Abstract
Renewable energy
sources can provide the energy requirements of resource-constrained systems due
to their inherent continuous availability. Solar power is a good example of the
most effective ambient energy source. In literature, it exhibits an
uncontrollable but predictable manner which makes the prediction of future
energy availability a critical issue. This study presents a new approach to
estimate the amount of energy that will available in future, depending on the
past energy generation pattern. This approach also considers the fluctuations
in energy generation in the current day. It is inspired by a well-known
algorithm, namely Exponential Weighted Moving-Average (EWMA). The performance
of the proposed scheme has been tested on various real-world scenarios in
comparison to EWMA. The simulation results show that our algorithm provide more
accurate estimation of future energy availability than EWMA.
References
- Akyildiz, F.I., Su, W., Sankarasubramaniam, Y., ve Cayirci, E. (2002) A survey on sensor networks, IEEE Commun. Magazine, 40(8), 102-114. DOI: 10.1109/MCOM.2002.1024422
- Ali, M.I., Al-Hashimi, B.M., Recas, J., ve Atienza, D. (2010) Evaluation and design exploration of solar harvested-energy prediction algorithm, IEEE European Conference in Design, Automation & Test, Germany, Dresden, 142-147. DOI: 10.1109/DATE.2010.5457222
- Andreas., A. ve Stoffel., T. (2015) Elizabeth City State University: Elizabeth City, North Carolina (Data), NREL Report No: DA-5500-56517.
- Buchli, B., Sutton, F., Beutel, J., ve Thiele, L. (2014) Dynamic power management for long-term energy neutral operation of solar energy harvesting systems, ACM Conference on Embedded Network Sensor Systems, Stanford, USA , 31-45. DOI: 10.1145/2668332.2668333
- Cammarano, A., Petrioli, C. ve Spenza, D. (2012) Pro-Energy: a novel energy prediction model for solar and wind energy-harvesting wireless sensor networks, IEEE International Conference on Mobile Ad-Hoc and Sensor Systems, Las Vegas, USA, 75-83. DOI: 10.1109/MASS.2012.6502504
- Kansal, A., Hsu, J., Zahedi, S., ve Srivastava, M.B. (2007) Power management in energy harvesting sensor networks, ACM Transactions on Embedded Computing Systems, 6(4), p.32. DOI: 10.1145/1274858.1274870
- Kosunalp, S. (2015) MAC protocols for energy harvesting wireless sensor networks: Survey, ETRI Journal, 37(4), 804-812. DOI: 10.4218/etrij.15.0115.0017
- Kosunalp, S. (2016) A new energy prediction algorithm for energy-harvesting wireless sensor networks with q-learning, IEEE Access, 4, 5755-5763. DOI: 10.1109/ACCESS.2016.2606541
- Kosunalp, S. (2016) A performance evaluation of solar energy prediction approaches for energy-harvesting wireless sensor networks, International Journal of Applied Mathematics, Electronics and Computers, 4, 424-427. DOI: 10.18100/ijamec.266963
- Kosunalp, S., Chu, Y., Mitchell, P.D., Grace, D., Clarke, T., (2016) Use of q-learning approaches for practical medium access control in wireless sensor networks, Engineering Applications of Artificial Intelligence, 55, 146-154. DOI: 10.1016/j.engappai.2016.06.012
- Kosunalp, S. (2017) An energy prediction algorithm for wind-powered wireless sensor networks with energy harvesting, Energy, 139, 1275-1280. DOI: 10.1016/j.energy.2017.05.175
- Noh, D.K. ve Kang, K. (2011) Balanced energy allocation scheme for a solar-powered sensor system and its effects on network-wide performance, Journal of Computer and System Sciences, 77, 917-932. DOI: 10.1016/j.jcss.2010.08.008
- J.C. Piorno, C. Bergonzini, D. Atienza & T.S. Rosing, “Prediction and management in energy harvested wireless sensor nodes,” In Proc. IEEE Wireless VITAE’09, 2009, pp. 6-10. DOI: 10.1109/WIRELESSVITAE.2009.5172412
- Sudevalayam, S., and Kulkarni, P. (2011) Energy harvesting sensor nodes: survey and implications, IEEE Commun. Survey Tutorials, 13(3), 443-461. DOI: 10.1109/SURV.2011.060710.00094
- Tuna, G., Gungor, V.C., ve Gulez, K. (2013a) Wireless sensor networks for smart grid applications: a case study on link reliability and node lifetime evaluations in power distribution systems, International Journal of Distributed Sensor Networks, vol. 2013, Article ID 796248. DOI: 10.1155/2013/796248
- Tuna, G., Gungor, V.C., ve Gulez, K. (2013b) Energy harvesting techniques for industrial wireless sensor networks, In Industrial Wireless Sensor Networks: Applications, Protocols, Standards and Products, 119-136
Abstract
Yenilenebilir enerji kaynakları doğasal olarak
sürekli mevcut olduklarından, kısıtlı kaynaklara sahip sistemlerin enerji
ihtiyaçlarını gidermek için önemli bir yer tutmaktadır. Güneş enerjisi en çok
kullanılan çevresel enerji kaynaklarına güzel bir örnektir. Güneş enerjisi
kontrol edilemeyen ama tahmin edilebilen bir enerji kaynağı olarak literatürde
yer almıştır. Güneş enerji miktarının gelecek için tahmini kritik bir konudur.
Bu çalışmada, geçmişte üretilen güneş enerji miktarına bakarak gelecekte muhtemelen
üretilecek güneş enerji miktarını tahmin eden yeni bir algoritma
geliştirilmiştir. Bu algoritma aynı zamanda tahmin yapılan gün içerisindeki
üretilen enerji miktarındaki değişimleri de göz önüne almaktadır. Önerilen
yaklaşım literatürde çokça temel alınan Exponential
Weighted Moving-Average (EWMA) algoritmasından esinlenmiştir. Gün
içerisinde güneş enerjisindeki dalgalanmaları göz önüne alan farklı senaryolar
üzerinde önerilen yaklaşımın performansı EWMA ile karşılaştırılarak
sunulmuştur. Gerçekleştirilen benzetimler önerilen algoritmanın güneş
enerjisindeki dalgalanmaları EWMA’ dan daha iyi olarak tahmin ettiğini
göstermektedir.
References
- Akyildiz, F.I., Su, W., Sankarasubramaniam, Y., ve Cayirci, E. (2002) A survey on sensor networks, IEEE Commun. Magazine, 40(8), 102-114. DOI: 10.1109/MCOM.2002.1024422
- Ali, M.I., Al-Hashimi, B.M., Recas, J., ve Atienza, D. (2010) Evaluation and design exploration of solar harvested-energy prediction algorithm, IEEE European Conference in Design, Automation & Test, Germany, Dresden, 142-147. DOI: 10.1109/DATE.2010.5457222
- Andreas., A. ve Stoffel., T. (2015) Elizabeth City State University: Elizabeth City, North Carolina (Data), NREL Report No: DA-5500-56517.
- Buchli, B., Sutton, F., Beutel, J., ve Thiele, L. (2014) Dynamic power management for long-term energy neutral operation of solar energy harvesting systems, ACM Conference on Embedded Network Sensor Systems, Stanford, USA , 31-45. DOI: 10.1145/2668332.2668333
- Cammarano, A., Petrioli, C. ve Spenza, D. (2012) Pro-Energy: a novel energy prediction model for solar and wind energy-harvesting wireless sensor networks, IEEE International Conference on Mobile Ad-Hoc and Sensor Systems, Las Vegas, USA, 75-83. DOI: 10.1109/MASS.2012.6502504
- Kansal, A., Hsu, J., Zahedi, S., ve Srivastava, M.B. (2007) Power management in energy harvesting sensor networks, ACM Transactions on Embedded Computing Systems, 6(4), p.32. DOI: 10.1145/1274858.1274870
- Kosunalp, S. (2015) MAC protocols for energy harvesting wireless sensor networks: Survey, ETRI Journal, 37(4), 804-812. DOI: 10.4218/etrij.15.0115.0017
- Kosunalp, S. (2016) A new energy prediction algorithm for energy-harvesting wireless sensor networks with q-learning, IEEE Access, 4, 5755-5763. DOI: 10.1109/ACCESS.2016.2606541
- Kosunalp, S. (2016) A performance evaluation of solar energy prediction approaches for energy-harvesting wireless sensor networks, International Journal of Applied Mathematics, Electronics and Computers, 4, 424-427. DOI: 10.18100/ijamec.266963
- Kosunalp, S., Chu, Y., Mitchell, P.D., Grace, D., Clarke, T., (2016) Use of q-learning approaches for practical medium access control in wireless sensor networks, Engineering Applications of Artificial Intelligence, 55, 146-154. DOI: 10.1016/j.engappai.2016.06.012
- Kosunalp, S. (2017) An energy prediction algorithm for wind-powered wireless sensor networks with energy harvesting, Energy, 139, 1275-1280. DOI: 10.1016/j.energy.2017.05.175
- Noh, D.K. ve Kang, K. (2011) Balanced energy allocation scheme for a solar-powered sensor system and its effects on network-wide performance, Journal of Computer and System Sciences, 77, 917-932. DOI: 10.1016/j.jcss.2010.08.008
- J.C. Piorno, C. Bergonzini, D. Atienza & T.S. Rosing, “Prediction and management in energy harvested wireless sensor nodes,” In Proc. IEEE Wireless VITAE’09, 2009, pp. 6-10. DOI: 10.1109/WIRELESSVITAE.2009.5172412
- Sudevalayam, S., and Kulkarni, P. (2011) Energy harvesting sensor nodes: survey and implications, IEEE Commun. Survey Tutorials, 13(3), 443-461. DOI: 10.1109/SURV.2011.060710.00094
- Tuna, G., Gungor, V.C., ve Gulez, K. (2013a) Wireless sensor networks for smart grid applications: a case study on link reliability and node lifetime evaluations in power distribution systems, International Journal of Distributed Sensor Networks, vol. 2013, Article ID 796248. DOI: 10.1155/2013/796248
- Tuna, G., Gungor, V.C., ve Gulez, K. (2013b) Energy harvesting techniques for industrial wireless sensor networks, In Industrial Wireless Sensor Networks: Applications, Protocols, Standards and Products, 119-136
Details
| Primary Language | Turkish |
|---|---|
| Subjects | Engineering |
| Journal Section | Research Articles |
| Authors | |
| Publication Date | April 24, 2018 |
| Submission Date | February 18, 2016 |
| Acceptance Date | April 9, 2018 |
| Published in Issue | Year 2018 Volume: 23 Issue: 1 |
Cite
Cited By
Investigation of Energy Generation Potential of Solar Panels Placed as Shutters for Windows in Residential
Electric Power Components and Systems
https://doi.org/10.1080/15325008.2023.2246961
Türkiye’nin Güneş Enerjisi Potansiyeli ve İskenderun için Örnek Üretim Projeksiyonu
Çukurova Üniversitesi Mühendislik Fakültesi Dergisi
https://doi.org/10.21605/cukurovaumfd.1095104
Announcements:
30.03.2021-Beginning with our April 2021 (26/1) issue, in accordance with the new criteria of TR-Dizin, the Declaration of Conflict of Interest and the Declaration of Author Contribution forms fulfilled and signed by all authors are required as well as the Copyright form during the initial submission of the manuscript. Furthermore two new sections, i.e. ‘Conflict of Interest’ and ‘Author Contribution’, should be added to the manuscript. Links of those forms that should be submitted with the initial manuscript can be found in our 'Author Guidelines' and 'Submission Procedure' pages. The manuscript template is also updated. For articles reviewed and accepted for publication in our 2021 and ongoing issues and for articles currently under review process, those forms should also be fulfilled, signed and uploaded to the system by authors.