Model predictive control of plug-in hybrid electric vehicles for frequency regulation in a smart grid

• Published in: IET generation, transmission & distribution Vol. 11; no. 16; pp. 3974 - 3983
• Main Authors: Elsisi, M, Soliman, Mahmoud, Aboelela, Magdy A.S, Mansour, W
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 09.11.2017
• Subjects: battery powered vehicles; bat‐inspired algorithm; BIA; decentralised control; decentralised model predictive control; energy storage; energy storage systems; frequency control; frequency perturbations; frequency regulation; governor dead bands; governor input signal manipulation; hybrid electric vehicles; ICA; imperialist competitive algorithm; load disturbances; MPC; PEHV battery; plug‐in hybrid electric vehicles; power system interconnection; predictive control; renewable energy sources; RES fluctuations; Research Article; smart grid; smart power grids; smart three‐area interconnected power system; system nonlinearities; time‐domain analysis; time‐domain based objective function; turbine generation rate constraints; MPC; governor input signal manipulation; frequency perturbations; imperialist competitive algorithm; PEHV battery; governor dead bands; smart power grids; decentralised control; smart three-area interconnected power system; energy storage systems; energy storage; power system interconnection; system nonlinearities; BIA; RES fluctuations; smart grid; battery powered vehicles; renewable energy sources; turbine generation rate constraints; ICA; plug-in hybrid electric vehicles; time-domain based objective function; time-domain analysis; load disturbances; frequency control; frequency regulation; bat-inspired algorithm; hybrid electric vehicles; predictive control; decentralised model predictive control
• ISSN: 1751-8687; 1751-8695
• DOI: 10.1049/iet-gtd.2016.2120

Integration between energy storage systems and renewable energy sources (RESs) can effectively smooth natural fluctuations of the latter and ensure better frequency regulation. Optimal performance of the plug-in hybrid electric vehicle (PEHV) battery, having longer plug-in than driving time, makes it a good candidate for integration with RESs. Decentralised model predictive control (MPC) is proposed here for frequency regulation in a smart three-area interconnected power system comprising PHEVs. Two MPCs in each area are considered to manipulate the input signals of the governor and PHEV in order to tolerate frequency perturbations subject to load disturbances and RES fluctuations. Setting the parameters of the six MPC controllers is carried out simultaneously based on imperialist competitive algorithm (ICA) and bat-inspired algorithm (BIA). Time-domain based objective function is suggested to account for system non-linearities emanating from governor dead bands and turbine generation rate constraints. The proposed tuning procedures utilising ICA and BIA are completely accomplished off-line. Comparative simulation results are presented to confirm the effectiveness of the proposed design.