Realistic Differentially-Private Transmission Power Flow Data Release. (arXiv:2103.14036v1 [cs.CR])

For the modeling, design and planning of future energy transmission networks,
it is vital for stakeholders to access faithful and useful power flow data,
while provably maintaining the privacy of business confidentiality of service
providers. This critical challenge has recently been somewhat addressed in [1].
This paper significantly extends this existing work. First, we reduce the
potential leakage information by proposing a fundamentally different
post-processing method, using public information of grid losses rather than
power dispatch, which achieve a higher level of privacy protection. Second, we
protect more sensitive parameters, i.e., branch shunt susceptance in addition
to series impedance (complete pi-model). This protects power flow data for the
transmission high-voltage networks, using differentially private
transformations that maintain the optimal power flow consistent with, and
faithful to, expected model behaviour. Third, we tested our approach at a
larger scale than previous work, using the PGLib-OPF test cases [10]. This
resulted in the successful obfuscation of up to a 4700-bus system, which can be
successfully solved with faithfulness of parameters and good utility to data
analysts. Our approach addresses a more feasible and realistic scenario, and
provides higher than state-of-the-art privacy guarantees, while maintaining
solvability, fidelity and feasibility of the system.



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