An energy prediction algorithm for wind-powered wireless sensor networks with energy harvesting. (15th November 2017)

• Record Type: Journal Article
• Authors: Kosunalp, Selahattin
• Is Part Of: Energy. Volume 139(2017)
• Page Start: 1275
• Page End: 1280
• Publication Date: 2017-11-15
• Subjects: Energy harvesting -- Wind power -- Wireless sensor networks -- Energy prediction; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2017.05.175
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Energy harvesting (EH) from environmental energy sources has the potential to ensure unlimited, uncontrollable and unreliable energy for wireless sensor networks (WSNs), bringing a need to predict future energy availability for the effective utilization of the harvested energy. The majority of previous prediction approaches have exploited the diurnal cycle dividing the whole day into equal-length time slots in which predictions were carried out in each slot independently. This is not, however, efficient for wind energy as it exhibits non-controllable behaviour in that the amount of energy to be harvested varies over time. This paper proposes a novel approach to predict the wind energy for EH-WSNs depending on the energy generation profile of latest condition. The distinctive feature of the proposed approach is to consider the recent conditions in current-day, instead of past-day's energy generation profiles. The performance of the proposed algorithm is evaluated using real measurements in comparison with state-of-art approaches. Results show that the proposed strategy significantly outperforms the two popular energy predictors, EWMA and Pro-Energy. Highlights: A new energy prediction model is proposed to supply unlimited energy for nodes. The idea relies on utilization of most recent information about energy generation. Results highlight the efficiency of the scheme outperforming the existing approaches.