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DOE OSTI2025

Spatiotemporal Downscaling Model for Solar Irradiance Forecast Using Nearest-Neighbor Random Forest and Gaussian Process

Accurate solar photovoltaic (PV) capacity estimation requires high-resolution, site-specific solar irradiance data to account for localized variability. However, global datasets, such as the National Solar Radiation Database (NSRDB), provide regional averages that fail to capture the fine-scale fluctuations critical for large-scale grid integration. This limitation is particularly relevant in the context of increasing distributed energy resources (DERs) penetration, such as rooftop PV. Additionally, it is critical to the implementation of the U.S. Federal Energy Regulatory Commission (FERC) Order 2222, which facilitates DER participation in U.S. bulk power markets. To address this challenge, this study evaluates Nearest-Neighbor Random Forest (NNRF) and Nearest-Neighbor Gaussian Process (NNGP) models for spatiotemporal downscaling of global solar irradiance data. By leveraging historical irradiance and meteorological data, these models incorporate spatial, temporal, and feature-based correlations to enhance local irradiance predictions. The NNRF model, a machine-learning approach, prioritizes computational efficiency and predictive accuracy, while the NNGP model offers a level of interpretability and prediction uncertainty by numerically quantifying correlations and dependencies in the data. Model validation was conducted using day-ahead predictions. The results showed that the average Goodness of Fit (GoF) of the NNRF model of 90.61% across all eight sites outperformed the GoF of the NNGP of 85.88%. Additionally, the computational speed of NNRF was 2.5 times faster than the NNGP. Finally, the NNGP displayed polynomial scaling while the NNRF scaled linearly with increasing number of nearest neighbors. Additional validation of the model on five sites in Puerto Rico further confirmed the superiority of the NNRF model over the NNGP model. These findings highlight the robustness and computational efficiency of NNRF for large-scale solar irradiance downscaling, making it a strong candidate for improving PV capacity estimation and real-time electricity market integration for DERs.

Asiedu, Shadrack (ORCID:0009000646004826)↗

NASA NTRS2019

Photogrammetry-Based Analysis of the On-Orbit Structural Dynamics of the Roll-Out Solar Array

The Roll-Out Solar Array (ROSA) flight experiment was launched to the International Space Station (ISS) on June 3rd, 2017. ROSA is an innovative, lightweight solar array with a flexible substrate that makes use of the stored strain energy in its composite structural members to provide deployment without the use of motors. This paper will discuss the results of various structural dynamics experiments conducted on the ISS during the weeks following launch. Data gathered from instrumentation on the solar array wing during the experiments was previously compared with pre-flight predictions from two different Finite Element Modeling (FEM) efforts. In this paper, data generated from photogrammetry is compared with accelerometer data and used to extend previous conclusions. Whereas previous analyses were only able to track the accelerations of six discrete points on the structure and photovoltaic (PV) blanket of ROSA, the photogrammetry analysis makes available displacements for dozens of points distributed throughout the array. This larger data set makes it possible to compare higher-order PV blanket modes with FEM predictions, in addition to verifying conclusions reached using accelerometer data. The goal in this effort was to better understand the performance of ROSA and to improve modeling efforts for future designs of similar solar arrays.

Chamberlain, Matthew K.↗

DOE OSTI2025

PV Reference Cells for Outdoor Use: Stability Over Four Years of Deployment

Photovoltaic (PV) reference cells are frequently used to evaluate the performance of PV power plants. They provide a measure of irradiance that strongly correlates with the electrical output of PV modules, which makes them very useful for detecting short-term anomalies or long-term degradation in PV power plant output. One very important quality is long-term stability. This report presents observations about the stability of a set of 22 commercial reference cells that have been in continuous operation for a period of four years at the Solar Radiation Research Laboratory (SRRL) site at the National Renewable Energy Laboratory (NREL). The 22 reference cells at the SRRL represent 10 different models from 6 manufacturers.

14 SOLAR ENERGY↗

DOE OSTI2024

Solar Photovoltaic (PV) Damage Assessment After Typhoon Mawar: Findings and Recommendations for Resilient PV on Guam

A team from the National Renewable Energy Laboratory (NREL) visited Guam in August 2023 to assess failure modes of solar photovoltaic (PV) systems after Typhoon Mawar and to provide recommendations to increase the resilience of PV systems on Guam. The team visited 30 systems: commercial and utility scale, and rooftop and ground-mounted. The team observed systems with no apparent damage, as well as systems that were completely lost. Systems fared very well overall. The average failure rate of rooftop systems was 18%, with a median failure rate of 2%, meaning the few systems that suffered total loss pulled up the average. Only eight 8 of the 25 rooftop systems suffered more than 5% damage. All ground-mounted systems suffered less than 0.5% damage, aside from a carport that lost 16% of its modules. PV systems at Andersen Air Force Base suffered 5% damage on average, with a median system failure of 0.6%. In almost all cases, failures were the result of: (1) Inadequate clamping of the module frame to the mount, (2) Module mounting clamps rotating out of underlying support rail (i.e., T-bolt that rotates free at less than 60 degrees of rotation), (3) An object hitting the panel resulting in a fracture, and in some cases leading to a cascading failure of several more panels, and (4) Excessive tilt angle (in Guam, greater than 5 degrees can be a risk due to wind speed, and power production trade-offs are insignificant).

14 SOLAR ENERGY↗

NASA NTRS1993

System performance predictions for Space Station Freedom's electric power system

Space Station Freedom Electric Power System (EPS) capability to effectively deliver power to housekeeping and user loads continues to strongly influence Freedom's design and planned approaches for assembly and operations. The EPS design consists of silicon photovoltaic (PV) arrays, nickel-hydrogen batteries, and direct current power management and distribution hardware and cabling. To properly characterize the inherent EPS design capability, detailed system performance analyses must be performed for early stages as well as for the fully assembled station up to 15 years after beginning of life. Such analyses were repeatedly performed using the FORTRAN code SPACE (Station Power Analysis for Capability Evaluation) developed at the NASA Lewis Research Center over a 10-year period. SPACE combines orbital mechanics routines, station orientation/pointing routines, PV array and battery performance models, and a distribution system load-flow analysis to predict EPS performance. Time-dependent, performance degradation, low earth orbit environmental interactions, and EPS architecture build-up are incorporated in SPACE. Results from two typical SPACE analytical cases are presented: (1) an electric load driven case and (2) a maximum EPS capability case.

Kerslake, Thomas W.↗

DOE OSTI2025

Unified Universal Control and Coordination of Inverter-Based Resources, and Validation for a PV + Battery Hybrid Plant

As renewable energy deployment grows, hybrid power plants (HPPs) combining photovoltaic (PV) and battery systems must evolve to offer both energy and grid stability services. These systems typically include a mix of grid-following (GFL) and grid-forming (GFM) inverters, presenting unique coordination and control challenges. This Department of Energy–funded project developed and validated a Unified Universal Control and Coordination (UUCC) framework for such PV + battery hybrid plants, enabling seamless and stable operation, including ultrafast black start, autonomous synchronization, and robust frequency and voltage regulation, under different grid conditions. The project significantly advanced the understanding of inverter-based resource (IBR) control by developing and validating three complementary system-level approaches for hybrid GFL/GFM operation: 1. A combined Virtual Resistance (VR)-based GFL and Virtual Oscillator Control (VOC)-based GFM method, where each inverter type is governed by a specialized control strategy. Together, these achieve stable, fast-response coordination, eliminating inrush current and enabling smooth black start and grid synchronization across a wide range of grid strengths. 2. A Deadbeat-based UUCC strategy, which uses discrete-time, switching-cycle-level control for both GFL and GFM inverters. This approach replaces traditional PI/PLL control with a control parameter-free, high-bandwidth framework that supports stable LVRT and instantaneous synchronization under all conditions. 3. A benchmark comparison with Siemens’ commercial GFM microgrid controller, which provided a fast baseline platform. The commercial approach decoupled v & f control was implemented on a commercial microgrid controller.The baseline commercial benchmark helped highlight superior transient response and black start performance offered by the deadbeat and VOC approaches. These technical contributions offer substantial improvements over conventional inverter control schemes, which often rely on slow phase-locked loop (PLL)-based synchronization, require careful control parameters tuning, and prone to unstable in weak grids with GFL inverters and in stiff grid with GFM inverters therefore challenging for hybrid GFL+GFM under all grid conditions. The deadbeat-based UUCC framework enables simpler, faster, and more robust operation of hybrid IBR systems using wide-bandgap (WBG) devices such as SiC power semiconductors. The rapid expansion of hybrid distributed energy resources (DERs), including residential and commercial PV-BESS installations such as Tesla Powerwall, PV with vehicle-to-grid (V2G) capability, and other integrated configurations, presents complex operational challenges for medium-voltage radial distribution feeders. These networks are subject to frequent disturbances such as faults, switching operations, rapid reclosing sequences, and feeder reconfigurations, all of which introduce dynamic stress on IBRs. In addition, planned feeder segmentation and deliberate islanding for resilience will require DERs that can autonomously perform blackstart, establish voltage and frequency references, and resynchronize with the main grid. The advanced deadbeat-based UUCC control and blackstart functionalities developed in this project directly address these requirements, enabling decentralized and autonomous operation of inverter-dominated DERs in distribution systems under a wide range of fault and reconfiguration scenarios. From a public benefit perspective, these innovations enable more reliable and cost-effective integration of renewable energy into distribution networks. The ability to autonomously black start and stabilize grids under varying grid conditions support accelerates recovery from outages and support decentralized resilient energy systems. By reducing system complexity and improving performance, this project lays critical groundwork for future inverter-dominated power grids that are clean, reliable, and accessible to all.

14 SOLAR ENERGY↗

DOE OSTI2025

Parallel derivative-free optimization for simulation-based design of behind-the-meter energy systems

In this work, the integrated design and dispatch of behind-the-meter or distributed resources (e.g. stationary battery storage and solar PV generation) is considered. A simulation-based framework is employed, generating high-fidelity results with closed-loop predictive control at a fine resolution, at the expense of high computational cost (several minutes to a few hours per design point). To address this challenge, parallel derivative-free design methods are considered. Four methods are compared, including state-of-the-art surrogate-based methods (Radial-Basis Functions and Gaussian processes) and sampling strategies, an evolutionary-based method, and a simple sequential grid refinement method. As a case study, two types of design problem with increasing complexity are considered, namely, the design of behind-the-meter resources (three design variables) and the inclusion of grid capacity (four design variables). The second yields a constrained design problem for which violations can only be determined after solving the computationally expensive simulation. For the three-dimensional case, all methods present a good performance, achieving a solution within 1% of the optimum after the first iteration, with the sequential grid refinement exhibiting the fastest convergence and achieving the best final objective value. This indicates that the parallel evaluation of multiple sampling points may be more important than the choice of method for small decision spaces. For the four-dimensional constrained case, the Genetic Algorithm presents the best tradeoff between performance and computational effort, while the rough objective function terrain generated by constraint violation penalties reduces the performance of surrogate-based methods. Contour plots with flat regions indicate flexibility in the optimal design and highlight the importance of characterizing the solution space.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2020

Potential vorticity structure of Titan's polar vortices from Cassini CIRS observations

The Cassini mission has provided the best opportunity to date to extensively study the seasonal variation in Titan’s atmosphere, with observations spanning almost half a Titan year (𝐿𝑠 = 293 − 93°). An important feature in the Titan middle-atmosphere is the formation of a polar vortex. Observations have shown that an initially well-developed northern vortex enriched with trace gas species gradually breaks down after spring equinox as a new vortex emerges in southern winter. Here we use Cassini CIRS observations to derive the temperature and composition of the middle-atmosphere. We use the gradient wind equation to first estimate the mean zonal winds, and then the Potential Vorticity (PV) throughout Titan’s atmosphere over the timespan of the Cassini mission. PV is a useful diagnostic quantity for studying the dynamics of polar vortices because it is materially conserved for adiabatic and frictionless flows, and can be inverted to find all other dynamical fields. Our results show the formation of a strong zonal jet in the winter hemisphere, with wind velocities reaching 220 m/s, which is consistent with previous studies. An annular PV structure is also observed over the winter poles, whereby a ring of PV encircles a local minima over the pole. Such distributions are often found to be unstable without a restoring force, yet they are seen here in numerous observations in both the northern and southern hemispheres. A comparison with the annular Martian vortices shows that latent heat release from condensation or subsidence-induced adiabatic heating may explain the origin and stability of the annulus. Finally, we investigate the evolution of the size of the vortices and the role of strong PV gradients as a dynamical mixing barrier for trace gas species across the vortex edge. We find that longer lived gases are less confined to the vortex than those with shorter photochemical lifetimes.

Conor Andrew Nixon↗

DOE OSTI2025

Suppression of phase separation in AlGaInAs compositionally graded buffers for 1550 nm photovoltaic converters on GaAs

We investigate strategies to suppress phase separation and reduce threading dislocation density (TDD) in AlGaInAs compositionally graded buffers (CGBs) that span the lattice constant range from GaAs to InP. Combining the results from high resolution x-ray diffraction, cathodoluminescence, transmission electron microscopy, and photovoltaic device measurements, we correlate the choices of epitaxial growth conditions with the defect structure of the CGBs and subsequent device performance. Both the use of substrates with high misorientation off (100) toward the (111)A plane and Zn doping instead of Si doping are shown to suppress phase separation and reduce TDD. We demonstrate a 0.74 eV GaInAs device grown on a GaAs substrate offcut 19.5° toward (111)A using a Zn-doped AlGaInAs CGB with TDD = 3.5 ± 0.2 × 10 6 cm -2 that has a bandgap-open circuit voltage offset of only 0.434 V measured under the AM1.5G solar spectrum. We characterized this device under high-intensity irradiance from a 1570 nm laser and measured a 31.9% peak laser power conversion efficiency at 3.6 W/cm 2 irradiance. These results provide a roadmap to the manufacture of laser- and thermal-power conversion devices with the performance and cost-effectiveness needed to drive adoption of these technologies at scale.

14 SOLAR ENERGY↗

DOE OSTI2024

A Neural Network-Based Power Mismatch Elimination Strategy for Integrated Solar and ESS AC/DC Systems (MARS)

The multiport autonomous reconfigurable solar power plant (MARS) is a promising concept for the integration of photovoltaic (PV) and energy storage system (ESS) to the transmission ac grid and a high-voltage direct current (HVdc) link. The presence of PV and ESS in each arm of the MARS results in uneven distribution of active power among different submodules (SMs), thereby leading to unbalanced SM capacitor voltages and potentially compromising the system stability. Moreover, in the case of partial shadings, shaded PV SMs will suffer from decreased power injections causing power mismatch in the MARS system. To address this issue, a neural-network-based power mismatch elimination (NNPME) strategy is proposed in this article. The proposed NNPME strategy optimizes ESS usage and leverages both dc and ac circulating currents to facilitate power transfer among the SMs, arms, and phases of the MARS system. Simulation and control hardware-in-the-loop (cHIL) experiments demonstrate the effectiveness of the proposed NNPME strategy. Compared with the traditional approaches, the proposed NNPME strategy can significantly enhance system efficiency and ensure stable and continuous operation, even in the presence of uneven power distribution within the MARS system.

14 SOLAR ENERGY↗

NASA NTRS1992

Reduction and analysis of seasons 15 and 16 (1991 - 1992) Pioneer Venus radio occultation data and correlative studies with observations of the near-infrared emission of Venus

Radio occultation experiments, and radio astronomical observations have suggested that significant variations (both spatial and temporal) in the abundances of sulfur-bearing gases are occurring below the Venus cloud layers. In addition, recent Near Infra-Red images of the nightside of Venus revealed large-scale features which sustain their shape over multiple rotations (the rotation periods of the features are 6.0 +/- 0.5 days). Presumably, the contrast variations in the NIR images are caused by variations in the abundance of large particles in the cloud deck. If these particles are composed of liquid sulfuric acid, one would expect a strong anticorrelation between regions with a high abundance of sulfuric acid vapor, and regions where there are large particles. One technique for monitoring the abundance and distribution of sulfuric acid vapor (H2SO4) at and below the main Venus cloud layer (altitudes below 50 km) is to measure the 13-cm wavelength opacity using Pioneer Venus Orbiter Radio Occultation Studies (PV-ORO). We are working to characterize variations in the abundance and distribution of subcloud H2SO4(g) in the Venus atmosphere by using a number of 13-cm radio occultation measurements conducted with the Pioneer Venus Orbiter near the inferior conjunction of 1991. When retrieved, the vertical profiles of the abundance of H2SO4(g) will be compared and correlated with NIR images of the night side of Venus made during the same period of time. Hopefully, the combination of these two different types of data will make it possible to constrain or identify the composition of the large particles causing the features observed in the NIR images. Considered on their own, however, the parameters retrieved from the radio occultation experiments are valuable science products.

Jenkins, Jon M.↗

NASA NTRS1990

Distribution of tessera terrain on Venus - Prediction for Magellan

Tessera terrain is the dominant tectonic unit in the northern hemisphere of Venus and is characterized by complex sets of intersecting structural trends and distinctive radar properties due to a high degree of meter and sub-meter scale (5 cm to 10 m) roughness. Based on these distinctive radar properties, a prediction of the global distribution of tessera can be made using Pioneer Venus (PV) reflectivity and roughness data. Where available, Benera 15/16 and Arecibo images and PV diffuse scattering data were used to evaluate the prediction. From this assessment, it is concluded that most of the regions with prediction values greater than 0.6 (out of 1) are likely to be tessera, and are almost certain to be techonically deformed.

Bindschadler, D. L.↗

NASA NTRS2009

Design of a Glenn Research Center Solar Field Grid-Tied Photovoltaic Power System

The NASA Glenn Research Center (GRC) designed, developed, and installed, a 37.5 kW DC photovoltaic (PV) Solar Field in the GRC West Area in the 1970s for the purpose of testing PV panels for various space and terrestrial applications. The PV panels are arranged to provide a nominal 120 VDC. The GRC Solar Field has been extremely successful in meeting its mission. The PV panels and the supporting electrical systems are all near their end of life. GRC has designed a 72 kW DC grid-tied PV power system to replace the existing GRC West Area Solar Field. The 72 kW DC grid-tied PV power system will provide DC solar power for GRC PV testing applications, and provide AC facility power for all times that research power is not required. A grid-tied system is connected directly to the utility distribution grid. Facility power can be obtained from the utility system as normal. The PV system is synchronized with the utility system to provide power for the facility, and excess power is provided to the utility for use by all. The project transfers space technology to terrestrial use via nontraditional partners. GRC personnel glean valuable experience with PV power systems that are directly applicable to various space power systems, and provide valuable space program test data. PV power systems help to reduce harmful emissions and reduce the Nation s dependence on fossil fuels. Power generated by the PV system reduces the GRC utility demand, and the surplus power aids the community. Present global energy concerns reinforce the need for the development of alternative energy systems. Modern PV panels are readily available, reliable, efficient, and economical with a life expectancy of at least 25 years. Modern electronics has been the enabling technology behind grid-tied power systems, making them safe, reliable, efficient, and economical with a life expectancy of at least 25 years. The report concludes that the GRC West Area grid-tied PV power system design is viable for a reliable, maintenance free, long life power system that is of significant value to NASA and the community.

Eichenberg, Dennis J.↗

NASA NTRS2000

Power System Options Evaluated for the Radiation and Technology Demonstration Mission

The Radiation and Technology Demonstration (RTD) Mission is under joint study by three NASA Centers: the NASA Johnson Space Center, the NASA Goddard Space Flight Center, and the NASA Glenn Research Center at Lewis Field. This Earth-orbiting mission, which may launch on a space shuttle in the first half of the next decade, has the primary objective of demonstrating high-power electric thruster technologies. Secondary objectives include better characterization of Earth's Van Allen trapped-radiation belts, measurement of the effectiveness of the radiation shielding for human protection, measurement of radiation effects on advanced solar cells, and demonstration of radiation-tolerant microelectronics. During the mission, which may continue up to 1 year, the 2000-kg RTD spacecraft will first spiral outward from the shuttle-deployed, medium-inclination, low Earth orbit. By the phased operation of a 10-kW Hall thruster and a 10-kW Variable Specific Impulse Magneto-Plasma Rocket, the RTD spacecraft will reach a low-inclination Earth orbit with a radius greater than five Earth radii. This will be followed by an inward spiraling orbit phase when the spacecraft deploys 8 to 12 microsatellites to map the Van Allen belts. The mission will conclude in low Earth orbit with the possible retrieval of the spacecraft by the space shuttle. A conceptual RTD spacecraft design showing two photovoltaic (PV) array wings, the Hall thruster with propellant tanks, and stowed microsatellites is presented. Early power system studies assessed five different PV array design options coupled with a 120-Vdc power management and distribution system (PMAD) and secondary lithium battery energy storage. Array options include (1) state-of-the-art 10-percent efficient three-junction amorphous SiGe thin-film cells on thin polymer panels deployed with an inflatable (or articulated) truss, (2) SCARLET array panels, (3) commercial state-of-the-art, planar PV array rigid panels with 25-percent efficient, three-junction GaInP2/GaAs/Ge solar cells, (4) rigid panels with 25-percent efficient, three-junction GaInP2/GaAs/Ge solar cells, in a 2 -concentrator trough configuration, and (5) thin polymer panels with 25-percent efficient, three-junction GaInP2/GaAs/Ge solar cells deployed with an inflatable (or articulated) truss. To assess the relative merits of these PV array design options, the study group developed a dedicated Fortran code to predict power system performance and estimate system mass. This code also modeled Earth orbital environments important for accurately predicting PV array performance. The most important environmental effect, solar cell radiation degradation, was calculated from electron-proton fluence input from the industry standard AE8/AP8 trapped radiation models and the concept of damage equivalence. Power systems were sized to provide 10 kW of thruster power and approximately 1 kW of spacecraft power at end of life. Of the five PV array design options, the option 1 (thin-film cells) power system was the most massive 590 kg, whereas the option 4 (trough concentrator) power system was the lightest 260 kg. Arguably, the lowest cost would come from the option 3 (commercial array panels) power system with an acceptable, albeit greater, system mass of 320 kg. Predicted power system performance during the spiral-out mission phase is shown the preceding graph for the option 5 (flexible-panel) array. From the results, the radiation-induced power loss over time is evident as the spacecraft slowly spirals outward through the trapped proton belt. The importance of the spiral trip time is also evident in the two curves representing 74-day and 182-day spiral-out periods. The longer spiral time introduces a beginning-of-life power oversizing penalty greater than 1 kW. Future studies will analyze power system performance and mass with a 50-Vdc power management and distribution architecture favorable to the VASIMR thruster and longer missions.

Kerslake, Thomas W.↗

DOE OSTI2025

A Two-Stage Approach for PV Inverter Engagement in Power Factor Correction and Voltage Regulation

The rapid integration of distributed energy resources, like solar photovoltaics (PVs), can lead to overvolt-age challenges due to reverse power flow and a noticeable decrease in power factor at the substation interface. While existing literature extensively explores utilizing smart inverter capabilities for reactive power flexibility using a volt-var curve (VVC), obtaining time-varying operating points of such curves in real-time is challenging due to computational demands and communication requirements. Similarly, employing optimization-based approaches for reactive power control and active voltage regulation in large-scale distribution feeders is difficult due to the complexity of the problem and the challenges in effectively engaging customer-owned resources. This paper proposes a two-stage strategy to harness smart inverters for reactive power support. The first stage formulates short-term planning by optimally designing VVCs (on a daily or hourly basis) for large-scale solar PVs based on projected system needs and communicating optimal curves to smart inverters in advance. Subsequently, the second stage employs a transactive-based method to involve customer-owned PVs for reactive power support, effectively enhancing overall system performance and addressing real-time demands. In conclusion, the efficacy of this approach will be demonstrated using real-world distribution circuits provided by Vermont Electric Power Company (VELCO) and Vermont Electric Cooperative (VEC).

Poudel, Shiva [Pacific Northwest National Laborato↗

DOE OSTI2024

Leveraging PHIL for Inverter Functionality Requirement Evaluation to Ensure a Reliable Grid

This presentation showcases NREL's ongoing research on advanced Multi-point Power Hardware-in-the-Loop (PHIL) systems, enabling comprehensive evaluation of interoperability, stability, and wide-area stability in complex power grids. Key features include high-power PHIL capabilities, seamless PHIL Interfaces for effortless Grid-Following (GFL) and Grid-Forming (GFM) mode switching, and advanced multi-domain PHIL/Controller Hardware-in-the-Loop (CHIL) capabilities for evaluating diverse technology mixes, facilitating rigorous testing and validation of emerging power systems for reliable integration, enhanced resilience, and optimal performance.

lab capabilities↗

DOE OSTI2026

PVWatts Calculator [Slides]

This slide deck is an introduction to PV Watts and how users can employ it. NREL's PVWatts® Calculator estimates the energy production of grid-connected photovoltaic (PV) energy systems.

14 SOLAR ENERGY↗

DOE OSTI2024

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↗