Air Conditioning for Smart Home Energy Management System

  • Authors

    • A. Ashraf
    • M. Faisal
    • K. Parvin
    • Pin Jern Ker
    • M. A. Hannan
    2018-11-30
    https://doi.org/10.14419/ijet.v7i4.35.22896
  • Automatic control, Electricity consumption, Grid, Smart meter, Utility bill.
  • Abstract

    Smart load management system with an advanced metering infrastructure operates to monitor the electricity consumption by the load and transferring data to the utility grid. It has direct benefit to the end-users by managing the load. This system has incorporated with home appliance for achieving the goal of home energy management system (HEMS) such as efficient energy utilization of house by avoiding the wastage. Efficient loading system can strengthen the efficient power utilization and thus can save the economy greatly. Air conditioner (AC), thermostat associated with a room were selected for this purpose as they have the high demand of electricity consumption. This study mainly focuses on developing the mathematical model and simulate it for the considered home appliances to assess the trend of electricity consumption. Research proved that, considering the ambient temperature developed model can provide the specific instructions for automatic controlling of the appliances which will save the electricity consumption and utility bill of end-users compare to the manual operation of the system. Matlab /Simulink software was used to implement and justify the model.

  • References

    1. [1] N. Kushiro and T. Kondo, “Home Energy Management by Handling Life Event,†no. 25330372, pp. 497–498, 2016.

      [2] S. Maharjan, Q. Zhu, Y. Zhang, S. Gjessing, and T. Başar, “Demand response management in the smart grid in a large population regime,†IEEE Trans. Smart Grid, vol. 7, no. 1, pp. 189–199, 2016.

      [3] M. M. Jalali and A. Kazemi, “Demand side management in a smart grid with multiple electricity suppliers,†Energy, vol. 81, pp. 766–776, 2015.

      [4] Safdarian, M. Fotuhi-Firuzabad, and M. Lehtonen, “Benefits of Demand Response on Operation of Distribution Networks: A Case Study,†Syst. Journal, IEEE, vol. PP, no. 99, pp. 1–9, 2014.

      [5] K. C. Sou, J. Weimer, H. Sandberg, and K. H. Johansson, “Scheduling smart home appliances using mixed integer linear programming,†IEEE Conf. Decis. Control Eur. Control Conf., pp. 5144–5149, 2011.

      [6] B. Zhou et al., “Smart home energy management systems: Concept, configurations, and scheduling strategies,†Renew. Sustain. Energy Rev., vol. 61, pp. 30–40, 2016.

      [7] J. Han, C.-S. Choi, and I. Lee, “More efficient home energy management system based on ZigBee communication and infrared remote controls,†IEEE Trans. Consum. Electron., vol. 57, no. 1, pp. 85–89, 2011.

      [8] S. Uddin, H. Shareef, A. Mohamed, and M. A. Hannan, “An analysis of harmonics from dimmable LED lamps,†2012 IEEE Int. Power Eng. Optim. Conf. PEOCO 2012 - Conf. Proc., pp. 182–186, 2012.

      [9] Salam, A. Mohamed, M. A. Hannan, and H. Shareef, “An improved inverter control scheme for managing the distributed generation units in a microgrid,†Int. Rev. Electr. Eng., vol. 5, no. 3, pp. 891–899, 2010.

      [10] L. I. Minchala-Avila, J. Armijos, D. Pesántez, and Y. Zhang, “Design and Implementation of a Smart Meter with Demand Response Capabilities,†Energy Procedia, vol. 103, no. April, pp. 195–200, 2016.

      [11] M. Pipattanasomporn, M. Kuzlu, and S. Rahman, “An algorithm for intelligent home energy management and demand response analysis,†IEEE Trans. Smart Grid, vol. 3, no. 4, pp. 2166–2173, 2012.

      [12] Di Giorgio and L. Pimpinella, “An event driven Smart Home Controller enabling consumer economic saving and automated Demand Side Management,†Appl. Energy, vol. 96, pp. 92–103, 2012.

      [13] On Adaptable Smart Home Energy Systems [14] Missaoui, R., Joumaa, H., Ploix, S. & Bacha, S. 2014. Managing Energy Smart Homes According to Energy Prices: Analysis of a Building Energy Management System. Energy and Buildings 71: 155-167.

      [14] D. Shahgoshtasbi and M. M. Jamshidi, “A new intelligent neuro-fuzzy paradigm for energy-efficient homes,†IEEE Syst. J., vol. 8, no. 2, pp. 664–673, 2014.

      [15] Y. Zhang, P. Zeng, and C. Zang, “Optimization Algorithm for Home Energy Management System Based on Artificial Bee Colony in Smart Grid,†pp. 734–740, 2015.

  • Downloads

  • How to Cite

    Ashraf, A., Faisal, M., Parvin, K., Ker, P. J., & Hannan, M. A. (2018). Air Conditioning for Smart Home Energy Management System. International Journal of Engineering & Technology, 7(4.35), 487-490. https://doi.org/10.14419/ijet.v7i4.35.22896

    Received date: 2018-12-02

    Accepted date: 2018-12-02

    Published date: 2018-11-30