Modeling and Control of a Renewable Hybrid Energy System with Battery Storage

Abstract

Abstract Conventional power systems heavily rely on fossil fuel resources for electricity generation, leading to the rapid depletion of these non-renewable sources and a simultaneous increase in environmental pollution. In response to the challenges, microgrids, incorporating renewable energy sources as well as energy storage systems and loads, have surfaced as a practical and sustainable alternative. Microgrids have the flexibility to operate in either autonomous or grid-connected mode, with the latter allowing seamless access to the utility grid. This thesis focuses specifically on island microgrids, with an emphasis on AC microgrids. This focus stems from the prevalence of AC in the majority of existing power systems and end-user loads. In this microgrid variant, power electronics-based inverters assume a pivotal role in controlling and managing power distribution among parallel distributed generation units. Consequently, this thesis addresses the imperative for sophisticated control techniques, detailing the application of advanced methods to meet the evolving requirements in voltage and frequency regulation for inverter-interfaced distributed generations, including droop control techniques, virtual synchronous generator approaches, and virtual oscillator control methods, to establish seamless power sharing among parallel inverters within microgrids. Secondly, HOMER Pro software is employed to determine the optimal configuration and sizing for our proposed hybrid microgrid, consisting of photovoltaic panels and batteries. Finally, a decentralized power management scheme utilizing the model predictive control approach is simulated and tested for a hybrid-island DC/AC microgrid. This is done to validate the effectiveness of the proposed control strategy under different scenarios and load conditions. Finally, a proposed predictive current-limiting method across various fault scenarios is presented to mitigate the identified risks for both symmetrical and asymmetrical faults.

Keywords: Islanded Microgrid, Droop Control, Virtual Synchronous Generator, Virtual Oscillator Control, Predictive Control, Microgrid Optimization, Fault Protection.