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 10,000 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 10,000 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.
To enable greater innovation in power systems, our research seeks to create entirely fictitious synthetic power system networks that capture the functionality, topology, and defining characteristics of the actual U.S. transmission system, and thus provide realistic test cases for research, without revealing any sensitive information. Creation of these models relies only on publicly available data and statistics derived from the actual grid. This paper outlines two fundamental steps for the creation of synthetic power system models: geographic load and generator substation placement and assignment of transmission line electrical parameters.
Geomagnetically induced currents (GICs) are a result of the changing magnetic fields during a geomagnetic disturbance interacting with the deep conductivity structures of the Earth. When assessing GIC hazard, it is a common practice to use layer‐cake or one‐dimensional conductivity models to approximate deep Earth conductivity. In this paper, we calculate the electric field and estimate GICs induced in the long lines of a realistic system model of the Pacific Northwest, using the traditional 1‐D models, as well as 3‐D models represented by Earthscope's Electromagnetic transfer functions. The results show that the peak electric field during a given event has considerable variation across the analysis region in the Pacific Northwest, but the 1‐D physiographic approximations may accurately represent the average response of an area, although corrections are needed. Rotations caused by real deep Earth conductivity structures greatly affect the direction of the induced electric field. This effect may be just as, or more, important than peak intensity when estimating GICs induced in long bulk power system lines.
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.
Due to information confidentiality issues, there is limited access to actual power system models that represent features of actual power grids for teaching, training, and research purposes. The authors' previous work describes the process of creating synthetic transmission networks, with statistics similar to those of actual power grids. Thus, this paper outlines a systematic methodology to augment the synthetic network base case for energy economic studies. The key step is to determine generator cost models by fuel type and capacity. Based on statistics summarized from the actual grids, two approaches are proposed to assign coefficients to generator cost models. To illustrate the proposed creation procedure, we describe the construction of a synthetic model for Electric Reliability Council of Texas footprint. Simulation results are presented to verify that the created test system is able to represent the behavior of actual power systems.
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