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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Parallel Harmony Search Based Distributed Energy Resource Optimization

This paper presents a harmony search based parallel optimization algorithm to minimize voltage deviations in three phase unbalanced electrical distribution systems and to maximize active power outputs of distributed energy resources (DR). The main contribution is to reduce the adverse impacts on voltage profile during a day as photovoltaics (PVs) output or electrical vehicles (EVs) charging changes throughout a day. The IEEE 123- bus distribution test system is modified by adding DRs and EVs under different load profiles. The simulation results show that by using parallel computing techniques, heuristic methods may be used as an alternative optimization tool in electrical power distribution systems operation.

Ceylan, Oguzhan↗
DOE OSTI2017

Summary of NREL's FY13-FY15 Photovoltaic Subprogram

In this report, you will find summaries of the completed FY13-FY15 Photovoltaic projects that were funded within NREL. The summaries describe the initial motivation for the project; significant achievements, including publications, intellectual property, and collaborations; and remaining challenges. Among the NREL projects, you will find research of almost every major PV technology - from the next generation of silicon PV to relatively new organic PVs - as well as projects advancing PV module durability and characterization. Each of these projects was designed to support SunShot's goals, putting the United States one step closer to widespread use of low-cost, clean electricity.

14 SOLAR ENERGY↗
DOE OSTI2017

Photovoltaic Hosting Capacity of Feeders with Reactive Power Control and Tap Changers

This paper proposes an algorithm to determine photovoltaic (PV) hosting capacity of power distribution networks as a function of number of PV injection nodes, reactive power support from the PVs, and the sub-station load tap changers (LTCs). In the proposed method, several minute by minute simulations are run based on randomly chosen PV injection nodes, daily PV output profiles, and daily load profiles from a pool of high-resolution realistic data set. The simulation setup is built using OpenDSS and MATLAB. The performance of the proposed method is investigated in the IEEE 123-node distribution feeder for multiple scenarios. The case studies are performed particularly for one, two, five and ten PV injection nodes, and looking at the maximum voltage deviations. Case studies show that the PV hosting capacity of the 123-node feeder greatly differs with the number of PV injection nodes. We have also observed that the PV hosting capacity increases with reactive power support and higher tap position of sub-station LTC.

14 SOLAR ENERGY↗
DOE OSTI2017

Chapter 5: Integration of Renewable Energy Technologies in Buildings and Cities

Sustainable Energy Technologies, such as the solar, wind, and waterpower systems described in other chapters of this book, need to be integrated into our energy systems to expand access to energy while avoiding harmful effects on the environment. The existing utility system or 'grid' is a network that consists of components for generation, transmission, distribution, and control of electric power from producers (also called 'resources') to consumers (also called 'loads' or 'demand'). Public safety necessitates that the grid be reliable, and public policy requires that grid power be affordable and broadly accessible. Much of the existing power grid was constructed before the advent of modern information technology for controls and automation. The existing grid is facing new challenges related to increases in power demand, complexity in managing more diverse and distributed resources, power quality issues introduced by 'non-linear' loads (that have parasitic inductance and capacitance like LED lights or computers), physical and cybersecurity threats, and challenges to the existing economic model of costs and revenues. Increases in power demand include not only growth in population and per-capita electricity use, but also call for electricity to meet the need for heating and transportation as well. Electric vehicles are a rapidly growing example of this electrification of previously fossil-fueled uses. [Your author's Chevrolet Volt vehicle uses about the same amount of electricity as his house, around 300 kWh/month. Fortunately, both are served with solar photovoltaics (PVs)]. Therefore, there is an immediate need for improvement toward a reliable, self-regulating, efficient, and economical grid system that will allow the integration of renewable distributed power generation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Seminar 13 - Advanced Methods for Grid Integration of High-Performance Residential Communities

High-performance residential communities such as net-zero energy (NZE) and NZE-ready communities are emerging across the United States as many cities and states have committed to achieve ambitious energy efficiency and renewable energy goals between now and 2050. The achievement of these goals will transform the nation's communities into the holistic paradigms consisting of pervasive solar photovoltaics (PVs) and other renewable distributed energy resources, energy storage and flexible loads. However, integrating residential communities with high PV penetration may bring many challenges to the grid. For example, during many hours of the year, electric power is flowing out of PV-enabled homes and back into the grid. When this happens simultaneously in many nearby homes, distribution feeder voltage can be raised significantly. Intermittent solar power can also cause voltage flickers, leading to potential damages on both distribution feeder and home appliances. Existing solutions, such as PV curtailment, battery storage, and direct load control, are not able to address all the challenges in a cost-effective way. Better understanding is needed on how to deploy rooftop PV, how to predict building loads, and how to coordinate the homes in a community to enhance grid reliability. This seminar consists of four integral presentations that cover different aspects of a solution to these challenges. First, we will present an automated method to identify the best surfaces to deploy PV and size PV according to the PV penetration goals in a community. Second, we will present a streamlined way to create gray-box building models that are suitable for large-scale building-grid co-simulation. Next, we will present a data-driven method to estimate the end-use energy consumption to better coordinate the behind-the-meter resources to reduce utility cost, provide grid services, and improve renewable energy integration. Lastly, we will present a hierarchical control system that integrates the building models and the estimated non-dispatchable loads into the decision-making process to enhance the reliability and resilience of the residential community. Simulation results from an NZE-ready community in Fort Collins, Colorado will be presented in all four presentations and the guidelines on better grid integration of residential communities will be provided.

14 SOLAR ENERGY↗
DOE OSTI2020

Optimal PV Inverter Control in Distribution Systems via Data-Driven Distributionally Robust Optimization

Distribution systems with high penetration of uncertain solar generation call for advanced control strategies of photovoltaics (PVs) inverters. This paper proposes a data-driven distributionally robust optimization (DDDRO) approach to optimally controlling the PV inverters to improve the system operation performance under solar power uncertainties. In the proposed DDDRO approach, a Wasserstein ball-based method is proposed to construct the distributional ambiguity set to model the uncertainties of PV generation through partial observations of historical data without knowing exact probability distributions. We further reformulate the computationally intractable DDDRO model to a mixed integer second order cone programming (MISOCP) problem. The effectiveness and out-of-sample performance of the proposed approach have been demonstrated on a modified IEEE 33-node system. We conduct a comparative study to compare the proposed method with traditional chance constrained programming (CCP). It shows that the proposed DDDRO approach can provide a less conservative yet robust solution to minimize the worse-case expectation of the total network loss while maintaining nodal voltages in a secure range.

Xue, Yaosuo↗
DOE OSTI2021

Coordinated Optimal Control of PV Inverters and HVAC Loads in Distribution Systems

The increasing integration of distributed energy resources (DERs), such as photovoltaics (PVs) and smart buildings into distribution systems complicate power system operation and controls. This paper proposes a coordinated optimal control strategy for PV inverters and Heating, ventilation, and air conditioning (HVAC) loads in smart buildings to minimize the total network loss in a distribution system. For the HVAC units, we enforce minimum on and off time constraints to avoid frequent switching that can degrade the unit. The proposed control will dispatch optimal control signals of active and reactive power to PV inverters and on/off commands to HVAC units while maintaining the nodal voltage within a secure range and the temperature of HVAC units at a comfort level. The simulation results on a modified IEEE 33-node distribution system demonstrate that the proposed coordinated control scheme can reduce the network loss.

Pani, Naveen↗
DOE OSTI2022

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources: Preprint

Integration of a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problem requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs) including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperformed other benchmark controllers regarding computation time without compromising operational performance.

DER↗
DOE OSTI2022

DERMS Online: A New Voltage Sensitivity-Enabled Feedback Optimization Framework: Preprint

This paper proposes a distributed energy resource management system (DERMS) solution by developing a new voltage sensitivity enabled feedback optimization framework. The key idea is to adopt a measurement feedback scheme to reformulate the original nonlinear optimization into a linear programming (LP) problem via perturb and observe-based voltage sensitivity analysis. The proposed solution eliminates the dependence on load knowledge and can be implemented online thanks to an efficient open-source solver for LP problems. The proposed DERMS online platform is generalizable to deal with various types of distributed energy resources (DERs), including distributed photovoltaics (PVs), energy storage, electric vehicles, demand response, etc. Comparison results with other control methods on a realistic distribution feeder in Southern California highlight the feasibility as well as benefits for the proposed framework.

distributed energy resources management↗
DOE OSTI2022

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources

Integrating a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problems requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs), including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperforms other benchmark controllers regarding computation time without compromising operational performance.

DER↗
DOE OSTI2023

Island Power Systems With High Levels of Inverter-Based Resources: Stability and Reliability Challenges

As many island power systems seek to integrate high levels of renewable energy, they face new challenges on top of the existing difficulties of operating an isolated grid. With their drastically declining cost, variable renewables, such as wind and photovoltaics (PVs), are increasingly being integrated into island grids to reduce the use of imported fuels. These deployments of renewable energy are dominated by PV and wind generators, which bring unique challenges of their own.

IBRs↗
DOE OSTI2015

Nominal Device Support for ATCA Shelf Manager

The ATCA standard specifies a mandatory Shelf Manager (ShM) unit which is a key element for the system operation. It includes the Intelligent Platform Management Controller (IPMC) which monitors the system health, retrieves inventory information and controls the Field Replaceable Units (FRUs). These elements enable the intelligent health monitoring, providing high-availability and safety operation, ensuring the correct system operation. For critical systems like ones of tokamak ITER these features are mandatory to support the long pulse operation. The Nominal Device Support (NDS) was designed and developed for the ITER CODAC Core System (CCS), which will be the responsible for plant Instrumentation and Control (I and C), supervising and monitoring on ITER. It generalizes the Enhanced Physics and Industrial Control System (EPICS) device support interface for Data Acquisition (DAQ) and timing devices. However the support for health management features and ATCA ShM are not yet provided. This paper presents the implementation and test of a NDS for the ATCA ShM, using the ITER Fast Plant System Controller (FPSC) prototype environment. This prototype is fully compatible with the ITER CCS and uses the EPICS Channel Access (CA) protocol as the interface with the Plant Operation Network (PON). The implemented solution running in an EPICS Input / Output Controller (IOC) provides Process Variables (PV) to the PON network with the system information. These PVs can be used for control and monitoring by all CA clients, such as EPICS user interface clients and alarm systems. The results are presented, demonstrating the fully integration and the usability of this solution. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Migration and Distribution of Natural Organic Matter Injected into Subsurface Systems - 16523

The Savannah River Site (SRS) was one of the major U.S. Department of Energy facilities that produced large amounts of radioactive and hazardous waste during the Cold War era, a legacy of material production for defense purposes. The unlined F-Area seepage basins received approximately 1.8 billion gallons of acidic waste solutions containing low-level radioactivity from numerous isotopes generated by uranium slug and irradiated fuel processing. Sufficient quantities of uranium isotopes, I-129, Tc-99, and tritium migrated into the groundwater, creating an acidic plume with a pH between 3 and 5.5. Humic substances (HS) are complex heterogeneous mixtures of poly-dispersed materials formed by biochemical and chemical reactions during the decay and transformation of plant and microbial remains. They are known for their excellent binding capacity for metals, making them a strong candidate for remediation efforts to reduce the mobility of uranium (VI) in the subsurface. Studies showed that HS are an important ion exchange and metal-complexing ligand, carrying a large number of functional groups with high complexing capacity that can greatly affect the mobility behavior of actinides in natural systems. Hence, it is a potential in situ amendment for treating groundwater contaminated with these constituents. Column experiments were conducted to address the complexities of HS in flow-through porous media representative of the acidic aquifer at the SRS F-Area Seepage Basins. The humate source used, Huma-K, is high in humic and fulvic compounds. The column studies were done using the soil obtained from SRS's FAW-1 core-hole at a depth interval of 60'-70'. A bromide tracer test was performed to obtain the pore volume (PV), variance and Peclet number. The columns were saturated with an artificial groundwater solution prepared to mimic the groundwater at SRS that was pH adjusted to 3.5 and 5 until the effluent pH reached equilibrium. Approximately one (1) PV of 5000 ppm of Huma-K was injected into the columns at 2 ml/min to study the sorption of Huma-K on the sediment. Desorption of Huma-K was studied by injecting approximately four (4) PVs of the pH adjusted artificial groundwater solution. A faster increase in pH was observed in column 1 (saturated with pH 3.5 AGW) compared to column 2 (saturated with pH 5 AGW). After injection of 2 PV of AGW, the pH of the columns reached 6.5 and 7, respectively, for columns 1 and 2. After injecting an additional PV of AGW, the pH remained relatively stable. With an increase in pH from 3.5 to 5.0, the overall retention of HA increased from 461 mg/kg for the column with pH 3.5 to 642 mg/kg for the column with pH 5. This suggests that retention is not due to adsorption alone, but adsorption coupled with precipitation and re-dissolution of Huma-K as it flows through the columns is a possible explanation for greater retention at pH 5. This negates the use of a simple Langmuir isotherm to explain humate behavior in the acidic environment of column 1. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Baseload Hydrogen Production Using Nuclear and Renewable Energy: A Comparative Analysis

As the global push towards net zero carbon gains momentum, the demand for clean hydrogen is expected to grow rapidly across various sectors, including transportation, industries and electrical grids. To meet this growing hydrogen demand, baseload hydrogen production facilities capable of providing a continuous and reliable supply of hydrogen will be necessary throughout the world. This paper explores the technoeconomic feasibility of establishing baseload electrolytic hydrogen production facilities in the United States, utilizing different clean generation resources. The key criteria include maintaining a consistent supply of clean hydrogen without putting baseload demand stress to already vulnerable power grid. In order to do that, the proposed facilities will host onsite clean power generation and energy storage technologies. The proposed facilities can capitalize on available investment and production incentives and have ability to export excess electricity to the utility at a bulk price. Several scenarios are considered based on the clean energy resources to support the electrolysis process including light water reactors (LWRs) currently evaluating retirement options, wind, solar PVs, and advanced small modular reactors (SMRs). For each scenario, a hypothetical hydrogen production facility is considered in a location in the US where the primary generation resource is at its peak strength. Comparative analysis in this paper reveal that the nuclear power plants are most economically viable for baseload hydrogen production facilities, outperforming renewable-based facilities with significantly lower levelized cost of hydrogen (LCOH). Even under best-case scenarios for resource availability, incentives and export prices, renewable-based facilities face challenges due to daily and seasonal generation variability, resulting in large installation sizes and lower capacity factors. Among renewable-based facilities, complementarity hybrids, providing more stable power supply, demonstrate superior economics compared to facilities based on a single renewable technology. While LWR-powered facility can achieve a negative LCOH with incentives, SMR-powered facilities can provide economic hydrogen supply with LCOH below $1/kg with high temperature electrolysis option. The analysis in this paper underscores the pivotal role of nuclear energy in the future hydrogen economy.

08 - HYDROGEN↗
DOE OSTI2016

A Nonrelational Data Warehouse for the Analysis of Field and Laboratory Data From Multiple Heterogeneous Photovoltaic Test Sites

A nonrelational, distributed computing, data warehouse, and analytics environment (Energy-CRADLE) was developed for the analysis of field and laboratory data from multiple heterogeneous photovoltaic (PV) test sites. This data informatics and analytics infrastructure was designed to process diverse formats of PV performance data and climatic telemetry time-series data collected from a PV outdoor test network, i.e., the Solar Durability and Lifetime Extension global SunFarm network, as well as point-in-time laboratory spectral and image measurements of PV material samples. Using Hadoop/HBase for the distributed data warehouse, Energy-CRADLE does not have a predefined data table schema, which enables ingestion of data in diverse and changing formats. For easy data ingestion and data retrieval, Energy-CRADLE utilizes Hadoop streaming to enable Python MapReduce and provides a graphical user interface, i.e., py-CRADLE. By developing the Hadoop distributed computing platform and the HBase NoSQL database schema for solar energy, Energy-CRADLE exemplifies an integrated, scalable, secure, and user-friendly data informatics and analytics system for PV researchers. Furthermore, an example of Energy-CRADLE enabled scalable, data-driven, analytics is presented, where machine learning is used for anomaly detection across 2.2 million real-world current-voltage (I–V) curves of PV modules in three distinct Koppen–Geiger climatic zones.

14 SOLAR ENERGY↗
DOE OSTI2017

Distribution and Charge State of Iron Impurities in Intentionally Contaminated Lead Halide Perovskites

Impurity contamination in thin-film solar cells remains an uncertain risk due to the little-known impact of impurities on recombination. Building upon previous work, in which we intentionally contaminated lead halide perovskite (LHP) solar cells with iron, we further examine the distribution and charge state of iron-induced defects in LHP films using synchrotron-based X-ray techniques. X-ray absorption measurements suggest that iron-rich regions, which form among iron feedstock concentrations that exceed 100 ppm, most closely resemble the chemistry of Fe 2 O 3 . Iron distributed within the bulk may form a mix of Fe 2+ and Fe 3+ , the latter of which is not expected to be recombination active, potentially allowing LHPs to incorporate more iron than traditional semiconductors. X-ray beam induced current measurements show little correlation between the presence of iron-rich regions and charge collection, which further suggests low recombination activity at these sites. In conclusion, these results further elucidate the recombination behavior caused by iron incorporation in LHP films, revealing insight into how inhomogeneous incorporation of impurities may mitigate photovoltaic performance degradation.

14 SOLAR ENERGY↗