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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Black-Box Optimization for Design of Concentrating Solar Power and Photovoltaic Hybrid Systems with Optimal Dispatch Decisions

The hybridization of concentrating solar power (CSP) and photovoltaics (PV) can enable dispatchable renewable electricity generation at a lower price than current stand-alone CSP systems. However, designing a CSP-PV hybrid system can be challenging because of the many degrees of freedom in design that affect the internal and external system interactions and trade-offs. We develop a methodology to determine optimal designs for CSP-PV hybrids by implementing NLopt's derivative-free, or “black-box,” algorithms around pre-existing CSP-PV hybrid simulation software that utilizes the National Renewable Energy Laboratory’s System Advisor Model (SAM); we then employ a dispatch optimization model to determine operational decisions that maximize a plant’s profits. We present optimal designs for CSP-PV hybrid systems dispatching against four time-of-delivery (ToD) pricing structures. NLopt’s algorithms can improve the base case design’s power purchase agreement (PPA) price by 15% to 21%, depending on the ToD pricing structure. In addition, we present the resulting optimal CSP-PV hybrid design’s annual performance metrics, which tend to have capacity factors between 50% and 62%, but are able to generate electricity during the year’s highest-valued periods about 90% of the time. Lastly, we investigate the trade-offs between capacity factor and PPA price using Pareto fronts and demonstrate that, for some ToD pricing structures, the system capacity factor can increase by 20% but at the expense of a 2% increase in PPA price.

black-box↗
DOE OSTI2024

Demystifying Cyberattacks: Potential for Securing Energy Systems With Explainable AI : Preprint

Modernization of energy systems has led to in- creased interactions among multiple critical infrastructures and diverse stakeholders making the challenge of operational decision making more complex and at times beyond cognitive capabilities of human operators. The state-of-the-art machine learning and deep learning approaches show promise of supporting users with complex decision-making challenges, such as those occurring in our rapidly transforming cyber-physical energy systems. However, successful adoption of data-driven decision support technology for critical infrastructure will be dependent on the ability of these technologies to be trustworthy and contextually interpretable. In this paper, we investigate the feasibility of implementing XAI for interpretable detection of cyberattacks in the energy system. Leveraging a proof-of-concept simulation use case of detection of a data falsification attack on a photovoltaic system using XGBoost algorithm, we demonstrate how Local Interpretable Model-Agnostic Explanations (LIME), a flavor XAI approach, can help provide contextual and actionable interpretation of cyberattack detection.

artificial intelligence↗
DOE OSTI2023

Model Predictive Control-Based Dual-Mode Operation of an Energy-Stored Quasi-Z-Source Photovoltaic Power System

The energy-stored quasi-Z-source inverter (ES-qZSI) has attracted much attention for photovoltaic (PV) power generations, due to its capability to stabilize the PV power fluctuations with simple structure and other advantages of Z-source inverter. The improved dual-mode (DM) ES-qZSI is able to support all-weather operation even at night or cloudy days when PV power is extremely low. However, the traditional proportional–integral (PI) based control suffers from complicated controller design and poor dynamic response during mode transition, due to two sets of PI control required for the daytime and night operation modes. In order to overcome that, here in this article, we propose a model predictive control strategy for the DM-ES-qZSI PV power system. The system predictive models in both day and night operating modes are derived. The control strategy is disclosed to ensure high performance of the system, through calling the predictive models and defined cost functions of the two modes within a single control loop. Simulation and experiment are carried out to verify the effectiveness of the proposed control strategy.

14 SOLAR ENERGY↗
DOE OSTI2022

Organic Macromolecular materials for Efficient Transport Properties in Light-Energy Conversion Applications. Final Report

We are grateful for the Department of Energy for support of this research related to the improvement of power conversion efficiency of organic photovoltaic architectures over the years. As we noted at the beginning and now, the fundamental photophysical pathways that connect the absorption of light to the production of charge carriers remain elusive in spite of continuing experimental and theoretical efforts. Our investigations were directed toward gaining information about the mechanism of this ultrafast, long-range charge separation in photovoltaic systems with non-fullerene acceptors. This problem is still of high importance for the organic photovoltaics because solving this problem will allow us to minimize the contribution of the geminate recombination and trapping the charges in bound charge transfer states. Extremely low charge separation driving energy specific to non-fullerene acceptor systems reduces the energy loss in organic photovoltaic cells making them competitive with inorganic and perovskite photovoltaic systems. A major accomplishment of this study was to detail the long-range ballistic charge separation in donor-non-fullerene acceptor photovoltaic systems. We have successfully probed the spatial structure of ultrafast long-range (~40nm) ballistic charge separation in donor-non-fullerene acceptor photovoltaic system. We performed a systematic investigation of the delocalized states in their connection to the efficient long-range charge separation using the pulse pair interferometric near-field microscopy method. This method possesses unique capability of detecting coherent effects with spatial resolution of few tens of nanometers. These measurements allowed us the determination of delocalized excitations locally in a thin film photovoltaic system and to be connected to the long-range charge separation and the power conversion efficiency. We also investigated long-lived coupled triplet pairs in a singlet fission process for the possibility of concerted extraction of two electrons from triplet entangled states. New experimental and theoretical approaches of the concerted double electron extraction were carried out. The impact of this work is the development of important structure-property relationships to the design criteria of more efficient organic photovoltaic cells in accordance with the BES mission.

14 SOLAR ENERGY↗
DOE OSTI2022

Impact of model predictive control-enabled home energy management on large-scale distribution systems with photovoltaics

Residential customers use more than one-quarter of the electricity in the world. Optimally managing home energy consumption is an effective way of easing the operational challenges facing the electric grid with increasing solar photovoltaics (PV). This paper studies the impact of the future proliferation of home energy management systems (HEMS) in the presence of PV on large-scale distribution systems. First, we present a stochastic HEMS model that minimizes residential customers' thermal discomfort and energy costs under uncertainty. The HEMS model schedules the optimal operations of residential appliances in the presence of PV within a mixed-integer linear programming-based model predictive control framework that links the proposed HEMS to a quasi-steady-state time-series simulation tool. Additionally, extensive simulations are conducted for a stand-alone residential home using two tariff structures and for 1977 homes on an 8,500-node distribution feeder. Simulation results quantify the impact of the future proliferation of HEMS on the large-scale distribution system with PV.

14 SOLAR ENERGY↗
DOE OSTI2026

Energy, power, and infrastructure demands from electrifying airport ground support equipment at United States airports

As the airline industry seeks to reduce costs and transition to clean energy, electric ground support equipment is emerging as a favorable option. The integration of electric ground support equipment into airport operations requires careful planning for vehicle deployment, charging infrastructure, and grid impacts. We develop a flexible, bottom-up modeling framework to assess energy and infrastructure needs across more than 300 U.S. airports. Our analysis estimates site-specific power and energy demand, equipment counts by type, charger requirements, and costs. Here we quantify the magnitude of new electrical loads created by the electrification of airport ground support equipment, finding that peak power demand at the largest airports can reach up to 20 megawatts, with annual electricity consumption approaching 51,000 megawatt-hours. We further show that behind-the-meter battery energy storage systems and solar photovoltaic systems can reduce peak load and lower total system costs by as much as 10 million dollars.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

A Review of Behind-the-Meter Solar Generation Modeling and Forecasting

Solar photovoltaic systems largely integrated within the distribution grid are operated 'behind-the-meter' and power generation cannot be directly monitored by most utilities. The increasing penetration of behind-the-meter solar photovoltaic systems can deter efficient network and market operations due to variability and uncertainty in net load, which is exacerbated by limited visibility and the difficulty in analyzing the hosting capacity. Risk introduced by behind-the-meter solar contributions may hinder reliable and secure grid operations due to biased system monitoring and forecasts. Accurate behind-the-meter estimations, together with capacity and specification forecasts, thus play a key role in balancing supply and demand and this article reviews the pertinent literature, identifying key characteristics and predictive methods for efficient behind-the-meter solar photovoltaic generation. Forecasting is central to methods herein. The fundamental characteristics of behind-the-meter solar forecasting, including which methods are applicable for scenario-driven use cases, are driven by the metrics most useful for system-wide performance evaluation. To this aim, the literature is reviewed with a focus on forecasting applications for aggregate, regional behind-the-meter generation useful to bulk system and utility operations. As distinguished from net load forecasting, subtleties in these coincident tasks are explored before concluding with recommendations for current practice and future implementations.

behind-the-meter↗
DOE OSTI2023

Solar Canopy Expansion Project (Final Technical Report)

This project is a parking-lot canopy solar photovoltaic system, consisting of four canopy structures and 1,080 470-watt (W) modules. The nameplate rating of the project is 507.6 kilowatts direct current (kWDC) at Standard Test Condition (STC), and 448 kilowatts alternating current (kWAC). It is interconnected to the existing Tribe-owned medium-voltage micro-grid generation system via a step-up transformer and short medium-voltage line. This project offsets energy usage from more expensive existing sources, specifically the Tribe-owned gas-fired engine generators providing the primary power source for existing Tribal facilities and the electric utility, which provides an alternate source. The solar photovoltaic system is a renewable source, which has the benefit of reducing reliance on fossil-fuel burning sources. By reducing demand on existing Tribe-owned conventional generators, the project has avoided the need to add more conventional generation and has prolonged the lifespan of existing gas-fired engine generators. The project reduced energy costs and reliance on fossil-fuel burning power sources, increasing Tribe-owned generating sources and self-reliance, and prolonging the lifespan of existing generators. A side benefit to the project is the production of dozens of covered parking spaces in the existing parking lot.

14 SOLAR ENERGY↗
DOE OSTI2022

Review of Potential–Induced Degradation in Bifacial Photovoltaic Modules

Bifacial modules are increasingly deployed in the field and are expected to represent half of the market share within 10 years. Their rear structure differs from monofacial modules to allow additional light absorption. However, it brings new reliability challenges to address. In particular, the risk of potential-induced degradation (PID) is increased as both module sides are impacted. Different PID processes have been identified in the literature: shunting type (PID-s), polarization type (PID-p), Na penetration type, and corrosion type (PID-c). Their occurrence depends on the photovoltaic system configuration as well as the module's materials. Apart from PID-s, PID processes are not well understood and extensive research is needed to elucidate the PID scenario and underlying mechanisms. Herein, current knowledge about PID processes and their impact on the main bifacial modules in the market are gathered with the aim to guide future research. Bifacial module technologies and leakage current paths leading to PID are described. Indoor and outdoor PID testing methods are detailed. For each bifacial module technology, the PID processes are investigated with their indicators, mechanism and recovery process. Furthermore, PID-impacting factors and limitation solutions are finally reported and a state of the art on PID modeling is presented.

14 SOLAR ENERGY↗
DOE OSTI2021

Assessing Machine Learning as a Tool to Explain Variance in Deployed Photovoltaic (PV) System Degradation

Degradation remains a large uncertainty in forecasting production for PV plants, creating significant risk for developers and financiers. This study aims to quantify the distribution and drivers of degradation across 10,000 PV systems deployed for distributed or utility generation by training a machine learning model to predict year-over-year degradation rates from metadata characteristics. A combination of K-Means clustering and random forest regressor were found to associate multiple metadata features as potential drivers of degradation, including module characteristics, system design, and climate features. From this, it is inferred that if machine learning is able to find complex patterns between metadata features and system performance loss, such methods can be employed to help developers and financiers make data-informed decisions when estimating long-term energy production forecasts in financial models.

Dunn, Jimmy C.↗
DOE OSTI2021

Deployment of Community Scale Solar Photovoltaic Energy Systems in Forest County Potawatomi Community

FCPC is a federally recognized tribe with a membership of more than 1400. The Tribe has a reservation in Forest County, Wisconsin, and tribal trust lands in Milwaukee County, Wisconsin, with significant governmental and business operations in both areas. Until relatively recently, FCPC was one of the poorest tribes in the Midwest. Due to its successful gaming operations, it now has improved its financial situation and is using its resources to benefit both its members and the general public through environmental and other community efforts, many of which are long-delayed because of the extended period of abject poverty. The Tribe has developed the long-term goal of becoming energy independent using renewable resources. In order to meet this goal, the Tribe has taken several important steps. As an interim step, FCPC is purchasing nearly 55 million kilowatt hours of renewable energy certificates (“RECs”) annually from certified renewable energy facilities in the United States. These RECs offset more than 100% of the present electricity use at all of the Tribe’s facilities. The Tribe is currently ranked number 11 on the Environmental Protection Agency’s (EPA) Top 20 Local Government list of green power purchasers and is a member of the EPA’s Green Power Partnership. The original project suggested small scale installations on tribal homes and certain government buildings. The Tribe suggested that the project would result in 730 kw installed. By revising the project, the Tribe was able to install 938 kw and owns the largest installation in Northern Wisconsin with the 800 kW installation at the Potawatomi Carter Casino Hotel (“PCCH”). The PCCH installation, in summer months, can provide near 90% of the use during daylight hours. Although tracking was not immediately available FCPC has since confirmed significant production with certain quarterly savings nearing $210,000. These installations provide a reduction in facility costs providing more revenue for Tribal services including cultural, health, sustainable food sources, environmental preservation and other Tribal initiatives. Further, the installations have resulted in positive steps towards the Tribe’s goals of energy sovereignty and the use of 100% renewable clean energy. Finally, the PCCH project, specifically, has had the additional benefit of providing a likely area for a microgrid. The size of the installation and offset achieved have pushed the Tribe toward planning for storage and a microgrid system that would both further the Tribe’s energy goals and provide a safe haven for the Community during times of need.

14 SOLAR ENERGY↗
DOE OSTI2020

Connector system for photovoltaic array

A photovoltaic assembly comprising; (a) at least two photovoltaic components that are adjacent to each other in a first direction, each photovoltaic component comprising (i) a partial recess in communication with the partial recess in an adjacent photovoltaic component and (ii) one or more connector receptors aligned in a second direction which is non-parallel to the first direction; (b) a connector located at feast partially in the partial recess of the photovoltaic component and at least partially in the partial recess of the adjacent photovoltaic component so that the connector connects the photovoltaic component to the adjacent photovoltaic component, the connector comprising: (i) a flexible housing having a first end and a second end; (ii) one or more connection ports at the first end; (iii) one or more connection ports at the second end; and (iv) one more flexible electrical conductors that extend from the one or more connection ports at the first end to the one or more connection ports at the second end; wherein the connector is flexible so that the first end and the second end are movable relative to each other in a plane, out of the plane, or both; wherein the one or more connection ports at the first end and the one or more connection ports at the second end form a connection with the one or more connector receptors of the photovoltaic component and the adjacent photovoltaic component so that the connector electrically connects the photovoltaic component to the adjacent photovoltaic component.

14 SOLAR ENERGY↗
DOE OSTI2023

Fairness-Aware Distributed Energy Coordination for Voltage Regulation in Power Distribution Systems

The accelerating deployment of solar photovoltaics into low-voltage distribution networks can cause reverse power flow and overvoltage problems. However, if coordinated properly, the real and reactive power flexibility of these resources enables distribution operators to manage their networks more efficiently. Existing literature is rich in droop-based control (Volt-Watt and Volt-VAr) and optimization-based distributed energy coordination for four-quadrant control of photovoltaics to prevent overvoltage issues. While optimal coordination can effectively mitigate overvoltage, it tends to treat resources at sensitive parts of the grid unfairly. Here, to address this concern, we propose a distributed optimal power flow formulation that incorporates fairness in curtailing photovoltaic generation and utilizes the reactive power capability of smart inverters. The proposed distributed formulation allows for scalable resource aggregation that can be leveraged to achieve fairness within a certain segment of the grid and/or fairness across the entire network. Fair curtailment of photovoltaic systems is demonstrated with aggregation at each of two layers in a distribution network: 1) area-level fairness and 2) feeder-level fairness. To explore the trade-off between fairness and optimal utilization, the fairness-aware control actions are compared against the performance of a centralized controller that aims to maximize the aggregate PV generation without incorporating fairness. Simulation results show that introducing area-level fairness increased curtailment by 0.0101 percentage points and feeder-level fairness increased curtailment by 0.0458 percentage points compared to a fairness-agnostic control.

Poudel, Shiva↗