Comparative Analysis Between Particle Swarm Optimization Algorithms Applied to Price-Based Demand Response

  • Diego L. Cavalca
  • Guilherme Spavieri
  • Ricardo A. S. FernandesEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10841)


Demand-side management is a useful and necessary strategy in the context of smart grids, as it allows to reduce electricity consumption in periods of increased demand, ensuring system reliability and minimizing resources wastage. In its range of activities, Demand Response programs have received great attention in recent years due to their potential impact measured in several studies. In this work, different approaches of the Particle Swarm Optimization algorithm are applied to the autonomous and distributed demand response optimization model based on energy price. In addition, a stochastic mechanism is proposed to mitigate the structural bias problem that such algorithm presents, boosting its application in the analyzed problem. Results provided by computational simulations show that the proposed approach contributes significantly to reduce the energy consumption costs in relation to tariff variations, as well as minimizing the use of residential equipment during peak hours of a group of consumers.


Particle Swarm Optimization Demand response Smart grid 



This paper was supported by FAPESP (grant number 2015/12599-0), CNPq (grant number 420298/2016-9) and CAPES.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Diego L. Cavalca
    • 1
  • Guilherme Spavieri
    • 2
  • Ricardo A. S. Fernandes
    • 1
    • 2
    Email author
  1. 1.Graduate Program in Computer ScienceFederal University of Sao CarlosSao CarlosBrazil
  2. 2.Department of Electrical EngineeringFederal University of Sao CarlosSao CarlosBrazil

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