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	   Dataset: GR-PLW6-Y07Y11

	Electricity Power Loads and Weather data
	    Greece, Jan.2007 - Dec.2011
 
	        Release Notes

	Copyright (c) 2016 by Harris V. Georgiou

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   Release:     Jul 30, 2016

   - Version:  1.1a
   - Format:   .mat
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This file contains important information about the
current version of the dataset package.

Downloading and using this material hints that you
accept the EULA/Terms-of-Use (please read carefully).

We welcome your comments and suggestions.

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WHAT'S IN THIS PACKAGE?

-  Overview
-  Available file formats
-  Files and Datasets
-  License Agreement

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OVERVIEW

Power load forecasting is one of the major technical challenges today,
especially for urban areas in developed and developing countries.
Short-term forecasting is based on the power load data series, as well
as localized weather data (e.g. temperature, cloud cover, etc).
The concept of "smart grid" is such an effort for addressing, among
other things, the tasks of early detection, emergency response and
self-healing of the energy grids in "smart cities".

This package contains two sets of data including five-year power load 
logs for the entire Greece, as registered by the Independent Power 
Transmission Operator (IPTO or ADMIE), and eight-year weather data 
from six measuring stations in areas of major trends in the mainland, 
as registered by the NOAA Satellite and Information Service (USA).

For further information see:
* Hellenic Transmission System Operator (HTSO), Unit Production Data:
http://www.desmie.gr/en/operations-data/settlement/unit-production/
* National Oceanic and Atmospheric Administration (NOAA) USA, 
Integrated Surface Global Hourly Data (DS3505):
https://data.noaa.gov/dataset/integrated-surface-global-hourly-data

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AVAILABLE FILE FORMATS

The datasets are available in the following formats (included):

*.mat	: Matlab/Octave native data file (workspace)

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FILES AND DATASETS

Root folder:	GR-PLW6-Y07Y11\

Dataset 1:  "loads\loads-dataseries-20xx.mat"
		Matlab/Octave dataset in structured format (see below)

	In the MAT files, the internal structure of the data is as follows:

        DS   :   base structure for series and other per-case data
                '.fname' = (string) source filename from import
                '.year'  = (number) year timestamp of logfiles
                '.month' = (number) month timestamp of logfiles
                '.Pt' = (1x24) daily 24-hour series of 'total' P
                '.Pc' = (1x24) daily 24-hour series of 'net' P
        DD   :   base structure for series and other per-case data
                '.time' = (number) the 'hour' value from the source cell
                '.dateN'  = (number) date-num timestamp of the current value
                '.dateV.v' = (1x6) full timestamp vector of the current value
                '.dateS.s' = (string) full timestamp string of the current value
                '.weekday' = (number) weekday of the current value (1=Monday)
                '.week' = (number) week number starting from 1st value (grouping)
                '.weekN' = (number) true week number for the current date
                '.month' = (number) month number for the current date
                '.year' = (number) year number for the current date
        DP   :   base structure for series and other per-case data
                '.Nsamples' = (number) total length of series
                '.Pt' = (1xN) daily 24-hour series of 'total' P
                '.Pc' = (1xN) daily 24-hour series of 'net' P

Dataset 2:  "weather\weatherdata-100x-xxxxx_2004-2011.mat"
		Matlab/Octave dataset in structured format (see below)

	In the MAT files, the internal structure of the data is as follows:

        TD   :   [Nx5] base data series matrix for 'Air Temperature'
                 (1)  full timestamp, date-time number
                 (2)  station ID, location info
                 (3)  date as number in YYYYMMDD format
                 (4)  time as number in HHMM format
                 (5)  measured temperature value

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LICENSE AGREEMENT

This material was produced primarily for academic research and educational purposes. 
Downloading and using this material implies acceptance of the Creative Commons
License: Attribution-NonCommercial-ShareAlike 4.0 International (BY-NC-SA), 2016.
* http://creativecommons.org/licenses/by-nc-sa/4.0/

Copyright (c) 2016 by Harris V. Georgiou (MSc,PhD) -- http://xgeorgio.info


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