Demand-side energy storage management is studied from a joint privacy-energy cost optimization perspective. Assuming that the user's power demand profile as well as the electricity prices are known non-causally, the optimal energy management (EM) policy that jointly increases the privacy of the user and reduces his energy cost is characterized. The backward water-filling interpretation is provided for the optimal EM policy. While the energy cost is reduced by requesting more energy when the prices are lower, energy consumption privacy is achieved by a smoother output load. It is shown that both gains can be achieved by using a limited size storage unit. The optimal trade-off between the user's privacy and energy cost is characterized, and the impact of the size of the storage unit and the resolution of the smart meter readings on this trade-off is studied.
Optimal privacy-cost trade-off in demand-side management with storage / Tan, O.; Gunduz, D.; Gomez-Vilardebo, J.. - 2015-:(2015), pp. 370-374. (Intervento presentato al convegno 16th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2015 tenutosi a KTH Royal Institute of Technology, swe nel 2015) [10.1109/SPAWC.2015.7227062].
Optimal privacy-cost trade-off in demand-side management with storage
D. Gunduz;
2015
Abstract
Demand-side energy storage management is studied from a joint privacy-energy cost optimization perspective. Assuming that the user's power demand profile as well as the electricity prices are known non-causally, the optimal energy management (EM) policy that jointly increases the privacy of the user and reduces his energy cost is characterized. The backward water-filling interpretation is provided for the optimal EM policy. While the energy cost is reduced by requesting more energy when the prices are lower, energy consumption privacy is achieved by a smoother output load. It is shown that both gains can be achieved by using a limited size storage unit. The optimal trade-off between the user's privacy and energy cost is characterized, and the impact of the size of the storage unit and the resolution of the smart meter readings on this trade-off is studied.
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