Dynamic programming based optimal renewable energy allocation in sustained wireless sensor networks: Fid-Bau Portal

Dynamic programming based optimal renewable energy allocation in sustained wireless sensor networks

Sharma, Amandeep / Kakkar, Ajay

Due to limited energy, conventional battery powered sensor nodes have constraints to meet the present day demanding applications. Although energy harvesting techniques lead to sustained network operation, uncertain energy availability initiates an important research issue of energy management in rechargeable sensor nodes. In the proposed work, an integrated approach of energy assignment principles with adaptive duty cycling has been introduced to efficiently utilize the available energy and to maximize the node performance. The machine learning based Cubist model has been used to pre-estimate the node duty cycle and simulated on the R interface. Real time changes in the computed duty cycle have been implemented by the dynamic programming based adaptive duty cycle algorithm and simulated using the MATLAB interface. The effectiveness of the proposed work has been validated by extensive simulations on real time solar energy profiles in terms of magnitude and stability of sensor's average duty cycle. The proposed algorithm achieves an average duty cycle of 62% to 67% with a limit of 70% maximum duty cycle irrespective of irregular radiation patterns throughout the day as well as for different forecasting horizons. The results also show minimum variation in the estimated and real time energy profiles in stable weather conditions and optimize the duty cycle in irregular weather conditions.