Privacy Preserving and Collusion Resistant Energy Sharing

Abstract

Energy has been increasingly generated or collected by different entities on the power grid (e.g., universities, hospitals and householdes) via solar panels, wind turbines or local generators in the past decade. With local energy, such electricity consumers can be considered as "microgrids" which can simulataneously generate and consume energy. Some microgrids may have excessive energy that can be shared to other power consumers on the grid. To this end, all the entities have to share their local private information (e.g., their local demand, local supply and power quality data) to each other or a third-party to find and implement the optimal energy sharing solution. However, such process is constrained by privacy concerns raised by the microgrids. In this paper, we propose a privacy preserving scheme for all the microgrids which can securely implement their energy sharing against both semihonest and colluding adversaries. The proposed approach includes two secure communication protocols that can ensure quantified privacy leakage and handle collusions.

Discovering communities for microgrids with spatial-temporal net energy

“…Finally, energy community discovery requests data collection from all the microgrids, which may compromise their privacy [36]. It is also interesting and challenging to propose privacy preserving energy community discovery techniques which enable the cooperation of microgrids while protecting their local information [5,7].…”

“…With autonomous energy, microgrids may fully or partially feed their local demand. Numerous microgrids would have great flexibility to utilize their local energy to collaboratively advance the energy management in the power grid, e.g., load balancing [4,5], energy sharing [6,7], and load shifting [8]. Thus, it is desirable to discover microgrid communities that can efficiently implement their cooperation in the grid [9][10][11].…”

Homogeneous and Mixed Energy Communities Discovery with Spatial-Temporal Net Energy

“…Furthermore, some cooperative models among distributed microgrids have been investigated in multiple applications, e.g., optimizing the power loss via a unified microgrid voltage profile [33], eliminating the central energy management unit and price coordinator via localized smart devices [5], load management via sharing local electricity [16], [19], [38], and load management via multiagent systems [45]. In this paper, we develop techniques to identify communities of microgrids which can directly implement all these cooperative applications within each energy community to further advance grid performance.…”

Securely Solving the Distributed Graph Coloring Problem

“…Finally, secure computation in real world applications can also be leveraged for the development of privacy preserving optimization. For instance, in the smart grid infrastructure [11,25,14,6,12] and search engine query applications [13,23,19,17], the secure communication protocols can be proposed based on the extension of privacy preserving linear or nonlinear programming models (by incorporating more real world constraints).…”