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1. SunDown: Model-driven Per-Panel Solar Anomaly Detection for Residential Arrays

   https://doi.org/10.1145/3378393.3402257  

   Feng, Menghong; Bashir, Noman; Shenoy, Prashant; Irwin, David; Kosanovic, Dragoljub (June 2020, Proceedings of the 3rd ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS))

   null (Ed.)

   Solar arrays often experience faults that go undetected for long periods of time, resulting in generation and revenue losses. In this paper, we present SunDown, a sensorless approach for detecting per-panel faults in solar arrays. SunDown's model-driven approach leverages correlations between the power produced by adjacent panels to detect deviations from expected behavior, can handle concurrent faults in multiple panels, and performs anomaly classification to determine probable causes. Using two years of solar data from a real home and a manually generated dataset of solar faults, we show that our approach is able to detect and classify faults, including from snow, leaves and debris, and electrical failures with 99.13% accuracy, and can detect concurrent faults with 97.2% accuracy. 

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2. Solar energy management as an Internet of Things (IoT) application

   https://doi.org/10.1109/IISA.2017.8316460  

   Spanias, Andreas S. (August 2017, 2017 IEEE 8th International Conference on Information, Intelligence, Systems & Applications (IISA))

   Photovoltaic (PV) array analytics and control have become necessary for remote solar farms and for intelligent fault detection and power optimization. The management of a PV array requires auxiliary electronics that are attached to each solar panel. A collaborative industry-university-government project was established to create a smart monitoring device (SMD) and establish associated algorithms and software for fault detection and solar array management. First generation smart monitoring devices (SMDs) were built in Japan. At the same time, Arizona State University initiated research in algorithms and software to monitor and control individual solar panels. Second generation SMDs were developed later and included sensors for monitoring voltage, current, temperature, and irradiance at each individual panel. The latest SMDs include a radio and relays which allow modifying solar array connection topologies. With each panel equipped with such a sophisticated SMD, solar panels in a PV array behave essentially as nodes in an Internet of Things (IoT) type of topology. This solar energy IoT system is currently programmable and can: a) provide mobile analytics, b) enable solar farm control, c) detect and remedy faults, d) optimize power under different shading conditions, and e) reduce inverter transients. A series of federal and industry grants sponsored research on statistical signal analysis, communications, and optimization of this system. A Cyber-Physical project, whose aim is to improve solar array efficiency and robustness using new machine learning and imaging methods, was launched recently 

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3. A Novel Quotient Space Approach to Model-Based Fault Detection and Isolation: Theory and Preliminary Simulation Evaluation

   https://doi.org/10.1109/IROS51168.2021.9636026  

   Mao, Annie M.; Whitcomb, Louis L. (September 2021, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS))

   We report the development of novel fault detection and isolation (FDI) methods for model-based fault detection (MB-FD) and quotient-space fault isolation (QS-FI). This FDI approach performs MB-FD and QS-FI of single or multiple concurrent faults in plants and actuators simultaneously, without a priori knowledge of fault form, type, or dynamics. To detect faults, MB-FD characterizes deviation from nominal behavior using the plant velocity and plant and actuator parameters estimated by nullspace-based adaptive identification. To isolate (i.e. identify) faults, the QS-FI algorithm compares the estimated parameters to a nominal parameter class in progressively decreasing-dimensional quotient spaces of the parameter space. A preliminary simulation study of these proposed FDI methods applied to a three degree-of-freedom uninhabited underwater vehicle plant model shows their ability to detect as well as isolate faults for the cases of both single and multiple simultaneous faults and suggests the generalizability of the MB-FD and QS-FI approaches to any well-defined second-order plant and actuator model whose parameters enter linearly: a broad class of systems which includes aerial vehicles, marine vehicles, spacecraft, and robot arms. 

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4. Daytime thermal effects of solar photovoltaic systems: Field measurements

   https://doi.org/10.1063/5.0219179  

   Cannon, Daniel_Trevor; Vasel-Be-Hagh, Ahmad (September 2024, Journal of Renewable and Sustainable Energy)

   Numerous gigawatt-scale solar installations will emerge globally within the coming decades, with the global solar installations growing to several hundred million acres by 2050. Understanding such extensive canopies' thermal and mechanical characteristics is crucial to developing an efficient site selection strategy and effective technologies to minimize and mitigate their potential environmental effects. This article shares the findings of a preliminary experimental study that aims to develop this understanding. This scaled, six-month-long field measurement campaign includes five photovoltaic panels instrumented by multiple heat flux, temperature, and humidity sensors, accompanied by wind anemometers and several pyranometers and pyrgeometers to measure incoming and outgoing shortwave and longwave radiations. In this article, the authors only compare fully sunny (no clouds) and completely overcast episodes. The research revealed that a quantitative comparison of upward radiation emitted and reflected by the surface of the panels and the ground using a scaled setup would not represent a utility-scale solar plant. This study also revealed the significant effect of the panels on surface heat flux, surface temperature, and air temperature. The panels also appeared to affect near-surface vertical turbulent heat and momentum fluxes. These effects intensify with increased incoming solar irradiance. Aside from providing a preliminary understanding of the effect of solar panels on surface and near-surface thermal characteristics, this study offers a valuable pool of data for validating computational models and feeding their boundary conditions. We will follow-up on this study by investigating a megawatt-scale solar farm using weather towers and full-scale computational simulations. 

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5. Multi-year analysis of physical interactions between solar PV arrays and underlying soil-plant complex in vegetated utility-scale systems

   https://doi.org/10.1016/j.apenergy.2024.123227  

   Choi, Chong Seok; Macknick, Jordan; McCall, James; Bertel, Rebecca; Ravi, Sujith (July 2024, Applied Energy)

   Concerns over the land use changes impacts of solar photovoltaic (PV) development are increasing as PV energy development expands. Co-locating utility-scale solar energy with vegetation may maintain or rehabilitate the land's ability to provide ecosystem services. Previous studies have shown that vegetation under and around the panels may improve the performance of the co-located PV and that PV may create a favorable environment for the growth of vegetation. While there have been some pilot-scale experiments, the existence and magnitude of these benefits of vegetation has not been confirmed in a utility-scale PV facility over multiple years. In this study we use power output data coupled with microclimatic measurements in temperate climates to assess these potential benefits. This study combines multi-year microclimatic measurements to analyze the physical interactions between PV arrays and the underlying soil-vegetation system in three utility-scale PV facilities in Minnesota, USA. No significant cooling of PV panels or increased power production was observed in PV arrays with underlying vegetation. Fine soil particle fraction was the highest in soils within PV arrays with the vegetation which was attributable to the lowest wind speeds from the compounding suppression of wind by vegetation and PV arrays. Soil moisture and soil nutrient response to re-vegetation varied between PV facilities, which could be attributed to differing soil texture. No statistically significant vegetation-driven panel cooling was observed in this climate. This finding prompts a need for site-specific studies to identify contributing factors for environmental co-benefits in co-located systems. 

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