Interdependence of Transmission Branch Parameters on the Voltage Levels

Transformers and transmission lines are critical components of a grid network. This paper analyzes the statistical properties of the electrical parameters of transmission branches and especially examines their interdependence on the voltage levels. Some interesting findings include: (a) with appropriate conversion of MVA rating, a transformer’s per unit reactance exhibits consistent statistical pattern independent of voltage levels and capacity; (b) the distributed reactance (ohms/km) of transmission lines also has some consistent patterns regardless of voltage levels; (c) other parameters such as the branch resistance, the MVA ratings, the transmission line length, etc, manifest strong interdependence on the voltage levels which can be approximated by a power function with different power constants. The results will be useful in both creation of synthetic power grid test cases and validation of existing grid models

Synthetic Modeling of Power Grids Based on Statistical Analysis

The development of new concepts and methods for improving the efficiency of power networks needs performance evaluation with realistic grid topology. However, much of the realistic grid data needed by researchers cannot be shared publicly due to the security and privacy challenges. With this in mind, power researchers studied statistical properties of power grids and introduced synthetic power grid topology as appropriate methodology to provide enough realistic power grid case studies. If the synthetic networks are truly representative and if the concepts or methods test well in this environment they would test well on any instance of such a network as the IEEE model systems or other existing grid models. In the past, power researchers proposed a synthetic grid model, called RT-nested-smallworld, based on the findings from a comprehensive study of the topology properties of a number of realistic grids. This model can be used to produce a sufficiently large number of power grid test cases with scalable network size featuring the same kind of small-world topology and electrical characteristics found in realistic grids. However, in the proposed RT-nested-smallworld model the approaches to address some electrical and topological settings such as (1) bus types assignment, (2) generation and load settings, and (3) transmission line capacity assignments, are not sufficient enough to apply to realistic simulations. In fact, such drawbacks may possibly cause deviation in the grid settings therefore give misleading results in the following evaluation and analysis. To address this challenges, the first part of this thesis proposes a statistical methodology to solve the bus type assignment problem. This method includes a novel measure, called the Bus Type Entropy, the derivation of scaling property, and the optimized search algorithm. The second part of this work includes a comprehensive study on generation/Load settings based on both topology metrics and electrical characteristics. In this section a set of approaches has been developed to generate a statistically correct random set of generation capacities and assign them to the generation buses in a grid. Then we determine the generation dispatch of each generation unit according to its capacity and the dispatch ratio statistics, which we collected and derived from a number of realistic grid test cases. The proposed approaches is readily applied to determining the load settings in a synthetic grid model and to studying the statistics of the flow distribution and to estimating the transmission constraint settings. Considering the results from the first two sections, the third part of this thesis will expand earlier works on the RT-nested-smallworld model and develop a new methodology to appropriately characterize the line capacity assignment and improve the synthetic power grid modeling

Modeling Cascading Failures in Power Systems in the Presence of Uncertain Wind Generation

One of the biggest threats to the power systems as critical infrastructures is large-scale blackouts resulting from cascading failures (CF) in the grid. The ongoing shift in energy portfolio due to ever-increasing penetration of renewable energy sources (RES) may drive the electric grid closer to its operational limits and introduce a large amount of uncertainty coming from their stochastic nature. One worrisome change is the increase in CFs. The CF simulation models in the literature do not allow consideration of RES penetration in studying the grid vulnerability. In this dissertation, we have developed tools and models to evaluate the impact of RE penetration on grid vulnerability to CF. We modeled uncertainty injected from different sources by analyzing actual high-resolution data from North American utilities. Next, we proposed two CF simulation models based on simplified DC power flow and full AC power flow to investigate system behavior under different operating conditions. Simulations show a dramatic improvement in the line flow uncertainty estimation based on the proposed model compared to the simplified DC OPF model. Furthermore, realistic assumptions on the integration of RE resources have been made to enhance our simulation technique. The proposed model is benchmarked against the historical blackout data and widely used models in the literature showing similar statistical patterns of blackout size