Year: 2024
Type: article
Abstract: Integrating renewable energy sources into the power distribution grid challenges protection system operation, leading to protection blinding when circuit breakers fail to trip due to fault current contribution from these sources. Communication-based adaptive protection can address this issue, but communication system components like sensors can fail. This research proposes a genetic algorithm-based approach to optimally place redundant sensors, minimising protection blinding under communication uncertainty within a redundancy budget. The fault tolerance, measured by a new metric called redundancy degree, reflects the number of redundant components deployed. Results demonstrate the algorithm’s effectiveness in optimising redundant sensor locations, reducing system costs, and improving fault tolerance. For the system and scenarios investigated, an average of 60% redundant sensors are relocated, reducing the average protection trip time by 36.65% compared to a baseline approach that does not consider communication uncertainty. This encourages incorporating communication component failure considerations in power system planning.
Institutions: University of Passau, Coventry University
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4404317110