Frequency stability study of interconnected power systems with high penetration of renewable energy in the restructured environment: emulation and control of virtual inertia using intelligent techniques.
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Date
2021
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Abstract
The main aim of power system operations and control is to ensure reliability and quality of power
supply, a key action that helps in achieving this aim is frequency control. Frequency control in
power systems is the ability to maintain the system frequency within specified operating limits,
i.e., proper coordination between generation and load. The task of frequency control, more importantly,
load frequency control (LFC) is becoming a complex control problem in the design and
operation of modern electric power systems due to its growing size, changing market structure,
newly emerging distributed renewable energy sources with little or no inertia support, evolving
regulatory requirements and the increasing interconnectedness of power systems. These developments
can lead to a reduction in the active overall inertia in the power system which reduces
its frequency response capability by increasing the amplitude of frequency deviation, continuous
frequency oscillations and increased settling time after a power mismatch in the system. The potential
role of virtual inertia in the task of frequency control has been identified as an integral
part of modern power systems. Therefore, in this thesis, novel methods for implementing virtual
inertia using intelligent control techniques are proposed in the LFC framework of a multi-area interconnected
system with high penetration of renewable energy in the deregulated environment.
The first method proposes the novel application of the artificial bee colony (ABC) optimization
algorithm in the design of the virtual inertial control in a grid-connected wind energy conversion
system (WECS). The WECS operates below the maximum power point to reserve a fraction of
active power for frequency response. The proposed ABC-based control method minimizes the first
frequency undershoot and active power transients compared to the classical optimization method.
Due to the non-storable and variable nature of renewable energy sources, the first method may not
be accessible when needed. To tackle this challenge, the second method proposes the application
of an energy storage system (ESS) and the type-II fuzzy logic control (FLC) in the development
of the virtual inertia control strategy. The proposed type-II FLC method gives a better performance
than the type-I FLC and derivative-based control methods with adaptive inertia gain, faster
response time for active power injection/discharge, and damped frequency oscillations. Lastly, a
novel hybrid LFC scheme is developed to further improve the dynamic response and stability of
the system. The hybrid LFC scheme consists of a robust unknown input observer (UIO) for state
estimation of the system in the presence of unknown inputs/disturbances, and the interval type-II
FLC for the LFC loop. The robust UIO relays the true state of the system frequency to the LFC
block in each control area to maintain its frequency and net tie line power flow at scheduled values.
The proposed methods are designed and implemented using the MATLAB/Simulink Software.
Description
Doctoral Degree. University of KwaZulu- Natal, Durban.