Heuristic Optimization for Automated Distribution System Planning in Network Integration Studies
This work addresses the need for automated planning tools for distribution system operators to assess impacts of future developments like renewable energy integration, though it appears incremental as it builds on existing optimization methods.
The study tackled the problem of automated distribution system planning for network integration studies by developing a heuristic optimization approach that calculates network reconfiguration, reinforcement, and extension plans automatically, enabling cost estimation in large-scale probabilistic simulations of real networks.
Network integration studies try to assess the impact of future developments, such as the increase of Renewable Energy Sources or the introduction of Smart Grid Technologies, on large-scale network areas. Goals can be to support strategic alignment in the regulatory framework or to adapt the network planning principles of Distribution System Operators. This study outlines an approach for the automated distribution system planning that can calculate network reconfiguration, reinforcement and extension plans in a fully automated fashion. This allows the estimation of the expected cost in massive probabilistic simulations of large numbers of real networks and constitutes a core component of a framework for large-scale network integration studies. Exemplary case study results are presented that were performed in cooperation with different major distribution system operators. The case studies cover the estimation of expected network reinforcement costs, technical and economical assessment of smart grid technologies and structural network optimisation.