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Risk-Constrained Operation for Internet Data Centers in Deregulated Electricity Markets

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Part of the book series: Green Energy and Technology ((GREEN))

Abstract

In deregulated electricity markets, there exist multiple markets of different time scales, e.g., forward markets and spot markets. When Internet data center operators only procure energy from spot markets, they can save energy cost by fully exploiting the temporal and spatial variations of spot prices. Meanwhile, prices in spot markets and workloads are volatile, and forecasted prices and workloads tend to be less accurate with the increase of planning horizon, consequently, the future energy cost of Internet data centers is full of uncertainty (or randomness), which is a risk for Internet data center operators since they may experience high probability of having high energy cost in the future. Thus, in this chapter, we consider the risk-constrained operation for Internet data centers in deregulated electricity markets and propose a stochastic programming-based decision framework to decide the optimal quantity of electricity that should be purchased in forward markets given the risk preference of Internet data center operators.

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Notes

  1. 1.

    In this study, we focus on day-ahead spot markets and assume that prices and workloads in the next day can be accurately predicted [22, 23].

  2. 2.

    A time-slotted system is considered in this chapter, where each slot represents a time interval in a given delivery period of EFCs, e.g., 1 h.

  3. 3.

    Here, a simple SLA is adopted as in [33, 35]. Other more complicated SLAs would be considered in future work.

  4. 4.

    http://www.nyiso.com/public/index.jsp, Sept. 2013.

  5. 5.

    http://www.ercot.com/mktinfo/, Sept. 2013.

  6. 6.

    http://ita.ee.lbl.gov/html/contrib/WorldCup.html, Sept. 2013.

References

  1. Qureshi A, Weber R, Balakrishnan H, Guttag J, Maggs B (2009) Cutting the electric bill for internet-scale systems. In: Proceedings of ACM special interest group on data communication (SIGCOMM)

    Google Scholar 

  2. Guo Y, Fang Y (2013) Electricity cost saving strategy in data centers by using energy storage. IEEE Trans Parallel Distrib Syst 24(6):1149–1160

    Article  Google Scholar 

  3. Rao L, Liu X, Xie L, Liu W (2010) Minimizing electricity cost: optimization of distributed internet data centers in a multi-electricity market environment. In: Proceedings of IEEE international conference on computer communications (INFOCOM)

    Google Scholar 

  4. Li J, Li Z, Ren K, Liu X, Su H (2011) Towards optimal electric demand management for internet data centers. IEEE Trans Smart Grid 2(4):1–9

    Article  Google Scholar 

  5. Rao L, Liu X, Xie L, Liu W (2012) Coordinated energy cost management of distributed internet data centers in smart grid. IEEE Trans Smart Grid 3(1):50–58

    Article  Google Scholar 

  6. Xu D, Liu X, Fan B (2011) Minimizing energy cost for internet-scale datacenters with dynamic traffic. In: Proceedings of international workshop on quality of service (IWQoS)

    Google Scholar 

  7. Le K, Bianchini R, Martonosi M, Nguyen TD (2009) Cost and energy-aware load distribution across data centers. In: Proceedings of workshop on power-aware computing and systems (HotPower)

    Google Scholar 

  8. Luo J, Rao L, Liu X (2013) Temporal load balancing with service delay guarantees for data center energy cost optimization. IEEE Trans Parallel Distrib Syst 25(3):775–784

    Google Scholar 

  9. Yao Y, Huang L, Sharma A, Golubchik L, Neely M (2013) Power cost reduction in distributed data centers: a two time scale approach for delay tolerant workloads. IEEE Trans Parallel Distrib Syst 25(1):200–211

    Google Scholar 

  10. Guo Y, Ding Z, Fang Y, Wu D (2011) Cutting down electricity cost in internet data centers by using energy storage. In: Proceedings of IEEE international conference on global communications (GLOBECOM)

    Google Scholar 

  11. Xu J, Luh PB, White FB, Ni E, Kasiviswanathan K (2006) Power portfolio optimization in deregulated electricity markets with risk management. IEEE Trans Power Syst 21(4):1653–1662

    Article  Google Scholar 

  12. Electric Power Markets: PJM. Available via DIALOG. http://www.ferc.gov/market-oversight/mkt-electric/pjm.asp. Accessed 23 Sept 2013

  13. Stevenson WJ (2012) Loose-leaf operations management, 11th edn. McGraw-Hill Higher Education, New York

    Google Scholar 

  14. Weron R (2006) Modeling and forecasting electricity loads and prices: a statistical approach. Wiley, New Jersey

    Book  Google Scholar 

  15. Deng SJ, Oren SS (2006) Electricity derivatives and risk management. Energy 31:940–953

    Article  Google Scholar 

  16. Benth FE, Cartea Á, Kiesel R (2008) Pricing forward contracts in power markets by the certainty equivalence principle: explaining the sign of the market risk premium. J Bank Financ 32(10):2006–2021

    Article  Google Scholar 

  17. Benth FE, Sgarra C (2012) The risk premium and the Esscher transform in power markets. Stoch Anal Appl 30(1):20–43

    Article  MathSciNet  MATH  Google Scholar 

  18. Carrión M, Philpott AB, Conejo AJ, Arroyo JM (2007) A stochastic programming approach to electric energy procurement for large consumers. IEEE Trans Power Syst 22(2):744–754

    Article  Google Scholar 

  19. Zare K, Moghaddam MP, Sheikh-El-Eslami MK (2011) Risk-based electricity procurement for large consumers. IEEE Trans Power Syst 26(4):1826–1835

    Article  Google Scholar 

  20. Rao L, Liu X, Xie L, Pang Z (2011) Hedging against uncertainty: a tale of internet data center operations under smart grid environment. IEEE Trans Smart Grid 2(3):555–563

    Article  Google Scholar 

  21. Pflug G (2000) Some remarks on the value-at-risk and the conditional value-at-risk. Probabilistic constrained optimization: methodology and applications. Kluwer Academic Publishers, Dordrecht

    Google Scholar 

  22. Wu L, Shahidehpour M (2010) A hybrid model for day-ahead price forecasting. IEEE Trans Power Syst 25(3):1519–1530

    Article  Google Scholar 

  23. Yao J, Liu X, He W, Rahman A (2012) Dynamic control of electricity cost with power demand smoothing and peak shaving for distributed internet data centers. In: Proceedings of international conference on distributed computing systems (ICDCS)

    Google Scholar 

  24. Birge JR, Louveaux F (1997) Introduction to stochastic programming. Springer, New York

    MATH  Google Scholar 

  25. Dupac̆ová J, Consigli G, Wallace SW (2000) Scenarios for multistage stochastic programs. Ann Oper Res 100(1–4):25–53

    Google Scholar 

  26. Heitsch H, Römisch W (2003) Scenario reduction algorithms in stochastic programming. Comput Optim Appl 24:187–206

    Article  MathSciNet  MATH  Google Scholar 

  27. Høyland K, Kaut M, Wallace SW (2003) A heuristic for moment-matching scenario generation. Comput Optim Appl 24:169–185

    Article  MathSciNet  Google Scholar 

  28. Conejo AJ, Carrión M, Morales JM (2010) Decision making under uncertainty in electricity markets. Springer, New York

    Book  MATH  Google Scholar 

  29. Chen G, He W, Liu J, Nath S, Rigas L, Xiao L, Zhao F (2008) Energy-aware server provisioning and load dispatching for connection-intensive internet services. In: Proceedings of networked systems design and implementation (NSDI)

    Google Scholar 

  30. Googles Green Data Centers. Available via DIALOG. http://www.google.com/green/bigpicture. Accessed 23 Sept 2013

  31. Gao PX, Curtis AR, Wong B, Keshav S (2012) It’s not easy being green. In: Proceedings of ACM special interest group on data communication (SIGCOMM)

    Google Scholar 

  32. Ghamkhari M, Mohsenian-Rad H (2013) Energy and performance management of green data centers: a profit maximization approach. IEEE Trans Smart Grid PP(99):1–9

    Google Scholar 

  33. Kusic D, Kephart JO, Hanson JE, Kandasamy N, Jiang G (2009) Power and performance management of virtualized computing environments via lookahead control. Clust Comput 12(1):1–15

    Article  Google Scholar 

  34. Ardagna D, Trubian M, Zhang L (2007) SLA based resource allocation policies in autonomic environments. J Parallel Distrib Comput 67:259–270

    Article  MATH  Google Scholar 

  35. Chen Y, Das A, Qin W, Sivasubramaniam A, Wang Q, Gautam N (2005) Managing server energy and operational costs in hosting centers. In: Proceedings of special interest group on measurement and evaluation (SIGMETRICS)

    Google Scholar 

  36. Hatami AR, Seifi H, Sheikh-El-Eslami MK (2009) Optimal selling price and energy procurement strategies for a retailer in an electricity market. Electr Power Syst Res 79(1):246–254

    Article  Google Scholar 

  37. Wang P, Rao L, Liu X, Qi Y (2012) D-pro dynamic data center operations with demand-responsive electricity prices in smart grid. IEEE Trans Smart Grid 4(3):1–12

    MATH  Google Scholar 

  38. Ahmed S (2006) Convexity and decomposition of mean-risk stochastic programs. Math Program 106(3):433–446

    Article  MathSciNet  MATH  Google Scholar 

  39. Gröwe-Kuska N, Heitsch H, Römisch W (2003) Scenario reduction and scenario tree construction for power management problems. In: Proceedings IEEE Bologna power technology conference

    Google Scholar 

  40. Arlitt M, Jin T (1999) Workload characterization of the 1998 world cup web site. HPL-1999-35(R.1)

    Google Scholar 

  41. McGee M (2013) By the numbers: twitter versus facebook versus google buzz. Available via DIALOG. http://searchengineland.com/by-the-numbers-twitter-vs-facebook-vs-google-buzz-36709. Accessed 23 Sept 2013

  42. Morales JM, Pineda S, Conejo AJ, Carrión M (2009) Scenario reduction for futures market trading in electricity markets. IEEE Trans Power Syst 24(2):878–888

    Article  Google Scholar 

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Correspondence to Tao Jiang .

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Jiang, T., Yu, L., Cao, Y. (2015). Risk-Constrained Operation for Internet Data Centers in Deregulated Electricity Markets. In: Energy Management of Internet Data Centers in Smart Grid. Green Energy and Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45676-7_5

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  • DOI: https://doi.org/10.1007/978-3-662-45676-7_5

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-45675-0

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