الفهرس 
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Abstract
Smart grid operations face a significant threat from the presence of cyber attacks or bad data that may contaminate the system observations. Therefore, in this thesis, we are interested in introducing a new strategy for detecting the presence of bad data in smart grids and we also try to simultaneously estimate it in order to be able to separate the bad data from the system observations. We aim to obtain the attack free observations which reflect the true state of the smart grid. This can be done by defining a joint detection-estimation strategy based on Bayesian and non-Bayesian settings where the costs in general will be functions of the observation. We start with Bayes approach and derive the detector (which in general may not be a likelihood ratio test) and then we set the problem by defining some maximum constraint under the null hypothesis based on the derived detector and minimize certain cost under the alternative hypothesis. Then, we apply our model on some cases that other models reported in previous works failed to deal with.Moreover, we focus on the important role the synchronized phasor measurement units (PMUs)play in the process of monitoring, controlling, and protection of today’s smart grid networks.Therefore, a strategic placement of these PMUs is essential to perform these tasks. Previous studies in this area mostly concentrate on minimizing the total number of PMUs while maintaining the system fully observable in various contingency situations. However, none of them take into consideration the communication constraints among PMUs, e.g., the finite communication capacity available when using power line communications (PLC) among PMUs. In this thesis, we introduce two different formulations to solve the problem of optimal PMUs placement (OPP), while taking into consideration a communication constraint for the case where the communication between the PMUs and the control center is established via wired power lines.