Integrated reliability and cost–benefit-based standards for transmission network operation

The growing interest in decarbonizing electricity systems, together with advances in communication and information technologies that may support the application of demand and generation solutions to solve network problems, has initiated reviews of traditional operational practices and security grid standards in a number of jurisdictions. The key concern is that these historical practices and standards, mostly developed in the 1950s, may be inappropriate for the new emerging system as they may pose entry barriers for both renewable generation and Smart Grid technologies. In this context, the current paper presents a probabilistic cost–benefit framework for the development of future efficient operating strategies and network security standards enabled by new technology. By optimally balancing the costs of network constraints with various operational measures composed of preventive and corrective control actions, considering potential outages of network and generation facilities, optimal network capacity that should be released to network users in real time is determined. This framework is compatible with Smart Grid concepts integrating new generation, network, and demand technology. The study demonstrates that any attempt to fix a single generic rule for operating the network, as in the present deterministic standards, will lead to potentially significant inefficiencies. It is also shown that various operational measures (such as generation and demand response) can be effectively used to release additional network capacity. The results suggest that the probabilistic approach provides the basis for the development of future network operation and design standards that would maximize the value of the transmission network to users, enhance the utilization of existing networks, foster the entrance of new technologies that may complement and provide alternative network reinforcement, and hence facilitate efficient integration of renewable generation.