EEWeb Pulse - Issue 74

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EEWebIssue 74

November 27, 2012

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Distribution SystemsAutomation andOptimizationPart 1

TECHNICAL ARTICLE

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PRODUCT REVIEW

President & CEORenesas Electronics America

Ali Sebt

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EEWeb PULSE TABLE OF CONTENTS


Ali Sebt PRESIDENT AND CEO OF RENESAS ELECTRONICS AMERICA

Keynote Address from Renesas DevCon 2012

Why Distribution Automation (DA) is considered to build upon in developing the Smart Grid as it transforms the distribution network towards more automation.

RTZ - Return to Zero Comic

Featured Products

BY NICHOLAS ABI-SAMRA WITH QUANTA TECHNOLOGY

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13

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Distribution Systems Automation and

Review of the Rigol DSA-815 Spectrum

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BY CHRIS ANDERSON WITH ECE101A detailed look into the specs and features of a new spectrum analyzer from Rigol.

Analyzer

Optimization - Part 1

EEWeb PULSE SPECIAL FEATURE

4 EEWeb | Electrical Engineering Community

AliSebtRenesas



AliSebtRenesasDevCon is a bi-annual conference sponsored by Renesas Electron-ics America. The event was held in Anaheim, California. The Renesas DevCon provides an environment for valuable technical information exchange and access to Renesas’ technology experts and partners from around the world. The event features hundreds of hours of lec-tures, workshops, panels and keynote addresses. This year’s event was dedicated to discussing how global tech leaders can enable the smart society of the future.

Ali Sebt, President and CEO of Renesas Electronics America, deliv-ered this year’s DevCon keynote address. He detailed the technolo-gies that Renesas provides to enable the smart society, providing countless opportunities for future generations. The following is an ex-cerpt from the keynote address.



Good morning, my name is Ali Sebt, President and CEO of Renesas in the Americas. When we were putting this video together, the thought that came to mind was that the sensationalism that exists in the news today—wars, famine, austerity measures—and all of the challenges that we as adults face, are very stressful. And oftentimes, I found myself very worried for my children’s future—I have a 14-year-old son and a 12-year old daughter—and I found myself very worried for their future. However, I realized that when I talked to my children, they had a very different perspective about their future. They see a future filled with possibilities. Sometimes, they say they want to be a doctor or a football player or a ballerina and I’m sure all of you who have children have experienced this; from time to time, they change what they want to be in the future. That says that they see a world and a future full of possibilities.

* * *

While Renesas is here today to share with you the techniques and the latest products we have to offer for embedded applications. The underlying unity and connection we have is joint responsibility we have for our children and the next generation. If we go back to the early 1800s, the world’s population stood at 1 billion. Fast forward a hundred years and the world’s population doubled to 2 billion. Fast forward to today, and the world’s population stands at 7 billion. We also know at the same time, throughout the past 100 years or so, that extracting fossil fuels has also become a challenge—our resources are becoming more scarce. At the same time, there’s a third dimension, which is the fact that all of us are utilizing more electricity and more power because all of us have more gadgets and electronics surrounding our lives. So, the purpose of this presentation is to talk about how we, as solution providers, and you, as embedded designers, can find a solution to these diametrically opposed forces; more people, more inhabitants, more users, less energy and more energy requirements per individuals.

This “Smart Society”—or the challenges that face the “Smart Society”—can be addressed by four areas: low-power electronics using low-leakage semiconductors; taking advantage of the proliferation of sensors—sensors are becoming ubiquitous around us; taking advantage of the signal chain—what Renesas provides (analog, microcontrollers and power stage)—and finally; security.

Let’s begin with low-power semiconductors. If we go back to the mainframe era, the focus of computing was really executing faster transactions. As we fast forward to the PC era, the focus was faster graphics and faster execution of instructions with limited focus to power consumption. Of course, in the last decade, as the networking and Internet grew around us, the focus was how we push more video and packets down the pipe. Throughout these decades, there has been little regard to how we address power consumption—it’s all been about performance. Renesas, on the other hand, for the past three or four decades, has been focusing on low-leakage transistor technology. Our microcontrollers are



developed with the very intent focus of developing low-power consuming technologies.

Over the past few decades, in general, embedded systems have focused on performance, and now there’s an imbalance between performance and power consumption. At the onset of this decade, we have seen a shift in this balance—we now have commercial-electric vehicles on the road, we have computer devices that truly do consume low-power. We have seen a shift in the mentality of embedded designers toward focusing on low-power consumption appliances. I will touch on one of our microcontrollers—the RL78—which addresses

the 8- and 16-bit space. We mention true low-power because I know you as engineers are always skeptical with specmanship. We know that some suppliers fine-tune their MCU architecture so that it works well in one mode and not necessarily in other modes. Often times, you have a challenge duplicating the results in your end system. Renesas provides a true low-power microcontroller in this area and I’ll show you some of the numbers.

In “Run” mode, the RL78 consumes 144 micro-amps per MHz. The closest competitor is Company S at 150. Remember, I said earlier that competitors fine-tune their

The underlying unity and

connection we have is joint

responsibility we have for our children and the next generation.

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microcontrollers to be low-power in one mode. Now as we go to the next mode, which is the “Halt” mode, you’ll see that the RL78 consumes less than half of one micro-amp. But the previous competitor, which was Company S that was the closest, is now off the charts.

Let’s go to the “Stop” mode. In this mode, and in Smart Society applications, this is one of the mode that your MCUs will most likely be in. You see that the RL78 is really showing off its low-leakage transistor capability. Now in this case, you’ll see that Company T, which was closest to us in the “Halt” mode, is now off the charts. We have also added a very special mode, called the “Snooze” mode, which is unique to Renesas. The “Snooze” mode allows, for example, the ADC to wake up and do some measurement and, if necessary, turn on the microcontroller to go into the operation “Run” mode. You can see how much power savings you’ll have if you are running system at 8 or 32 MHz. Incredible savings using the “Snooze” mode.

Let me now talk about sensors. As I mentioned, sensors are around us and are becoming ubiquitous. In order for the Smart Society to be effective, we have to take advantage of our analog, real-world environment. Let’s take, for example, irrigation. Often times, we drive by parks, golf courses, and lawns where we see that the driveway is wet because water seeps through the soil at different rates. Soil is made up of different compositions; there’s clay, sand and three other types. This is why you see dry spots and wet spots. Imagine if we embed moisture sensors in the ground that will be able to communicate back to the control panel if an area of the lawn has had enough water. We know that water is also very precious, so we not only want to conserve the energy that delivers water, but water itself. Of course, as embedded applications are connected to the Internet, you will know if there is rain in the forecast that day and will prevent the irrigation from watering that lawn altogether.

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At the onset of this decade, we have seen a shift in this balance—we have now commercial-electric vehicles on the road, we have computer devices that truly do consume low-power.

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Let’s take this sensor concept to the next stage. We know that in the automotive arena, more and more companies are deploying frontal-view cameras for safety. We also know that they are deploying frontal view radar for safety. However, none of these sensors alone, is adequate to provide enough intelligence for the onboard computer to make a smart decision for safety purposes. So the next stage in utilizing sensors is sensor-fusion, where you need to have enough performance with your microcontroller to take in these different types of sensor data, fuse them and make an intelligent decision.

Let’s look at conference rooms and building environments. We see the deployment of temperature sensors, humidity sensors and passive infra-red sensors. Detectors, using our analog microcontroller and power semiconductors, are being deployed in local areas to take advantage of this raw-data, fuse that data, and make an intelligent decisions based on that environment. Here’s an example: these detectors that take localized sensor information and provide intelligent information back to the central unit can aide an emergency response team so they will not have to go to every floor and area in a burning building so that they can focus on saving lives.

You’ve seen sensors, sensor fusion and detectors, so let’s talk about how the detectors are built—which is where the signal chain comes in. All of these sensors provide analog information. This analog information first has to be conditioned and amplified so that the microcontroller can receive it in the right format. Then, the microcontroller will fuse this information and make an intelligent decision. But remember, you are no longer in an on/off world—you are in a world of multiple analog and multiple forms of information, so you need a highly powerful and low-power consuming microcontroller that can mathematically and algorithmically compute this information and make the right decision. And, of course, coming out of the microcontroller is the power stage, which will invoke a decision back into the real world.

Renesas has introduced a new technology called Smart Analog. It’s a singular device that has a programmable and re-configurable analog front-end, which is basically made up of op-amps mated with the true low-power RL78 MCU into one package. So, using a web-based, GUI IDE, you can design, test and validate your system in one day without having to build a physical system and tune the analog system all day long. Of course, your component count will be reduced almost 10 to 1. When you think about it, you no longer need to have your



resistors, diodes and capacitors on the board, because it’s all going to be programmable and re-configurable in this one chip.

Let’s talk about security. With the Internet of things, which is a part of this Smart Society, machines are going to be connected to everything in the network. With a machine-to-machine connection, it’s very important to secure your information and secure the credentials of who will have access to your machines. When we talk about security, we are really talking about authentication. Typically, in machine applications, there are three levels of authentication. First, you have to authenticate the user. Second, you have to authenticate the machine. And third, you have to authenticate the services. So, in this example, if a friend comes to your house and wants to charge their electric vehicle at your house, you obviously don’t want to pay for that. The utility company will authenticate your friend, in this case, so they know who to bill. They will authenticate the electrical vehicle so they know what kind of charging is required for this vehicle. And, of course, they will authenticate the services so they know how to bill, where to bill and so on.

Our DNA and our R&D, as we develop these products and solutions for our smart society, are focused on these fundamental areas: how do we enable you to generate, store, control and ultimately save energy. All of our products and solutions are designed and developed with these areas in mind.

To watch the entire keynote address and other Renesas videos on their

YouTube page:

Click Here

http://www.youtube.com/playlist?list=PL8B1DC420CF309108&feature=plcp

www.renesas.com

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EEWeb PULSE TECH ARTICLE


Present day Distribution Automation (DA) goes beyond reducing manual procedures. DA makes distribution systems more controllable and flexible based on accurate data for decision-making applications. This is accomplished through a set of intelligent sensors, processors and fast communications to remotely monitor and coordinate distribution assets.

DA is considered a foundation to build upon in developing the Smart Grid as it transforms the distribution network towards more automation.

Nicholas Abi-SamraVice President of Quanta Technologies

DistributionSystems

Part 1

Automation &Optimization

Vice President, Asset Management - Quanta Technology



Nicholas Abi-SamraVice President of Quanta Technologies

DistributionSystems

Part 1

Automation &Optimization



Distribution Automation History and Initial Concepts

Over 30-40% of the total investments in the electrical sector go to distribution systems, yet, they have not received the technological impact in the same manner as the generation and transmission systems. Up until recently, most of the distribution networks have worked with minimum monitoring systems, mainly with local and manual control of capacitors, sectionalizing switches and voltage regulators and, without adequate computation support for the system’s operators. This is now changing, with the trend increasingly moving to automate distribution systems to improve their reliability, efficiency and service quality.

Over the years, Distribution Automation took many shapes, form local automation with no communication requirements, to more advanced, two-way communication, as shown in Table 1. The concept of automation in distribution systems has been around for many decades, but had a ripple in in the 1970’s, albeit at a sporadic pace, for the improvement of distribution system operating performance. Early automation applications included capacitor switching, voltage regulation and limited feeder reconfiguration. From the 1990’s distribution networks started to come under pressure to improve the quality and reliability of the delivered power. Efforts to make the power distribution systems ‘smarter’ started to get hold and traditional distribution automation (DA) was born.

During those years, the use of reclosers and automatic switches to reduce outage times became more widespread. In addition, due to deregulation, distribution systems also came under cost pressure for optimization of operation and maintenance practices. In the 2000’s, the above pressures increased along with new ones such as the ever increasing occurrences of distributed generation in many forms in MV and LV networks. These requirements are pushing further the need for monitoring, automation, control and protection of distribution systems. DA applications have been related with the deployment of SCADA (Supervisory Control and Data Acquisition) technology in the distribution circuits and substations.

TypeCommunicationsRequirements

LocalAutomationNoCommunications

Monitoring& ControlOne-WayCommunications(Limited Bandwidth)

AdvancedDistributionAutomationAdvanced Two-WayCommunications

Example Applications/Automation Level

• Sectionalizers: Automated fault restoration via pre-programmed sequencing.• Voltage regulators: Automated voltage regulation for long feeders

• Remote control of capacitors and feeder reclosers• Messages from short circuit indicators control center for fast fault location• Distribution line monitoring• Power Quality (Harmonic content) measurements

• Fault detection and restoration• Automatic reconfiguration of feeders• Voltage regulation and reactive power control for: ° Reduction of line voltage during peak load conditions, or for energy conservation ° Reduction of system losses ° Buck/boost bus voltages in case of abnormal situations, such as threat of voltage collapse, back-feeding, etc.• Distribution underground network grid monitoring and control• Supporting Distributed Energy Resources (DER) and microgrids• Complementing AMI• Interacting with transmission system

Distribution Automation (DA) or Advanced Distribution Automation (ADA)?

Some like to divide the terminology used for DA and ADA, in the sense that the former is concerned with automated control of basic distribution circuit switching functions, while the latter, ADA, is concerned with complete automation of all the controllable equipment and functions in the distribution system. In this document, the term DA is chosen to automation applied to the distribution system, with regard to the above distinction.

The number of DA projects at the different utilities is



increasing, with different approaches. Many of these projects encompass a large area of a distribution system. It is unlikely that any one approach of DA will be the sole preferred technique for utilities. There are too many differences between various utilities -- and even within an individual utility -- to justify a universal solution.

Benefits of Distribution Automation

The benefits of DA can be grouped into three bins: operational, customer-related and financial:

Distribution Circuit Congestion

Most distribution systems in the United States were designed decades ago based on the loading analysis performed at the time. These were based on historical load profiles, statistical analysis with some assumed diversity factors.

Many distribution circuits have been operating close to their operating limits, and additional load may push them above their emergency operating limits. Several electric vehicles (EV) plugged into the same circuit could cause a localized overload on the distribution circuit and transformers while these are subjected to variations in demand due to normal customer activities. The unbalanced conditions created by such loads are on top of imbalance due to the large number of unequal single-phase and double-phase loads. The above could result in degradation of customer power quality, congestion on certain feeders, voltage concerns on longer feeders and increased line losses.

The major changes in load types, levels and load patterns may now require upgrades to the transformers and other equipment or shifting loads between transformers.

II. FEEDER AUTOMATION

Feeder automation is an important part of distribution automation and has received considerable attention over the last few years. Many approaches have been proposed and implemented in power utilities worldwide. Progress in large scale distribution automation has been slow due to the massive investments needed, but funding by the federal government for utilities implementing smart grids has accelerated deployment of these technologies.

Feeder automation is implemented either based on a centralized approach or a distributed one. A centralized approach is capable of providing complete FA functions but requires large scale implementation. A distributed approach is simpler, more flexible, can be implemented in a small scale but can only provide limited FA functionalities.

III. FEEDER RECONFIGURATION

Distribution systems are normally configured radially for effective coordination of their protective devices. Two types of switches are generally found in the system for both protection and configuration management:

1. Sectionalizing switches (normally closed switches)

OperationalBenefits

CustomerBenefits

FinancialBenefits

• Better fault detection, isolation and restoration• Reduced outage duratiion• Improved voltage profile and reactive power (VAR) management/optimization• Better visibility into the grid and more accurate data informaation for system operation and planning• Better component loading

• Better quality of supply and service reliability• More customer choice

• Less manual labor• Decreased interruption costs2

• Improved utilization of system capacity• Better customer retention for improved quality of supply

I. THEN AND NOW: THE DISTRIBUTION POWER SYSTEM, TWO DIFFERENT ENVIRONMENTS

The increasing penetration of residential and municipal solar generation, and the distributed generation in general, impose challenges on the existing distribution infrastructure and the system operator. New flow patterns may require changes to the protection and control strategies, enhanced distribution automation and microgrid capabilities, capabilities, voltage and VAR management, and over all enforcement of distribution grid infrastructure. The changes are best depicted in the Figures 1 and 2.

2 Over the next 10 years, individual utilities may use various combinations of DA approaches across their service areas to create reliability tiers to maximize customer and utility value. The creation of reliability tiers could introduce new utility revenue models and would allow commercial and industrial customers to choose between “higher-grade” utility power or expanded uses of back-up generators, to lower consumers’ overall energy costs.



2. Tie switches/breakers (normally opened switches).

By changing the status of the sectionalizing and tie switches, the configuration of distribution system is varied and loads are transferred among the feeders while the radial configuration format of electrical supply is preserved and all load points are not interrupted. Feeder reconfiguration entails the modification of the topology of an electrical system by closing or opening tie and sectionalizing switches, in order to obtain a better performance of the system. It has been used to improve voltage regulation balance, feeder loading, as well as reducing system losses. Examples of objectives of feeder reconfiguration include: real power loss reduction, equipment (e.g., transformer and feeder) load balancing, phase balancing, system restoration, bus voltage profile improvement, increasing reliability and power quality improvement.

Real Power Loss Reduction

Under normal operating conditions, the network is reconfigured to reduce the system’s losses. One method which can be used to achieve this is through an explicit formula for determining the variations in system losses, three-phase line flows and voltages in terms of system and network data, with respect to variations in control devices, network components and connections. Transformer losses can be minimized if the substation transformers are loaded in proportion to their capacity.

The reconfiguration of the system for reliability and loss reduction can be accomplished in an automated mode using the same sectionalizers which are used for fault isolation and service restoration.

From a practical point of view, reconfiguration once every few hours would be sufficient for loss reduction. The additional benefit of more frequent reconfiguration is very minimal.

Equipment Feeder Load Balancing

Feeder reconfiguration may be used to avoid over loading of critical transformers (and/or feeders) resulting from load variations. In order to keep the system reliable, a part of the load from the

Figure 1: Then...Simplified Power Systems

Figure 2: Now...Excepted Changes in Flows of Electric Power

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overloaded feeder must be transferred to an adjacent transformer feeder that is relatively lightly loaded. Similarly main transformer overloading problem can be addressed by identifying the appropriate feeder causing the overload and transferring a part of load from that feeder load to an adjacent transformer which is lightly loaded. This redistribution of load among feeders and transformers makes the system more balanced and the risk of overloading is reduced thereby increasing the reliability of a system.

The network can be reconfigured to balance load in feeders and/or to avoid the overloading of critical transformers and feeders resulting from load variations. This redistribution of load among feeders and transformers makes the system more balanced and the risk of overloading is reduced thereby increasing the reliability of a system. One method this could be accomplished is through monitoring certain electrical parameters (current, voltage etc.) in the system and initiating breaker trips based on hitting threshold values.

Reconfiguration in Case of a Fault

By the use of remote interconnect switching; utilities can restore power to as many consumers as possible during the time of multiple faults. Under conditions of permanent failure, the network is reconfigured to restore the service, minimizing the zones without power.

Reconfiguration for Reliability

Predictive reliability models and schemes can be used to compute reliability indices for the distribution system in order to apply algorithms to reconfigure the system to achieve optimum reliability. Thus feeder reconfiguration presents electric utilities with an opportunity to boost reliability without the addition of new components.

Equipment Loading and Voltage Drop Criteria

System reconfigurations should not violate equipment loading and voltage drop criteria; hence, a power flow for each system configuration needs to be performed to identify voltage and capacity violations.

Optimization Techniques

Heuristic techniques have been proposed to reach a near optimal solution for feeder reconfiguration in a short period. Other approaches have been in which the optimal configuration was achieved by opening the branches with lowest current in the optimal load flow solutions for the configuration with all switches closed.

Fuzzy logic and the combinatorial optimization-based methods have also been used.

Special Considerations

Reconfiguration with Weighted Objectives

Reconfiguration of the system may be defined in terms of maximum reliability or minimum losses, or a combination of these two. The task of finding the optimal balance between them is approached as a multicriteria/multiobjective optimization problem. On one hand, we have the customers’ reliability demands for power delivery and on the other hand we have the losses and their economic impact on the system. In the optimization total customer interruption cost is used as the measure of system reliability performance from the customer perspective. The losses costs are closely related to the analyzed network, its components, structure and available resources.

It is possible to extend the multiobjective approach by studying every feeder as an individual objective instead of the total system. Furthermore, with more objectives, the solution space quickly becomes difficult to grasp with the increasing number of load points. It is interesting to note that the two objectives do not entirely point the solution in two different directions.

Reconfiguration with Unbalanced Conditions

The actual distribution feeders are primarily unbalanced in nature due to various reasons, for example, unbalanced consumer loads, presence of single, double, and three-phase line sections, and existence of asymmetrical line sections. The inclusion of system unbalances increases the dimension of the feeder configuration problem because all three phases have to be considered instead of a single phase balanced representation. Consequently, the analysis of distribution systems necessarily required a power flow algorithm with complete three-phase model. Potential unbalanced conditions created by such loads could cause problems on main feeders and other laterals.

Feeder Reconfiguration with Distributed Generation

Recent development in DG technologies such as wind, solar, fuel cells, hydrogen, and biomass has drawn attention for utilities to accommodate DG units in their systems. The introduction of DG units brings a number of technical issues to the system since the distribution network with DG units is no longer passive.



IV. VOLTAGE AND REACTIVE POWER (VAR) CONTROL AND OPTIMIZATION

As energy demands increase, and power-hungry new technologies such as electric vehicles proliferate, utilities will need to find ways to meet peak-load requirements. Volt-VAR optimization, which reduces losses from transmission and distribution, can free up much needed capacity to help meet future demand. For that, the industry has progressed from fixed capacitor banks to one way controlled devices, and now capacitor banks managed by two-way communications and fully intelligent controls that operate based on existing conditions and handle reactive-power loads throughout the distribution system.

Conventional Voltage Control

Conventional voltage control is intended to maintain acceptable voltage profile along a distribution feeder in accordance with locally available measurements. Though this often leads to sensible control actions taken at the local level, this could be suboptimal when it comes to voltage and reactive power (var) control on a larger scale. In addition, utilities continually face system losses from reactive load, or “VAR,” created by large customer load devices such as washing machines, air conditioning units, etc. To address these losses, utilities have implemented methods to regulate and reduce the amount of VAR on their systems through “Volt/VAR control” (a general term used to describe different approaches to regulating voltage and VAR on distribution feeders). By optimizing voltage and reactive power, great efficiencies can be realized on the distribution system. The primary goal of Volt/VAR control is to minimize the amount of VARs generated by centralized generation and shipped via transmission or distribution systems and, in turn, helping utilities achieve greater system efficiency and increased system capacity.

Conservation Voltage Reduction (CVR)

The most common smart distribution voltage control function is Conservation Voltage Reduction (CVR) to intentionally lower the voltage on the distribution feeder to the lowest acceptable voltage value to reduce demand and energy consumption.

The ROI for a VVO project could be as short as two years as a result of cost savings from reduced losses and reduced generation costs.

Ideally, information should be collected form all voltage and VAR control devices and acted upon to obtain optimal consistency with optimized control objectives. This approach is commonly referred to as integrated VVO.

VVO is an advanced application that runs periodically or in response to operator demand and uses two-way communication infrastructure. VVO makes it possible to optimize the energy delivery efficiency on distribution systems using real-time information without causing voltage/current violations. VVO should work in various system design and operating conditions.

Technical Challenges

The control variables available to VVO are the control settings for switchable capacitors and tap changers of voltage regulating transformers.

VVO is basically an optimization problem due to the following challenges:

Load Sensitivity to the voltage profile

Work by this author has shown that customer load is sensitive to the voltage profile of the system and that the load must be modeled accurately to quantify the impacts and benefits of Volt/var measures.

“Discrete”(integer) orbinary decisionvariables

Nonlinearobjective

High dimensionnonlinearconstraints

Large searchspace and control variables

Many possible solutions are notcontinuous, but rather discrete.Examples: For a single switchable capacitorbank, the control variable is binary (Out: 0 or In: 1)For a typical tap changer, the controlvariable is an integer that varies from-16 to +16

Energy loss is a non-linear function

Thousands of powerflow equations

Optimization algorithms need to beefficient and robust for large problems

However, improving the voltage profile (e.g., with capacitors) can result in an increase in load that may exceed the loss reduction. Some conventional loads do not accurately model changes to the system resulting from changes in the voltage profile.



Real-time VVO

New generation of automation control, more robust bidirectional communication, and a new range of line-sensing solutions to enable centralized and distributed control schemes hold a lot of promise for real-time volt-VAR control for reducing line losses and peak-demand shaving. By aggregating and analyzing volt and reactive power real-time data from across the distribution grid operators can monitor the reliability of the system as load-profile shifts occur (thus making long-established power-flow models obsolete). Volt-VAR optimization programs can also provide another opportunity to boost returns from installed assets, such as advanced meters. Closed-loop control schemes, based on real-time data collection, can enable utilities to dynamically manage power quality. Utilities can prevent harmful voltage excursions that inevitably damage and/or reduce the useful life of equipment. The latest technology enhancements offered through advanced volt-VAR controls determine whether devices are turned off or on by taking real-time measurements and analyzing the associated VAR flows. This allows utilities to optimize the system across all feeders served by a substation, eliminating a situation in which one feeder has a leading power factor and another has a lagging power factor but in which the substation bus has met the target power factor. Innovations in volt-VAR management technology are enabling the industry to move closer to maintaining a consistent power factor across all operating conditions

Centralized and Distributed VVO Intelligence

Centralized intelligence allows the management of the grid on an overall substation level to maximize efficiency. Centralized intelligence can be layered over distributed intelligent controls. Such an approach eliminates vulnerability to a single point of failure, such a communication failure which may cause the system to lose all functionality. In a layered system, and in the event that communications are lost, the system would continue to function as a result of the distributed intelligence, albeit, at less optimal level.

VVO Coordination with Other DA Technologies

Volt-VAR can be layered in with self-healing and distributed energy management systems. This could to provide addition layers of intelligence that will improve voltage and VAR support under different operating conditions and system topology changes.

VVO Requirements

For VVO to operate properly, it is necessary to assure that the optimal quantity, sizing and placement of capacitors and regulators across individual feeders. Intelligent controls and communications, as well as central analytical software are then added to into the system.

VVO with Distributed Generation

Advanced volt-VAR control systems are needed to manage the effects that renewable energy resources, plug-in EVs and photovoltaics on the grid. These have the potential of dramatically changing a system’s voltage profile, affecting the quality of service. Having analytics and sensing and a number of voltage monitoring points will create a real-time view of a system’s voltage profile on the system with such devices. Because voltage is managed within tight ANSI norms, the accuracy of the sensing data is important . Communication bandwidth and low latency are also vital factors for obtaining quality data in real time for correct control decisions. It is also important to have sufficient voltage-regulation devices on the feeders, whether these are capacitor banks or line voltage regulators to deal with the intermittency of some of the devices.

About the Author

Nicholas Abi-Samra has been actively involved in IEEE for more than 35 years. As Vice President of Asset Management at Quanta Technology, he and his team help utilities better manage and modernize their assets at lower total lifecycle cost. He was both General Chair and overall Technical Program Coordinator for the 2012 IEEE Power & Energy Society General Meeting.

Part 1 of a 3-part series...

Low Voltage ORing FET ControllerISL6146The ISL6146 represents a family of ORing MOSFET controllers capable of ORing voltages from 1V to 18V. Together with suitably sized N-channel power MOSFETs, the ISL6146 increases power distribution efficiency when replacing a power ORing diode in high current applications. It provides gate drive voltage for the MOSFET(s) with a fully integrated charge pump.

The ISL6146 allows users to adjust with external resistor(s) the VOUT - VIN trip point, which adjusts the control sensitivity to system power supply noise. An open drain FAULT pin will indicate if a conditional or FET fault has occurred.

The ISL6146A and ISL6146B are optimized for very low voltage operation, down to 1V with an additional independent bias of 3V or greater.

The ISL6146C provides a voltage compliant mode of operation down to 3V with programmable Undervoltage Lock Out and Overvoltage Protection threshold levels

The ISL6146D and ISL6146E are like the ISL6146A and ISL6146B respectively but do not have conduction state reporting via the fault output.

Features• ORing Down to 1V and Up to 20V with ISL6146A, ISL6146B,

ISL6146D and ISL6146E

• Programmable Voltage Compliant Operation with ISL6146C

• VIN Hot Swap Transient Protection Rating to +24V

• High Speed Comparator Provides Fast <0.3µs Turn-off in Response to Shorts on Sourcing Supply

• Fastest Reverse Current Fault Isolation with 6A Turn-off Current

• Very Smooth Switching Transition

• Internal Charge Pump to Drive N-channel MOSFET

• User Programmable VIN - VOUT Vth for Noise Immunity

• Open Drain FAULT Output with Delay- Short between any two of the ORing FET Terminals- GATE Voltage and Excessive FET VDS- Power-Good Indicator (ISL6146C)

• MSOP and DFN Package Options

Applications• N+1 Industrial and Telecom Power Distribution Systems

• Uninterruptable Power Supplies

• Low Voltage Processor and Memory

• Storage and Datacom Systems

TABLE 1. KEY DIFFERENCES BETWEEN PARTS IN FAMILY

PART NUMBER KEY DIFFERENCES

ISL6146A Separate BIAS and VIN with Active High Enable

ISL6146B Separate BIAS and VIN with Active Low Enable

ISL6146C VIN with OVP/UVLO Inputs

ISL6146D ISL6146A wo Conduction Monitor & Reporting

ISL6146E ISL6146B wo Conduction Monitor & Reporting

FIGURE 1. TYPICAL APPLICATION FIGURE 2. ISL6146 GATE HIGH CURRENT PULL-DOWN

VIN GATE VOUT

GND

ADJ

+

-

+

VOUT

+

-

+ COMMONPOWERBUS

Q1

ISL6146BFLT

BIAS

VOLTAGE

DC/DCVOLTAGE

DC/DC

EN

(3V - 20V)

(3V - 20V)

Q2

COMMONPOWERBUS

VIN GATE VOUT

GND

ADJISL6146B

FLT

BIAS

EN

GATE FAST OFF, ~200ns FALL TIME~70ns FROM 20V TO 12.6V ACROSS 57nFGATE OUTPUT SINKING ~ 6A

October 5, 2012FN7667.3

Intersil (and design) is a registered trademark of Intersil Americas Inc. Copyright Intersil Americas Inc. 2011, 2012All Rights Reserved. All other trademarks mentioned are the property of their respective owners.

Get the Datasheet and Order Samples

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EEWeb PULSE PRODUCT REVIEW


RIGOLDSA-815SpectrumAnalyzer

Review of the

Chris AndersonEMC Engineer, Lab Manager



In this review, I will be looking at this Rigol DSA-815 Spectrum Analyzer, it covers a frequency of 9 khz to 1.5 ghz. One of the first things you’ll notice when you take it out of the box, is that it’s relatively small, especially for a spectrum analyzer. Yet despite its small size it actually has some heft to it. It gives you a very good feeling about the build quality.

RIGOLDSA-815SpectrumAnalyzer

Review of the

Chris AndersonEMC Engineer, Lab Manager



Here are some of the features and specs:

- 9 kHz to 1.5 GHz Frequency Range

- Typical -135 dBm Displayed Average Noise Level (DANL)

-80 dBc/Hz @10 kHz offset Phase Noise

- Total Amplitude Uncertainty <1.5 dB

- 100 Hz Minimum Resolution Bandwidth (RBW)

One of the things that I noticed when I pulled it out of the box and got it powered on, was the menu structure and the front panel buttons are very similar to those of an Agilent analyzer. I’ve used Agilent Spectrum Analyzers a lot in the past, and I was able to pull this out of the box, power it up, and get right to work. I didn’t need to go through the documentation, dig through it to find different settings, or different modes that I could put the analyzer in; it was all very familiar to me.

On the left you’ll see some status indicators, and those will tell you what kind of detector you’re using, what mode your traces are in, and other settings.

To illustrate just how easy it is to get right to work with this analyzer, I have a 950 mhz signal input into the analyzer (Figure 1).

Since I want to measure it the first thing I’d do is put the marker on it by choosing the peak button, and the second thing I want to do is center my analyzer on it. To do this put the marker on it and hit marker to center frequency. Now I am going to zoom in on that signal, I’m going to dial this band down. Since I know it’s a pretty

narrow signal I can keep dialing down like this, or go right down here and say I want to go down to 10 mhz. And there’s my signal (Figure 2).

Now, if I want to go ahead – and I only have one peak here, but if I want to – I can say I want to go to peak, and I want to turn on my peak table. You can see that it’s detecting any additional peaks that show up, and it’s updating frequency and amplitude in real time.

This unit also has a tracking generator built in. If you’ve never used a tracking generator before they’re very handy for determining correction factors. This analyzer can correct data for you in real time. If you have a correction factor file you can load it in, and it will adjust the amplitude based on frequency, depending on that correction factor.

I’m going to go ahead and switch over to a different circuit, a filter circuit, just to show you the utility of a tracking generator.

Now I have the analyzer hooked up to a filter circuit. The output of the tracking generator is going into the input of the filter, and the output of the filter is coming back into the spectrum analyzer.

What you’ll see with the tracking generator is that it sweeps the same frequency output as it’s reading on the input of the analyzer, so it makes it very easy to determine gain or loss through a filter or an amplifier, or even just through a long run of cable where you need to know what the loss is.

I’m going to go ahead and hit the tracking generator button, and you’ll see that the green light lights up. So

Frequency Range

DANL*1

Phase Noise

Total AmplitudeAccuracy*2

Minimum RBW

Trigger Source

External TriggerLevel

Dimensions

Weight

Interfaces

9kHz - 1.5 GHz

-135dBm, typical

-80dBc/Hz @10kHz o�set, typical

<1.5dB

100Hz

Free Run, Video, External

5V TTL Level

Width X Height X Depth = 14.2 in. X 7.0 in. X 5.0 in. (361.6 mm X178.8 mm X 128 mm)

9.4 lbs. (4.25 kg)

USB host & device, LAN, GPIB (optional), 10 MHZ REF In, 10MHz REF Out, External Trigger In



even if you go over to another menu you’ll know that it’s on, and here you see the pass band of my filter (Figure 3).

If I then go in and want to determine what that pass band actually is I can turn on some markers, and I can set this marker over here, let’s say right about here – let’s say that’s the pass band. It might not be the exact 3db point, but it’ll be close.

Let’s add another marker, and let’s put that marker over here at about the same amplitude, and we’ll say that that’s about our pass band. And if I want to say, “okay what is my actual marker,” without actually switching between them, then I can come down here and I can turn on my marker table, and you’ll see that it’s about 925.5 mhz to 967.5 mhz, and you’ll see those amplitudes updating in real time.

If I want to let the analyzer settle, so that I can account for any noise (or anything else that is being generated) to get a good readout, I can come in here and I can change my trace from “clear right” to “max hold,” and that will retain the greatest value at each frequency point as the analyzer sweeps.

If I clear that menu off I can see that it’s starting to settle in, and it looks like I did an “ok” job picking those points. But maybe I want to know if I really got a 3db point, so I can add another marker, which I’m going to send to the peak, so that one’s coming in at negative 23.63 db. I’m actually setting at about 5 db down, I could go in and dial in those markers if I needed to, but I think this demonstrates the point.

Figure 1: DSA-815 with Signal

Figure 2: DSA-815 Zoomed on Signal

Figure 3: DSA-815 Tracking Generator



Here are a couple other images of the spectrum analyzer:

Figure 4: DSA-815 Side View

Figure 5: DSA-815 Back of Instrument



Of course, one of the things you have to consider when you’re buying an analyzer is the price. I think the Rigol DSA-815 will be hard to beat in that category. The base price is $1,295, and if you need the tracking generator that’s a $1,495 starting price for the entire unit, so it’s a $200 add-on.

I think if you evaluate the DSA-815 against its competitors, as long as the DSA-815 meets your needs from a frequency range and noise level perspective, it would be pretty hard to beat on value. I know a lot of the larger manufacturers don’t even compete in that price range. When I saw it and I saw the price, I didn’t know what to expect when I pulled it out of the box. But I’ve been very impressed and I think it’s a wonderful value – I think if you get to play with one yourself you’ll be very pleased.

To watch the full video review of the Rigol DSA-815, visit the EEWeb YouTube page by clicking the image below:

http://www.youtube.com/watch?feature=player_embedded&v=ZvMFXnkk4PY

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EEWeb Pulse - Issue 74

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