A novel adaptive intelligent MPC scheme for frequency stabilization of a microgrid considering SoC control of EVs

• Published in: Applied energy Vol. 309; p. 118423
• Main Authors: Khokhar, Bhuvnesh, Parmar, K. P. Singh
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.2022
• Subjects: Adaptive intelligent MPC (AIMPC); Electric vehicle; Load frequency control; Microgrid; SoC control; SoC control; Electric vehicle; Load frequency control; Adaptive intelligent MPC (AIMPC); Microgrid
• ISSN: 0306-2619; 1872-9118
• DOI: 10.1016/j.apenergy.2021.118423

In the recent years, the vehicle-to-grid (V2G) technology has been successfully implemented to stabilize the frequency deviations in a microgrid (MG) whereby charging/discharging of battery of electric vehicles (EVs) is utilized depending upon their state-of-charge (SoC). Compared to the conventional battery energy storage technology, lower degradation tendency and lesser cost of an EV battery are obvious reasons for its utilization as an alternate. This paper proposes a novel adaptive intelligent model predictive control (AIMPC) scheme for frequency stabilization of an MG considering the SoC control of the battery of the EVs. The MPC scheme operates by predicting the future behavior of a plant whereby an explicit discrete-time state-space model of the plant is utilized. Since optimal performance of the MPC depends upon the tuning parameter (τw) present in its cost function, an intelligent optimization algorithm is implemented to dynamically optimize the parameter τw and simultaneously the proposed control scheme is made adaptive. Effect of the SoC control on the frequency deviation response (FDR) of the MG is demonstrated. Further, competence of the proposed control scheme is established over the adaptive fuzzy MPC and PID controller considering diverse loading conditions in the MG. Simulation results clearly establish that the FDRs of the MG are improved with the implementation of the proposed control scheme. Lastly, sensitivity of the proposed scheme is corroborated considering parametric uncertainties in the MG. •A novel adaptive intelligent MPC scheme is proposed for LFC analysis of an MG.•State-of-charge (SoC) control of EV battery is simultaneously considered.•Effect of SoC control is demonstrated on the LFC performance of the microgrid.•Competence of the proposed scheme is established over some reputed control schemes.•Diverse loading patterns are considered in the MG for the performance comparison.