An 18 kW solar array research facility for fault detection experiments

Abstract

Monitoring utility-scale solar arrays was shown to minimize cost of maintenance and help optimize the performance of the array under various conditions. In this paper, we describe the design of an 18 kW experimental facility that consists of 104 panels fitted with smart monitoring devices. Each of these devices embeds sensors, wireless transceivers, and relays that enable continuous monitoring, fault detection, and real-time connection topology changes. The facility enables networked data exchanges via the use of wireless data sharing with servers, fusion and control centers, and mobile devices. Research planned at this stage includes developing machine learning methods for fault detection. Preliminary simulation results on fault detection using machine learning are given in this paper.

Optimizing Solar Power Using Array Topology Reconfiguration With Regularized Deep Neural Networks

“…The authors of [10] and [37] propose a reconfiguration algorithm similar to the one proposed in this work. In the paper, the authors first perform panel fault detection [1], [2] to classify the healthy and faulty modules. Reconfiguration is then performed based upon which topology produces the maximum operating power for a given irradiance profile.…”

“…Modern cyber-physical PV systems [1] are equipped with servers that can communicate wirelessly with the solar array. Every PV panel is augmented with specialized sensors or smart monitoring devices (SMDs) [2] which can communicate to the central server as well the neighbouring panels. The SMDs also support topology reconfiguration by providing signals to the switch bank which modifies the electrical connections to realize different topologies.…”

“…Modern PV arrays [1] are augmented with inexpensive, computer controlled, panel-level sensors and relay actuators [2] to control electrical connections between panels. The usage of such equipment allows the array to be viewed as a cyber-physical system that can be accessed remotely and monitored in real-time with customized algorithms providing scope for PV data analytics.…”

Dropout and Pruned Neural Networks for Fault Classification in Photovoltaic Arrays

“…The presence of such SMDs renders the solar array system as a cyber-physical system [7] that can be monitored and controlled in real-time with algorithms and software. Figure 1 shows a cyber-physical 18 kW PV testbed described in [8].…”