Reactive optimization of transmission and distribution networks

Some of the challenges associated with the multi-objective optimization on a modern power system were addressed in this work. Optimization of reactive resources was performed in order to simultaneously optimize several criteria: transmission losses, distribution losses, voltage stability, etc. The optimization was performed simultaneously on the entire power system; transmission and distribution subsystems included. The inherent physical complexity of modeling together transmission and distribution systems was considered first. After considering all pros and cons for such a task, a model of the entire power system was successfully developed. The inherent mathematical complexity of high-dimensional optimization space was handled by introducing the decoupling principle. System is first decoupled in several independent models and optimizations were performed on each part of the system. An algorithm is developed that properly combines the independent solutions to reach the overall system optima. The principle of algorithm synthesis is used to reduce the size of the solution space. Deterministic algorithms are used to locate the local optima which are subsequently refined by probabilistic algorithm. The algorithm is applied on a "real-life" test system and it is shown that the obtained solutions outperform the solution obtained with the conventional algorithms.Ph.D.Committee Chair: Begovic, Miroslav; Committee Member: Divan, Deepakraj; Committee Member: Dorsey, John; Committee Member: Ferri, Bonnie; Committee Member: Lambert, Fran

Optimization Techniques for the Developing Distribution System

The most rapidly changing part of today’s power grid is the distribution system. Many new technologies have emerged that revolutionize the way utilities provide, and now sometimes receive, power to and from their customers. To an extent, the push for de-regulation of utilities has also led to an increased focus on reliability and efficiency. These changes make design and operation of power systems more complex causing utilities to question if they are operating optimally. Operations Research (OR) is an area of mathematics where quantitative analysis is used to provide a basis for complex decision making. The changing landscape in electric distribution makes it a prime candidate for the application of OR techniques. This research seeks to develop optimization methods that can be applied to any distribution feeder or group of feeders that allows for optimal decisions to be made in a reasonable time frame. Two specific applications identified in this thesis are optimal reconfiguration during outage situations and optimal location of Battery Energy Storage Systems (BESS). Response to outages has traditionally relied on human-in-the-loop approaches where a dispatcher or a crew working the field decides what switching operations are needed to isolate affected parts of the system and restore power to healthy ones. This approach is time consuming and under-utilizes the benefits provided by widely-adopted, remotely-controlled switching technologies. Chapters Two and Three of this thesis develop a partitioning method for determining the switching operations required to optimize the amount of load that is restored during an event. Most people would agree that renewable forms of Distributed Generation (DG) provide great benefits to the power industry, especially through reduced impact on the environment. The variable nature of renewables, however, can cause many issues for operation and control of a utilities’ system, especially for distribution interconnections. Storage technologies are thought to be the primary solution to these issues with much research focused on sizing and control of BESSs. Equally important for integration, but often overlooked, is the location at which the device is connected. Chapter Four explores this idea by drawing conclusions about optimal BESS location based on well-studied ideas of optimal capacitor location

A framework for network traffic analysis using GPUs

During the last years the computer networks have become an important part of our society. Networks have kept growing in size and complexity, making more complex its management and traffic monitoring and analysis processes, due to the huge amount of data and calculations involved. In the last decade, several researchers found effective to use graphics processing units (GPUs) rather than a traditional processors (CPU) to boost the execution of some algorithms not related to graphics (GPGPU). In 2006 the GPU chip manufacturer NVIDIA launched CUDA, a library that allows software developers to use their GPUs to perform general purpose algorithm calculations, using the C programming language. This thesis presents a framework which tries to simplify the task of programming network traffic analysis with CUDA to software developers. The objectives of the framework have been abstracting the task of obtaining network packets, simplify the task of creating network analysis programs using CUDA and offering an easy way to reuse the analysis code. Several network traffic analysis have also been developed