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Demand Side Management Using Meta-Heuristic Techniques and ToU in Smart Grid

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Advances in Network-Based Information Systems (NBiS 2017)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 7))

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Abstract

In this paper, we perform performance evaluation of home energy management system (HEMS) for demand side management (DSM) in smart grid. In this work, smart home is equipped with HEMS, smart meter, and smart appliances for two-way communication between utility and consumer. HEMS performs scheduling of smart appliances based on meta-heuristic techniques to balance load for whole day to avoid peak creation in any hour. Smart meter performs electricity cost calculation for consumed energy based on time of use (ToU) pricing signal provided by utility. Our focus is to efficiently handle user demand, reduction in peak-to-average ratio (PAR) and electricity cost minimization. The implemented meta-heuristic techniques in this work are: Enhanced differential evolution (EDE), harmony search algorithm (HSA), bacterial foraging algorithm (BFA), and genetic algorithm (GA). The simulation results show the performance of HEMS based on optimization techniques using ToU.

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References

  1. Mhanna, S., Verbi, G., Chapman, A.C.: A faithful distributed mechanism for demand response aggregation. IEEE Trans. Smart Grid 7(3), 1743–1753 (2016)

    Article  Google Scholar 

  2. Ye, F., Qian, Y., Hu, R.Q.: A real-time information based demand-side management system in smart grid. IEEE Trans. Parallel Distrib. Syst. 27(2), 329–339 (2016)

    Article  Google Scholar 

  3. Nguyen, H.K., Song, J.B., Han, Z.: Distributed demand side management with energy storage in smart grid. IEEE Trans. Parallel Distrib. Syst. 26(12), 3346–3357 (2015)

    Article  Google Scholar 

  4. Basit, A., Sardar Sidhu, G.A., Mahmood, A., Gao, F.: Efficient and autonomous energy management techniques for the future smart homes. IEEE Trans. Smart Grid (2015)

    Google Scholar 

  5. Li, C., Xinghuo, Y., Wenwu, Y., Chen, G., Wang, J.: Efficient computation for sparse load shifting in demand side management. IEEE Trans. Smart Grid 8(1), 250–261 (2017)

    Article  Google Scholar 

  6. Samadi, P., Wong, V.W.S., Schober, R.: Load scheduling and power trading in systems with high penetration of renewable energy resources. IEEE Trans. Smart Grid 7(4), 1802–1812 (2016)

    Article  Google Scholar 

  7. Safdarian, A., Fotuhi-Firuzabad, M., Lehtonen, M.: Optimal residential load management in smart grids: a decentralized framework. IEEE Transactions on Smart Grid 7(4), 1836–1845 (2016)

    Article  Google Scholar 

  8. Ma, J., Chen, H.H., Song, L., Li, Y.: Residential load scheduling in smart grid: a cost efficiency perspective. IEEE Trans. Smart Grid 7(2), 771–784 (2016)

    Google Scholar 

  9. Javaid, N., Javaid, S., Abdul, W., Ahmed, I., Almogren, A., Alamri, A., Niaz, I.A.: A hybrid genetic wind driven heuristic optimization algorithm for demand side management in smart grid. Energies 10(3), 319 (2017)

    Article  Google Scholar 

  10. Zhu, Z., Tang, J., Lambotharan, S., Chin, W.H., Fan, Z.: An integer linear programming based optimization for home demand-side management in smart grid. In: 2012 IEEE PES Innovative Smart Grid Technologies (ISGT), pp. 1–5. IEEE (2012)

    Google Scholar 

  11. Zhao, Z., Lee, W.C., Shin, Y., Song, K.-B.: An optimal power scheduling method for demand response in home energy management system. IEEE Trans. Smart Grid 4(3), 1391–1400 (2013)

    Article  Google Scholar 

  12. Ma, K., Yao, T., Yang, J., Guan, X.: Residential power scheduling for demand response in smart grid. Int. J. Electr. Power Energy Syst. 78, 320–325 (2016)

    Article  Google Scholar 

  13. Khalid, A., Javaid, N., Mateen, A., Khalid, B., Khan, Z.A., Qasim, U.: Demand side management using hybrid bacterial foraging and genetic algorithm optimization techniques. In: 2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS), pp. 494–502. IEEE (2016)

    Google Scholar 

  14. Zafar, A., Shah, S., Khalid, R., Mehboob Hussain, S., Rahim, H., Javaid, N.: A meta-heuristic home energy management system. In: 2017 31st International Conference on Advanced Information Networking and Applications Workshops (WAINA), pp. 244–250. IEEE (2017)

    Google Scholar 

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Author information

Authors and Affiliations

  1. COMSATS Institute of Information Technology, Islamabad, 44000, Pakistan

    Sajeeha Ansar, Kainat Ansar, Muhammad Zabih Ullah Raja & Nadeem Javaid

  2. National University of Sciences and Technology, Islamabad, 44000, Pakistan

    Wajeeha Ansar

  3. Roots Millennium School, Islamabad, 44000, Pakistan

    Mohammad Hashir Mehmood

Authors
  1. Sajeeha Ansar
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  2. Wajeeha Ansar
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  3. Kainat Ansar
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  4. Mohammad Hashir Mehmood
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  5. Muhammad Zabih Ullah Raja
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  6. Nadeem Javaid
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Corresponding author

Correspondence to Nadeem Javaid .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Faculty of Information Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Rissho University, Tokyo, Japan

    Tomoya Enokido

  3. Hosei University, Tokyo, Japan

    Makoto Takizawa

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Ansar, S., Ansar, W., Ansar, K., Mehmood, M.H., Raja, M.Z.U., Javaid, N. (2018). Demand Side Management Using Meta-Heuristic Techniques and ToU in Smart Grid. In: Barolli, L., Enokido, T., Takizawa, M. (eds) Advances in Network-Based Information Systems. NBiS 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 7. Springer, Cham. https://doi.org/10.1007/978-3-319-65521-5_18

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  • DOI: https://doi.org/10.1007/978-3-319-65521-5_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65520-8

  • Online ISBN: 978-3-319-65521-5

  • eBook Packages: EngineeringEngineering (R0)

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