TY - JOUR
T1 - Improved Stabilization of Nonlinear DC Microgrids
T2 - Cubature Kalman Filter Approach
AU - Kardan, Mohammad Amin
AU - Asemani, Mohammad Hassan
AU - Khayatiyan, Alireza
AU - Vafamand, Navid
AU - Khooban, Mohammad Hassan
AU - Dragicevic, Tomislav
AU - Blaabjerg, Frede
PY - 2018/9
Y1 - 2018/9
N2 - This paper investigates the injecting power stabilization of nonlinear dc microgrids (MGs) with constant power loads (CPLs). By considering a centralized controller scheme, the limitations of the communication utilities are considered. Therefore, limited information is transferred through the nonideal noisy communication network. Consequently, a cubature Kalman filter (CKF) with a third degree is proposed to mitigate the effect of the noisy measurement and the noisy network on the system's information. Moreover, an estimation-based robust feedback controller is developed to design an optimal value for the injecting power. The considered CKF algorithm is robust against the system uncertainty and noisy environments and has a low computational time for high-order dc MGs with a high number of sources and CPLs. In addition, a systematic procedure to compute the feedback gain of the controller is presented, which can be numerically solved by linear matrix inequality techniques. Hardware-in-the-loop real-time simulation results verify the simplicity of the controller implementation, enhanced performance for the case of limited information, and better robustness against the noisy measurements compared to the state-of-the-art methods.
AB - This paper investigates the injecting power stabilization of nonlinear dc microgrids (MGs) with constant power loads (CPLs). By considering a centralized controller scheme, the limitations of the communication utilities are considered. Therefore, limited information is transferred through the nonideal noisy communication network. Consequently, a cubature Kalman filter (CKF) with a third degree is proposed to mitigate the effect of the noisy measurement and the noisy network on the system's information. Moreover, an estimation-based robust feedback controller is developed to design an optimal value for the injecting power. The considered CKF algorithm is robust against the system uncertainty and noisy environments and has a low computational time for high-order dc MGs with a high number of sources and CPLs. In addition, a systematic procedure to compute the feedback gain of the controller is presented, which can be numerically solved by linear matrix inequality techniques. Hardware-in-the-loop real-time simulation results verify the simplicity of the controller implementation, enhanced performance for the case of limited information, and better robustness against the noisy measurements compared to the state-of-the-art methods.
KW - Constant power load (CPL)
KW - cubature Kalman filter (CKF)
KW - dc microgrid (MG)
KW - hardware-in-the-loop (HiL)
KW - linear matrix inequality (LMI)
KW - nonideal communication network
UR - http://www.scopus.com/inward/record.url?scp=85048885558&partnerID=8YFLogxK
U2 - 10.1109/TIA.2018.2848959
DO - 10.1109/TIA.2018.2848959
M3 - Journal article
SN - 0093-9994
VL - 54
SP - 5104
EP - 5112
JO - I E E E Transactions on Industry Applications
JF - I E E E Transactions on Industry Applications
IS - 5
M1 - 8388287
ER -