Abstract
For large-scale photovoltaic module monitoring, wireless sensor network technology has been widely used, in which time synchronization is a significant factor. However, there are still outstanding issues in existing time synchronization algorithms for large-scale networking. To this end, this paper proposes a new Adaptive Energy-efficient Reference Broadcasting Synchronization method (AERBS) for wireless sensor networks, aiming to reduce the energy consumption whilst improving the synchronization precision. Moreover, the proposed method can reduce the number of synchronization information exchanges and self-adaptively determine the re-synchronization cycle. Simulation experiments demonstrate that our proposed AERBS outperforms the existing ERBS algorithm, in terms of reducing the synchronization number and the achieved reduction in energy consumption. The algorithm herein can be fully applied in the monitoring of large-scale photovoltaic module. At the same time, as a typical application of IoT (Internet of Things), it also provides a reference for distributed edge computing.
Highlights
In the time synchronization agreement on wireless sensor network, such factors as the scale of the network, data fusion, safety and tracking, synchronization precision, energy consumption, topology and robustness should be taken into consideration
In order to balance the synchronization precision and energy consumption, and to meet the needs of global synchronization, this proposes a forward adaptive time synchronization algorithm based on Adaptive Energy-efficient Reference Broadcasting Synchronization method (AERBS), which, with an adaptive time synchronization method and an efficient reference broadcast synchronization algorithm (ERBS) time synchronization algorithm, effectively meets the requirements of wireless sensor network time synchronization as required by large-scale photovoltaic module monitoring
In order to compare the differences of RBS, time synchronization protocol with Gaussian delay model (TSP-GDM), ERBS and AERBS algorithms in terms of synchronization times, in the above simulation environment, simulation of synchronization times are observed for the four algorithms
Summary
OF RELATED TIME SYNCHRONIZATION ALGORITHM In 2002, J. According to the characteristic that the time delay of PV module monitoring node conforms to the Gaussian delay model, the node clock bias estimation method in the Gaussian model layer is used to solve the problem of node clock offset estimation in the module monitoring area layer On this basis, the local exchange and sharing of data packets in the monitoring subnet is realized by modeling, and the phase offset and frequency offset of nodes are resolved based on the statistical signal characteristics. In the process of solving the clock offset, considering the impact of environmental temperature on the clock offset, the phase offset and frequency offset of the node are resolved based on signal parameter estimation, which can effectively save parts of the network overhead This enables the PV module monitoring network to achieve a high-precision synchronization of the entire network, and provides the basis for photovoltaic module monitoring and fault diagnosis
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