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At least 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Beyond Expected Values Evolving Metrics for Resource Adequacy Assessment

Resource adequacy analysis quantifies the likelihood of capacity shortfall on a power system in a probabilistic manner. Using a combination of statistical techniques and power system fundamentals, the analysis typically evaluates hundreds or thousands of stochastic random samples (replications) of varying load, generator outages, variable renewable energy availability, and other aspects of power system uncertainty. In this range of uncertainty, there are - at times - periods where the power system's available resources are insufficient to meet system demand, referred to as a shortfall event. Today's power systems' rapidly evolving generation mix is changing the types of data needed by system planners and regulators, which can often render traditional resource adequacy metrics insufficient for ensuring resource adequacy for tomorrow's grid. In this paper we provide a critical assessment of traditional measures of shortfall risk in power systems, discussing their shortcomings and how they compare to metrics used in other domains. From this analysis we propose four steps forward for improving power system resource adequacy risk metrics in the future.

ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

The value of hydropower flexibility for electricity system decarbonization

Hydropower is an abundant, dispatchable, clean energy resource that will play an important role in supporting the clean energy transition. In particular, dispatchable hydropower can provide the operational flexibility that will be required in future systems with high variable renewable energy penetrations. However, the theoretical operational flexibility of hydropower can be restricted in practice by various non-power constraints. In this paper, we quantify how increasing the operational flexibility of dispatchable hydropower resources with reservoirs impacts least-cost generation portfolios and supports power system decarbonization. Specifically, we conduct a capacity expansion analysis of a two-zone system: a hydro-dominated region and a neighboring region with aggressive decarbonization targets that are represented by the United States Pacific Northwest and California respectively. We then introduce a quantifiable index for characterizing the operational flexibility of reservoir hydropower and assess how changes in this metric impact the system-optimal generation portfolio. We find that increasing hydropower flexibility leads to more investment in wind generation, less investment in natural gas generation, lower system costs, and lower system emissions. We further demonstrate a substitution effect between the grid services provided by flexible hydropower operation, increased transmission capacity on a congested line, and energy storage resources. Finally, we show that increasing the operational flexibility of hydropower increases the effective load carrying capability of both hydropower and wind resources. This research supports a more nuanced understanding of how hydropower can support electricity system decarbonization and may motivate reassessing the cost-benefit tradeoffs of non-power constraints that restrict operational flexibility.

Capacity expansion modeling↗
DOE OSTI2025

Low-Cost, Screen-Printed Silver Metal Complex Inks for Silicon Heterojunction Solar Cells

Screen printing using metal particle pastes, the current photovoltaic industry metallization standard, provides fast and reliable metal grids for silicon solar cells. Recently, metal complex or reactive metal inks are attracting research interest due to their significantly low cost and higher performance compared to traditional nanoparticle silver pastes. In this work, we demonstrate, for the first time, screen-printed high-efficiency silicon heterojunction solar cells metallized by silver metal complex inks on industrial G1-size (158.75 x 158.75 mm2) wafers. We demonstrate screen-printed Ag metal complex ink grid patterns with continuous fingers ~100-120 ..mu..m wide. The printed Ag grid is very thin (~1 ..mu..m), which is an order of magnitude thinner than the current ~20-30 ..mu..m fingers printed with low-temperature nanoparticle-based pastes. Double printing allows silicon heterojunction devices with efficiencies >20%. This is the highest efficiency so far, to our knowledge, of industrial solar cell precursors using this metallization technology. Simulation results suggested that increasing the thickness of the metal film does not significantly improve efficiency due to the dense, highly conductive films. So, a single print of ~1 ..mu..m finger would be enough to produce cells that perform similarly to a ~20 ..mu..m thick nanoparticle paste printed cells. Additionally, solar cells printed on G1 wafers with silver metal complex ink required more than 10 times less silver (~0.03 g) compared to those using silver/copper nanoparticle paste (~0.4 g of Ag). These results indicate that metal complex inks are a very promising replacement for silver nanoparticle pastes for industrial-scale metallization in an age of resource scarcity and high costs of noble metals.

14 SOLAR ENERGY↗
DOE OSTI2025

Assessing the Impact of Lubrication on Efficiency and Life Cycle Economics of the US Wind Turbine Fleet: Cooperative Research and Development (Final Report)

As with any mechanical system, lubrication plays a key role in the performance of wind turbines used to generate electricity. The lubricant design offers a way to optimize the competing requirements of efficiency, component reliability, and maintenance strategy. This project will estimate the impact of improved lubrication on the levelized cost of energy of the US wind turbine fleet as a means of identifying opportunities for disruptive innovation or system-level optimization. The models developed will provide a clear understanding of the benefits and potential for advanced lubrication of wind turbines. The project will enable identification of high value targets for wind turbine component suppliers and a roadmap that highlights where the greatest return on technology investment can be achieved. This will promote efficient resource allocation in areas of new technology development.

17 WIND ENERGY↗
NASA NTRSDate not supplied

A Prototype Early Planetary Organic Processor Assembly (OPA) Based on Dual-Stage Anaerobic Membrane Bioreactor (AnMBR) for Fecal and Food Waste Treatment and Resource Recovery

Long-duration, deep-space exploration and habitation missions demand robust and reliable technologies to ensure crew health, safety, and mission success. Local food production will be essential for crew nutrition and morale. However, at $10,000/lb, the payload costs and mass/volume limitations to transport and provide the necessary resources, including fertilizer, for an anticipated 30-month mission become challenging over time. For mission success and sustainability, the Environmental Control and Life Support System (ECLSS) of the near future will need to recover resources from all “waste” sources and be near-closed loop. Organic wastes (e.g., fecal and food) offer a renewable source of C, N, P, water and other trace elements necessary to sustain crop production. However, these high solidwastes are often difficult to treatdue to factors includingheterogeneity, complexity, high organic strength, and the presence of pathogens. To date, there is no flight-ready technology capable of treating mixed organic wastes, creating a technology gap for future space missions. To address this need, a prototype Organic Processor Assembly (OPA) was developed through collaboration between the University of South Florida (USF) and NASA’s Kennedy Space Center (KSC). The OPA is based on the anaerobic membrane bioreactor (AnMBR), a hybrid technology coupling high-rate anaerobic digestion with membrane filtration. The system is designed for an early planetary base (EPB) scenario to aid in closing the resource recovery loop and decreaseresupply dependence. This presentation discusses initial research pertaining to: 1) design challenges in maximizing hydraulic/organic throughputandReliability, Availability, Maintainability, and Safety(RAMS)while minimizingmass and volume; 2) create capabilities for treating simulated high solids waste under steady and non-steady state conditions; and 3) measuresolids performance parameter(s). Future research and development pertaining to further optimization on system operation, performance, and expanded treatment capabilities arepresented.

Bioreactor↗
DOE OSTI2020

Water and Wastewater Systems as Potential Distributed Energy Resources for California - High-level Feasibility Assessment

Water systems in California are a major electricity user, and electricity costs represent a significant portion of water utilities’ operating costs. Water and wastewater utilities have the capacity to shift demand in response to grid needs or price signals and can generate power through biogas, hydropower or onsite renewable energy systems like solar panels and wind turbines. This report points to some of the most promising opportunity areas for water and wastewater utilities to implement distributed energy resources while also carefully laying out practical considerations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Transforming E-Waste Into Strategic Resources: Techno-Economic Analysis of Gallium and By-products Recovery from LEDs via Bioleaching

The growing demand for gallium in optoelectronics and renewable energy applications raises concerns about supply security and production sustainability. This study evaluates the techno-economic feasibility of recovering gallium and by-products (copper and nickel) from waste GaN-based LEDs via bioleaching. A process flowsheet encompassing transportation, robotic disassembly, ball milling, bioleaching, solvent extraction/electrowinning, and refining was modeled. Based on mass balance analysis, more than 53 tons of LED waste are required annually to yield 1 kg of gallium alongside substantial copper and nickel co-products. Preliminary techno-economic analysis (TEA) shows an average total cost (ATC) of 6.84 USD/kg metal when costs are allocated by mass-weighted economic value (market price) fraction, corresponding to 6.75 USD/kg for copper, 15.91 USD/kg for nickel, and 470.95 USD/kg for gallium. For gallium, direct operational costs account for more than 70% of the cost. Monte Carlo simulations further quantify cost uncertainties under market price fluctuations. This work represents the first TEA of gallium recovery from GaN-based LEDs and highlights potential pathways for future cost reduction.

36 MATERIALS SCIENCE↗
DOE OSTI2024

ТЕХНІКО-ЕКОНОМІЧНИЙ АНАЛІЗ ПОТЕНЦІАЛУ ІНТЕГРАЦІЇ РОЗПОДІЛЕНИХ ЕНЕРГЕТИЧНИХ РЕСУРСІВ ДЛЯ ВОДОКАНАЛУ М.ЧЕРВОНОГРАД В УКРАЇНІ [Technical and Economic Screening for Potential of Distributed Energy Resource Integration at Chervonohrad Water Utility in Ukraine] (Ukrainian Translation)

In this report, the authors present a preliminary techno-economic screening for distributed renewable energy for Chervonohrad Vodokanal, the water utility in Chervonohrad, Ukraine. The screening estimates the technical potential and economics of integrating solar photovoltaics (PV) and battery energy storage systems (BESS) at Chervonohrad Vodokanal water pumping stations, Pravda, Bendiuha, and Mezhyrichchya. For the English version of this report, see NREL/TP-7A40-89599 (https://www.nrel.gov/docs/fy24osti/89599.pdf).

14 SOLAR ENERGY↗
DOE OSTI2020

Chapter 7: Predictive Analytics in Future Power Systems: A Panorama and State-of-the-Art of Deep Learning Applications

The challenges surrounding the optimal operation of power systems are growing in various dimensions, due in part to increasingly distributed energy resources and a progression towards large-scale transportation electrification. Currently, the increasing uncertainties associated with both renewable energy generation and demand are largely being managed by increasing operational reserves - potentially at the cost of suboptimal economic conditions - in order to maintain the reliability of the system. This chapter looks at the big picture role of forecasting in power systems from generation to consumption and provides a comprehensive review of traditional approaches for forecasting generation and load in various contexts. This chapter then takes a deep dive into the state-of-the-art machine learning and deep learning approaches for power systems forecasting. Furthermore, a case study of multi-time-horizon solar irradiance forecasting using deep learning is discussed in detail. Smart grids form the backbone of the future interdependent networks. For addressing the challenges associated with the operations of smart grid, development and wide adoption of machine learning and deep learning algorithms capable of producing better forecasting accuracies is urgently needed. Along with exploring the implementation and benefits of these approaches, this chapter also considers the strengths and limitations of deep learning algorithms for power systems forecasting applications. This chapter, thus, provides a panoramic view of state-of-the-art of predictive analytics in power systems in the context of future smart grid operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Collaborative Decision Approach for Electricity Pricing-demand Response Stackelberg Game

Demand response programs are considered as a valuable resource in smart grids that provide several advantages of load shifting, peak load reduction, mediating intermittency of renewable energy integration, etc. Flexible price-based incentives have been recognized as a critical strategy in motivating and compensating consumers' load adjustment actions for successful implementation of demand response. Game theoretical approaches, especially Stackelberg games are popularly adopted to model the relationship between electricity price and customers' demand response and solved by the classical centralized backward induction (BI) method. However, the BI method generally requires convexity of the follower's model for necessary optimality conditions, and the computational time of any centralized approach increases sharply with larger problem instances. In this paper, the Stackelberg game of electricity pricing-demand response between a distribution system operator (DSO) and load aggregators (LAs) is decomposed based on a collaborative optimization (CO) framework, where each LA is treated as a discipline with its own domain constraints (e.g. building temperature control), while the DSO at the system level tries to reduce the solution discrepancy and guide the searching towards optimality. Several groups of comparison experiments have demonstrated the effectiveness of the proposed collaborative decision approach in solving the demand response game.

Chen, Yang↗
DOE OSTI2020

BI-LEVEL OPTIMIZATION FOR ELECTRICITY TRANSACTION IN SMART COMMUNITY WITH MODULAR PUMP HYDRO STORAGE

Grid integration of the increasing distributed energy resources could be challenging in terms of new infrastructure investment, power grid stability, etc. To resolve more renewables locally and reduce the need for extensive electricity transmission, a community energy transaction market is assumed with market operator as the leader whose responsibility is to generate local energy prices and clear the energy transaction payment among the prosumers (followers). The leader and multi-followers have competitive objectives of revenue maximization and operational cost minimization. This non-cooperative leader-follower (Stackelberg) game is formulated using a bi-level optimization framework, where a novel modular pump hydro storage technology (GLIDES system) is set as an upper level market operator, and the lower level prosumers are nearby commercial buildings. The best responses of the lower level model could be derived by necessary optimality conditions, and thus the bi-level model could be transformed into single level optimization model via replacing the lower level model by its Karush-Kuhn-Tucker (KKT) necessary conditions. Several experiments have been designed to compare the local energy transaction behavior and profit distribution with the different demand response levels and different local price structures. The experimental results indicate that the lower level prosumers could benefit the most when local buying and selling prices are equal, while maximum revenue potential for the upper level agent could be reached with non-equal trading prices.

Chen, Yang↗
DOE OSTI2020

dGen™ (Distributed Generation Market Demand Model) [SWR-17-09]

The Distributed Generation Market Demand (dGen™) model is a geospatially rich, bottom-up, market-penetration model that simulates the potential adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the continental United States through 2050. The National Renewable Energy Laboratory (NREL) developed dGen to analyze the key factors that will affect future market demand for distributed solar, wind, storage, and other DER technologies in the United States within a single modeling platform. The dGen model builds on, extends, and provides significant advances over NREL’s SolarDS model (Denholm et al. 2009), which is now deprecated. All Authors and Contributors are alphabetized in the Developers section with Authors of Code listed first, followed by Contributors and do not reflect equal contributions.

Sigrin, Benjamin↗
DOE OSTI2020

dGen™ (Distributed Generation Market Demand Model) [SWR-17-09]

The Distributed Generation Market Demand (dGen™) model is a geospatially rich, bottom-up, market-penetration model that simulates the potential adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the continental United States through 2050. The National Renewable Energy Laboratory (NREL) developed dGen to analyze the key factors that will affect future market demand for distributed solar, wind, storage, and other DER technologies in the United States within a single modeling platform. The dGen model builds on, extends, and provides significant advances over NREL’s SolarDS model (Denholm et al. 2009), which is now deprecated.

Preus, Robert↗
DOE OSTI2020

Iquitos Solar Energy Integration Study

The National Renewable Energy Laboratory performed an evaluation of the technical and economic feasibility of incorporating solar photovoltaic (PV) resources into the Iquitos, Peru power system at the request of Peru's Ministerio de Energia y Minas (MINEM). The Iquitos power system is electrically islanded due to its remote location; heavy fuel oil is used to generate electricity in the system leading to high electricity generation costs from high fuel prices. Solar PV has the potential to provide locally derived energy to ensure a reliable, affordable, and equitable power grid for the Iquitos region.

14 SOLAR ENERGY↗
DOE OSTI2020

Integrated Energy Systems: 2020 Roadmap

This roadmap defines potential industrial scale integrated energy systems (IES) and identifies key technology gaps to achieving commercial deployment of such systems. IES under consideration could include multiple energy generation resources and energy use paths, with a focus on low-emission technologies, such as nuclear and renewable generators. Together these technologies provide affordable, reliable, and resilient energy while simultaneously reducing environmental emission of CO 2 and greenhouse gases (GHGs). System design and optimization would consider both technical performance and economic viability within various deployment markets.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Repurposing Fossil-Fueled Assets For Energy Storage

The annual retirement of U.S. coal-fired electricity generation units (CF-EGU) is at an all-time high and is expected to continue. This loss of reliable baseload generation, combined with predicted growth of variable renewable energy (VRE) generation, is expected to stress grid reliability as the number of load-following resources drops below the experienced load variability. Many regions are already experiencing challenges, and fossil retirement-related warnings by the North American Electric Reliability Corp. are becoming more dire. All CF-EGU retirements pose significant challenges to asset owners, local workforces, and their communities. Repurposing a retiring CF-EGU as a long-duration energy storage plant can address these challenges and offer a suite of additional benefits to asset owners, the grid, and society. This project performed a techno-economic evaluation and assessment of repurposing a Duke Energy fossil-fueled asset (in particular, a coal plant) into an energy storage system by integrating the retiring asset with a Malta long duration Pumped Heat Energy Storage (PHES) system. The project validated the technoeconomic benefits of repurposing retiring coal plants into long-duration energy storage using Malta’s PHES. Key findings for this project are summarized below: (1) Technical: (a) Retiring coal plants (and other steam turbine fossil generation) can be repurposed to enable the clean energy transition using Malta’s technology. (b) For older retiring coal plants, repurposing the site and electrical interconnection for a standalone PHES plant is the most economically favorable option. (c) For newer coal plants where there is also a local peaking capacity need, repowering the steam cycle into a hybrid integration with PHES is attractive. (d) A process was developed to assist fossil generation owners in choosing the best path for each plant’s circumstances. (2) Economic (a) Communities facing economic challenges caused by the retirement of fossil generation would benefit from repurposing the plant as long-duration energy storage using Malta’s PHES. (b) On a $/MW basis, repowering retiring coal units into Malta PHES plants can maintain the same number and types of jobs and economic activity. (c) For a 70% carbon reduction scenario, a 10-hour Malta PHES plant is more economic for the asset owner than similar-power 4-hour batteries. This project showed that repurposing a retiring coal unit into thermal energy storage, by integrating it with a Malta PHES system, makes techno-economic sense. At least two integration options are available, with the optimal solution depending on the coal plant and its location. Repurposing retiring coal plant into energy storage results in economic benefits for the plant owner and local communities.

20 FOSSIL-FUELED POWER PLANTS↗