Electric power systems are undergoing a transformation, characterized by an increase in power electronic converter interfaced technologies, e.g. wind and solar resources, FACTS devices, High-Voltage DC (HVDC) lines or power electronic interfaced loads. Increasing penetration of renewable energy resources, low gas prices, and the retirement of coal and nuclear power plants motivate the use of gas-fired power plants to mitigate the variability and uncertainty of wind and solar resources. The reliance on natural gas for electricity generation has increased over the past years in the US which comes with associated reliability and security risks due to the dependency an energy system may have on one another. Poor coordination between power and gas operations may compound the weaknesses of an already congested network. In addition, the proliferation of smart grid technologies that control distribution systems introduce higher levels of variability and uncertainty to the operation of power grids. In this research, we present a set of tools to model energy systems, including transmission and distribution power systems, or natural gas pipelines, and cyber networks. This framework is then used to devise algorithms that improve the security and reliability of interdependent energy systems and propose counter-measures against unexpected events. The first part of this thesis (Chapter 2) presents the models and algorithms to simulate and optimize North American power and gas delivery operations, both in transmission and distribution systems. The second part of this thesis (Chapter 3) provides novel datasets that aim to serve as a support to perform studies using the models proposed in Chapter 2. In this section, we focus our efforts in natural gas datasets in the continental United States, filling a gap in the literature and enabling academic studies of coupled natural gas and electricity delivery operations. In addition, we propose models to generate high-resolution and scalable solar time series to better capture the impacts of renewable energy uncertainty and variability on power system operations. The last part of this thesis (Chapters 4 and 5) studies the events that compromise security and reliability of energy systems from two different angles. We consider contingency events that are a result of a cyber-attack, e.g. perpetuated by a terrorist group or a nation-state, or due to natural circumstances, e.g. failure of a generator unit and extreme weather events. In these chapters, we propose algorithms and counter-measures to mitigate contingency events by ensuring that the system can operate in a safe and flexible secure region.