Resilience-oriented design and proactive preparedness of electrical distribution system

Extreme weather events, such as hurricanes and ice storms, pose a top threat to power distribution systems as their frequency and severity increase over time. Recent severe power outages caused by extreme weather events, such as Hurricane Harvey and Hurricane Irma, have highlighted the importance and urgency to enhance the resilience of electric power distribution systems. The goal of enhancing the resilience of distribution systems against extreme weather events can be fulfilled through upgrading and operating measures. This work focuses on investigating the impacts of upgrading measures and preventive operational measures on distribution system resilience. The objective of this dissertation is to develop a multi-timescale optimization framework to provide some actionable resilience-enhancing strategies for utility companies to harden/upgrade power distribution systems in the long-term and do proactive preparation management in the short-term. In the long-term resilience-oriented design (ROD) of distribution system, the main challenges are i) modeling the spatio-temporal correlation among ROD decisions and uncertainties, ii) capturing the entire failure-recovery-cost process, and iii) solving the resultant large-scale mixed-integer stochastic problem efficiently. To deal with these challenges, we propose a hybrid stochastic process with a deterministic casual structure to model the spatio-temporal correlations of uncertainties. A new two-stage stochastic mixed-integer linear program (MILP) is formulated to capture the impacts of ROD decisions and uncertainties on system responses to extreme weather events. The objective is to minimize the ROD investment cost in the first stage and the expected costs of loss of load, DG operation, and damage repairs in the second stage. A dual decomposition (DD) algorithm with branch-and-bound is developed to solve the proposed model with binary variables in both stages. Case studies on the IEEE 123-bus test feeder have shown the proposed approach can improve the system resilience at minimum costs. For an upcoming extreme weather event, we develop a pre-event proactive energy management and preparation strategy such that flexible resources can be prepared in advance. In order to explicitly materialize the trade-off between the pre-event resource allocation cost and the damage loss risk associated with an event, the strategy is modeled a two-stage stochastic mixed-integer linear programming (SMILP) and Conditional Value at-Risk (CVaR). The progressive algorithm is used to solve the proposed model and obtain the optimal proactive energy management and preparation strategy. Numerical studies on the modified IEEE 123-bus test feeder show the effectiveness of the proposed approach to improve the system resilience at different risk levels

Optimizing Service Restoration in Distribution Systems with Uncertain Repair Time and Demand

This paper proposes a novel method to co-optimize distribution system operation and repair crew routing for outage restoration after extreme weather events. A two-stage stochastic mixed integer linear program is developed. The first stage is to dispatch the repair crews to the damaged components. The second stage is distribution system restoration using distributed generators, and reconfiguration. We consider demand uncertainty in terms of a truncated normal forecast error distribution, and model the uncertainty of the repair time using a lognormal distribution. A new decomposition approach, combined with the Progressive Hedging algorithm, is developed for solving large-scale outage management problems in an effective and timely manner. The proposed method is validated on modified IEEE 34- and 8500-bus distribution test systems.Comment: Under review in IEEE Transactions on Power System

Optimal Scheduling of Distributed Energy Resources Considering Volt-VAr Controller of PV Smart Inverters

This paper proposes an operational scheduling model of distributed energy resources (DERs) and PV smart inverters with Volt-VAr controller using an accurate AC optimal power flow (ACOPF) in an unbalanced distribution network. A mathematical mixed-integer model of local Volt-VAr droop controller of the distributed mixed-phase PV smart inverters is proposed based on the IEEE 1547-2018 standard and is incorporated in the unbalanced ACOPF, which enables effective utilization of the Volt-VAr controllers to not only alleviate voltage issues locally but also at the feeder level. The proposed model is tested on two actual snapshots of a distribution feeder in Arizona. Also, the proposed operational scheduling method considering the Volt-VAr droop controller of PV smart inverters is compared with a recent work in scheduling of the PV smart inverters. The results illustrate that the PV smart inverters dispatches obtained by the proposed model can be practically implemented by local controller of inverters.Comment: In proceedings of the 11th Bulk Power Systems Dynamics and Control Symposium (IREP 2022), July 25-30, 2022, Banff, Canad

Road Crack Detection Using Deep Convolutional Neural Network and Adaptive Thresholding

Crack is one of the most common road distresses which may pose road safety hazards. Generally, crack detection is performed by either certified inspectors or structural engineers. This task is, however, time-consuming, subjective and labor-intensive. In this paper, we propose a novel road crack detection algorithm based on deep learning and adaptive image segmentation. Firstly, a deep convolutional neural network is trained to determine whether an image contains cracks or not. The images containing cracks are then smoothed using bilateral filtering, which greatly minimizes the number of noisy pixels. Finally, we utilize an adaptive thresholding method to extract the cracks from road surface. The experimental results illustrate that our network can classify images with an accuracy of 99.92%, and the cracks can be successfully extracted from the images using our proposed thresholding algorithm.Comment: 6 pages, 8 figures, 2019 IEEE Intelligent Vehicles Symposiu

Using hierarchical folders and tags for file management

Hierarchical folders have been widely used for managing digital files. A well constructed hierarchical structure can keep files organized. A parent folder can have several subfolders and one subfolder can only reside in one parent folder. Files are stored in folders or subfolders. Files can be found by traversing a given path, going through different levels of folders and subfolders. Folders can be moved, renamed, copied and deleted to serve the needs of the changing working environment. However, previous research has revealed several problems with hierarchical folder structures. One important problem is that users frequently have to turn to desktop search to re-find files. Tagging is the activity of applying users’ own descriptors to digital objects, such as web pages, photos, and documents. Compared with traditional indexing which enforces a controlled vocabulary, tagging systems give users freedom in describing digital resources. We believe that tagging may have the potential to improve information navigation and information organization. This research aimed at exploring the possibility of incorporating tagging into the hierarchical folder structure for file management, especially for the process of file organization and file re-finding.We studied users’ behavior and preference of using three file management structures, a hierarchical folder structure, a tagging structure, and a hybrid structure with both hierarchical folder and tagging functionalities. We found that using tag alone or using folder alone generated similar results in file organization time, in file re-finding time and in answer correctness. Combining folders and tags resulted in longer file organization time but no improvement in file re-finding efficiency. The tagging structure required the least number of mouse clicks in the re-finding process among the three structures. The primary contribution of the study is a comparison of three file management structures for better organizing and re-finding files in the desktop environment. Advantages and disadvantages of each structure were revealed from the study. Users’ preference among the three structures was compared. Both quantitative and qualitative research methods were used in the research. This work will provide design implications for future file management tools.Ph.D., Information Science and Technology -- Drexel University, 201