Distributed Hydropower Microgrids for Creating Energy Resiliency in Agriculture
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13 HYDRO ENERGY↗
SEARCH · Engineering Papers
Results for “distributed solar PV”
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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PV Hosting Capacity Estimation: Experiences with Scalable Framework; Preprint
Hosting capacity is an indication of the amount of photovoltaics (PV) can be hosted in a distribution system. This paper presents a framework for estimating distributed PV hosting capacity at scale. We first analyze the key challenges of performing relevant large scale simulation including computational and modeling challenges. Then, we develop two python-based software tools in order to conduct repeatable distribution analyses: Distribution Integration Solution Cost Options (DISCO) for configuring and analyzing simulations, and JADE for parallelizing jobs on HPC clusters. A case study of hosting capacity estimation for SMART-DS SFO 2000+ synthetic feeders is used to demonstrate the capability of the developed framework and tools. The framework and tools can help utilities assess the overall hosting capacity of their service territory, through which the overall upgrade cost can be better planned in order to integrate more PV in the future.
distributed energy resources↗
Flux concentrations on solar dynamic components due to mispointing
Mispointing of the solar dynamic (SD) concentrator designed for use on Space Station Freedom (SSF) causes the optical axis of the concentrator to be nonparallel to the incoming rays from the Sun. This causes solar flux not to be focused into the aperture hole of the receiver and may position the flux on other SSF components. A Rocketdyne analysis has determined the thermal impact of off-axis radiation due to mispointing on elements of the SD module and photovoltaic (PV) arrays. The conclusion was that flux distributions on some of the radiator components, the two-axis gimbal rings, the truss, and the PV arrays could present problems. The OFFSET computer code was used at Lewis Research Center to further investigate these flux distributions incident on components. The Lewis study included distributions for a greater range of mispoint angles than the Rocketdyne study.
Rylicki, Daniel S.↗
Risk-Informed Condition Evaluation of Solar-centered Energy Generation and Distribution Networks through Bayesian Learning and Inference
We develop a methodology based on Bayesian inference over Probabilistic Graphical Models (PGMs) to understand and quantify risk in solar-centered grids using targeted measurements and learned system behavior. Being non-prescriptive but, rather, able to infer system behavior and, ultimately, address risk queries from data, our machine learning-type paradigm is tailored for diverse topologies and threat scenarios often associated with distributed energy generation and photovoltaic distributed energy resources (PV-DERs) in particular. We describe algorithmic processes for: (i) learning the structure of PGMs that result from attack-prone PV-DER-proliferated distribution systems, (ii) quantifying cause-effect relationships, and (iii) evaluating risk queries based on diverse evidence. The contributions are illustrated on a residential grid subject to output impairment attacks on its PV-DER infrastructure.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Predicting Wind Loading and Instability in Solar Tracking PV Arrays
Wind loading and the fluctuating pressure loads it creates on PV panel surfaces are associated with multiple degradation mechanisms and failures. Modest wind speeds create reversing loads that can initiate cell cracks and weather cracked cells. Stronger wind speeds and extreme weather events can lead to larger scale forces and the aerodynamic instability known as torsional galloping. All these effects are dependent on the complex coupling between wind speed, panel orientation, and a myriad of other hardware and site-specific factors. In this work, we present the latest developments from our work to build an open-source, high-performance computing (HPC) fluid dynamics solver to predict and mitigate these effects. This simulation package allows users to easily specify different array layouts, solar-tracking angles, panel geometries, and weather conditions before automatically generating a refined computational mesh and solving for the unsteady loading on each panel surface. Small domains (e.g., a single panel row in isolation) can be solved on a modern laptop, while larger domains or very high-fidelity studies can be solved on distributed or HPC resources with minimal modifications to the underlying problem specification. We present preliminary case studies obtained using this simulation package and highlight how increased wind speeds combined with sub-optimal tracking angles can exacerbate degradation drivers.
aerodynamics↗
Design and Techno-Economic Analysis of a 150-MW Hybrid CSP-PV Plant
The interest in concentrated solar power (CSP) has increased significantly over the years since it is dispatchable and requires thermal storage instead of electric storage. When compared to photovoltaics (PV), CSP has a higher Levelized Cost of Electricity (LCOE). In this paper, we present the design of a hybrid power plant using CSP and PV technologies. The hybrid system offers a lower LCOE than CSP but will still have dispatchability. The 150-MW hybrid system consists of 100-MW CSP and 50-MW PV capacity. Furthermore, the CSP system (central receiver system) has a molten salt-based thermal storage of 12 hours. The geographical focus of this study is Pakistan, which is a developing country struggling with energy crises, but which has high solar potential. The hybrid system is modeled using the System Advisor Model (SAM). The results show that by hybridizing CSP with PV, the LCOE can be reduced by 18.5%.
concentrated solar power↗
Onsite Energy Techno-Economic Analysis Using REopt
Since 2019, the National Renewable Energy Laboratory (NREL) has collaborated with IEDO's Combined Heat and Power (CHP) Deployment Program and the CHP Technical Assistance Partnerships (TAPs) to expand the capabilities of NREL's publicly available REopt® tool for techno-economic analysis of on-site energy. As a result, capabilities to analyze heating and cooling loads and serve those loads with CHP were added to the REopt tool in 2021. Currently, NREL is using REopt to evaluate the economics and feasibility of deploying distributed energy resources at sites of 3-5 manufacturers. The analysis is based on location, site-specific load data, customized utility bill analysis, and other criteria such as resilience needs and decarbonization targets. The objectives of the current effort are to (1) assist manufacturers with analyzing on-site energy options, including CHP, solar photovoltaics (PV), wind, and battery storage, (2) validate the capabilities and use of REopt to provide technical assistance to manufacturers, and (3) publish case studies showcasing the engagement, key takeaways, and lessons learned. Future work is expected to include additional REopt capabilities for evaluating other technologies to reduce scope 1 emissions, such as electrifying process heating loads, using carbon-free fuels, and other clean heat strategies.
ENERGY PLANNING, POLICY, AND ECONOMY↗
Security assessment and impact analysis of cyberattacks in integrated T&D power systems
In this paper, we examine the impact of cyberattacks in an integrated transmission and distribution (T&D) power grid model with distributed energy resource (DER) integration. We adopt the OCTAVE Allegro methodology to identify critical system assets, enumerate potential threats, analyze and prioritize risks for threat scenarios. Based on the analysis, attack strategies and exploitation scenarios are identified which could lead to system compromise. Specifically, we investigate the impact of data integrity attacks in inverted-based solar PV controllers, control signal blocking attacks in protective switches and breakers, and coordinated monitoring and switching time-delay attacks. Index Terms—Cyberattacks, security assessment, impact analysis, case studies, integrated power systems.
14 SOLAR ENERGY↗
Investigating Local Carrier Dynamics in PERC Patterned CdTe Solar Cells
Remarkable progress has been achieved in CdTe photovoltaics (PVs) to further improve cell performance while reducing manufacturing costs. Researchers optimized the front contact that leads the short-circuit current density (J sc ) over 31mA/cm 2 (e.g., (Zn, Mg)O buffer layer and/or alloying CdTe with Se). Reese et al. reported an open-circuit voltage (V oc ) over 1 V with group-V doped single crystal, showing the feasibility of increasing V oc in CdTe PV that is fixed to less than 900 mV in most cases. Recent studies suggested that the V oc improvement in polycrystalline CdTe PVs requires well-passivated back contact. One possible strategy is to use CdMgTe alloy (E g > 1.8 eV), where the band-gap offset (ΔE CB ≈ 0.2 eV) reflects minority carrier electrons, thereby decreasing surface recombination. Another strategy is to utilize a stable Al 2 O 3 layer as an electron reflector; experimental works confirmed the improved performance with a conformal Al 2 O 3 layer. In this configuration, the precise control of Al 2 O 3 (≈1 nm) over the entire CdTe layer is essential because the J sc greatly depends on the tunneling current. While promising, both CdMgTe and Al 2 O 3 passivation on CdTe introduce unfavorable valence band offset that blocks the hole transport. Kephart et al. proposed a patterned passixc vation layer (≈ 20 nm Al 2 O 3 ) with point contacts (≈ 3 μm in diameter) that extract hole carriers. This configuration is similar to the passive emitter and rear contact (PERC) design that has been extensively studied in Si PVs. While remarkably high carrier lifetime and photoluminescence (> 10 X) were measured, consistent improvement in V oc and efficiency in this CdTe PERC were not yet observed. At this time, it is unclear how the surface potential is distributed in the presence of patterned Al 2 O 3 reflectors and how this additional field impacts the PV performance for Cu-doped and group-V doped CdTe PERC devices. To tackle this challenge, we develop robust nanofabrication and characterization platform to study CdTe PERC devices consisting of a patterned Al 2 O 3 layer on CdSe( 1-x )Te x (Cu-doped, GrV-doped; x = 0 to 1; CST). First Solar supplies high-quality CST materials. The dark and light I-Vs under 1-sun illumination are extracted for a series of each set of devices. We perform quantitative and qualitative PV analysis for a series of Cu-doped and Gr-V doped PERC devices, showing notably different V oc changes for GrV-doped compared to Cu-doped PERC devices. This project attempts to produce individual contacts on single grains and grain boundaries to measure lateral transport. As a model system, we use a CdSe( 1-x )Te x film on glass prepared by a colossal grain growth (CGG) technique at National Renewable Research Laboratories (NREL). Our preliminary results confirm that intergranular transport is hindered by the electrical barrier formed near grain boundaries. The PERC fabrication and the lateral transport measurement platform developed in this project can easily be applied to other types of advanced CdSe( 1-x )Te x architectures to better understand local photocarrier transport, in turn, providing the fundamental knowledge to improve the performance of CdTe PVs.
14 SOLAR ENERGY↗
Investigating capacity credit sensitivity to reliability metrics and computational methodologies
Assigning capacity value to renewable energy sources (RES) is a challenge faced in planning their integration with the grid. The difficulties stem from the natural characteristics of variability and intermittency of wind and solar sources. The capacity credit (CC) analysis evaluates the system’s actual power output compared with a constant capacity generator, i.e., conventional generator and determines an effective capacity to use for planning and operation. Herein this paper presents different factors that could affect the CC of a system. Two methods are proposed to determine the CC, namely equivalent firm capacity (EFC) and effective load carrying capability (ELCC). Since these methods are based on satisfying reliability criteria, daily loss of load expectation (LOLE), hourly loss of load (LOLH), and expected energy not served (EENS) have been employed as indices. To obtain the CC value, both methods apply two techniques: traditional and optimization. Genetic algorithm (GA) is the optimization approach used in this paper. Then, this work compares the two techniques and shows the superior performance of the optimization approach. Two hybrid systems, stand-alone (SA) and grid-connected (GC) modes, are proposed and used as case studies. The hybrid systems consist of photovoltaic (PV), wind turbine (WT), and battery energy storage system (BESS). In this work, three different scenarios are used to compare capacity credit: system as a whole, only wind, and no batteries. Finally, sensitivity analysis is carried out to examine the impact of varying the wind speed, solar irradiation, and load. It is demonstrated that the choice of reliability index plays an important role in determining the capacity credit and it is shown that EENS is a more comprehensive and consistent index of reliability.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Solar Radiation Research Laboratory (SRRL) Core Project Final Report: Fiscal Years 2022-2024
The Solar Radiation Research Laboratory (SRRL) at the National Laboratory of the Rockies (NLR) is a world-leading solar calibration and measurement facility and maintains and disseminates the World Radiation Reference (essentially the W/m2) for the United States that is essential for traceable and accurate measurements of solar radiation at all solar generation facilities. SRRL operates two calibration facilities that meet International Standards Organization-17025 (ISO-17025) standards and provide unique high-quality calibrations to NREL and other U.S. Department of Energy laboratories. The Baseline Measurement System (BMS) at SRRL provides a high-quality record of solar irradiance and surface meteorological conditions. SRRL capabilities are used to develop (1) improved methods for the calibration of solar radiometers; (2) new standards through the ISO, the International Electrotechnical Commission (IEC), and the American Standards for Testing of Materials (ASTM) International; (c) solar radiation and meteorological models; and (d) advanced instrumentation and methods for operating solar measurement stations. The SRRL datasets are also critical for the validation of new models and datasets, such as the National Solar Radiation Database (NSRDB). The research and development of solar radiation measurement systems and resource modeling techniques are essential for advancing the scientific basis for producing reliable resource data. Specifically, the spatial, temporal, and spectral (wavelength dependency) characteristics of the solar resource are required in several different time frames for various project phases.
14 SOLAR ENERGY↗
Experimental Setup and Learning-Based AI Model for Developing Accurate PV Inverter Models [Slides]
The integration of power electronics-based interfaces presents challenges due to the absence of detailed models and the high computational complexity. Generic models used in system studies lack accuracy in capturing converter dynamics. This paper proposes a data-driven approach developed from experimental setup data. This approach enhances accuracy in photovoltaic inverter modeling. We used two types of PV inverters in the experiment. The recorded experimental data undergo processing through a machine learning model. Results from the model trained through machine learning is also presented.
14 SOLAR ENERGY↗
pvlib python: 2023 project update
pvlib python is a community-developed, open-source software toolbox for simulating the performance of solar photovoltaic (PV) energy components and systems. It provides reference implementations of over 100 empirical and physics-based models from the peer-reviewed scientific literature, including solar position algorithms, irradiance models, thermal models, and PV electrical models. In addition to individual low-level model implementations, pvlib python provides high-level workflows that chain these models together like building blocks to form complete “weather-to-power” photovoltaic system models. It also provides functions to fetch and import a wide variety of weather datasets useful for PV modeling. pvlib python has been developed since 2013 and follows modern best practices for open-source python software, with comprehensive automated testing, standards-based packaging, and semantic versioning. Its source code is developed openly on GitHub and releases are distributed via the Python Package Index (PyPI) and the conda-forge repository. pvlib python’s source code is made freely available under the permissive BSD-3 license. Here we (the project’s core developers) present an update on pvlib python, describing capability and community development since our 2018 publication (Holmgren, Hansen, & Mikofski, 2018).
14 SOLAR ENERGY↗
MgZnO High‐Voltage Transparent Thin‐Film Transistors Built on Glass
Recently, there has been increasing interest in building‐integrated photovoltaic (BIPV), which enables harvesting solar energy effectively. Large‐area glass components such as windows are widely used in modern constructions. In addition to the PV on opaque components such as walls and roofs, the transparent photovoltaic (TPV) directly built on glass is complementary to fully utilize the PV energy in BIPV. A high‐voltage transparent thin‐film transistor (HVTTFT) built on glass is an ideal option for distributed microinverters for TPV modules. A wide‐bandgap oxide‐based HVTTFT on glass for this purpose is reported. The HVTTFT on glass uses ZnO‐based materials with different functions for two roles: a semiconductor Mg 0.01 Zn 0.99 O (MZO) as TFT channel and Al‐doped ZnO (AZO) as transparent conductive oxide (TCO) electrodes. The centrosymmetric circular structure of the MZO HVTTFT with a high‐k‐stacking gate dielectric enables a blocking voltage as high as ≈1 kV and an on/off ratio of 10 6 . The device exhibits an average optical transmittance of 81% over the visible spectrum.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Colloidal Quantum Dot Photovoltaics: Current Progress and Path to Gigawatt Scale Enabled by Smart Manufacturing
Colloidal quantum dots (QDs) have lately been pursued with intense vigor for optoelectronic applications such as photovoltaics (PV), flexible electronics, displays, mid-infrared photodetectors, lasers, and single-photon emitters. These nanometer-sized semiconducting crystals can be suitably mass-produced and size-tuned via cost-effective solution-based synthetic routes to operate in the quantum size confinement regime, endowing them with a wide array of exotic optical and electronic properties. While the first potential market entry could be in displays and in niche applications such as “internet-of-things”, ultimately, the technology has the potential to influence large-scale terrestrial power generation, because it is amenable to high-throughput synthesis from Earth-abundant materials and large-area solution-based coating techniques and can be air-stable. In this Review, we chronicle the recent advances that have propelled QD PV toward commercialization and highlight potential areas for further progress. We present an account of the material compositions being explored as QDs and their various benefits, major chemical passivation and doping strategies that have been developed to allay QD surface traps, and advanced device designs deployed to maximize charge extraction. We also discuss pathways to >20% efficient QD PV and describe recent advances in high-precision and autonomous synthesis of such materials. With recent demonstrations of scalable synthesis of high-quality QDs, smart manufacturing of QDs and QD solids, and fabrication of stable solar cells under ambient conditions, we suggest that the technology is on the road to achieving maturity and technological relevance and that gigawatt per year distributed panel production sites may be within reach.
14 SOLAR ENERGY↗
Power Supply Options for the Marpi Landfill, Saipan: Feasibility Study
The Marpi Landfill, located on the northern end of the island of Saipan in the Commonwealth of the Northern Mariana Islands (CNMI), is powered by an on-site diesel generator that only operates when the landfill is open and staffed. The CNMI Office of Planning and Development (OPD) aspires to provide the Marpi Landfill with 24-hour power availability despite its remote location and to increase the use of sustainable energy within the CNMI. CNMI has a 20% target for renewable energy consumption, as documented in Sustainable Development Goal #7 in the Comprehensive Sustainable Development Plan (OPD 2021) and the renewable portfolio standard (GPO 2014). To accomplish these goals, the U.S. Department of Energy, through its Interagency Reimbursable Work Agreement with the Federal Emergency Management Agency, funded this feasibility study to assess and prioritize power supply options for the landfill. The availability of solar and wind resources varies seasonally, as does the load. A BESS can help to balance mismatches between generation and load on short (hourly or daily) timescales, but not across seasons. The microgrid scenarios evaluated for Marpi consider options for technology combinations that will both meet the load and utilize available resources, despite the challenge presented by higher loads and lower solar and wind availability during the rainy season, depicted in Figure ES-2. The seven scenarios evaluated are summarized in Table ES-1. Each scenario’s configuration was optimized to include component capacities that reduce capital and operating costs, meet the load, and minimize carbon emissions, as feasible. The costs and levelized cost of energy (LCOE) shown do not assume the use of any grant funding or incentives, although these options were also evaluated. To assist with decision-making, a prioritization matrix (Table ES-3) was created to compare the microgrid scenarios evaluated in this feasibility study according to various stakeholder priorities. The prioritization metrics were chosen based on discussions with OPD and will be finalized through stakeholder feedback. The scenarios were given a score between 1 and 7 for each prioritization metric (the lower the score, the higher the priority), and total scores were calculated using assigned weights based on the relative priority of each metric. The total scores were then ranked to produce a prioritized list of microgrid scenarios based on the metrics most important to the project stakeholders. As shown, scenario 4 (100 kW of solar PV, a 75 kW/300 kWh BESS, and 160 kW of diesel generation) ranks highest.
14 SOLAR ENERGY↗