Background: Nowadays, Wireless Sensor Network (WSN) plays an important role in
various fields. The limited power capability of the sensor nodes in the WSN brings constraints on
the performance of the network. Low Energy Adaptive Clustering Hierarchy (LEACH) is a promising
protocol for WSN that suffers from higher energy consumption.
Objective: The primary objective of this study is to give an alternate harvesting resource power to
sensor nodes in the LEACH algorithm which can be equally capable of providing the same or
sometimes better results.
Methods: This study is based on real-time meteorological data. A real-time wind speed data is
taken for the starting of a day to the end of the day on an hourly basis from the weather forecast.
Now to convert this rotational energy into electrical energy, we used two types of wind turbines.
For the proposed methodology, a micro wind turbine generator and 300watt wind turbine are used.
Then this converted electrical energy is given to sensor nodes. For the clustering, the wind power
operated nodes are given maximum preference to be elected as the cluster heads based on realtime
wind meteorological data. We consider 10 wind-powered sensor nodes. As we increase the
number of wind-powered sensor nodes in the network, the performance is increased in terms of a
lifetime but then increases the complexity of the network. These wind-powered nodes remain
alive in the network. Since the deployment of the sensor nodes is random, each simulation runs for
5 times and the average of first node dead, half node dead and last node dead is considered.
Results: The experimental results for the micro wind turbine generator are compared based on
with and without the MPPT controller. MPPT controller gives the maximum power by using the
tip speed ratio control, power signal feedback control, and hill climb search control method.
Therefore, the network lifetime should be higher for the MPPT based wind generator. Network
lifetime and Energy consumption are compared for a micro wind turbine generator and 300watt
wind turbine. Finally, the performance of the proposed system is compared with the modified solar
LEACH implemented using real-time meteorological data.
Conclusion: This paper has investigated the wind-based LEACH which uses the real-time meteorological
data for the selection of the cluster head. Two types of wind generators are considered
for the implementation and it is found that the performance of the commercial 300W wind turbine
and the micro wind turbine with and without MPPT is almost similar since the data from both
wind turbines are given on hourly basis. The performance of the wLEACH is compared with the
sLEACH which shows that the network lifespan of the wLEACH is also nearly the same compared
to the sLEACH. However, it was found that wind power generation is cheaper and efficient
than solar power generation. Therefore, it is inferred that this proposed wLEACH provides a costefficient