0.5) probability of success. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure that corresponds to unity for reliability p (or p = 1). Weight can be reduced to a small value for the most failure-prone design with a reliability that approaches zero (p = 0). Reliability can be changed for different components of an airframe structure. For example, the landing gear can be designed for a very high reliability, whereas it can be reduced to a small extent for a raked wingtip. The SDO capability is obtained by combining three codes: (1) The MSC/Nastran code was the deterministic analysis tool, (2) The fast probabilistic integrator, or the FPI module of the NESSUS software, was the probabilistic calculator, and (3) NASA Glenn Research Center s optimization testbed CometBoards became the optimizer. The SDO capability requires a finite element structural model, a material model, a load model, and a design model. The stochastic optimization concept is illustrated considering an academic example and a real-life raked wingtip structure of the Boeing 767-400 extended range airliner made of metallic and composite materials.

Patnaik, Surya N.↗

Cryogenic Carbon Capture Development (Final Report)

This project extends and leverages the work completed under funding from ARPA-E and other sources by exploring aspects of the Cryogenic Carbon Capture™ (CCC) process and issues discovered during those projects, but that were not within the scope or budget of previous projects or that became apparent during field tests. Our successful completion of the tasks outlined in this project has increased the reliability, efficiency, and scalability of the CCC process and we are better prepared for pilot-scale testing. The first phase of this project improved key areas of the process through iterative design and experiment, culminating with recommendations for improvements to the existing skid-scale system developed under non-federal funding. The second phase of this project implemented the improved unit operations into the Cryogenic Carbon Capture External Cooling Loop (CCC ECL™) skid and field tests the improved system at a coal-fired power plant. The specific areas of work in this project are: Budget Period 1: 1) Selection of the most energy-efficient drying system for ambient-pressure flue gas. Sustainable Energy Solutions, LLC (SES) has successfully demonstrated a dryer that removes bulk water using a low-temperature brine to remove about 99% of the water followed by a mol sieve 3A desiccant dryer to remove the remaining 1% water; 2) Selection and demonstration of efficient solution to fouling due to dissolved CO 2 . SES has tested several commercial heat exchangers that purport to be able to handle fouling issues similar to those experienced in the contact liquid chiller. Replicated tests using the CCC ECL™ skid and dimpled brazed plate heat exchangers demonstrate that quick throttling of refrigerant combined with a burst of clean gas mitigate the fouling caused by CO 2 solubility in contact liquid with only minor increases in parasitic load. SES models indicate that parasitic load would increase by approximately 0.0125 GJ/tonne, an order of magnitude less than what was determined to be the maximum allowable additional parasitic load caused by this system; 3) Selection and demonstration of efficient and scalable solid–liquid separation system. The screw press technology met or exceeded the 70% solids loading benchmark during several test runs exceeding 24 hours on the CCC ECL™ skid. The average solids loading during the entire 50-hour run was 67%. The energy demand for this system is less than 0.1 GJ e /tonne of CO 2 processed; 4) Optimize design and demonstration of patented desublimating heat exchangers. We designed and built a hybrid spray tower that was tested over many hundreds of hours and a 50-hour continuous test run was completed capturing over 0.5 tonne CO 2 /day at >90% capture; (5) Plan for safe dilution of oxygen-depleted, cleaned flue-gas stream. The AERSCREEN simulator developed by the EPA modeled the dispersion of oxygen-depleted flue gas from the CCC process at a commercial plant. The results indicate that this plan effectively mitigates the flue gas hazards; (6) Simulation of and experimental work related to multi-pollutant capture. SES programmed an upgrade to its solid/vapor/liquid equilibrium (SVLE) algorithm. This enables simultaneous modeling of multiple pollutants (i.e., CO 2 , SO x , NO x , Hg, HCl). Budget Period 2; (7) Modify the CCC ECL™ skid for field testing and complete shakedown testing. The plans for modifying the CCC ECL™ skid were finalized and put into place. Shakedown testing of the updated CCC ECL™ skid occurred at SES using closed-loop mode (i.e., using a synthetic flue gas consisting of only N 2 and CO 2 ) and at the Hunter Power Plant using flue gas from the coal-fired boiler. Shakedown testing took longer than expected due to delays in receiving equipment and unexpected equipment performance in the field; (8) Operate the CCC ECL™ skid in the field. Longer testing of the CCC ECL™ skid occurred at the Hunter Power Plant. Multiple tests exceeding 35 hours were completed, with a total of over 600 hours of CO 2 capture completed using flue gas at the Hunter Power Plant with an average CO 2 capture rate of over 91% during those hours. Extensive notes and documentation were acquired informing improved methods for controls, startup, operation, and shut down; (9) Determine figures of merit and quantify process improvement. SES defined figures of merit for unit operation performance and overall CCC ECL™ process performance. All figures of merit were achieved or surpassed, except for 500 continuous hours of demonstration at the Hunter Power Plant; (10) Complete an Environmental Health and Safety Risk assessment by a third party. Tri-State completed an Environmental Health and Safety Risk assessment; (11) Update techno-economic analysis with third-party validation. The techno-economic analysis has been completed. It confirms the potential large reduction in energy and cost of the CCC process compared with leading alternatives and that the estimates and estimation techniques are reliable.

20 FOSSIL-FUELED POWER PLANTS↗

Fluctuating loads measured on an over-the-wing supersonic jet model

Fluctuating pressure loads on the wing and flap of an over-the-wing supersonic jet model were measured. The model was tested statically and at a Mach number of 0.1 in a small free jet to simulate forward speed. Test parameters were impingement angle, nozzle height, and flap deflection. Load levels as high as 170 db were measured at the center of the impingement region during static tests. Forward speed reduced the loading about 1 db. Load level increased with increasing impingement angle and decreasing nozzle height above the wing. The effect of flap deflection was small. When scaled to full-size aircraft conditions, the maximum amplitude of the one-third-octave fluctuating pressure spectra was about 154 db at about 160 Hz. Maximum load level occurred near the intersection of the nozzle center line with the impinged surface. Downstream of the maximum the fluctuating pressure is inversely proportional to the distance downstream of the nozzle.

Willis, C. M.↗

Lockdown impacts on residential electricity demand in India: A data-driven and non-intrusive load monitoring study using Gaussian mixture models

This study evaluates the effect of complete nationwide lockdown in 2020 on residential electricity demand across 13 Indian cities and the role of digitalisation using a public smart meter dataset. We undertake a data-driven approach to explore the energy impacts of work-from-home norms across five dwelling typologies. Our methodology includes climate correction, dimensionality reduction and machine learning-based clustering using Gaussian Mixture Models of daily load curves. Results show that during the lockdown, maximum daily peak demand increased by 150-200% as compared to 2018 and 2019 levels for one room-units (RM1), one bedroom-units (BR1) and two bedroom-units (BR2) which are typical for low- and middle-income families. While the upper-middle- and higher-income dwelling units (i.e., three (3BR) and more-than-three bedroom-units (M3BR)) saw night-time demand rise by almost 44% in 2020, as compared to 2018 and 2019 levels. Our results also showed that new peak demand emerged for the lockdown period for RM1, BR1 and BR2 dwelling typologies. We found that the lack of supporting socioeconomic and climatic data can restrict a comprehensive analysis of demand shocks using similar public datasets, which informed policy implications for India's digitalisation. We further emphasised improving the data quality and reliability for effective data-centric policymaking.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Distributed Energy Resources Customer Adoption Model (DER-CAM) v5.9

The Distributed Energy Resources Customer Adoption Model (DER-CAM) is a powerful and comprehensive decision support tool that primarily serves the purpose of finding optimal distributed energy resource (DER) investments in the context of either buildings or multi-energy microgrids. Version 5.9 introduces significant advancements to DER-CAM, including support for wholesale market integration (ancillary services), storage aging effects, improved solar thermal collector modeling, improved part-load efficiency modeling for conventional generators, added support for hydro generation, among others.

Deforest, Nicholas↗

Dynamic Spatial and Temporal Structures on the Surface of Solids under Load

A model and a method are proposed to explain the origin and main specific features of the dynamic patterns of different types, which were previously observed on the free surface of solids under load in experiments. It is shown that the pattern is formed due to the dynamic instability of the flat surface of the solid under load. This instability develops at the relaxation mechanism caused by the dynamic atomic displacements due to a change in the interatomic interaction during the electron-density redistribution.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Learjet Model 55 Wing Analysis with Landing Loads

The NASTRAN analysis was used to determine the impact of new landing loads on the Learjet Model 55 wing. These new landing loads were the result of a performance improvement effort to increase the landing weight of the aircraft to 18,000 lbs. from 17,000 lbs. and extend the life of the tires and brakes by incorporating larger tires and heavy duty brakes. Landing loads for the original 17,000 lb. airplane landing configuration were applied to the full airplane NASTRAN model. The analytical results were correlated with the strain gage data from the original landing load static tests. The landing loads for the 18,000 lb. airplane were applied to the full airplane NASTRAN model, and a comparison was made with the original Model 55 data. The results of this comparison enable Learjet to determine the difference in stress distribution in the wing due to these two different sets of landing loads.

Boroughs, R. R.↗

A robust dynamic state estimation approach against model errors caused by load changes

Dynamic state estimation (DSE) plays an important role in power system security monitoring and online control. In practice, there are two approaches to implementing DSE. The first approach is distributed DSE, which is based on the assumption that the terminal bus of each generator can be measured by PMUs (phasor measurement units). The assumption cannot be satisfied currently, however, because PMUs usually are installed at important high-voltage buses such as 500-kV buses installed in portions of the grid overseen by the Western Electricity Coordinating Council. Another issue of this approach is that performance of DSE is vulnerable to bad measurement data. The reason for this vulnerability is that DSE is performed separately through measurements at each terminal bus, and measurements at terminal buses are the only measurement upon which DSE can rely. Therefore, important redundant measurements are not included in this approach. The second approach is centralized DSE. This approach does not have the requirement for PMU location, and redundant measurements can be considered fully. However, load changes and grid topology changes impact centralized DSE. In this paper, we propose a new approach for handling the impact of load changes on DSE. We have developed a new algorithm that includes two sequential steps. In the first step, errors caused by load changes are detected by analyzing the difference between prediction results and measured results. In the second step, once model error is detected, a model optimization procedure is run to correct the error so the state estimation error can be mitigated. Simulation results from the IEEE 68 bus system show that the proposed approach can effectively handle model errors caused by load changes.

robust dynamic state estimation, load change, powe↗

UNF-ST&DARDS Enhancements for RCCA Data in As-loaded Dual Purpose Cask Models

This report summarizes the work performed to enable detailed modeling of rod cluster control assembly (RCCAs) in dual purpose canisters (DPCs) in as-loaded configurations using the Used Nuclear Fuel – Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS). The goal of this project was to evaluate the reactivity impact that RCCAs have on k eff of DPCs with pressurized water reactor (PWR) fuel to potentially use the additional margin in future post-closure criticality safety analysis. This preliminary evaluation determined the number of DPCs that currently require compensatory actions prior to emplacement in a repository because of their high reactivity under post-closure criticality scenarios, which could be made acceptable by including the as-loaded RCCAs as specified in the Unified Database (UDB). This report briefly describes the modeling methods currently used within UNF-ST&DARDS and the modifications made to automate inclusion of the as-loaded RCCAs in the DPCs for post-closure criticality calculations for the loss of neutron absorber (NA) scenarios, or NA models. For the Zion site, the loss of basket scenarios, or degraded basket (DB) models, are also included. Discussion is also provided regarding the UDB data compared to available site-specific loading map data for the sites, which are specifically evaluated herein. This report compares the modifications to a similar evaluation for the Zion by site conducted by Walker as an initial validation. After the partial validation, all existing PWR sites with applicable NA models within the UDB were evaluated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Axisymmetric modeling of cometary mass loading on an adaptively refined grid: MHD results

The first results of an axisymmetric magnetohydrodynamic (MHD) model of the interaction of an expanding cometary atmosphere with the solar wind are presented. The model assumes that far upstream the plasma flow lines are parallel to the magnetic field vector. The effects of mass loading and ion-neutral friction are taken into account by the governing equations, whcih are solved on an adaptively refined unstructured grid using a Monotone Upstream Centered Schemes for Conservative Laws (MUSCL)-type numerical technique. The combination of the adaptive refinement with the MUSCL-scheme allows the entire cometary atmosphere to be modeled, while still resolving both the shock and the near nucleus of the comet. The main findingsare the following: (1) A shock is formed approximately = 0.45 Mkm upstream of the comet (its location is controlled by the sonic and Alfvenic Mach numbers of the ambient solar wind flow and by the cometary mass addition rate). (2) A contact surface is formed approximately = 5,600 km upstream of the nucleus separating an outward expanding cometary ionosphere from the nearly stagnating solar wind flow. The location of the contact surface is controlled by the upstream flow conditions, the mass loading rate and the ion-neutral drag. The contact surface is also the boundary of the diamagnetic cavity. (3) A closed inner shock terminates the supersonic expansion of the cometary ionosphere. This inner shock is closer to the nucleus on dayside than on the nightside.

Gombosi, Tamas I.↗