To encourage and support innovation, synthetic electric grids are fictional, designed systems that mimic the complexity of actual electric grids but contain no confidential information. Synthetic grid design is driven by the requirement to match wide variety of metrics derived from statistics of actual grids. In order to scale these systems to ten thousand buses or more, robust reactive power planning is needed, accounting for power flow convergence issues. This paper addresses reactive power planning and power flow convergence in the context of large synthetic power grids. The iterative algorithm presented by this paper supplements a synthetic transmission network that has been validated by a dc power flow with a realistic set of voltage control devices to meet a specified voltage profile, even with the constraints of difficult power flow convergence for large systems. The algorithm is illustrated with an example new synthetic ten thousand bus system, geographically situated in the western United States, which is publicly available and useful for a variety of research studies. An analysis is shown validating the synthetic system with actual grid characteristics.

Studies to evaluate the power system impacts of geomagnetic disturbances (GMDs) can benefit from geographically realistic public test cases to validate methodologies and analysis tools. Presently very few GMD test cases exist that are not restricted by data confidentiality. In this paper, we outline a method to generate completely synthetic transmission system networks suitable for GMD studies. Public energy and census data form the basis for generation, load, and geographic substation placement. The transmission line topology of the synthetic network is designed to match statistical characteristics observed on the Eastern Interconnect in North America: average nodal degree, average shortest path length, and average clustering coefficient. We apply the Delaunay triangulation to transmission network synthesis, showing it provides an excellent starting place for generating realistic topologies. A 150-bus case is developed and released with benchmark GMD results, for using in testing GMD models and methods.

A synthetic network modeling methodology has been developed to generate completely fictitious power system models with capability to represent characteristic features of actual power grids. Without revealing any confidential information, synthetic network models can be shared freely for teaching, training, and research purposes. Additional complexities can be added into synthetic models to widen their applications. Thus, this paper aims to extend synthetic network base cases for transient stability studies. An automated algorithm is proposed to assign appropriate models and parameters to each synthetic generator, according to fuel type, generation capacity, and statistics summarized from actual system cases. A two-stage model tuning procedure is also proposed to improve synthetic dynamic models. Several transient stability metrics are developed to validate the created synthetic network dynamic cases. The construction and validation of dynamics for a 2000-bus synthetic test case is provided as an example. Simulation results are presented to verify that the created test case is able to satisfy the transient stability metrics and produce dynamic responses similar to those of actual system cases.

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.

This paper introduces a methodology for building synthetic electric grid data sets that represent fictitious, yet realistic, combined transmission and distribution (T&D) systems. Such data sets have important applications, such as in the study of the wide-area interactions of distributed energy resources, in the validation of advanced control schemes, and in network resilience to severe events. The data sets created here are geographically located on an actual North American footprint, with the end-user load information estimated from land parcel data. The grid created to serve these fictional but realistic loads is built starting with low-voltage and medium-voltage distribution systems in full detail, connected to distribution and transmission substations. Bulk generation is added, and a high-voltage transmission grid is created. This paper explains the overall process and challenges addressed in making the combined case. An example test case, syn-austin-TDgrid-v03, is shown for a 307,236-customer case located in central Texas, with 140 substations, 448 feeders, and electric line data at voltages ranging from 120 V to 230 kV. Such new combined test cases help to promote high quality in the research on large-scale systems, particularly since much actual power system data are subject to data confidentiality. The highly detailed, combined T&D data set can also facilitate the modeling and analysis of coupled infrastructures.

This paper describes the use of large electric grids in university electric power systems courses. Since much actual power system information is not publicly available, the application of public domain synthetic grids developed by the authors is presented including a 2000-bus grid. Discussion of the educational applications utilized in a senior level class are given for power flow analysis and sensitivity, economic dispatch, contingency analysis, optimal power flow (OPF), security-constrained OPF, transient stability, and real-time dynamic operations. In each of these, the application of the large synthetic grids give students insights and experience with cases closer to actual power systems in complexity and size.