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Demand Response for Residential Loads in Smart Grid Under Normal and Abnormal Conditions

Authors(2) :-Dr. Shaharam Karimi, Raua Alwan

This paper proposes a price-based demand response program by the nonlinear control method. The demand response program is formulated as a nonlinear power management system with price feedback. We give the conditions of the price parameters for both the global asymptotic stability of the system and the social welfare optimality of the equilibrium point. Furthermore, the system is shown to be input-to-state (ISS) stable when there are additive disturbances on the power measurements and the price, and the discrete-time implementation of the power management system is given. Simulation results demonstrate the balance between supply and demand and the stability of the system with and without disturbances.
Dr. Shaharam Karimi, Raua Alwan
Smart Grid, Demand Response, Power Management System, Nonlinear Control, Disturbances
  • Albadi MH, El-Saadany E. A summary of demand response in electricity markets. Electric Power Syst Res 2008;78(11):1989–96.
  • Mohsenian-Rad A, Wong VW, Jatskevich J, Schober R, Leon-Garcia A.Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid. IEEE Trans Smart Grid 2010;1(3):320–31.
  • Sheikhi A, Bahrami S, Ranjbar A, Oraee H. Strategic charging method for plugged in hybrid electric vehicles in smart grids: a game theoretic approach.Int J Electric Power Energy Syst 2013;53:499–506.
  • Ma K, Hu G, Spanos JC. Distributed energy consumption control via real-time pricing feedback in smart grid. IEEE Trans Control Syst Technol 2014;22(5):1907–14.
  1. Nadali M, Mehdi E, Saha TK. Employing demand response in energy procurement plans of electricity retailers. Int J Electric Power Energy Syst 2014;63:455–60.
  2. Nazari M, Akbari Foroud A. Optimal strategy planning for a retailer considering medium and short-term decisions. Int J Electric Power Energy Syst 2013; 45(1):107–16.
  3. Lu H, Sriyanyong P, Song YH, Dillon T. Experimental study of a new hybrid PSO with mutation for economic dispatch with non-smooth cost function. Int JElectric Power Energy Syst 2010;32(9):921–35.
  4. Samadi P, Mohsenian-Rad A, Schober R, Wong VW, Jatskevich J. Optimal realtime pricing algorithm based on utility maximization for smart grid. In: 1st IEEE international conference on smart grid communications (SmartGridComm), 2010. IEEE; 2010. p. 415–20.
  5. Chen L, Li N, Jiang L, Low SH. Optimal demand response: problem formulation and deterministic case. New York: Springer; 2012. p. 63–85.
  6. Gatsis N, Giannakis GB. Residential load control: distributed scheduling and convergence with lost AMI messages. IEEE Trans Smart Grid 2012;3(2): 770–86.
  7. Yang J, Zhang G, Ma K. Matching supply with demand: a power control and real time pricing approach. Int J Electric Power Energy Syst 2014;61:111–7.
  8. Deng R, Yang Z, Chen J, Asr NR, Chow MY. Residential energy consumption scheduling: a coupled-constraint game approach. IEEE Trans Smart Grid 2014;5(3):1340–50.
  9. Wang and M. de Groot, "Managing end-user preferences in the smart grid," in Proc. 1st Int. Conf. Energy-Efficient Comput. Network. (ACM e-Energy), 2010.
  10. Mohsenian-Rad A, Wong VW, Jatskevich J, Schober R, Leon-Garcia A.Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid. IEEE Trans Smart Grid 2010;1(3):320–31.
  11. Chen L, Li N, Jiang L, Low SH. Optimal demand response: problem formulation and deterministic case. New York: Springer; 2012. p. 63–85.
  12. Samadi P, Mohsenian-Rad A, Schober R, Wong VW, Jatskevich J. Optimal realtime pricing algorithm based on utility maximization for smart grid. In: 1st IEEE international conference on smart grid communications (SmartGridComm), 2010. IEEE; 2010. p. 415–20.
  13. Wood AJ, Wollenberg BF. Power generation, operation, and control. Hoboken,NJ: John Wiley & Sons Inc.; 1996.
  14. Kelly FP, Maulloo AK, Tan DK. Rate control for communication networks: shadow prices, proportional fairness and stability. J Operat Res Soc 1998:237–52.
  15. Veit D, Weidlich A, Yao J, Oren S. Simulating the dynamics in two-settlement electricity markets via an agent-based approach. Int J Manage Sci Eng Manage 2006;1(2):83–97.
  16. Horn RA, Johnson CR. Matrix analysis. Cambridge: Cambridge University Press;1999.
Publication Details
  Published in : Volume 2 | Issue 6 | November-December 2016
  Date of Publication : 2016-12-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 51-58
Manuscript Number : IJSRST162588
Publisher : Technoscience Academy
PRINT ISSN : 2395-6011
ONLINE ISSN : 2395-602X
Cite This Article :
Dr. Shaharam Karimi, Raua Alwan, "Demand Response for Residential Loads in Smart Grid Under Normal and Abnormal Conditions ", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 2, Issue 6 , pp.51-58, November-December-2016
URL : http://ijsrst.com/IJSRST162588