2017
DOI: 10.15199/48.2017.07.20
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Site selection for wind and solar parks based on resources temporal and spatial complementarity – mathematical modelling approach

Abstract: The aim of this paper was the assessment of spatial and temporal complementarity of wind and solar resources based on selected locations in Poland. More specifically, we asked the following questions: a) does the spatial distribution of photovoltaic systems and wind farms own the property of smoothing the energy generation curve? b) is it possible as a result of renewable energy sources distribution over several locations to decrease instances of outliers in terms of energy production? c) to what extent depend… Show more

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Cited by 7 publications
(4 citation statements)
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“…More recently, energetic complementarity has also been employed in the formulation of optimisation problems. Jurasz and Mikulik [35] presented a simple mathematical model for selecting an optimal location for solar and wind parks, aiming to reduce the ramp rates of aggregated solar-wind generation, using data from several locations in Poland, considering VRES complementarity on a temporal and spatial scale. Aza-Gnandji et al [36] assessed the complementarity between solar and wind energy in Benin Republic.…”
Section: A Literature Review About Energetic Complementaritymentioning
confidence: 99%
“…More recently, energetic complementarity has also been employed in the formulation of optimisation problems. Jurasz and Mikulik [35] presented a simple mathematical model for selecting an optimal location for solar and wind parks, aiming to reduce the ramp rates of aggregated solar-wind generation, using data from several locations in Poland, considering VRES complementarity on a temporal and spatial scale. Aza-Gnandji et al [36] assessed the complementarity between solar and wind energy in Benin Republic.…”
Section: A Literature Review About Energetic Complementaritymentioning
confidence: 99%
“…However, due to the fact that in their work the average correlation between hourly generation was examined, and in this work the monthly average, the obtained correlation was smaller (correlation between offshore wind and onshore wind: 0.36, correlation between OWF and PV sources: −0.14) compared to the results obtained in this study (correlation between offshore and onshore wind: from 0.77 to 0.868, correlation between OWF and PV sources: from −0.936 to −0.970). In Poland, Jurasz et al [62] obtained a strong negative correlation between the monthly generation in photovoltaic and wind sources located on land but close to the sea (in Łeba). The mean monthly correlation coefficient was −0.85, which is very close to the results obtained in this study.…”
Section: Discussionmentioning
confidence: 99%
“…The most common purposes for calculating the Pearson correlation coefficient regarding energetic complementarity has been: 1) conducting an statistical analysis for evaluating if the renewable energies available in one region could allow the configuration of efficient power systems based on renewables ( [15], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34]); 2) as a tool for improving the operation or planning of existing power plants or systems ( [12], [13], [35], [36], [37], [38]); 3) as part of the set of equations, parameters and inequalities in an optimization model ( [39], [40], [41], [42], [43], [44], [45], [46]).…”
Section: Pearson Correlation Coefficient (Simple Correlationrxy)mentioning
confidence: 99%