Design of a Cleaning Program for a PV Plant Based on Analysis of Energy Losses
Solar photovoltaic (PV) energy has grown significantly over the past few years. However, despite the increase in installed capacity, this energy source still raises important concerns related to the variability of power production. The short-term effects such as cloud shadowing and supply interruptions, as well as long-term effects such as dust accumulation, seasonal variation, and ageing of PV modules, can cause variability of power production. Therefore, the analysis of all the variability sources in order to provide statistically consistent power production data is an important challenge. This study presents a methodology to analyze data from a PV plant in order to have an independent evaluation of the different effects of variability, identifying dust deposition, and proposing a cost-based optimal cleaning program for a PV plant installed in the northern region of Chile.
Recently, a lot of mobile devices spread rapidly. However, an issue of the battery of the mobile device appeared because the capacity of the battery limits usage time of the mobile device. Therefore, some mobile devices are installed with photovoltaic modules but the photovoltaic module is easily breakdown. Because consumers want to know the breakdown, the diagnostic method focused on mobile device is needed. In this paper, a fault diagnostic method of photovoltaic modules on mobile device is implemented and the algorithm is proposed. The proposed method has high accuracy for diagnostic photovoltaic.