Impacts of Electric Vehicle Charging on Electric Power Distribution Systems

Electric Avenue, located on the PSU campus along SW Montgomery Street, is a joint project between Portland General Electric, Portland State University (PSU) and the City of Portland. Launched in August 2011, Electric Avenue is intended as a research platform for understanding the impact electric vehicles have within the larger context of the city. For this research, we used Electric Avenue to investigate the impacts electric vehicles (EVs) may have on electric power distribution systems. Nonlinear loads, such as EV chargers, will often introduce power quality (PQ) issues within distribution circuits, which can have detrimental effects on system components. PQ encompasses several specific concepts such as harmonic distortion, DC offset, phase imbalance, and voltage deviations, among others, and these are quantified in myriad ways. For this study, we focus on harmonic currents since these have the potential to affect the lifetime of magnetic assets such as distribution transformers and instrument transformers. Utilities plan asset management by anticipating the nature of loads and selecting assets designed to handle those loads. A deeper understanding of these matters specific to EVs will aid utilities in the design of distribution systems and provide guidance for asset planning. A load\u27s PQ affects magnetic assets because of the potential for insulation failure and core saturation. Understanding the PQ of nonlinear loads assists distribution engineers with the selection of k-factor ratings for distribution transformers, selection of CTs and VTs, protection settings and decisions regarding conductor ampacity. For this study, we measured the PQ of EV chargers, paying specific attention to total harmonic distortion (THD) of individual EV chargers and total demand distortion (TDD) of the Electric Avenue service. We also noted phase imbalance, phantom loading and other PQ issues observed during the course of our study. Our objective is to expand the electric utility industry’s understanding that EVs have on these issues

Product Specification: Distributed Control Module (DOE-PSU-0000922-5)

This product specification describes the architecture, implementation, and hardware descriptions of a Distributed Control Module (DCM) prototype. A DCM is an enabling technology for distributed energy resources (DER). DERs are grid-enabled generation, storage, and load devices that are owned by utility customers. DCMs enable information exchange between a distributed energy resource management system (DERMS) and DERs for the purpose of networking large numbers of DERs. The DCM prototype described within this document enables DER participation in a service-oriented aggregation system. A DERMS server provides IEEE 2030.5 smart energy resource services to DCM clients using a request/response information exchange process. DCMs serve as gateways between the DERMS and the DERs, and they act as agents on behalf of the DER owners to provide intelligent management of the DERs

Implementation Profile: Modeling Environment (DOE-PSU-0000922-3)

This implementation profile provides the scope, background, and requirements necessary to implement a Modeling Environment (ME) to test a Distributed Energy Resource (DER) Management System (DERMS). A DERMS is used by an aggregator to dispatch large numbers of DERs in order to provide grid services to a Grid Operator. The ME addresses scalability issues inherent to Hardware-in-the-Loop DERMS simulation; a large number of assets are needed in order to observe effects on the grid from deployment and dispatch of DERs

Resource Study of Large-Scale Electric Water Heater Aggregation

Residential-scale distributed energy assets, like residential electric water heaters, individually present a negligible load to the power grid. When aggregated, however, these assets can impart significant effects within a balancing area; they may be dispatched en masse to provide grid services. An aggregation of water heaters may be controlled to assume generator-like functions with the ability to effectively “decrement power” through dispatch of load. This resource study examines the capabilities of a 10,000 unit water heater aggregation by subjecting the aggregate to dispatch requests of various size and duration, then analyzing how the aggregate responds to and recovers from these requests. Results show that a large-scale aggregation of electric water heaters may effectively decrement power on the scale of megawatts when the dispatch request size and duration are appropriately considered

Fast Sequence Component Analysis for Attack Detection in Synchrophasor Networks

Modern power systems have begun integrating synchrophasor technologies into part of daily operations. Given the amount of solutions offered and the maturity rate of application development it is not a matter of "if" but a matter of "when" in regards to these technologies becoming ubiquitous in control centers around the world. While the benefits are numerous, the functionality of operator-level applications can easily be nullified by injection of deceptive data signals disguised as genuine measurements. Such deceptive action is a common precursor to nefarious, often malicious activity. A correlation coefficient characterization and machine learning methodology are proposed to detect and identify injection of spoofed data signals. The proposed method utilizes statistical relationships intrinsic to power system parameters, which are quantified and presented. Several spoofing schemes have been developed to qualitatively and quantitatively demonstrate detection capabilities.Comment: 8 pages, 4 figures, submitted to IEEE Transaction

Detecting Fast Frequency Events in Power System: Development and Comparison of Two Methods

In power systems, frequency deviation from nominal value can occur due to reasons such as loss of generation, loss of load, or major faults in the grid. Such frequency fluctuations can lead to serious subsequent outages and damages to both end-user and utility equipment. Therefore, a proper frequency deviation detection methodology must be in place to effectively identify frequency events in a timely manner. This manuscript provides a comparative analysis between two frequency deviation detection algorithms. One is based on signal processing and statistical analysis. The other is a regression-based algorithm. Both of these algorithms have multiple adjustable parameters, making them highly tunable for different Balancing Authorities

Product Specification: Distributed Trust Model System (DOE-PSU-0000922-4)

A Distributed Trust Model (DTM) System is a supervisory component within an energy grid of things. The role of a DTM System is to implement the trust aspects of an energy services interface. The DTM System augments existing security measures by monitoring the communication between the various EGoT System actors and quantifying metrics of trust of each actor

Trust Model System for the Energy Grid of Things Network Communications

Network communication is crucial in the Energy Grid of Things (EGoT). Without a network connection, the energy grid becomes just a power grid where the energy resources are available to the customer uni-directionally. A mechanism to analyze and optimize the energy usage of the grid can only happen through a medium, a communications network, that enables information exchange between the grid participants and the service provider. Security implementers of EGoT network communication take extraordinary measures to ensure the safety of the energy grid, a critical infrastructure, as well as the safety and privacy of the grid participants. With the dynamic nature of network communication of the EGoT, the information provided by the customer or the service provider can be falsified by a malicious attacker. Therefore, a trust model is necessary to monitor any abnormal activities. This paper describes a distributed trust model system that meets the need of the EGoT. This paper describes methods for evaluating and improving the distributed trust model using standard hypothesis testing metrics such as true positive, false positive, true negative, false negative, equal error rate, and F1 score. Example calculations are shown based on generated sample data

Chlamydia trachomatis Serology in Women with and without Ovarian Cancer

Pelvic inflammation has been implicated in the genesis of ovarian cancer. We conducted serologic measurements of Chlamydia trachomatis antibodies as a surrogate marker of chlamydial pelvic inflammatory disease. Women with ovarian cancer (n = 521) and population-based controls (n = 766) were tested. IgG antibodies to serovar D of chlamydia elementary bodies (EBs) were detected using an ELISA assay. The odds of having ovarian cancer among women with the highest titers (≥0.40 OD units) were 0.6 (95% CI 0.4–0.9). These data do not support our earlier finding of elevated titers for antibodies to C. trachomatis among women with ovarian cancer

Dynamical derivation of Bode's law

In a planetary or satellite system, idealized as n small bodies in initially coplanar, concentric orbits around a large central body, obeying Newtonian point-particle mechanics, resonant perturbations will cause dynamical evolution of the orbital radii except under highly specific mutual relationships, here derived analytically apparently for the first time. In particular, the most stable situation is achieved (in this idealized model) only when each planetary orbit is roughly twice as far from the Sun as the preceding one, as observed empirically already by Titius (1766) and Bode (1778) and used in both the discoveries of Uranus (1781) and the Asteroid Belt (1801). ETC.Comment: 27 page