Optimal battery management with ADHDP in smart home environments

  • Authors:

  • Danilo Fuselli;Francesco De Angelis;Matteo Boaro;Derong Liu;Qinglai Wei;Stefano Squartini;Francesco Piazza

  • Affiliations:

  • Dipartimento di Ingegneria dell'Informazione, Universitá Politecnica delle Marche, Ancona, Italy;Dipartimento di Ingegneria dell'Informazione, Universitá Politecnica delle Marche, Ancona, Italy;Dipartimento di Ingegneria dell'Informazione, Universitá Politecnica delle Marche, Ancona, Italy;State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China;State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China;Dipartimento di Ingegneria dell'Informazione, Universitá Politecnica delle Marche, Ancona, Italy;Dipartimento di Ingegneria dell'Informazione, Universitá Politecnica delle Marche, Ancona, Italy

  • Venue:
  • ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part II
  • Year:
  • 2012

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Abstract

In this paper an optimal controller for battery management in smart home environments is presented in order to save costs and minimize energy waste. The considered scenario includes a load profile that must always be satisfied, a battery-system that is able to storage electrical energy, a photovoltaic (PV) panel, and the main grid that is used when it is necessary to satisfy the load requirements or charge the battery. The optimal controller design is based on a class of adaptive critic designs (ACDs) called action dependent heuristic dynamic programming (ADHDP). Results obtained with this scheme outperform the ones obtained by using the particle swarm optimization (PSO) method.