Energy Scheduling of Battery Storage Systems in Micro Grids

Andreas Armstorfer; Helmuth Biechl; Argo Rosin

doi:10.1515/ecce-2017-0004

Abstract

Microgrids in island mode with high penetration of renewable energy sources in combination with gensets and battery storage systems need a control system for voltage and frequency. In this study the main goal is maximization of the energy feed-in by renewable sources. Therefore it is necessary to keep the State of Energy for the Battery Storage System in a range that the excess energy can be absorbed and used in a later period of the day. In this paper an approach for State of Charge scheduling based on load and generation prediction is described.

References

[1] D. Oeding and B. Oswald, Elektrische Kraftwerke und Netze. 2011.10.1007/978-3-642-19246-3
Search in Google Scholar Back to article
[2] A. J. Schwab, Elektroenergiesysteme, 3. Auflage. Springer Berlin Heidelberg, 2012.10.1007/978-3-642-21958-0
Search in Google Scholar Back to article
[3] J. Rocabert, A. Luna, F. Blaabjerg, and P. Rodríguez, “Control of PowerConverters in AC Microgrids,” IEEE Transactions on Power Electronics, vol. 27, no. 11, pp. 4734–4749, Nov. 2012.https://doi.org/10.1109/tpel.2012.219933410.1109/TPEL.2012.2199334
Open DOI Search in Google Scholar Back to article
[4] K. De Brabandere, B. Bolsens, J. Van den Keybus, A. Woyte, J. Driesen, and R. Belmans, “A Voltage and Frequency Droop Control Method for Parallel Inverters,” IEEE Transactions on Power Electronics, vol. 22, no. 4, pp. 1107–1115, Jul. 2007. https://doi.org/10.1109/tpel.2007.90045610.1109/tpel.2007.900456
Open DOI Search in Google Scholar Back to article
[5] S. Nourollah, A. Pirayesh, and F. Aminifar, “Combinational scheme for voltage and frequency recovery in an islanded distribution system,” IET Generation, Transmission & Distribution, vol. 10, no. 12, pp. 2899–2906, Sep. 2016. https://doi.org/10.1049/iet-gtd.2015.130210.1049/iet-gtd.2015.1302
Search in Google Scholar Back to article
[6] S. Krishnamurthy, T. M. Jahns, and R. H. Lasseter, “The operation of diesel gensets in a CERTS microgrid,” 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, Jul. 2008, pp. 1–8. https://doi.org/10.1109/pes.2008.459650010.1109/pes.2008.4596500
Open DOI Search in Google Scholar Back to article
[7] Y. Zhang, R. Xiong, H. He, and W. Shen, “Lithium-Ion Battery Pack State of Charge and State of Energy Estimation Algorithms Using a Hardware-in-the-Loop Validation,” IEEE Transactions on Power Electronics, vol. 32, no. 6, pp. 4421–4431, Jun. 2017. https://doi.org/10.1109/tpel.2016.260322910.1109/tpel.2016.2603229
Open DOI Search in Google Scholar Back to article
[8] M. Ceci, R. Corizzo, F. Fumarola, D. Malerba, and A. Rashkovska, “Predictive Modeling of PV Energy Production: How to Set Up the Learning Task for a Better Prediction?,” IEEE Transactions on Industrial Informatics, vol. 13, no. 3, pp. 956–966, Jun. 2017. https://doi.org/10.1109/tii.2016.260475810.1109/TII.2016.2604758
Search in Google Scholar Back to article
[9] G. Sideratos and N. D. Hatziargyriou, “An Advanced Statistical Method for Wind Power Forecasting,” IEEE Transactions on Power Systems, vol. 22, no. 1, pp. 258–265, Feb. 2007. https://doi.org/10.1109/tpwrs.2006.88907810.1109/TPWRS.2006.889078
Open DOI Search in Google Scholar Back to article
[10] H.-T. Yang, C.-M. Huang, Y.-C. Huang, and Y.-S. Pai, “A Weather-Based Hybrid Method for 1-Day Ahead Hourly Forecasting of PV Power Output,” IEEE Transactions on Sustainable Energy, vol. 5, no. 3, pp. 917–926, Jul. 2014. https://doi.org/10.1109/iciea.2014.693122010.1109/ICIEA.2014.6931220
Search in Google Scholar Back to article
[11] A. Dolara, S. Leva, M. Mussetta, and E. Ogliari, “PV hourly day-ahead power forecasting in a micro grid context,” 2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC), Jun. 2016, pp. 1–5. https://doi.org/10.1109/eeeic.2016.755563610.1109/eeeic.2016.7555636
Open DOI Search in Google Scholar Back to article
[12] Y. Hosoda and T. Namerikawa, “Short-term photovoltaic prediction by using H∞ filtering and clustering,” 2012 Proceedings of SICE Annual Conference (SICE), Akita, 2012, pp. 119–124.
Search in Google Scholar Back to article
[13] A. Shakya, S. Michael, C. Saunders, D. Armstrong, P. Pandey, S. Chalise, and R. Tonkoski, “Solar Irradiance Forecasting in Remote Microgrids Using Markov Switching Model,” IEEE Transactions on Sustainable Energy, vol. 8, no. 3, pp. 895–905, Jul. 2017. https://doi.org/10.1109/tste.2016.262997410.1109/TSTE.2016.2629974
Search in Google Scholar Back to article
[14] “IREN2”, [Online]. Available: http://www.iren2.de
Search in Google Scholar Back to article
[15] R. Köberle, K. Mayr, B. Rindt, T. Sowa, D. Buchstaller, A. Armstorfer, and H. Biechl, “IREN2: Zukunftsfähige Netze zur Integration Regenerativer Energiesysteme,” in ETG-Fb. 145: Von Smart Grids zu Smart Markets 2015, 2015.
Search in Google Scholar Back to article
[16] A. Armstorfer, H. Biechl, B. Alt, H. Müller, R. Sollacher, D. Most, A. Szabo, R. Köberle, and M. Fiedeldey, “Einsatz von Batteriespeichern in Smart Grids – Operation of Battery Storage Systems in Smart Grids,” Int. ETG-Kongress, pp. 1–8, 2013.
Search in Google Scholar Back to article

Energy Scheduling of Battery Storage Systems in Micro Grids

Abstract

Paradigm

My account