Power systems that are known as the most complex systems encounter different types of disturbances and emergence events. To operate such systems in a stable mode, several control protection techniques are in need. Frequency plays a vital role in power systems and needs to be properly maintained in a permissible level. To this end, under-frequency load-shedding (UFLS) techniques are used to intercept the frequency decline when a system encounters a severe disturbance. In this paper, a novel, wide-area measurement system (WAMS)-based optimal UFLS technique is proposed. The system frequency response (SFR) model is identified online based on the real-time measurements collected by phasor measurement units (PMUs). Then, the SFR model is used to design a new optimal multi-stage UFLS scheme. Imperialist competitive algorithm (ICA), which is a powerful evolutionary computing method, is then adopted for solving the suggested multi-stage UFLS optimization problem. The applicability of the proposed method is shown on a practical test system. The effectiveness of the proposed optimal multi-stage UFLS scheme is verified by several simulation and comparison scenarios.
Wide-Area Measurement System-Based Optimal Multi-Stage Under-Frequency Load-Shedding in Interconnected Smart Power Systems Using Evolutionary Computing Techniques
