A Robust Cascade Controller for Load Frequency Control of a Standalone Microgrid Incorporating Electric Vehicles

• Published in: Electric power components and systems Vol. 48; no. 6-7; pp. 711 - 726
• Main Authors: Khokhar, Bhuvnesh, Dahiya, Surender, Singh Parmar, K. P.
• Format: Journal Article
• Language: English
• Published: Philadelphia Taylor & Francis 27.08.2020; Taylor & Francis Ltd
• Subjects: Algorithms; cascade control; Clean energy; Computer simulation; Control stability; Controllers; Distributed generation; Eigenvalues; electric vehicle; Electric vehicles; Electrical loads; Energy consumption; Energy storage; energy storage systems; Frequency control; integral square error; load frequency control; Optimization; PI-PD cascade controller; Power management; renewable and green energy sources; Robust control; salp swarm optimization; standalone microgrid; Storage systems; total energy model
• ISSN: 1532-5008; 1532-5016
• DOI: 10.1080/15325008.2020.1797936

Intermittency in the output power of renewable and green energy sources (RGES) and low inertia of a standalone microgrid (SMG) result in large frequency deviations. Use of energy storage systems (ESSs) alleviate the SMG frequency deviations in an adorable manner but their high cost and low power density calls for alternative sources to balance the mismatch between power supply and demand. In recent years, utilization of the battery of an electric vehicle (EV) to minimize the frequency deviations has gained a lot of attention. Consequently, this paper proposes a robust and newly developed bio-inspired Salp Swarm Optimization (SSO) algorithm based PI-PD cascade controller for load frequency control (LFC) of the SMG integrated with the EVs. To demonstrate the efficacy of the proposed controller, its performance has been compared with other well-known controllers and algorithms considering diverse SMG operating scenarios. Simulation results distinctly prove the superiority of the proposed controller over the other controllers. Also, robustness of the proposed controller has been tested subject to ±50% variation in certain SMG parameters. Results clearly justify the robustness of the proposed controller. Additionally, operational stability of the SMG has been appraised through Eigenvalue and Bode diagram analysis for all the scenarios.