Visible to the public Model-Based Assessment for Balancing Privacy Requirements and Operational Capabilities in the Smart Grid

TitleModel-Based Assessment for Balancing Privacy Requirements and Operational Capabilities in the Smart Grid
Publication TypeConference Paper
Year of Publication2015
AuthorsKnirsch, Fabian, Engel, Dominik, Frincu, Marc, Prasanna, Viktor
Conference Name2015 IEEE Power Energy Society Innovative Smart Grid Technologies Conference (ISGT)
ISBN Number978-1-4799-1785-3
Keywordsapproximation theory, billing, Collaboration, common high-level use case, composability, data privacy, demand response, distributed power generation, forward mapping privacy, Heterogeneous systems, Human Behavior, human factors, Load Curtailment, Mathematical model, merging, Metrics, model-based assessment, numeric approximation, Numerical models, operational capabilities, operational requirement, optimal balancing algorithm, policy-based governance, power generation protection, power system security, privacy, Privacy Requirements, privacy-aware data processing, privacy-aware data storage, pubcrawl, resilience, Resiliency, Scalability, security, Smart grid, Smart Grid Privacy, Smart grids, Smart Metering, smart power grids, University of Southern California, USC microgrid

The smart grid changes the way energy is produced and distributed. In addition both, energy and information is exchanged bidirectionally among participating parties. Therefore heterogeneous systems have to cooperate effectively in order to achieve a common high-level use case, such as smart metering for billing or demand response for load curtailment. Furthermore, a substantial amount of personal data is often needed for achieving that goal. Capturing and processing personal data in the smart grid increases customer concerns about privacy and in addition, certain statutory and operational requirements regarding privacy aware data processing and storage have to be met. An increase of privacy constraints, however, often limits the operational capabilities of the system. In this paper, we present an approach that automates the process of finding an optimal balance between privacy requirements and operational requirements in a smart grid use case and application scenario. This is achieved by formally describing use cases in an abstract model and by finding an algorithm that determines the optimum balance by forward mapping privacy and operational impacts. For this optimal balancing algorithm both, a numeric approximation and - if feasible - an analytic assessment are presented and investigated. The system is evaluated by applying the tool to a real-world use case from the University of Southern California (USC) microgrid.

Citation Keyknirsch_model-based_2015