Sayyad Nojavan

A variety of operational and financial benefits is offered by demand response programs (DRPs) for load-serving entities, grid operators, and electricity customers. Variation of grid condition in different periods, highly capital-incentive system, and economics of electricity storage as well as long lead investment time are the most important characteristics of the power system. These features beside the different uncertainty sources in the system are the main reasons to implement DRPs, which can provide flexibility at considerably low cost. Regarding the demand, properly modeling of the way that consumers react against the time-dependent electricity prices is essential. It is seen that when the consumer faced by the very large or sudden power price increases, they tend to curtail their electricity consumption. Although, during the long term, in order to cope with periodic fluctuations, the consumers try to shift their load demand to balance the potential cost saving against the extra or inconvenience expense which is obtained by changing the consuming time. Also, developing a model, which properly presents the effects of DRPs as part of a forward-looking network planning is the main challenge of implementing and planning of the DRPs. Furthermore, providing a framework to address both the economic and technical aspects the system is the only way to solve the problem. Developing models, which are responsive to the power price, is essential to assay the effects of DRPs on different characteristics of market and network such as reserve margin, load profile, transmission congestion etc. It is obvious that many feasible structural forms are provided for the customer response. For example, linear models of price responsive loads are developed for the DRPs. Also, developing economic nonlinear models for price responsive loads are required because of the nonlinear formulation of the customer profit problem, which give more realistic modeling of the demand. Implementing vario