Markovian models of solar power supply for a LTE macro BS

descriptionPublicationkeyboard_double_arrow_right Article , Conference object 01 May 2016 Spain Publisher:IEEEJournal:2016 IEEE International Conference on Communications (ICC)Funded by:EC | 5G-Crosshaul

Authors: Giuseppe Leonardi; Michela Meo; Marco Ajmone Marsan;

doi: 10.1109/icc.2016.7510698

handle: 20.500.12761/277

Markovian models of solar power supply for a LTE macro BS

- Summary
- Subjects
- Metrics

Abstract

We consider a solar power supply for a LTE macro base station (BS) based on a photovoltaic (PV) panel and a battery, and we develop two discrete-time Markov chain (DTMC) models for the analysis and the dimensioning of the system elements (PV panel size and battery capacity). The DTMC models account for the solar irradiance levels in pairs or triples of consecutive days, and for the quantity of energy stored in the battery. From the DTMC steady-state (or transient) solution it is possible to derive performance metrics on which the system dimensioning can be based. We apply our models to BS locations in southern and northern Italy. Results show that the simpler model contains sufficient details for an effective system design.

DOI: 10.1109/ICC.2016.7510698

TRUE

pub

Country

Spain

Related Organizations

Keywords

Energy consumption, Batteries, Radiation effects, Base stations, Computational modeling, Power supplies, Photovoltaic systems

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	12
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%