TY - JOUR
T1 - Differentially Private Demand Side Management for Incentivized Dynamic Pricing in Smart Grid
AU - Ul Hassan, Muneeb
AU - Rehmani, Mubashir Husain
AU - Du, Jia Tina
AU - Chen, Jinjun
N1 - Publisher Copyright:
IEEE
PY - 2022
Y1 - 2022
N2 - In order to efficiently provide demand side management (DSM) in smart grid, carrying out pricing on the basis of real-time energy usage is considered to be the most vital tool because it is directly linked with the finances associated with smart meters. Hence, every smart meter user wants to pay minimum possible amount along with getting maximum benefits. In here, usage based dynamic DSM pricing strategies plays their role and provide users with specific incentives. However, these reported real-time values can leak privacy of smart meter users, which can cause serious consequences such as spying. Moreover, most of dynamic pricing algorithms charge all users equally irrespective of their contribution in causing peak factor. Therefore, this paper proposes a modified usage based dynamic pricing mechanism that only charges the users responsible for causing peak factor. We further integrate differential privacy to protect the privacy of real-time smart metering data, and to calculate accurate billing we propose a noise adjustment method. Finally, we propose Demand Response enhancing Differential Pricing (DRDP) strategy that effectively enhances demand response along with providing dynamic pricing to smart meter users. The performance evaluation shows that DRDP outperforms previous mechanisms in terms of dynamic pricing and privacy preservation.
AB - In order to efficiently provide demand side management (DSM) in smart grid, carrying out pricing on the basis of real-time energy usage is considered to be the most vital tool because it is directly linked with the finances associated with smart meters. Hence, every smart meter user wants to pay minimum possible amount along with getting maximum benefits. In here, usage based dynamic DSM pricing strategies plays their role and provide users with specific incentives. However, these reported real-time values can leak privacy of smart meter users, which can cause serious consequences such as spying. Moreover, most of dynamic pricing algorithms charge all users equally irrespective of their contribution in causing peak factor. Therefore, this paper proposes a modified usage based dynamic pricing mechanism that only charges the users responsible for causing peak factor. We further integrate differential privacy to protect the privacy of real-time smart metering data, and to calculate accurate billing we propose a noise adjustment method. Finally, we propose Demand Response enhancing Differential Pricing (DRDP) strategy that effectively enhances demand response along with providing dynamic pricing to smart meter users. The performance evaluation shows that DRDP outperforms previous mechanisms in terms of dynamic pricing and privacy preservation.
KW - Demand Response (DR)
KW - Demand Side Management (DSM)
KW - Differential privacy
KW - Differential Privacy (DP)
KW - Dynamic Pricing
KW - Load modeling
KW - Pricing
KW - Privacy
KW - Privacy Preservation
KW - Real-time systems
KW - Smart Grid (SG)
KW - Smart homes
KW - Vehicle dynamics
UR - http://www.scopus.com/inward/record.url?scp=85127027831&partnerID=8YFLogxK
U2 - 10.1109/TKDE.2022.3157472
DO - 10.1109/TKDE.2022.3157472
M3 - Article
AN - SCOPUS:85127027831
JO - IEEE Transactions on Knowledge and Data Engineering
JF - IEEE Transactions on Knowledge and Data Engineering
SN - 1041-4347
ER -