Environmental Data Processing by Clustering Methods for Energy Forecast and Planning

2011

This paper presents a statistical approach based on the k-means clustering technique to manage environmental sampled data to evaluate and to forecast of the energy deliverable by different renewable sources in a given site. In particular, wind speed and solar irradiance sampled data are studied in association to the energy capability of a wind generator and a photovoltaic (PV) plant, respectively. The proposed method allows the sub-sets of useful data, describing the energy capability of a site, to be extracted from a set of experimental observations belonging the considered site. The data collection is performed in Sicily, in the south of Italy, as case study. As far as the wind generation…

Comparative Analysis of Spatial Interpolation Methods in the Mediterranean Area: Application to Temperature in Sicily

2015

An exhaustive comparison among different spatial interpolation algorithms was carried out in order to derive annual and monthly air temperature maps for Sicily (Italy). Deterministic, data-driven and geostatistics algorithms were used, in some cases adding the elevation information and other physiographic variables to improve the performance of interpolation techniques and the reconstruction of the air temperature field. The dataset is given by air temperature data coming from 84 stations spread around the island of Sicily. The interpolation algorithms were optimized by using a subset of the available dataset, while the remaining subset was used to validate the results in terms of the accur…

CAMBIAMENTI CLIMATICI E EROSIONE IDRICA: UN’APPLICAZIONE AL BACINO DEL COMUNELLI, SICILIA

2008

CONFRONTO TRA DIVERSE TECNICHE DI INTERPOLAZIONE DI DATI DI PRECIPITAZIONE E TEMPERATURA PER LA CREAZIONE DI DATASET DI SERIE STORICHE MENSILI COMPLE…

2010

THE PROBLEM OF MISSING DATA IN HYDROCLIMATIC TIME SERIES. APPLICATION OF SPATIAL INTERPOLATION TECHNIQUES TO CONSTRUCT A COMPREHENSIVE ARCHIVE OF HYD…

2011

Planning, management and e ective control of water resource systems, require a considerable amount of hydrological data variables such as rainfall, temperature, stream- ow, etc.. Such data are required when a hydrological model has to be developed, as well. Very often hydrological data sequences at a given gauge have gaps or are incomplete, or are not characterized by a good quality or are not su ciently length. This can severely a ect, for example, the reliability of the design of a hydropower plant, the construction of dams, etc. Furthermore, the problem of missing values is a common obstacle in time series analysis and speci cally in the context of rainfall, temperature and rainfall runo…

Mapping the annual runoff data in Sicily using a geostatistical approach

2011

The availability of reliable and long time series of runoff data is fundamental for most of the hydrological analyses and for the assessment and the management of water resources even in condition of global climatic change. However, hydrologic data set are often characterized by a short duration and also suffer from missing data values, mainly due to malfunctioning of gauging stations for a specific period. In order to overcome this problem and obtain long and continuous runoff time series, different models and methods have been previously developed and proposed. While some models, used to extent the streamflow record, are conceptual, empirical, regressive models based on the rainfall input…