Modeling and Control of Smart Standalone Microgrids within Cyber Physical System Frameworks

TL;DR

This paper develops control strategies for smart standalone microgrids within cyber-physical frameworks, addressing stability challenges caused by cyber and physical disturbances, sensor failures, and renewable energy variability.

Contribution

It introduces adaptive control schemes for hybrid microgrids and a cyber-physical coordination framework to enhance stability under disturbances and sensor faults.

Findings

Adaptive control improves stability during atmospheric changes.

Cyber-physical coordination enhances disturbance handling.

Sensor fault resilience is increased in the proposed control schemes.

Abstract

The ability of grid-connected microgrids (MG) to operate in islanded mode makes them an efficient solution for improving power quality and reliability. This property of MG is very much beneficial for remote and undeveloped areas in progressing countries. Moreover, ICT technology has led to the development of Smart Standalone Microgrids (SSMG), which are inundated with a plethora of sensors. This allows multiple microgrids to be controlled in a coordinated way to achieve self-sufficiency in power. In such systems, there is much interdependency between various power, control and communication parameters. Owing to these developments, the control of physical variables like voltage get affected by cyber parameters like, communication structure, delay and link loss. Moreover, due to isolation from main grid and abundance of renewable power generation units like solar PV, the inertia of these standalone grids is reduced greatly and calls for advanced control algorithms which use an abundance of sensors. Hence, the stability of these systems is greatly affected by sensor failures apart from many physical parameters like load and environmental conditions. In this thesis, a generic structure of an AC-DC hybrid microgrid is considered which is subdivided into various AC and DC counterparts. The AC and DC SSMGs are separately modeled and control solutions are proposed to improve their stability. The first two contributions propose adaptive control schemes on the primary level of control in the hybrid microgrid. Their function is to provide fast and stable parameters regulation in the DCSSMG when subjected to atmospheric changes along with faults in sensor readings. The third and fourth contributions cater to development of coordinated control cyber physical frameworks in the ACSSMG to handle the presence of simultaneous disturbances from both cyber/physical domains.