Results for “PV generators” — Page 45

DOE OSTI2026

Baseline vs. DER Scenario

Projections and associated uncertainty estimates are generated for a variety of user-selectable EV charging sessions, electricity tariffs, subsidy levels, revenue schemes, charging station configurations, and on-site solar and/or storage options. The outputs are presented in CHIP's web portal browser in the form of easily interpretable graphics (interactive graphs and bar charts) that facilitate convenient comparison among different scenarios to aid decision-making. The user should bring assumptions for modeling on simulation planning horizon, number of EV charging sessions per year, electricity costs (energy and demand charge rates; flat versus time-of-use rate), site capital costs (equipment for EV chargers and transformer), solar PV, and battery energy storage (kW).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Baseline vs. DER Scenario

Projections and associated uncertainty estimates are generated for a variety of user-selectable EV charging sessions, electricity tariffs, subsidy levels, revenue schemes, charging station configurations, and on-site solar and/or storage options. The outputs are presented in CHIP's web portal browser in the form of easily interpretable graphics (interactive graphs and bar charts) that facilitate convenient comparison among different scenarios to aid decision-making. The user should bring assumptions for modeling on simulation planning horizon, number of EV charging sessions per year, electricity costs (energy and demand charge rates; flat versus time-of-use rate), site capital costs (equipment for EV chargers and transformer), solar PV, and battery energy storage (kW).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Baseline vs. DER Scenario

Projections and associated uncertainty estimates are generated for a variety of user-selectable EV charging sessions, electricity tariffs, subsidy levels, revenue schemes, charging station configurations, and on-site solar and/or storage options. The outputs are presented in CHIP's web portal browser in the form of easily interpretable graphics (interactive graphs and bar charts) that facilitate convenient comparison among different scenarios to aid decision-making. The user should bring assumptions for modeling on simulation planning horizon, number of EV charging sessions per year, electricity costs (energy and demand charge rates; flat versus time-of-use rate), site capital costs (equipment for EV chargers and transformer), solar PV, and battery energy storage (kW).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Baseline vs. DER Scenario

Projections and associated uncertainty estimates are generated for a variety of user-selectable EV charging sessions, electricity tariffs, subsidy levels, revenue schemes, charging station configurations, and on-site solar and/or storage options. The outputs are presented in CHIP's web portal browser in the form of easily interpretable graphics (interactive graphs and bar charts) that facilitate convenient comparison among different scenarios to aid decision-making. The user should bring assumptions for modeling on simulation planning horizon, number of EV charging sessions per year, electricity costs (energy and demand charge rates; flat versus time-of-use rate), site capital costs (equipment for EV chargers and transformer), solar PV, and battery energy storage (kW).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Baseline vs. DER Scenario

Projections and associated uncertainty estimates are generated for a variety of user-selectable EV charging sessions, electricity tariffs, subsidy levels, revenue schemes, charging station configurations, and on-site solar and/or storage options. The outputs are presented in CHIP's web portal browser in the form of easily interpretable graphics (interactive graphs and bar charts) that facilitate convenient comparison among different scenarios to aid decision-making. The user should bring assumptions for modeling on simulation planning horizon, number of EV charging sessions per year, electricity costs (energy and demand charge rates; flat versus time-of-use rate), site capital costs (equipment for EV chargers and transformer), solar PV, and battery energy storage (kW).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Baseline vs. DER Scenario

Projections and associated uncertainty estimates are generated for a variety of user-selectable EV charging sessions, electricity tariffs, subsidy levels, revenue schemes, charging station configurations, and on-site solar and/or storage options. The outputs are presented in CHIP's web portal browser in the form of easily interpretable graphics (interactive graphs and bar charts) that facilitate convenient comparison among different scenarios to aid decision-making. The user should bring assumptions for modeling on simulation planning horizon, number of EV charging sessions per year, electricity costs (energy and demand charge rates; flat versus time-of-use rate), site capital costs (equipment for EV chargers and transformer), solar PV, and battery energy storage (kW).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Baseline vs. DER Scenario

Projections and associated uncertainty estimates are generated for a variety of user-selectable EV charging sessions, electricity tariffs, subsidy levels, revenue schemes, charging station configurations, and on-site solar and/or storage options. The outputs are presented in CHIP's web portal browser in the form of easily interpretable graphics (interactive graphs and bar charts) that facilitate convenient comparison among different scenarios to aid decision-making. The user should bring assumptions for modeling on simulation planning horizon, number of EV charging sessions per year, electricity costs (energy and demand charge rates; flat versus time-of-use rate), site capital costs (equipment for EV chargers and transformer), solar PV, and battery energy storage (kW).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Baseline vs. DER Scenario

Projections and associated uncertainty estimates are generated for a variety of user-selectable EV charging sessions, electricity tariffs, subsidy levels, revenue schemes, charging station configurations, and on-site solar and/or storage options. The outputs are presented in CHIP's web portal browser in the form of easily interpretable graphics (interactive graphs and bar charts) that facilitate convenient comparison among different scenarios to aid decision-making. The user should bring assumptions for modeling on simulation planning horizon, number of EV charging sessions per year, electricity costs (energy and demand charge rates; flat versus time-of-use rate), site capital costs (equipment for EV chargers and transformer), solar PV, and battery energy storage (kW).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Evaluating the Capabilities of Behind-the-Meter Solar-plus-Storage for Providing Backup Power during Long-Duration Power Interruptions [Slides]

The study estimates the performance of behind-the-meter solar PV-plus-energy-storage-systems (PVESS) in providing critical-load or whole-building backup across a wide range of geographies, building types, and power interruption conditions. The study also considers a set of 10 historical long-duration power outage events and evaluates how PVESS could have performed in providing backup power during those specific events. The analysis is the first in what will be a series of studies by Berkeley Lab, in collaboration with the National Renewable Energy Laboratory, on the use of PVESS for backup power. This initial study, which relies on simulated end-use level building loads, solar generation, and storage dispatch, is intended to provide a baseline set of performance estimates and to illustrate key performance drivers.

14 SOLAR ENERGY↗

NASA NTRS2009

Managing PV Power on Mars - MER Rovers

The MER Rovers have recently completed over 5 years of operation! This is a remarkable demonstration of the capabilities of PV power on the Martian surface. The extended mission required the development of an efficient process to predict the power available to the rovers on a day-to-day basis. The performance of the MER solar arrays is quite unlike that of any other Space array and perhaps more akin to Terrestrial PV operation, although even severe by that comparison. The impact of unpredictable factors, such as atmospheric conditions and dust accumulation (and removal) on the panels limits the accurate prediction of array power to short time spans. Based on the above, it is clear that long term power predictions are not sufficiently accurate to allow for detailed long term planning. Instead, the power assessment is essentially a daily activity, effectively resetting the boundary points for the overall predictive power model. A typical analysis begins with the importing of the telemetry from each rover's previous day's power subsystem activities. This includes the array power generated, battery state-of-charge, rover power loads, and rover orientation, all as functions of time. The predicted performance for that day is compared to the actual performance to identify the extent of any differences. The model is then corrected for these changes. Details of JPL's MER power analysis procedure are presented, including the description of steps needed to provide the final prediction for the mission planners. A dust cleaning event of the solar array is also highlighted to illustrate the impact of Martian weather on solar array performance

Mars dust↗

DOE OSTI2022

Overcoming Shockley-Queisser limit using halide perovskite platform?

The Intergovernmental Panel on Climate Change (IPCC) reveals that the global temperature has reached its highest level in the last 2,000 years. Development of emissions-free electrification technologies such as photovoltaics (PV) can be a great paramountcy to balance the climate pressure and the growing demand on energy. Although many PV technologies have been demonstrated so far, all the single-junction PVs are still subjected to the well-known efficiency cap of the Shockley-Queisser limit (33.7%), with most of the absorbed solar energy lost into heat. In parallel to delicate system-level designs, such as tandem, multi-junction, photothermal, or up-/down-conversion, we ask the question about the feasibility of overcoming the SQ limit at material level. In this study, we first dissect the origin of the limit, and then, by using the emerging perovskite as the platform, we list several potential pathways (i.e., hot carrier, multi-exciton generation, intermediate band gap, and ferroelectricity that have been newly discovered or can be introduced in the perovskite) to the roadmap of exceeding the SQ limit.

14 SOLAR ENERGY↗

DOE OSTI2026

OCHRE

OCHRE™ uses a variety of input data sources to run time-series simulations. Building models can be taken from the ResStock™ database or generated using the Building Energy Optimization Tool (BEopt™) or other OpenStudio-HPXML workflows. EV charging profiles can be taken from datasets used in NLR's 2030 National Charging Network project. Weather data can be taken from the National Solar Radiation Database or EnergyPlus® weather files. There are no public datasets with OCHRE outputs at this time. However, a recent project dataset on water heater and EV demand flexibility can be requested. OCHRE is a Python-based energy modeling tool designed to model flexible loads in residential buildings. OCHRE includes detailed models and controls for flexible devices including HVAC equipment, water heaters, EVs, solar PV, and batteries. It is designed to run in co-simulation with custom controllers, aggregators, and grid models.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Hybrid Power Plants: Status of Installed and Proposed Projects [Slides]

As battery prices fall and wind and solar generation rises, power plant developers are increasingly combining wind and solar projects with on-site batteries, creating “hybrid” power plants. But hybrid or co-located plants have been part of the U.S. electricity mix for decades, with widely ranging configurations that extend beyond pairing a generator with a battery. This new summary tracks and maps existing hybrid and co-located plants across the United States while also synthesizing data from generation interconnection queues to illustrate developer interest in the next wave of plants. The scope is inclusive of co-located hybrid plants that pair two or more generators and/or that pair generation with storage at a single point of interconnection, and also full hybrids that feature co-location and co-control. The focus is on larger, 1 MW+ systems: smaller (often behind-the-meter) projects are also increasingly common, but are not included in the data synthesis. Based in part on EIA Form 860 data, there were at least 125 co-located hybrid plants (>1 MW) already operating across the United States at the end of 2019, totaling over 14 GW of aggregate capacity. Some of the most common configurations include wind+storage (13 projects, 1,290 MW wind, 184 MW storage), PV+storage (40 projects, 882 MW PV, 169 MW storage), and fossil+storage (10 projects, 2,414 MW fossil, 91 MW storage). Data from interconnection queues demonstrates the considerable commercial interest that exists in hybrid power plants, especially solar co-located with storage. By the end of 2019, there were at least 367 GW of solar plants in the nation’s queues; 102 GW (~28%) of this capacity was proposed as a hybrid, most typically pairing PV with battery storage. For wind, 225 GW of capacity sat in the queues, with 11 GW (~5%) proposed as a hybrid, again most-often pairing wind with storage. The proposed solar+storage plants are located throughout the United States, but with California and the non-ISO West being the most prominent areas of commercial interest. Proposed wind+storage and standalone storage plants also center to a degree on these regions of the country.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Experimentation in Exploring Photovoltaic Inverter Dynamics Under Different Irradiance Levels Through a Data-Driven Approach

As conventional direct connections of synchronous generators are being phased out, inverter-based resources (IBRs) with grid support functions are increasingly being integrated into power systems. This transition requires the development of accurate dynamic models for IBRs to predict how power systems will adapt to varying levels of IBRs penetration, establish grid code requirements, and ensure compliance. Here, this study introduces an active probing signal-based data-driven modeling technique to accurately derive the dynamics model of a smart photovoltaic inverter operating in Volt-Watt and Freq-Watt modes, in compliance with the IEEE 1547–2018 standard. The paper focuses on investigating how the dynamics of the PV inverter model respond to fluctuations in solar irradiance, utilizing real-time digital simulator experimentation. The experimental analysis demonstrates that the amplitude of dynamics fluctuates with changes in irradiance across both operational modes and confirms the active power’s dependence on irradiance levels. Furthermore, the nature of inverter dynamics varies distinctly between the different modes of activation. Critically, our findings indicate that dynamic models require DC-gain adjustments to accommodate contrasting irradiance levels, highlighting a negative gradient linear relationship between the DC-gain of each model and the irradiance.

14 SOLAR ENERGY↗

DOE OSTI2024

Analysis of Grid-Forming Inverter Controls for Grid-Connected and Islanded Microgrid Integration

Autonomous grid-forming (GFM) inverter testbeds with scalable platforms have attracted interest recently. In this study, a self-synchronized universal droop controller (SUDC) was adopted, tested, and scaled in a small network and a test feeder using a real-time simulation tool to operate microgrids without synchronous generators. We presented a novel GFM inverter control adoption to better understand the dynamic behavior of the inverters and their scalability, which can impact the distribution system (DS). This paper provides a steady-state and transient analysis of the GFM power inverter controller via simulation to better understand voltage and frequency stabilization and ensure that the critical electric loads are not affected during a prolonged power outage. The controllers of the GFM inverter are simulated in HYPERSIM to examine voltage and frequency fluctuations. This analysis includes assessing the black start capability for photovoltaic microgrids, both grid-connected and islanded, during transient fault conditions. The high photovoltaic PV penetration levels open exciting opportunities and challenges for the DS. The GFM inverter control demonstrated appropriate response times for synchronization, connection, and disconnection to the grid. The DS has become more resilient and independent of fossil fuels by increasing the penetration of inverter-based distributed energy resources (DERs).

Ward, Laura (ORCID:0000000345501581)↗

NASA NTRS2002

Chemical Vapor Deposition for Ultra-lightweight Thin-film Solar Arrays for Space

The development of thin-film solar cells on flexible, lightweight, space-qualified substrates provides an attractive cost solution to fabricating solar arrays with high specific power, (W/kg). The use of a polycrystalline chalcopyrite absorber layer for thin film solar cells is considered as the next generation photovoltaic devices. A key technical issues outlined in the 2001 U.S. Photovoltaic Roadmap, is the need to develop low cost, high throughput manufacturing for high-efficiency thin film solar cells. At NASA GRC we have focused on the development of new single-source-precursors (SSPs) and their utility to deposit the chalcopyrite semi-conducting layer (CIS) onto flexible substrates for solar cell fabrication. The syntheses and thermal modulation of SSPs via molecular engineering is described. Thin-film fabrication studies demonstrate the SSPs can be used in a spray CVD process, for depositing CIS at reduced temperatures, which display good electrical properties, suitable for PV devices.

Hepp, Aloysius F.↗

DOE OSTI2020

Demand Response Potential from the Bulk Grid Perspective

Gain insight from an exploration of the potential value of demand response (DR) in future power systems. Using hourly DR resource estimates by sub-sector, electrical end-use, and grid service, we incorporate virtual generator models of DR resources into large-scale production cost models, and analyze the grid-level impacts in terms of the ability of DR to reduce system costs and potentially help integrate renewables or reduce system emissions. Additionally, we examine the value of DR, its revenue, and how these change under different system conditions. In this panel session, we will describe our input data and modeling methods, provide an overview of the production cost models used, and summarize key results from analyses in Florida and the western United States. Findings include variations in DR value by end-use and geography, an ability to increase economic PV deployment potential in high penetration systems, and mixed emissions outcomes depending on system composition and fuel prices.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

An Analysis Framework for Distribution Network DER Integration Analysis in India: Distributed Solar in Tamil Nadu

This report is part of a two-part series that represents a year-long collaboration with the Tamil Nadu Generation and Distribution Corporation Limited (TANGEDCO) on power sector planning. The first report in this series, the Pathways for Tamil Nadu’s Electric Power Sector 2017-2030 report outlines NREL’s work with TANGEDCO's electricity sector planning department to develop a model of the State’s power system and evaluate multiple scenarios of system growth given resource constraints, costs of technologies, and power sector policies. This second report in this series focuses on the rapidly transforming distribution network in the State. The report outlines a framework developed by NREL with TANGEDCO's distribution utility to quickly and accurately analyze the impacts of integrating renewable energy, specifically rooftop solar PV onto Tamil Nadu's distribution system. Together these studies help to prepare Tamil Nadu for a rapidly transforming power system.

14 SOLAR ENERGY↗