@inproceedings{81e143f43a414e69a55f4c229a1a339e,
title = "Efficient customer selection for sustainable demand response in smart grids",
abstract = "Regulating the power consumption to avoid peaks in demand is a common practice. Demand Response(DR) is being used by utility providers to minimize costs or ensure system reliability. Although it has been used extensively there is a shortage of solutions dealing with dynamic DR. Past attempts focus on minimizing the load demand without considering the sustainability of the reduced energy. In this paper an efficient algorithm is presented which solves the problem of dynamic DR scheduling. Data from the USC campus micro grid were used to evaluate the efficiency as well as the robustness of the proposed solution. The targeted energy reduction is achieved with a maximum average approximation error of r¿ 0.7\%. Sustainability of the reduced energy is achieved with respect to the optimal available solution providing a maximum average error less than 0.6\%. It is also shown that a solution is provided with a low computational cost fulfilling the requirements of dynamic DR.",
keywords = "change making, demand response, optimization, real time, scheduling, sustainability",
author = "Vasileios Zois and Marc Frincu and Charalampos Chelmis and Saeed, \{Muhammad Rizwan\} and Viktor Prasanna",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 International Green Computing Conference, IGCC 2014 ; Conference date: 03-11-2014 Through 05-11-2014",
year = "2015",
month = feb,
day = "10",
doi = "10.1109/IGCC.2014.7039149",
language = "English",
series = "2014 International Green Computing Conference, IGCC 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2014 International Green Computing Conference, IGCC 2014",
}