Application of Advanced Early Warning Systems with Adaptive Protection

This project developed and field-tested two methods of Adaptive Protection systems utilizing synchrophasor data. One method detects conditions of system stress that can lead to unintended relay operation, and initiates a supervisory signal to modify relay response in real time to avoid false trips. The second method detects the possibility of false trips of impedance relays as stable system swings “encroach” on the relays’ impedance zones, and produces an early warning so that relay engineers can re-evaluate relay settings. In addition, real-time synchrophasor data produced by this project was used to develop advanced visualization techniques for display of synchrophasor data to utility operators and engineers

Power and energy visualization for the micro-management of household electricity consumption

The paper describes a pilot system for the detailed management of domestic electricity consumption aimed at minimizing demand peaks and consumer cost. Management decisions are made both interactively by consumers themselves, and where practical, automatically by computer. These decisions are based on realtime pricing and availability information, as well as current and historic usage data. The benefits of the energy strategies implied by such a system are elaborated, showing the potential for significant peak demand reduction and slowing of the need for growth in generation capacity. An overview is provided of the component technologies and interaction methods we have designed, but the paper focuses on the communication of real-time information to the consumer through a combination of specific and ambient visualizations. There is a need for both overview information (eg how much power is being used right now; how much energy have we used so far today; what does it cost?) and information at the point-of-use (is it OK to turn this dryer on now, or should I wait until later?). To assist the design of these visualizations, a survey is underway aimed at establishing people's understanding of power and energy concepts

Demonstration of visualization techniques for the control room engineer in 2030.:ELECTRA Deliverable D8.1. WP8: Future Control Room Functionality

Deliverable 8.1 reports results on analytics and visualizations of real time flexibility in support of voltage and frequency control in 2030+ power system. The investigation is carried out by means of relevant control room scenarios in order to derive the appropriate analytics needed for each specific network event

An Assessment of PIER Electric Grid Research 2003-2014 White Paper

This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014

Computer simulation and visualization in medicine

LectureThe goals of medical simulation and visualization are multifaceted. While some simulations and visualizations facilitate diagnosis, others help physicians plan surgery, therapy, and other forms of treatment. Still other simulation and visualization techniques are used for medical training and to acquire a better understanding of human physiology. Among the most exciting and pressing problems facing computer scientists today are those involving the use of computers in medical applications. With the help of computers, the medical community now verges on important breakthroughs in diagnosing, controlling, treating, and even curing numerous life-threatening conditions, including heart disease and a variety of cancers

The application of computational modeling to data visualization

Researchers have argued that perceptual issues are important in determining what makes an effective visualization, but generally only provide descriptive guidelines for transforming perceptual theory into practical designs. In order to bridge the gap between theory and practice in a more rigorous way, a computational model of the primary visual cortex is used to explore the perception of data visualizations. A method is presented for automatically evaluating and optimizing data visualizations for an analytical task using a computational model of human vision. The method relies on a neural network simulation of early perceptual processing in the retina and visual cortex. The neural activity resulting from viewing an information visualization is simulated and evaluated to produce metrics of visualization effectiveness for analytical tasks. Visualization optimization is achieved by applying these effectiveness metrics as the utility function in a hill-climbing algorithm. This method is applied to the evaluation and optimization of two visualization types: 2D flow visualizations and node-link graph visualizations. The computational perceptual model is applied to various visual representations of flow fields evaluated using the advection task of Laidlaw et al. The predictive power of the model is examined by comparing its performance to that of human subjects on the advection task using four flow visualization types. The results show the same overall pattern for humans and the model. In both cases, the best performance was obtained from visualizations containing aligned visual edges. Flow visualization optimization is done using both streaklet-based and pixel-based visualization parameterizations. An emergent property of the streaklet-based optimization is head-to-tail streaklet alignment, the pixel-based parameterization results in a LIC-like result. The model is also applied to node-link graph diagram visualizations for a node connectivity task using two-layer node-link diagrams. The model evaluation of node-link graph visualizations correlates with human performance, in terms of both accuracy and response time. Node-link graph visualizations are optimized using the perceptual model. The optimized node-link diagrams exhibit the aesthetic properties associated with good node-link diagram design, such as straight edges, minimal edge crossings, and maximal crossing angles, and yields empirically better performance on the node connectivity task