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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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At least 253 records · Page 14

Energy Paths for the Yurok People

This Yurok Tribe energy strategic planning study examined electricity usage, costs and infrastructure, as well as electricity needs on the Reservation. It also assessed the Tribe’s energy resources. Equipped with this information, the project team conducted an energy options analysis that examined different project opportunities and identified key projects that are both feasible to implement and will help the Tribe reach its stated Energy Vision. A key finding of the energy needs assessment is that there are still numerous households that are without grid electric power, and it is likely that most of them will remain disconnected from the grid because of their remoteness. To provide these community members with reliable, affordable, modern energy services their homes will need to be electrified via a robust off-grid energy services program that installs and maintains off-grid energy systems. This is the key need that is explored and addressed in this plan. The approach taken is to establish a new business entity, a Tribal Energy Authority or Utility, that will operate a Tribal Energy Program. The Energy Strategic Plan identifies a number of potential funding sources that could be used to support both the On-grid and Off-grid Energy Programs. This plan also promotes continued efforts to reduce electricity consumption through the implementation of energy efficiency measures in existing facilities and the enforcement of a strong energy-efficient building code for all new construction on the Reservation. Finally, the plan promotes added resilience at critical Tribal facilities on the Reservation by recommending that battery energy storage systems and microgrid controls be coupled with rooftop solar PV systems to create cutting edge microgrid facilities that can provide critical power services to Tribal facilities when the main electric grid is shutdown.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The Solar Curtailment Paradox

This presentation summarizes work recently published in a Joule article, "The Curtailment Paradox in the Transition to High Solar Power Systems." Rising penetrations of variable renewable energy (VRE) in power systems are expected to increase the curtailment of these resources because of oversupply and operational constraints. We evaluate the effect on curtailment from various flexibility approaches, including storage, thermal generator flexibility, operating reserve eligibility rules, transmission constraints, and temporal resolution, by using a highly resolved realistic system. Results reveal two aspects of a curtailment paradox as the system evolves to higher solar penetration levels. First, thermal generator parameters, especially in restricting minimum operating levels and ramp rates, affect VRE curtailment more in mid-PV penetration levels (~25%–40%) but much less at lower (~20%) or higher (~45%) PV penetration levels. Second, although allowing VRE and storage to provide operating reserve results in significant operating costs and curtailment benefits, the price suppression effect from these resources reduces incentives for PV to provide operating reserves with curtailed energy.

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

Endogenizing Probabilistic Resource Adequacy Risks in Deterministic Capacity Expansion Models

In this work, we demonstrate how power system capacity expansion models can understate the stochastic effects of thermal outages when considering resource availabilities on an hourly expected value basis, yielding system designs with multiple orders of magnitude more shortfall risk than stated adequacy targets. We develop a novel approximation approach to efficiently endogenize awareness of this risk in a deterministic, linear capacity expansion framework. We compare this approach to exogenous tuning of an energy reserve margin, the leading alternative method to compensate for unmodeled probabilistic shortfall risk. Empirical results from a test system show that the new endogenous method cost-effectively meets all regional reliability targets with a single optimization solve, and produces a near-identical system design as the incumbent method without the need for repeated re-optimizations to find an appropriate reserve level. The endogenous method may also use iterative re-optimizations to further improve solution quality, although these incremental benefits were modest in the system studied.

capacity expansion modeling↗

Economic Dispatch Optimization of Multi-Unit SMR Site

With the increase of integration of variable renewable into the grid, grid resilience can be compromised without flexible electricity suppliers. Flexible operation of NPP can expand the scope of integration of new nuclear power plants in regions with high share of renewables. It also provides opportunity to increase profits through participation in ancillary services. In this research, NuScale modules are used as the case study. NuScale is an integrated pressurized water reactor with thermal power of 250 MWth. Having multiple units can provide higher flexibility in changing power levels and supplying the grid with electricity all year long. Additionally, load-following might perturbate the ordered sequence of refueling (every 24 months for NuScale). To maintain the 2 year refueling cycles, the loading patterns will need to be adjusted in a year-to-year basis, resulting in additional unnecessary costs. Another solution is to find the optimal outage schedule. This will also shift the focus of the planned outage to a more optimized predictive outages and maintenance. Results from short-term optimization (i.e., daily participation in energy and ancillary services markets) shows that average commitment to regulation down ancillary service markets during late night and early morning hours can increase revenues. Participating in upward reserves during pre-work commuting hours and early evening hours can also generate additional revenues due to high ramp up of electricity demand. Having multiple units at a single site can also help operate flexibly. Results from long-term optimization show that daily fluctuation in electric power is usually handled by few units while other units operate on base-load profile. It is possible to combine base-load operation with flexible operation to extend component remaining useful life in some units and find optimal outage schedule for the units.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Effects of random forest modeling decisions on biogeochemical time series predictions

Abstract Random forests (RF) are an increasingly popular machine learning approach used to model biogeochemical processes in the Earth system. While RF models are robust to many assumptions that complicate deterministic models, there are several important parameterization decisions for appropriate use and optimal model fit. We explored the role that parameter decisions, including training/testing data splitting strategies, variable selection, and hyperparameters play on RF goodness‐of‐fit by constructing models using 1296 unique parameter combinations to predict concentrations of nitrate, a key nutrient for biogeochemical cycling in aquatic ecosystems. Models were built on long‐term, publicly available water quality and meteorology time series collected by the National Estuarine Research Reserve monitoring network for two contrasting ecosystems representing freshwater and brackish estuaries. We found that accounting for temporal dependence when splitting data into training and testing subsets was key for avoiding over‐estimation of model predictive power. In addition, variable selection, the ratio of training to testing data, and to a lesser degree, variables per split and number of trees, were significant parameters for optimizing RF goodness‐of‐fit. We also explored how model parameter decisions influenced interpretation of the relative importance of predictors to the model, and model predictor‐dependent variable relationships, with results suggesting that both data structure and model parameterization influence these factors. Because much of the current RF literature is written for the computational and statistical science communities, the primary goal of this study is to provide guidelines for aquatic scientists new to machine learning to apply RF techniques appropriately to aquatic biogeochemical datasets.

54 ENVIRONMENTAL SCIENCES↗

Technical challenges of integrating the Space Shuttle

A review is presented of the technology involved in integrating the Space Shuttle system. A powered flight analysis of the Shuttle is presented, touching upon the following areas: ascent profile and abort mode integration, sizing and design, control of load factor by a stage thrust shaping, structural load constraints, flight performance reserve and trajectory design for the orbital flight test. A discussion is presented of aerothermodynamics including aerodynamic and plume heating. Flight control and separation is considered with attention paid to liftoff, ascent to booster staging, elevon load relief, booster tailoff thrust mismatch and gimbal limitations and booster separation. Structural analysis and dynamics is examined, considering: vehicle loads and modes and the pogo effect. Propulsion aspects (hydraulics, the LH2 recirculation system, the antigeyser system, the pressurization system, etc.), ground vibration tests, separation system verification and flight readiness firing are all described.

Martin, A. C.↗

ISRU Evaluation of Artemis Campaign Sites: Considerations and Methodology

The Artemis campaign has stated goals of ‘sustainable exploration’ [1] which includes In-Situ Resource Utilization (ISRU). The selection of the lunar polar region for Artemis was in part due to the identification of water in permanently shadowed regions (PSRs) which is of both scientific and exploration interest. The potential use of this water (as is, or as oxygen/hydrogen) for NASA and commercial applications, such as refueling vehicles, for power systems, or supplying life support consumables, is reflected in NASA’s Moon to Mars objectives (LI-7) [2]. These objectives also specify the need to locate and characterize the lunar water such that a water ‘reserve’ can be identified (AS-3). While infusion of ISRU capabilities is not planned for Artemis III, it is an opportunity to collect information to identify water reserves for later Artemis and commercial use. Selection of an Artemis III site with ISRU consideration will help advance the infusion of ISRU into later missions.

In situ resource utilization↗

A Multi-Stage Stochastic Risk Assessment With Markovian Representation of Renewable Power

Probabilistic forecasts provide a distribution of possible outputs and so can capture the uncertainty and variability of Variable Renewable Energy (VRE). However, taking advantage of uncertainty information has practical challenges that make it difficult to integrate probabilistic forecasting into control room decision-making. This paper proposes a novel use-case for probabilistic forecasts by incorporating them into the hour-ahead operations for situational awareness via a risk-averse multi-stage stochastic program. We employ a Markovian representation of the probabilistic forecasts that enables the formulation of the multi-stage problem and avoids a scenario generation phase. We test the model on a realistically sized system to assess risk and showcase the capability of using probabilistic renewable forecast as input to produce probabilistic output forecasts of future system states. The results show that the model can capture time consistency in the reserves and Area Control Error (ACE) forecast. The solution times are adequate for risk profiling in hour-ahead timescales.

forecasting↗

Compound cycle engine program

The Compound Cycle Engine (CCE) is a highly turbocharged, power compounded power plant which combines the lightweight pressure rise capability of a gas turbine with the high efficiency of a diesel. When optimized for a rotorcraft, the CCE will reduce fuel burned for a typical 2 hr (plus 30 min reserve) mission by 30 to 40 percent when compared to a conventional advanced technology gas turbine. The CCE can provide a 50 percent increase in range-payload product on this mission. A program to establish the technology base for a Compound Cycle Engine is presented. The goal of this program is to research and develop those technologies which are barriers to demonstrating a multicylinder diesel core in the early 1990's. The major activity underway is a three-phased contract with the Garrett Turbine Engine Company to perform: (1) a light helicopter feasibility study, (2) component technology development, and (3) lubricant and material research and development. Other related activities are also presented.

Bobula, G. A.↗

Compound cycle engine program

The Compound Cycle Engine (CCE) is a highly turbocharged, power compounded power plant which combines the lightweight pressure rise capability of a gas turbine with the high efficiency of a diesel. When optimized for a rotorcraft, the CCE will reduce fuel burn for a typical 2 hr (plus 30 min reserve) mission by 30 to 40 percent when compared to a conventional advanced technology gas turbine. The CCE can provide a 50 percent increase in range-payload product on this mission. A program to establish the technology base for a Compound Cycle Engine is presented. The goal of this program is to research and develop those technologies which are barriers to demonstrating a multicylinder diesel core in the early 1990's. The major activity underway is a three-phased contract with the Garrett Turbine Engine Company to perform: (1) a light helicopter feasibility study, (2) component technology development, and (3) lubricant and material research and development. Other related activities are also presented.

Bobula, G. A.↗

O-THREE: A high altitude, remotely piloted vehicle

A conceptual design for a remotely piloted vehicle to be used for ozone research above 80,000 feet was developed as part of the one-semester NASA/Universities Space Research Association Aerospace Design course at Case Western Reserve University in Fall 1989. The O-Three design team chose as its mission requirements a cruise altitude of 100,000 ft, a range of 1000 n.m., an endurance of 6 hrs., a 1000 lb payload, and a power to payload of 2 kW. These are based on the Boeing requirements for an ozone research vehicle. In addition, the vehicle should not be restricted to operation over any particular global location. Efforts were made to minimize atmospheric contamination that might increase the rate of ozone depletion and cause discrepancies in data accuracy. Design was not limited to today's level of technology. The design team was divided into four groups: aerodynamics, structures, stability, and control. The specifications and performance estimates for cruise at altitude are given in tabular form.

Source record↗

An economic assessment of behind-the-meter photovoltaics paired with batteries on the Hawaiian Islands.

Due to natural variability and uncertainty, the ever-increasing penetration of solar generation in Hawaii presents challenges to power grid operators to maintain reliable system operation. Demand response (DR) has the potential to be a cost-effective tool for Hawaii to reach its aggressive renewable energy goals while maintaining the reliability of power grids. The Hawaii Public Utilities Commission has approved the Hawaiian Electric Company's revised portfolio of DR programs. The companies have released a grid services purchase agreement and subscribed an initial tranche of load into their DR programs. This paper presents innovative analytical methods and comprehensive economic assessment for distributed photovoltaics (PV) paired with battery energy storage systems (BESSs) for two new DR programs, including fast frequency response and capacity grid service. Optimal dispatch and sizing methods are proposed for the paired system considering different tariff schedules and PV compensation programs across five islands. It was found that while the best resource configuration and potential economic benefits vary with tariff structure, a BESS paired with PV can be optimally dispatched to generate multiple value streams simultaneously. Compensation from DR programs is an important value stream to help increase the cost-effectiveness of the integrated system.

Battery energy storage system↗

Technology developments for a compound cycle engine

The Compound Cycle Engine (CCE) is a highly turbocharged, power compounded power plant which combines the light weight pressure rise capability of a gas turbine with the high efficiency of a diesel. When optimized for a rotorcraft, the CCE will reduce fuel burned for a typical 2 hour (plus 30 min reserve) mission by 30 to 40 percent when compared to a conventional advanced technology gas turbine. The CCE can provide a 50 percent increase in range-payload product on this mission. Results of recent activities in a program to establish the technology base for a CCE are presented. The objective of this program is to research and develop those critical technologies which are necessary for the demonstration of a multicylinder diesel core in the early 1990s. A major accomplishment was the initial screening and identification of a lubricant which has potential for meeting the material wear rate limits of the application. An in-situ wear measurement system also was developed to provide accurate, readily obtainable, real time measurements of ring and liner wear. Wear data, from early single cylinder engine tests, are presented to show correlation of the in-situ measurements and the system's utility in determining parametric wear trends. A plan to demonstrate a compound cycle engine by the mid 1990s is included.

Bobula, George A.↗

Use Probabilistic Forecasts in Reliable and Economic Electricity Market Scheduling and Operations

The value of probabilistic forecasts in electricity market operations is being increasingly recognized lately, however, the use is still limited. This study demonstrates two cases of using probabilistic forecasts in scheduling and operations of the California electricity market. We first develop a data-driven method to give weather-informed estimates of ramping reserves based on short-term probabilistic solar irradiance forecasts. By using forecasts across multiple sites, our proposed method presents advantages over the real-world baseline in terms of system reliability and economics. Our second case uses probabilistic hydro power forecasts in the scheduling of a hydro power plant under economic and environmental constraints. By optimizing the bids into both the day-ahead and real-time markets, our results demonstrate considerable economic benefits.

13 HYDRO ENERGY↗

Modeling the Strategic Behavior of an Active Distribution Network in the ISO Markets

With increasing integration of distributed energy resources (DERs), active distribution networks (ADNs) can actively participate in the electricity markets by dispatching their DERs, which can change the existing electricity market paradigm. It is essential to investigate the strategic behaviors of ADNs and their DER dispatch when they participate in the wholesale market as price-makers. This paper proposes a bi-level optimization model to study the strategic behavior of an ADN in both energy and reserve markets. The optimal scheduling of DERs in the ADN is modeled as the upper level problem and the joint energy and reserve market-clearing of the ISO is modeled as the lower-level problem. The two-level optimization models exchange bidding information and energy/reserve prices with each other. The proposed bi-Ievel optimization problem is converted to a mathematical programming with equilibrium constraints (MPEC) by using Karush-Kuhn Tucker (KKT) conditions and strong duality theory. Further, the MPEC problem is reformulated as a computationally-solvable mixed integer second order cone programming (MISOCP) model. The simulation results on an illustrative case demonstrate the impact of the strategic bidding of the ADN on the day-ahead energy and reserve market prices.

active distribution network↗

The power reliability event simulator tool (PRESTO): A novel approach to distribution system reliability analysis and applications

The growing interest in onsite solar photovoltaic and energy storage systems is partially motivated by customer concerns regarding grid reliability. However, accurately assessing the effectiveness of PVESS in mitigating these interruptions requires a comprehensive understanding of location-specific outage patterns and the ability to simulate realistic scenarios. To address the gap, we introduce the Power Reliability Event Simulation TOol (PRESTO), the first publicly available tool that simulates location-specific power interruptions at the county level. PRESTO allows for a more realistic assessment of system reliability by considering the unpredictability and location-specific patterns of power interruptions. We applied PRESTO in a case study of a single-family home across three U.S. counties, examining the performance of a solar photovoltaic system with 10kWh of battery storage during short-duration power interruptions. Our findings show that this system reliably met 93% of energy demand for essential non-heating and cooling loads, fully serving these loads in 84% of events, despite the constraints of daily time-of-use bill management which limits the battery's state-of-charge reserve. However, when heating and cooling loads were included, system performance decreased significantly, with only 70% of demand met and full service in 43% of events. These results highlight the challenges of using solar photovoltaic and energy storage systems for short-duration outages, emphasizing the need to consider factors like battery size and grid charging strategies to improve reliability. Our study demonstrates the practical applications of PRESTO, providing valuable insights into potential mitigation strategies including grid charging and optimizing battery size.

14 SOLAR ENERGY↗

Bayesian Structural Time Series for Behind-the-Meter Photovoltaic Disaggregation: Preprint

Distributed photovoltaic (PV) generation often occurs ``behind the meter": a grid operator can only observe the net load, which is the sum of the gross load and distributed PV generation. This lack of observability poses a challenge to system operation at both bulk level and distribution level. The lack of real-time or near-future disaggregated estimates of gross load and PV generation will lead to over scheduling of energy production and regulation reserves, reliability constraints violations, wear and tear of controller devices, and potentially cascading failures of a system. In this paper we propose the use of a Bayesian Structural Time Series (BSTS) model with local solar irradiance measurements to disaggregate the summed PV generation and gross load signals at a downstream measurement site. BSTSs are a highly expressive model class that blends classic time series models with the powerful Bayesian state space estimation framework. Disaggregation is done probabilistically, which automatically quantifies the uncertainties of the estimated PV generation and gross load consumption. Depending on the data availability in real-time, it can be used to disaggragate PV and gross load at customer site, or can be used at the feeder level. In this paper, we focus on solving the problem at feeder level. We compare the performance of a BSTS model as well as a handful of state-of-the-art methods on a Pecan Street AMI dataset, using the National Solar Radiation Database (NSRDB) to estimate local irradiance.

Bayesian structural time series↗