Energy Reports (Nov 2022)

Battery-aided privacy preservation of household electricity load profiles under time-of-use tariffs

  • Mao Zhu,
  • Xi Luo,
  • Zhiyi Li,
  • Can Wan

Journal volume & issue
Vol. 8
pp. 437 – 448

Abstract

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Collecting fine-grained data on electricity usage can reduce the user’s energy cost by accurate demand response and improve the services from utilities. However, non-intrusive power load monitoring (NILM) technology shows that these data will reveal the user’s privacy. In this paper, we first design a price-sensitive BLH scheme which achieves differential privacy. Then regarding such issues above, we propose a price-sensitive cost-friendly differential privacy (PCDP) scheme through a contextual multi-armed bandit framework. Last, realistic electricity consumption data is extracted to validate the proposed method. The results show that our method provides effective privacy protection and achieve considerable cost saving.

Keywords