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Conventional DECT Technology Is an Option for the Smart Home

Tuesday, August 8th, 2017

A smart home used to mean one with contemporary décor and upmarket furnishings. Now, a smart home is a connected dwelling, based on convenience and energy saving.

Smart homes save energy by not having the heating or lighting on when no one is home; it can protect, monitoring and alerting the user to intruders or fire. Smart lighting and climate controls, connected security systems and entertainment systems can be controlled remotely, with settings adjusted to suit, making the domestic setting more comfortable, secure, and energy-efficient.

The large installed base of DECT (an estimated 600 million homes), coupled with the energy savings of ULE, have created a technology that, for once, does not have to achieve traction from a standing start.

By 2021, there are expected to be 73 million smart homes in North America and 80.6 million smart homes in Europe, according to a report by Berg Insight, Smart Homes and Home Automation. This shows exceptional growth, rising from 22 million smart homes in North America in 2016, and growing from 8.5 million in Europe, in the same year. The projected figures translate to over half of the homes in North America (55 percent), with 36 percent of European households expected to be smart homes. A smart home is defined as a dwelling with a system of Internet connected devices operated by a smartphone app or web portal, controlling automation features, such as lighting, climate control, security, and audio control.

Figure 1: The connected smart home is designed for comfort. (Picture credit: STMicroelectronics)

Figure 1: The connected smart home is designed for comfort. (Picture credit: STMicroelectronics)

“This year is anticipated to be a good year for smart home technology as entry-level smart home systems have become affordable for the mass market at the same time as the reliability and features have improved significantly,” says Anders Frick, senior analyst at Berg Insight.

DECT and ULE Architecture
While protocols battle for supremacy, one well-established wireless communications standard has been working its way into a comprehensive ecosystem to offer a reliable, multi-vendor accessible, infrastructure for the smart home.

Ultra Low Energy (ULE) uses Digital Enhanced Cordless Telecommunications (DECT), the standard for wireless phones, to connect wireless sensors and actuators in a network for a low energy smart home. The DECT ULE wireless communication standard connects wireless sensors and actuators in domestic settings. It is promoted by the ULE Alliance, based in Switzerland, but has silicon and node suppliers around the world. At CES 2017, the ULE Alliance showcased its ULE technology, with multiple vendor demonstrations in its Smart Home.

DECT is an established technology for audio services. Since 1993 when it was defined by the European Telecommunications Standards Institute (ETSI), it has been used in wireless telephones in over 600 million households in over 100 countries around the world. DECT devices can plug into the Internet and are controlled by a DECT handset, making it one of the simplest networks to install.
The Smart Home demonstration in Las Vegas was designed to show the interoperability of products, from multiple vendors for the point-to-point technology. Using the DECT ULE frequency of 1.9GHz (1.8GHz in Europe), wireless connectivity is free from interference and uses the installed DECT telephony base.

ULE offers a low cost of ownership, due to the volume of installed devices and available chips. Most users will know DECT in its analog form, with a standalone DECT base with one or more handsets. In this format, the handset can be used as entry level terminals to control the system. Its other form is as a DECT/Cordless Advanced Technology—Internet and quality (CAT-iq) base, which is integrated into a home gateway. The IP gateway could be a broadband router or a DECT phone base with an Ethernet connection, enabling Asymmetric Digital Subscriber Line (ADSL), fiber or cable to be used for the Internet Protocol (IP) backhaul.

DECT ULE has a range of 70m indoors and 600m outdoors, to connect home automation, security and environmental control in most residential settings, says the ULE Alliance.

The low amount of data that is transmitted to, for example, a monitor detector or door/window contacts, mean that power consumption is low. The sensor node operates on a sleep/wake mode, to preserve battery life, further contributing to energy savings and low maintenance.

Ease of Installation
The installed base of DECT reduces the cost of ownership of ULE technology, which is used to network door phone entry systems, security cameras for internal or external views, door and window locks, motion detectors, smoke and fire detectors and baby monitors.

The DECT ULE standard was introduced by ETSI in 2013. The low energy extension of the DECT standard was designed specifically for wireless home networking. It supports data and voice transmission, to communicate network status or send alerts, for example if a window lock is opened, or when a motion detector is activated.

Unlike other short-range wireless technologies, DECT ULE does not share a spectrum, as is the case with Wi-Fi and Bluetooth. Using a dedicated frequency reduces interference and translates to lower installation costs, as less repeaters are required to cover the same distance range. Less repeaters also reduces the maintenance requirements for the network and means that devices can be added easily to networks.

ULE is more energy-efficient than standard DECT and allows a larger number of sensors and actuators on a single network. Up to 2,000 actuators and sensors can share a DECT ULE network and node devices can be upgraded using the secure ETSI DECT protocol for light data services, Software Update Over The Air (SUOTA).

The star topology used for DECT ULE is based on a central device communicating to nodes, or sensors, on a point-to-point basis. This is less complex than a mesh network and reduces the need for repeaters around the network. The transport layer has a low latency which enables it to connect to an actuator, send a signal, and disconnect in less than 50-millisecond for real-time communication between the DECT basestation and nodes. Maximum data rate is less than ZigBee or Bluetooth Low Energy, at 1-Mbit per second, but suitable for the status update and commands messages which are required in the smart home. Nodes only wake up and communicate when activated, such as a magnetic-contact door lock being opened. This also contributes to energy saving, as many nodes can operate for years on a single AAA battery. ULE uses Advanced Encryption Standard (AES) 128 encryption to protect the transmission of data.

Industry Support
One of the features of DECT ULE is its self-configuring mode. Dialog Semiconductor has produced the Smart Pulse Integrated Circuits (ICs) that are interoperable with the wireless standard. When integrated into end products, the wireless sensors self-configure to connect with the DECT ULE-enabled hub or IP gateway. A smartphone or tablet can manage the sensors within the smart home ULE network.

Figure 2: SmartPulse ICs do not require RF expertise to integrate into a network, says Dialog Semiconductor.

Figure 2: SmartPulse ICs do not require RF expertise to integrate into a network, says Dialog Semiconductor.

For data, Dialog offers the SC14WSMDATA wireless sensor IC, and the SC14WSMDECT for data and audio. The sensor nodes integrate the baseband, radio transceiver, antenna, and power amplifier into a single IC. Power consumption is less than 3-micro A in sleep mode.

There is also the SC14CVMDECT which can be integrated into a hub or gateway for remote management over an Internet connection. This supports voice and data and can connect up to six voice and 256 data sensor nodes. It supports DECT ULE, DECT 6.0, and CAT-iq.

At CES 2017, the ULE Alliance Smart Home demonstration showed the diversity of suppliers that support ULE. Interoperability is assured with the ULE Certification Program. This gives developers confidence that DECT chips, sensors, and nodes as well as basestations can be implemented and controlled without issues of compatibility or multi-vendor supply.

The Crow Group was featured in the Smart Home demonstration with door and window locks, which send an alert when contact is broken. Motion sensors, fire detectors, and humidity and temperature control units also figured in the demonstration.

Figure 3: The DHAN-S module is integrated into many end products and is in the ULE Starter Kit from DSP Group.

Figure 3: The DHAN-S module is integrated into many end products and is in the ULE Starter Kit from DSP Group.

In its ULE-enabled security and life safety nodes, the Crow Group uses the ULE DHX91 System on a Chip (SoC) from DSP Group. This low power SoC is based on an  ARM926 processor and has an RF transceiver, power amplifiers, and hardware accelerators for video and voice applications. In hibernation mode it consumes less than 1-micro Amp.

DSP Group also provides a ULE starter kit to connect and validate nodes on a network. It has a ULE node which uses the DHAN-S module, a controller with a Graphical User Interface (GUI). Code can be generated and inserted into the ULE controller so that it can pair alarms, events, switches and locks and adjust the sensor settings for the network. It also validates the node.

The following month, in Barcelona, at the Mobile World Congress, Leedarson showed its lighting, security and sensing and control systems, which use the DHAN-S module from DSP Group. The module is built around the DHX91 and can be used as a wireless connectivity channel for lighting, environmental or security applications that run on an external microcontroller. It can also be used to control smart device hibernation features.

The large installed base of DECT (an estimated 600 million homes), coupled with the energy savings of ULE, have created a technology that, for once, does not have to achieve traction from a standing start.

Energy management in the home, such as smart thermostats and humidity controls, remains the initial focus of smart homes, with monitoring and security, as well as smart lighting are driving adoption. What is clear is that the base of support and multiple vendor accessibility will make deployment and adoption easier to achieve.

hayes_caroline_115Caroline Hayes has been a journalist covering the electronics sector for more than 20 years. She has worked on several European titles, reporting on a variety of industries, including communications, broadcast and automotive.

Smart Thinking

Friday, February 17th, 2017

Smart meters are well-established, but companies are still finding ways to improve communications and smart energy management.

The two-way communications and data systems of smart meters benefit consumers, as they are able to measure energy consumption and so reduce usage to save on bills. The monitoring and measuring functions can also alert users and utility companies when behavior changes to signal maintenance checks. Outside of the home environment, smart meters ensure that manufacturing equipment and motors run efficiently and with minimal downtime. For utility companies, the cost of meter reading is reduced, with reports also noting a decrease in collections and disconnections following smart meters’ debut. Earlier detection of meter tampering and theft strengthens security, compared with older, mechanical meters, and improved transformer load management and capacitor bank switching aid efficiency and reliability.

Figure 1: Smart meters are rising in numbers in homes and industrial networks.

Figure 1: Smart meters are rising in numbers in homes and industrial networks.

Initial fears of exposure to Radio Frequency (RF) have proved groundless. Smart meters have lower RF than other sources found in a typical home. Around the world, however, the operating frequencies vary. IEEE 802.15.4g stipulates a frequency range of 750 to 960MHz. In the European Union (EU) the Wireless M-Bus standard has an operating frequency of 169MHz (for systems in N mode), 433MHz (for systems operating in F mode) and 868MHz, for systems operating in S, C and T modes. Japan’s ARIB STD-T108 operates at 920MHz, and China has adopted Q-GDW347.3, operating at 470 to 510MHz.

Another fear, that smart meter accuracy is weaker than mechanical meter accuracy, has been allayed, overcoming consumer reticence to adopt the smart meter systems.

Worldwide Compatibility

Recognizing the variations around the world, Lapis Semiconductor, part of the ROHM Group, introduced a sub-GHz, wireless communication Large Scale Integration (LSI) device, designed for low power consumption over long distances, for example in smart meters. It allows system developers to configure wireless networks, which are compatible with smart meters worldwide and with agricultural, alarm, and security systems.

The Lapis ML7345 device (Figure 1) covers 160MHz to 960MHz to support the ARIB STD-T108 and IEEE 802.15.4g. It is also compliant with the latest, 2013, version of the Wireless M-bus standard, where improvements to packet handling support extended packet specifications. As well as simplifying networking, a reduction in the number of relays improves system reliability. To conserve energy consumption there is a reduced sleep current during standard operating mode, the majority of communication time, points out the company. The average current is decreased by 48 percent, in 10 second intervals, compared with conventional products, claims the company. Energy management is further enhanced with a high-speed radio wave check function that performs receiver start-up in a short period of time to conserve power. This minimizes the total time for receiver strength detection and decreases current during sleep mode to 0.9µA, or 58 percent less than currently available models, says the company.

Figure 2: Support for worldwide standards makes the ML7345 deployable around the world.

Figure 2: Support for worldwide standards makes the ML7345 deployable around the world.

The LSI’s high output of 100mW is optimized for the Chinese market. The programmable receiver bandwidth settings support the specifications for electricity, gas, water and thermal meters, and for crime and disaster prevention systems.

A transmission power variation of less than ±1dB across the operating temperature range adds stability. The company claims that this increases stability by a factor of three compared to conventional products and simplifies network configuration, as changing environmental conditions do not require the use of multi-hop operation smart meters.

An evaluation kit with onboard LSI is available, with reference design data (circuit diagram, peripheral parts list, PCB pattern recommendation), multiple test scenarios and sample programs, a user manual and tools.

SoC for Multiple Power Sources

Appealing to a wide, near-universal marketplace is clearly a theme for smart meter semiconductor companies. STMicroelectronics has achieved certification at 500kHz for its STCOMET smart meter Systems on Chips (SoCs). The company’s multicore SoC incorporates a PowerLine Communication (PLC) modem, which complies with smart meter industry standards, to simplify design.

The recent certification to the latest G3-PLC protocol for narrow band, low frequency, powerline communications, and PowerRline Intelligent Metering Evolution, or PRIME, v1.4-profile 2 specifications, are described as vital to wide-scale adoption by the company. The PRIME v4.1 powerline communication architecture covers frequency bands up to 500kHz, such as U.S. Federal Communications Commission (FCC) bands. The SoC is certified according to existing G3-PLC and PRIME v1.4 approvals covering European electrotechnical standardization, CENELEC-A, meeting major, worldwide standards.

To meet the needs of various territories, there are four devices in the family. There is the STCOMET05 and STCOMET10 with either 512-kbyte or 1-Mbyte of program Flash, an application-processing sub-system, dedicated security engine with privacy and anti-hacking protection, metering front end, and the PLC module. The simplified versions of each can be used with the developer’s own, proprietary metering front end with the on-chip application processor, security engine, and PLC module.

An ecosystem, including certified protocol stacks, reference designs, prototyping hardware, and tools such as metrology-management software and drivers, supports the development of single-phase or three-phase smart meters based on the ICs.

Software for Energy Measurement

The value of smart meters stems not just from power management, but also from the meters’ usefulness for power consumption monitoring. Software can record energy usage, and the data can be analyzed to meet a building’s requirements or to set parameters for efficient use.

Figure 3: A modular approach combines hardware and software in WAGO’s Energy Data Management system.

Figure 3: A modular approach combines hardware and software in WAGO’s Energy Data Management system.

A recent introduction is WAGO’s Energy Data Management system (Figure 3), which combines hardware and software to record and manage energy data. Based on the PFC200 Series Application Controller and the WAGO-I/O-SYSTEM 750 fieldbus-independent, I/O systems, the modular systems can record energy-specific values. For example, the values could be electrical currents or voltages, gas, heat, water, compressed air or temperature. Software is pre-loaded on the modules. Inputs for recording can be adjusted using parameters, with settings that can be input during operation via a mouse click. The Graphic User Interface (GUI) can be accessed via HyperText Transfer Protocol Secure (HTTPS) communication and a standard browser.

Data can be forwarded to a higher-level energy management software via Modbus Transmission Control Protocol/Internet Protocol (TCP/IP) communication protocol or as a comma-separated values (CSV) file, which stores tabular data. Recorded data can be saved on a Secure Digital (SD) card.

Using the integrated visualization tool makes generating different energy use evaluations possible— a means to create consumption curves that are synchronized to a power supplier. Alternatively, a second-by-second display can show which areas consume peak loads. Monitoring energy in relation to specific process adaptations, another activity the visualization tool enables, can determine how much energy would be saved by using variable speed motors or new lamps, for example, in industrial settings or domestic/office buildings.

Smart energy can provide many benefits for the end user and for the utility supplier. Some of the recent developments highlighted here show how these benefits can be integrated more simply and efficiently for a managed, reliable smart energy network around the world.

hayes_caroline_115Caroline Hayes has been a journalist covering the electronics sector for more than 20 years. She has worked on several European titles, reporting on a variety of industries, including communications, broadcast and automotive.

Smart Energy Grids Integrating Renewables Require New Local-Storage Technologies

Friday, February 19th, 2016

Supercapacitors paired with microcontrollers forge an intelligent power-management solution for distributed networks.

As we modernize our power grids, we become increasingly reliant on Smart Energy, which integrates renewable energy generators to improve reliability and resource efficiency on distributed power networks. At the same time, we need to move toward a better energy-storage technology that’s cleaner and lasts longer than lead-acid batteries. The emerging class of hybrid supercapacitors are superior to lead-acid batteries in both respects. To function on a smart grid integrating locally stored power seamlessly for the user, supercapacitors require embedded controls to balance power production on a distribution network based on supply and demand.

Figure 1: Smart Energy storage unit containing multiple Hybrid-Supercapacitors requiring individual monitoring and control

Figure 1: Smart Energy storage unit containing multiple Hybrid-Supercapacitors requiring individual monitoring and control

ZigBee mesh networks for Smart Energy are an important and well-established market for embedded control. But with the explosive growth of distributed power networks and power-backup systems for mission- critical applications, Smart Energy storage is playing a pivotal role in expanding the makeup of today’s complex power grid. This key role presents a great opportunity to developers of embedded electronic sensors and controls.

Good-bye to “Battery Shortfalls Included”?

Local customer storage of both on-grid and renewable energy has evolved from electrochemical energy storage to alternative technologies for safety, environmental, cost and regulatory reasons. Off-grid and localized microgrids, which operate either in parallel or autonomously to mitigate disturbance on the grid, share similar storage and load-leveling Smart Energy needs. Though time-tested lead-acid batteries are robust and simple from the standpoint of electronic control, they’re unreliable due to a short lifespan of two to three years. And their toxicity makes them environmentally unfriendly.

Similarly, new paradigms have emerged as alternatives to traditional battery-based transportation methods such as Wayside Energy Storage systems, which are substations that buffer power for electric rail applications. Supercapacitors and on-train regenerative power-storage systems are challenging the cost of ownership of lead-acid batteries and the efficiency/cost of extended grid storage. Instead of transporting recovered energy through a low efficiency third rail to remote locations, light power-dense technologies such as hybrid-supercapacitors may be incorporated within the power-train to significantly reduce the transient delivery burden on the power grid.

For a grid increasingly powered by renewables, where timing of peak energy demand can further diverge from peak production, the need for local grid energy storage becomes an imperative. Opportunity has sprung up for safe and reliable power dense-storage solutions, along with better controls, sensors and feedback loops throughout the Smart Energy grids.

Today, alternatives such as mechanical flywheel and capacitive solutions address the shortfalls of lead-acid batteries and can anticipate greater inroads into these and other energy-storage markets. Capacitive solutions are especially interesting for peak power and energy storage applications in that they have the higher power and energy-delivery capabilities for a given volume, when compared to lead-acid batteries. They also have lifecycles that are two to three times longer and are eco-friendly and safe alternatives.

Achieving TCO Advantages

As often happens, the downside to integrating new technology is that more complex system controls and management are required to achieve a total cost of ownership advantage over existing solutions. Hybrid-supercapacitor solutions are no exception. Where older battery technologies are tolerant of over-charge, new system controllers accommodate strict-use constraints while providing reliability monitors for state-of-health and operational-condition communication for hybrid supercapacitors.

A simplified example of embedded control for stacked-cell energy systems is shown in Figure 1. To accommodate elevated voltages and energy requirements, either battery cells or supercapacitors are series-parallel connected to meet specifications. Inherently, cells in a series stack, in some applications supporting voltages up to 800Vdc, are mismatched with regards to their storage characteristics and require constant monitoring and control to ensure maximum storage capability, long life and safety. Specifically, the control processor function of Figure 1 must monitor for imbalance and redistribute energy within the stack when appropriate. The telemetric requirements for this system will include total capacity and capacity utilization, servicing requirements and fault conditions.

Indeed, if you think that Smart Meters are the only embedded process controls useful in grid power systems, think again! With the advent of Smart Energy, applications for process control abound in local power storage as we experience explosive growth in new energy models that bring with them rich opportunities for embedded control. You can liken this challenge to the evolution of power-storage solutions for mobile computing devices in the 1990s, where the need for new, safe and reliable power storage hastened in the era of fuel-gauges and smart-chargers, creating unparalleled opportunity for embedded controls that continues to this day.


GeneArmstrong_webGene Armstrong is the Sr Director of Applications for Paper BatteryCompany. He has consumer industry knowledge in battery integration and management from world leading semiconductor companies such as Maxim, TI, Benchmarq and Sharp.

The Hybrid of PLC and RF Maximizes Reliability in Smart Grid Networks

Wednesday, November 4th, 2015

An unholy trio of impedance variations, attenuation on selective frequencies and noise interference is at war with PLC communication, but the Smart Grid is fighting back with an strategy that makes PLC the backbone superhero of the network with low-power RF as a trusty sidekick.

Intelligent self-configuring fully adaptable networks that connect the power producer with the consumer form the Smart Grid. Smart grids create a platform of robust data networks that enable bi-directional exchange of data for all kinds of power supplies and electrical devices that are plugged into the power grid. This enables remote and active monitoring of operation and fault conditions of the electricity network, thereby delivering the benefits of a highly efficient power network that automatically regulates and controls the distribution and consumption of electricity without failures and outages.

The use of power line communication (PLC) and low-power RF (Radio Frequency) as the communications media for smart grids has many advantages over traditional twisted pair RS-485 networks. With the absence of data cabling between nodes, the team of PLC and RF is easier and less costly to install and provides better communications security.

PLC Network Technology

PLC is a unique means of communication for a power supply system, which takes full advantage of the wide coverage of power line installations without having to lay dedicated cables. This has attracted the attention of power producers and users. Like RF wireless modules, PLC modules can be easily embedded into electrical meters. With mesh networking technology, data collection units (DCUs) are able to exchange data with all the electrical meters within their network of control. Power lines go through floors and walls in the building. Therefore, theoretically, as long as there are power lines, communications over power line may be achieved. However, power lines are constructed with the primary objective of delivering electricity. Its complex distribution network and noisy environments may cause interference, resulting in unstable communications. The factors causing interference can be summed up as:

  1. Huge load impedance variations impact PLC signals: Load impedance changes will affect PLC signal voltages coupled onto the power lines, and this has a direct impact on the transmission distance. Changes in power factor and location of power loads will change load impedances dynamically over time.
  2. Attenuation on selective PLC carrier frequencies: The random switching of electrical devices on a power distribution network may lead to changes in power parameters, resulting in attenuation on PLC signals on selective frequencies. At the same location and instance, this impact may vary across different PLC carrier frequencies. When certain frequencies are unsuitable for PLC, changing to different frequencies for communication might yield better results.
  3. Strong noise interference:  Electrical equipment on the power grid, such as switched-mode power supplies and inverters, can produce significant amounts of interference on multiple frequencies that varies randomly.

Low-Power RF Networking Technology

Low-power RF networking refers to the use of 315M/433M/780M/2.4GHz frequencies with transmit power equal to or less than 50mW. Low-power RF modules may be embedded within electrical meters, to enable the use of wireless data communications in Automatic meter reading (AMR) for power consumption monitoring and data collection. Low-power RF modules can be embedded directly into the meter during production and installed on site without laying cables when deploying. Mature wireless mesh networking technology allows the concentrator to communicate with all the meters within its network control. This kind of low-power RF network is most suitable for deployment within a restricted range where there is a concentration of a large number of low-power communications modules, for example, within a single floor of a building or a room of networked electrical meters. Low-power RF networking also features low power consumption, auto-routing networks, two-way real-time communications and mobility. RF modules are easily embedded into electrical meter, DCUs and electrical appliances.

As low-power RF communications make use of publicly available radio frequencies, other devices that make use of the same frequencies will inevitably cause signal interference. Also, RF signals are vulnerable to obstructions such as walls, which cause signal instability and result in shorter effective communication distances. Signal interference can be alleviated with frequency hopping.

However, when other devices also use frequency hopping to counter interference, this in itself introduces more interference. Hence, the problem of mutual interference cannot be easily resolved.  RF signals’ vulnerability to obstructions also limits their use in smart grid applications. For example, wireless communications between different floors, for instance, between the basement and the ground floor, are often impeded by thick walls resulting in unstable or no communications at all. On the other hand, a PLC network could easily resolve such problems.

PLC devices, like RF devices, may be networked, thus boosting effective communication distances between the DCU and its meters. However, the realization of reliable, long distance, communications between two points should be the basis of any PLC network. Unlike low-power RF, PLC may often enjoy exclusive use of the entire power line communication frequency spectrum from 50kHz to 500kHz. With this ability to use the entire spectrum comes the wherewithal to counter the three major problems notes earlier: impedance, attenuation and interference.

First, depending on different load impedance situations, transmitter output power needs to be automatically adjusted: this would boost the signals coupled onto the power line when required and maximize the transmit distance as much as possible.

The second method for fixing these problems is the use of single frequency hopping. PLC OFDM technology, which uses multiple carrier frequencies, is effective in countering selective carrier frequency attenuation. However, its inherent Peak-to-Average Power Ratio issue presents another set of problems, which results in signal power being averaged down as compared to using a single carrier frequency. An effective approach that is similar to frequency hopping in OFDM is the use of a single carrier frequency to automatically change to the next best carrier frequency when the current carrier frequency encounters interference. This single-frequency hopping has the advantage of ensuring that there is sufficient power coupled to the power line while effectively addressing signal interference issues due to load impedance variations and selective carrier frequency attenuation.

By changing the transmit output power and the carrier frequencies between two nodes in point-to-point communications, load impedance, line attenuation and noise interference may be generally overcome. This effectively improves the reliability and distance for point-to-point communications thus providing a layer of robustness to mesh networks.

Hybrid Implementation Achieves the Best of Both Worlds

While the above measures are effective, they still cannot guarantee a foolproof PLC network in all situations and at all times. To best maximize the reliability, gridComm has developed a hybrid approach with an integration of low-power RF wireless networking technology with ever-robust PLC technology.

The approach is to make use of PLC as the backbone of the network supplemented with low-power RF technology. As a backbone, PLC easily works between different rooms or between different floors. Low-power RF then supplements this in places of overly strong signal interference or where the power lines are physically separated, or on different phases. In addition, RF with reduced power to avoid mutual interference may be used in wide-open places with a high concentration of electrical equipment.

Smart grids deployed using the hybrid approach will form a highly robust network that should counter most of the issues of signal obstruction, interference and attenuation, maximizing Smart Grid networking reliability.

Li Zhou Dai is the CTO of gridComm, a company that provides fully adaptable self-configuring PLC solutions for smart grid, smart street lighting and all other forms of M2M. Dai, who architected the GC2200 OFDMA PLC transceiver, has several years of research and development experience on PLC at the Harbin Institute of Technology. Dai designed the first PLC-based AMI system in China in Langfang city of Heibei province that automatically controls load balancing and consumption of households besides performing normal AMR. This is accomplished by integrating the Medium-Voltage network with the Low-Voltage network using the GC2200 as the underlying PLC device. More than 30,000 units of GC2200 are currently deployed between household low-voltage meters and the medium-voltage distribution system. Dai graduated from Harbin Institute of Technology in China with a Master of Engineering in Electrical Control and Automation.

Secure Smart Meters Enable Smart Choices

Thursday, February 19th, 2015

In small subscriber areas where using data concentrators on the smart grid is like taking a sledgehammer to crack a nut, gateways cannot only save costs but also offer the flexibility of managing different networks from the same data center.

Low-cost embedded processors and increasingly ubiquitous data networks have made it possible to revolutionize energy metering. By enabling two-way communication between residences and utility companies, connected meters with embedded processors can record and transmit usage data to a power company’s data center for use in billing and customer service. These new “smart” meters can also help customers make intelligent choices to save energy and reduce their gas and electric bills.

Benefits for both power companies and their customers explain why utilities are rolling out these communication-enabled meters on a massive scale in countries across the world. However, enabling this two-way communication presents networking and security challenges.

One approach to safeguarding networked metering applications involves embedded SoCs that incorporate features such as advanced security engines and robust data encryption.

Ordinary to Smart

Having intelligence and connectivity built into the meter is not enough to reliably connect smart meters. Achieving reliable connectivity requires advanced networking technologies linking meters with the utilities. Devices such as data concentrators, routers, communications hubs and gateways are essential to connect meters to the backbone of the system. This connectivity, along with embedded processing, is what converts an ordinary meter into a smart meter.

The use and location of these devices on the smart grid differs from country to country. It depends on local regulations, whether it’s an electricity, gas or water meter, and in the case of electricity meters, the architecture of the power distribution network. In the United Kingdom, for example, a communication hub helps gas and electricity meters talk among each other and home displays through ZigBee (Figure 1), sending the information to the backbone system through a Global System for Mobile Communications/General Packet Radio Service (GSM/GPRS) modem.

Figure 1: An example of the communication hub system architecture used in the United Kingdom.

Data concentrators or gateways are preferred for electricity meters, although this depends on region, power distribution network topology, the level of subscriber concentration and the quality of the networking infrastructure.

In countries like Italy, France, Portugal and Spain, data concentrators have been used on a massive scale. They read and store meter information using the narrow power line signal for last-mile communication, and GPRS wireless or Ethernet for upstream communication.

The Argument for Gateways

The level of concentration at the secondary substation is between 200-300 subscribers in big cities. Doing data concentration with or without low voltage supervision works best. A data concentrator is divided into two main components. One component pulls in the data from the meters and stores this information in a database with a complex and powerful web interface. The second component is the communication interface with network coordination capabilities. The PoweRline Intelligent Metering Evolution (PRIME) standard calls this the base node (Figure 2). The application layer of the data concentrator has an embedded Distribution Line Messaging Specification/COmpanion Specification for Energy Metering (DLMS/COSEM) client, which interrogates the meters using the software stack’s encryption capabilities. Usually the data concentrator includes a 3-phase low-voltage supervisor for energy balance and remote supervision. The base node is the part of the data concentrator that builds and keeps the meter network stable, providing a transparent channel to the application layer to talk with each meter.

Figure 2: A data concentrator architecture used in power-line communication

Utilities must deal with a percentage of areas where the number of subscribers is very low—anything between 5-50. In these situations, a data concentrator scaled to manage hundreds of devices is not optimum. Here a gateway, which simplifies installation and offers a cost advantage over a traditional data concentrator, is a better value proposition.

The gateway is a pure communication device. Low-voltage supervision is usually not required. Another important difference: Unlike with a traditional data concentrator, it’s not necessary to store data on the device. The memory only has to store the communication protocols. The application layer can host the DLMS/COSEM client into the central data server, saving license costs and allowing management of different networks from the same data center. You should secure information downstream and upstream with commonly used security and encryption algorithms such as RSA, DSA, AES, SHA, ECC, etc. Anti-tampering features are also important to detect and avoid illegal access to the equipment.

A good example of gateway utilization is the PRIME standard smart metering network (Figure 3). A PRIME gateway comprises a PRIME base node that manages everything related to power line communication (PLC) networking, a GPRS/GSM modem and an Ethernet interface.

Figure 3: The PRIME gateway architecture.

A smart metering architecture based on gateways opens a-world of possibilities as the smart grid evolves. The advantages are lower costs in low-subscriber density areas, as well as in the operation and maintenance of the network. The gateway concept allows the integration of different telecommunication technologies over PLC enabled smart meters. This improves the performance of the entire network.

jesus_tejeiroJesus Teijeiro is director of business development for Smart Energy products at Atmel Corporation. He has an electrical engineering background and more than 18 years experience in the semiconductor industry. He has worked for semiconductor distributors Arrow Electronics and EBV Elektronics, and semiconductor companies including National Semiconductor, Fairchild, Fujitsu, Cypress and ADD Semiconductors.

Data Concentrators are Key to Engineering a Smarter Grid

Wednesday, April 9th, 2014

To design cost-efficient and future-proof concentrators, developers need to carefully consider WAN and NAN options, hardware platform scalability, software availability and networking/data security design.

According to a recent An­nual Energy Outlook, worldwide energy con­sumption will increase 50 percent by 2035, and electricity alone will increase by 30 percent during the same time1. Global demand for electrical power has outstripped supply and there’s no end to the situation in sight. Unfortunately, only generating more power is not a viable solution. A more feasible way for both the short and long term is to be more efficient with the electrical power that is already being generated and dis­tributed over the grid.

A step in this direction would be to make the grid itself more intelligent so that power utilities, governmental regulators, power distribution companies and consum­ers could better monitor, analyze and control energy generation, distribution and usage. Along with smart meters deployed worldwide in the last ten years, data concentrators play a key role in enabling intelligent power consumption with more robust end-to-end communications.

Challenges Facing the Smart Grid

Data concentrators serve as the interface between the utility-controlled smart grid distribution network and end users, managing the data exchange between the utility and multiple smart meters in a particular geographical area. In both advanced metering infrastructure (AMI) and automated meter reading (AMR) systems, data concentrators—also called data aggregators—provide the core functionality required to measure, analyze and collect energy usage. They then communicate that data to a central database for billing, troubleshooting and analyzing.

Before we jump into the details about data concentrators, let’s take a look at the current grid challenges that concentrators need to address:

  • First, a variety of communication standards and protocols exist between meters and utility servers. On one side, smart meters could be configured with a neighbor-area network (NAN) communications, featuring narrow bandwidth and lower power consumption, based on regional or country-wide policy, such as RS485, narrow band power line communication (PLC), broad band PLC, low power RF, etc. On the other side, utilities may have an existing wide-area network (WAN) communication, featuring higher bandwidth and higher data speed, to collect data such as GSM/GPRS (migrating to 3G/4G network), Ethernet, optical cable, even proprietary radio. The concentrator should have enough communication processing capability and flexible / configurable interfaces to deal with those protocols.
  • Cyber security and privacy protection is a major concern. With the adoption of cloud-based smart grid solutions, increasing cyber threats are forcing stronger security measures on all levels of smart grid equipment. Research suggests2 the global smart grid cyber security market will grow at a CAGR of almost 30 percent over the period 2012-2016. Also, information from private residential dwellings needs to be protected, and not accessible by non-authorized parties. Specifically, utilities are requiring more and more security features on data concentrators, including device security, content encryption and anti-hacking.
  • Real-time monitoring is needed to diagnose the status of a regional grid. Along with modern grid network migration, utilities need to access the status of the grid network, not only the residential low-voltage power grid, but also renewable and distributed energy networks, such as from solar inverters, solar panels, industrial lighting networks, etc. Metrology and power analytics will be required on data concentrators to monitor power-line performance and efficiency, so utilities can take immediate actions to reduce outage or fix local power line issues.
  • Finally, support is needed for a number of applications, software and upgrades. To enable advanced applications such as demand response, metering data management, billing information statistics, inventory management, web browsing, networking protocol conversion, etc., utilities must have advanced operating systems and powerful processors on the data concentrator.

Main Functions of a Data Concentrator

Data concentrators push intelligence to the edge of the grid by integrating, organizing and aggregating information from e-meters or other end equipment on the grid. Typically located at the transformer or a secondary substation level, data concentrators need to have the following basic functions (Figure 1):

  • Provide reliable communication with meters and head ends
  • Secure consumers’ data and information
  • Monitor regional grid status
  • Support various data management applications.
TI Figure 1
Figure 1. The main functions required of modern data concentrators

Technologies To Consider When Designing Data Concentrators

Typically, data concentrator systems use sophisticated designs based on microcontrollers (MCU) or microprocessors (MPU) and rely on multiple wireless or wired communication in the last mile. There are many considerations when starting to develop a concentrator system, including how system flexibility will comply with regional or global communication regulations, how system scalability will support from 10s of service node to more than a thousand service nodes with a reasonable cost structure, key security features, and how to support advanced applications. A superset of a smart data concentrator system is shown in Figure 2.

TI Figure 2
Figure 2. A diagram of a typical data concentrator system, based on TI’s Smart Data Concentrator reference design.

NAN Communication Options

Power line communication (PLC) has been used for many decades and gained worldwide interest with its ability to modulate communication signals over existing power lines and enabling devices to be networked without introducing any new wires or cables. This capability is extremely attractive across a diverse range of applications, including utility metering, home area networks, lighting and solar, which can leverage greater intelligence and efficiency through networking.

A variety of new services and applications now require greater reliability and data rates than PLC techniques from the past. Several factors impact PLC performance, including impulsive and narrowband noise, time-varying line impedance and frequency-selective channels. Table 1 and Figure 3 present three-phase PLC data concentrator PHY test criteria and performance results with special care to cope with those factors.

TI Table 1
Table 1. Criteria and results from a three-phase PLC data concentrator PHY test
TI Figure 3
Figure 3. Performance of a three-phase PLC data concentrator

PRIME, G3 and IEEE P1901.2 are the three PLC standards most discussed in the market recently, all of them based on orthogonal frequency division multiplexing (OFDM) modulation and channel coding techniques to efficiently utilize the CENELEC band (regulated in Europe) to achieve high resiliency to interference and attenuation, and data speeds up to 40kbps. If using the full FCC band (3kHz-490kHz), a higher data rate (40Kbps-1Mbps) can be reached. On the PHY layer, robust modes are defined and enable communication across the medium voltage (MV) to low voltage (LV) transformers. As a result, the latest PLC can achieve reliable communications up to 10 km away while crossing between medium voltage transformers. The standards also enable communications over the low voltage and medium voltage (LV/MV) transformer crossing for a total distance of up to 4-5 km, depending on the channel condition. (3)(4)(5)

On the MAC layer, PRIME, G3 and IEEE P1901.2 support IPv4/IPv6 networks in an efficient manner so no additional router is needed to run in IP network.

To achieve the best bill of materials (BOM), a designer needs to consider and integrated analog front end (AFE) to support the full FCC band and a programmable PLC modem to support multiple PLC standards through a software upgrade method. At the network level, a developer also must consider the number of nodes connected to the concentrator, the number of levels from the “leaf” node to the “root” node, the reliability of the switch node, locations and length of the low voltage lines in order to run a reliable automated meter reading and control application.

Aside from PLC, low power RF technology is also widely used at certain regions, as well as RS485 communication used to support legacy meters deployed in those markets. Those require MCUs or MPUs with enough serial interfaces (for example, up to 8 UARTs).

Considering WAN Communication

10/100/1000M Ethernet and optical cable have been widely used in grid infrastructure as WAN options, but those may be not accessible everywhere, nor the best options from a CAPEX/OPEX perspective. Wireless access technology is another choice. Currently, GSM/GPRS technology has been adopted (up to 52kbps throughput); future alternatives are WCDMA/CDMA2000 (up to 2Mbps) and LTE (up to 1Gbps). The appropriate choice for WAN technology will likely be made on the following criteria: availability, price, throughput, latency and indoor coverage, with a mix of different technologies possible in the future.

System Scalability

The scalability of a data concentrator’s hardware platform and software capability is important, and it can save a lot of engineering cost and time to market. Depending on specific utility requirements and deployment scenarios, one data concentrator could be connected to less than 100 service nodes (meters), or up to 1000 service nodes. The operating system is also required to enable easy maintenance and upgrading with new applications and networking stacks. For example, with more than a decade of development, Linux has general acceptance as the open source, royalty-free operating system with lots of rich features, also a real-timing patch could be added on if needed. If Linux is needed, some low-end MCUs, not having enough internal memory space and external flash memory support, will be out of consideration. Most engineers are should seriously consider a pin-to-pin compatible MCU/MPU platform with core frequency scaled from 300Mhz to 1GHz, enabling a longer life cycle (>5 years) for the concentrator in the field.

Beyond the hardware considerations, developers need to consider the software needs for their system. In addition to full PLC software stacks, developers can use a complete implementation of the IEC 62056 DLMS/COSEM protocol stack (including server and client stacks), which allows AMI/AMR vendors to jumpstart development of data concentrators and metering head end nodes, not to mention accelerating time-to-market. Another example would be metrology software, which is used to monitor voltage, current, frequency, active power, reactive power, and harmonics over the power line. Most semiconductor chip vendors can provide MCU-optimized metrology libraries.

Cyber Security and Data Protection

There are a couple different levels of security, each based on certain network deployment and overall security strategies that different utilities may require.

  • Network security
    • This will be managed by the communication protocol itself, for example, IPSec, SRTP, ciphering (AES, DES, SHA-1/-2), etc.
  • Device security
    • Includes secure boot and runtime security.
    • Secure boot protects software stored in the boot image and protects device from executing unauthorized software; multiple public keys and customer keys will be involved during the boot sequence.
    • Runtime security controls the management of emulation, debug, trace and test capabilities within the system. Memory pages, registers and peripherals will be configured with access levels, such as “user” or “supervisor” mode; read, write or execute mode, etc.
  • Secure storage
    • This will protect the data in non-volatile peripherals or off-chip memory (vender software/IP, or user private data).
    • Also provides re-authoring support (re-encryption with device specific key).


Data concentrators play an important role in a modern AMR/AMI system. To design cost-efficient and future-proof concentrators, developers need to carefully consider WAN and NAN options, hardware platform scalability, software availability, and networking/data security design.



James Hao is marketing manager for TI’s Smart Grid Infrastructure solutions. He is responsible for worldwide grid infrastructure business development. He has more than 12 years of experience in industrial, wireless communication and networking applications. He earned a BSEE and MSEE from the University of Electronic and Science Technology of China (UESTC).

Smart Monitoring Improves Distribution-Grid Reliability

Wednesday, December 4th, 2013

To accommodate changing use models—including growth in electric vehicles—and improve reliability, smart powerline monitors are necessary for utilities to track dynamic operating conditions on distribution grids.

Four broad trends are changing operating conditions on electric-power distribution grids, and thus increasing stress on distribution infrastructure:

  1. Energy-use preferences have been shifting toward electric power, resulting in electricity-use growth rates which are twice that of other energy sources.
  2. Aging distribution equipment is now on average older than its manufacturers’ recommended operating lifetimes.
  3. Increasing use of electronic loads reduces load power factors and decreases grid utilization efficiency.
  4. Distribution grids are no longer static one-way power-delivery systems, but are now dynamic two-way links that also connect distributed generation resources to loads.

To accommodate changing use models and improve reliability, smart powerline monitors are necessary for utilities to track dynamic operating conditions on distribution grids. Let’s take a closer look.

Challenges for the Grid
Structurally, distribution grids have changed little over the past century. They developed to service comparatively modest, linear loads over moderate distances. Until a few decades ago, that model was a realistic characterization of distribution grids’ operating conditions.

For the last several decades, however, electric power use has been changing. According to International Energy Agency (IEC) estimates, worldwide electricity demand rose from 5.1PWh to 17.9PWh (1015 Wh) between 1973 and 2010.1 Although electric energy use more than tripled over 37 years, it represents only a 3.44% compound annual growth rate (CAGR). It is also more than double the CAGR of overall energy use, 1.69%, and of global population, 1.54%.2

During the same time, most monitoring technology deployments happened at generation and transmission facilities, with monitoring on the distribution grid limited to the head end at the substation. Historical use models allowed utilities to assume correctly that measurements at substations reflected operating conditions throughout the distribution grid. This assumption, however, is actually less valid because actual grid use has become more complex.

Upgrading the distribution infrastructure is expensive. According to a study commissioned by the Edison Electric Institute (EEI), the cost for newly constructed overhead distribution lines ranges from $86,700 to $1,000,000 (U.S. dollars) per mile, depending on the locale and population density.3 Costs for newly constructed underground distribution lines are more than three times those for overhead wires. Utilities are, therefore, eager to squeeze as much use from existing distribution grids as they can.

In addition to the three-fold increase of electric power use in absolute terms, the nature of power loads has changed over the same period in ways that affect grid capacity. Electric power generation and use are measured and billed in energy terms—the kWh. Utilities assess their distribution capacity, however, in terms of current.

Customers pay for real power—the instantaneous product of the voltage and current waveforms. Nonresistive loads present current waveforms that are not strictly in phase with the voltage waveform. In such cases, one can separate the current waveform into the real or in-phase component and the reactive or quadrature-phase component. The load extracts useful work from the real component of the current waveform, but the utility must provide the total current.

Power factor is a measure of real power, as a fraction of the sum of real and reactive power. Even a power factor as high as 0.9 accounts for up to 11% excess grid utilization over and above that for which the power provider can charge residential and most commercial customers (Figure 1). Although electronics manufacturers have been improving their products’ power-factor performance, a large amount of legacy equipment is still in service with power factors as poor as 0.55, corresponding to 82% excess grid utilization (Table 1).

Figure 1: A power factor less than 1.0 forces the utility to provide current in excess of that warranted by the useful power it delivers to a load. Data and graph used with permission from JAS Technical Media ©2013.
Table 1:4 Power Factors and Corresponding Excess Grid Utilizations for Common Electronic Devices

Much of the energy-use growth during the last several decades has been due to the penetration of electronic (as distinct from electric) devices, which present nonlinear loads to the grid. Nonlinear loads generate current-waveform harmonics, which also degrade power factor and drive up excess grid utilization. Various agencies and standards organizations set limits on the harmonic content of current waveforms, typically counting the first 40 to 50 harmonics corresponding to 2kHz to 3kHz measurement bandwidths depending on the controlling norm and locale.

Among the various user sectors, transportation has historically represented a small fraction of the total load on distribution grids (Figure 2).5 In percentage terms, transportation represents a smaller fraction of total global electric-energy use, but in absolute terms, the sector has more than doubled (Table 2).

Figure 2: Although the transportation sector’s percentage use of electric power decreased on a worldwide basis between 1973 and 2010, in absolute terms the sector’s power usage more than doubled during the same period. Adoption of plug-in EV and HEV passenger vehicles is expected to accelerate the growth of this sector during the current decade. Source: Key World Energy Statistics 2012 © OECD/IEA, 2012, p.35.
Table 2.6 World-Wide Electrical Energy Use by Sector

In the U.S. the transportation sector’s electric power use is set to grow faster than the historic organic rate due, in part, to a 2011 White House initiative with the goal of one million cumulative electric passenger vehicles (EVs) by 2015.7 Meanwhile, sales of hybrid-electric vehicles (HEVs) have grown to almost 3% of the annual 12-million vehicle U.S. market, and interest is growing in the plug-in versions of these vehicles.

EV and HEV adoption, however, has not homogeneously distributed across the entire county. Rather, sales have tended to cluster in 24 metropolitan areas so their effect on grid power demand will be greater in some geographies early in their adoption.8 One motivator for vehicle owners to switch to EVs or plug-in HEVs is the cost disparity between regular gasoline and the so-called eGallon—the cost of the electric-energy equivalent to a gallon of regular gasoline: The U.S. average price for a gallon of regular gasoline in August 2013 was $3.56 compared to $1.22 for an eGallon.9

Finally, distributed generation and especially small-to medium-scale renewables are changing the distribution grid from a static, one-way power-delivery structure to a more complex and dynamic two-way system. In particular, customer-based photovoltaic and small-scale wind generation pushes power back onto the distribution grid when their power generation exceeds the customer’s immediate use and, if present, local storage capacity. Moderate-sized customer-owned photovoltaic sites, such as those appearing on the rooftops of office buildings and parking structures, can generate over 500kW and supply more than 250MWh annually. During low use periods, such as weekends, these facilities can push excess energy back onto the distribution grid.

With the distribution grid’s historic operating model, utilities have struggled to detect and respond to a variety of grid conditions, such as voltages at the grid edge from distributed generators.

The High Cost of Failure
The annual economic consequences of electric power reliability events(i.e., power failures) to U.S. power utility customers is about $79 billion according to the Lawrence Berkeley National Laboratory base-case estimate.10 Of this amount, about two-thirds is attributable to momentary service interruptions—those lasting less than five minutes. The duration for the remainder can extend from minutes to days. Loss figures do not include investments in power-failure mitigation equipment such as customer-owned backup generation, batteries or power-conditioning equipment to moderate power-quality events.

In addition to their own financial motivations, electric power utilities are under pressure from customers, industry organizations and regulatory agencies to minimize reliability events. Powerline monitors throughout the distribution grid can operate in concert with automated switchgear to quickly identify anomalous operating conditions, route around affected areas and expedite problem resolution.11

Beyond asset management, monitoring valuable infrastructure components such as branch reclosers and secondary transformers is integral to fast-acting protection methods. Monitoring can also provide valuable data from the distribution grid’s edge. Deployment of powerline monitoring at the secondary transformer level is in its early stages, but is projected to exceed the traditional power-transformer market by 2015 (Figure 3).12 This development is possible, in part, due to the availability of analog and mixed-signal IC components that greatly simplify the task.

Figure 3: Secondary-transformer monitoring is on track for rapid growth, exceeding generator-power- and distribution-substation-transformer monitoring by 2015. Data and chart used with permission from GTM Research.

Smart Monitoring
Powerline monitors located in the distribution grid are topologically similar to those at the substation and elsewhere in the electric power delivery system. Voltage transformers provide scaled representations of the voltage on each of the three power phases and on the neutral. Similarly, current transformers provide a voltage representation of the current passing through each of the three power phases and neutral. The monitor’s analog front-end (AFE) electronics can buffer the eight resulting signals and filter them to ensure that out-of-band (OOB) energy does not alias down to the baseband during the digitization process (Figure 4).

Figure 4: Analog and mixed-signal ICs simplify the power-monitor design task. As the shaded regions indicate in this diagram of potential and current (PT/CT) transformers, most of the necessary functions are available from Maim Integrated.13

In common wye-connected distribution systems, the utility drives the three phases with 120° offset between pairs; voltages are measured with reference to a fourth neutral lead. Under balanced load conditions, 100% of the current flows through the phase connections. Current flowing through the neutral signifies an imbalance. Such an imbalance could indicate, for example, an emerging defect in a secondary transformer’s insulation system, thereby providing the utility with advanced warning and allowing them to replace the transformer on a schedule. Such edge information-gathering saves both the utility the cost of an emergency response and saves the customer the cost and inconvenience of an unanticipated field failure.

Calculating the power over one line cycle requires accurate and simultaneous measurement of both the voltage and current signals for each phase and the neutral. For each lead, the monitor must compute:


Where v(θ) is the instantaneous voltage at cycle phase θ, and i(θ) is the instantaneous current. The monitor can compute reactive power by multiplying the RMS values of voltage and current and subtracting the real component.

The European Union’s IEC 62053 standard for Class 0.2 equipment typifies requirements for power monitors. It calls for measurement error ≤ 0.2% of the nominal voltage and current. Power-factor measurement requires phase matching voltage and current samples to ≤ 0.1%.

Such measurement specifications require that the eight digitizers required for a three-phase line closely match one another and that their sampling times are tightly controlled. Analog and mixed-signal IC makers such as Maxim Integrated provide 4-channel analog-to-digital converters (ADCs) well suited to these measurements.

The ADCs’ differential inputs and control features allow groupings of up to 32 channels of simultaneous sampling. Integrated 8-channel ADCs are also available for monitoring applications that can use single-ended inputs.

Data from a line’s eight voltage and current samples can feed a microcontroller or digital signal processor (DSP) to provide accurate power calculations and assessment of power factor. Systems can use the power factor data to control local capacitor banks and thereby improve overall grid utilization. Protection devices can use the power data for fast-acting automated breakers. Such systems can not only use the data to quickly open a breaker in the event of a sufficiently large line anomaly, but can also use the same data stream to close the breaker, minimizing the duration of the downstream power interruption.


  1. Key World Energy Statistics 2012 © OECD/IEA, 2012,, restated in PWh units by JAS Technical Media.
  2. Population Data—1960 to 2012, World Bank,
  3. Hall, Kenneth L., Out of Sight, Out of Mind 2012, An Updated Study on the Undergrounding Of Overhead Power Lines, Edison Electric Institute, January 2013.
  4. Data for Table 1 were generated from direct measurements. Data source is JAS Technical Media ©2013.
  5. Key World Energy Statistics, 2012 © OECD/IEA, 2012, p. 35.
  6. Data from Key World Energy Statistics 2012 © OECD/IEA, 2012, p. 35, restated in PWh units by JAS Technical Media.
  7. One Million Electric Vehicles By 2015: February 2011 Status Report, U.S. DOE, 2011, .
  8. Charging Ahead: The Last Mile—Is the U.S. electric infrastructure ready to support one million electric vehicles? Deloitte, 2012.
  9. eGallon: compare the costs of driving with electricity, U.S. DOE, 2013. . See also Leistikow, Dan, The eGallon: How Much Cheaper Is It to Drive on Electricity? U.S. DOE, June 2013, .
  10. LaCommare, Kristina Hamachi and Eto, Joseph H., Understanding the Cost of Power Interruptions to U.S. Electricity Consumers, Ernest Orlando Lawrence Berkeley National Laboratory, Sept 2004. Prepared for the Energy Storage Program, Office of Electric Transmission and Distribution, U.S. DOE and Office of Planning, Budget, and Analysis, Assistant Secretary for Energy Efficiency and Renewable Energy, U.S. DOE,
  11. Smart-Grid Technologies Can Reduce Power Outages, but Legislative Action Is Needed, National Electrical Manufacturers Association, July 2012,,-but-Legislative-Action-Is-Needed.aspx .
  12. See Kellison, Ben, Transformer Monitoring Markets, 2013-2020: Technologies, Forecasts, and Leading Venders, greentechgrid, April 2013,
  13. For more information about the parts that Maxim offers for a PT/CT module, go to .



David Andeen is the reference design manager at Maxim Integrated. He joined Maxim in 2005 in the sales department and assumed responsibility for the energy segment from 2011 through 2013. He holds a Ph.D. in materials science from the University of California, Santa Barbara.


Atmel Acquires IDT’s Smart Metering Product Line To Broaden Smart Energy Portfolio

Thursday, March 7th, 2013

Acquisition Completes Atmel Smart Energy Portfolio From the Analog Front-end
to the Processor and Communications Stack

Atmel® Corporation (NASDAQ: ATML), a leader in microcontroller and touch technology solutions, has announced that it has completed the acquisition of Integrated Device Technology’s (NASDAQ: IDTI) smart metering IC product lines and technologies, further enhancing Atmel’s smart energy product portfolio. Terms of the transaction were not disclosed.

The acquisition includes IDT’s Metrology Analog Front End (AFE) and System-On-Chip (SoC) devices for single- and poly-phase energy meters. The smart metering IC product line offers best-in-class single- and poly-phase measurement accuracy with better than 0.1 percent accuracy over 5000:1 dynamic range and complements the existing family of Atmel smart metering offerings. Atmel’s smart metering portfolio includes the world’s first single-chip power line communications (PLC)-based solution targeting the rapidly growing PRIME smart metering market.

“Smart energy is a key focus for Atmel and we are delighted that we have been able to expand our smart energy solutions portfolio with this acquisition,” stated Steve Laub , President and CEO, Atmel Corporation. “By offering a broader, more integrated product portfolio, existing IDT and Atmel customers now have access to a more complete and compelling suite of smart energy solutions that will enable a wider range of applications.”

According to market research firm Pike Research, annual smart grid revenue will grow to $73 billion by 2020, a compound annual growth rate of over 10 percent.

About Atmel

Atmel Corporation (Nasdaq: ATML) is a worldwide leader in the design and manufacture of microcontrollers, capacitive touch solutions, advanced logic, mixed-signal, nonvolatile memory and radio frequency (RF) components. Leveraging one of the industry’s broadest intellectual property (IP) technology portfolios, Atmel is able to provide the electronics industry with complete system solutions focused on industrial, consumer, communications, computing and automotive markets.

© 2013 Atmel Corporation. All Rights Reserved. Atmel®, Atmel logo and combinations thereof and others are registered trademarks or trademarks of Atmel Corporation or its subsidiaries. Other terms and product names may be trademarks of others.

Safe Harbor for Forward-Looking Statements

Information in this release regarding Atmel’s forecasts, business outlook, expectations, and beliefs are forward-looking statements that involve risks and uncertainties. These statements may include comments about our future operating and financial performance, including our earnings outlook beyond 2013 and the progress we may achieve with the integration of acquired products into our business plans and strategies. All forward-looking statements included in this release are based upon information available to Atmel as of the date of this release, which may change. These statements are not guarantees of future performance and actual results could differ materially from our current expectations. Factors that could cause or contribute to such differences include, without limitation, general economic conditions (including solvency issues affecting various European countries, economic slowdowns in China, and fiscal and budgetary uncertainties in the United States), the cyclical nature of the semiconductor industry; the inability to realize anticipated benefits related to our acquisition of the IDT products, restructuring activities or other initiatives in a timely manner or at all; the impact of competitive products and pricing; disruption to our business caused by our increased dependence on outside foundries, industry and/or company overcapacity or under capacity, including capacity constraints of our independent assembly contractors, timely design acceptance by our customers, timely introduction of new products and technologies, industry wide shifts in supply and demand for semiconductor products; financial stability in foreign markets and the impact of foreign exchange rates; adverse changes in tax laws, unanticipated costs and expenses or the inability to identify expenses which can be eliminated; the market price or volatility of our common stock; compliance with U.S. and international laws and regulations by us and our distributors, our ability to protect intellectual property rights, litigation (including intellectual property litigation in which we may be involved or in which our customers may be involved, especially in the mobile device sector), the possible unfavorable results of legal proceedings, and other risks detailed from time to time in Atmel’s SEC reports and filings, including our Form 10-K for the year ended December 31, 2012, filed on February 26, 2013 and our subsequent Form 10-Q reports. Atmel assumes no obligation and does not intend to update any forward-looking statements, whether as a result of new information, future events or otherwise. 


Contact Information

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tele: 408.441.0311
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Why Securing the Electrical Grid Is Generating So Much Buzz

Friday, December 7th, 2012

Today’s electrical grid faces three basic threats: Acts of nature. Acts of terror. Acts of complacency. Focusing on the last two, let’s look at how cyber-terrorism may target known vulnerabilities in our aging electric grid using malicious software, and the glacial pace at which these risks are being mitigated. An increasingly computerized "smart grid" must be designed with security in mind.

The U.S. electrical grid is the nation’s most vital and strategic asset. Comprising a vast combination of public and private electrical generation and distribution systems, it is the infrastructure component that has the greatest impact on the quality of our daily lives. Aside from heating and cooling our homes and providing the basis for food preparation and storage, it also supplies the necessary power for clean water, transportation, communications, life-saving services at hospitals and more. Reliable electricity is essential to commerce, air traffic safety, defense systems and national security.

That’s the good news. The bad news is that the electrical grid has proven highly vulnerable in the face of devastating storms such as Katrina and Sandy. Even more alarming, the greatest threat to the grid is likely to strike without warning and with the potential for far more widespread destruction than any hurricane. That threat, of course, is cyberterrorism. Its prime targets are the countless embedded systems that make up our electrical grid.

More Worms are Surfacing
In recent years, cyberweapons have moved from the pages of spy novels to the front pages of newspapers. The Stuxnet worm generated a flurry of media attention and speculation in 2010, when it attacked several facilities around the world, including Iran’s nuclear enrichment infrastructure. Stuxnet took over programmable logic controllers (PLCs) that control the automation of mechanical processes, causing Iran’s uranium centrifuges to spin out of control.

Since then, discoveries of more advanced variants of the same malware have been reported around the world. In a survey on critical infrastructure security by McAfee and the Center for Strategic and International Studies (CSIS), nearly half of the respondents from the energy sector said they had found Stuxnet on their systems. Security experts who deconstructed the worm deemed it to have a level of sophistication that could only be achieved with a multimillion- dollar budget and “nation-state support.” In addition, more recent examination provided some shocking insights – namely, that the ultimate sophistication of Stuxnet lies in the worm’s ability to conceal the maker’s identity. Worse still, creating the actual cyber payload is not that difficult given today’s prevalence of malware rootkits.

An apparent descendant of Stuxnet called Duqu has also been reported in energy facilities in at least eight countries. Duqu probes for sensitive information and weaknesses that could be exploited in future attacks. More recently, a virus dubbed Shamoon has been discovered by security experts. It targets the infrastructure of the energy sector by wiping critical files from operational computers and overwriting master boot records, rendering the machines useless.


The Mother of All Systemic Failures
Today’s leading security experts believe the next catastrophic electrical failure may have more to do with Father Time than Mother Nature. Why? During recent decades, the focus of energy innovation has been to modernize energy distribution and make it safer, cleaner, more efficient, less costly and open to more alternative forms of production – all viable goals.

These goals are being achieved by adding intelligent devices to the grid and connecting them via the Internet to other operational systems, thus enabling utilities to gain greater operational control of systems. However, over the course of time, this effort to automate and integrate previously disparate and largely proprietary systems has produced a grid that is far more vulnerable than ever before. Here are three key contributors to this vulnerability:

  • Outdated systems – An estimated 70 percent of the existing energy grid is more than 30 years old. Security has largely been an afterthought while connecting these aging systems to the Internet.
  • Automation – Moving systems from manual processes to ones that are Internet-connected gave energy grid operators real-time information while allowing administrators to telecommute and field workers to manage and program systems from remote locations. However, linking industrial control systems (ICS) and system control and data acquisition (SCADA) eliminated built-in system security air gaps, making them accessible to the outside world through the Internet.
  • Interconnection of embedded systems – The third and perhaps most alarming cause of vulnerability is the proliferation and increasing interconnection of embedded software and devices directing the flow of energy. More and more of these devices are being built with off-the-shelf rather than proprietary software, making them increasingly generic, in need of patching and vulnerable. As such, embedded systems are the prime targets of intruders seeking to control or disrupt the delivery of energy.

These trends and their resulting vulnerabilities are readily apparent to Paul Stockton, assistant secretary for Homeland Defense. On July 26, 2012, Stockton told the Aspen Security Forum of his concern about the possibility of a terrorist attack on the U.S. electrical grid that would cause a "long-term, large-scale outage."

Reconnaissance Attacks Are Under Way
Beginning in 2009, a series of attacks known as "Night Dragon" were launched against the global energy, oil and petrochemical sectors. This espionage campaign (either corporate- or state-sponsored) gained access to web extranets, desktop PCs and servers by capturing user names and passwords that could then be used to extract sensitive proprietary data, intellectual property and confidential communications.

According to the McAfee/CSIS study, the leading cyberthreat reported by the energy sector is extortion, affecting one in four interviewed companies. This alarming practice has become commonplace in some countries – 60 percent of executives surveyed in India and 80 percent in Mexico reported extortion attempts. Worldwide, hundreds of millions of dollars are being paid in ransom, according to some estimates.

According to Jason Healy, director of the Cyber Statecraft Initiative at the Washington-based Atlantic Council, "Stuxnet should have been the wake-up call. Now that we know the Internet has been weaponized, what do we need to do before we push too far and too fast on the smart grid? We have to bake security in from the beginning."

Healy’s views are shared with other cybersecurity experts such as Gary McGraw, chief technology officer at software security consulting firm Cigital. McGraw insists that most modern control systems are so poorly designed from a security perspective that they are vulnerable to attacks devised more than fifteen years ago. According to McGraw, securing these systems requires "security engineering – building security in as we create our systems, knowing full well that they will be attacked in the future."

Building Security Intelligence into the Smart Grid
As it turns out, hardening the energy grid is not only possible, it’s highly plausible using a wide range of technologies that currently secure medical devices, industrial control equipment, point- of-sale systems and other embedded devices. These technologies range from antivirus and anti-malware protection to firewalls, advanced encryption and application blacklisting and whitelisting. Whitelisting technology is particularly useful in hardening distributed devices. It ensures that embedded devices will only accept commands from a known, recognized, authorized, and trusted application. If a piece of malware succeeds in getting through the system interfaces and into the device itself, the virus commands are ignored and the intrusion is reported.

With the help of parent company Intel, McAfee, the world’s largest dedicated security company, has applied its computer security expertise to protect embedded systems. McAfee addresses data security within the electrical grid with a viable, highly effective, low-overhead solution that secures and manages virtually any embedded system – including critical infrastructure for process control, SCADA devices and electrical transmission components. McAfee understands the need to integrate real-time security oversight into every embedded device on the system.

Building security intelligence into the smart grid is a necessary step to ensure efficient and reliable electrical service delivery. Cybersecurity analysts recommend the approach adopted by McAfee, and design engineers already possess the skills and knowledge to implement effective solutions based on McAfee technologies.



Michael Cioffi is a solutions architect at McAfee. He is responsible for management of the worldwide technical sales team within the OEM sales organization. Cioffi’s focus since 2006 has been enhancing endpoint security through the utilization of embedded security such as whitelisting. He has designed and applied the key principles of whitelisting at well-known organizations including Siemens and Phillips Medical and spanning numerous verticals such as medical, industrial automation, retail, and transportation.

All About the Fifth Play, Smart Home and Smart Energy

Thursday, November 29th, 2012

The home area network and the smart energy network need to be considered as separate and independent; one controlled by the utility and virtually invisible for the consumer; the other the consumer-controlled home network, which will help the consumer live in a smart home.

The Fifth Play is not the local production of your community theater – it is what cable companies and service providers currently are rolling out to increase their market share and to help prevent losing their valuable customers. Time Warner Intelligent Home, Verizon’s Home Monitoring & Control and Comcast’s xFinity are just some of the large operators who are now expanding their service offerings into safety, security and comfort systems, and helping consumers to become smart about their homes.

What is the Fifth Play? Service providers are currently marketing three or four different types of services for their customers – the so-called Three Plays or Four Plays.

The Four Plays are TV/movies, broadband, VoIP and cell phone service. The new Fifth Play is smart home services – i.e., energy management and monitoring; home security; health monitoring; heating, ventilation and air-conditioning control (HVAC); solar panel control; etc., all connected to the smart meter or the set-top box or the more properly named “home-control box.”

Communicating via the web through the home-control box, the smart connected home’s various systems can be controlled via smartphone or smart device apps.

By using the various flavors of the new and open standard ZigBee – ZigBee RF4CE, ZigBee Pro, ZigBee IP and/or ZigBee Smart Energy – these operators will be able to overcome the major obstacles to the market acceptance of the smart, connected Home: interoperability and the ongoing costs of installation, device and system maintenance and monitoring.

Smart Home Alone
As a central home controller with one or more ZigBee radio chips inside, the new generation set-top box will be able to talk to a wide range of devices in the home. Light switches, lamp controllers and other devices that do not require any power or can operate using a type of energy harvesting, can use ZigBee Green Power to communicate to the home-control box. By using ZigBee RF4CE, the home controller will be able to communicate interactivity with local remote controls, portable health monitoring devices, window access alarms and other low-data-rate devices. By using ZigBee Pro or ZigBee IP, the central control unit will be able to talk to and communicate with devices that require AC line power such as security systems, window opening and closing systems, door lock/unlock systems, security cameras, HVAC, etc.

As all of the these devices connect and talk to the home-control box and from there to the Internet via an Internet gateway, they can be controlled from smartphones or mobile web devices using apps or other web-hosted user interfaces. The Internet gateway can be integrated inside the home-control box or can be a separate box, either connected to a broadband cable and using the connected TV screen as a display to set up and control the device. Actually, a truly smart TV could have both the home-control box and the Internet gateway integrated inside of it.

Currently most smart-home/connected-home installations are handled by do-it-yourselfers (DIYers), hobbyists and early innovators. Some sophisticated connected home systems are also being installed and maintained by custom home electronics integrator companies. However, as the service providers increasingly roll out these systems, for a monthly fee the operator will be responsible for these chores. Similar to how cable TV and VoIP are installed in homes today, trained technicians will be dispatched and will be responsible for handling the installation, maintenance and repair. No longer will the homeowner have to figure out and troubleshoot a nest of cables and connections.

Once the smart-home/connected-home is a reality, the next step is the “really smart home.” This is true machine-to-machine intelligence and communication – when these smart-home services and devices actually exchange information and talk to each other without human intervention. For example, the smart home will know if there is anyone in the home and where in the house they are and then adjust heating or air conditioning accordingly. If everyone is in the den watching TV, why waste energy heating the bedrooms?

A security breach in the home can immediately send a text message to the homeowner and a response company. Water leaks can be immediately identified and alerted, saving money and preventing damage. Elderly people can be monitored by their children and medical staff via smartphone and alerts. Medicine consumption can be automatically monitored. Air-conditioning turns off when windows get opened. Lights are switched off in rooms where there are no people. Rooftop solar panels can be monitored and controlled to ensure optimal operating efficiency.

What about ZigBee Smart Energy?
ZigBee Smart Energy is a protocol (application profile) that was developed for the utilities to manage and control the energy consumption of the consumer in the home. There were also intentions to help the consumer better understand the energy consumption, and remotely control it, or to drive down the energy bill, etc.

But the first goal for smart energy developed by the large utilities was so they can better manage (reduce) peak load, and in particular, avoid everyone recharging using heavy energy-demand appliances at the same time. Smart energy enables the utilities to switch on and off selective equipment in the home (electric car charger, freezer, air conditioner and pool pump). Consumers who are willing to allow the utilities to take this control will receive a discount.

This is all legitimate but introduces questions about privacy, security, ownership of usage data and so forth. Smart energy extends the reach of the utilities from the power plant into the home, and not anymore to the front door of the home (the smart meter, so to say): Smart energy integrates the connected home into the smart grid. In addition, there is talk of bundling low-data home-automation services through the smart meter and effectively transforming the power utility into a service provider.

ZigBee Smart Energy version 1.x was developed to provide metering support for electric, gas, water and thermal power. ZigBee 1.x can also support load control with built-in customer-override capabilities and energy pricing that can change per time of day and level of consumer consumption. ZigBee Smart Energy also enables secure communications between the device and the utility, over-the-air updates and the ability to transmit important text messages and alerts to the homeowner. Smart Energy 1.x can also be used to connect meter integrated or standalone gateways, programmable thermostats and a wide variety of other power consuming devices such as water heaters, lighting and pool pumps.

The new Smart Energy Profile version 2.0 is currently under development and offers IPv6-based control for advanced metering infrastructure and home area networks (HANs). How and even whether this version will replace ZigBee Smart Energy version 1.x is still open for discussion and probably will vary by country or region. Version 2.0 will offer utilities and energy service providers additional options for developing advanced metering infrastructure and HANs.

ZigBee Smart Energy version 2.0 builds on version 1x by adding control of plug-in electric vehicle (PEV) charging stations, support for health area network devices and various other interactive consumer services.

There are two versions of Smart Energy 1.x (running on top of ZigBee PRO) and Smart Energy 2.0 (running on top of ZigBee IP).

What is ZigBee Home Automation and How Does It Differ from ZigBee Smart Energy?
Running over ZigBee Pro, ZigBee Home Automation is a protocol (application profile) for the consumer to manage any equipment in the home: connecting security devices, HVAC devices, consumer electronic devices, lights, etc. It clearly has the consumer in mind, and it provides opportunities to do smart things in the home, to allow people to remotely control these devices and help reduce energy consumption – for example, by turning the lights off in a room when there are no people in it.

However, this is NOT smart energy. Devices that are part of the home area network are not part of the smart energy network or vice versa, although devices can be part of both networks at the same time. But actually, the two networks need to be considered as two separate and independent networks; one network controlled by the utility and virtually invisible for the consumer. The other network is the consumer-controlled home network, which will help the consumer to live in a smart home.

Will the future continue this way? Would it not be great if the home automation network could also read information from the smart energy network? Actually, discussions are ongoing. But frankly, for security reasons the utilities would prefer it that they control and collect information from a few devices in your home that make the difference in the total energy consumption bill, and then return it to you over the Internet after you have logged in. A device in the kitchen on which you can see the energy consumption, directly read from the smart meter is underway.



Cees Links, is the founder and CEO of GreenPeak. Under his responsibility, the first wireless LANs were developed, ultimately becoming household technology integrated into PCs and notebooks. He also pioneered the development of access points, home networking routers and hotspot base-stations. He was involved in the establishment of the IEEE 802.11 standardization committee and the Wi-Fi Alliance. And he was instrumental in establishing the IEEE 802.15 standardization committee to become the basis for the ZigBee sense and control networking. GreenPeak Technologies is a fabless semiconductor company and is a leader in ZigBee silicon solutions for the smart home. For more information, please visit


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