Stochastic Model Predictive Control for Hybrid Energy Systems

A. Gienger, PhD student, J. Sachs, PhD,
O. Sawodny, Professor
Institute for System Dynamics, University of Stuttgart
(Waldburgstr. 17/19, 70563 Stuttgart, Germany)
Tel.: +49 71168565934, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.,
e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Tel.: +49 71168566302, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Èlektron. model. 2017, 39(1):39-50


Microgrids are a promising approach for the integration of renewable energy sources in existing networks and the energy supply of rural areas. A cost effective option for a microgrid is given by a hybrid energy system, which combines e.g. diesel generators, photovoltaic panels and batteries as considered in this paper. However, the interaction of the components and uncertainties in the load demand and photovoltaic power make the controller design challenging. This paper discusses a Stochastic Model Predictive Control approach which yields promising results regarding effectiveness and reliability as shown in a simulation study.


microgrid, hybrid energy system, optimal energy dispatch, Stochastic Model Predictive Control.


1. Kuznetsova, E., Li, Y.-F., Ruiz, C. and Zio, E. (2014), “An integrated framework of agent-based modelling and robust optimization for microgrid energy management”, Applied Energy, vol. 129, pp. 70-88.
2. Dong, C., Huang, G., Cai, Y. and Liu, Y. (2013),“ Robust planning of energy management systems with environmental and constraint-conservative considerations under multiple uncertainties”, Energy Conversion and Management, Vol. 65, pp. 471-486.
3. Zakariazadeh, A., Jadid, S. and Siano, P. (2014), “Stochastic multi-objective operational planning of smart distribution systems considering demand response programs”, Electric Power Systems Research, Vol. 111, pp. 156-168.
4. Alharbi, W. and Raahemifar, K. (2015), “Probabilistic coordination of micro-grid energy resources operation considering uncertainties”, Electric Power Systems Research, Vol. 128, pp. 1-10.
5. Baziar, A. and Kavousi-Fard, A. (2013), “Considering uncertainty in the optimal energy management of renewable mi-crogrids including storage devices”, Renewable Energy, Vol. 59, pp. 158-166.
6. Hooshmand, A., Poursaeidi, M., Mohammadpour, J., Malki, H. and Grigoriads, K. (2012), “Stochastic model predictive control method for microgrid management”, 2012 IEEE PES Innovative Smart Grid Technologies, Washington, 2012.
7. Gulin, M., Matusko, J. and Vasak, M. (2015), “Stochastic model predictive control for optimal economic operation of a residential DC microgrid”, 2015 IEEE International Conference on Industrial Technology, Seville, 2015.
8. Olivares, D. et al. (2015), “Stochastic-predictive energy management system for isolated microgrids”, IEEE Transactions on Smart Grid, Vol. 6, no. 6, pp. 2681-2693.
9. Parisio, A. and Glielmo, L. (2013), “Stochastic Model Predictive Control for economic/environmental operation management of microgrids”, 2013 European Control Conference, Zurich,
10. Parisio, A., Rikos, E. and Glielmo, L. (2016), “Stochastic model predictive control for economic/environmental operation management of microgrids: An experimental case study”, Journal of Process Control, Vol. 43, pp. 24-37.
11. Zhu, D. and Hug, G. (2014), “Decomposed stochastic model predictive control for optimal dispatch of storage and gen-eration”, IEEE Transactions on Smart Grid 5.4, pp. 2044-2053.
12. Sachs, J., Gienger, A. and Sawodny, O. (2016), “Combined Probabilistic and Set-Based Uncertainties for a Stochastic Model Predictive Control of Island Energy Systems”, 2016 American Control Conference, Boston, 2016.
13. Sachs, J. and Sawodny, O. (2016), “A Two-Stage Model Predictive Control Strategy for Economic Diesel-PV-Battery Island Microgrid Operation in Rural Areas”, IEEE Transactions on Sustainable Energy, Vol. 7, no. 3, pp. 903-913.
14. De Soto, W., Klein, S. and Beckman, W. (2006), “Improvement and validation of a model for photovoltaic array perfor-mance”, Solar Energy, Vol. 80, no. 1, pp. 78-88.
15. Shepherd, C. (1965), “Design of primary and secondary cells II. An equation describing battery discharge”, Journal of the Electrochemical Society, Vol. 112, no. 7, pp. 657-664.
16. Sachs, J., Sonntag, M. and Sawodny, O. (2015), “Two layer model predictive control for a cost efficient operation of island energy systems”, 2015 American Control Conference, Chicago, 2015.
17. Lee, C.-M. and Ko, C.-N. (2011), “Short-term load forecasting using lifting scheme and arima models”, Expert Systems with Applications, Vol. 38, no. 5, pp. 5902-5911.
18. Bellman, R. (1956), “Dynamic programming and Lagrange multipliers”, Proceedings of the National Academy of Sciences, pp. 767-769.

Full text: PDF (in Russian)