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Photosynthetically Active Radiation or PAR is the part of the electromagnetic spectrum that drives photosynthesis in plants. Measuring PAR is an important task in farming, plant biology and environmental science. This article reviews the theoretical basis and various practical approaches for measuring PAR. This review also describes the principles of operation and the technology behind different types of PAR sensors. Comparisons between commercially-available PAR sensors and sensors that are in the prototyping stage are provided to give the reader a quick overview of the technologies available for PAR measurement. The aim of this review is threefold: 1) to serve as an introduction to the topic of PAR sensing for researchers new to the field, 2) to provide list of options for readers seeking to use commercially-available PAR sensors and 3) to give the theoretical foundation and technical information to those readers that seek to develop custom PAR sensing solutions.

Abstract Plant growth under spectrally-enriched low light conditions leads to adjustment in the relative abundance of the two photosystems in an acclimatory response known as photosystem stoichiometry adjustment. Adjustment of photosystem stoichiometry improves the quantum efficiency of photosynthesis but how this process perceives light quality changes and how photosystem amount is regulated remain largely unknown. By using a label-free quantitative mass spectrometry approach in Arabidopsis here we show that photosystem stoichiometry adjustment is primarily driven by the regulation of photosystem I content and that this forms the major thylakoid proteomic response under light quality. Using light and redox signaling mutants, we further show that the light quality-responsive accumulation of photosystem I gene transcripts and proteins requires phytochrome B photoreceptor but not plastoquinone redox signaling as previously suggested. In far-red light, the increased acceptor side limitation might deplete active photosystem I pool, further contributing to the adjustment of photosystem stoichiometry.

Solar generation has increased rapidly worldwide in recent years and it is projected to continue to grow exponentially. A problem exists in that the increase in solar energy generation will increase the probability of grid disturbances. This study focuses on analyzing the grid disturbances caused by the massive integration to the transmission line of utility-scale solar energy loaded to the balancing authority high-voltage transmission lines in four regions of the United States electrical system: (1) California, (2) Southwest, (3) New England, and (4) New York. Statistical analysis of equality of means was carried out to detect changes in the energy balance and peak power. Results show that when comparing the difference between hourly net generation and demand, energy imbalance occurs in the regions with the highest solar generation: California and Southwest. No significant difference was found in any of the four regions in relation to the energy peaks. The results imply that regions with greater utility-level solar energy adoption must conduct greater energy exchanges with other regions to reduce potential disturbances to the grid. It is essential to bear in mind that as the installed solar generation capacity increases, the potential energy imbalances created in the grid increase.

Predictive maintenance models are thought to be a reliable alternative to costly on-site maintenance techniques in the solar photovoltaic industry. They provide the owners with a third-party system to objectively diagnose and prevent failures in the system or any of its components. These models depend on data acquisition and analysis to compare the estimated performance with the actual energy production of the system, to conclude on the systems' health status. Ambient temperature, cell temperature, and solar irradiance forecasting are crucial parameters in predictive maintenance models’ formulation. These parameters represent the input variables to the model and define its efficiency to a great extent. Nonetheless, the current approaches to predict weather-related parameters have a high dependency on data availability and, in some cases, sensibility to the location where they are being measured. Forecasting climate parameters using neighboring weather stations seems to be a promising option to tackle the cost of on-site sensing and data availability, however, the scarcity of applications of specialized forecasting methods to predict solar irradiance and temperature (cell and ambient) for such applications represents an obstacle. This document will present a review of the state-of-the-art comparing the techniques to forecast solar irradiance, and ambient and cell temperature, and their relationship with predictive maintenance models, by acquiring data from weather stations. This review evaluates the suitability of the models for solar photovoltaic applications, taking on their forecasting horizon, computational cost, and improvement opportunities to propose a framework for future work in the photovoltaic industry.

Selecting the correct weather forecasting technique is a crucial task when planning an efficient solar energy generation system. Estimating accurate solar photovoltaic systems power output depends on the correct modeling of solar irradiance and ambient temperature, evidencing the need for a framework to select the correct technique to forecast these parameters. This paper presents a review of the forecasting methods to predict solar irradiance and ambient temperature, considering the sensitivity to the forecasting horizon. The methodology includes estimating an interval for ambient temperature and solar irradiance by using the Mean Absolute Error as the percentage of variation in these parameters. To provide context, the study considers best-case and worst-case scenarios for four cities, estimating the power output for a sample array and analyzing the differences between the cases. The power output estimation of the PV array varied between 36% and 50% (on average) for the short-term prediction, and 54% to 95% for the long-term. The changes in the location produced an average variation of 43% in terms of power production, and up to 187% in economic value (USD) for the short term, and 44.5% and 187% for the long term. The results suggest a marked sensitivity to the variation in the forecasting horizon and significance with regards to location selection (considering the changes in solar irradiation and the cost of electricity).

Abstract Background Light exposure induces oxidative stress, which contributes to ocular diseases of aging. Blue light provides a model for light-induced oxidative stress, lipid peroxidation and retinal degeneration in Drosophila melanogaster. In contrast to mature adults, which undergo retinal degeneration when exposed to prolonged blue light, newly-eclosed flies are resistant to blue light-induced retinal degeneration. Here, we sought to characterize the gene expression programs induced by blue light in flies of different ages to identify neuroprotective pathways utilized by photoreceptors to cope with light-induced oxidative stress. Results To identify gene expression changes induced by blue light exposure, we profiled the nuclear transcriptome of Drosophila photoreceptors from one- and six-day-old flies exposed to blue light and compared these with dark controls. Flies were exposed to 3 h blue light, which increases levels of reactive oxygen species but does not cause retinal degeneration. We identified substantial gene expression changes in response to blue light only in six-day-old flies. In six-day-old flies, blue light induced a neuroprotective gene expression program that included upregulation of stress response pathways and downregulation of genes involved in light response, calcium influx and ion transport. An intact phototransduction pathway and calcium influx were required for upregulation, but not downregulation, of genes in response to blue light, suggesting that distinct pathways mediate the blue light-associated transcriptional response. Conclusion Our data demonstrate that under phototoxic conditions, Drosophila photoreceptors upregulate stress response pathways and simultaneously, downregulate expression of phototransduction components, ion transporters, and calcium channels. Together, this gene expression program both counteracts the calcium influx resulting from prolonged light exposure, and ameliorates the oxidative stress resulting from this calcium influx. Thus, six-day-old flies can withstand up to 3 h blue light exposure without undergoing retinal degeneration. Developmental transitions during the first week of adult Drosophila life lead to an altered gene expression program in photoreceptors that includes reduced expression of genes that maintain redox and calcium homeostasis, reducing the capacity of six-day-old flies to cope with longer periods (8 h) of light exposure. Together, these data provide insight into the neuroprotective gene regulatory mechanisms that enable photoreceptors to withstand light-induced oxidative stress.

Neuroscience: Vision is stressful for old flies Paradoxically, light is essential for vision, yet it also induces stress that damages the sensitive cells in the eye. Vikki Weake and her team at Purdue University examined how exposure to blue light causes damage to the retina in fruit flies. Blue light causes death of photoreceptors, the light-sensing neurons. Surprisingly, very young flies are resistant to blue light. Increasing levels of a single protein, Cytochrome-b5, mimicked youthful resilience in older flies. Cytochrome-b5 is central to an ancient cellular defense system that protects membranes from oxidative damage. With expansive sensory membranes containing specialized lipids, photoreceptors are especially sensitive to membrane lipid peroxidation, an emerging final common pathway for cell death in aging and disease. Research into preventing lipid peroxidation might help to develop therapies for age-related diseases such as age-related macular degeneration.

A programmable optical stimulator for Drosophila eyes is presented. The target application of the stimulator is to induce retinal degeneration in fly photoreceptor cells by exposing them to light in a controlled manner. The goal of this work is to obtain a reproducible system for studying age-related changes in susceptibility to environmental ocular stress. The stimulator uses light emitting diodes and an embedded computer to control illuminance, color (blue or red) and duration in two independent chambers. Further, the stimulator is equipped with per-chamber light and temperature sensors and a fan to monitor light intensity and to control temperature. An ON/OFF temperature control implemented on the embedded computer keeps the temperature from reaching levels that will induce the heat shock stress response in the flies. A custom enclosure was fabricated to house the electronic components of the stimulator. The enclosure provides a light-impermeable environment that allows air flow and lets users easily load and unload fly vials. Characterization results show that the fabricated stimulator can produce light at illuminances ranging from 0 to 16000 lux and power density levels from 0 to 7.2 mW/cm2 for blue light. For red light the maximum illuminance is 8000 lux which corresponds to a power density of 3.54 mW/cm2. The fans and the ON/OFF temperature control are able to keep the temperature inside the chambers below 28.17 °C. Experiments with white-eye male flies were performed to assess the ability of the fabricated simulator to induce blue light-dependent retinal degeneration. Retinal degeneration is observed in flies exposed to 8 h of blue light at 7949 lux. Flies in a control experiment with no light exposure show no retinal degeneration. Flies exposed to red light for the similar duration and light intensity (8 h and 7994 lux) do not show retinal degeneration either. Hence, the fabricated stimulator can be used to create environmental ocular stress using blue light.

Within the United States solar energy industry, there is a general motto of “set it and forget it” with solar energy. This notion is derived from much of the research and reliability studies around the photovoltaic (PV) panels themselves, not necessarily the PV system as a whole (including the inverter and other components). This implies that maintenance and regular monitoring is not needed. Yet many things can go wrong to cause the actual performance to deviate from the expected performance. If failures and/or unanticipated degradation issues go undetected, they will lead to reduced energy generation (and associated electricity credits) and/or potential loss of component warranty because of manufacturer turnover. Given the size of the problem and gaps with current solutions, the authors propose that PV system owners need an unbiased third-party off-the-shelf system-level predictive maintenance tool to optimize return-on-investment and minimize time to warranty claim in PV installations. This paper reviews the literature highlighting challenges, current approaches, and opportunities for PV predictive maintenance. The paper concludes with a call to action for establishing a collaborative agenda toward prioritizing PV predictive maintenance.