scholarly journals Correlation between air temperature and electricity demand by linear regression and wavelet coherence approach: UK, Slovakia and Bosnia and Herzegovina case study

2013 ◽  
Vol 62 (4) ◽  
pp. 521-532 ◽  
Author(s):  
Samir Avdakovic ◽  
Alma Ademovic ◽  
Amir Nuhanovic
Keyword(s):  
Linear Regression ◽  
Power Systems ◽  
Air Temperature ◽  
Electricity Demand ◽  
Wavelet Coherence ◽  
Frequency Space ◽  
Time Frequency ◽  
Close Relationship ◽  
Dynamics Of Correlations

Abstract In this paper, the results of correlations between air temperature and electricity demand by linear regression and Wavelet Coherence (WTC) approach for three different European countries are presented. The results show a very close relationship between air temperature and electricity demand for the selected power systems, however, the WTC approach presents interesting dynamics of correlations between air temperature and electricity demand at different time-frequency space and provide useful information for a more complete understanding of the related consumption.

scholarly journals Wavelet analysis of land subsidence time-series: Madrid Tertiary aquifer case study

2020 ◽  
Vol 382 ◽  
pp. 353-359
Author(s):  
Roberto Tomás ◽  
José Luis Pastor ◽  
Marta Béjar-Pizarro ◽  
Roberta Bonì ◽  
Pablo Ezquerro ◽  
...  
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
Land Subsidence ◽  
Wavelet Coherence ◽  
Interferometric Synthetic Aperture Radar ◽  
Frequency Space ◽  
Time Frequency ◽  
Cross Wavelet Transform ◽  
Cross Wavelet

Abstract. Interpretation of land subsidence time-series to understand the evolution of the phenomenon and the existing relationships between triggers and measured displacements is a great challenge. Continuous wavelet transform (CWT) is a powerful signal processing method mainly suitable for the analysis of individual nonstationary time-series. CWT expands time-series into the time-frequency space allowing identification of localized nonstationary periodicities. Complementarily, Cross Wavelet Transform (XWT) and Wavelet Coherence (WTC) methods allow the comparison of two time-series that may be expected to be related in order to identify regions in the time-frequency domain that exhibit large common cross-power and wavelet coherence, respectively, and therefore are evocative of causality. In this work we use CWT, XWT and WTC to analyze piezometric and InSAR (interferometric synthetic aperture radar) time-series from the Tertiary aquifer of Madrid (Spain) to illustrate their capabilities for interpreting land subsidence and piezometric time-series information.

Dynamic correlation of Eastern and Western markets and forecasting: Scale-by-scale wavelet-based approach

2017 ◽  
Vol 04 (04) ◽  
pp. 1750040 ◽  
Author(s):  
Emrah Oral ◽  
Gazanfer Unal
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
Moving Average ◽  
Wavelet Coherence ◽  
Vector Autoregressive ◽  
Frequency Space ◽  
Time Frequency ◽  
Dynamic Correlation ◽  
Frequency Scale ◽  
Highly Correlated

In this paper, dynamic four-dimensional (4D) correlation of eastern and western markets is analyzed. A wavelet-based scale-by-scale analysis method has been introduced to model and forecast stock market data for strongly correlated time intervals. The daily data of stock markets of SP500, FTSE and DAX (western markets) and NIKKEI, TAIEX and KOSPI (eastern markets) are obtained from 2009 to the end of 2016 and their co-movement dependencies on time–frequency space using 4D multiple wavelet coherence (MWC) are determined. Once the data is detached into levels of different frequencies using scale-by-scale continuous wavelet transform, all of the time series possessing the same frequency scale are selected, inversed and forecasted using multivariate model, vector autoregressive moving average (VARMA). It is concluded that the efficiency of forecasting is increased substantially using the same-frequency highly correlated time series obtained by scale-by-scale wavelet transform. Moreover, the increasing or decreasing trend of prospected price shift is foreseen fairly well.

Co-movement analysis of Asian stock markets against FTSE100 and S&P 500: Wavelet-based approach

2016 ◽  
Vol 03 (04) ◽  
pp. 1650033 ◽  
Author(s):  
Adil Yilmaz ◽  
Gazanfer Unal
Keyword(s):  
Stock Markets ◽  
Movement Analysis ◽  
Point Of View ◽  
Wavelet Coherence ◽  
Short Term ◽  
Middle Term ◽  
Frequency Space ◽  
Time Frequency ◽  
Dynamic Correlation ◽  
Over Time

Wavelet coherence of time series provide valuable information about dynamic correlation and its impact on time scales. Here we analyze the wavelet coherence of FTSE100 and S&P 500 with selected Asian markets of S&P/ASX 200 (Australia), S&P/ASX200 A-REIT (Australia), BIST (Turkey), HIS (Hong Kong), IDX (Indonesia), KLSE (Malaysia), KOSPI (Korea), N225 (Japan), RTS (Russia), Shenzhen (China), 0050.TW (Taiwan). Wavelet coherence results revealed interconnected relationships between stock markets and how these relationships vary in the time–frequency space. We conclude that developed economy stock markets have strong influences over Asian stock markets, although market dependencies vary by country and change over time. We also suggested that because co-movements shift over time, short term and middle term diversification could be more beneficial taking into account the degree of interrelations. From investors point of view, these relationships provides beneficial information, especially for portfolio diversification and risk elimination.

Co-movement and Forecasting Analysis of Major Real Estate Markets by Wavelet Coherence and Multiple Wavelet Coherence

2017 ◽  
Vol 05 (02) ◽  
pp. 1750010 ◽  
Author(s):  
Cengiz KARATAS ◽  
Gazanfer UNAL ◽  
Adil YILMAZ
Keyword(s):  
Time Series ◽  
Real Estate ◽  
Real Estate Market ◽  
Wavelet Coherence ◽  
Real Estate Markets ◽  
Frequency Space ◽  
Time Frequency ◽  
Dynamic Correlation ◽  
The Usa ◽  
Multiple Wavelet Coherence

Wavelet coherence of time series provides valuable information about dynamic correlation and its impact on time scales. Here, the authors analyze the wavelet coherence of major real estate markets data, and take the USA, Hong Kong of China, Canada, Japan, and Developed Europe real estate market prices as time series. The wavelet coherence results show relationships among these markets, the correlations between the two and three markets (by multiple wavelet coherence) and how these relationships vary in the time-frequency space. These relationships allow the authors to build VARMA models of real estate data which produce forecasts with small errors.

scholarly journals Recognizing relationship between groundwater level and hydrological time series (Case study: Ardabil plain)

2021 ◽  
Author(s):  
Farnaz Daneshvar Vousoughi
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
Groundwater Level ◽  
Entropy Measure ◽  
Main Role ◽  
Rainfall Runoff ◽  
Frequency Space ◽  
Time Frequency ◽  
Common Time

Abstract Two approaches to identify the relation between hydrological time series (rainfall and runoff) and groundwater level (GWL) were used in the Ardabil plain. In this way, Wavelet-entropy measure (WEM) and wavelet transform coherence (WTC) as two approaches of wavelet transform (WT) were used. WEM have been considered as a criterion for the degree of time series fluctuations and WTC present common time-frequency space. In WEM calculation, monthly rainfall, runoff and GWL time series were divided into three different time periods and decomposed to multiple frequent time series and then, the energies of wavelet were calculated for each sub-series. The result showed WEM reduction in rainfall, runoff and GWL. The reduction of WEM presents the natural fluctuations decrease of time series. The reduction of entropy for runoff, rainfall and GWL time series were about 1.58, 1.36 and 29% respectively, it is concluded that fluctuation reduction of hydrological time series has relatively not more effect on the oscillation patterns of GWL signal. In this regard, it could be concluded that the human activities such as water driving from wells can be played main role in the reduction of GWL in Ardabil plain. WTC findings showed that runoff had most coherence (0.9-1) among the hydrological variables with GWL time series in the frequency bands of 4-8 and 8-16 months.

scholarly journals Taking into Consideration the Inclusion of Wind Generation in Hybrid Microgrids: A Methodology and a Case Study

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4082
Author(s):  
Luis Arribas ◽  
Natalia Bitenc ◽  
Andreo Benech
Keyword(s):  
Power Systems ◽  
Design Process ◽  
Research Community ◽  
Wind Generation ◽  
Generation System ◽  
Economic Barriers ◽  
Wind Generation System

During the last decades, there has been great interest in the research community with respect to PV-Wind systems but figures show that, in practice, only PV-Diesel Power Systems (PVDPS) are being implemented. There are some barriers for the inclusion of wind generation in hybrid microgrids and some of them are economic barriers while others are technical barriers. This paper is focused on some of the identified technical barriers and presents a methodology to facilitate the inclusion of wind generation system in the design process in an affordable manner. An example of the application of this methodology and its results is shown through a case study. The case study is an existing PVDPS where there is an interest to incorporate wind generation in order to cope with a foreseen increase in the demand.

Sign in / Sign up

Export Citation Format

Share Document