This chapter deals with a statistical approach to manage sampled data coming from a photovoltaic installation. The proposed method adopts kmeans clustering and the normal density probability distribution. This allows the problem of PV plant energy assessment to be simplified with respect to obtaining the desired information by managing a large amount of experimental observations. The proposed methods represent useful tools for an appropriate energy planning in distributed generation systems.

Data Clustering for Accurate Energy Planning of a Photovoltaic Plant

A Di Piazza;G Vitale
2015

Abstract

This chapter deals with a statistical approach to manage sampled data coming from a photovoltaic installation. The proposed method adopts kmeans clustering and the normal density probability distribution. This allows the problem of PV plant energy assessment to be simplified with respect to obtaining the desired information by managing a large amount of experimental observations. The proposed methods represent useful tools for an appropriate energy planning in distributed generation systems.
2015
Istituto di Studi sui Sistemi Intelligenti per l'Automazione - ISSIA - Sede Bari
Inglese
2
18
16
978-1-4438-8377-1
http://www.cambridgescholars.com/download/sample/63048
Cambridge scholars press
Newcastle
REGNO UNITO DI GRAN BRETAGNA
Sì, ma tipo non specificato
Photovoltaic energy
Distributed generation
Energy Planning
Renewable energy
Statistics.
3
02 Contributo in Volume::02.01 Contributo in volume (Capitolo o Saggio)
268
none
A. Di Piazza; M. Carmela Di Piazza; G. Vitale
info:eu-repo/semantics/bookPart
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/315849
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