Heuristic Optimization for Automated Distribution System Planning in Network Integration Studies

TL;DR

This paper presents an automated heuristic optimization approach for distribution system planning, enabling large-scale probabilistic network integration studies with cost estimation, smart grid assessment, and network optimization.

Contribution

It introduces a fully automated method for network reconfiguration, reinforcement, and extension planning, supporting large-scale probabilistic simulations in network integration studies.

Findings

Effective cost estimation for network reinforcement

Assessment of smart grid technologies

Structural network optimization results

Abstract

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.