Ayman Faza

Reliability modeling for the advanced electric power grid

The advanced electric power grid promises a self-healing infrastructure using distributed, coordinated, power electronics control. One promising power electronics device, the Flexible AC Transmission System (FACTS), can modify power flow locally within a grid. Embedded computers within the FACTS devices, along with the links connecting them, form a communication and control network that can dynamically change the power grid to achieve higher dependability. The goal is to reroute power in the event of transmission line failure. Such a system, over a widespread area, is a cyber-physical system. The overall reliability of the grid is a function of the respective reliabilities of its two major subsystems, namely, the FACTS network and the physical components that comprise the infrastructure. This paper presents a mathematical model, based on the Markov chain imbeddable structure, for the overall reliability of the grid. The model utilizes a priori knowledge of reliability estimates for the FACTS devices and the communications links among them to predict the overall reliability of the power grid.

Reliability Analysis for the Advanced Electric Power Grid: From Cyber Control and Communication to Physical Manifestations of Failure

The advanced electric power grid is a cyber-physical system comprised of physical components, such as transmission lines and generators, and a network of embedded systems deployed for their cyber control. The objective of this paper is to qualitatively and quantitatively analyze the reliability of this cyber-physical system. The original contribution of the approach lies in the scope of failures analyzed, which crosses the cyber-physical boundary by investigating physical manifestations of failures in cyber control. As an example of power electronics deployed to enhance and control the operation of the grid, we study Flexible AC Transmission System (FACTS) devices, which are used to alter the flow of power on specific transmission lines. Through prudent fault injection, we enumerate the failure modes of FACTS devices, as triggered by their embedded software, and evaluate their effect on the reliability of the device and the reliability of the power grid on which they are deployed. The IEEE118 bus system is used as our case study, where the physical infrastructure is supplemented with seven FACTS devices to prevent the occurrence of four previously documented potential cascading failures.

The Advanced Electric Power Grid: Complexity Reduction Techniques for Reliability Modeling

The power grid is a large system, and analyzing its reliability is computationally intensive, rendering conventional methods ineffective. This paper proposes techniques for reducing the complexity of representations of the grid, resulting in a mathematically tractable problem to which our previously developed reliability analysis techniques can be applied. The IEEE118 bus system is analyzed as an example, incorporating cascading failure scenarios reported in the literature.

Sensitivity analysis for the IEEE 30 bus system using load-flow studies

Load flow analysis is the backbone of the power system studies and design, and through it the voltage magnitude and phase angle at each bus and the complex power flowing in each transmission line can be obtained. In this paper, we use the load-flow to perform a sensitivity analysis of the IEEE 30 bus system. We find the maximum complex power flowing in each transmission line in case of no fault and in case of a single transmission line fault in the steady state condition. The results of this analysis helps identify the most critical lines in the system, which can help better plan the capacities of such lines, and minimize the probability of potential cascading failures.

Reliability Modeling for the Advanced Electric Power Grid: A Proposal for Doctoral Research

The advanced electric power grid is a cyber-physical system comprised of physical components such as power generators and transmission lines, and cyber components that control the operation of the grid. The objective of the proposed doctoral research is to develop a reliability model for the grid that reflects interdependencies among cyber and physical failures, through capturing the semantics of the system operation. We investigate several failure modes for devices that carry out cyber control of the grid, and examine the effect of their failure in terms of physical power flow in the grid. We propose the use of fault injection into the software of the cyber layer to refine the model, as well as the development of statistical methods to determine confidence levels for our model.

A probabilistic model for estimating the effects of photovoltaic sources on the power systems reliability

Abstract As the power grid is continuously expanding, the increased amount of loading and the corresponding amount of generation is causing the grid to become more and more complex. The addition of intelligent devices for control and communications is also making the grid more vulnerable to failures. The addition of distributed renewable energy sources can potentially alleviate some of the stress on the grid, and help improve its reliability; however, their effects on the grid are not yet fully understood. In this paper, we study the effects of adding photovoltaic (PV) sources to the grid from a reliability perspective. We use monte carlo simulation to assess the reliability of the system in the presence of transmission line contingencies and potential cascading failures, and we use the particle swarm optimization to find the optimal placement of PV sources in the network that would maximize the system reliability. Our results show that while adding PV sources to the network can, under certain conditions, improve the system reliability, increasing the amount of PV indefinitely does not necessarily continue to improve it. There is a certain optimal amount of PV power that would improve the system reliability, and any further increase can have negative effects.

A smart street lighting system using solar energy

This paper demonstrates a prototype for a smart street-lighting system, in which a number of DC street lights are powered by a photovoltaic (PV) source. A battery is added to store the excess energy of the solar panel, which can later be retrieved at night time, or whenever the sunlight is being obstructed by clouds or other forms of shading. A charge controller is used to protect the battery from overcharging and to control the overall system operation. Furthermore, the system is expanded to include a motion sensing circuit, and a dust-cleaning circuit. The overall result is a smart and efficient street lighting system, which can be implemented as a standalone off-grid system, or connected to the rest of the grid as part of a bigger system.

Performance of three islanding detection methods for grid-tied multi-inverters

Islanding occurs when distributed resources continue to power even though electrical power from the utility grid is no longer present. Islanding can be harmful for utility workers, who may not realize that this part is still powered. For the reason of safety hazards and equipment damage due to lack of utility control on voltage and frequency in the island, distributed resources must detect an island and immediately stop producing power. In this paper, we study the operation of multiple inverters utilizing different active islanding detection methods. The Sandia Voltage Shift (SVS), the Sandia Frequency Shift (SFS) and the Slip Mode frequency Shift (SMS) are used in this work. The study reported is based on MATLAB/Simulink time-domain simulations, taking into account modern international standards. It is shown that a multi-inverter system, which uses three different methods, can detect an island in case of power-matched load. However, it has a reduced performance and slower detection time, compared to single inverter structure.

Analysis of the effects of distributed generation sources on power grid reliability

Distributed Generation (DG) sources such as solar and wind power sources are gaining an increased popularity due to the various advantages they provide over the traditional fossil-fuel-based power generation sources. However, their effects on the system operation, while expected to be positive, are not yet fully understood. In this paper, we study the effect of adding DG sources to the grid on the overall system reliability. We simulate the effect of gradually injecting limited amount of real power at the load buses of the IEEE 14 bus system, and combine that with a single-transmission line contingency to study the effect of the DG sources on improving the operation of the grid in terms of reducing the stress on the transmission network, and reducing the total number of and the amount of overloads that could possibly occur in the transmission lines, due to the line contingencies. Our results show a general improvement in the operation of the power grid, due to the addition of the DG sources, but also shows that the amount of injected power has to be limited to generally small values, and in some cases should be planned in a way that keeps in mind the capacities of the lines in the transmission network.

Infrared and Intertial Tracking in the Immersive Audio Environment for Enhanced Military Training

The Immersive Audio Environment (IAE) was designed to provide an effective military training facility. Its efficacy at synthesizing sounds from desired directions and also the ability to synthesize moving sounds has been previously reported. This paper discusses the addition of a tracking system to evaluate subject training performance. Numerous tracking systems have been developed for tracking in immersive environments. Some examples include using head mounted web cams, visible light cameras mounted on the support structure, or even single camera tracking as in commercially available entertainment. Our system uses a combination of an existing infrared tracking system and a specially designed system of inertial tracking. This paper presents tests and results to evaluate the accuracy of the tracking system with respect to our application and verifies the efficacy of using the IAE for training enhancement.