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

On the Scaling Property of Power Grids

Compared with other natural or man-made networks, electric power grid assumes distinct electric topology with special small-world properties and electrical parameter settings. In this paper we study the scaling property of power grid in terms of both topology measures and electric parameters, with a number of realistic power grid test cases of different size. The examined measures and parameters include average node degree, average path length, algebraic connectivity, the bus type entropy that characterize relative locations of generation and load buses, generation capacity, total demand, and transmission capacity. Interpreting and testing the scaling property of power grid will help us better understand the intrinsic characteristics of electric energy delivery network of this critical infrastructure; and enable the development of an appropriate synthetic modeling that could be utilized to generate power grid test cases with accurate grid topology and electric parameters

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

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

Improving Grid Hosting Capacity and Inertia Response with High Penetration of Renewable Generation

To achieve a more sustainable supply of electricity, utilizing renewable energy resources is a promising solution. However, the inclusion of intermittent renewable energy resources in electric power systems, if not appropriately managed and controlled, will raise a new set of technical challenges in both voltage and frequency control and jeopardizes the reliability and stability of the power system, as one of the most critical infrastructures in the today’s world. This dissertation aims to answer how to achieve high penetration of renewable generations in the entire power system without jeopardizing its security and reliability. First, we tackle the data insufficiency in testing new methods and concepts in renewable generation integration and develop a toolkit to generate any number of synthetic power grids feathering the same properties of real power grids. Next, we focus on small-scale PV systems as the most growing renewable generation in distribution networks and develop a detailed impact assessment framework to examine its impacts on the system and provide installation scheme recommendations to improve the hosting capacity of PV systems in the distribution networks. Following, we examine smart homes with rooftop PV systems and propose a new demand side management algorithm to make the best use of distributed renewable energy. Finally, the findings in the aforementioned three parts have been incorporated to solve the challenge of inertia response and hosting capacity of renewables in transmission network

The Creation, Validation, and Application of Synthetic Power Grids

Public test cases representing large electric power systems at a high level of fidelity and quality are few to non-existent, despite the potential value such cases would have to the power systems research community. Legitimate concern for the security of large, high-voltage power grids has led to tight restrictions on accessing actual critical infrastructure data. 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. The creation approach presented here is a four-stage process which mimics actual power system planning. First, substations are geo-located and internally configured from seed public data on generators and population. The substation placement uses a modified hierarchical clustering to match a realistic distribution of load and generation substations, and the same technique is also used to assign nominal voltage levels to the substations. With buses and transformers built, the next stage constructs a network of transmission lines at each nominal voltage level to connect the synthetic substations with a transmission grid. The transmission planning stage uses a heuristic inspired by simulated annealing to balance the objectives associated with both geographic constraints and contingency reliability, using a linearized dc power flow sensitivity. In order to scale these systems to tens of thousands of buses, robust reactive power planning is needed as a third stage, accounting for power flow convergence issues. The iterative algorithm presented here 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. Validation of the created synthetic grids is crucial to establishing their legitimacy for engineering research. The statistical analysis presented in this dissertation is based on actual grid data obtained from the three major North American interconnects. Metrics are defined and examined for system proportions and structure, element parameters, and complex network graph theory properties. Several example synthetic grids are shown as examples in this dissertation, up to 100,000 buses. These datasets are available online. The final part of this dissertation discusses these specific grid examples and extensions associated with synthetic grids, in applying them to geomagnetic disturbances, visualization, and engineering education