Abstract
Public power system test cases that are of high quality benefit the power systems research community with expanded resources for testing, demonstrating, and cross-validating new innovations. Building synthetic grid models for this purpose is a relatively new problem, for which a challenge is to show that created cases are sufficiently realistic. This paper puts forth a validation process based on a set of metrics observed from actual power system cases. These metrics follow the structure, proportions, and parameters of key power system elements, which can be used in assessing and validating the quality of synthetic power grids. Though wide diversity exists in the characteristics of power systems, the paper focuses on an initial set of common quantitative metrics to capture the distribution of typical values from real power systems. The process is applied to two new public test cases, which are shown to meet the criteria specified in the metrics of this paper.
Highlights
Synthetic power grids are test cases that are not based on any real power system
Work characteristics found on actual grids that can be used to evaluate the realism of a synthetic power
While there is wide variety among actual grids, this paper sampled fourteen systems of various that do not compromise the confidentiality of the infrastructure
Summary
Synthetic power grids are test cases that are not based on any real power system. The motivation for building such cases it that real grids are subject to data confidentiality restrictions, and usually real power system cases cannot be shared publicly. Energies 2017, 10, 1233 high degree of clustering, exponential degree distribution, and average nodal degree around 2.3–2.8 are documented as typical of power grid graphs These topological metrics have been applied in studies [8,9,10,11,12] to synthetic power grids, both as pieces of a network generation algorithm and as validation criteria for networks considered. The size of a network can affect its statistical properties, since large networks have averaging effects Each of these issues is addressed in this paper by studying a high-quality, diverse, large set of North American power system models. The initial suite of validation metrics defined here contributes a benchmark for developed cases
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
