The vision of the smart grid is predicated upon pervasive use of modern digital communication techniques in today's power system. As wide area measurements and control techniques are being developed and deployed for a more resilient power system, the role of communication networks is becoming prominent. Advanced communication infrastructure provides much wider system observability and enables globally optimal control schemes. Wide area measurement and monitoring with Phasor Measurement Units (PMUs) or Intelligent Electronic Devices (IED) is a growing trend in this context. However, the large amount of data collected by PMUs or IEDs needs to be transferred over the data network to control centers where real-time state estimation, protection, and control decisions are made. The volume and frequency of such data transfers, and real-time delivery requirements mandate that sufficient bandwidth and proper delay characteristics must be ensured for the correct operations. Power system dynamics get influenced by the underlying communication infrastructure. Therefore, extensive integration of power system and communication infrastructure mandates that the two systems be studied as a single distributed cyber-physical system. This dissertation proposes a global event-driven co-simulation framework, which is termed as GECO, for interconnected power system and communication network. GECO can be used as a design pattern for hybrid system simulation with continuous/discrete sub-components. An implementation of GECO is achieved by integrating two software packages: PSLF and NS2 into the framework. Besides, this dissertation proposes and studies a set of power system applications which can be only properly evaluated on a co-simulation framework like GECO, namely communication-based distance relay protection, all-PMU state estimation and PMU-based out-of-step protection. All of them take advantage of interplays between the power grid and the communication infrastructure. The GECO experiments described in this dissertation not only show the efficacy of the GECO framework, but also provide experience on how to go about using GECO in smart grid planning activities. / Ph. D.