http://dx.doi.org/10.1109/ICCEP.2015.7177583URL http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7177583 http://www.scopus.com/inward/record.url?eid=2-s2.0-84946542317&partnerID=40&md5=16052cf0838d1ca3aca33ca53c8eca02 Keywords
maximum power point trackers; photovoltaic power systems; power system simulation; sunlight; synchronisation; wireless sensor networks; MIC PV plants; Matlab-Simulink; PV generator; PV module electric variables; WSN; centralized MPPT system; data losses; efficiency assessment; module integrated converter; power generator;solar irradiation; wireless data transfer network ;wireless sensor networks; Microwave integrated circuits; Radiation effects; Software packages; Temperature measurement; Temperature sensors; Wireless communication; Wireless sensor networks;.Maximum Power Point Tracking; Module Integrated Converter; Photovoltaic systems; Wireless Sensor Network
The paper describes a simulation framework able to accomplish a simulation of a PV plants including a Wireless Sensor Network (WSN). The
developed framework is entirely implemented in a Matlab/Simulink environment, and can be used to accomplish in-depth performance evaluation
of two very different systems interacting between them, the power generator and the wireless data transfer network. As an example, the
developed framework is exploited to investigate the effects of possible data losses, or delays, on the efficiency of a PV generator based
on the Module Integrated Converter concept and equipped with a centralized MPPT system exploiting a WSN to monitor PV modules electric
variables and the distribution of solar irradiation and temperature over the plant area.
We study the problem of data gathering in wireless sensor networks and compare several approaches belonging to different research
fields; in particular, signal processing, compressive sensing, information theory, and networking related data gathering techniques
are investigated. Specifically, we derived a simple analytical model able to predict the energy efficiency and reliability of different
data gathering techniques.Moreover, we carry out simulations to validate our model and to compare the effectiveness of the above
schemes by systematically sampling the parameter space (i.e., number of nodes, transmission range, and sparsity). Our simulation
and analytical results show that there is no best data gathering technique for all possible applications and that the trade-off between
energy consumptions and reliability could drive the choice of the data gathering technique to be used. In this context, our model
could be a useful tool.