Forecasting of solar radiation is an issue with exceedingly practical consequences since it is expected that solar energy will be one of the major contributors in the future global energy supply.
Such dependence seriously affects the short-term predictability of solar irradiation. However, the presence of the higher randomness (which can be detected from the analysis of measured solar irradiation time series) may significantly reduce the predictability time; (ii) Therefore, results obtained in this study can be used in the choice of equations and variables that could be included in a forecasting model.
The second group of the stations is also situated at the lower altitudes (38; 558 m) but relatively close to the ocean (573; 8664 m).
(1) Encoding the time series by creating a sequence S of the characters 0 and 1 written as s(i),i=1,2,,N, according to the rule s(i) = 0 if xi
However, in addition to this application, its use is essential in the investigation of, e.g., ranked variables of entities coded by numerical symbols. Data curation, S.M. In fact, the simple Lempel Ziv partition contains enough data to estimate complexity without performing the entire compression encoding process. From Table 2 it can be seen that the distribution of stations regarding the order of KCM is the same as those grouped pursuing the order of KC values, i.e., (1) higher than 0.90 (stations 4, 5, 7, 8, 1 and 3) and (2) less than 0.90 (2, 10, 11, 6 and 9), where, for both groups stations are ordered in a decreasing sequence. Solcast data has very low uncertainty, is delivered rapidly (in minutes), is available in multiple formats, and includes free credit to get you started. It is estimated to be proportional to its randomness, i.e., KT=1/KC (in time units, second, hour or day, etc.). We notice three regions with different randomness: (1) station 9 with low values (South-West); (2) stations (1, 11, 5, and 2) located on North-East side of the island with higher values comparing to region 1 and (3) stations (4, 7, 6, 3, and 8) which are located in the direction extending from the South-East to the North-West side of the island, where the high randomness is dominant. Badosa J., Haeffelin M., Chepfer H. Scales of spatial and temporal variation of solar irradiance on Reunion tropical island. SoDa'sannual solar training, co-organized with Mines ParisTech research center, is the opportunity to get knowledge about solar radiation calculation methods. Otherwise, if KC becomes considerably higher, accurate long-term predictions are not reasonable, but short-term ones can be made. Recognition of the patterns with the LZA algorithm can be described in the following way: Now, let us consider a short example with the binary sequence 1011010. ; Formal analysis, D.T.M., M.B., S.M., I.A.
As shown in this figure, the KC is ranged in the interval (0, 1).
Proceedings of the International Workshop on Solar Resource from the Local Level to Global Scale in Support of the Resource Management of Renewable Electricity Generation. Therefore, the distances are unaffected by the distance of the object from the origin. One of them is the HAM distance that is described in the previous subsection. SoDa team is strongly involved inresearch and innovationand has the objective to provide yousolar knowledge and to supportyour business activities.
Ambainis A., Gasarch W., Srinivasan A., Utis A. Kolmogorov complexity (KC), sample entropy (SE), and the highest value in the Kolmogorov complexity spectrum (KCM) of half-day solar irradiation time series of 11 stations at La Reunion (France). Then. Figure 10 can be considered as an average picture of randomness of half-day solar irradiation time series over La Reunion. This research was funding by the Ministry of Education and Science of the Republic of Serbia (4307) and European funding (FEDER).
TMY data is frequently used by solar engineers, as a data input to energy system simulations. We just shortly summarize sources of cloudiness affecting the island: (i) the advection of trade cumuli and large-scale cloud systems; (ii) local formation by convection as a result of the interaction between synoptic wind, local thermal winds and the orography (Figure 6b) and (iii) acceleration of trade winds, along the island coasts parallel to the synoptic wind direction, due to the Venturi effect when clouds tend to be blown away. Despite the difficulties, which are often discussed, LZA algorithm is among the more accessible universal complexity estimators. In addition, we introduced the Kolmogorov time (KT) indicating time window within a time series where complexity remains nearly unchanged. Let us note that trends of SE and KCHA in Figure 8 have a common feature. For practical purposes, the approximate period limit is usually computed, often called Lyapunov time, for accurate prediction since it is an inverse function of the maximal value of the LE. Let X denote solar irradiation time series and x its specific value. We briefly describe the calculation of the KC complexity of a time series X(x1,x2,x3,,xN) by the LZA algorithm. Otherwise, if LE becomes considerably higher, accurate long-term predictions are not reasonable, but short-term ones can be made instead. Furthermore, chaotic processes are perfectly deterministic while random processes are attached to some prior probabilities. Solar radiation network (11 stations, see Table 1) which provide global horizontal irradiance (GHI) and the diffuse horizontal irradiance (DHI) at 1-min intervals are obtained using SPN1 sunshine pyranometer from Delta-T devices.
It could be stated that the KT designates the size of the time window within time series where complexity remains nearly unchanged. The colour of boxes: (1) HAMRn > KC (yellow), (2) KC > HAMRn (blue) and (3) KC ~ HAMRn (green). Hu J., Gao J., Principe J.C. The stations having lower values of KC (and lower randomness) are placed above the red line (2, 6, 9, 10 and 11), while other stations (1, 3, 4, 5, 7 and 8) have KT values that are closer to one. Approximate entropy as a measure of system complexity. The study area is Reunion Island (Figure 6a,b) which is a tropical oversea French department (2, 512 km) located in the south-west Indian Ocean (21 S, 55 E) between Madagascar and Mauritius. In this study, we use the Hamming distance (HAM). Here, we will not deal with the specific synoptic details of the occurrence of cloudiness. Thus, if LE 0 implies that the Lyapunov time tends to , then accurate long-term predictions are possible. Some of the most popular being: Hamming distance [11], Minkowski distance, Euclidean distance, Manhattan distance and Chebyshev distance [12]. Let us visualize the meaning of the Kolmogorov time by the computational experiment using the logistic equation (see Section 2.2.2). This time is used for predicting the time series. Henceforth, we shall denote this quantity Kolmogorov time (KT), as it quantifies the time span beyond which randomness significantly influences predictability. The presence of the higher randomness in a time series may significantly reduce the predictability time of physical quantity we deal with. The KC, KCM and SE values of half-day solar irradiation data are given in Table 2 and Figure 8, while the Kolmogorov complexity spectra are depicted in Figure 9.
Flowchart for calculation of the Kolmogorov complexity (KC) using the Lempel-Zev algorithm (LZA). Corresponding values of KT are also shown in the same figure. The KC values for the stations closest to the sea coast (4 and 8, as seen in Table 1) are affected by the sea-breeze effect, trade wind effect and cloud cover too. The following conclusions are drawn from this study: This study was realized as part of the project Studying climate change and its influence on the environment: impacts, adaptation and mitigation (43007) financed by the Ministry of Education and Science of the Republic of Serbia within the framework of integrated and interdisciplinary research for the period 20112018. Towards the spatial Hamming distance. The spatial Hamming distance Therefore, in practice, we examine large pre-existing databases in order to generate new information. At the first part of the day they have a slightly higher value, but at the annual level, this feature is negligible. The concluding remarks are given in part 5. However, in reality, we see that they are just a copy (negative) of each other. and S.M.-M.; Methodology, D.T.M., M.B., P.J., M.D. The objective of this study therefore is to investigate the complexity and predictability of half-day (from sunrise to sunset) solar irradiation time series of 11 stations at La Reunion (France), using information measures KC, KC spectrum, KCM, sample entropy (SE) and Hamming distance (HAM) as one of information distances and a proposed measure that is a combination of KC complexity and HAM distance (KCHA). Sign up using the Solcast toolkit and get free credits so you can download some sample data, thats relevant for you, for free, right now. Dreg,i=ijHAM(xi,xj), Assigned stations in group 1 correspond to stations mainly located in the windward side of the island where the trade wind flow is splitting by the Fournaise Volcano. Towards an explanation of the Kolmogorov time (KT). The Hamming distance is an essential measure for detecting the errors in transmission of information suggested by [11] as was already mentioned. Badosa J., Haeffelin M., Kalecinski N., Bonnardot F., Jumaux G. Reliability of day-ahead solar irradiance forecasts on Reunion Island depending on synoptic wind and humidity conditions. The highest value KmC as in this series, i.e., KmC=max{ci}, is the highest value of Kolmogorov complexity spectrum (KCM), as seen in Figure 2. The current status of forecasting solar irradiance for energy generation purposes is comprehensively reviewed, in regard to short-term forecasting (up to a few hours) and forecasts for up to two days primarily for use in practical applications, by [29].
What is more, by KC we are not able to determine, even approximately, how significant the local or regional impacts are on this information measure. Accessibility As pointed out by [15] if, in this case, bits represent an image, they are still the same, except that one is a negative copy of the other. We find that all half-day (from sunrise to sunset) solar irradiation series exhibit high complexity. Evaluating the solar resource is crucial for any solar energy investment decision. [(accessed on 23 June 2018)]; Lesouf D., Gheusi F., Delmas R., Escobar J.
For their combination, we use the product of those two quantities (KCHA) in the form. However, complexity estimation using this algorithm usually amounts to performing the entire compression process and comparing inverse compression ratios as a measure of complexity. 
time series of solar radiation data
