Grid Outages Research Articles

Virtual Synchronous Machine-Based Control of a Single-Phase Bi-Directional Battery Charger for Providing Vehicle-to-Grid Services

This paper presents a single-phase virtual synchronous machine (VSM) and its possible application for providing vehicle-to-grid (V2G) services from domestic battery chargers of electric vehicles (EVs). In a VSM, the power converter is controlled to emulate the inertia and damping effect of a synchronous machine. Thus, a VSM-based EV charger can contribute to the spinning reserve and the frequency regulation of the power system. In case of grid outages, the VSM can seamlessly establish an islanded grid and supply local loads from the battery onboard the EV. In order to avoid the influence on the virtual inertia from power oscillations associated with a single-phase circuit, the proposed control scheme relies on a virtual two-phase system for calculating active and reactive powers. The proposed VSM implementation is described in detail, and its dynamic performances in grid-connected as well as stand-alone operation are demonstrated by numerical simulations and by laboratory experiments.

Front Lines Against the Darkness: Enhancing the Resilience of the Electricity Grid Through Microgrid Facilities

power grids are supposed to be fault-tolerant, but you doubt the premise when you consider daily outages in more populated parts of the world and more recent brownouts and blackouts globally. Power engineers have been pushing forward the frontiers of power systems, and the hard-fought battle against the darkness is supposed to have been won, but the struggle is by no means over. Indeed, the electricity grid today is faced more intensely with challenging issues concerning cyber and physical system security. The recent blackout in Turkey on 31 March 2015, which knocked out the transportation infrastructure in major cities, causing massive traffic jams, is a testimony to this claim. It also shut down vital services to thousands of offices for several hours, inflicting business and social losses (see Figure 1). Although widespread blackouts are regarded as low-probability events, they carry immense socioeconomic costs. In such events, the burden of responsibility often lies with extreme weather events, cascading failures, or similar low-probability, high-impact incidents. According to a report from the White House Council of Economic Advisors, severe weather is the major cause of power grid outages in the United States. Meanwhile, it is estimated that weather-related power outages cost the American economy more than US$300 billion between 2003 and 2012. The report calls for increased investment to enhance the resilience of the power grid against rising incidences of extreme weather such as thunderstorms, hurricanes, and blizzards predicted by climate models.

Optimal Integration of Alternative Energy Sources in Production Systems With Customer Demand Forecast

The objective of this paper is to develop an optimal planning framework for a production system utilizing multisource distributed energy supplies, in order to improve its energy efficiency and to reduce the dependency on grid energy and outage risk. The energy consumption of an automotive seat assembly plant is modeled using a discrete-event simulation, which consumes energy supplied by wind and solar, as well as traditional power grids. Machines can be halted for designed time period to avoid high peak load and operate efficiently in terms of power consumption. On the other hand, the inventory level can be planned by adjusting production goal to better utilize alternative energy and accommodate demand uncertainty using stochastic programming method. The results from case studies show that optimizing waiting time for each process can effectively reduce outage risk while meeting customer demands. Having the optimal production goal to over-produce when alternative energy supply is high can reduce the dependency on grid energy. Also, the benefit of considering predicted future customer demands would have the effect of safety inventory, which can prevent shortages during extremely high customer demand periods.

Structural vulnerability analysis of electric power distribution grids

Power grid outages cause huge economical and societal costs. Disruptions in the power distribution grid are responsible for a significant fraction of electric power unavailability to customers. The impact of extreme weather conditions, continuously increasing demand, and the over-ageing of assets in the grid, deteriorates the safety of electric power delivery. Measures to analyse the robustness characteristics and to identify vulnerabilities of power grids are of utmost importance. This paper proposes a metric to quantitatively assess the robustness of power distribution grids from a topological point of view. Real-world data is used to demonstrate the applicability of the proposed metric as a tool to assess the criticality of assets in a distribution grid.

Structural vulnerability analysis of electric power distribution grids

Power grid outages cause huge economical and societal costs. Disruptions in the power distribution grid are responsible for a significant fraction of electric power unavailability to customers. The impact of extreme weather conditions, continuously increasing demand, and the over-ageing of assets in the grid, deteriorates the safety of electric power delivery in the near future. It is this dependence on electric power that necessitates further research in the power distribution grid security assessment. Thus measures to analyze the robustness characteristics and to identify vulnerabilities as they exist in the grid are of utmost importance. This research investigates exactly those concepts- the vulnerability and robustness of power distribution grids from a topological point of view, and proposes a metric to quantify them with respect to assets in a distribution grid. Real-world data is used to demonstrate the applicability of the proposed metric as a tool to assess the criticality of assets in a distribution grid.

SIMULASI SISTEM KONTROL OPERASI ON GRID SERTA ISLANDING PEMBANGKIT LISTRIK TENAGA SURYA DI JURUSAN TEKNIK ELEKTRO UNIVERSITAS UDAYANA

An on-grid solar power plant will distribute electric power to the grid in normal conditions. But when the supply of grid outages (islanding), on-grid solar power plant also can’t operate because the loss of the reference signal that is used as a reference for the inverter in the synchronization process. So there is potential loss of power when solar power plant can be used as a substitute source of electrical energy while PLN can’t serve consumers. In this research developed a simulation model that refers to the off grid solar power plant 500 Wp in the Department of Electrical Engineering, University of Udayana and can operate on-grid and off grid when islanding in matlab simulink. In this model made operation scenario where solar power plant operates on grid at the beginning of the simulation and after that operate off-grid (not connected to the grid and supply the local load). The simulation results show the model off grid solar power plant has been able to generate a voltage of 220 V and a frequency of 50 Hz in accordance with the solar power plant at the research site. The simulation results also show model of on grid solar power plant has been able to synchronize to the low voltage grid of PLN not loaded and loaded. On/off grid solar power plant model can operate on-grid or off-grid that corresponds to the operation scenario and produce the same output. Thus solar power plant can supply.

A Seamless Transfer Algorithm Based on Frequency Detection with Feedforward Control Method in Distributed Generation System

This paper proposes a control strategy based on the frequency detection method, comprising a current control and a feed-forward voltage control loop, is proposed for grid-interactive power conditioning systems (PCS). For continuous provision of power to critical loads, PCS should be able to check grid outages instantaneously. Hence, proposed in the present paper are a frequency detection method for detecting abnormal grid conditions and a controller, which consists of a current controller and a feedforward voltage controller, for different operation modes. The frequency detection method can detect abnormal grid conditions accurately and quickly. The controller which has current and voltage control loops rapidly helps in load voltage regulation when grid fault occurs by changing reference and control modes. The proposed seamless transfer control strategy is confirmed by experimental results.

A More Resilient Grid: The U.S. Department of Energy Joins with Stakeholders in an R&D Plan

ELECTRIC DISTRIBUTION GRID RESEARCH AND DEVELOPment (R&D) has long focused on the reliability, affordability, flexibility, and efficiency of electricity delivery for end users; however, this focus has primarily been outside the realm of severe climate events. Due to the increasing frequency and intensity of weather-caused grid outages in recent years, the U.S. Department of Energy (DOE) has placed an added emphasis on R&D to enhance resilience to climate change and extreme weather. To forge a focused national R&D effort on grid resilience, the DOE is adopting a public/private partnership approach to join with key stakeholders in developing and implementing a resilient grid R&D plan. This article presents the plan development process and the R&D need areas identified for pursuit.

Flexible Mode Control of Grid Connected Wind Energy Conversion System Using Wavelet

Small wind turbine systems offer services to critical loads during grid faults and also connected back to grid in normal condition. The connection of a wind energy conversion system to the grid requires a robust phase locked loop (PLL) and continuous monitoring of the grid conditions such as overvoltage, undervoltage, overfrequency, underfrequency, and grid outages. This paper describes a flexible control operation to operate a small wind turbine in both stand-alone mode via planned islanding and grid connected mode as well. In particular, a proper monitoring and control algorithm is required for transition between the modes. A wavelet based energy function is used for detection of grid disturbances as well as recovery of grid so that transition between the modes is made. To obtain good power quality LCL filter is used to reduce ripples. PLL is used for synchronization whenever mode changes from stand-alone to grid connected. Simulation results from a 10 kW wind energy conversion system are included to show the usefulness of the proposed methods. The control method is tested by generated gate pulses for single phase bridge inverter using field programmable gate array (FPGA).

A Brushless Wound Rotor Induction Generator for Variable Speed Microhydel Plants Without Ballast Load

A new generator topology for microhydel power plants, capable of unsupervised operation, is proposed. While conventional microhydel plants operate at constant speed with switched ballast loads, the proposed generator, based on the wound rotor induction machine, operates at variable speed and does away with the need for ballast loads. This increases reliability and substantially decreases system costs and setup times. The proposed generator has a simplified decoupled control structure with stator-referenced voltage control similar to a conventional synchronous generator, and rotor-side frequency control that is facilitated by rotating electronics mounted on the rotor. While this paper describes an isolated plant, the topology can also be tailored for distributed generation enabling conversion of the available hydraulic power into useful electrical power when the grid is present, and supplying local loads in the event of grid outage.

Optimal battery sizing for storm-resilient photovoltaic power island systems

Photovoltaic systems with battery storage are analyzed from the perspective that they can operate as a local power island in circumstances of storm-damage or other grid outage. The specific focus is to determine the optimal battery size for a given solar array size, taking into account reasonable day-to-day and seasonal sunlight variations as well as efficiency losses when converting from DC to AC for connection to the grid, or for provision of power during island mode. Three locations in the United States are used as case studies (Newark NJ, Boulder CO, and Tucson AZ). These provide a wide range of sunlight characteristics and illustrate variability factors that will be similar to many locations in continental North America. The analysis of the probability distributions for sunlight brightness then allow for the establishment of a 95% confidence rating for the steady-state power output from a specific combined battery and solar array configuration when faced with a grid interruption. This rating system can be used as a guide for designing systems for future installation.

Nonlinear Koopman Modes and Power System Stability Assessment Without Models

The loss of stability-an instability-can become a critical cause of emergent cascading outages leading to wide-spread blackouts. Penetration of renewable energy sources makes the problem of instability more urgent because of the highly fluctuating nature of such sources. Here we show a data-based approach to stability assessment of power systems without models. This approach is enabled by Koopman mode analysis for nonlinear dynamical systems, which detects an instability based on the properties of the point spectrum of the Koopman operator. We apply the technique to data on physical power flows sampled from the two major accidents, the 2011 Arizona-Southern California grid outage and the 2006 system disturbance of the European interconnected grid, and successfully detect unstable power flow patterns that govern the complex dynamics occurring during the accidents.

Bayesian assessment of electrical power transmission grid outage risk

Lack of unified risk assessment approach to electrical power transmission grid outages when taking into account uncertain data is addressed in this paper. Authors take on Bayesian approach to analyse statistical data of electric grid outages – this enables to achieve a more coherent way to express uncertainty in data and to obtain reliability related measures of the grid. The considered methodology of how to properly manage the statistical inference process is demonstrated through real outage data collected from North American transmission grid. The different cases of electrical power lines unreliability as well as cascading outages are addressed on various levels of complexity – starting from simple Bayesian assessment and then building a more general hierarchical Bayesian model. As a result, geography and environment related variability level is found to be of significant influence suggesting that unreliability of grid lines should in general be analysed having in mind specificity of each line. In addition, such variability highly influences the reliability of the whole grid or any network, as demonstrated in the paper as well. Considering the case of cascading outages, we obtained a hierarchical model, built under the basis of Borel–Tanner distribution, and demonstrated the capability to simulate large blackouts, which has a non-negligible probability of occurrence, as the history of blackouts in the last decades has already demonstrated.

Simple Real Time Non-Co-Operative Game Theoritic Model for Energy Cost Optimization in Developing Countries

This paper describes the significant cost saving opportunities for consumers in developing countries by the use of a simple non-cooperative game theoretic mathematical model for demandside management techniques to mitigate the massive use of diesel back-up during grid outages and also other cost optimization schemes. Application of real time load scheduling optimization is investigated during power outages, for residential consumer in India. This method involves a beautiful formulation of a non–cooperation behavior between the diesel generator & the residential consumer during power outages. This involves a tree model with a two player game, where in player one is the diesel generator & player two is the consumer. Depending on the duration of the outage & the consumers limit on the cost for energy different cost optimization strategies can be generated. The load types modeled include passive loads and schedulable, i.e. typically heavy loads. It is found that this DSM schemes show excellent benefits to the consumer. The maximum diesel savings for the consumer due to strategy formulation can be approximately ranging from 45% to as high as 75% for a flat-tariff grid. The study also showed that the actual savings potential depends on the timing of power outage, duration and the specific load characteristics.

Bayesian Methods for Analysis of Electric Grid Outages

Electric transmission network reliability assessment is considered in this paper. The lack of coherent probabilistic treatment of network reliability is discussed and advantages of Bayesian modelling are used in order to take into account uncertainties due to differences of network parts (i.e. transmission lines located in varying environmental conditions) and resulting failure mechanisms. By analysing real North American electric transmission grid outage event data we show the superiority of Bayesian hierarchical models for network reliability evaluation. General results of network outage hierarchical analysis were directly transferred to evaluate reliability of specific network configuration of several lines.

Grid reconnection detection for synchronous distributed generators in stand-alone operation

Industrial plants/commercial facilities with synchronous generation, seek reliable and continuous operation even at the time of grid outages. Thus, islanding detection methods have been proposed in the literature that can be used to change the operating mode of the employed distributed generators from grid-parallel to stand-alone. Among the few solutions previously presented for switching the control mode in the reverse event of reconnecting to the grid, the method presented in this paper is unique. This grid-reconnection detection technique is low cost, fast, and does not interact with the power quality of the island although it only uses one, locally measured, variable. The method implies processing of oscillatory modes in frequency signal and is independent of the autonomous island's boundary. The investigation also includes a discussion on similar event of merging of adjacent islands. Simulations confirm the successful discrimination between reconnection event and other switching/power quality events. Copyright © 2013 John Wiley & Sons, Ltd.

Parameter tuning for a multi-fidelity dynamical model of the magnetosphere

Geomagnetic storms play a critical role in space weather physics with the potential for far reaching economic impacts including power grid outages, air traffic rerouting, satellite damage and GPS disruption. The LFM–MIX is a state-of-the-art coupled magnetospheric–ionospheric model capable of simulating geomagnetic storms. Imbedded in this model are physical equations for turning the magnetohydrodynamic state parameters into energy and flux of electrons entering the ionosphere, involving a set of input parameters. The exact values of these input parameters in the model are unknown, and we seek to quantify the uncertainty about these parameters when model output is compared to observations. The model is available at different fidelities: a lower fidelity which is faster to run, and a higher fidelity but more computationally intense version. Model output and observational data are large spatiotemporal systems; the traditional design and analysis of computer experiments is unable to cope with such large data sets that involve multiple fidelities of model output. We develop an approach to this inverse problem for large spatiotemporal data sets that incorporates two different versions of the physical model. After an initial design, we propose a sequential design based on expected improvement. For the LFM–MIX, the additional run suggested by expected improvement diminishes posterior uncertainty by ruling out a posterior mode and shrinking the width of the posterior distribution. We also illustrate our approach using the Lorenz ‘96 system of equations for a simplified atmosphere, using known input parameters. For the Lorenz ‘96 system, after performing sequential runs based on expected improvement, the posterior mode converges to the true value and the posterior variability is reduced.

Dynamic Modeling of Community Energy Storage for Lifetime Estimation During Islanding

This paper implements a dynamic model of “community energy storage,” a 25 kWh transformer-level battery system, to show its ability to island downstream electric loads during a grid outage. We utilize one-minute electric demand and rooftop photovoltaic generation data collected in Austin, Texas with the dynamic model to quantify how long community energy storage could island downstream loads before its minimum cutoff voltage is reached and it is brought offline. Our results show that photovoltaics nearly triple the average islanding lifetime of community energy storage during outages occurring in the morning, highlighting the symbiosis between distributed energy storage and distributed photovoltaic generation.

Battery/Supercapacitors Combination in Uninterruptible Power Supply (UPS)

This study presents a study of the reduction in battery stresses by using supercapacitors (SCs) in a 500-kVA rated UPS. We aim at investigating the optimal supercapacitors-battery combination versus the SCs cost. This investigation is threefold; first, supercapacitors and battery models developed using MATLAB/Simulink are presented and validated. Second, the architecture and the simulation of the designed system that combines the SCs and the battery are shown. The supercapacitors are used as high-power storage devices to smooth the peak power applied to the battery during backup time and to deliver full power during short grid outages. By charging the SCs through the battery at a suitable rate, all impulse power demands would be satisfied by the supercapacitors. Third, extensive simulations are carried out to determine the gain in battery RMS current, the gain in energy losses, the energy efficiency and the elimination rate of surge load power. These four performance parameters are determined by simulation and then analyzed. The influence of the SCs recharge on the performance indicators is highlighted. A thorough analysis involving optimal study proposes to draw the optimal SCs number and filter constant from the variation of the aforementioned parameters versus the cost of the SCs.

Parasol and GreenSwitch

Several companies have recently announced plans to build "green" datacenters, i.e. datacenters partially or completely powered by renewable energy. These datacenters will either generate their own renewable energy or draw it directly from an existing nearby plant. Besides reducing carbon footprints, renewable energy can potentially reduce energy costs, reduce peak power costs, or both. However, certain renewable fuels are intermittent, which requires approaches for tackling the energy supply variability. One approach is to use batteries and/or the electrical grid as a backup for the renewable energy. It may also be possible to adapt the workload to match the renewable energy supply. For highest benefits, green datacenter operators must intelligently manage their workloads and the sources of energy at their disposal. In this paper, we first discuss the tradeoffs involved in building green datacenters today and in the future. Second, we present Parasol, a prototype green datacenter that we have built as a research platform. Parasol comprises a small container, a set of solar panels, a battery bank, and a grid-tie. Third, we describe GreenSwitch, our model-based approach for dynamically scheduling the workload and selecting the source of energy to use. Our real experiments with Parasol, GreenSwitch, and MapReduce workloads demonstrate that intelligent workload and energy source management can produce significant cost reductions. Our results also isolate the cost implications of peak power management, storing energy on the grid, and the ability to delay the MapReduce jobs. Finally, our results demonstrate that careful workload and energy source management can minimize the negative impact of electrical grid outages.