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At least 1,207 records · Page 67

REopt: A Platform for Energy System Integration and Optimization: Preprint

REopt is NREL's energy planning platform offering concurrent, multi-technology integration and optimization capabilities to help clients meet their cost savings and energy performance goals. The REopt platform provides techno-economic decision-support analysis throughout the energy planning process, from agency-level screening and macro planning to project development to energy asset operation. REopt employs an integrated approach to optimizing a site?s energy costs by considering electricity and thermal consumption, resource availability, complex tariff structures including time-of-use, demand and sell-back rates, incentives, net-metering, and interconnection limits. Formulated as a mixed integer linear program, REopt recommends an optimally-sized mix of conventional and renewable energy, and energy storage technologies; estimates the net present value associated with implementing those technologies; and provides the cost-optimal dispatch strategy for operating them at maximum economic efficiency. The REopt platform can be customized to address a variety of energy optimization scenarios including policy, microgrid, and operational energy applications. This paper presents the REopt techno-economic model along with two examples of recently completed analysis projects.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Pansophy enhancements for SRF through collecting and analyzing inputs/outputs to further project efficiency in reporting and performance

SRF cavity and Cryomodule testing and production requires a consistent means of collecting and analyzing data against quality and production parameters. JLab's engineering data management system, Pansophy, is utilized to assist project leaders and subject matter experts (SMEs) with such tasks, by providing a means to data mine key parameter indicators (KPI) and production planning and status data. Recent enhancements to reporting and trending have been utilized for the LCLS-II and CEBAF 12GeV upgrade projects. Further enhancements are being planned for future projects, like SNS-PPU, such as KPI trending, KPI quality, vendor quality, production timelines and user defined queries. Being able to understand past trends will assist with enhancements to future projects.

Bookwalter, Valerie D.↗

A retrospective planning analysis comparing intensity modulated radiation therapy (IMRT) to volumetric modulated arc therapy (VMAT) using two optimization algorithms for the treatment of early-stage prostate cancer

The primary aim of this study is to compare intensity modulated radiation therapy (IMRT) to volumetric modulated arc therapy (VMAT) for the radical treatment of prostate cancer using version 10.0 (v10.0) of Varian Medical Systems, RapidArc radiation oncology system. Particular focus was placed on plan quality and the implications on departmental resources. The secondary objective was to compare the results in v10.0 to the preceding version 8.6 (v8.6). Twenty prostate cancer cases were retrospectively planned using v10.0 of Varian's Eclipse and RapidArc software. Three planning techniques were performed: a 5-field IMRT, VMAT using one arc (VMAT-1A), and VMAT with two arcs (VMAT-2A). Plan quality was assessed by examining homogeneity, conformity, the number of monitor units (MUs) utilized, and dose to the organs at risk (OAR). Resource implications were assessed by examining planning and treatment times. The results obtained using v10.0 were also compared to those previously reported by our group for v8.6. In v10.0, each technique was able to produce a dose distribution that achieved the departmental planning guidelines. The IMRT plans were produced faster than VMAT plans and displayed improved homogeneity. The VMAT plans provided better conformity to the target volume, improved dose to the OAR, and required fewer MUs. Treatments using VMAT-1A were significantly faster than both IMRT and VMAT-2A. Comparison between versions 8.6 and 10.0 revealed that in the newer version, VMAT planning was significantly faster and the quality of the VMAT dose distributions produced were of a better quality. VMAT (v10.0) using one or two arcs provides an acceptable alternative to IMRT for the treatment of prostate cancer. VMAT-1A has the greatest impact on reducing treatment time.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

NASA ground communications

As part of the Communications Requirements and Constraints, NASA's two major Ground Data Networks were briefly described. The NASA Communication Network, called NASCOM, is the worldwide operational telecommunications system which interconnects as the tracking and telemetry acquisition sites, launch areas, mission and project control centers, data capture facilities, and network control centers in support of space flight. For the Space Station era, NASCOM plans are set for higher data rate service utilizing data packet switched technology. Increased use of fiber optics is expected in a much more diverse network topology. The second major ground network, the Program Support Communications Network (PSCN), interconnects all NASA Centers and NASA contractor locations for intercenter non-operation communications. The primary functions are to transport voice, video, data and facsimile information for intercenter coordination, and to provide user access to space science and applications data bases. For the Space Station era, PSCN plans address the significant increase in forecast requirements for science data distribution and access to the Numerical Aerodynamics Simulator, and increased use of the Video Teleconference System.

Roeder, John↗

The Uniform Methods Project: Smart Thermostat Evaluation Protocol

A smart thermostat is an internet-connected device that controls home heating, ventilation, and air-conditioning (HVAC) equipment and can automatically adjust temperature set points to optimize performance and achieve energy savings. Smart thermostat features often include two way communication, occupancy detection (such as geofencing and occupancy sensors), schedule learning, and seasonal optimization algorithms. Smart thermostats can control most conventional HVAC systems, including central air conditioners, heat pumps, and forced air furnaces. Several types of residential utility programs offer smart thermostats as replacements measures. Working with smart thermostat vendors, utilities can offer separate optimization programs to produce energy savings beyond those achieved by installing a smart thermostat. From an evaluation perspective, smart thermostat programs have several noteworthy features. First, the energy savings from a smart thermostat may change over the life of the device. As a smart thermostat is connected to the internet, original equipment manufacturers can update the thermostat software to improve the thermostat's energy efficiency. Likewise, users can adjust the thermostat settings and schedules over time in response to changes in weather, thermal comfort, energy prices, or preferences for energy efficiency. Additionally, many thermostat manufacturers offer seasonal optimization programs that recommend changes or make minor, automated adjustments to the thermostat settings to improve energy efficiency. These opt-in programs are now standard offerings for many smart thermostat manufacturers and provided at no additional cost to users. The potential for software updates and continuous optimization and the evolving nature of user interactions mean future energy savings may differ from first-year savings and the energy savings of smart thermostats may need to be evaluated more than once. Second, smart thermostats often have small unit energy savings relative to a home's total energy consumption, especially in comparison to whole- home retrofit programs. This can make it difficult to detect the smart thermostat savings in billing or advanced metering infrastructure (AMI) meter consumption data. For example, as cooling loads in many regions average about 20% of annual electricity consumption, smart thermostat savings of 10% of cooling energy use would equate to a 2% reduction in home electricity consumption. Evaluators should use regression analysis of whole-home billing consumption or advanced metering infrastructure (AMI) meter consumption data to evaluate smart thermostat savings because, as explained at greater length below , these data are usually available to evaluators and regression can control for the impacts of weather and other potentially confounding factors on a home's energy consumption. Finally, as with other energy efficiency programs, participation in smart thermostat programs is self-selective. As discussed at greater length below , smart thermostat participants tend to be, among other things, younger, higher-income, and more likely to adopt electric vehicles (EVs) and internet connected devices than nonparticipants. These differences are often unobservable to the evaluator and correlated with a home's energy consumption, creating the potential for bias in estimating savings. Due to the small unit savings of thermostats, errors and biases from self-selection that may not be very consequential when evaluating a whole- home retrofits (e.g., ±2% of home electricity consumption) can have a major impact when evaluating the savings and cost-effectiveness of smart thermostat programs. A percentage point change in the estimated savings could affect the cost-effectiveness of a program. This means it is important for evaluators to assess and to minimize the potential for error from selection bias in estimating smart thermostat program savings. The Uniform Methods Project provides model protocols for determining energy savings and demand reductions that result from specific energy efficiency measures implemented through state and utility programs. In most cases, the measure protocols are based on a particular option identified by the International Performance Verification and Measurement Protocol ; however, this work provides a more detailed approach to implementing that option. Each chapter is written by technical experts in collaboration with their peers, reviewed by industry experts, and subject to public review and comment. The UMP protocols can be used by utilities, program administrators, public utility commissions, evaluators, and other stakeholders for both program planning and evaluation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Photovoltaic inverter-based quantification of snow conditions and power loss

Snow is a significant challenge for photovoltaic (PV) systems at northern latitudes, where the pace of deployment is rapid but snow-related power losses can exceed 30% of annual production. Accurate snow-related power loss estimation methods for utility-scale sites can support snow mitigation strategies, inform resource planning and validate predictive snow-loss models. This study builds on our previous work on inverter-based detection of snow, and its implications for utility-scale power production, by validating the accuracy of our snow-loss method across different PV sites and system designs and highlighting its value in bringing greater visibility to PV plant operations in winter. Our estimation method is both novel and scalable, requiring only standard monitoring data to correlate snow-related losses with meteorological data. As demonstrated here, our validation method involved three main steps: 1) estimation of performance losses for multiple systems by comparing measured inverter data to modeled data; 2) application of a detection framework to identify which performance losses are snow-related; and 3) comparison of snow-related losses among three utility-scale sites differing in tilt angle. Results show that utility-scale systems at higher tilt angles consistently shed snow more quickly/completely than their lower-tilt counterparts. Further, monthly and seasonal snow losses are inversely and non-linearly correlated with tilt angle when normalized for cumulative snowfall. These results are consistent with the findings of previous studies and support the broad applicability of this method to fixed-tilt utility-scale PV systems around the world that routinely experience snow-related performance losses.

Cooper, Emma C. (ORCID:0000000190554098)↗

Site 200 #1400 Block Area New Trailers Project, Soil Sampling and Analysis Plan/Quality Assurance Plan

Lawrence Livermore National Laboratory's (LLNL) Project Management Office (PMO) is proposing to install a series of modular trailers and install associated underground utilities in the 1400 Block at the Livermore Site. This Sampling and Analysis Plan (SAP) outlines the processes and procedures to collect environmental and geotechnical soil samples from the project area and to send the samples to the appropriate laboratory or laboratories for analysis or testing. The resulting environmental laboratory data will determine whether excavated soils can be reused on the project, or which type of landfill or landfills the soils may be sent for disposal. This SAP has been prepared and is organized to be consistent with LLNL's Soils Screening and Management Plan (SSMP) (LLNL, 2019), as well as the U.S. Environmental Protection Agency's (EPA) Data Quality Objectives programs (EPA, 2006).

54 ENVIRONMENTAL SCIENCES↗

SU-F-T-448: Use of Mixed Photon Energy Beam in Volumetric Modulated Arc Therapy (VMAT) Treatment Plan for Prostate Cancer

Purpose: To study the impact of different photon beam combination during VMAT planning and treatment delivery. Methods: Five prostate patients with no nodal involvement were chosen for the study and only prostate was considered as target (7920cGy/44fractions). In each case, three different VMAT plans were generated with two arcs (200°–160°&160°–200°). First plan used only 6MV in both arcs (6X-6X) and second utilized 6MV&15MV (6X-15X), whereas third one used 15MV&15MV (15X-15X). For consistency, all the plans were generated by the same planner using Monaco− treatment planning system (V5.1) for Elekta Synergy− linear accelerator with 1cm leaf-width. For plan comparison, target mean dose, conformity index (CI)=Planning target volume (PTV) covered by 95% of prescription dose/PTV were analyzed. Mean doses of bladder, rectum, left femur and right femur were analyzed. Integral dose (liter-Gray) to normal tissue (patient volume minus PTV), total monitor unit (MU) required to deliver a plan and gamma pass rate for each plan was analyzed. Results: The CI for PTV was 0.9937±0.0037, 0.9917±0.0033, and 0.9897±0.0048 for 6X-6X, 6X-15X and 15X-15X, respectively. Mean dose to target slightly increases with the decrease of energy. Mean doses to bladder were 3546.23±692.13cGy, 3487.43±715.53cGy and 3504.40±683.1cGy for 6X-6X, 6X-15X and 15X-15X, respectively. Mean doses to rectum were 4294.60±309.5cGy, 4277.07±279.93cGy and 4290.77±379.07cGy. Mean doses to left femur were 2737.13±545.93cGy, 2668.67±407.12cGy and 2416.77±300.73cGy and mean doses to the right femur were 2682.70±460.81cGy, 2722.58±541.92cGy and 2598.57±481.83cGy. Higher Integral doses to normal tissue observed for 6X-6X (163.06±24.6 Litre-Gray) followed by 6X-15X (154.35±24.74 Litre-Gray) and 15X-15X (145.84±26.03 Litre-Gray). Average MU required to deliver one fraction was 680.75±72.09, 634.81±95.07 and 605.06±114.65. Gamma pass rates were 99.83±0.21, 99.53±0.27 and 99.2±0.20. Conclusion: 6X-15X VMAT plan offer dosimetric advantage compared to 6X-6X in terms of lesser MU and integral dose without significant compromise in plan quality, where as in 15X-15X, neutron contamination risk is relatively higher.

60 APPLIED LIFE SCIENCES↗

Commonwealth of the Northern Mariana Islands Energy Action Plan

This document describes the three near-term energy strategies selected by the CNMI Energy Task Force during action planning workshops conducted in March 2013, and outlines the steps being taken to implement those strategies. The three energy strategies selected by the task force are (1) designing a demand-side management program focusing on utility, residential and commercial sectors, (2) developing an outreach and education plan focused on energy conservation in government agencies and businesses, including workplace rules, and (3) exploring waste-to-energy options. The task force also discussed several other medium- and long-term energy strategies that could be explored at a future date.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Community Solar Value Project

The Community Solar Value Project (CSVP) is designed to assist electric utilities in designing better community solar programs. Better programs seek new sources of value to promote “win-win” solutions between utilities and their customers. The CSVP focused on five “challenge areas” in identifying new sources of value: - Strategic solar design for community solar projects (including technology choices, siting, orientation, and related issues) - Market research and targeted marketing approaches (for program design and for customer recruitment) - Procurement and financing (for establishing best practices that can bring economies of scale and economies of expertise) - Integration of “companion measures” (such as storage and demand-response options that can benefit customer and utility net load shapes) - Pricing in program design (including best practices for integration of identified value in program prices or credits) The CSVP directly engaged the Sacramento Municipal Utility District (SMUD), the Public Service Company of New Mexico (PNM), and more than a dozen other utilities to develop improved community solar program designs. The outcomes include a plan at SMUD for over 100 MW or more of community and shared solar and support for new or expanded programs at 15 other utilities so far. Resulting best-practice solutions have not only informed program applications, but also have generated discussion among experts and industry associations about the new opportunities and challenges CSVP has brought forth. In these ways, the CSVP has impacted community solar programs and DER plans, competitive innovations and policies nationwide. The CSVP team has been led by Extensible Energy under John Powers, President and CEO. Jill Cliburn, of Santa Fe, NM-based Cliburn and Associates, has served as Principal Investigator. The team also benefitted from expertise from Navigant, Olivine Inc. and Millennium Energy, LLC, in addition to the collaborative and cost-sharing contributions of its utility partners. The CSVP team participated fully in the Solar Market Pathways Program, which was initiated under the U.S. Department of Energy SunShot program and reports to the U.S. Department of Energy Solar Energy Technologies Office. This report summarizes a multi-disciplinary project that took place over 33 months from January, 2015 through September, 2017.

14 SOLAR ENERGY↗

Beyond DERMS: Demonstration of Automated Grid Services, Mode Transition, and Resilience

This report describes the results of more advanced use cases including Ancillary Services, Black-sky-day operation, and Mode Switching from Phase 3 of the “Beyond DERMS” project aiming to build, deploy, and demonstrate a holistic platform that supports the integrated operation and planning of future power distribution networks with bi-directional power flows, many diverse distributed energy resources (DERs), and inverter-based resources. These test results demonstrated how a Beyond DERMS platform can fuse together AMI, SCADA, and DER data to provide a utility with deep insights into distribution network operations and planning, extending the value of DERMS and BTM DER resources.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Climate-Water Impacts on Interconnection-Scale Electricity System Planning

A growing literature emphasizes the importance of integrating climate change impacts into electricity system planning. Rising average temperatures can increase and shift electricity demand while reducing generator and transmission efficiency. Changes to water availability and quality can reduce the output of thermally cooled generators and hydropower. Electric power grids across the US and globally are undergoing transformational changes that present new opportunities and challenges to reliability assurance. However, electric utilities and system operators have limited internal capabilities to incorporate these effects into planning practices. This work addresses gaps in utility and system planner practices by integrating climate-water-electricity expertise from universities and U.S. Department of Energy National Laboratories with electricity system planners and stakeholders in the Western Electricity Coordinating Council (WECC). Using a highly collaborative approach, global climate model data, high-resolution hydrology models, and long-term electric sector capacity expansion tools are employed to analyze a range of climate outcomes for future electricity scenarios aligned with recent WECC planning studies. Doing so allows WECC to expand its climate-agnostic planning assessments to consider how future temperature and precipitation patterns could influence generation and transmission planning. We explore how changes to climate-water conditions can affect power plant investment and operation, system economics, and environmental impacts, providing an expanded perspective on interconnection-wide decision making under climate uncertainty.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Renewable Energy Deployment in Colorado and the West: Extended Policy Sensitivities

The Resource Planning Model is a capacity expansion model designed for a regional power system, such as a utility service territory, state, or balancing authority. We apply a geospatial analysis to Resource Planning Model renewable energy capacity expansion results to understand the likelihood of renewable development on various lands within Colorado.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Decomposition of Sources of Errors in Seasonal Streamflow Forecasting over the U.S. Sunbelt

Seasonal streamflow forecasts, contingent on climate information, can be utilized to ensure water supply for multiple uses including municipal demands, hydroelectric power generation, and for planning agricultural operations. However, uncertainties in the streamflow forecasts pose significant challenges in their utilization in real-time operations. In this study, we systematically decompose various sources of errors in developing seasonal streamflow forecasts from two Land Surface Models (LSMs) (Noah3.2 and CLM2), which are forced with downscaled and disaggregated climate forecasts. In particular, the study quantifies the relative contributions of the sources of errors from LSMs, climate forecasts, and downscaling/disaggregation techniques in developing seasonal streamflow forecast. For this purpose, three month ahead seasonal precipitation forecasts from the ECHAM4.5 general circulation model (GCM) were statistically downscaled from 2.8deg to 1/8deg spatial resolution using principal component regression (PCR) and then temporally disaggregated from monthly to daily time step using kernel-nearest neighbor (K-NN) approach. For other climatic forcings, excluding precipitation, we considered the North American Land Data Assimilation System version 2 (NLDAS-2) hourly climatology over the years 1979 to 2010. Then the selected LSMs were forced with precipitation forecasts and NLDAS-2 hourly climatology to develop retrospective seasonal streamflow forecasts over a period of 20 years (1991-2010). Finally, the performance of LSMs in forecasting streamflow under different schemes was analyzed to quantify the relative contribution of various sources of errors in developing seasonal streamflow forecast. Our results indicate that the most dominant source of errors during winter and fall seasons is the errors due to ECHAM4.5 precipitation forecasts, while temporal disaggregation scheme contributes to maximum errors during summer season.

Decomposition↗

4D tumor centroid tracking using orthogonal 2D dynamic MRI: Implications for radiotherapy planning

Purpose: Current pretreatment, 4D imaging techniques are suboptimal in that they sample breathing motion over a very limited “snapshot” in time. Heretofore, long-duration, 4D motion characterization for radiotherapy planning, margin optimization, and validation have been impractical for safety reasons, requiring invasive markers imaged under x-ray fluoroscopy. To characterize 3D tumor motion and associated variability over durations more consistent with treatments, the authors have developed a practical dynamic MRI (dMRI) technique employing two orthogonal planes acquired in a continuous, interleaved fashion.Methods: 2D balanced steady-state free precession MRI was acquired continuously over 9–14 min at approximately 4 Hz in three healthy volunteers using a commercial 1.5 T system; alternating orthogonal imaging planes (sagittal, coronal, sagittal, etc.) were employed. The 2D in-plane pixel resolution was 2 × 2 mm{sup 2} with a 5 mm slice profile. Simultaneous with image acquisition, the authors monitored a 1D surrogate respiratory signal using a device available with the MRI system. 2D template matching-based anatomic feature registration, or tracking, was performed independently in each orientation. 4D feature tracking at the raw frame rate was derived using spline interpolation.Results: Tracking vascular features in the lung for two volunteers and pancreatic features in one volunteer, the authors have successfully demonstrated this method. Registration error, defined here as the difference between the sagittal and coronal tracking result in the SI direction, ranged from 0.7 to 1.6 mm (1σ) which was less than the acquired image resolution. Although the healthy volunteers were instructed to relax and breathe normally, significantly variable respiration was observed. To demonstrate potential applications of this technique, the authors subsequently explored the intrafraction stability of hypothetical tumoral internal target volumes and 3D spatial probability distribution functions. The surrogate respiratory information allowed the authors to show how this technique can be used to study correlations between internal and external (surrogate) information over these prolonged durations. However, compared against the gold standard of the time stamps in the dMRI frames, the temporal synchronization of the surrogate 1D respiratory information was shown to be likely unreliable.Conclusions: The authors have established viability of a novel and practical pretreatment, 4D tumor centroid tracking method employing a commercially available dynamic MRI sequence. Further developments from the vendor are likely needed to provide a reliably synchronized surrogate 1D respiratory signal, which will likely broaden the utility of this method in the pretreatment radiotherapy planning context.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Cascade energy optimization for waste heat recovery in distributed energy systems

The efficiency of distributed energy systems can be significantly increased through waste heat recovery from industry or power generation. The technologies used for this process are typically dependent on the quality and temperature grades of waste heat. To maximize the efficiency of cascade heat utilization, it is important to optimize the choice of waste heat recovery technologies and their operation. Here, a detailed mixed integer linear programming optimization model is proposed for waste heat recovery in a district-scale microgrid. The model can distinguish waste heat quality for planning and operation optimization of distributed energy systems. Heat utilization technologies are formulated in this developed model and categorized in different temperature grades. The developed model is validated using four typical cases under different settings of system operation and business models. It is found that the optimization model, by distinguishing waste heat temperature, can increase energy cost savings by around 5%, compared to models that do not consider waste heat temperature grades. Additionally, the results indicate that the developed model can provide more realistic configuration and technologies dispatch.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Electromagnetic Transient Simulation Algorithms for Evaluation of Large-Scale Extreme Fast Charging Systems (Distribution Grid Models)

The distribution and transmission grids are observing an increased penetration of power electronics in loads and generations. For example, there is increasing interest in integrating in extreme fast charging (XFC) systems for fast charging of electrical vehicles. As these systems are integrated, developing high-fidelity electromagnetic transient model of XFC systems in distribution grids and evaluating their interactions with the power grid would be of significant interest. This model will be utilized for design of XFC systems, to identify upgrades in distribution and/or transmission grids, for planning purposes by transmission planners or operators or owners, among others. It can also be utilized in operations for improved reliable performance of the grid and/or XFC station. The challenge with simulating these models is the high computational complexity introduced by the large number of states present in the system and the time-step needed to simulate the system. In this paper, advanced simulations algorithms are applied to reduce the computational complexity of simulating large-scale XFC systems. The algorithms include numerical stiffness-based segregation, time constant-based segregation, clustering and aggregation on differential algebraic equations (DAEs), and multi-order integration approaches. While the first three algorithms split the matrix that needs to be inverted from a large matrix to much smaller matrices, the final algorithm reduces the computational burden of applying higher-order integration approaches in the complete system. The comparison made in the previous sentence is with respect to use of homogeneous integration approaches used in conventional electromagnetic transient simulators like power systems computer aided design (PSCAD). The approaches mentioned here have resulted in speed-up of 36x in the simulation of a single distribution system with 15 XFCs.

Debnath, Suman↗