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Energy Systems
Erschienen in: Energy Systems 2/2016

01.05.2016 | Original Paper

Slow dynamics model of compressed air energy storage and battery storage technologies for automatic generation control

verfasst von: Venkat Krishnan, Trishna Das

Erschienen in: Energy Systems | Ausgabe 2/2016

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Abstract

Increasing variable generation penetration and the consequent increase in short-term variability makes energy storage technologies look attractive, especially in the ancillary market for providing frequency regulation services. This paper presents slow dynamics model for compressed air energy storage and battery storage technologies that can be used in automatic generation control studies to assess the system frequency response and quantify the benefits from storage technologies in providing regulation service. The paper also represents the slow dynamics model of the power system integrated with storage technologies in a complete state space form. The storage technologies have been integrated to the IEEE 24 bus system with single area, and a comparative study of various solution strategies including transmission enhancement and combustion turbine have been performed in terms of generation cycling and frequency response performance metrics.
Vorheriger Artikel A comparative study on applications of artificial intelligence-based multiple models predictive control schemes to a class of industrial complicated systems
Nächster Artikel Co-optimization of electricity transmission and generation resources for planning and policy analysis: review of concepts and modeling approaches

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Literatur
1.
2.
3.
4.
Chen, Y., et al.: Incorporating short-term stored energy resource into Midwest ISO energy and ancillary service market. IEEE Trans. Power Syst. 26(2), 829–838 (2011)CrossRef
5.
Tripathy, S.C., Juengst, K.P.: Sampled data automatic generation control with superconducting magnetic energy storage in power systems. IEEE Trans. Energy Convers. 12(2), 187–192 (1997)CrossRef
6.
Lyons, P.G.: Energy storage for power systems with rapidly changing loads. Thesis, Purdue University (1992)
7.
Xie, P., Qian, B., Shi, D., Chen, J., Zhu, L.: Supplementary automatic generation control using electric vehicle battery swapping stations. In: 2013 IEEE Power and Energy Society General Meeting (PES), Vancouver, BC, 21–25 July 2013, pp. 1–5 (2013)
8.
Cheng, Y., Tabrizi, M., Sahni, M., Povedano, A., Nichols, D.: Dynamic available AGC based approach for enhancing utility scale energy storage performance. IEEE Trans. Smart Grid 5(2), 1070–1078 (2014)CrossRef
9.
Donadee, J.: Wang J, AGC signal modeling for energy storage operations. IEEE Trans. Power Syst. 29(5), 2567–2568 (2014)CrossRef
10.
Keyhani, A., Chatterjee, A.: Automatic generation control structure for smart power grids. IEEE Trans. Smart Grid 3(3), 1310–1316 (2012)CrossRef
11.
Antonishen, M.P., Han, H.Y., Brekken, T.K.A., von Jouanne, A., Yokochi, A., Halamay, D.A., Song, J., Naviaux, D.B., Davidson, J.D., Bistrika, A.: A methodology to enable wind farm participation in automatic generation control using energy storage devices. In: 2012 IEEE Power and Energy Society General Meeting, San Diego, CA, 22–26 July 2012, pp 1–7 (2012)
12.
Gampa, S.R., Das, D.: Real power and frequency control of a small isolated power system. Int. J. Electr. Power Energy Syst. 64, 221–232 (2015)CrossRef
13.
Das, D.C., Roy, A.K., Sinha, N.: GA based frequency controller for solar thermal-diesel-wind hybrid energy generation/energy storage system. Int. J. Electr. Power Energy Syst. 43(1), 262–279 (2012)CrossRef
14.
Chatterjee, A., Ghoshal, S.P., Mukherjee, V.: Transient performance improvement of grid connected hydro system using distributed generation and capacitive energy storage unit. Int. J. Electr. Power Energy Syst. 43(1), 210–221 (2012)CrossRef
15.
Pandey, S.K., Mohanty, S.R., Kishor, N., Catalão, J.P.S.: Frequency regulation in hybrid power systems using particle swarm optimization and linear matrix inequalities based robust controller design. Int. J. Electr. Power Energy Syst. 63, 887–900 (2014)CrossRef
16.
Ramakrishna, K., et al.: Automatic generation control of interconnected power system with diverse sources of power generation. Int. J. Eng. Sci. Technol. 2(5), 51–65 (2010)CrossRef
17.
Rowen, W.I.: Simplified mathematical representation of heavy duty gas turbines. ASME J. Eng. Power 105, 865–869 (1983)CrossRef
18.
Robinson, M.: Midwest ISO market design: wind in energy, capacity and ancillary services markets. In: UWIG Workshop, UWIG 2004. Albany - Albany, NY (2004)
19.
Das, T., Krishnan, V., McCalley, J.: High-fidelity dispatch model of storage technologies for production costing studies. IEEE Trans. Sustain. Energy 5(4), 1242–1252 (2014)CrossRef
20.
Samineni, S.: Modeling and analysis of a flywheel energy storage system for voltage sag correction. M.S. Thesis, University of Idaho (2003)
21.
Das, T., Krishnan, V., Yang, G., McCalley, J.D.: Compressed air energy storage: state space modeling and performance analysis. In: 2011 IEEE Power and Energy Society General Meeting, San Diego, CA, 24–29 July 2011, pp. 1–8 (2011)
22.
Ferguson, T.B.: The Centrifugal Compressor Stage. Butterworth, London (1963)
23.
Succar, S., Williams, R.H.: Compressed air energy storage: theory, resources, and applications for wind power. In: Energy Systems Analysis Group, Princeton Environmental Institute. Princeton university, Princeton (2008)
24.
Korpaas, M., Holen, A.T., Hildrum, R.: Operation and sizing of energy storage for wind power plants in a market system. Int. J. Electr. Power Energy Syst. 25, 599–606 (2003)CrossRef
25.
Moran, M.J., Shapiro, H.N., Munson, B.R., Dewitt, D.P.: Introduction to Thermal Systems Engineering. Wiley, New York (2002)
26.
F. Crotogino, K. U. Mohmeyer and R. Scharf, Huntorf CAES: More than 20 Years of Successful Operation. Spring 2001 Meeting, USA
27.
28.
Tremblay, O., Dessaint, L.A.: Experimental validation of a battery dynamic model for EV applications. World Electr. Veh. J. 3, 1–10 (2009) (ISSN 2032–6653, \({\copyright }\) 2009 AVERE, EVS24 Stavanger, Norway, May 13–16, 2009)
29.
Krishnan, V., Das, T., McCalley, J.: Impact of short-term storage on frequency response under increasing wind penetration. J. Power Sour. 257, 111–119 (2014)CrossRef
Metadaten
Titel
Slow dynamics model of compressed air energy storage and battery storage technologies for automatic generation control
verfasst von
Venkat Krishnan
Trishna Das
Publikationsdatum
01.05.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
Energy Systems / Ausgabe 2/2016
Print ISSN: 1868-3967
Elektronische ISSN: 1868-3975
DOI
https://doi.org/10.1007/s12667-015-0157-5

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