In spite of the large use of batteries throughout the years, both in photovoltaic systems and in other uses, there are still no comprehensive analyses in ageing studies and, when they exist, statistics turn out to be limited. In this sense, this macro-grid is a unique experience, since the experiment is already composed of 1600 identical stand-alone photovoltaic systems and almost 10 years of data taking on 10 minute interval for the main magnitudes. In this paper, it is proposed a method for the estimation of the state of the health for lead-acid batteries, based on the evolution in time of the corresponding voltage distribution. The study is based on the statistical analysis of such a distribution with a monthly frequency.
Abstract.Batteries have been used in a lot of different applications for a quite large time period, in particular in solar photovoltaic energy. In spite of this fact, their ageing mechanisms turn out to be still deeply out of control. We show in this paper the results of applying the evolution of a preliminary method for the estimation of lead-acid batteries state of health which is based on the Root Mean Square Error (RMSE) between voltage distributions throughout a time period of nine years. A complete set of batteries, concerning the main parameters that could influence their lifetime, was analised.
The paper describes an international cooperation project for depressed zones. The aim of the project is to supply electricity and hot water in a refuge for around 150 children in El Alto (Bolivia) with solar energy.
Abstract. During the winter of 2009, technicians inform about how during a visual inspection they detect failures in the surface of different solar panels. The inspection was not casual, but due to problems with the level of charge of the batteries. Because of the aspect on the failure we will name it "spiders" (arañitas). But other anomalies, associated to the expected ageing, have been observed, like panels with blued cells, browed surface and others. In the present note, we will describe each of the observed failures, their possible causes and their effect on the solar panel operation. The full data sample we used has been obtained either on dedicated laboratory test (PAO, USC, CIEMAT) or by direct measurement in the field.
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