Model predictive control of combined renewable energy sources

The paper presence a Fuzzy Model Predictive Control (FMPC) for grid tied inverter with multiport DC-DC converter. Three phase grid tied inverter with multiple renewable energy sources are widely used to connect the distributive generating systems to the utility grid. Compare with the conventional control schemes, FMPC scheme is suitable for distributed generation system for its unique advantages likes reliable, fast and more accurate. In this proposed system, different sources having nonlinear parameters and it’s controlled by Fuzzy system. All linear states of three phase grid connected inverters are tested to attain the control objectives. FMPC is proposed to reduce the Total Harmonic Distortion (THD) of the output power. In the proposed system, the inverter control algorithm is developed using some essential vectors. The aim is to monitor the three phase grid current stability and improve the constancy function of the grid-tied inverter during variation of grid voltage. The grid tied converter is designed in two phase standing vector (αβ)model, and the FMPC of grid tied inverter is realized during variation of grid voltage. The simulation results show the superiority of the FMPC in control strategy

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Active Power Filter Shape Class Model Predictive Controller tuning by Multiobjective Optimization

Proceedings 5th CARPE Conference: Horizon Europe and beyond ◽

10.4995/carpe2019.2019.10166 ◽

2019 ◽

Author(s):

Carlos Cateriano Yáñez ◽

Jörg Richter ◽

Georg Pangalos ◽

Gerwald Lichtenberg ◽

Javier Sanchís Saez

Keyword(s):

Renewable Energy ◽

Power Systems ◽

Power Quality ◽

Predictive Control ◽

Renewable Energy Sources ◽

Active Power Filter ◽

Active Power ◽

Energy Sources ◽

Model Based Control ◽

Power Filter

As the share of renewable energy sources (RES) in distribution grids increases, several power quality challenges arise. Due to its intermittent nature, RES lead to voltage and frequency fluctuations in the grid that affect power quality. Moreover, as RES are connected via power converters, there is also a higher harmonic distortion pollution introduced by the switching power electronics involved, (Liang, 2017). A proven solution is the implementation of Active Power Filters (APF), which are able to compensate the unbalanced, harmonic, and reactive components of a load under different supply conditions. In order to achieve the desired compensation characteristics, the selection of an appropriate control strategy is critical, (Kumar & Mishra, 2016). Classic APF control strategies achieve said goals, although with struggles under changing load scenarios with limitations on their operational modes, (Weihe, Cateriano Yáñez, Pangalos, & Lichtenberg, 2018).This paper proposes the use of an advanced model-based control method, i.e. Model Predictive Control (MPC), to improve the performance of APF devices. Model-based control methods allow for better performance when the model of the plant is known before hand or through measurements, the MPC extends this further by introducing a cost function that ensures optimal operation even under constraints, (Maciejowski, 2002). References Kumar, P., & Mishra, M. K. (2016). A comparative study of control theories for realizing APFs in distribution power systems. 2016 National Power Systems Conference (NPSC), 1–6. https://doi.org/10.1109/NPSC.2016.7858905 Liang, X. (2017). Emerging Power Quality Challenges Due to Integration of Renewable Energy Sources. IEEE Transactions on Industry Applications, 53(2), 855–866. https://doi.org/10.1109/TIA.2016.2626253 Maciejowski, J. M. (2002). Predictive Control with Constraints. Pearson education. Weihe, K., Cateriano Yáñez, C., Pangalos, G., & Lichtenberg, G. (2018, July). Comparison of Linear State Signal Shaping Model Predictive Control with Classical Concepts for Active Power Filter Design. 167–174. Retrieved from http://www.scitepress.org/PublicationsDetail.aspx?ID=QatbWGUbqSE=&t=1

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