A Critical Review of Methods and Validation Techniques for Developing Synthetic Network Models

Synthetic power networks are developed to study the impacts and benefits of new energy technologies in a location-specific electrical network. While the network topologies, models, assets, and loading information are proprietary and, in many cases, are not publicly available, synthetic networks are developed using open-source data. A synthetic network represents a location-specific transmission or distribution network (DN), with similar topological characteristics to real networks. In the pursuit of developing a synthetic network for grid integration and network flexibility studies, this paper presents a comprehensive review of existing methodologies for synthetic DN developments along with the input data requirements and software platforms. This paper also provides a thorough appraisal of various validation approaches for developed synthetic networks and their demonstration in power system studies. This study aims to identify (i) the input data and software requirements for synthetic network development and (ii) the most accurate and efficient approaches for modeling and validation of existing synthetic DNs to be used for grid integration studies. This paper identified the GIS data-based followed by data-driven approaches as the most widely used methods in developing a synthetic DN. Furthermore, operational validation has been commonly utilized to measure the accuracy of the developed synthetic DNs.