The power transfer capability of existing transmission networks can be enhanced through the use of automated system protection schemes (SPS), which rapidly respond to disturbances on the network to keep the system's variables within operational bounds. However, reliance on such schemes may expose the network to large impacts-including blackouts-if the SPS does not respond as designed, so the deployment of SPS should balance risks and benefits. This paper formulates a risk-based cost-benefit framework that allows the operator to strike an optimal balance between constraint costs and risks of demand curtailment due to malfunctioning SPS. It is applied to a simple 4-bus power system inspired by the GB network, for which an exact optimisation problem can be formulated. A component-based dependability model is developed for the SPS to determine its failure modes and associated probabilities. The resulting cost-minimisation problem is solved for a range of operating conditions and SPS reliability levels. The results consistently show cost savings from the use of an SPS, even if it is highly unreliable, when a hedging strategy may be used. The optimal solution is highly sensitive to the problem parameters, but it is demonstrated that optimal operational strategies are associated with particular SPS outcomes. This finding may be used as empirical guidance to develop operational strategies for complex networks with unreliable SPS.

Distribution networks have been traditionally conceived for transporting electricity downstream into low voltage demand nodes. However, the connection of significant amounts of distributed generation may reverse this condition, resulting in distribution nodes exporting power to other parts of the network. The current planning standard of the UK distribution networks (Engineering recommendation P2/6) requires making available sufficient capacity and redundancy for downstream flows under peak demand levels. However, it does not explicitly consider the implications of DG-mediated flow reversals that may cause flow constraints under circuit outage conditions. Relying on a Monte Carlo approach to sample wind and demand with adjustable correlations, this paper provides insights into the risks associated with an increase of variable distributed generation to the point where reverse flows may exceed the connection capacity under circuit outage conditions. Remote tripping schemes that disconnect distributed generators upon occurrence of a fault are explored to mitigate outage related costs. The latter strategy carries benefits but also novel risks in the form of a reliance on real-time communication and control, which may malfunction. It is shown that even unreliable corrective actions convey significant benefits to system reliability.