Nanomembrane Interactive Forward Osmosis (FO) Polymers for Desalination and Remediation
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29 ENERGY PLANNING, POLICY, AND ECONOMY↗
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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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Learning infinite-horizon average-reward restless multi-action bandits via index awareness
We consider the online restless bandits with average-reward and multiple actions, where the state of each arm evolves according to a Markov decision process (MDP), and the reward of pulling an arm depends on both the current state of the corresponding MDP and the action taken. Since finding the optimal control is typically intractable for restless bandits, existing learning algorithms are often computationally expensive or with a regret bound that is exponential in the number of arms and states. In this paper, we advocate \textit{index-aware reinforcement learning} (RL) solutions to design RL algorithms operating on a much smaller dimensional subspace by exploiting the inherent structure in restless bandits. Specifically, we first propose novel index policies to address dimensionality concerns, which are provably optimal. We then leverage the indices to develop two low-complexity index-aware RL algorithms, namely, (i) GM-R2MAB, which has access to a generative model; and (ii) UC-R2MAB, which learns the model using an upper confidence style online exploitation method. We prove that both algorithms achieve a sub-linear regret that is only polynomial in the number of arms and states. A key differentiator between our algorithms and existing ones stems from the fact that our RL algorithms contain a novel exploitation that leverages our proposed provably optimal index policies for decision-makings.
Xiong, Guojun↗
A Cross-Domain Optimization Framework of PMU and Communication Placement for Multidomain Resiliency and Cost Reduction
Phasor measurement units (PMUs) play a crucial role in real-time monitoring and control of power grids. They rely on a communication network to transfer measurement data to the phasor data concentrator (PDC) for further processing and analysis. In this paper, a resilient cross-domain PMU and communication link placement method for minimizing the overall installation cost of the wide-area measurement system (WAMS) is proposed. Here, the main idea is to break down the barrier between the power grid domain and the communication domain, and consider the impact of one when design the other. The PMU placement in the power grid domain takes into account the cost of communication links by generating multiple solutions with equally minimum PMU costs for communication link placement evaluation. On the other hand, the communication link placement problem reduces the cost by customizing the routing policies based on the different roles of PMUs in grid observability. The proposed WAMS design is capable of withstanding any single component failure in the power domain (PMU failure or power branch failure) or in the communication domain (communication link failure or PDC failure). Numerical study on the IEEE 57-bus system reveals that the developed cross-domain optimization framework can significantly reduce the overall installation cost of WAMS while attaining multi-domain resiliency.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Final Technical Report-WestSmart EV: Western Smart Plug-in Electric Vehicle Community Partnership
The WestSmartEV (WSEV) project has accelerated adoption of plug-in electric vehicles (PEV) throughout the PacifiCorp/Rocky Mountain Power’s (RMP) service territory in the intermountain west by developing a large-scale, sustainable PEV charging infrastructure network with coordinated PEV adoption programs. The project objectives have strategically deployed 79 DC fast charging to create two primary electric interstate highway corridors along I-15 and I-80; incentivized installation of Level 2 AC chargers at workplace locations; incentivized the purchase of PEVs; provided all electric solutions for first-mile and last-mile trips, including electrified mobility service; provided centralized data collection, analysis, modeling, and tool development to inform investment and policy decisions; and developed education outreach materials and conducted workshops across the WSEV region.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Initial Feasibility Assessment of Agrivoltaics in Jackson County, IL
Consistent with concerns raised in other rural communities, the agricultural community in Jackson County, IL is reluctant to install ground based photovoltaic (PV) systems on prime agricultural land. Agrivoltaic solutions have the potential to mitigate community concerns of conversion of farmland to solar energy by allowing for both energy production and farming practices to occur on the same land area. To assess the potential for agrivoltaics in Jackson County, IL, the Jackson County Coalition requested technical assistance to perform an initial technoeconomic assessment, resource assessment, and feasibility assessment based on the unique agricultural context present in the area. In this paper, the National Renewable Energy Laboratory (NREL) interviewed five Jackson County experts for five key crops (vineyards, strawberries, pumpkins, apple and pear orchards, and hemp) to examine potential for agrivoltaics integration and identify key barriers that could hamper development. NREL performed technoeconomic analysis for different agrivoltaic system designs to determine the economic constraints and opportunities of agrivoltaics development. Overall, there is no one path for agrivoltaics success in Jackson County. Pilot projects can assist in demonstrating agrivoltaic feasibility to stakeholders reluctant to be first adopters. Based on preliminary analyses, agrivoltaic integration with vineyards may prove most feasible as the per acre returns of grapes are comparable with the returns needed to offset higher solar development costs for agrivoltaic systems. In terms of technical specifications of solar, pumpkins and strawberries could be integrated into more traditional solar designs, but there are concerns with shading and pest control. There is no one size fits all solution, and many options may need exploring before a workable solution is found.
14 SOLAR ENERGY↗
A Model-Based Systems Engineering Approach for Effective Decision Support of Modern Energy Systems Depicted with Clean Hydrogen Production
A holistic approach to decision-making in modern energy systems is vital due to their increase in complexity and interconnectedness. However, decision makers often rely on narrowly-focused strategies, such as economic assessments, for energy system strategy selection. The approach in this paper helps considers various factors such as economic viability, technological feasibility, environmental impact, and social acceptance. By integrating these diverse elements, decision makers can identify more economically feasible, sustainable, and resilient energy strategies. While existing focused approaches are valuable since they provide clear metrics of a potential solution (e.g., an economic measure of profitability), they do not offer the much needed system-as-a-whole understanding. This lack of understanding often leads to selecting suboptimal or unfeasible solutions, which is often discovered much later in the process when a change may not be possible. This paper presents a novel evaluation framework to support holistic decision-making in energy systems. The framework is based on a systems thinking approach, applied through systems engineering principles and model-based systems engineering tools, coupled with a multicriteria decision analysis approach. The systems engineering approach guides the development of feasible solutions for novel energy systems, and the multicriteria decision analysis is used for a systematic evaluation of available strategies and objective selection of the best solution. The proposed framework enables holistic, multidisciplinary, and objective evaluations of solutions and strategies for energy systems, clearly demonstrates the pros and cons of available options, and supports knowledge collection and retention to be used for a different scenario or context. The framework is demonstrated in case study evaluation solutions for a novel energy system of clean hydrogen generation.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
U.S. Department of Energy Solar Decathlon
The U.S. Department of Energy (DOE) Solar Decathlon® Design Challenge is a collegiate competition that challenges student teams to design high-performance buildings that push the boundaries of the industry. In the 2020 Design Challenge, DOE piloted the Design Partners Program, a low-risk opportunity for builders and building owners to harness student innovation and explore zero energy design for current or upcoming projects. Design Partners provide a student team of architects and engineers with project requirements. By the end of the Design Challenge, Design Partners receive a zero-energy design alternative and cost estimate for their project. The collaboration allows Design Partners to incorporate innovative concepts such as grid-interactivity, resilience, and low embodied carbon in a low-risk environment. It also provides the future generation of engineers and architects with invaluable experience designing a building for a client under real-world circumstances. This article summarizes the current policy, technology, health, and economic trends that make zero energy buildings desirable and feasible, and presents the value of the Solar Decathlon to industry. We highlight innovative solutions 2020 Design Partner pilot projects are bringing to the building industry.
30 DIRECT ENERGY CONVERSION↗
The Realistic Potential of Soil Carbon Sequestration in U.S. Croplands for Climate Mitigation
Existing estimates of the climate mitigation potential from cropland carbon sequestration (C-sequestration) are limited because they tend to assume constant rates of soil organic carbon change over all available cropland area, use relatively coarse land delineations, and often fail to adequately consider the agronomic and socioeconomic dimensions of agricultural land use. This results in an inflated estimate of the C-sequestration potential. We address this gap by defining a more appropriate land base for cover cropping in the United States for C-sequestration purposes: stable croplands in annual production systems that can integrate cover cropping without irrigation. Our baseline estimate of this suitable stable cropland area is 32% of current U.S. cropland extent. Even an alternative, less restrictive definition of stability results in a large reduction in area (44% of current U.S. croplands). Focusing cover crop implementation to this constrained land base would increase durability of associated C-sequestration and limit soil carbon loss from land conversion to qualify for carbon-specific incentives. Applying spatially-variable C-sequestration rates from the literature to our baseline area yields a technical potential of 19.4 Tg CO 2 e yr –1 annually, about one-fifth of previous estimates. We also find the cost of realizing about half (10 Tg CO 2 e yr –1 ) of this potential could exceed 100 USD Mg CO 2 e –1 , an order of magnitude higher than previously thought. While our economic analyses suggest that financial incentives are necessary for large-scale adoption of cover cropping in the U.S., they also imply any C-sequestration realized under such incentives is likely to be additional.
54 ENVIRONMENTAL SCIENCES↗
Transferable Reinforcement Learning for Smart Homes: Preprint
To harness the great amount of untapped resources at the demand side, smart home technology plays a vital role in solving the "last mile" problem in smart grid. Reinforcement learning (RL), which has demonstrated an outstanding performance in solving many sequential decision-making problems, can be a great candidate to be used in smart home control. For instance, many studies have started investigating the load scheduling problem under dynamic pricing scheme. Based on those, this study aims at providing an affordable solution to encourage a higher smart home adoption rate. Specifically, we investigate combining transfer learning (TL) with RL to reduce the training cost of an optimal RL control policy. Given an optimal policy for a benchmark home, TL can jump-start the RL training of a policy for a new home, which has different appliances and user preferences. Simulation results show that by leveraging TL, RL training converges faster and requires much less computing time for new homes that are similar to the benchmark home. In all, this study proposes a cost-effective approach for training RL control policies for homes at scale, which ultimately reduces the controller's implementation costs, increases the adoption rate of RL controllers, and makes more homes grid-interactive.
ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION,↗
Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems
Quantum computing is a computational paradigm with the potential to outperform classical methods for a variety of problems. Proposed recently, the Quantum Approximate Optimization Algorithm (QAOA) is considered as one of the leading candidates for demonstrating quantum advantage in the near term. QAOA is a variational hybrid quantum-classical algorithm for approximately solving combinatorial optimization problems. The quality of the solution obtained by QAOA for a given problem instance depends on the performance of the classical optimizer used to optimize the variational parameters. In this paper, we formulate the problem of finding optimal QAOA parameters as a learning task in which the knowledge gained from solving training instances can be leveraged to find high-quality solutions for unseen test instances. To this end, we develop two machine-learning-based approaches. Our first approach adopts a reinforcement learning (RL) framework to learn a policy network to optimize QAOA circuits. Our second approach adopts a kernel density estimation (KDE) technique to learn a generative model of optimal QAOA parameters. In both approaches, the training procedure is performed on small-sized problem instances that can be simulated on a classical computer; yet the learned RL policy and the generative model can be used to efficiently solve larger problems. Furthermore, extensive simulations using the IBM Qiskit Aer quantum circuit simulator demonstrate that our proposed RL- and KDE-based approaches reduce the optimality gap by factors up to 30.15 when compared with other commonly used off-the-shelf optimizers.
97 MATHEMATICS AND COMPUTING↗
Powering Large Loads: Solutions Across Transmission, Utility, and Facility Scales
This report synthesizes current strategies for accommodating large load growth through a review of publicly available technical literature and media insights around the United States (U.S.). Solutions are organized across three implementation scales (transmission, utility, and facility) and categorized according to common implementation pathways (including structural expansion, operations and efficiency, upgrades, and planning and policy).
Valdez, Raquel Lynn [Sandia National Laboratories ↗
Citizen-Led Community Innovation for Food Energy Water Nexus Resilience
Food-energy-water (FEW) resources are necessary for the function of multiple socio-natural systems. Understanding the synergies and trade-offs in the FEW nexus, and how these interconnections impact earth’s systems, is critical to ensure adequate access to these resources in the future; an essential component for achieving the Sustainable Development Goals (Scanlon et al., 2017). Although, over the last decade, the identification of FEW nexus complexities has increased at a global (IPCC, 2018; D’Orodico et al., 2018), national (Lant et al., 2019), and city scale (Rushforth and Ruddell, 2018), these findings are yet to be adequately translated into ‘on the ground’ action due a lack of technical and political capacity (Weitz et al., 2017). Specifically, local FEW systems have been overlooked in these analyses (Scanlon et al., 2017; Lant et al., 2019), thus leaving small and medium towns vulnerable due to a lack of data and inadequate FEW system management. Building on three years of field-tested FEW nexus research in the Ruddell Lab, we argue that participatory citizen science projects, such as our FEWSION for Community Resilience initiative, can bridge the data-policy gaps that exist within local FEW system management by: 1) providing last mile data on the FEW system, and 2) translating local data into evidence-based solutions at a grassroots level. Thus, we present a broadly applicable framework and call to action for local scale participatory citizen science to solve complex FEW nexus issues at a local, regional, and national scale.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA/WVU Software Research Laboratory, 1995
In our second year, the NASA/WVU Software Research Lab has made significant strides toward analysis and solution of major software problems related to V&V activities. We have established working relationships with many ongoing efforts within NASA and continue to provide valuable input into policy and decision-making processes. Through our publications, technical reports, lecture series, newsletters, and resources on the World-Wide-Web, we provide information to many NASA and external parties daily. This report is a summary and overview of some of our activities for the past year. This report is divided into 6 chapters: Introduction, People, Support Activities, Process, Metrics, and Testing. The Introduction chapter (this chapter) gives an overview of our project beginnings and targets. The People chapter focuses on new people who have joined the Lab this year. The Support chapter briefly lists activities like our WWW pages, Technical Report Series, Technical Lecture Series, and Research Quarterly newsletter. Finally, the remaining four chapters discuss the major research areas that we have made significant progress towards producing meaningful task reports. These chapters can be regarded as portions of drafts of our task reports.
Sabolish, George J.↗
From Concept to Capital: How Developers Secure Private Investment
With an increased need for funding diversity in hydropower, private capital is becoming more important than ever. Investors are actively seeking opportunities, but what makes a project attractive for investment, and how can companies secure private equity or venture capital backing? This session brings together experts to discuss what capital providers look for in providing financing for hydropower projects. Panelists will explore key barriers - such as the lack of diversified portfolios and long-term revenue certainty - and strategies to overcome them through innovative financing mechanisms, partnerships, and market-driven solutions.
16 TIDAL AND WAVE POWER↗
Policy-Based Negotiation Engine for Cross-Domain Interoperability
A successful policy negotiation scheme for Policy-Based Management (PBM) has been implemented. Policy negotiation is the process of determining the "best" communication policy that all of the parties involved can agree on. Specifically, the problem is how to reconcile the various (and possibly conflicting) communication protocols used by different divisions. The solution must use protocols available to all parties involved, and should attempt to do so in the best way possible. Which protocols are commonly available, and what the definition of "best" is will be dependent on the parties involved and their individual communications priorities.
Vatan, Farrokh↗
Online Energy-optimal Routing for Electric Vehicles with Combinatorial Multi-arm Semi-Bandit
We have seen a rapid growth in the adoption of electric vehicle in today’s commercial mobility service market, from carrying passengers to the delivery of goods. One cardinal issue concerning the operation of EVs is the optimal routing of EV fleets with limited battery capacity. In this study, we investigate the energy-optimal online routing problem for the fleet of EVs, which focuses on identifying real-time minimum electricity consumption paths (MECP) for multiple OD pairs with limited information. We develop a multi-OD combinatorial multi-arm semi-bandit model (MCMAB) that uses the fleet of EVs as sensors in the transportation network and promotes the utilization of common information shared by different OD pairs. We further enrich the model with the path elimination policy to obtain MECP of high confidence while significantly reducing the number of learning iterations and the number of explorations needed. We demonstrate the effectiveness of the MCMAB and the efficiency of the path elimination policy with comprehensive numerical experiments in Manhattan, NYC. The results show that the proposed online routing algorithms can achieve near-optimal MECPs efficiently, and the quality of the solutions is significantly better than using the shortest travel time paths as approximate MECPs.
Chen, Xiaowei↗
Perspectives on Charging Medium- and Heavy-Duty Electric Vehicles
Electric vehicles (EVs) adoption is gaining momentum globally thanks to major technological advancements as well as policy actions and support from multiple stakeholders. EVs are well positioned to replace internal combustion engine vehicles for passenger cars, SUVs, vans, trucks, and buses, but a plethora of solutions is needed to provide effective, convenient, and affordable charging to different vehicles and for various applications. This talk focuses on charging of medium and heavy-duty vehicles, the second largest source of US transportation GHG emissions, providing an overview of charging needs for different applications. Moreover, we offer a deep dive on depot charging solutions for short-haul heavy-duty trucks based on a recent Nature Energy paper.
ADVANCED PROPULSION SYSTEMS↗
Trends and 2025 Insights on the Rise of Electric Vehicles in the USA
Plug-in electric vehicles (EVs) are reshaping the transportation energy landscape, providing a practical alternative to petroleum fuels for a growing number of applications. EV sales grew 55x in the past decade (2014-2024) and 6x since 2020, driven by technological progress enabled by policies to reduce transportation emissions as well as industrial plans motivated by strategic value of EVs for global competitiveness, jobs and geopolitics. In 2024, 22% of passenger cars sold globally were EVs and opportunities for EVs beyond on-road applications are growing, including solutions to electrify off-road vehicles, maritime and aviation. This Review updates and expands our 2020 assessment of the scientific literature and describes the current status and future projections of EV markets, charging infrastructures, vehicle-grid integration and supply chains in the USA. EV is the lowest-emission motorized on-road transportation option, with life-cycle emissions decreasing as electricity emissions continue to decrease. Charging infrastructure grew in line with EV adoption but providing ubiquitous reliable and convenient charging remains a challenge. EVs are reducing electricity costs in several US markets and coordinated EV charging can improve grid resilience and reduce electricity costs for all consumers. The current trajectory of technology improvement and industrial investments points to continued acceleration of EVs.
33 ADVANCED PROPULSION SYSTEMS↗