  The utility company has many motivations for modifying energy consumption
patterns of consumers such as revenue decoupling and demand response programs.
We model the utility company--consumer interaction as a principal--agent
problem. We present an iterative algorithm for designing incentives while
estimating the consumer's utility function. Incentives are designed using the
aggregated as well as the disaggregated (device level) consumption data. We
simulate the iterative control (incentive design) and estimation (utility
learning and disaggregation) process for examples including the design of
incentives based on the aggregate consumption data as well as the disaggregated
consumption data.
