COI-based quantitative frequency security assessment of power system in estimating maximum penetration level of wind power

Due to the increase in sustainable energy resource integration, the operation and control of power system have become very complicated. This has resulted in a significant challenge faced by system operators to maintain a stable power system operation. With the widespread integration of wind power to the system, the frequency security assessment (FSA) has become essential due to the impact of less inertia and variable nature brought by this power on system frequency. Many studies have been conducted assessing the frequency security level of power system. However, these methods can only measure the severity of disturbance at one point in time. On top of that, most assessment methods depend on a unit frequency that may differ according to disturbance location or unit status. Therefore, there is a need to find a comprehensive method for assessing frequency security covering the time of frequency deviation based on equivalent system frequency. Thus, the present study was conducted to explore and address a new method to evaluate frequency security, identify system’s weakest frequency bus and estimate the maximum wind penetration level using transient frequency deviation index (TFDI) based on the Centre of Inertia frequency (fCOI). The first objective of this study is to use fCOI together with TFDI to quantitatively assess system’s security level. Thus, a methodology evaluating the frequency security level is presented in this study. The second objective of this thesis seeks to identify the weakest frequency bus using the ability of TFDI to evaluate the security level of individual buses (consumers). The final purpose of this study is to introduce a method to estimate the maximum level of wind power that can be integrated into the grid by maintaining acceptable operation frequency. The first contribution of this study is represented by the development of a new and particular method for FSA to enhance security assessment. By using fCOI features, the security level of system disturbances can be easily achieved without identifying all system bus frequencies. Additionally, this method is able to evaluate whole system security levels irrespective of affected generator or disturbance location. Previously, TFDI was not used to identify system’s weakest bus. Therefore, the second contribution of this study is the introduction of an approach that can identify system’s weakest bus frequency using the ability of TFDI to evaluate the security level of individual bus and use it as a wind power integrated bus to enhance the accuracy in estimating maximum wind power penetration level. Finally, the third contribution of the study is that it provides a simple method to estimate the maximum allowable amount of wind power that can be added to the grid without affecting system frequency security. This new method is simple as it does not require complicated calculations or historical data.

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