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Evaluation and Design Exploration of Solar Harvested-Energy Prediction Algorithm

Evaluation and Design Exploration of Solar Harvested-Energy Prediction Algorithm
Evaluation and Design Exploration of Solar Harvested-Energy Prediction Algorithm
To respond to variations in solar energy, harvested-energy prediction is essential to harvested-energy management approaches. The effectiveness of such approaches is dependent on both the achievable accuracy and computation overhead of prediction algorithm implementation. This paper presents detailed evaluation of a recently reported solar energy prediction algorithm to determine empirical bounds on achievable accuracy and implementation overhead using an effective error evaluation technique. We evaluate the algorithm performance over varying prediction horizons and propose guidelines for algorithm parameter selection across different real solar energy profiles to simplify implementation. The prediction algorithm computation overhead is measured on actual hardware to demonstrate prediction accuracy-cost trade-off. Finally, we motivate the basis for dynamic prediction algorithm and show that more than 10% increase in prediction accuracy can be achieved compared to static algorithm.
Energy Harvesting, Solar Energy Prediction, Wireless Sensor Node, MSP430, Harvested-Energy Management
Ali, Mustafa
f1794260-ca94-480a-ae59-92c477c4c8da
Al-Hashimi, Bashir
0b29c671-a6d2-459c-af68-c4614dce3b5d
Recas, Joaquin
5babea0d-b33e-4b63-b041-76df8b04d1c5
Atienza, David
61fa5a27-fe94-4e15-b380-3caf4d4f3e7f
Ali, Mustafa
f1794260-ca94-480a-ae59-92c477c4c8da
Al-Hashimi, Bashir
0b29c671-a6d2-459c-af68-c4614dce3b5d
Recas, Joaquin
5babea0d-b33e-4b63-b041-76df8b04d1c5
Atienza, David
61fa5a27-fe94-4e15-b380-3caf4d4f3e7f

Ali, Mustafa, Al-Hashimi, Bashir, Recas, Joaquin and Atienza, David (2010) Evaluation and Design Exploration of Solar Harvested-Energy Prediction Algorithm. DATE 2010 - Design Automation and Test in Europe 2010, Dresden, Germany. 08 - 12 Mar 2010. (Submitted)

Record type: Conference or Workshop Item (Other)

Abstract

To respond to variations in solar energy, harvested-energy prediction is essential to harvested-energy management approaches. The effectiveness of such approaches is dependent on both the achievable accuracy and computation overhead of prediction algorithm implementation. This paper presents detailed evaluation of a recently reported solar energy prediction algorithm to determine empirical bounds on achievable accuracy and implementation overhead using an effective error evaluation technique. We evaluate the algorithm performance over varying prediction horizons and propose guidelines for algorithm parameter selection across different real solar energy profiles to simplify implementation. The prediction algorithm computation overhead is measured on actual hardware to demonstrate prediction accuracy-cost trade-off. Finally, we motivate the basis for dynamic prediction algorithm and show that more than 10% increase in prediction accuracy can be achieved compared to static algorithm.

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More information

Submitted date: 7 December 2010
Additional Information: Event Dates: 8-12 March 2010
Venue - Dates: DATE 2010 - Design Automation and Test in Europe 2010, Dresden, Germany, 2010-03-08 - 2010-03-12
Keywords: Energy Harvesting, Solar Energy Prediction, Wireless Sensor Node, MSP430, Harvested-Energy Management
Organisations: Electronic & Software Systems

Identifiers

Local EPrints ID: 268299
URI: http://eprints.soton.ac.uk/id/eprint/268299
PURE UUID: bb962d9d-2fba-4085-9c03-1becd42ae630

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Date deposited: 07 Dec 2009 14:34
Last modified: 14 Mar 2024 09:07

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Contributors

Author: Mustafa Ali
Author: Bashir Al-Hashimi
Author: Joaquin Recas
Author: David Atienza

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