TY - GEN
T1 - Incentive design for Direct Load Control programs
AU - Alizadeh, Mahnoosh
AU - Xiao, Yuanzhang
AU - Scaglione, Anna
AU - Van Der Schaar, Mihaela
PY - 2013/1/1
Y1 - 2013/1/1
N2 - We study the problem of optimal incentive design for voluntary participation of electricity customers in a Direct Load Scheduling (DLS) program, a new form of Direct Load Control (DLC) based on a three way communication protocol between customers, embedded controls in flexible appliances, and the central entity in charge of the program. Participation decisions are made in real-time on an event-based basis, with every customer that needs to use a flexible appliance considering whether to join the program given current incentives. Customers have different interpretations of the level of risk associated with committing to pass over the control over the consumption schedule of their devices to an operator, and these risk levels are only privately known. The operator maximizes his expected profit of operating the DLS program by posting the right participation incentives for different appliance types, in a publicly available and dynamically updated table. Customers are then faced with the dynamic decision making problem of whether to take the incentives and participate or not. We define an optimization framework to determine the profit-maximizing incentives for the operator. In doing so, we also investigate the utility that the operator expects to gain from recruiting different types of devices. These utilities also provide an upper-bound on the benefits that can be attained from any type of demand response program.
AB - We study the problem of optimal incentive design for voluntary participation of electricity customers in a Direct Load Scheduling (DLS) program, a new form of Direct Load Control (DLC) based on a three way communication protocol between customers, embedded controls in flexible appliances, and the central entity in charge of the program. Participation decisions are made in real-time on an event-based basis, with every customer that needs to use a flexible appliance considering whether to join the program given current incentives. Customers have different interpretations of the level of risk associated with committing to pass over the control over the consumption schedule of their devices to an operator, and these risk levels are only privately known. The operator maximizes his expected profit of operating the DLS program by posting the right participation incentives for different appliance types, in a publicly available and dynamically updated table. Customers are then faced with the dynamic decision making problem of whether to take the incentives and participate or not. We define an optimization framework to determine the profit-maximizing incentives for the operator. In doing so, we also investigate the utility that the operator expects to gain from recruiting different types of devices. These utilities also provide an upper-bound on the benefits that can be attained from any type of demand response program.
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U2 - 10.1109/Allerton.2013.6736638
DO - 10.1109/Allerton.2013.6736638
M3 - Conference contribution
AN - SCOPUS:84897740713
SN - 9781479934096
T3 - 2013 51st Annual Allerton Conference on Communication, Control, and Computing, Allerton 2013
SP - 1029
EP - 1036
BT - 2013 51st Annual Allerton Conference on Communication, Control, and Computing, Allerton 2013
PB - IEEE Computer Society
T2 - 51st Annual Allerton Conference on Communication, Control, and Computing, Allerton 2013
Y2 - 2 October 2013 through 4 October 2013
ER -