Multifractal Analysis of Daily Global Horizontal Radiation in Complex Topography Island: La Reunion as a Case Study

Malinović-Milićević

et al. 2018

Entropy

Self Cite

Analysis of daily solar irradiation variability and predictability in space and time is important for energy resources planning, development, and management. The natural intermittency of solar irradiation is mainly triggered by atmospheric turbulent conditions, radiative transfer, optical properties of cloud and aerosol, moisture and atmospheric stability, orographic and thermal forcing, which introduce additional complexity into the phenomenological records. To address this question for daily solar irradiation data recorded during the period 2011–2015, at 32 stations measuring solar irradiance on La Reunion French tropical Indian Ocean Island, we use the tools of non-linear dynamics: the intermittency and chaos analysis, the largest Lyapunov exponent, Sample entropy, the Kolmogorov complexity and its derivatives (Kolmogorov complexity spectrum and its highest value), and spatial weighted Kolmogorov complexity combined with Hamming distance to assess complexity and corresponding predictability. Finally, we have clustered the Kolmogorov time (that quantifies the time span beyond which randomness significantly influences predictability) for daily cumulative solar irradiation for all stations. We show that under the record-breaking 2011–2012 La Nina event and preceding a very strong El-Nino 2015–2016 event, the predictability of daily incident solar energy over La Réunion is affected.

Section: Materials and Methodologymentioning

confidence: 99%

to a spatial weighted Kolmogorov complexity

using pair-wise dissimilarity between binarized time series.…”

Section: Study Locations and Pyranometer Measurementsmentioning

confidence: 99%

Spatial and Temporal Non-Linear Dynamics Analysis and Predictability of Solar Radiation Time Series for La Reunion Island (France)

Bessafi¹,

Malinović-Milićević

et al. 2018

Entropy

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“…The most salient characteristic of solar irradiation is periodic seasonal variation which does not require additional analyses since its causes are well-known and predictable (Bessafi et al 2018). At the same time, a great deal of information resides within daily, weekly and sitespecific fluctuations which have not been studied thus far due to the lack of appropriate tools.…”

Section: Introductionmentioning

confidence: 99%

“…KC is underpinned by the idea of algorithmic compressibility which gives it access to patterning and makes it more sensitive to pattern regularities relative to uncertainty-based measures. Although compressibility is important for entropy, KC uses it directly to measure pattern randomness (or absence thereof).The complexity of a string is defined as the length of the shortest algorithm capable of encoding it.For example, KC has been applied to geophysical time series such as UV irradiation (Mihailović et al 2013), radon concentration (Aksentijevic et al 2020a, b;Mihailović et al 2015) and solar irradiation (Bessafi et al 2018;Mihailović et al 2018). Although KC is an important measure of the complexity of atmospheric processes and the climatic impact of sunlight, its ability to capture regularities in solar activity, atmospheric processes and their interactions has not been examined thus far.…”

Section: Introductionmentioning

confidence: 99%

Mapping regularities in the solar irradiance data using complementary complexity measures

Stoch Environ Res Risk Assess

Aksentijevic

Mihailović

2020

Solar irradiance represents one of the principal phenomena of interest in geophysics and recent research, especially which concerned with renewable energy, suggests that the complexity of solar irradiance time series offers important insights into the dynamics of different geophysical systems. We examined the complexity of the daily cumulative global horizontal irradiance (kWh/m2; dGHI in further text) recorded by satellite for 32 stations on the island of La Réunion over a 35-month period (2004–2006) using Kolmogorov complexity (KC) and a recently introduced measure—Aksentijevic–Gibson complexity (AG) which is capable of quantifying the complexity of both long and short strings. Previous examinations of physical data suggest that AG could represent a useful addition to the geophysical analysis toolkit. Our results demonstrate for the first time that running KC is capable of capturing periodic patterns in data and that AG is sensitive to both global/long-scale spatial and temporal structure and local/short-range complexity fluctuations. Importantly, we report a putative weekly periodicity which might be related to environmental factors and human activity. In conclusion, we suggest that AG could represent a useful tool in the study of solar irradiation time series but also with other types of geophysical data.

“…In addition, spatial and time cloud cover patterns are triggered by marine boundary layer turbulence and large-scale synoptic circulation in the tropical troposphere. Thus, the space and time variability of daily solar radiation is very complex and its forecast is still a challenge for solar resource research [ 1 , 2 ]. As mentioned previously, the predictability of solar radiation remains a social and economic stake for small islands located in the tropical ocean area.…”

Section: Introductionmentioning

confidence: 99%

Algorithmic Probability Method Versus Kolmogorov Complexity with No-Threshold Encoding Scheme for Short Time Series: An Analysis of Day-To-Day Hourly Solar Radiation Time Series over Tropical Western Indian Ocean

Bessafi¹,

P³

et al. 2019

Entropy

Self Cite

The complexity of solar radiation fluctuations received on the ground is nowadays of great interest for solar resource in the context of climate change and sustainable development. Over tropical maritime area, there are small inhabited islands for which the prediction of the solar resource at the daily and infra-daily time scales are important to optimize their solar energy systems. Recently, studies show that the theory of the information is a promising way to measure the solar radiation intermittency. Kolmogorov complexity (KC) is a useful tool to address the question of predictability. Nevertheless, this method is inaccurate for small time series size. To overcome this drawback, a new encoding scheme is suggested for converting hourly solar radiation time series values into a binary string for calculation of Kolmogorov complexity (KC-ES). To assess this new approach, we tested this method using the 2004–2006 satellite hourly solar data for the western part of the Indian Ocean. The results were compared with the algorithmic probability (AP) method which is used as the benchmark method to compute the complexity for short string. These two methods are a new approach to compute the complexity of short solar radiation time series. We show that KC-ES and AP methods give comparable results which are in agreement with the physical variability of solar radiation. During the 2004–2006 period, an important interannual SST (sea surface temperature) anomaly over the south of Mozambique Channel encounters in 2005, a strong MJO (Madden–Julian oscillation) took place in May 2005 over the equatorial Indian Ocean, and nine tropical cyclones crossed the western part of the Indian Ocean in 2004–2005 and 2005–2006 austral summer. We have computed KC-ES of the solar radiation time series for these three events. The results show that the Kolmogorov complexity with suggested encoding scheme (KC-ES) gives competitive measure of complexity in regard to the AP method also known as Solomonoff probability.