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Open AccessArticle

Efficient Wind Speed Forecasting for Resource-Constrained Sensor Devices

AtlanTTic, Universidade de Vigo, 36310 Vigo, Spain
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: Geoff Merrett
Sensors 2021, 21(3), 983;
Received: 30 November 2020 / Revised: 22 January 2021 / Accepted: 29 January 2021 / Published: 2 February 2021
(This article belongs to the Special Issue Green Sensors Networking)
Wind energy harvesting technology is one of the most popular power sources for wireless sensor networks. However, given its irregular nature, wind energy availability experiences significant variations and, therefore, wind-powered devices need reliable forecasting models to effectively adjust their energy consumption to the dynamics of energy harvesting. On the other hand, resource-constrained devices with limited hardware capacities (such as sensor nodes) must resort to forecasting schemes of low complexity for their predictions in order to avoid squandering their scarce power and computing capabilities. In this paper, we present a new efficient ARIMA-based forecasting model for predicting wind speed at short-term horizons. The performance results obtained using real data sets show that the proposed ARIMA model can be an excellent choice for wind-powered sensor nodes due to its potential for achieving accurate enough predictions with very low computational burden and memory overhead. In addition, it is very simple to setup, since it can dynamically adapt to varying wind conditions and locations without requiring any particular reconfiguration or previous data training phase for each different scenario. View Full-Text
Keywords: energy harvesting; wind energy; energy management; energy prediction energy harvesting; wind energy; energy management; energy prediction
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MDPI and ACS Style

Herrería-Alonso, S.; Suárez-González, A.; Rodríguez-Pérez, M.; Rodríguez-Rubio, R.F.; López-García, C. Efficient Wind Speed Forecasting for Resource-Constrained Sensor Devices. Sensors 2021, 21, 983.

AMA Style

Herrería-Alonso S, Suárez-González A, Rodríguez-Pérez M, Rodríguez-Rubio RF, López-García C. Efficient Wind Speed Forecasting for Resource-Constrained Sensor Devices. Sensors. 2021; 21(3):983.

Chicago/Turabian Style

Herrería-Alonso, Sergio; Suárez-González, Andrés; Rodríguez-Pérez, Miguel; Rodríguez-Rubio, Raúl F.; López-García, Cándido. 2021. "Efficient Wind Speed Forecasting for Resource-Constrained Sensor Devices" Sensors 21, no. 3: 983.

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