The Smart Grid, regarded as the next generation power grid, uses two-way flows of electricity and information to create a widely distributed automated energy delivery network. In this article, we survey the literature till 2011 on the enabling technologies for the Smart Grid. We explore three major systems, namely the smart infrastructure system, the smart management system, and the smart protection system. We also propose possible future directions in each system. colorred{Specifically, for the smart infrastructure system, we explore the smart energy subsystem, the smart information subsystem, and the smart communication subsystem.} For the smart management system, we explore various management objectives, such as improving energy efficiency, profiling demand, maximizing utility, reducing cost, and controlling emission. We also explore various management methods to achieve these objectives. For the smart protection system, we explore various failure protection mechanisms which improve the reliability of the Smart Grid, and explore the security and privacy issues in the Smart Grid.

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Smart Grid — The New and Improved Power Grid: A Survey

Smart Grid - The New and Improved Power Grid:

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The National Academies Press

A control circuit of a surgical device is disclosed. The control circuit includes a first circuit portion coupled to at least one switch operable between an open state and a closed state. The first circuit portion communicates with a surgical generator over a conductor pair to receive a control signal to determine a state of the at least one switch.

Surgical generator for ultrasonic and electrosurgical devices

This paper proposes a novel load management solution for coordinating the charging of multiple plug-in electric vehicles (PEVs) in a smart grid system. Utilities are becoming concerned about the potential stresses, performance degradations and overloads that may occur in distribution systems with multiple domestic PEV charging activities. Uncontrolled and random PEV charging can cause increased power losses, overloads and voltage fluctuations, which are all detrimental to the reliability and security of newly developing smart grids. Therefore, a real-time smart load management (RT-SLM) control strategy is proposed and developed for the coordination of PEV charging based on real-time (e.g., every 5 min) minimization of total cost of generating the energy plus the associated grid energy losses. The approach reduces generation cost by incorporating time-varying market energy prices and PEV owner preferred charging time zones based on priority selection. The RT-SLM algorithm appropriately considers random plug-in of PEVs and utilizes the maximum sensitivities selection (MSS) optimization. This approach enables PEVs to begin charging as soon as possible considering priority-charging time zones while complying with network operation criteria (such as losses, generation limits, and voltage profile). Simulation results are presented to demonstrate the performance of SLM for the modified IEEE 23 kV distribution system connected to several low voltage residential networks populated with PEVs.

Real-Time Coordination of Plug-In Electric Vehicle Charging in Smart Grids to Minimize Power Losses and Improve Voltage Profile

This paper describes work performed by Texas A&M University on the detection of high impedance faults on distribution primary conductors. Some grounded distribution primary conductors may exhibit a very low fault current such that they may not be cleared by over-current protection. These faults may persist indefinitely, possibly causing a fire hazard or a hazard to humans by contact with an energized line. The paper begins with an examination of the high impedance fault problem from the perspective of system protection. The fault detection theory is presented next. The system utilizes a fault-generated increase in the 2-10 kHz component of feeder current for fault detection. EPRI funding enabled the verification and demonstration of this fault detection concept. Measurements were made on several faulted and unfaulted feeders to develop a representative data base of signals to which a relay would be subject. Analysis of these data provided a time and frequency domain signature of these faults. A microcomputer-based prototype relay was constructed and installed on a typical utility feeder. It successfully detected most staged faults while not indicating a false trip during a three month demonstration.

Distribution High Impedance Fault Detection Utilizing High Frequency Current Components

Certain smart grid technologies can reduce the number of customers affected by prolonged outages, and thereby increase reliability through automated switching to restore service. Such technologies are useful, but reactive in nature, performing their function only after a fault occurs and an outage has been detected. They must presume that nonfaulted feeder sections and alternative feeders are healthy and capable of carrying increased power flow. Research at Texas A&M University has demonstrated that sophisticated, automated real-time analysis of feeder electrical waveforms can be used to predict failures and assess the health of distribution lines and line apparatus. Reliability can be substantially improved by detecting, locating, and repairing incipient failures before catastrophic failure, often before an outage occurs. Requirements for data and computation are substantially greater than for devices like digital relays and power-quality meters, but feasible with modern electronics. This paper provides selected examples of failures that have been predicted by intelligent distribution fault anticipation (DFA) algorithms. The data requirements and processing analysis to detect these failures are discussed. The problems related to full-scale deployment of the proposed system in a utility-wide application are presented. The authors use experience gained from their long-term research to propose concepts for overcoming these impediments.

Intelligent Systems for Improved Reliability and Failure Diagnosis in Distribution Systems

Previous papers have described a method for the detection of arcing fallen distribution primiary conductor faults using the electrical noise in feeder current above 2kHz. While this method provided improved detection of such faults, this high frequency signal often would not propagate past capacitor banks. In the present paper, we describe a technique for the identification of arcing high impedance faults using burst noise signals at frequencies near the power system fundamental and low order harmonics. Arcing generates non-synchronous burst noise signals which approximate white noise, providing a signal which can be differentiated from synchronous power system signals in the frequency bands of interest. The primary advantage of monitoring frequencies near the fundamental is that this arcing fault signal at low frequencies will exhibit little attenuation from capacitor banks or other sources. This paper provides preliminary results that arcing faults can be detected effectively using frequency components below 60 Hz or between low order harmonics of 60 Hz. The technique is demonstrated through analysis of analog signals recorded during numerouis staged utility downed conductor tests.

Detection of Distribution High Impedance Faults Using Burst Noise Signals near 60 HZ

To prevent unnecessary power outages, and to remove feeder lines from service only when certain hazardous fault conditions occur, a load analysis system (10) including an apparatus and method, monitors the load level of a feeder line (12) and determines the presence of any arcing on the feeder line. In a two stage load pattern analysis, the presence of arcing and load current level changes are used to discriminate high impedance, low current conditions including a downed conductor, a broken and dangling conductor, a tree or object contact with the feeder line, overcurrent activities, and normal switching events such as recloser operation. The load analysis system (10) also provides output commands including wait, alarm, trip-ready, trip and normal, depending upon which status is diagnosed.

Load analysis system for fault detection

A method and apparatus are provided for detecting an arcing fault on a power line carrying a load current. The apparatus monitors and analyzes the load current to obtain frequency components. The analyzed load current is then compared to frequency components of an arcing fault model spectrum to determine whether an arcing fault exists on the power line. If the difference between the analyzed load current and the model spectrum is less than a selected error value, then an arcing fault exists on the power line. Otherwise, no arcing fault exists and conditions are normal on the line.

B. Don Russell

Papers

Distribution High Impedance Fault Detection Utilizing High Frequency Current Components

Intelligent Systems for Improved Reliability and Failure Diagnosis in Distribution Systems

Detection of Distribution High Impedance Faults Using Burst Noise Signals near 60 HZ

Load analysis system for fault detection

ARC spectral analysis system