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Erschienen in:
Introduction Kapitel lesen Erstes Kapitel lesen

2015 | OriginalPaper | Buchkapitel

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

verfasst von : Tao Jiang, Liang Yu, Yang Cao

Erschienen in: Energy Management of Internet Data Centers in Smart Grid

Verlag: Springer Berlin Heidelberg

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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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Vorheriges Kapitel Joint Workload and Battery Scheduling for Data Center Energy Cost Minimization
Nächstes Kapitel Conclusions
Fußnoten
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
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
Here, a simple SLA is adopted as in [33, 35]. Other more complicated SLAs would be considered in future work.
 
Literatur
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)
2.
Guo Y, Fang Y (2013) Electricity cost saving strategy in data centers by using energy storage. IEEE Trans Parallel Distrib Syst 24(6):1149–1160CrossRef
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)
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):1–9CrossRef
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):50–58CrossRef
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)
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)
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
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
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)
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):1653–1662CrossRef
12.
13.
Stevenson WJ (2012) Loose-leaf operations management, 11th edn. McGraw-Hill Higher Education, New York
14.
Weron R (2006) Modeling and forecasting electricity loads and prices: a statistical approach. Wiley, New JerseyCrossRef
15.
Deng SJ, Oren SS (2006) Electricity derivatives and risk management. Energy 31:940–953CrossRef
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):2006–2021CrossRef
17.
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):744–754CrossRef
19.
Zare K, Moghaddam MP, Sheikh-El-Eslami MK (2011) Risk-based electricity procurement for large consumers. IEEE Trans Power Syst 26(4):1826–1835CrossRef
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):555–563CrossRef
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
22.
Wu L, Shahidehpour M (2010) A hybrid model for day-ahead price forecasting. IEEE Trans Power Syst 25(3):1519–1530CrossRef
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)
24.
Birge JR, Louveaux F (1997) Introduction to stochastic programming. Springer, New YorkMATH
25.
Dupac̆ová J, Consigli G, Wallace SW (2000) Scenarios for multistage stochastic programs. Ann Oper Res 100(1–4):25–53
26.
27.
Høyland K, Kaut M, Wallace SW (2003) A heuristic for moment-matching scenario generation. Comput Optim Appl 24:169–185CrossRefMathSciNet
28.
Conejo AJ, Carrión M, Morales JM (2010) Decision making under uncertainty in electricity markets. Springer, New YorkCrossRefMATH
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)
30.
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)
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
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):1–15CrossRef
34.
Ardagna D, Trubian M, Zhang L (2007) SLA based resource allocation policies in autonomic environments. J Parallel Distrib Comput 67:259–270CrossRefMATH
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)
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):246–254CrossRef
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):1–12MATH
38.
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
40.
Arlitt M, Jin T (1999) Workload characterization of the 1998 world cup web site. HPL-1999-35(R.1)
41.
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):878–888CrossRef
Metadaten
Titel
Risk-Constrained Operation for Internet Data Centers in Deregulated Electricity Markets
verfasst von
Tao Jiang
Liang Yu
Yang Cao
Copyright-Jahr
2015
Verlag
Springer Berlin Heidelberg
Buch
Energy Management of Internet Data Centers in Smart Grid

Print ISBN: 978-3-662-45675-0

Electronic ISBN: 978-3-662-45676-7

Copyright-Jahr: 2015

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