  When energy customers schedule loads ahead of time, this information, if
acquired by their energy retailer, can improve the retailer's load forecasts.
Better forecasts lead to wholesale purchase decisions that are likely to result
in lower energy imbalance costs, and thus higher profits for the retailer.
Therefore, this paper monetizes the value of the customer schedulable load data
by quantifying the retailer's profit gain from adjusting the wholesale purchase
based on such data. Using a cooperative game theoretic approach, the retailer
translates their increased profit in expectation into the value of cooperation,
and redistributes a portion of it among the customers as monetary incentives
for them to continue providing their load data. Through case studies, this
paper demonstrates the significance of the additional profit for the retailer
from using the proposed framework, and evaluates the long-term monetary
benefits to the customers based on different payoff allocation methods.
