Spatial representation of temporal complementarity between three variable energy sources using correlation coefficients and compromise programming

Canales, Fausto A.; Jurasz, Jakub; Kies, Alexander; Beluco, Alexandre; Arrieta-Castro, Marco; Peralta-Cayón, Andrés

doi:10.1016/j.mex.2020.100871

Cited by 18 publications

(8 citation statements)

References 12 publications

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“…The general idea is interesting but depends on the system's particular characteristics 105 and does not provide a direct complementarity metric. Canales et al (2020a); Arias et al (2015); Canales et al (2020b) introduced a method that assesses temporal complementarity between three variable energy sources, using a combination 110 of correlation coefficients, Euclidean vectors, compromise programming, and normalization. The method's basis is correlation analysis, and therefore their proposal shares the criticism we made above.…”

Section: Linearity Of the Relation Is Also An Issue Evenmentioning

confidence: 99%

Total variation as a metric for complementarity in energy resources time series

Cantor¹,

Ochoa²,

Sánchez³

2021

Preprint

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Complementarity has become an essential concept in energy supply systems. Although there are some other metrics, most studies use correlation coefficients to quantify complementarity. The standard interpretation is that a high negative correlation indicates a high degree of complementarity. However, we show that the correlation is not an entirely satisfactory measure of complementarity. As an alternative, we propose a new index based on the mathematical concept of the total variation. For two time series, the new index φ is one minus the ratio of the total variation of the sum to the sum of the two series' total variation. We apply the index first to an auto-regressive (AR) process and then to various Colombian electric system series. The AR case clearly illustrates the limitations of the correlation coefficient as a measure of complementarity. We then evaluate complementarity across various space-time scales in the Colombian power sectors, considering hydro and wind projects. The complementarity assessment on a broad temporal and geographical scale helps analyze large power systems with different energy sources. The case study of the Colombian hydropower systems suggests that φ is better than ρ because (i) it considers scale, whereas ρ, being non-dimensional, is insensitive to the scale and even to the physical dimensions of the variables; (ii) one can apply φ to more than two resources; and (iii) ρ tends to overestimate complementarity.

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Section: Linearity Of the Relation Is Also An Issue Evenmentioning

confidence: 99%

Total variation as a metric for complementarity in energy resources time series

Cantor¹,

Ochoa²,

Sánchez³

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Pearson's correlation coefficient was used to estimate complementarity. Canales et al (2020a) developed a temporal complementarity index that combines Pearson's correlation coefficient and compromise programming, and applied it in a follow-up paper across Colombia's territory using wind speed, solar radiation and surface runoff data from 2015 (see Canales et al, 2020b). The studies mentioned above have found evidence of high complementarity potential between solar radiation and runoff, and wind speed and runoff.…”

Section: Literature Reviewmentioning

confidence: 99%

Assessing the Complementarities of Colombia’s Renewable Power Plants

et al. 2020

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“…To quantify solar and wind synergy, various studies use statistical measures such as (anti)correlation-based [4,10,[20][21][22] or variability-based [3,10,17,18] metrics between the solar and wind power profiles. A recent study [3] showed that when such metrics are applied on hourly timescales, they typically fail to put realistic constraints on capacity factors of the considered resources.…”

Section: Introductionmentioning

confidence: 99%

Pieces of a puzzle: solar-wind power synergies on seasonal and diurnal timescales tend to be excellent worldwide

Nyenah¹,

Sterl²,

Thiery³

2022

Environ. Res. Commun.

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Moving from fossil fuel-based electricity generation to renewable electricity generation is at the heart of current developments in power sectors worldwide. In this context, synergy assessment between renewable electricity sources is of great significance for local and regional power planning. Here we use synergy metrics (stability coefficient (Cstab) and normalised Pearson correlation coefficient (r) to a state-of-the-art reanalysis product from 2011–2020 to preliminarily assess solar-wind synergies globally on diurnal and seasonal time scales assuming equal installed capacities of solar and wind hybrid system. Our results suggest that medium-to-good diurnal and seasonal complementarities between solar photovoltaic and wind power potential are the norm, rather than the exception, which could help many countries in achieving balanced power mixes based on renewable resources. Our results also suggest that many regions in the tropics and sub tropics may need to explore synergic benefits of other renewables in addition to solar power. An open-access application is now available on the European Copernicus cloud to explore solar and wind synergies on diurnal and seasonal time scales worldwide.

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Spatial representation of temporal complementarity between three variable energy sources using correlation coefficients and compromise programming

Cited by 18 publications

References 12 publications

Total variation as a metric for complementarity in energy resources time series

Total variation as a metric for complementarity in energy resources time series

Assessing the Complementarities of Colombia’s Renewable Power Plants

Pieces of a puzzle: solar-wind power synergies on seasonal and diurnal timescales tend to be excellent worldwide

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