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2018 | OriginalPaper | Buchkapitel

How to Manage the Complexity of the Grid?

verfasst von : Eugene Litvinov, Feng Zhao, Tongxin Zheng

Erschienen in: Energy Markets and Responsive Grids

Verlag: Springer New York

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Abstract

Power industry is facing revolutionary changes. The direction of the US Government to low carbon footprint and, as a consequence, high penetration of renewable energy resources and smart grid technologies are completely transforming planning and operational patterns for electric grid. As more and more variable and demand response resources being integrated into the electric grid, the grid operation is experiencing increasing level of uncertainties. The decision-making process under such environment becomes more challenging. The grid architecture and control also become more and more decentralized requiring new control paradigms and reliability metrics to be investigated in order to achieve much higher level of flexibility and resilience. These changes are disruptive enough to cause even transformations in utility business dealing with completely unknown situations. On the other hand, the evolution in computing; generation, transmission, and distribution technologies; and mathematical methods creates opportunities for innovation in power system design and control. New mathematical models for power system analysis and operation are being developed to address above challenges. We will discuss the need for new power system control and electricity market design directions while managing grid complexity.

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Nächstes Kapitel Naïve Electricity Markets
Literatur
1.
Jensen HJ (1998) Self-organized criticality: emergent complex behavior in physical and biological systems. Cambridge lecture notes in physics. Cambridge University Press, Cambridge
2.
DyLiacco T (1968) Control of power systems via the multi-level concept. Technical report SRC-68-19, Case Western Reserve University, Systems Research Center
3.
Bonabeau E (1999) Editor’s introduction: stigmergy. Special issue of Artif Life Stigmergy 5(2):95–96
4.
Maslennikov S, Litvinov E (2009) Adaptive emergency transmission rates in power system and market operation. IEEE Trans Power Syst 24(2):923–929
5.
Zhao J, Zheng T, Litvinov E (2016) A unified framework for defining and measuring flexibility in power system. IEEE Trans Power Syst 31(1):339–347
6.
Wang Q, McCalley J, Zheng T, Litvinov E (2013) A computational strategy to solve preventive risk-based security constrained OPF. IEEE Trans Power Syst 28(2):1666–1675
7.
Carpentier P, Gohen G, Culioli JC, Renaud A (1996) Stochastic optimization of unit commitment: a new decomposition framework. IEEE Trans Power Syst 11:1067–1073
8.
Bertsimas D, Litvinov E, Sun XA, Zhao J, Zheng T (2014) Closure to the discussion of “adaptive robust optimization for the security constrained unit commitment problem”. IEEE Trans Power Syst 29(2):996–997
9.
Wang Q, Yang A, Wen F, Li J (2013) Risk-based security-constrained economic dispatch in power systems. J Mod Power Syst Clean Energy 1(2):142–149
10.
Nivad N, Rosenwald G, Chatterjee D (2011) Ramp capability for load following in MISO markets. Available https://​www.​misoenergy.​org/​layouts/​MISO/​ECM/​Redirect.​aspx?​ID=​112806
11.
Monticelli A, Pereira MVF, Granville S (1987) Security-constrained optimal power flow with post-contingency corrective rescheduling. IEEE Trans Power Syst 2(1):175–180
12.
Capitanescu F, Wehenkel L (2008) A new iterative approach to the corrective security-constrained optimal power flow problem. IEEE Trans Power Syst 23(4):1533–1541
13.
Pinto H, Stott B (2010) Security constrained economic dispatch with post-contingency corrective rescheduling. In: FERC conference, Washington, DC, June 23–24
14.
Liu Y, Ferris MC, Zhao F (2014) Computational study of security constrained economic dispatch with multi-stage rescheduling. IEEE Trans Power Syst 30(2):920–929
15.
Takriti S, Birge JR, Long E (1996) A stochastic model for the unit commitment problem. IEEE Trans Power Syst 11:1497–1508
16.
Ozturk UA, Mazumdar M, Norman BA (2005) A solution to the stochastic unit commitment problem using chanced constrained programming. IEEE Trans Power Syst 19(3):1589–1598
17.
Wu L, Shahidehpour M, Li T (2007) Stochastic security-constrained unit commitment. IEEE Trans Power Syst 22:800–811
18.
Ryan SM, Silva Monroy C, Watson JP, Wets RJB, Woodruff DL (2013) Toward scalable, parallel progressive hedging for stochastic unit commitment. In: Proceedings of the IEEE 2013 IEEE power and energy society general meeting
19.
Papavasiliou A, Oren SS, Rountree B (2015) Applying high performance computing to transmission-constrained stochastic unit commitment for renewable energy integration. IEEE Trans Power Syst 30(3):1109–1120
20.
Ben-Tal A, Nemirovski A (1998) Robust convex optimization. Math Oper Res 23:769–805
21.
Ben-Tal A, Nemirovski A (1999) Robust solutions of uncertain linear programs. Oper Res Lett 25(1):1–13
22.
Ben-Tal A, Nemirovski A (2000) Robust solutions of linear programming problems contaminated with uncertain data. Math Program 88:411–421
23.
Ghaoui LE, Lebret H (1997) Robust solutions to least-squares problems with uncertain data. SIAM J Matrix Anal Appl 18:1035–1064
24.
Ghaoui LE, Oustry F, Lebret H (1998) Robust solutions to uncertain semidefinite programs. SIAM J Optim 9(1):33–52
25.
Bertsimas D, Sim M (2003) Robust discrete optimization and network flows. Math Program 98:48–71
26.
Bertsimas D, Sim M (2004) The price of robustness. Oper Res 52:35–53
27.
Bertsimas D, Brown DB (2009) Constructing uncertainty sets for robust linear optimization. Oper Res v57(6):1483–1495
28.
Lannoye E, Flynn D, O’Malley M (2013) Evaluation of power system flexiblity. IEEE Trans Power Syst 27(2):922–931
29.
Ma J, Kirschen D, Silva V, Belhomme R (2011) Optimizing the flexibility of a portfolio of generating plants to deal with wind generation. In: IEEE power and energy society general meeting, San Diego, CA
30.
Menemenlis N, Huneault M, Robitaille A (2011) Thoughts on power system flexibility quantification for the short-term horizon. In: IEEE power and energy society general meeting, San Diego, CA
31.
Bouffard F, Ortega-Vazquez M (2011) The value of operational flexibility in power systems with significant wind power generation. In: Power and energy society general meeting, San Diego, CA
32.
Studarus K, Christie R (2013) A deterministic metric of stochastic operational flexibility. In: IEEE power and energy society general meeting, Vancouver, BC
33.
Ulbig A, Andersson G (2012) On operational flexibility in power systems. In: IEEE power and energy society general meeting, San Diego, CA
34.
Conejo AJ, Aguado JA (1998) Multi-area coordinated decentralized DC optimal power flow. IEEE Trans Power Syst 13(4):1272–1278
35.
Echeverri MG, Lezama JML, Roberto J, Mantovani S (2010) Decentralized AC power flow for multi-area power systems using a decomposition approach based on Lagrangian relaxation. Rev Fac Ing Univ Antioquia 53:225–235
36.
Bakirtzis AG, Biskas PN (2003) A decentralized solution to the DC-OPF of interconnected power systems. IEEE Trans Power Syst 18(3):1007–1013
37.
38.
39.
40.
41.
Phulpin Y (2009) Coordination of reactive power scheduling in a multi-area power system operated by independent utilities. Ph.D. thesis, Georgia Institute of Technology
42.
Zhao F, Zheng T, Litvinov E (2014) A marginal equivalent decomposition method and its application to multi-area optimal power flow problems. IEEE Trans Power Syst 29(1):53–61
43.
Grimm V, Wissel C (1997) Babel or the ecological stability discussions: an inventory and analysis of terminology and a guide for avoiding confusion. Oecologia 109:323–334
44.
45.
Liao H, Apt J, Talukdar S (2004) Phase transitions in the probability of cascading failures. In: Electricity transmission in deregulated markets
46.
Richards M et al (2009) Metrics for evaluating survivability in dynamic multi-attribute tradespace exploration. J Spacecr Rockets 46:1049–1064
47.
Sterbenz J et al (2010) Resilience and survivability in communication networks: strategies, principles, and survey of disciplines. Comput Netw 54:1245–1265
48.
Richards MG, Hastings DE, Rhodes DH, Ross AM, Weigel AL (2009) Design for survivability: concept generation and evaluation in dynamic tradespace exploration. In: Second international symposium on engineering systems, MIT, Cambridge, MA
Metadaten
Titel
How to Manage the Complexity of the Grid?
verfasst von
Eugene Litvinov
Feng Zhao
Tongxin Zheng
Copyright-Jahr
2018
Verlag
Springer New York
Buch
Energy Markets and Responsive Grids

Print ISBN: 978-1-4939-7821-2

Electronic ISBN: 978-1-4939-7822-9

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-1-4939-7822-9_1

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