Ross T. Guttromson

Pacific Northwest GridWise™ Testbed Demonstration Projects; Part I. Olympic Peninsula Project

This report describes the implementation and results of a field demonstration wherein residential electric water heaters and thermostats, commercial building space conditioning, municipal water pump loads, and several distributed generators were coordinated to manage constrained feeder electrical distribution through the two-way communication of load status and electric price signals. The field demonstration took place in Washington and Oregon and was paid for by the U.S. Department of Energy and several northwest utilities. Price is found to be an effective control signal for managing transmission or distribution congestion. Real-time signals at 5-minute intervals are shown to shift controlled load in time. The behaviors of customers and their responses under fixed, time-of-use, and real-time price contracts are compared. Peak loads are effectively reduced on the experimental feeder. A novel application of portfolio theory is applied to the selection of an optimal mix of customer contract types.

Robust RLS Methods for Online Estimation of Power System Electromechanical Modes

This paper proposes a robust recursive least square (RRLS) algorithm for online identification of power system modes based on measurement data. The measurement data can be either ambient or ringdown. Also, the mode estimation is provided in real-time. The validity of the proposed RRLS algorithm is demonstrated with both simulation data from a 17-machine model and field measurement data from a wide area measurement system (WAMS). Comparison with the conventional recursive least square (RLS) and least mean square (LMS) algorithms shows that the proposed RRLS algorithm can identify the modes from the combined ringdown and ambient signals with outliers and missing data in real-time without noticeable performance degradation. An adaptive detrend algorithm is also proposed to remove the signal trend based on the RRLS algorithm. It is shown that the algorithm can keep up with the measurement data flow and work online to provide real-time mode estimation.

Residential energy resource models for distribution feeder simulation

Advances in information technology, ubiquitous communications, and distributed generation and storage reveal new opportunities for the participation of demand-side resources in balancing the physical and economic operation of electric power systems. To better understand the potential impact of this participation, accurate, detailed energy resource models are necessary at the distribution feeder level. This presentation describes a detailed approach to residential energy resource modeling that preserves the individual characteristics of major residential appliances and human behavior patterns so that their contribution to energy efficiency schemes and intelligent demand curtailment algorithms is properly portrayed. These models are derived from previous analyses of residential and commercial building systems supported by data collected from the end-use load and consumer assessment program (ELCAP) undertaken by the Bonneville power administration from 1983 to 1990. Preliminary results of using these models in distribution system simulations indicate that non-obvious, complex behavior patterns can emerge when consumers are confronted with varying price signals.

Simulating the dynamic coupling of market and physical system operations

As energy trading products cover shorter time periods and demand response programs move toward real-time pricing, financial market-based activity impacts ever more directly the physical operation of the system. To begin to understand the complex interactions between the market-driven operation signals, the engineered controlled schemes, and the laws of physics, new system modeling and simulation techniques must be explored. This discussion describes requirements for interactions and an approach to capture the dynamic coupling between energy markets and the physical operation of the power system appropriate for dispatcher reaction time frames.

Modeling distributed energy resource dynamics on the transmission system

As distributed energy resource (DER) projects grow in popularity, there has been little focus on their potential to influence the dynamic stability of a transmission system. If implemented in large enough numbers, DER equipment may feasibly be leveraged to provide ancillary services such as spinning reserve, system inertia, or system stabilization. To determine the potential impacts of DER on future transmission grid stability, dynamic models of DER load combinations were created, reduced in order, and scattered throughout central and southem Califomia within an existing Western Systems Coordinating Council (WSCC) dynamic model. Evaluation of the composite WSCC-DER dynamic model allows correlations to be drawn between various DER properties and the transmission grid stability. Key findings show that increasing DER inertia tends to destabilize the transmission system. The cause of this counterintuitive relationship requires further study but likely is related to the high impedance separating the DER from the transmission grid.

A Novel Visualization Technique for Electric Power Grid Analytics

The application of information visualization holds tremendous promise for the electric power industry, but its potential has so far not been sufficiently exploited by the visualization community. Prior work on visualizing electric power systems has been limited to depicting raw or processed information on top of a geographic layout. Little effort has been devoted to visualizing the physics of the power grids, which ultimately determines the condition and stability of the electricity infrastructure. Based on this assessment, we developed a novel visualization system prototype, GreenGrid, to explore the planning and monitoring of the North American Electricity Infrastructure. The paper discusses the rationale underlying the GreenGrid design, describes its implementation and performance details, and assesses its strengths and weaknesses against the current geographic-based power grid visualization. We also present a case study using GreenGrid to analyze the information collected moments before the last major electric blackout in the Western United States and Canada, and a usability study to evaluate the practical significance of our design in simulated real-life situations. Our result indicates that many of the disturbance characteristics can be readily identified with the proper form of visualization.

Large-scale hybrid dynamic simulation employing field measurements

Simulation and measurements are two primary ways for power engineers to gain understanding of system behaviors and thus accomplish tasks in system planning and operation. Many well-developed simulation tools are available in todays market. On the other hand, large amount of measured data can be obtained from traditional SCADA systems and currently fast growing phasor networks. However, simulation and measurement are still two separate worlds. There is a need to combine the advantages of simulation and measurements. In view of this, This work proposes the concept of hybrid dynamic simulation which opens up traditional simulation by providing entries for measurements. A method is presented to implement hybrid simulation with PSLF/PSDS. Test studies show the validity of the proposed hybrid simulation method. Applications of such hybrid simulation include system event playback, model validation, and software validation.

Towards efficient power system state estimators on shared memory computers

We are investigating the effectiveness of parallel weighted- least-square (WLS) state estimation solvers on shared-memory parallel computers. Shared-memory parallel architectures are rapidly becoming ubiquitous due to the advent of multi-core processors. In the current evaluation, we are using an LU-based solver as well as a conjugate gradient (CG)-based solver for a 1177-bus system. In lieu of a very wide multi-core system we evaluate the effectiveness of the solvers on an SGI Altix system on up to 32 processors. On this platform, as expected, the shared memory implementation (pthreads) of the LU solver was found to be more efficient than the MPI version. Our implementation of the CG solver scales and performs significantly better than the state-of-the-art implementation of the LU solver: with CG we can solve the problem 4.75 times faster than using LU. These findings indicate that CG algorithms should be quite effective on multicore processors

Integration of wind generation and load forecast uncertainties into power grid operations

In this paper, a new approach to evaluate the uncertainty ranges for the required generation performance envelope, including the balancing capacity, ramping capability and ramp duration is presented. The approach includes three stages: statistical and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence intervals. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis incorporating all sources of uncertainty and parameters of a continuous (wind forecast and load forecast errors) and discrete (forced generator outages and failures to start up) nature. Preliminary simulation using California Independent System Operator (CAISO) real life data has shown the effectiveness and efficiency of the proposed approach.

A sensemaking perspective on situation awareness in power grid operations

With increasing complexity and interconnectivity of the electric power grid, the scope and complexity of grid operations continues to grow. New paradigms are needed to guide research to improve operations by enhancing situation awareness of operators. Research on human factors/situation awareness is described within a taxonomy of tools and approaches that address different levels of cognitive processing. While user interface features and visualization approaches represent the predominant focus of human factors studies of situation awareness, this paper argues that a complementary level, sensemaking, deserves further consideration by designers of decision support systems for power grid operations. A sensemaking perspective on situation awareness may reveal new insights that complement ongoing human factors research, where the focus of the investigation of errors is to understand why the decision makers experienced the situation the way they did, or why what they saw made sense to them at the time.