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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Extension of the energetic particle transport kick model in TRANSP to multiple fast ion species

Abstract Alfvénic instabilities (AEs) are well known to cause enhanced transport of energetic particles (EPs) in fusion devices. Most studies until now have focused on characterizing and understanding AE stability in single-species plasmas heated by neutral beams (NB), where deuterium is typically used as both main plasma species and NB fuel. As the fusion community moves toward fusion reactors that target burning plasma conditions, such as ITER, the single-species picture breaks down. Burning plasmas, which will use a mix of deuterium and tritium (DT) as main fuel, also feature the presence of several supra-thermal fusion products such as alpha particles, protons, helium isotopes and high-energy tritium ions. This work presents the extension of the EP transport kick model implemented in the TRANSP time-dependent tokamak transport code to study the combined effect of multiple EP species on AE stability and, in turn, the response of different EP species to plasma instabilities in terms of their redistribution and losses. Further validation of the enhanced model is planned based on experimental results expected from the JET DT campaign scheduled for 2021, in preparation for ITER plasmas and beyond.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Conference Support, 32nd Western Photosynthesis Conference 2023

This DOE-BES award provided conference support for the 32nd Western Photosynthesis Conference (WPC2023), held January 5–8, 2023 at the Bodega Bay Marine Laboratory in Bodega Bay, California. The Western Photosynthesis Conference is one of three regional photosynthesis meetings held annually in the United States and serves as a primary venue for early-career scientists—graduate students, postdoctoral researchers, and undergraduates—to present research and build professional networks alongside established investigators in the field. Photosynthesis research is central to the DOE Office of Science's Basic Energy Sciences mission, underpinning fundamental understanding of solar energy conversion, biofuels, and the biological transformation of light into chemical energy. DOE-BES funds were used, as proposed, to support registration and housing costs for 20 early-career participants (9 postdoctoral researchers, 9 graduate students, and 2 undergraduates) and to help defray travel costs for two junior invited speakers based outside California, for a total DOE-BES expenditure of $10,060. The meeting was executed as planned, with no significant deviations from the approved program, budget, or schedule. WPC2023 drew 76 registrants across six scientific topic areas, featured 8 of 9 invited/keynote speakers, and provided extensive opportunities for early-career scientists to present talks and posters, compete for recognition awards, and network with senior researchers in the field.

conference↗
DOE OSTI2023

A Complex Brownfields Case Study—The Former Bannister Federal Complex, Kansas City, Missouri

Abstract In November 2017, 225 acres (91 ha) of the former Bannister Federal Complex (BFC) in Kansas City, Missouri were transferred from the Federal Government to Bannister Transformation & Development, LLC (BTD), for demolition; environmental corrective measures; and preparation of the site for redevelopment. This presented a once‐in‐a‐lifetime opportunity to reconfigure groundwater remedies and address long‐standing soil contamination issues. The property included more than 40 previously‐identified Solid Waste Management Units, 3.9 million square feet (362,000 m 2 ) of buildings, subsurface utilities dating back to the 1940s, and an active groundwater containment system. Demolition of buildings and installation of an interim groundwater containment system began almost immediately after property transfer. In 2018, BTD substantially modified its project schedule to incorporate the construction of the first new buildings while demolition and remedial activities were ongoing. By October 2020, construction of the first new warehouse commenced while excavation and capping of contaminated soils, installation of a groundwater containment treatment systems, and abandonment of legacy utilities were still underway. Completion of this work, within the originally planned timeframe, was made possible by factors including up‐front multi‐year funding, early and ongoing engagement of regulators, an extended 3‐year due diligence program and planning stage, and establishment of well‐defined environmental targets. Both the soil and groundwater remedies were also designed with the flexibility needed to accommodate unknown conditions, changing schedules, and revisions to the regrading and redevelopment plans. This case study highlights key technical and management factors that led to the successful completion of this complex brownfields remediation project.

Water Resources↗
DOE OSTI2021

The Wonders of Physics -- Public Outreach (Final Technical Report)

The mission of The Wonders of Physics (TWoP) outreach program is to generate interest in physics among people of all ages and backgrounds. The objective is to generate interest in physics, increase appreciation for the significance of physics in our lives, and encourage children to consider careers in science and plasma physics. The primary means for achieving that objective is to make entertaining presentations to audiences that would not normally be motivated to attend a lecture on physics or plasmas, while at the same time introducing some of the fundamental concepts and applications. During this reporting period, the students Michael Hall, Megan Tabbutt and Connor Sullivan, Director of Communications Sarah Perdue, Director of Undergraduate Program Jim Reardon, and Senior Information Processing Consultant Paul Wilhite worked to make outreach programs a success and prepare for the future of The Wonders of Physics, which will continue. Because of the curtailment of public events due to Covid-19, there will not be an in person Annual Show or Physics Fair in 2021, but a video competition has already been announced and planning continues for The Wonders of Physics in 2022 and beyond. The annual shows and Physics Fair are scheduled for February 12-13 and February 19-20, 2022. These continue to be our premier outreach events, engaging diverse audiences in real hands-on science. Further shows and exploration stations are planned.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Models and Strategies for Optimal Demand Side Management in the Chemical Industries

Deregulation and the increase of renewable electricity generation from wind and solar photovoltaics have transformed the U.S. electricity market. Economic and environmental benefits notwithstanding, the presence of renewables has increased variability and uncertainty on the supply side of the grid. Managing demand, rather than generation – a strategy referred to as “demand response (DR)” – is an attractive approach for mitigating this imbalance. DR efforts aim to reduce electricity usage during peak demand times, lessening stress on the grid. Industrial users are particularly attractive entities for DR participation since they present large, localized loads that can provide significant relief on grid demand and –unlike other large loads, such as buildings – are minimally dependent on human needs and preferences. In this project, we accomplished three main objectives. (1) We developed data-driven low-order DR scheduling-relevant dynamic models of chemical processes. Concurrently, we studied the formulation and solution of the associated optimal DR production scheduling problems. (a) A prototype air separation unit (ASU) model was used to generate simulated operating data for initial modeling efforts, which enabled the later use of industrial data for data-driven modeling. (b) We utilized Hammerstein-Wiener (HW) and Finite Step Response (FSR) models to represent nonlinear plant dynamics. (c) The HW models were linearized using exact linearization so they could potentially be embedded in power system models, which are formulated as mixed integer linear programs (MILPs). (d) We solved DR optimization problems under uncertainty and found that even naïve predictions of electricity price and product demand led to significant cost savings benefits. (2) Our DR scheduling optimization problem formulations are amenable to real-time solution. (a) We utilized Lagrangian Relaxation (LR) to efficiently solve the optimization problem by decoupling subproblems linked by complicating constraints. (b) We have achieved computation times for the 3-day DR scheduling problem of an ASU as low as 1.88 minutes. (3) Our representations of the DR behavior of chemical process as grid-level batteries were embedded in power system models. (a) For a small-scale grid, we found that incorporating the dynamics of the chemical plant in the optimal power flow calculations resulted in better resource management leading to up to 15% and 46% cost reduction for the grid and chemical plant operations, respectively, during periods of power line congestion. We have published several works dedicated to modeling and solving DR optimization problems from the user side. These were published in top peer-reviewed journals and are summarized in this report. The most recent work (and papers in preparation) considers DR scheduling from the grid side. Future efforts will consider networked plants (e.g., air separation units operating on a common pipeline) for DR participation, which is expected to amplify the capabilities of industrial DR participants to perform load-shifting. Our consideration of uncertainty in DR has inspired future directions in this area as well: we plan to develop multistage methods to fully account for the effects of uncertainty in DR scheduling.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Evaluation of HPK n + - p planar pixel sensors for the CMS Phase-2 upgrade

To cope with the challenging environment of the planned high luminosity upgrade of the Large Hadron Collider (HL-LHC), scheduled to start operation in 2029, CMS will replace its entire tracking system. The requirements for the tracker are largely determined by the long operation time of 10 years with an instantaneous peak luminosity of up to 7.5 × 10 34 cm –2 s –1 in the ultimate performance scenario. Depending on the radial distance from the interaction point, the silicon sensors will receive a particle fluence corresponding to a non-ionizing energy loss of up to $\Phi_{\text {eq}}$ = 3.5 × 10 16 cm –2 . Here this paper focuses on planar pixel sensor design and qualification up to a fluence of $\Phi_{\text {eq}}$ = 1.4 × 10 16 cm –2 . For the development of appropriate planar pixel sensors an R&D program was initiated, which includes $n^+ -p$ sensors on 150 mm (6”) wafers with an active thickness of 150 μm with pixel sizes of 100 × 25 μm 2 and 50 × 50 μm 2 manufactured by Hamamatsu. Single chip modules with ROC4Sens and RD53A readout chips were made. Irradiation with protons and neutrons, as well was an extensive test beam campaign at DESY were carried out. This paper presents the investigation of various assemblies mainly with ROC4Sens readout chips. It demonstrates that multiple designs fulfill the requirements in terms of breakdown voltage, leakage current and efficiency. The single point resolution for 50 × 50 μm 2 pixels is measured as 4.0 μm for non-irradiated samples, and 6.3 μm after irradiation to $\Phi_{\text {eq}}$ = 7.2 × 10 15 cm –2 .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Risk-based System Upgrade Planning for AOT-IC Presentation [Slides]

The number of deployed systems and different HW/SW form factors makes it difficult to maintain a complete understanding of their health which leads to a reduced level of certainty when assessing risk and trying to prioritize system upgrade efforts. AOT-IC must constantly plan and execute system upgrade and replacement projects to ensure the longevity of the control system. There are many more projects needed than the group can realistically accomplish given schedule and resource constraints. The group must prioritize their upgrade projects to choose only the highest priority projects to execute each year. Currently plans upgrade and replacement projects based on alignment with mission needs, group vision, resource availability, and qualitative risk assessments based on SME estimates. The group maintains a risk register. This is useful as a tool for shaping strategic planning but currently lacks the quantitative data and process needed to generate accurate risk assessments.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Arbitrage and Capacity Firming in Coordination with Day-Ahead Bidding of a Hybrid PV Plant

A hybrid PV plant (HPP) combines a photovoltaic (PV) plant with a battery energy storage system (BESS), which is considered a promising step towards the future of renewable power plants by the U.S. Department of Energy. When the renewable penetration reaches a significant level, a hybrid PV plant can bid in as a controllable thermal plant in the future electricity market. In this study, a bidding and BESS scheduling model is proposed for the HPP. The robust optimization (RO) technique has been utilized to identify the worst-case scenario of uncertainties during the bidding process. To address the overly conservative issue of the single-stage RO, we have decoupled the BESS schedule for arbitrage and PV capacity firming by a two-stage RO formulation. By comparing the output of single-stage RO and two-stage RO, the two-stage RO bids and schedules in a more aggressive manner, which increases the income of HPP. Also, the penalty of under-generation is considered in our model so that the day-ahead bidding decision and arbitrage schedules can be adjusted based on the potential UNDER-GENERATION penalty. Because the proposed model is non-convex and contains multi-stages, the Column-and-Constraint Generation (C&CG) algorithm is applied to the model as the solution. The proposed model has shown better economic performance compared to a state-of-art single-stage bidding method in case studies.

BESS scheduling↗
DOE OSTI2021

Stochastic Continuous-time Flexibility Scheduling and Pricing in Wholesale Electricity Markets

Large-scale integration of intermittent renewable energy sources (RES) is calling for additional flexibility resources as well as more advanced modeling and optimization techniques to account for the increasing uncertainty and variability in power systems operation. As the RES integration gains momentum, the magnitude and frequency of their variations increase, which may trigger ramping scarcity events in real-time power systems operation. This necessitates revisiting the present definition of power systems flexibility and reserve services to reflect their robustness and adequacy towards sub-interval variations of the load and RES, as well as adjusting the operation models to accommodate the new reserve services. This project took a fundamental approach and aimed at developing continuous-time scheduling and pricing model that accurately models the continuous-time variations of load and RES and efficiently deploys the ramping capability of flexible resources to compensate the sources of variability and uncertainty in the market. In this regard, this project pursued the following goals: Developing stochastic multi-fidelity continuous-time optimization models for scheduling of energy storage (ES) systems and flexible loads in wholesale energy markets; Developing the theory and practices of continuous-time locational marginal pricing for valuating energy storage systems and flexible loads in wholesale energy markets; Developing function space solution approach to convert the proposed stochastic multi-fidelity continuous-time optimization models into tractable mixed-integer linear optimization models; and Defining flexibility reserve as a new type of reserve in markets that would enable ultimate participation of energy storage devices in provision of services to compensate the variability and uncertainty of RES in electricity markets. This project successfully completed all five major tasks defined in the SOPO, and produced 8 high-impact journal papers, 6 conference papers, 3 published U.S. patents, and one web-based software for continuous-time operation optimization of power systems. The application of the proposed flexibility reserve and the stochastic multi-fidelity continuous-time operation scheduling models would modify the forward commitment and schedule of generating units, ES devices and flexible loads, and would line up the resources in such a way that the composition of available resources is better prepared to respond to the sub-hourly variations of the load and renewable resources in real-time operation. Therefore, this project paves the way to sustainable, reliable, and economic integration of renewable energy resources in power system, supporting the progress towards reaching the national targets on energy independence. Even if the proposed models offers a radically different point of view as compared to existing models, it does not alter fundamentally the architecture of power systems operations, nor the complexity of the scheduling problem, so the integration of this project in power systems is extremely practical.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Machine Learning–Based Condition Monitoring of a Circulating Water System of a Canadian Nuclear Plant

With the need to maintain long-term reliable energy using nuclear power plants, there is an underlying demand to ensure that the maintenance of plant components and systems is also done in an efficient and cost-effective manner. One way to achieve this is by moving from time-based maintenance to condition-based maintenance. The research presented in this paper focuses on applying statistical and machine-learning-based methods to capture anomalies within data for fault detection to further develop into condition monitoring. This paper focuses on system data for a circulating water system (CWS) of a pressurized heavy-water reactor for detecting anomalies. The different methodologies used for detecting and capturing anomalies in the CWS data are matrix profile, density-based spatial clustering of applications with noise (DBSCAN), and support vector machines (SVMs). Matrix profile and DBSCAN are used to distinguish between normal data and anomalous data. This paper presents a hybrid method using DBSCAN and SVM when a portion of the data is used for DBSCAN to generate clusters. This portion of data is then used to train the SVM along with the clusters generated by DBSCAN as output. SVM is then tested on unseen data as a predictive tool, which can work in real time to categorize data points as either normal or anomalous. This paper presents results that show the high accuracies of DBSCAN and SVM in capturing anomalies within the data for a CWS for fault detection. Thus, the maintenance plan would be focused on component condition rather than a time-based schedule by switching to an automated system to identify and predict faults within a CWS.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Production and Performance of High Sulfur Concentration Waste Glasses (FY21)

In FY21 Savannah River National Laboratory (SRNL) was tasked to investigate the practical aspects of low activity waste (LAW) glass production with high sulfur loading for the Office of River Protection (ORP). Relationships between sulfur solubility, retention, and melter resonance need to be evaluated to refine waste loading limits and the super saturated melting (triple melt, grind, and wash) methodology. The impact of high sulfur concentration on durability and phase stability (crystallization and liquid-liquid immiscibility) during slow cooling also needs to be further evaluated. To accomplish this, SRNL proposed scaled melter testing using simulants with matched physicochemical properties to melter feed, as opposed to laboratory reagents. This type of testing is expected to validate applicability to design parameters and functional criteria expected during unit operations. This work was expected to commence in FY21, with the first melter tests being performed near the end of the FY. However, reduced access to Savannah River Site and personnel availability during the COVID-19 pandemic significantly reduced the amount of time and resources available to perform the task. This report documents the experimental plan and progress towards this task. The following is a summarized list of scheduled testing that will be performed on feed, condensate, cold cap and glass: 1) Melter runs; 2) Product consistency test (PCT); 3) Inductively coupled plasma optical emission spectroscopy (ICP-OES); and 4) Optical (OM) and scanning electron microscopy (SEM).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Data Fusion to Enhance Quality Control and Analysis with Instruments at the Marine and Coastal Research Laboratory

Deploying environmental monitoring instruments in the marine environment can be challenging, facing challenges around device survivability, biofouling and corrosion, and consistent data collection. This project explores the use of data fusion – the process of integrating multiple data sources to produce more consistent, accurate, and useful information – to build a consistent long-term monitoring system at the Marine and Coastal Research Laboratory (MCRL) in Sequim, Washington. Unused instruments that had been acquired from past projects were inventoried and deployments planned on the MCRL pier and floating dock. A total of 8 instruments were deployed including a tide gauge, hydrophone, acoustic Doppler current profiler (ADCP), photosynthetically active radiation (PAR) sensors, meteorological station, and three water quality sensors. Deployments were planned to be well-protected around the pier structure and a maintenance schedule was created for cleaning and recalibration. An automated data pipeline was created to aggregate data on edge computers that push data to Amazon Web Services (AWS) cloud storage every 15 minutes, performing automated quality control and data transformations using the Time Series Data Analytical Toolkit (TSDAT). Continued efforts are underway to maintain this system into the future, take a data-driven approach to maintenance scheduling, improve the reliability of the system, and share the data with a variety of end-users.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Hydropower Flexibility and Environmental Tradeoffs Analysis

The importance of hydropower increases as the power grid evolves with the higher variable renewable contribution. As conventional thermal power plants are retired, the importance of hydropower contribution increases to balance the variability of solar and wind generation. However, reservoir water resources are constrained by multiple constraints, and variability of water inflow to the reservoirs creates limitations to dam water releases for power grid needs. Coordinating multiple tools, including water resources, ecological, and technical and economic power grid modeling, informs dam water releases. The case study, the Columbia River Basin multipurpose reservoir project, is operated for hydropower production and many other purposes considering the aquatic habitat of the river basin. Specifically, the river basin fish population is a vital element for the tribal community of the river basin. We integrated a production cost model, a water resource model, and decades of tribal knowledge to analyze the fish-friendly way of operating Columbia hydropower scheduling and grid impacts. We measure power grid impacts for various water resources planning scenarios in terms of total system operating cost, system reliability indicators, changes in wind and solar generation and curtailments, local marginal prices, and revenue for hydropower producers. The study results inform reservoir operating rules decisions from hydropower power producers, system operators, other water users, tribes, environmentalists, and other stakeholders.

Columbia River↗
DOE OSTI2023

Multistage robust optimization for the day-ahead scheduling of hybrid thermal-hydro-wind-solar systems

The integration of large-scale uncertain and uncontrollable wind and solar power generation has brought new challenges to the operations of modern power systems. In a power system with abundant water resources, hydroelectric generation with high operational flexibility is a powerful tool to promote a higher penetration of wind and solar power generation. In this paper, we study the day-ahead scheduling of a thermal-hydro-wind-solar power system. The uncertainties of renewable energy generation, including uncertain natural water inflow and wind/solar power output, are taken into consideration. We explore how the operational flexibility of hydroelectric generation and the coordination of thermal-hydro power can be utilized to hedge against uncertain wind/solar power under a multistage robust optimization (MRO) framework. To address the computational issue, mixed decision rules are employed to reformulate the original MRO model with a multi-level structure into a bi-level one. Column-and-constraint generation (C &CG) algorithm is extended into the MRO case to solve the bi-level model. The proposed optimization approach is tested in three real-world cases. Furthermore, the computational results demonstrate the capability of hydroelectric generation to promote the accommodation of uncertain wind and solar power.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Well-Controlled Hydro-thermo-chemical Stimulation of a Coso Geothermal Well to Enhance Productivity

The goal of this project was to demonstrate controlled fracturing and permeability increase to enhance resource production and power generation at Coso. It was planned to stimulate at least two intervals in the Well 73-18RD with zonal isolation using advanced high-temperature packer technology. The anticipation was that a hydraulic fracture would form in one zone and in the second zone natural fractures would reopen, shear and extend, thereby increasing fluid communication in the field. In both cases, the intent was to carefully design the stimulation to take advantage of the relative roles of hydraulic pressure, thermal stress and chemical (“hydro-thermo-chemical”) dissolution. The project had planned to use the Welltec Annular Barrier (WAB) system developed as part of another DOE-funded project which was on schedule to be ready for field deployment. If successful, the Coso Operating Company would incorporate this approach into their ongoing well maintenance in other wells increasing the total MWs produced. The project had multiple tasks and the objective of Task 1 was to develop a workover plan, to build a geologic model, to design a stimulation program, and to work with the operating and services companies to develop a detailed budget and obtain the necessary permits and sundry notices. In Phase 2 the workover plan would be implemented, the designed stimulation would be carried out, and subsequently the well would logged and tested to measure the impact of stimulation. Per sponsor request, a Pre-Task 1 activity with a Go/No Go decision point was scheduled in Task 1.

02 PETROLEUM↗
DOE OSTI2022

Towards Net Zero: Modeling Approach to the Right-Sized Facilities

As the concentration of greenhouse gases (GHGs) in the atmosphere increases, the concerns about carbon emissions are growing. Several net-zero initiatives are taking place around the globe to achieve a balance between the GHGs put into the atmosphere and those taken out. While most efforts present a sectorized approach, this paper describes the importance of integrating information across different sectors for effective modeling of carbon emissions and holistic reduction opportunity analysis. Using the Idaho National Laboratory (INL) campus as a test case, this work provides a web-based tool for INL stakeholders to use when engaging in strategic planning to achieve carbon emissions reduction. This net-zero engineering support tool (NEST) uses historical data as foundational information for applying the modeling framework. Prediction of CO 2 emissions throughout project completion integrates various approaches and schedules aimed at energy conservation, fleet decarbonization, and other GHG reduction activities. Using NEST, stakeholders can visualize carbon emissions, electricity consumption, and costs for decision making when planning the pathway for reaching carbon net zero. The INL’s initiative to transition into an EV fleet was used to demonstrate the developed framework and the advantages of using NEST. It was shown that electrifying different fossil-fueled campus vehicles before 2030 with aggressive replacement schedules require high annual capital expenditure (CAPEX), which may not be available. The tool allows decision makers to test different replacement schedules and prioritize those that yield CAPEX below a certain threshold while meeting target milestones. While the demonstration focused on vehicle electrification, the developed framework lays the foundation for further quantitative analysis of other GHG reduction activities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Wash Vehicle Fleet Sizing for Contingency Planning Against Dust Storms

Wash vehicles containing either high- or low-pressure water sprayers, a collection of rotating brushes, or a combination of these, are frequently utilized in concentrating solar power (CSP) plants to maintain a high level of optical efficiency in the solar field. In recent years, multiple modeling approaches have been developed to obtain fleet sizes and mirror-washing schedules that optimize the tradeoff of vehicle capital and use costs and labor versus lost revenues due to soiling. These planning models cover normal operating conditions well but do not consider rare events such as dust storms which can cause a significant reduction in receiver productivity, or shut down operations until most or all of the solar field's mirrors have been cleaned. To that end, we propose a methodology that evaluates whether additional capital should be deployed to hedge against these events by weighing the net present value of the expected benefits against the capital costs. The output of this method is a breakeven frequency, a metric we sue to determine whether an additional vehicle should be purchased to address the contingency of dust storms by comparing it to the expected annual storm frequency We develop a small collection of case studies using commercial-scale CSP tower plants and obtain breakeven frequencies that mostly fall between 0.1 and 1.0 storms per year, depending on the existing fleet size and storm severity.

concentrating solar power↗
DOE OSTI2021

Wash Vehicle Fleet Sizing for Contingency Planning Against Dust Storms: Preprint

Wash vehicles containing either high- or low-pressure water sprayers, a collection of rotating brushes, or a combination of these, are frequently utilized in concentrating solar power (CSP) plants to maintain a high level of optical efficiency in the solar field. In recent years, multiple modeling approaches have been developed to obtain fleet sizes and mirror-washing schedules that optimize the tradeoff of vehicle capital and use costs and labor versus lost revenues due to soiling. These planning models cover normal operating conditions well but do not consider rare events such as dust storms which can a significant reduction in receiver productivity, or shut down operations until most or all of the solar field’s mirrors have been cleaned. To that end, we propose a methodology that evaluates whether additional capital should be deployed to hedge against these events by weighing the net present value of the expected benefits against the capital costs. The output of this method is a breakeven frequency, a metric we sue to determine whether an additional vehicle should be purchased to address the contingency of dust storms by comparing it to the expected annual storm frequency We develop a small collection of case studies using commercial-scale CSP tower plants and obtain breakeven frequencies that mostly fall between 0.1 and 1.0 storms per year, depending on the existing fleet size and storm severity.

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