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At least 127 records · Page 7

Bringing Solar Energy to Low- and Moderate-Income Communities

The U.S. solar photovoltaics (PV) industry has taken off over the past decade, but without deliberate action low- and moderate-income communities could be left behind. Key recommendations for policymakers and funders in the renewable energy and community development fields that emerged from this process include the following: • Help to capitalize and support community-based lenders to provide flexible, low-cost, and long- term financing to mission-driven solar projects— including providing guarantees or other forms of credit enhancement. • Provide a grant-in-lieu-of-credits option for the Investment Tax Credit as was done during the last recession. • Develop pools of government and philanthropic support that can complement financing from community-based lenders to complete the capi- tal stack for mission-driven projects, as well as to support education and technical assistance to both consumers and potential project sponsors. • Create a national Renewable Energy Credits pro- gram that includes social equity targets to provide a baseline of support for clean energy generation. • Change utility regulations to remove barriers to low-income solar projects, provide greater certainty for developers, and measure progress toward equity in renewable energy policy implementation.

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Assessing the nexus between groundwater and solar energy plants in a desert basin with a dual-model approach under uncertainty

Globally, many solar power plants and other types of renewable energy are being located in water-scarce regions. Many projects rely on groundwater resources whose sustainability is uncertain. In the Chuckwalla Basin in California, quantification of recharge and trans-valley underflow is needed to estimate the impacts of solar project withdrawals on the water table. However, such estimates are highly challenging due to data scarcity, heterogeneous soils and long residence times. Conventional assessment employs isolated groundwater models configured with crude and uniform estimates of recharge. Here, we employ a data-constrained surface subsurface processes model, PAWS+CLM, to provide an ensemble of recharges and underflows with perturbed parameters. Then, the Parameter Estimation (PEST) package is used to calibrate MODFLOW aquifer conductivity and filter out implausible recharges. The novel dual-model approach, potentially applicable in other arid regions, can effectively assimilate groundwater head observations, reject unrealistic parameters, and narrow the range of estimated drawdowns. Simulated recharge concentrates along alluvial fans at the mountain fronts and ephemeral washes where run-off water infiltrates. If an evenly distributed recharge was assumed, it resulted in under-estimated drawdown and larger uncertainty bounds. The withdrawals are approaching total inflow, suggesting the system will be nearing, if not exceeding, its sustainable groundwater production capacity, and a boom of such projects will not be sustainable. Especially, the cost/benefit of pumped-storage projects is called into question as the initial-fill phase depletes entire area’s recharge. Our study highlights the stress on groundwater resources of solar development, and that the speed of groundwater recovery does not indicate sustainability. Main point 1: A novel dual model approach, involving an integrated surface/subsurface model and a groundwater parameter-estimation model, was able to better constrain the model. Main point 2: The groundwater system may be nearing, if not exceeding, its sustainable groundwater production capacity and the speed of recovery is not indicative of sustainability. Main point 3: Results from using conventionally-assumed uniform recharge distort calibrated K fields and impacts assessment

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Solar Energy Development on the FSST Reservation

FSST undertook this project to install PV solar with the goal of reducing retail power consumption at 11 Tribal buildings. A combined total of 318kW has been installed over these sites and power savings are being recorded on a regular basis. The Tribe entered into the project with several specific objectives that made this a unique effort. First of all, all of the systems were installed by Tribal maintenance personnel with some technical support. This model had been developed with previous projects that Nebraska Renewable Energy Systems (NRES) had completed and had shown great success. This approach helped to ensure we met the DOE goal of ‘building capacity’ within the Tribe. There was some skepticism about this model in Flandreau at the onset of discussions, but the excellent final results spoke for themselves! A second objective was to overcome the sore lessons that were learned after FSST invested in early deployment of pole mounted solar systems that were not sturdy enough for SD winds. It was a very courageous decision to move forward again with solar pole mounts (and other types) in this very high wind area. We shall report that the Tribe was fully successful in achieving what they set out to do there. The final major objective was to deploy the PV Solar systems in such a way as to integrate them into their surroundings wherever possible. In some cases the mounting choice was clear, but in several locations, the system was designed to be a functional and aesthetically enhancing part of their surroundings. These elevated systems allowed the PV system to act as a shade structure and create useful space under them as well as making power. FSST had these elevated ground mount systems specially designed for our application by Ironridge and were rated for the tough winds of South Dakota (120MPH+).

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Decision Support Tool for Solar Energy Cybersecurity Policy and Regulation

The Decision Support Tool helps users address four discrete challenges: (1) complex requirements of relevant codes and standards, (2) technical complexity of solar assets, (3) undefined cyber risk severity, and (4) unclear roles and responsibilities. Content includes an analysis of cyber vulnerability risks, a decision support resource for policymakers to mitigate cyber risks to solar photovoltaic systems, and background resources for informing policy development. A key component of this tool is the Probable Risk Assessment (PRA), based on established, formal variables, models, and consequences, which helps users understand the determined risk and assigned ownership of the physical components. It helps states draw logical lines between vulnerabilities and mitigative solutions, of which some have been further detailed as Cybersecurity Advisory Team for State Solar (CATSS) tools.

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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.

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Solar Energy Implementation Strategies on Picuris Pueblo

Picuris Pueblo is a small tribal community in Northern New Mexico consisting of about 306 members and 86 homes. Picuris Pueblo has made advances with renewable energy implementation, including the installation of a 1 megawatt photovoltaic (PV) array. This array has provided the tribe with economic and other benefits that contribute toward the tribe's goal of tribal sovereignty. The tribe is seeking to implement more PV generation as well as battery energy storage systems. Picuris Pueblo is considering different implementation methods, including the formation of a microgrid system. This report studies the potential implementation of a PV and battery storage microgrid system and the associated benefits and challenges. The benefits of a microgrid system include cost savings, increased resiliency, and increased tribal sovereignty and align with the tribe's goals of becoming energy independent and lowering the cost of electricity.

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Solar Energy from a Big Picture Perspective to Nanoscale Insights via TOF-SIMS

The world is undergoing a rapid transformation in the ways that we generate and store energy. This has been driven not only by concerns about the climate but by simple economic factors due to the dramatic cost decreases in wind in solar power. In most places of the world where one would now want to build a new power plant, the cheapest option is to use wind of solar for power generation. Abundant clean energy when the sun shines most is driving new research for daily and seasonal energy storage in many different technologies. Here, we will briefly these discuss energy trends as a whole, before diving into our recent contributions to the field using time-of-flight secondary-ion mass spectrometry (TOF-SIMS) to improve the performance and reliability of solar cells.

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Performance analysis of integrated Nuclear-Solar Energy system sharing same molten salt thermal energy storage

Advanced nuclear reactors may be deployed with integrated thermal energy storage to improve flexibility and maximize revenue. This presents opportunities for thermal integration with concentrating solar power (CSP) to generate component synergies and/or improve performance. Here in this study, a computational model is developed for an integrated nuclear and CSP system that both share the same molten salt thermal energy storage (TES). Optimized dispatch schedules are developed subject to various market conditions, and the ratio of the nuclear to CSP thermal output is also varied. Performance of the combined system is compared to separate nuclear and solar plants, to determine if there is an overall benefit that can be derived from sharing the TES. Given sufficient volatility in electricity prices (e.g., under CAISO market conditions), synergies of up to 8% in net revenue are observed as a result of sharing the same TES, primarily due to improved revenue from enabling operation of the turbine closer to its design point, as well as being able to better take advantage of higher electricity prices. The synergy benefits are largest when the nuclear and solar plants have similar thermal output. However, when prices are less volatile the opposite behavior can be observed and it can be preferable to operate the nuclear plant as a baseload generator.

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Sustainable Solar Energy for Hughes Village (Hudotl’eekkaakk’e Tribe) (Final Technical Report)

Hughes Village Council is the local Tribal government for Hughes, Alaska. With the funding from this project, the Village Council designed and installed a 120kW solar Photo Voltaic (PV) array with a 250 kW/335kWh lithium-ion battery bank that has offset diesel consumption in the community by an estimated 10% per year. This translates to approximately 6,000 gallons of fuel per year. The goal is to reduce diesel consumption and turn the diesel generators off for certain periods of the Alaskan summer when solar PV is abundant and electrical loads in the community are low. Daily generator logs from the community show an average load of approximately 50kW-60kW with peaks ranging from 100kW-160kW. This project aligns with the tribe’s mission to work towards tribal energy sovereignty, utilizing sustainable energy technologies, and their overall goal of 25% clean energy by 2025.

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Interesting Solar Energy System Simulations in 1990 and 2025

This presentation uses a simulation by the author in 1991 and newer developements in 2025 to illustrate strategies to address problems that arise when steady state assumption is applied in time series simulation: 1) high resolution time series data; 2) distirbution functiion; 3) machine learning. The presentation does not report new findings (previously published material is cited).

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Prediction of Solar Irradiance and Photovoltaic Solar Energy Product Based on Cloud Coverage Estimation Using Machine Learning Methods

Cloud cover estimation from images taken by sky-facing cameras can be an important input for analyzing current weather conditions and estimating photovoltaic power generation. The constant change in position, shape, and density of clouds, however, makes the development of a robust computational method for cloud cover estimation challenging. Accurately determining the edge of clouds and hence the separation between clouds and clear sky is difficult and often impossible. Toward determining cloud cover for estimating photovoltaic output, we propose using machine learning methods for cloud segmentation. We compare several methods including a classical regression model, deep learning methods, and boosting methods that combine results from the other machine learning models. To train each of the machine learning models with various sky conditions, we supplemented the existing Singapore whole sky imaging segmentation database with hazy and overcast images collected by a camera-equipped Waggle sensor node. We found that the U-Net architecture, one of the deep neural networks we utilized, segmented cloud pixels most accurately. However, the accuracy of segmenting cloud pixels did not guarantee high accuracy of estimating solar irradiance. We confirmed that the cloud cover ratio is directly related to solar irradiance. Additionally, we confirmed that solar irradiance and solar power output are closely related; hence, by predicting solar irradiance, we can estimate solar power output. This study demonstrates that sky-facing cameras with machine learning methods can be used to estimate solar power output. This ground-based approach provides an inexpensive way to understand solar irradiance and estimate production from photovoltaic solar facilities.

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Argonne-Northwestern Solar Energy Research Center (08/01/2009-07/31/2018) and renamed Center for Light Energy Activated Redox Processes (LEAP) (Final Report)

In 2009-2014 the ANSER Center focused on understanding how molecules, materials, and systems can use sunlight to generate charges that drive catalysts for solar fuels formation and directly power photovoltaic cells. We addressed a common set of fundamental questions that must be answered in both contexts to successfully utilize sunlight as a renewable energy source for fuels and electricity. By attacking the common questions intrinsic to solar fuels and electricity in the same research center, ANSER provided opportunities for cross-cutting solutions not possible by addressing only fuels or electricity alone.

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San Xavier District Solar Energy Project for Administration Building and Education Center

The San Xavier District of the Tohono O’odham Nation (District) developed grid-tied solar photovoltaic (PV) systems for two tribal buildings: the San Xavier District Administration Building and Education Center. For the Administration Building, an approximately 182-kilowatt (kW) solar PV system is projected to produce roughly 310,000 kilowatt-hours (kWh) per year and displace about 80% of the energy use of the building. For the Education Center, an approximately 73.5-kw system is projected to produce roughly 130,000 kWh per year and displace about 95% of the building’s energy use. The anticipated 25-year cost savings from the combined 255-kW systems are estimated to be approximately $1,750,000 and $820,000 for the Administration Building and the Education Center, respectively.

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