Designing of robust frequency stabilization using optimized MPC-(1+PIDN) controller for high order interconnected renewable energy based power systems
Muhammad Majid Gulzar
Abstract
Abstract The challenge of controlling frequency becomes greater as the complexity of a power network increases. The stability of a power system is highly dependent upon the robustness of the controller. This paper presents automatic generation control (AGC) of a four-area interconnected power system along with integrated renewable energy sources of PV and wind energy. The designed model is a challenge given the increased penetration levels of PV and wind along with a thermal-hydropower system. The addition of a hydropower system as a fourth type results in the pole of the open loop system of the hydropower system being located at the right half side of the s-plan. This demands a robust control. A novel MPC-(1 + PIDN) is designed for high-order interconnected areas (HOIA) to stabilize the frequency in a robust way. The salp swarm algorithm is adopted to optimize the parameters of the PIDN controller. The performance of the proposed controller under HOIA is tested in a unbalanced load environment with uncertainty in the power system. The proposed controller can effectively handle the frequency disruption by stabilizing it in $$0.86 s$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>0.86</mml:mn> <mml:mi>s</mml:mi> </mml:mrow> </mml:math> for Area-1, $$1.08 s$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>1.08</mml:mn> <mml:mi>s</mml:mi> </mml:mrow> </mml:math> for Area-2, $$0.81 s$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>0.81</mml:mn> <mml:mi>s</mml:mi> </mml:mrow> </mml:math> for Area-3, and $$0.84 s$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>0.84</mml:mn> <mml:mi>s</mml:mi> </mml:mrow> </mml:math> for Area-4 with an average time of $$0.89 s$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>0.89</mml:mn> <mml:mi>s</mml:mi> </mml:mrow> </mml:math> for all the areas, whereas the average time for GWO: PI-PD, MPC/PI and GA-PI is $$3.48 s$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>3.48</mml:mn> <mml:mi>s</mml:mi> </mml:mrow> </mml:math> , $$10.36 s$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>10.36</mml:mn> <mml:mi>s</mml:mi> </mml:mrow> </mml:math> and $$18.47 s$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>18.47</mml:mn> <mml:mi>s</mml:mi> </mml:mrow> </mml:math> , respectively. The results demonstrate the effectiveness of the controller when compared to other controllers.