Introduction to the open source PV LIB for python Photovoltaic system modelling package

Andrews, Robert W.; Stein, Joshua S.; Hansen, Clifford W.; Riley, Daniel

doi:10.1109/pvsc.2014.6925501

Cited by 86 publications

(50 citation statements)

References 8 publications

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“…The time series for PV and solar thermal are created with the PV-Lib [67]. The weather data is derived from the DIN EN 12831 [68] by finding the closest location listed.…”

Section: Creation Of Demand and Supply Time Seriesmentioning

confidence: 99%

Bottom-up energy supply optimization of a national building stock

Kotzur¹,

Markewitz²,

Robinius³

et al. 2020

Energy and Buildings

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The installation and operation distributed energy resources (DER) and the electrification of the heat supply significantly changes the interaction of the residential building stock with the grid infrastructure. Evaluating the mass deployment of DER at the national level would require analyzing millions of individual buildings, entailing significant computational burden.To overcome this, this work proposes a novel bottom-up model that consists of an aggregation algorithm to create a spatially distributed set of typical residential buildings from census data. Each typical building is then optimized with a Mixed-Integer Linear Program to derive its cost optimal technology adoption and operation, determining its changing grid load in future scenarios.The model is validated for Germany, with 200 typical buildings considered to sufficiently represent the diversity of the residential building stock. In a future scenario for 2050, photovoltaic and heat pumps are predicted to be the most economically and ecologically robust supply solutions for the different building types. Nevertheless, their electricity generation and demand temporally do not match, resulting in a doubling of the peak electricity grid load in the rural areas during the winter. The urban areas can compensate this with efficient co-generation units, which are not cost-efficient in the rural areas.

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“…The time series for PV and solar thermal are created with the PV-Lib [67]. The weather data is derived from the DIN EN 12831 [68] by finding the closest location listed.…”

Section: Creation Of Demand and Supply Time Seriesmentioning

confidence: 99%

Bottom-up energy supply optimization of a national building stock

Kotzur¹,

Markewitz²,

Robinius³

et al. 2020

Energy and Buildings

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“…To calculate PV power we apply the open-source PV modeling environment PV_LIB for python (Andrews et al, 2014). It converts direct and diffuse radiation, temperature and wind speed into normalized PV power.…”

Section: Pv-power Calculationmentioning

confidence: 99%

Impact of the 4 April 2014 Saharan dust outbreak on the photovoltaic power generation in Germany

et al. 2017

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Abstract. The importance for reliable forecasts of incoming solar radiation is growing rapidly, especially for those countries with an increasing share in photovoltaic (PV) power production. The reliability of solar radiation forecasts depends mainly on the representation of clouds and aerosol particles absorbing and scattering radiation. Especially under extreme aerosol conditions, numerical weather prediction has a systematic bias in the solar radiation forecast. This is caused by the design of numerical weather prediction models, which typically account for the direct impact of aerosol particles on radiation using climatological mean values and the impact on cloud formation assuming spatially and temporally homogeneous aerosol concentrations. These model deficiencies in turn can lead to significant economic losses under extreme aerosol conditions. For Germany, Saharan dust outbreaks occurring 5 to 15 times per year for several days each are prominent examples for conditions, under which numerical weather prediction struggles to forecast solar radiation adequately. We investigate the impact of mineral dust on the PV-power generation during a Saharan dust outbreak over Germany on 4 April 2014 using ICON-ART, which is the current German numerical weather prediction model extended by modules accounting for trace substances and related feedback processes. We find an overall improvement of the PV-power forecast for 65 % of the pyranometer stations in Germany. Of the nine stations with very high differences between forecast and measurement, eight stations show an improvement. Furthermore, we quantify the direct radiative effects and indirect radiative effects of mineral dust.For our study, direct effects account for 64 %, indirect effects for 20 % and synergistic interaction effects for 16 % of the differences between the forecast including mineral dust radiative effects and the forecast neglecting mineral dust.

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“…This model requires energy supply and demand patterns. The energy supply patterns were modelled with the open source package PVLIB [7]. This package provides functions to model the PV yield using atmospheric and PV system parameters.…”

Section: A Parametersmentioning

confidence: 99%

On the influence of electricity demand patterns, battery storage and PV system design on PV self-consumption and grid interaction

Litjens

Sark

Worrell

2016

2016 IEEE 43rd Photovoltaic Specialists Conference (PVSC)

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Abstract-New policies supporting photovoltaics (PV) selfconsumption and reduced feed-in power flows are advocated in many countries. Consequently, knowledge about the influences of demand patterns and battery energy storage on PV selfconsumption and grid impact is required. This study analysed these influences for 400 residential and 26 commercial systems from the Netherlands. Results show larger self-consumption rates for commercial systems than residential systems. Batteries increase the self-consumption rate depending on the PV size and the battery size. Averaged curtailment losses are larger for residential systems than commercial systems and decrease with the addition of a battery to the system.

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Introduction to the open source PV LIB for python Photovoltaic system modelling package

Cited by 86 publications

References 8 publications

Bottom-up energy supply optimization of a national building stock

Bottom-up energy supply optimization of a national building stock

Impact of the 4 April 2014 Saharan dust outbreak on the photovoltaic power generation in Germany

On the influence of electricity demand patterns, battery storage and PV system design on PV self-consumption and grid interaction

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