Sliding Mode Control Strategy for DC Microgrid Powered by Wind Energy, Diesel Generator and Energy Storage System with Pulsating Loads

Akhand Pratap Singh, Adeeb Uddin Ahmad, Kuldeep Sahay

Abstract


This paper examines the use of sliding mode control (SMC) to enhance the operation of a DC Microgrid that includes wind energy, a diesel generator, and battery backup. The integration of renewable sources like wind introduces instability due to their intermittent nature. To address this, the Microgrid incorporates a diesel generator and battery backup to improve reliability and resilience during periods of low renewable energy. SMC is proposed as an effective control strategy for managing these challenges, offering benefits such as disturbance rejection and quick response. Through detailed simulations, the study demonstrates that SMC significantly improves the stability and performance of the Microgrid under various conditions. This approach highlights the potential of SMC to create more efficient and sustainable energy management systems in Microgrids with diverse energy sources.

Keywords


Battery backup; DC microgrid; diesel generator; efficiency; sliding mode control

Full Text:

PDF

References


Jacob H. and X. Wang. 2015. Sliding mode control of a permanent magnet synchronous generator for variable speed wind energy conversion systems. Systems Science & Control Engineering 3(1): 453-459.

Guerrero J.M., Chandorkar M., Lee T.L., and Loh, P.C., 2013. Advanced control architectures for intelligent microgrids—Part II: Power quality, energy storage, and AC/DC microgrids. IEEE Transactions on Industrial Electronics 60(4), 1263-1270.

Dragicevic T., Lu X., and Vasquez J.C., 2016. DC microgrids—Part I: A review of control strategies and stabilization techniques. IEEE Transactions on Power Electronics 31(7), 4876-4889.

Mousavi Y., Geraint Bevan I.B., Kucukdemiral, A.F., Sliding mode control of wind energy conversion systems: Trends and applications, Renewable and Sustainable Energy Reviews.

Xiao J. and P. Wang. 2013. Multiple modes control of household DC microgrid with integration of various renewable energy sources. In Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE, 2013, pp. 1773-1778.

Lirong Z., Yi W., Heming L., and Pin S., 2012. Hierarchical coordinated control of DC microgrid with wind turbines. In IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society, 2012, pp. 3547-3552.

Esram T. and P.L. Chapman. 2007. Comparison of photovoltaic array maximum power point tracking techniques. IEEE Transactions on Energy Conversion 22(2), 439-449.

Hau E., 2006. Wind Turbines—Fundamentals, Technologies, Application and Economics, 2nd ed.; Springer: Berlin/Heidelberg, Germany.

Heier S., 2014. Grid Integration of Wind Energy: Onshore and Offshore Conversion Systems; John Wiley & Sons: Hoboken, NJ, USA.

Abdullah M.A., Yatim A.H.M., and Tan C.W.A., 2011. Study of maximum power point tracking algorithms for wind energy system. In Proceedings of the IEEE First Conference on Clean Energy and Techonology (CET), Kuala Lumpur, Malaysia, 27–29 June 2011; pp. 321–326.

Abdullah M.A., Yatim A.H.M., Tan C.W., Saidur R., 2012. A review of maximum power point tracking algorithms for wind energy systems. Renewable and Sustainable Energy Reviews 16, 3220–3227.

Sadick A., 2023. Maximum Power Point Tracking Simulation for Photovoltaic Systems Using Perturb and Observe Algorithm’, Solar Radiation - Enabling Technologies, Recent Innovations, and Advancements for Energy Transition [Working Title]. IntechOpen, May 11, 2023. doi: 10.5772/intechopen.111632.

Senjyu T., Nakaji T., Uezato K., and Funabashi T., 2005. A hybrid power system using alternative energy facilities on an isolated island. IEEE Transactions on Energy Conversion 20(2): 406–414.

Rakopoulos, Constantine D., Giakoumis, and Evangelos G., 2009. Diesel Engine Transient Operation- Principles of Operation and Simulation Analysis, Springer, 2009.

Stavrakakis G.S. and G.N. Kariniotakis. 1995. A general simulation algorithm for the accurate assessment of isolated diesel- wind turbines systems interaction. IEEE Transactions on Energy Conversion 10(3): 577–583.

Sharaf A.M. and E.S. Abdin. 1989. A digital simulation model for wind-diesel conversion scheme. 26-28 Mar 1989, pp. 160–166.

Wamkeue R., Baetscher F., and Kamwa I., 2008. Hybrid state model-based time-domain identification of synchronous machine parameters from saturated load rejection test records. IEEE Transactions on Energy Conversion, vol. 23, no. 1, pp. 68–77, 2008.

Wang Z., Li S. and Li Q., 2020. Continuous Nonsingular Terminal Sliding Mode Control of DC–DC Boost Converters Subject to Time-Varying Disturbances. In IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 67, no. 11, pp. 2552-2556, Nov. 2020

Petrone G. and C. Ramos-Paja. 2011. Modeling of photovoltaic fields in mismatched conditions for energy yield evaluations. Electric Power Systems Research 81, no. 4, pp. 1003–1013, 2011.

Bianconi E., Calvente J., Giral R., Mamarelis E., Petrone G., Ramos-Paja C.A., Spagnuolo G., and Vitelli M., 2013. A fast current based MPPT technique employing sliding mode control. IEEE Transactions on Industrial Electronics 60, no. 3, pp. 1168–1178, 2013.

Joshi K.R. and H.V Kannad. 2015. Design of Sliding Mode Control for BUCK Converter, pp. 4001-4008.