Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Electrical and Electronic Engineering(IJEREEE)

Monthly Journal for Electrical and Electronic Engineering

ISSN : 2395-2717 (Online)

Call For Paper : Vol. 9, Issue 7 2022
Optimization Approaches for Demand Side Management in Smart Grids

Author : H. Lakshmi 1 2

Date of Publication :21st February 2018

Abstract: This paper describes the novel simulation and optimization approaches for demand-side management (DSM) in smart grids. Over the past two decades, power systems have witnessed significant changes in the use of renewable and distributed energy resources, energy control technologies, and technical advances in communication and computation, which has led to the development of smart grids. Smart grids provide sustainable power grids with the capabilities of self-healing and automatic execution in an isolated mode, but the operation and control planning of smart grids are challenging procedures. The main challenges arise from energy load scheduling of customers using interruption load management (ILM) and load shifting strategies; communication between customers and utility companies or third-party aggregators to increase customer satisfaction and decrease costs; and the need to provide reliable and high-quality energy to customers to address the main challenges in the operation and control planning of smart grid threshold values.

Reference :

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    3.  P.Murphy et al.,“Enabling tomorrow’s electricity system: report of the Ontario Smart Grid forum,” Tech. Rep., Ontario Smart Grid Forum, 2010,
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    1. J.Gao, Y. Xiao, J.Liu, W.Ling, and C.L.P.Chen, “A survey of communication / networking in Smart Grids, “Future Generation Computer Systems, vol.28, no.2, pp.391– 404,2012.
    2. W. Wang, Y. Xu, and M. Khanna, “A survey on the communication architectures in smartgrid,”Computer Networks, vol.55, no.15, pp.3604–3629,2011.
    3. P.Murphy et al.,“Enabling tomorrow’s electricity system: report of the Ontario Smart Grid forum,” Tech. Rep., Ontario Smart Grid Forum, 2010,
    4. CEA,“The smart grid: a pragmatic approach,” Tech .Rep., Canadian Electricity Association, 2010, http://www. electricity. ca/ media /Smart Grid /SmartGridpaperEN. pdf.
    5. Palensky, P. and D. Dietrich, Demand side management: Demand respons intelligent energy systems, and smart loads. IEEE transactions on industrial informatics, 2011. 7(3): p. 381-388
    6. Sad, W., et al., Game-theoretic methods for the smart grid: An overview of microgrid systems, demand-side management, and smart grid communications. IEEE Signal Processing Magazine, 2012. 29(5): p. 86-105.
    7. Strbac, G., Demand side management: Benefits and challenges. Energy policy, 2008. 36(12): p. 4419-4426.
    8. Wang, B., Y. Li, and C. Gao, Demand side management outlook under smart grid infrastructure. Automation of Electric Power Systems, 2009. 20: p. 17-22.
    9.  Boshell, F. and O. Veloza. Review of developed demand side management programs including different concepts and their results. in Transmission and Distribution Conference and Exposition: Latin America, 2008 IEEE/PES. 2008. IEEE.
    10. Ming-jun, W., Load management and demand side management in electricity market environment [J]. Power System Technology, 2005. 5: p. 000.
    11. Mohsenian-Rad, A.-H., et al., Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid. IEEE transactions on Smart Grid, 2010. 1(3): p. 320-331.

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