@INPROCEEDINGS{Lizondo17,
     author = {Lizondo, Diego and Araujo, Pedro and Will, Adrian and Rodriguez, Sebastian},
   keywords = {artificial immune network, ASPECS Methodology, Biological system modeling, Cyber-Physical Systems, Demand-Side Management, energy consumption, Estimation, Load modeling, Multi-agent systems, Multiagent System, Organizations, Peak load, Smart Grids},
      month = {April},
      title = {Multiagent Model for Distributed Peak Shaving System with Demand-Side Management Approach},
  booktitle = {2017 First IEEE International Conference on Robotic Computing (IRC)},
       year = {2017},
      pages = {352-357},
        doi = {10.1109/irc.2017.50},
   abstract = {Energy management is one of the most important problems in the world today, due among other reasons to the increase in clients electricity demand which generates the Peak Load problem. The rise of Smart Grids as a new paradigm, developed mainly to address those requirements, allows the design and implementation of more complex management and monitoring systems. In this paper, we propose a modelization based on Organizational Multiagent System (MAS) for a distributed control system. Its main aims consist into address the Peak Load problem with Cyber-Physical Systems using the Demand-Side Management approach. The control decision process of the system implements an Artificial Immune Network algorithm to determine the state of consumption of any controlled device connected to the Smart Grid. The first stage of the ASPECS methodology was adopted in order to develop the proposed models. The simulation results show a reduction of about 20\% in energy consumption. We conclude that the MAS approach adopted fits the requirements to model the proposed AIN-Peak Shaving System.}
}