scholarly journals Investigating the Predictability of Photovoltaic Power Using Approximate Entropy

2021 ◽  
Vol 9 ◽  
Author(s):  
Mao Yang ◽  
Kaixuan Wang ◽  
Yang Cui ◽  
Fan Feng ◽  
Xin Su ◽  
...  
Keyword(s):  
Time Series ◽  
Spatial Scale ◽  
Approximate Entropy ◽  
Measured Data ◽  
Prediction Methods ◽  
Coefficient Variation ◽  
Photovoltaic Power

The predictability concept of Photovoltaic (PV) power on the time series was presented and the approximate entropy algorithm and predictable coefficient were used to quantificationally analyze the predictability of PV power on time series, then the approximate entropy and predictable coefficient variation at different spatial scale were analyzed. Finally, the measured data of a PV plant in western Ningxia were used for testing and confirming the result. The results of several typical prediction methods show that the proposed method can effectively characterize the predictability of PV power on time series.

Making investment decisions in stock markets using a forecasting-Markowitz based decision-making approaches

2019 ◽  
Vol 15 (2) ◽  
pp. 647-659 ◽  
Author(s):  
Zahra Moeini Najafabadi ◽  
Mehdi Bijari ◽  
Mehdi Khashei
Keyword(s):  
Decision Making ◽  
Time Series ◽  
Stock Markets ◽  
Time Series Prediction ◽  
Investment Decisions ◽  
Rate Of Return ◽  
Expected Returns ◽  
Prediction Methods ◽  
Content Type ◽  
Markowitz Model

Purpose This study aims to make investment decisions in stock markets using forecasting-Markowitz based decision-making approaches. Design/methodology/approach The authors’ approach offers the use of time series prediction methods including autoregressive, autoregressive moving average and artificial neural network, rather than calculating the expected rate of return based on distribution. Findings The results show that using time series prediction methods has a significant effect on improving investment decisions and the performance of the investments. Originality/value In this study, in contrast to previous studies, the alteration in the Markowitz model started with the investment expected rate of return. For this purpose, instead of considering the distribution of returns and determining the expected returns, time series prediction methods were used to calculate the future return of each asset. Then, the results of different time series methods replaced the expected returns in the Markowitz model. Finally, the overall performance of the method, as well as the performance of each of the prediction methods used, was examined in relation to nine stock market indices.

scholarly journals Multiscale Cross-Approximate Entropy Analysis as a Measure of Complexity among the Aged and Diabetic

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Hsien-Tsai Wu ◽  
Cyuan-Cin Liu ◽  
Men-Tzung Lo ◽  
Po-Chun Hsu ◽  
An-Bang Liu ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Time Series ◽  
Pulse Transit Time ◽  
Approximate Entropy ◽  
Physiological Signals ◽  
Diabetes Group ◽  
Group 4 ◽  
Group 2 ◽  
Aged Subjects

Complex fluctuations within physiological signals can be used to evaluate the health of the human body. This study recruited four groups of subjects: young healthy subjects (Group 1,n=32), healthy upper middle-aged subjects (Group 2,n=36), subjects with well-controlled type 2 diabetes (Group 3,n=31), and subjects with poorly controlled type 2 diabetes (Group 4,n=24). Data acquisition for each participant lasted 30 minutes. We obtained data related to consecutive time series with R-R interval (RRI) and pulse transit time (PTT). Using multiscale cross-approximate entropy (MCE), we quantified the complexity between the two series and thereby differentiated the influence of age and diabetes on the complexity of physiological signals. This study used MCE in the quantification of complexity between RRI and PTT time series. We observed changes in the influences of age and disease on the coupling effects between the heart and blood vessels in the cardiovascular system, which reduced the complexity between RRI and PTT series.

scholarly journals Comparison Between Measurements and WRF Numerical Simulation of Global Solar Irradiation in Romania

2013 ◽  
Vol 57 (1) ◽  
pp. 24-33 ◽  
Author(s):  
Dragos Isvoranu ◽  
Viorel Badescu
Keyword(s):  
Numerical Simulation ◽  
Preliminary Analysis ◽  
Measured Data ◽  
Solar Irradiation ◽  
Short Term ◽  
Data Accessibility ◽  
Power Stations ◽  
Photovoltaic Power ◽  
Global Solar Irradiation ◽  
Global Irradiation

Abstract The paper presents a comparative analysis between the surface global irradiation measured for Romania and the predicted irradiation obtained by numerical simulation. The measured data came from the Romanian National meteorological Administration. Based on a preliminary analysis that took into account several criteria among which, performance, cost, popularity and meteorological and satellite data accessibility we concluded that a combination GFS-WRF(NMM) or GFS-WRF(ARW) is most suitable for short term global solar irradiation forecasting in order to assess the performance of the photovoltaic power stations (Badescu and Dumitrescu, 2012, [1], Martin et al., 2011, [2]).

scholarly journals Damage detection by recurrence and entropy methods on the basis of time series measured during composite milling

2020 ◽  
Vol 111 (1-2) ◽  
pp. 549-563
Author(s):  
Krzysztof Kecik ◽  
Krzysztof Ciecielag ◽  
Kazimierz Zaleski
Keyword(s):  
Time Series ◽  
Damage Detection ◽  
Approximate Entropy ◽  
Recurrence Plot ◽  
Milling Process ◽  
Fiber Reinforced Polymer ◽  
Reinforced Polymer ◽  
Glass Fiber Reinforced ◽  
Damage Indicators ◽  
Different Diameters

Abstract This paper presents methods for damage detection in machined material on the basis of time series measured during milling of glass-fiber–reinforced polymer (GFRP). Recurrence methods and different types of entropy have emerged as useful tools for detecting subtle non-stationarities and/or changes in nonlinear signals. In this research, a recurrence plot, recurrence quantifications, an approximate entropy, and sample entropy are used. By identifying changes in the cutting force measured during the composite milling process, the damage occurrence has been detected. Firstly, the damage has been modelled as the intentionally introduced hole with different diameters and depths in order to estimate the size detectable damages and to select proper recurrence measures as damage indicators. Next, the experiments with the real damage have been performed and the damage indicators have used.

scholarly journals Analysis of day-ahead generation diagram in power network consisting of renewable energy sources

2019 ◽  
Vol 84 ◽  
pp. 01002
Author(s):  
Zsolt Čonka ◽  
Dušan Medveď ◽  
Michal Ivančák ◽  
Michal Kolcun
Keyword(s):  
Renewable Energy ◽  
Power Plant ◽  
Renewable Energy Sources ◽  
Measured Data ◽  
Energy Sources ◽  
Power Network ◽  
Photovoltaic Power ◽  
Future Expectation ◽  
Specific Part ◽  
Variable Energy

This article deals with the analysis of a day-ahead generation diagram in specific part of a power network with renewable energy sources. As a renewable energy source a photovoltaic power plant was chosen. Input data for a day-ahead analysis was obtained from the database of previous measurement that was realised on the existing configuration in off-grid network at the department of authors. The simulation network was created in Matlab/Simscape Power System environment that consisted of rotating generators (for regulation of generated power due to fluctuated power generation from photovoltaic sources) and photovoltaic power plant of variable energy generation and loads. The results refer to a necessity to consider the previous measured data of the weather for prediction of future expectation of a day-ahead load diagram.

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