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http://dx.doi.org/10.5370/JEET.2015.10.1.064

The Consumer Rationality Assumption in Incentive Based Demand Response Program via Reduction Bidding  

Babar, Muhammad (Electrical Energy Systems Group, Department of Electrical Engineering, Technology University of Eindhoven)
Imthias Ahamed, T.P. (Department of Electrical and Computer Engineering, College of Engineering, Dhofar University)
Alammar, Essam A. (Department of Electrical Engineering, King Saud University)
Publication Information
Journal of Electrical Engineering and Technology / v.10, no.1, 2015 , pp. 64-74 More about this Journal
Abstract
Because of the burgeoning demand of the energy, the countries are finding sustainable solutions for these emerging challenges. Demand Side Management is playing a significant role in managing the demand with an aim to support the electrical grid during the peak hours. However, advancement in controls and communication technologies, the aggregators are appearing as a third party entity in implementing demand response program. In this paper, a detailed mathematical framework is discussed in which the aggregator acts as an energy service provider between the utility and the consumers, and facilitate the consumers to actively participate in demand side management by introducing the new concept of demand reduction bidding (DRB) under constrained direct load control. Paper also presented an algorithm for the proposed framework and demonstrated the efficacy of the algorithm by considering few case studies and concluded with simulation results and discussions.
Keywords
Aggregator; Demand side management; Direct load control; Dynamic bidding; Dynamic programming;
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  • Reference
1 M. Babar, T.A. Taj, T.I. Ahamed, and E.A. AlAmmar, “The conception of the aggregator in demand side management for domestic consumers,” 2013.
2 M. Babar, T.A. Taj, T.I. Ahamed, and I. Ijaz, “Design of a framework for the aggregator using demand reduction bid (drb),” Journal of Energy Technologies and Policy, vol. 4, no. 1, pp. 1-7, 2014.
3 P. Samadi, H. Mohsenian-Rad, R. Schober, and V. Wong, “Advanced demand side management for the future smart grid using mechanism design,” IEEE Transactions on Smart Grid, vol. 3, no. 3, pp. 1170-1180, 2012.   DOI   ScienceOn
4 R. Yu, W. Yang, and S. Rahardja, “Optimal real-time price based on a statistical demand elasticity model of electricity,” in First International Workshop on Smart Grid Modeling and Simulation (SGMS), 2011 IEEE. IEEE, 2011, pp. 90-95.
5 C. Puckette, G. Saulnier, R. Korkosz, and J. Hershey, “Ghm aggregator,” Feb. 12 2002, uS Patent 6,346,875.
6 S. Amin, “For the good of the grid,” IEEE Power and Energy Magazine, vol. 6, no. 6, pp. 48-59, 2008.   DOI   ScienceOn
7 “Us department of energy - smart grid.” [Online]. Available: http://energy.gov/oe/technologydevelopment/smart-grid
8 B. Kirby, Spinning reserve from responsive loads. Department of Energy-United States. 2003.
9 M. Albadi and E. El-Saadany, “A summary of demand response in electricity markets,” Electric Power Systems Research, vol. 78, no. 11, pp. 1989-1996, 2008.   DOI   ScienceOn
10 K. Huang and Y. Huang, “Integrating direct load control with interruptible load management to provide instantaneous reserves for ancillary services,” IEEE Transactions on Power Systems, vol. 19, no. 3, pp. 1626-1634, 2004.   DOI   ScienceOn
11 “Aggregator managed portfolio (amp) program, pacific gas and electric company.” [Online]. Available: http://www.pge.com/mybusiness /energysaving srebates/demandresponse/amp/
12 H. Salehfar, P. Noll, B. LaMeres, M. Nehrir, and V. Gerez, “Fuzzy logic-based direct load control of residential electric water heaters and air conditioners recognizing customer preferences in a deregulated environment,” in IEEE Power Engineering Society Summer Meeting, 1999., vol. 2. IEEE, 1999, pp. 1055-1060.
13 M. Babar, I. Ahmed, A. Shah, S. Al Ghannam, E. AlAmmar, N. Malik, and F. Pazehri, “An algorithm for load curtailment in aggregated demand response program,” in 2012 IEEE PES Conference on Innovative Smart Grid Technologies-Middle East (ISGT Middle East). IEEE, 2012.
14 H. Jorge, C. Antunes, and A. Martins, “A multiple objective decision support model for the selection of remote load control strategies,” IEEE Transactions on Power Systems, vol. 15, no. 2, pp. 865-872, 2000.   DOI   ScienceOn
15 I. Cobelo, “Active control of distribution networks,” Ph.D. dissertation, The University of Manchester, 2005.
16 J. Torriti, M. G. Hassan, and M. Leach, “Demand response experience in europe: Policies, programmes and implementation,” Energy, vol. 35, no. 4, pp. 1575-1583, 2010.   DOI   ScienceOn
17 M. Babar, T. Imthias Ahamed, E. A. Al-Ammar, and A. Shah, “A novel algorithm for demand reduction bid based incentive program in direct load control,” Energy Procedia, vol. 42, pp. 607-613, 2013.   DOI   ScienceOn
18 T. Ericson, “Direct load control of residential water heaters,” Energy Policy, vol. 37, no. 9, pp. 3502-3512, 2009.   DOI   ScienceOn
19 D. S. Kirschen, “Demand-side view of electricity markets,” Power Systems, IEEE Transactions on, vol. 18, no. 2, pp. 520-527, 2003.   DOI   ScienceOn
20 B. F. Hobbs, H. Rouse, and D. T. Hoog, “Measuring the economic value of demand-side and supply resources in integrated resource planning models,” Power Systems, IEEE Transactions on, vol. 8, no. 3, pp. 979-987, 1993.   DOI   ScienceOn
21 A. Brooks, E. Lu, D. Reicher, C. Spirakis, and B. Weihl, “Demand dispatch,” IEEE Power and Energy Magazine,, vol. 8, no. 3, pp. 20-29, 2010.   DOI