Hassan Bevrani - Renewable Integrated Power System Stability and Control

PMU data‐based power‐load imbalance estimation is a key estimation to successfully handle the emergency control strategies, e.g. load shedding, and protection plans. In case of detecting a contingency or an emergency condition, following comparing of frequency, voltage, and their rate of changes with the specified threshold values, an estimation algorithm must estimate the size of disturbance to use in the available emergency control systems and special protection schemes. This online estimation is an important issue to realize a successful load‐shedding scheme with minimum amount of shed load.

Conventionally, for the estimation of the size of load‐power mismatch, the swing equation is used. The estimated imbalance based on this method may far from real power mismatch as it relies on three worst assumptions: (i) there is no additional active power variation except for that of disturbance, (ii) there is a negligible reactive‐power imbalance in response to sudden active power imbalance, and (iii) the inertia constant assumed to be known. This under/over‐estimation causes inaccurate calculation of total amount of load to be shed.

In [117], for estimating the size of disturbance, some appropriate base‐case features are selected from a set of pre‐defined base cases. Moreover, an efficient yet simple logic is defined to select appropriate base‐case for the received data. This approach benefits from the use of PMU data to precise calculation of the required amount of load to be shed, in one‐step and in a short time in comparison with the actual time. The proposed scheme relies on fast, yet iterative, estimation of frequency nadir, and time of minimum frequency occurrence. Accordingly, the inertia constant as well as the size of power mismatch are estimated which, in turn, compares with the maximum size of imbalance, satisfying the pre‐specified thresholds, to determine the amount of shed load.

Modern power grids face new technical challenges arising from the increasing penetration of power‐electronic‐connected RESs/DGs. Increasing MGs/DGs penetration level may adversely affect frequency response and voltage and system control and lead to degraded performance of traditional control schemes. This, in turn, may result in large deviations and, potentially, system instability.

This chapter provides the pre‐requirement terminology and general background for the next chapters of this book. The term power system stability and control with an updated brief review on the areas of frequency, voltage, and angle controls, concerning the penetration of RESs/DGs, is discussed. In response to the existing challenges in penetration of more RESs/DGs to the grid, the necessity of using data‐driven modeling, parameters estimation, and control synthesis in wide‐area power systems is emphasized.

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