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Decrease and reset for power-down

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Abstract

We consider the classical power management problem: There is a system or “device” which has two states—ON and OFF—and one has to develop a control algorithm for changing between these states as to minimize cost (energy or some other hybrid cost) when given a sequence of service requests. We analyze this problem in terms of online competitive analysis to obtain worst-case guarantees. Although an optimal 2-competitive algorithm exists, that algorithm does not result in good performance in many practical situations, especially in case the device is not used frequently. To take the frequency of device usage into account, we construct an algorithm based on the concept of “slackness degree”. Then by relaxing the worst-case competitive ratio of our online algorithm to \(2 + \varepsilon\), where \(\varepsilon\) is an arbitrary small constant, we make the algorithm flexible to slackness. The algorithm thus automatically tunes itself to slackness degree and gives better performance than the optimal 2-competitive algorithm for real world inputs. In addition to worst-case competitive ratio analysis, a queueing model analysis is given and computer simulations are reported, confirming that the performance of the algorithm is high. We show how the approach can be generalized to a situation where the system has a number of intermediate states. Our model can be used to facilitate renewable energy integration into the electrical grid and we highlight that an online competitive approach can yield techniques for grid resiliency.

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References

  1. Ackooij, W., Danti Lopez, I., Frangion, A., Lacalandra, F., Tahanan, M.: Large-scale unit commitment under uncertainty: an updated literature survey. Ann. Oper. Res. 271(1), 11–85 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  2. Agarwal, Y., Hodges, S., Chandra, R., Scott, J., Bahl, P., Gupta, R.: Somniloquy: augmenting network interfaces to reduce pc energy usage. In: Proceedings of the 6th USENIX Symposium on Networked Systems Design and Implementation, NSDI’09, pp. 365–380, Berkeley, CA, USA, 2009. USENIX Association

  3. Agarwal, Y., Savage, S., Gupta, R.: Sleepserver: a software-only approach for reducing the energy consumption of PCs within enterprise environments. In: Proceedings of the 2010 USENIX Conference on USENIX Annual Technical Conference, USENIXATC’10, pp. 22–22, Berkeley, CA, USA, (2010). USENIX Association

  4. Albers, S.: Energy-efficient algorithms. Commun. ACM 53(5), 86–96 (2010)

    Article  Google Scholar 

  5. Alqahtani, B.J., Patiño-Echeverri, D.: Integrated solar combined cycle power plants: paving the way for thermal solar. Appl Energy 169, 927–936 (2016)

    Article  Google Scholar 

  6. Andro-Vasko, J., Avasarala, S.R., Bein, W.: Continuous state power-down systems for renewable energy management. In: Latifi, S. (ed.) Information Technology: New Generations: 15th International Conference on Information Technology, vol. 738, pp. 701–707. Springer International Publishing (2018)

  7. Andro-Vasko, J., Bein, W., Nyknahad, D., Ito, H.: Evaluation of online power-down algorithms. In: 2015 12th International Conference on Information Technology—New Generations, vol. 1346, pp. 473–478 (2015)

  8. Andro-Vasko, J., Bein, W., Pathak, G.: A heuristic for state power down systems with few states. In: Latifi, S. (ed.) Information Technology: New Generations: 14th International Conference on Information Technology, vol. 1, pp. 877–882. Springer International Publishing (2018)

  9. Andro-Vasko, J., Bein, W., Ito, H.: Energy efficiency and renewable energy management with multi-state power-down systems. Information 10(2), 44 (2019)

    Article  Google Scholar 

  10. Augustine, J., Irani, S., Swamy, C.: Optimal power-down strategies. In: IEEE Symposium on Foundations of Computer Science, pp. 530–539. Cambridge University Press, (2004)

  11. Augustine, J., Irani, S., Swamy, C.: Optimal power-down strategies. SIAM J. Comput. 37(5), 1499–1516 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  12. Bein, W., Madan, B.B., Bein, D, Nyknahad, D.: Algorithmic approaches for a dependable smart grid. In: Latifi, S. (ed.) Information Technology: New Generations: 13th International Conference on Information Technology, vol. 448, pp. 677–687. Springer International Publishing (2016)

  13. Ben-Tal, A., Bertsimas, D., Brown, D.B.: A soft robust model for optimization under ambiguity. Oper. Res. 58(4, Part 2 of 2), 1220–1234 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  14. Borodin, A., El-Yaniv, R.: Online Computation and Competitive Analysis. Cambridge University Press (1998)

    MATH  Google Scholar 

  15. Chung, E., Benini, L., Bogliolo, A., Lu, Y., De Micheli, G.: Dynamic power management for nonstationary service requests. IEEE Trans. Comput. 51(11), 1345–1360 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  16. Budischak, C., Sewell, D.A., Thomson, H., Mach, L., Veron, D.E., Kempton, W.: Cost-minimized combinations of wind power, solar power and electrochemical storage, powering the grid up to 99.9% of the time. J. Power Sources 225, 60–74 (2013)

    Article  Google Scholar 

  17. de Mars, P., O'Sullivan, A., Keppo, I.: Estimating the impact of variable renewable energy on base-load cycling in the GB power system. Energy 195, 9 (2020)

    Google Scholar 

  18. Eggers, S.J., Katz, R.H.: Evaluating the performance of four snooping cache coherency protocols. In: Proc. 16th International Symp. on Computer Architecture (ISCA). IEEE, pp. 2–15 (1989)

  19. Hall, R., Erdélyi, R., Hanna, E., Jones, J.M., Scaife, A.A.: Drivers of North Atlantic Polar front jet stream variability. Int. J. Climatol. 35, 1697–1720 (2014)

    Article  Google Scholar 

  20. Huang, Y., Pardalos, P.M., Zheng, Q.P.: Electrical Power Unit Commitment. Springer, Boston (2017)

    Book  Google Scholar 

  21. Irani, S., Gupta, R., Shukla, S.: Competitive analysis of dynamic power management strategies for systems with multiple power savings states. In: DATE ’02: Proceedings of the conference on Design, automation and test in Europe, p. 117, Washington, DC, USA, (2002). IEEE Computer Society

  22. Irani, S., Pruhs, K.R.: Algorithmic problems in power management. In: ACM SIGACT News, vol. 36, pp. 63–76 (2005)

  23. Karlin, A.R., Kenyon, C., Randall, D.: Dynamic tcp acknowledgement and other stories about \(e/(e-1)\). In: Proc. 33rd STOC, pp. 502–509. ACM (2001)

  24. Karlin, A., Manasse, M., McGeoch, L., Owicki, S.: Competitive randomized algorithms for nonuniform problems. Algorithmica 11, 542–571 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  25. Karlin, A., Manasse, M., Rudolph, L., Sleator, D.: Competitive snoopy caching. Algorithmica 3, 79–119 (1988)

    Article  MathSciNet  MATH  Google Scholar 

  26. Maimo-Far, A., Tantet, A., Homar, V., Drobinski, P.: Predictable and unpredictable climate variability impacts on optimal renewable energy mixes: the example of Spain. Energies 13(9), 25 (2020)

    Google Scholar 

  27. Marini, B.: Are simple cycles or combined cycles better for renewable power integration? Power 159, 72–76 (2015)

    Google Scholar 

  28. Kumar, N., Besuner, P., Lefton, S., Agan, D., Hilleman, D.: Power Plant Cycling Costs. NREL (2012)

    Book  Google Scholar 

  29. Meyerson, A.: Online algorithms for network design. In: SPAA 2004: Proceedings of the Sixteenth Annual ACM Symposium on Parallelism in Algorithms and Architectures, June 27–30, Barcelona, Spain, pp. 275–280 (2004)

  30. Nedevschi, S., Chandrashekar, J., Liu, J., Nordman, B., Ratnasamy, S., Taft, N.: Skilled in the art of being idle: Reducing energy waste in networked systems. In: Proceedings of the 6th USENIX Symposium on Networked Systems Design and Implementation, NSDI’09, pages 381–394, Berkeley, CA, USA, (2009). USENIX Association

  31. Padhy, N.P.: Unit commitment—a bibliographical survey. IEEE Trans. Power Syst. 19(2), 1196–1205 (2004)

    Article  Google Scholar 

  32. Phillips, S., Westbrook, J.: Competitive analysis and beyond. In: Atallah M.J. (ed.) Algorithms and Theory of Computation Handbook. Chapter 10, CRC Press, ISBN 0849326494 (1999)

  33. Reich, J., Goraczko, M., Kansal, A., Padhye, J., Padhye, J.: Sleepless in Seattle no longer. Technical report, Microsoft. 2010. https://www.microsoft.com/en-us/research/publication/sleepless-in-seattle-no-longer/. Accessed 7 June 2021

  34. Ringkjøb, H.-K., Haugan, P.M., Solbrekke, I.M.: A review of modelling tools for energy and electricity systems with large shares of variable renewables. Renew. Sustain. Energy Rev. 96, 440–459 (2018). (ISSN 1364-0321)

    Article  Google Scholar 

  35. Sällberg, E., Lind, A., Velut, S., Åkesson, J., Yances, S.G., Link, K.: Start-up optimization of a combined cycle power plant. In: Proceedings of the 9th International Modelica Conference, Linköping Electronic Conference Proceedings, vol. 76, pp. 619–630 (2012)

  36. Tahanan, M., van Ackooij, W., Frangioni, A., Lacalandra, F.: Large-scale unit commitment under uncertainty. 4OR-Q J Oper Res 13, 115–171 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  37. Vincent, T., Calvin, S., Katherine, C., Geoffrey, K., Fields, F., Clement, Z., Bauer, D.: Implications of power plant idling and cycling on water use intensity. Environ. Sci. Technol. 53, 4657–4666 (2019)

    Article  Google Scholar 

  38. Van den Bergh, K.: Cycling of conventional power plants: technical limits and actual costs. Energy Convers. Manag. 97, 70–77 (2015)

    Article  Google Scholar 

  39. Wolff, R.W.: Stochastic Modeling and the Theory of Queues. Prentice Hall (1989)

    MATH  Google Scholar 

  40. Wu, D., Zheng, X., Xu, Y., Olsen, D., Xia, B., Singh, C., Xie, L.: An open-source model for simulation and corrective measure assessment of the 2021 Texas Power Outage. 05 April (2021), PREPRINT (Version 1) available at Research Square https://doi.org/10.21203/rs.3.rs-384535/v1

  41. Yoshida, Y., Yoshida, T., Enomoto, Y.. Osaki, N., Nagahama, Y., Tsuge, Y.: Start-up optimization of combined cycle power plants: a field test in a commercial power plant. J. Eng. Gas Turbines Power. 141(3), 9 (2018)

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Acknowledgements

This research has been carried out in collaboration with “Consumer Electronics Network Eco Management” project sponsored by Panasonic Corporation. We would like to thank the project members, Mr. Toshiya Naka, Mr. Hideyuki Yoshida and Mr. Kazuhiro Aizu. We also would like to thank Prof. Hiroshi Fujiwara of Toyohashi University of Technology for his valuable comments on power consumption problems and helpful discussions. Author Wolfgang Bein acknowledges a sabbatical granted by the University of Las Vegas, Nevada to conduct research in Japan. He also acknowledges NSF grant CCR-9821009. The authors are grateful to two anonymous referees for a number of helpful comments and insights that improved the paper.

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Authors and Affiliations

  1. Department of Computer Science, Center for Information Technology and Algorithms, University of Nevada, Las Vegas, Las Vegas, NV, USA

    James Andro-Vasko & Wolfgang Bein

  2. School of Informatics and Engineering, The University of Electro-Communications, Tokyo, Japan

    Hiro Ito

  3. Division of Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, Nara, Japan

    Shoji Kasahara & Jun Kawahara

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  1. James Andro-Vasko
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Correspondence to Wolfgang Bein.

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A preliminary version appeared in the Proceedings of the 9th Workshop on Approximation and Online Algorithms.

Wolfgang Bein: Research supported by NSF grant CCR-9821009. Shoji Kasahara: Part of JST ERATO MINATO Project.

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Andro-Vasko, J., Bein, W., Ito, H. et al. Decrease and reset for power-down. Energy Syst 14, 445–471 (2023). https://doi.org/10.1007/s12667-021-00475-3

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