research-article

Optimal Power Management with Guaranteed Minimum Energy Utilization for Solar Energy Harvesting Systems

Authors:

Bernhard Buchli,

Stefan Draskovic,

Pratyush Kumar,

Lothar ThieleAuthors Info & Claims

ACM Transactions on Embedded Computing Systems (TECS), Volume 18, Issue 4

Article No.: 30, Pages 1 - 26

https://doi.org/10.1145/3317679

Published: 10 June 2019 Publication History

Abstract

In this work, we present a formal study on optimizing the energy consumption of energy harvesting embedded systems. To deal with the uncertainty inherent in solar energy harvesting systems, we propose the Stochastic Power Management (SPM) scheme, which builds statistical models of harvested energy based on historical data. The proposed stochastic scheme maximizes the lowest energy consumption across all time intervals while giving strict probabilistic guarantees on not encountering battery depletion. For situations where historical data is not available, we propose the use of (i) a Finite Horizon Control (FHC) scheme and (ii) a non-uniformly scaled energy estimator based on an astronomical model, which is used by FHC. Under certain realistic assumptions, the FHC scheme can provide guarantees on minimum energy usage that can be supported over all times. We further propose and evaluate a piece-wise linear approximation of FHC for efficient implementation in resource-constrained embedded systems. With extensive experimental evaluation for eight publicly available datasets and two datasets collected with our own deployments, we quantitatively establish that the proposed solutions are highly effective at providing a guaranteed minimum service level and significantly outperform existing solutions.

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Cited By

Vogelgesang KRaffeck PWägemann PHerfet TSchröder-Preikschat W(2024)WIP: Towards a Transactional Network Stack for Power-Failure Resilience2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)10.1109/CCNC51664.2024.10454781(803-806)Online publication date: 6-Jan-2024
https://doi.org/10.1109/CCNC51664.2024.10454781
Giordano MCortesi SMekikis PCrabolu MBellusci GMagno M(2023)Energy-Aware Adaptive Sampling for Self-Sustainability in Resource-Constrained IoT DevicesProceedings of the 11th International Workshop on Energy Harvesting & Energy-Neutral Sensing Systems10.1145/3628353.3628545(65-71)Online publication date: 12-Nov-2023
https://dl.acm.org/doi/10.1145/3628353.3628545
Rabah SZaier ALloret JDahman H(2023)Improving IoT Network Lifetime Through HHO-MPPT optimized Solar Energy Harvesting2023 IEEE International Workshop on Mechatronic Systems Supervision (IW_MSS)10.1109/IW_MSS59200.2023.10369996(1-6)Online publication date: 2-Nov-2023
https://doi.org/10.1109/IW_MSS59200.2023.10369996
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Optimal Power Management with Guaranteed Minimum Energy Utilization for Solar Energy Harvesting Systems

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Published In

cover image ACM Transactions on Embedded Computing Systems

ACM Transactions on Embedded Computing Systems Volume 18, Issue 4

July 2019

217 pages

ISSN:1539-9087

EISSN:1558-3465

DOI:10.1145/3340300

Editor:
Sandeep K. Shukla
Indian Institute of Technology, India

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Copyright © 2019 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

Journal Family

ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 10 June 2019

Accepted: 01 March 2019

Revised: 01 September 2018

Received: 01 August 2016

Published in TECS Volume 18, Issue 4

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Cited By

Vogelgesang KRaffeck PWägemann PHerfet TSchröder-Preikschat W(2024)WIP: Towards a Transactional Network Stack for Power-Failure Resilience2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)10.1109/CCNC51664.2024.10454781(803-806)Online publication date: 6-Jan-2024
https://doi.org/10.1109/CCNC51664.2024.10454781
Giordano MCortesi SMekikis PCrabolu MBellusci GMagno M(2023)Energy-Aware Adaptive Sampling for Self-Sustainability in Resource-Constrained IoT DevicesProceedings of the 11th International Workshop on Energy Harvesting & Energy-Neutral Sensing Systems10.1145/3628353.3628545(65-71)Online publication date: 12-Nov-2023
https://dl.acm.org/doi/10.1145/3628353.3628545
Rabah SZaier ALloret JDahman H(2023)Improving IoT Network Lifetime Through HHO-MPPT optimized Solar Energy Harvesting2023 IEEE International Workshop on Mechatronic Systems Supervision (IW_MSS)10.1109/IW_MSS59200.2023.10369996(1-6)Online publication date: 2-Nov-2023
https://doi.org/10.1109/IW_MSS59200.2023.10369996
Kraemer FAsad HBach KRenner B(2023)Online Machine Learning for 1-Day-Ahead Prediction of Indoor Photovoltaic EnergyIEEE Access10.1109/ACCESS.2023.326781011(38417-38425)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3267810
Dobiáš PCasseau ESinnen O(2023)Online fault tolerant energy-aware algorithm for CubeSatsSustainable Computing: Informatics and Systems10.1016/j.suscom.2023.10085338(100853)Online publication date: Apr-2023
https://doi.org/10.1016/j.suscom.2023.100853
Veiga TAsad HKraemer FBach K(2023)Towards containerized, reuse-oriented AI deployment platforms for cognitive IoT applicationsFuture Generation Computer Systems10.1016/j.future.2022.12.029142:C(4-13)Online publication date: 1-May-2023
https://dl.acm.org/doi/10.1016/j.future.2022.12.029
Li YKang WZhou KQiu KZhao W(2022)Experimental Demonstration of STT-MRAM-based Nonvolatile Instantly On/Off System for IoT Applications: Case StudiesACM Transactions on Embedded Computing Systems10.1145/354619322:2(1-24)Online publication date: 5-Jul-2022
https://dl.acm.org/doi/10.1145/3546193
Espe AHaugan TMathisen G(2022)Magnetic Field Energy Harvesting in RailwayIEEE Transactions on Power Electronics10.1109/TPEL.2022.314143737:7(8659-8668)Online publication date: Jul-2022
https://doi.org/10.1109/TPEL.2022.3141437
Ahmed RDraskovic SThiele L(2022)Stochastic Guarantees for Adaptive Energy Harvesting SystemsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2022.319851941:11(3614-3625)Online publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1109/TCAD.2022.3198519
Stricker NThiele L(2022)Accurate Onboard Predictions for Indoor Energy Harvesting using Random Forests2022 11th Mediterranean Conference on Embedded Computing (MECO)10.1109/MECO55406.2022.9797188(1-6)Online publication date: 7-Jun-2022
https://doi.org/10.1109/MECO55406.2022.9797188
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