Optimal data-driven adaptive overcurrent relay coordination for active distribution networks

Abstract

Massive integration of distributed generation originates the active distribution networks, introducing new control, protection and operation challenges. This paper proposes a strategy for adaptively protecting active distribution networks that undergo frequent changes in operating conditions. Numerical overcurrent relays capable of storing multiple setting groups, each with different settings designed to address various operating conditions, are used to overcome this issue. The proposed strategy uses locally acquired voltage and current measurements to accurately identify the operating conditions during fault occurrence. The identified condition is then used to select the appropriate overcurrent relay settings using a strategy which includes signal characterisation, data recognition, and optimisation to minimise the operating time for both primary and backup relays. Validation of the protection strategy is conducted on the IEEE 34-Bus test system, and the results indicate its ability to accurately detect different operating conditions in both connected and islanded operating modes, even in the presence of high-impedance faults and load variation. The performance rate exceeds 97.27% for all analysed cases, and the proposal identifies the operating condition in less than 20 ms after fault inception, demonstrating its low computational burden and suitability for implementation in field applications.