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At least 91 records · Page 5

Bio-inspired strategies for next-generation perovskite solar mobile power sources

Smart electronic devices are becoming ubiquitous due to many appealing attributes including portability, long operational time, rechargeability and compatibility with the user-desired form factor. Integration of mobile power sources (MPS) based on photovoltaic technologies with smart electronics will continue to drive improved sustainability and independence. With high efficiency, low cost, flexibility and lightweight features, halide perovskite photovoltaics have become promising candidates for MPS. Realization of these photovoltaic MPS (PV-MPS) with unconventionally extraordinary attributes requires new ‘out-of-box’ designs. Natural materials have provided promising designing solutions to engineer properties under a broad range of boundary conditions, ranging from molecules, proteins, cells, tissues, apparatus to systems in animals, plants, and humans optimized through billions of years of evolution. Applying bio-inspired strategies in PV-MPS could be biomolecular modification on crystallization at the atomic/meso-scale, bio-structural duplication at the device/system level and bio-mimicking at the functional level to render efficient charge delivery, energy transport/utilization, as well as stronger resistance against environmental stimuli (e.g., self-healing and self-cleaning). In this paper, we discuss the bio-inspired/-mimetic structures, experimental models, and working principles, with the goal of revealing physics and bio-microstructures relevant for PV-MPS. Here the emphasis is on identifying the strategies and material designs towards improvement of the performance of emerging halide perovskite PVs and strategizing their bridge to future MPS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Solar Energy Technologies Office Workforce Request for Information and Convenings (Summary)

On May 4, 2021, the U.S. Department of Energy (DOE) Solar Energy Technologies Office (SETO) published a Request for Information (RFI) on programs that support the development of a diverse and skilled clean energy workforce. The purpose of the RFI was to solicit feedback from industry, academia, government agencies, worker organizations (including unions), and other stakeholders on issues related to the employment needs of the solar industry, and the perceived value of different workforce development programs, training strategies, and tools. To supplement the RFI, SETO hosted four virtual convenings that brought together the utility-scale solar industry, the distributed generation solar industry, and labor and other workforce training organizations to hear direct feedback on the questions in the RFI. In addition, SETO held listening sessions with about a dozen other organizations and staff who could not participate in the virtual convenings. Altogether, SETO received 45 responses from the RFI and heard directly from 80-100 other stakeholders via the convenings and listening sessions. This document summarizes the stakeholder feedback that SETO received as a result of this process. While both the RFI and convening series were focused on solar deployment and solar industry members, much of this information is relevant across clean energy technologies and programs. It is important to recognize that DOE is intentionally reviewing our workforce development programming and support to focus on clean energy careers more holistically.

14 SOLAR ENERGY↗

Development of High Temperature (>700°C) Molten Salt Pump Technology for Generation 3 Solar Power Tower Systems

Bearings are required for long-shafted pumps historically used in concentrating solar thermal power applications. For molten chloride salts, bearings for such service conditions are not commercially available, nor has a design been demonstrated to work. Therefore, a project was sponsored by the Department of Energy’s Solar Energy Technologies Office for the development and demonstration of a submerged bearing for use in chloride salt pumps. This project’s tasks covered the tribological testing of candidate materials and the design, fabrication, testing, and post-test analysis of full-scale salt-compatible bearings. This work expands upon previous work. The effects of potential particulate in the salt were investigated through tribological bench testing. Through 11 tests, the MgO particulate size and concentration in a molten chloride salt were varied, and the effects on friction, wear rate, and wear characteristics were recorded. Novel journal bearings for chloride salt service were designed and fabricated based on these results. The bearings were of a relevant scale (i.e., for a 1.5 in. pump shaft) to demonstrate the technology with respect to further scale-up. The bearings were made of Haynes 244 and Yttria Partially Stabilized Zirconia. A custom bearing test rig, salt tanks, and associated infrastructure (e.g., heaters, tanks, transfer lines, gas flow control) were designed, procured, and installed. A few issues were encountered in the system fabrication process, resulting in delay of the project schedule. The system was successfully fabricated and assembled. Heating, cover gas, and pump motor systems were integrated into the control logic. This progress of the bearing test system represents a significant step forward towards demonstrating this promising technology. Nevertheless, the project ended before testing of the full-scale bearings could be performed.

14 SOLAR ENERGY↗

Comprehensive energy balance analysis of photon-enhanced thermionic power generation considering concentrated solar absorption distribution

The present article reports a comprehensive energy balance analysis of a photon-enhanced thermionic emission (PETE) device when it is used for concentrated solar power (CSP) generation. To this end, we consider a realistic PETE device composed of a boron-doped silicon emitter on glass and a phosphorus-doped diamond collector on tungsten separated by the interelectrode vacuum gap. Here, depth-dependent spectral solar absorption and its photovoltaic and photothermal energy conversion processes are rigorously calculated to predict the PETE power output and energy conversion efficiency. Our calculation predicts that when optimized, the power output of the considered PETE device can reach 1.6 W/cm 2 with the energy conversion efficiency of ~ 18% for 100× solar concentration, which is substantially lower than those predicted in previous works under ideal conditions. In addition, the photon-enhancement ratio is lower than 10 and decreases with the increasing solar concentration due to the photothermal heating of the emitter assembly, suggesting that PETE should be more suitable for lowto- medium CSP below ~ 100× concentration. These observations signify the importance of a rigorous energy balance analysis based on spectral and spatial solar absorption distribution for the accurate prediction of PETE power generation.

14 SOLAR ENERGY↗

Optimal Power System Black start using Inverter-Based Generation

Power system black start readiness is part of the system planning. Utility planners perform periodic studies to assess if their power system is capable of total restoration following a black out. Hydro and diesel generators are the most commonly used black start capable resources by power utilities. However, with increasing penetration of solar generation, inverter-based resources can be considered to provide black start capability. Since the solar inverters can be located at multiple locations throughout the power system, and in view of their unique characteristics, an optimal real-time capable plan is helpful for system operators for faster black start. Black start optimization is a multi stage mixed-integer non-linear optimization which is extremely hard to solve. In this paper, we propose an optimal black start methodology that is easier to solve and scalable in real-time. We demonstrate the proposed methodology on two test systems and illustrate how inverter-based resources can contribute and improve power system restoration.

power system restoration, blackstart, Inverter-bas↗

Development of a 95-Year Solar Dataset for Resource Adequacy Studies

Long-term high-resolution solar data provides enhanced understanding of variability of solar generation and enhances our ability to develop strategies for a resilient and reliable electric grid under high deployment of solar energy. Therefore, it is important to develop long-term synthetic datasets that can provide multiple occurrences of various severe weather scenarios that are expected to test the limits of resource adequacy under scenarios contain various energy generation sources. Examples of such scenarios could be long periods of high temperatures when demand for electricity is high or periods where high winds could lead to a shut-down of transmission lines for long periods of time to ensure fire safety. NREL has developed the first version of such a dataset covering a 95-year period covering 2006-2100 at a 4km hourly resolution. This dataset contains all variables necessary to calculate solar generation. During development of this dataset, we focused on creating unbiased, high-resolution solar irradiance through statistical downscaling methods, using Regional Climate Model (RCM) simulations from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) as input. The National Solar Radiation Database (NSRDB) containing over 25 years of observations was used to calibrate the statistical downscaling models. This presentation will outline the primary steps in developing this dataset, including (1) regridding RCM data to a common grid at 20-km resolution, (2) correcting RCM biases with NSRDB, (3) applying temporal and spatial downscaling methods to generate high-resolution (4-km, hourly) solar and ancillary data. Additionally, we will present an evaluation of the downscaled data against the NSRDB across various zones in the CONUS. Lastly, we will present a user guide for accessing the datasets.

14 SOLAR ENERGY↗

Multi-agent voltage control in distribution systems using GAN-DRL-based approach

Active distribution grids can experience voltage fluctuations and violations due to the high penetration of variable distributed energy resources (DERs). These problems might occur because of the uncertain and variable generation natures of these resources, especially solar photovoltaic resources, during panel shadowing scenarios. Volt-VAR control (VVC) is an efficient method that controls the reactive power set-points of the inverters to regulate the voltage of distribution grids. Although several VVC approaches have been proposed recently, the performance of these approaches degrades significantly if behind-the-meter solar generation data are unobservable/missing. Therefore, it is necessary to impute missing/unobservable PV data accurately to be utilized in VVC approaches. Further, this paper proposes a model-free, data-driven, centrally trained, and decentrally executed multi-agent deep reinforcement learning-based VVC architecture to regulate the voltage of distribution networks. A generative adversarial network (GAN) is incorporated to impute the unobservable PV data accurately, which improves the performance of the proposed control architecture. The proposed multi-agent-soft-actor–critic algorithm (MASAC)-based VVC technique utilizes the actual PV dataset as well as the imputed dataset from the GAN framework to learn the optimal coordinated control policy for controlling the optimal reactive power set-points of PV inverters. The effectiveness of the proposed approach is analyzed on a modified IEEE 34-bus test case with added PV inverters. The results are compared and analyzed with a base case model with no VVC and VVC with a local droop control approach, genetic algorithm optimization, and a centralized soft actor–critic-based approach. Moreover, the performance of the proposed approach is compared with that of a multi-agent VVC framework without using the PV generation data and load information as the system state. The results illustrate that the proposed method with more state input improves the voltage profile and reduces the power loss of the network across various loading and PV generation scenarios.

14 SOLAR ENERGY↗

California Time-of-Use (TOU) Transition: Effects on Distributed Wind and Solar Economic Potential

Time-of-use (TOU) retail energy rates price electricity differently by the time of day, communicating to consumers the costs of supplying electricity diurnally. This study evaluates the impact of Decision D.15.07-001, which mandates a transition in 2020 to default TOU rates for residential ratepayers in California, on the economic viability of behind-the-meter distributed wind and solar systems. Previous studies have demonstrated that increasing wind and solar generation will materially affect the diurnal cost of wholesale electricity. As retail and wholesale prices become more aligned, this could affect the inter-technology economic viability of distributed generation. We assess economic viability through 'economic potential,' or the amount of generation capacity that exceeds a rate of return of 5.4%. In addition, we identify sensitivities of economic potential to capital costs and other techno-economic factors as well as the specific counties and sectors with substantial economic potential. We find that TOU implementation is projected to moderately increase economic potential of distributed wind and marginally decrease that of distributed solar. Over the long-term as variable renewable energy penetration increases in California, particularly utility-scale solar, net peak load and thus peak prices will shift later in the evening. To the extent that retail rates continue to evolve with wholesale prices, we find the changes could positively affect the value of wind generation more than that of solar generation. Over the scenarios considered, model results indicate realistic pathways to reaching a robust distributed wind market in California though solar economic potential was found to be substantially larger than that of wind.

17 WIND ENERGY↗

The WRF-Solar Ensemble Prediction System: Development, Test, and Validation

Providing reliable probabilistic solar radiation information is needed to improve management of the uncertainty and variability of solar generation. Thus, guidance on how to develop skillful and accurate ensemble forecasts is essential and it will ultimately contribute to integration of high amounts of solar energy on the grid. A team from the National Renewable Energy Laboratory and the National Center for Atmospheric Research had been collaborating to develop the WRF-Solar ensemble prediction system (WRF-Solar EPS) in the past three years to produce probabilistic solar irradiance forecasts and better predict solar energy by quantifying forecast uncertainty. The WRF-Solar EPS basically generates ensemble members for solar irradiance based on stochastic perturbations to provide intraday and day-ahead probabilistic forecasts. This study will present main research steps in developing the WRF-Solar EPS including: (a) tangent linear analysis for identifying key input variables of six WRF-Solar modules significantly related to predicting of cloud and solar irradiance, (b) combining stochastic perturbation technique with the WRF-Solar model, and (c) ensemble calibration method to decrease error and uncertainty of ensemble-based solar forecasts. The capability of WRF-Solar EPS is now updated to the most recent version of standard WRF model. This presentation will summarize comprehensive results from the evaluation of forecasts against the National Solar Radiation Data Base as well as ground-measured observations. Moreover, we will introduce the user's guide for WRF-Solar EPS (e.g., parameters to configure stochastic perturbations) and future extension of this research.

day-ahead forecast↗

Estimating the impacts of natural gas power generation growth on solar electricity development: PJM's evolving resource mix and ramping capability

Abstract Expansion of distributed solar photovoltaic (PV) and natural gas‐fired generation capacity in the United States has put a renewed spotlight on methods and tools for power system planning and grid modernization. This article investigates the impact of increasing natural gas‐fired electricity generation assets on installed distributed solar PV systems in the Pennsylvania–New Jersey–Maryland (PJM) Interconnection in the United States over the period 2008–2018. We developed an empirical dynamic panel data model using the system‐generalized method of moments (system‐GMM) estimation approach. The model accounts for the impact of past and current technical, market and policy changes over time, forecasting errors, and business cycles by controlling for PJM jurisdictions‐level effects and year fixed effects. Using an instrumental variable to control for endogeneity, we concluded that natural gas does not crowd out renewables like solar PV in the PJM capacity market; however, we also found considerable heterogeneity. Such heterogeneity was displayed in the relationship between solar PV systems and electricity prices. More interestingly, we found no evidence suggesting any relationship between distributed solar PV development and nuclear, coal, hydro, or electricity consumption. In addition, considering policy effects of state renewable portfolio standards, net energy metering, differences in the PJM market structure, and other demand and cost‐related factors proved important in assessing their impacts on solar PV generation capacity, including energy storage as a non‐wire alternative policy technique. This article is categorized under: Photovoltaics > Economics and Policy Fossil Fuels > Climate and Environment Energy Systems Economics > Economics and Policy

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Chemically tuned intermediate band states in atomically thin Cu x GeSe/SnS quantum material for photovoltaic applications

A new generation of quantum material derived from intercalating zerovalent atoms such as Cu into the intrinsic van der Waals gap at the interface of atomically thin two-dimensional GeSe/SnS heterostructure is designed, and their optoelectronic features are explored for next-generation photovoltaic applications. Advanced ab initio modeling reveals that many-body effects induce intermediate band (IB) states, with subband gaps (~0.78 and 1.26 electron volts) ideal for next-generation solar devices, which promise efficiency greater than the Shockley-Queisser limit of ~32%. The charge carriers across the heterojunction are both energetically and spontaneously spatially confined, reducing nonradiative recombination and boosting quantum efficiency. Using this IB material in a solar cell prototype enhances absorption and carrier generation in the near-infrared to visible light range. Tuning the active layer’s thickness increases optical activity at wavelengths greater than 600 nm, achieving ~190% external quantum efficiency over a broad solar wavelength range, underscoring its potential in advanced photovoltaic technology.

36 MATERIALS SCIENCE↗

Modeling Needs to Support the Reconstruction Strategy of Ukraine

Ukraine has been facing difficult times. Russia started a full-scale invasion on February 24, 2022, and has caused huge human and infrastructure losses. As a result of the invasion, more than 8 million people left their homes. The Russian army has targeted Ukrainian energy sources, destroying or damaging over 50% of thermal power generation capacity (coal and gas), 30% of solar generation, and 90% of wind generation. The Russians are also threatening Ukrainian energy security, as they currently control the Zaporizhzhia nuclear power plant – Europe’s largest. In addition, Russia has destroyed 121,000 buildings, including 5,300 multistory buildings - more buildings than Ukraine built during the past five years. The occupiers destroyed or damaged 343 district heat boiler stations (destroyed 12 / damaged 331) and 8 CHPs (destroyed 4/ damaged 4). There is no doubt that Ukraine will be able to protect its sovereignty and restore its territorial integrity; however, this will be a long process. The Government of Ukraine needs to simultaneously focus on many issues, from waging war to the restoration of electricity, water, and heat supply in the territories close to the front line. In addition to these time-sensitive issues, the government also needs to plan a long term multi-sector strategy for the reconstruction of Ukraine’s economy. Ukraine initiated a broad-based political process for recovery at the International Ukraine Recovery Conference (URC 2022) in Lugano, Switzerland. Prior to URC 2022, Ukraine applied for EU membership on February 28 and was granted the status of candidate country by the European Council on June 23, 2022. More than 40 nations are fully committed to supporting Ukraine throughout its path from early to long-term recovery. In addition, these countries link a successful recovery to Ukraine’s European future (URC, 2022a). The reconstruction process will be long. The government also recognizes that it is not enough to build energy infrastructure back – it should be built back better. The government is committed to building a more sustainable and cleaner energy sector. Energy modeling can provide important insights into paths to decarbonize Ukraine’s economy while rebuilding it after the war. Pacific Northwest National Laboratory (PNNL) and the Institute for Economics and Forecasting of the National Academy of Sciences of Ukraine (IEF) work on modeling decarbonization scenarios in the energy sector of Ukraine. The teams focus on the heat sector, which includes district heat, autonomous and individual heating, and energy consumption by final energy consumption sectors, including buildings. Since the teams use world-class integrated assessment models, other sectors will be analyzed as well. The purpose of the document is to describe the needs of key Ukrainian ministries in modeling the reconstruction process. The scope of this document is limited to modeling energy consumption by the power and heat sectors, final energy consumption by buildings, and GHG emissions from these two sectors. The rest of this policy memo is organized as follows. After this introduction, Chapter 2 discusses key provisions of the reconstruction strategy with a focus on energy, buildings, heat supply, environment, and European integration aspirations. Section 3 provides an overview of recent developments and key decisions of the Government of Ukraine in the area of energy efficiency and decarbonization. Finally, Section 4 provides key suggestions on how PNNL and IEF can help the Government of Ukraine in developing strategic documents.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Carbon-Free Energy: How Much, How Soon?

The scientific consensus is that carbon emissions need to reach net zero by 2050 to stabilize a global temperature rise below 2 degrees C. Many studies have focused on reaching net zero in the power sector by 2050 and have posited the need for clean firm power sources. Resources such as nuclear, fossil generation with carbon capture and sequestration, or other technologies would be needed to complement variable wind and solar generation.

carbon dioxide↗

Nanotechnology for catalysis and solar energy conversion

This roadmap on Nanotechnology for Catalysis and Solar Energy Conversion focuses on the application of nanotechnology in addressing the current challenges of energy conversion: 'high efficiency, stability, safety, and the potential for low-cost/scalable manufacturing' to quote from the contributed article by Nathan Lewis. This roadmap focuses on solar-to-fuel conversion, solar water splitting, solar photovoltaics and bio-catalysis. It includes dye-sensitized solar cells (DSSCs), perovskite solar cells, and organic photovoltaics. Smart engineering of colloidal quantum materials and nanostructured electrodes will improve solar-to-fuel conversion efficiency, as described in the articles by Waiskopf and Banin and Meyer. Semiconductor nanoparticles will also improve solar energy conversion efficiency, as discussed by Boschloo et al in their article on DSSCs. Perovskite solar cells have advanced rapidly in recent years, including new ideas on 2D and 3D hybrid halide perovskites, as described by Spanopoulos et al 'Next generation' solar cells using multiple exciton generation (MEG) from hot carriers, described in the article by Nozik and Beard, could lead to remarkable improvement in photovoltaic efficiency by using quantization effects in semiconductor nanostructures (quantum dots, wires or wells). These challenges will not be met without simultaneous improvement in nanoscale characterization methods. Terahertz spectroscopy, discussed in the article by Milot et al is one example of a method that is overcoming the difficulties associated with nanoscale materials characterization by avoiding electrical contacts to nanoparticles, allowing characterization during device operation, and enabling characterization of a single nanoparticle. Besides experimental advances, computational science is also meeting the challenges of nanomaterials synthesis. The article by Kohlstedt and Schatz discusses the computational frameworks being used to predict structure–property relationships in materials and devices, including machine learning methods, with an emphasis on organic photovoltaics. The contribution by Megarity and Armstrong presents the 'electrochemical leaf' for improvements in electrochemistry and beyond. In addition, biohybrid approaches can take advantage of efficient and specific enzyme catalysts. These articles present the nanoscience and technology at the forefront of renewable energy development that will have significant benefits to society.

14 SOLAR ENERGY↗