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

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.

[1]  Robinson Musembi,et al.  Livestock Farmers' Perception on Generation of Cattle Waste-based Biogas Methane: the case of Embu West District, Kenya , 2014 .

[2]  Muhammad Babar,et al.  Design of a Framework for the Aggregator using Demand Reduction Bid (DRB) , 2014 .

[3]  Vincent W. S. Wong,et al.  Advanced Demand Side Management for the Future Smart Grid Using Mechanism Design , 2012, IEEE Transactions on Smart Grid.

[4]  Mohammed H. Albadi,et al.  A summary of demand response in electricity markets , 2008 .

[5]  Anita,et al.  Design and Implementation of Solar PV for Power Quality Enhancement in Three-Phase Four-Wire Distribution System , 2015 .

[6]  Susanto Rahardja,et al.  Optimal real-time price based on a statistical demand elasticity model of electricity , 2011, 2011 IEEE First International Workshop on Smart Grid Modeling and Simulation (SGMS).

[7]  Brock J. LaMeres,et al.  Fuzzy logic-based direct load control of residential electric water heaters and air conditioners recognizing customer preferences in a deregulated environment , 1999, 1999 IEEE Power Engineering Society Summer Meeting. Conference Proceedings (Cat. No.99CH36364).

[8]  J. Torriti,et al.  Demand response experience in Europe: Policies, programmes and implementation , 2010 .

[9]  Kun-Yuan Huang,et al.  Integrating direct load control with interruptible load management to provide instantaneous reserves for ancillary services , 2004, IEEE Transactions on Power Systems.

[10]  Muhammad Babar,et al.  A Novel Algorithm for Demand Reduction Bid based Incentive Program in Direct Load Control , 2013 .

[11]  B. J. Kirby,et al.  Spinning Reserve From Responsive Loads , 2003 .

[12]  S.M. Amin For the Good of the Grid , 2008, IEEE Power and Energy Magazine.

[13]  Alec Brooks,et al.  Demand Dispatch , 2010, IEEE Power and Energy Magazine.

[14]  Carlos Henggeler Antunes,et al.  A multiple objective decision support model for the selection of remote load control strategies , 2000 .

[15]  Mariesa Crow,et al.  The New Centurions , 2010, IEEE Power and Energy Magazine.

[16]  Benjamin F. Hobbs,et al.  Measuring the economic value of demand-side and supply resources in integrated resource planning models , 1993 .

[17]  D. Kirschen Demand-side view of electricity markets , 2003 .

[18]  Muhammad Babar,et al.  An algorithm for load curtailment in aggregated demand response program , 2012 .

[19]  Torgeir Ericson,et al.  Direct load control of residential water heaters , 2009 .

[20]  Muhammad Babar,et al.  The conception of the aggregator in demand side management for domestic consumers , 2013 .