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This paper presents an improved secondary voltage control (SVC) methodology incorporating compressive sensing (CS) for a multi-area power system. SVC minimizes the voltage deviation of the load buses while CS deals with the problem of the limited bandwidth capacity of the communication channel by reducing the size of massive data output from phasor measurement unit (PMU) based monitoring system. The proposed strategy further incorporates the application of a Morphological Median Filter (MMF) to reduce noise from the output of the PMUs. To keep the control area secure and protected locally, Mathematical Singular Entropy (MSE) based fault identification approach is utilized for fast discovery of faults in the control area. Simulation results with 27-bus and 486-bus power systems show that CS can reduce the data size up to 1/10 th while the MSE based fault identification technique can accurately distinguish between fault and steady state conditions. N communication channel, and communication channel cost.CS is regarded as a promising joint data acquisition and reconstruction method to deal with the problem of limited bandwidth and data congestion. The data retrieved from the PMUs can be compressed before sending through the communication channel and can be recovered at the end of communication channel. Plenty of research has been performed to recover the signal at the end of communication channel [13], [14]. A CS based control strategy is developed for load frequency control in a multi-area power system network [15]. This strategy helps reduce the transmission data loss and increase the reliability of the communication network.Performance of CS may be affected by the noise in the signal, which may induce error in the signal processing and degrade the system's dynamic performance [16]. In order to deal with such problems, several noise filtering techniques have been developed in the recent literature [17], [18]. Based on the theory of Mathematical Morphology (MM), a mathematical morphological filter (MMF) is proposed in [21],

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In real-time applications involving power flow equations, measuring of voltage phase angle difference of the connected buses is essential. However, it needs special techniques to measure voltage angle difference, which may enlarge the computational burden of the working controller and hence, may make the control process slow. In this paper, authors investigate the approximation of angle difference to zero and its effects on the convergence speed and optimal solutions of a distributed algorithm. To test this approximation, a distributed nonlinear algorithm is proposed to optimize the multi-objective function which includes power loss, voltage deviation and cost of reactive power generation, by controlling the reactive power generations from distributed generators. Authors investigate the reasons which may outlaw making this approximation and finally, propose a condition to make such approximation. Importance of making this approximation in terms of fast convergence of the algorithms is also illustrated.Index Terms-voltage angles difference approximation, AC power flow, Reactive power control, power loss, voltage deviation.