Abstract: ` i ABSTRACT The distribution grid is expected to change in the near future as a result of recent advancements in the field of smart grids. The future grid will accommodate generation and storage options, active consumer participation through demand response schemes, and the widespread installation of smart energy management systems. With more demand side participation, distributed generators, and (potentially) meshed distribution system networks, there is a push to integrate transmission and distribution (T&D) systems models together. Ideally, the T&D systems should be modeled by an integrated optimal power flow (OPF) framework and solved simultaneously to schedule the generation and demand in the entire system. In comparison, existing practices do not include the distribution system when solving the OPF for the transmission system; instead, the load is estimated and placed at the connection point at the sub-transmission level. However, integrating T&D system models together is a challenge for OPF due to the size of the system, which makes these problems computationally intractable with existing technologies. The objective of this research is to develop an integrated T&D framework that couples the two subsystems together with due consideration to conventional demand flexibility. The proposed framework ensures accurate representation of the system resources and the network conditions when modeling the distribution system in the transmission OPF and vice-versa. It is further used to develop an accurate pricing mechanism (Distribution-based Location Marginal Pricing, ` ii DLMP), which is reflective of the moment-to-moment costs of generating and delivering electrical energy, for the distribution system. By accurately modeling the two subsystems , we can improve the economic efficiency and the system reliability, as the price sensitive resources (PSR) can be controlled to behave in a way that benefits the power system as a whole. The proposed framework decomposes the integrated OPF framework into two subsequent OPF problems: the transmission OPF and the distribution OPF. The decomposition requires iterations between the two sub-problems to ensure adequate representation of one subsystem when solving the other subsystem. Instead of using a one-shot approach where the transmission system modeled is solved only once, the proposed approach requires resolving the transmission OPF with an updated residual demand curve. The distribution system is modeled by its aggregate residual demand curve in the transmission OPF while the transmission system is modeled by a transmission-constrained residual supply curve in the distribution OPF. The iterative framework is further used to demonstrate the application and potential …