Energy efficiency analysis of 1 MW PV farm mounted on fixed and tracking systems

Walichnowska, Patrycja; Mroziński, A.; Idzikowski, Adam; Fröhlich, Siegmund Richard

doi:10.17512/bozpe.2022.11.09

Cited by 2 publications

(4 citation statements)

References 9 publications

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“…At Km = 683.002 lm•W -1 [20], by equations ( 5) and ( 8) Kph = 406.480 phlm•W -1 and κ = 1.68469 phlux•lux -1 , which fully defines phytocandela, phytolumen and phytolux allowing measurements by the cheapest and the most available deviceslux-meters. For rough measurements in solar energetics, which is a promising technology in Ukraine and the world [25][26][27][28][29][30][31][32][33][34][35], we can use the same approach applying the corresponding spectrums in full ranges. Also, we can see that candela cannot be a universal physical value.…”

Section: Resultsmentioning

confidence: 99%

Problems of standardising illumination for plants in greenhouses and green structures

Tkachenko

Mileikovskyi

Moskvitina

et al. 2023

22nd International Scientific Conference Engineering for Rural Development Proceedings

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Today greenhouses are transformed. In the middle of the past century, they were almost glazing buildings above the ground. Due to the development of planting technologies, including mats or trays with substratum, aero – and hydroponics, etc., greenhouses now can be anywhere, including underground. This gives impetus for urban agriculture with optimal logistics (growing near consuming). Indoor green structures become more and more popular. The illumination of them is very important because plants lose decorative properties in unfavourite conditions. At the beginning of this century, there was an analysis of a lot of failed attempts to create winter gardens on underground floors. The illumination was calculated successfully by today’s norms, but the plants withered. This is because the norms were developed for natural-illumination greenhouses. Usually, the illumination is measured in lux or μmol/day. The first unit is weighted by wavelength according to the people’s eyes sensitivity. The second one accumulates all photons. But the plants have another photosynthetic activity curve. They use two photosynthetic substances – chlorophyll and beta-carotenoid (active on the green light). The chlorophyll changes its absorption curves dependent on solvent presence (a and b). This allows some variability for adapting to the light spectrum, which is used by water plants. Thus, both units do not apply to artificial illumination. In this work, we analyse the curves of solar and phytolamp spectrums, averaged sensibility and spectral luminous efficiency for photopic vision. Integration of the curves allows recalculation of the lux-meter reading to the equivalent solar illumination or the last one to the phytolamp power. We propose a new unit system – phytocandela-phytolumen-phytolux – according to the photosynthesis efficiency curve that is numerically equal to candela-lumen-lux under sunlight. This shows that lux may not be a base unit because it is related to a single biological species but not a physical property.

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Section: Resultsmentioning

confidence: 99%

Problems of standardising illumination for plants in greenhouses and green structures

Tkachenko

Mileikovskyi

Moskvitina

et al. 2023

22nd International Scientific Conference Engineering for Rural Development Proceedings

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“…AI also offers an opportunity here to support research, monitoring, inference and prediction, but this requires its integrated industrial-scale application in energy companies. The costs of adapting the electricity system to distributed energy (including PV installations) will be enormous, and the process of upgrading the grid itself will be spread over many years and be adaptive, as the number of PV installations will increase, but the population itself will tend to decrease and the population distribution will change-towards migration to larger centers [4,5].…”

Section: Limitations Of Own Studiesmentioning

confidence: 99%

“…The use of AI in the PV industry should be approached globally. This field can be used not only in the area indicated in this article, but also in other stages [4,5,[44][45][46]]:…”

Section: Direction For Further Studiesmentioning

confidence: 99%

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Machine Learning- and Artificial Intelligence-Derived Prediction for Home Smart Energy Systems with PV Installation and Battery Energy Storage

Rojek,

Mikołajewski,

Mroziński

et al. 2023

Energies

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Overview: Photovoltaic (PV) systems are widely used in residential applications in Poland and Europe due to increasing environmental concerns and fossil fuel energy prices. Energy management strategies for residential systems (1.2 million prosumer PV installations in Poland) play an important role in reducing energy bills and maximizing profits. Problem: This article aims to check how predictable the operation of a household PV system is in the short term—such predictions are usually made 24 h in advance. Methods: We made a comparative study of different energy management strategies based on a real household profile (selected energy storage installation) based on both traditional methods and various artificial intelligence (AI) tools, which is a new approach, so far rarely used and underutilized, and may inspire further research, including those based on the paradigm of Industry 4.0 and, increasingly, Industry 5.0. Results: This paper discusses the results for different operational scenarios, considering two prosumer billing systems in Poland (net metering and net billing). Conclusions: Insights into future research directions and their limitations due to legal status, etc., are presented. The novelty and contribution lies in the demonstration that, in the case of domestic PV grids, even simple AI solutions can prove effective in inference and forecasting to support energy flow management and make it more predictable and efficient.

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Energy efficiency analysis of 1 MW PV farm mounted on fixed and tracking systems

Cited by 2 publications

References 9 publications

Problems of standardising illumination for plants in greenhouses and green structures

Problems of standardising illumination for plants in greenhouses and green structures

Machine Learning- and Artificial Intelligence-Derived Prediction for Home Smart Energy Systems with PV Installation and Battery Energy Storage

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