Model Predictive Control of Distributed Energy Resources with Predictive Set-Points for Grid-Connected Operation

Document Type : Research Article

Authors

Electrical Engineering Department, Bu-Ali Sina University, Hamedan, Iran

Abstract

This paper proposes an MPC - based (model predictive control) scheme to control active and reactive powers of DERs (distributed energy resources) in a grid - connected mode (either through a bus with its associated loads as a PCC (point of common coupling) or an MG (micro - grid)). DER may be a DG (distributed generation) or an ESS (energy storage system). In the proposed scheme, the set - points provided to MPC are forecast for future instances by a linear extrapolation to gain smooth active and reactive power exchange under various loading conditions (e.g. balanced / imbalanced, nonlinear and dynamic loading) and voltage imbalance imposed by the upstream grid. In this scheme active and reactive power control change to current control and the references of the currents are forecast. The stability of the proposed control scheme is analyzed and discussed. The effectiveness of the proposed scheme is demonstrated by extensive time - domain simulations using PSCAD / EMTDC for various conditions (various loads, voltage imbalance, parallel operation with other DGs, parameter uncertainties and measurement noises) in several case studies. Comparing the obtained results with those of the two other schemes (PI - based and convectional MPC) shows the superiority of the proposed scheme.

Keywords

Main Subjects

References

[1] G. Pepermans, J. Driesen, D. Haeseldonckx, R. Belmans, W. Dhaeseleer, Distributed generation: Definition, benefits and issues, Energy Policy, 33(6): (2005) 787–98.
[2] T. C. Green, M. Prodanovic, Control of inverter-based micro-grids, Electr. Power Syst. Res. Distrib. Generation, 77(9) (2007) 1204–13.
[3] J. Rocabert, A. Luna, F. Blaabjerg, P. Rodriguez, Control of Power Converters in AC Microgrids, IEEE Trans. on Power Electronics, 27(11) (2012) 4734-4749.
[4] F.A. Bhuiyan, A. Yazdani, Energy Storage Technologies for Grid-Connected and Off-Grid Power System Applications, IEEE Electrical Power and Energy Conference, 2012.
[5] A. Deihimi, B. Keshavarz Zahed, R. Iravani, An interactive operation management of a micro-grid with multiple distributed generations using multi-objective uniform water cycle algorithm, Energy, 106 (2016) 482-509.
[6] A. Yazdani, R. Iravani, Voltage-Sourced Converters in Power Systems: modeling, control and applications, IEEE Wiley Press, 2010.
[7] L. Shang, J. Hu, Sliding-mode-based direct power control of grid-connected wind-turbine-driven doubly fed induction generators under unbalanced grid voltage conditions, IEEE Trans. Energy Conversion, 27(2) (2012) 362–373.
[8] L. Shang, D. Sun, J. Hu, Sliding-mode-based direct power control of grid-connected voltage-sourced inverters under unbalanced network conditions, IET Power Electron, 4(5) (2011) 570–579.
[9] M.M, Rezaei, J. Soltani, A robust control strategy for a grid-connected multi-bus microgrid under unbalanced load conditions, Electrical Power and Energy Systems, 71 (2015) 68-76.
[10] M. Mehrasa, E. Pouresmaeil, B. N. Jørgensen, J. P.S. Catalão, A control plan for the stable operation of microgrids during grid-connected and islanded modes, Electric Power Systems Research, 129 (2015) 10-22.
[11] A. H. Syed, M.A. Abido, New enhanced performance robust control design schemefor grid-connected VSI, Control Engineering Practice, 53 (2016) 92-108.
[12] E. Pouresmaeil, O. Gomis-Bellmunt, D. Montesinos-Miracle, J. Bergas-Jané, Multilevel converters control for renewable energy integration to the power grid, Energy, 36 (2011) 950-363.
[13] J. Hu, J. Zhu, D. G. Dorrell, Model predictive control of inverters for both islanded and grid-connected operations in renewable power generations, IET Renewable Power Generation, 8(3) (2013) 240-248.
[14] V. Yaramasu, B. Wu, Model predictive decoupled active and reactive power control for high-power grid-connected four-level diode-clamped inverters, IEEE Trans. Power Electron, 61(7) (2014) 3407–3417.
[15] R. Halvgaard, L. Vandenberghe, N.K. Poulsen, H. Madsen, J.B. Jørgensen, Distributed model predictive control for smart energy systems, IEEE Trans. Smart Grid, 7(3) (2016) 1675-1682.
[16] A.S. Ashtari, A. Khaki Sedigh, Adaptive Simplified Model Predictive Control with Tuning Considerations, Amirkabir International Journal of Science& Research, 46(2) (2014).
[17] P. Kou, D. Liang, L. Gao, F. Gao, Stochastic coordination of plug-In electric vehicles and wind turbines in microgrid: a model predictive control approach, IEEE Trans. Smart Grid, 7(3) (2016) 1537-1551.
[18] J. Rodriguez, P. Cortes, Predictive Control of Power Converters and Electrical Drives, IEEE Wiley Press, 2012.
[19] L. Tarisciotti, P. Zanchetta, A. Watson, S. Bifaretti, J. C. Clare, Modulated model predictive control for a 7- level cascaded H-bridge back-to-back converter, IEEE Trans. Ind. Electron, 61(2) (2014) 5375-5383.
[20] K. M. Abo-Al-Ez, A. Elaiw, X. Xia, A dual-loop model predictive voltage control/sliding-mode current control for voltage source inverter operation in smart microgrids, Electric Power Components and Systems, 42(3) (2014) 348-360.
[21] P. Cortés, G. Ortiz, J. I. Yuz, J. Rodriguez, S. Vazquez, L. G. Franquelo, Model predictive control of an inverter with output LC filter for UPS applications, IEEE Trans. Ind. Electron, 56(6) (2009) 1875-1883.
[22] K. T. Tan, X. Y. Peng, P. L. So, Y. C. Chu, M. Z. Q. Chen, Centralized Control for Parallel Operation of Distributed Generation Inverters in Microgrids, IEEE Trans. On Smart Grid, 3(4) (2012) 1977-1987.
[23] D. Song, J. Yang, M. Dong, Y. H. Joo, Model predictive control with finite control set for variable-speed wind turbines, Energy, Accepted Manuscript (2017).
[24] M. Hamzeh, H. Karimi, H. Mokhtari, Harmonic and Negative-Sequence Current Control in an Islanded Multi-Bus MV Microgrid, IEEE Trans. On Smart Grid, (2013).
[25] S. K. Chung, A phase tracking system for three phase utility interface inverters, IEEE Transactions on Power Electronics, 5(3) (2000) 431-438.
[26] A. Medjber, A. Guessoum, H. Belmili, A. Mellit, New neural network and fuzzy logic controllers to monitor maximum power for wind energy conversion system, Energy, 106 (2016) 137-146.
[27] S. Ganjefar, A. Mohammadi, Variable speed wind turbines with maximum power extraction using singular perturbation theory, Energy, 106 (2016) 510-519.
[28] M. E. Basoglu, B. Çakir, A novel voltage-current characteristic based global maximum power point tracking algorithm in photovoltaic systems, Energy, 112 (2016) 153-163.
[29] S. S. Mohammed, D. Devaraj, T.P. I. Ahamed, A novel hybrid Maximum Power Point Tracking Technique using Perturb & Observe algorithm and Learning Automata for solar PV system, Energy, 112 (2016) 1096-1106.
[30] L. Wang, Model Predictive Control System Design and Implementation Using MATLAB, London, 2009.
[31] PSCAD/EMTDC v. 4.5.0.0, Manitoba HVDC Research Centre, Winnipeg, MB, Canada, 2012.
[32] J. Lofberg, Linear Model Predictive Control Stability and Robustness, Sweden, 2001.
[33] L. Grune, J. Pannek, Nonlinear Model Predictive Control: Theory and Algorithems, Springer Press 2017.
[34] J. M. Maciejowski, Predictive Control with Constraints, London, 2000.
[35] W. H. Chen, Stability Analysis of Classic Finite Horizon Model Predictive Control, International Journal of Control, Automation and Systems, 8(2) (2010) 187-197.
[36] N. Suyaroj, N. Watson, Transients State Estimation with Measurement Noise, IEEE Conference, 2015.
AUT Journal of Electrical Engineering
Volume 50, Issue 2
December 2018
Pages 109-120

Files

Share

How to cite

Statistics