Abstract
One-level optimization methods have been proposed to optimize the load profile of a single user or a cluster of users in the smart grids. In this work, two two-level optimization methods are studied, one considering technical requirements and other considering economic criteria. In the upper level, the supplier optimizes it objective function. Meanwhile, at the lower level, users optimize their electrical costs. The proposed methods are based on genetic algorithm methods. In this sense, an indirect control is established in which users react to a price signal. Simulations results illustrate that both cases improve the demand profile and increase the retailer profit. However, when the supplier tries to maximize the profit, some users receive benefits in detriment of others, concluding that the technical approach is preferable than the economical one.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
