A New Hourly Dataset for Photovoltaic Energy Production for the Continental USA

In the case of building surfaces, the installation of green roofs or green facades can be used to reduce the temperature of the environment and the building. In addition, introducing photovoltaic energy production will help to reduce CO2 emissions. Both approaches (building greenery and photovoltaic energy production) compete, as both of them are located on the exterior of buildings. This paper aims to give an overview of solutions for the combination of building greenery (BG) systems and photovoltaic (PV) panels. Planning principles for different applications are outlined in a guideline for planning a sustainable surface on contemporary buildings. A comprehensive literature review was done. Identified solutions of combinations were systematically analysed and discussed in comparison with additional relevant literature. The main findings of this paper were: (A) BG and PV systems with low sub-construction heights require shallow substrates/low growing plants, whereas in the case of the combination of (a semi)-intensive GR system, a distance of a minimum 60 cm between the substrate surface and lower panel edge is recommended; (B) The cooling effect of the greenery depends on the distance between the PV and the air velocity; (C) if the substrate is dry, there is no evapotranspiration and therefore no cooling effect; (D) A spectrum of different PV systems, sub-constructions, and plants for the combination of BG and PV is necessary and suitable for different applications shown within the publication.

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Quantifying Wildfire-Induced Impacts to Photovoltaic Energy Production in the western United States

10.1109/pvsc43889.2021.9518514 ◽

2021 ◽

Author(s):

Samuel D. Gilletly ◽

Nicole D. Jackson ◽

Andrea Staid

Keyword(s):

United States ◽

Energy Production ◽

Western United States ◽

Photovoltaic Energy

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PREDICTION OF DAILY PHOTOVOLTAIC ENERGY PRODUCTION USING WEATHER DATA AND REGRESSION

Journal of Solar Energy Engineering ◽

10.1115/1.4051262 ◽

2021 ◽

pp. 1-20

Author(s):

Hüseyin Sarper ◽

Igor Melnykov ◽

Lee Anne Martínez

Keyword(s):

Energy Production ◽

Weather Prediction ◽

Model Construction ◽

Weather Data ◽

Good Prediction ◽

Linear Regression Models ◽

Data Set ◽

Photovoltaic Energy ◽

Pv Systems ◽

Good Prediction Accuracy

Abstract This paper presents linear regression models to predict the daily energy production of three photovoltaic (PV) systems located in southeast Virginia. The prediction is based on daylight duration, sky index, the average relative humidity, and the presence of fog or mist. No other daily weather report components were statistically significant. The proposed method is easy to implement, and it can be used in conjunction with other advanced methods in estimating any given future days energy production if weather prediction is available. Data from 2013-2015 was used in the model construction. Model validation was performed using newer (2016, 2017, 2020, and 2021) data not used in the model construction. Results show good prediction accuracy for a simple methodology, free of system parameters, that can be utilized by ordinary photovoltaic energy users. The entire data set can be downloaded using the link provided.

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