Active consumers who engage in energy consumption, production, storage and provide ancillary services in a dynamic and interactive manner will be an integral part of the future grid. Firstly, this dissertation models and analyzes the interaction between active consumers and aggregators with a specific focus on consumer actions in response to real-time electricity pricing and the resulting impact on grid voltage. A unique prospect theory based consumer behavior model is introduced. This model captures wide range of consumers each with their individual preferences by modeling the interaction between the active consumers and the aggregator as a Stackelberg game. However, unlike existing game theoretic efforts that assume rational behavior of consumers, the prospect theory based models systematically incorporate realistic consumer behavior including irrationality. Secondly, this dissertation develops probabilistic voltage sensitivity analysis. In contrast to prior approaches that limit themselves to economic aspects, the proposed techno-economic perspective provides an understanding of the impact of large scale penetration of active consumers on the physical grid. Most current studies are scenario-based, and derived results are scenario specific. Determining the impact of spatially distributed active consumers with temporally variable behavior requires investigation of a large number of scenarios, which is computationally intractable using current iterative power flow algorithms. This work provides a new analytical method of voltage sensitivity analysis that allows for stochastic analysis of change in grid voltage due to change in consumer behavior (load and generation choices). This work first derives an upper bound for change in voltage at a particular bus due to change in power consumption at other buses in a radial distribution network. Next, this bound is used to derive the probability distribution of change voltage at a bus due to randomly changing power consumption/injection of random spatial distribution of the active consumers. This upper bound is also used to develop an algorithmic approach to identify the dominant influencer of voltage fluctuations in the power distribution system. Thirdly, security and stability aspects of transactive energy market based power distribution system is investigated. Specifically, the impact of attacks on pricing/load signals on the physical grid is quantified. This work models the interaction between real-time electricity price and total energy demand in the form of a discrete time non-linear autonomous dynamical system. Equilibrium electricity price and energy demand associated with this coupled dynamical system is derived and conditions for bounded input bounded output (BIBO) stability are identified. Then, a BIBO stable algorithm to design real-time electricity pricing scheme from a techno-economic perspective is developed. Finally, the impact of various level of false data injection (FDI) attack on price of electricity, demand and distribution system voltage is investigated. This dissertation shows that impact of FDI attack on electricity prices is more severe than an attack on electricity demand.