Posts Tagged ‘Demand Response’

This is the second part of a two-part series (the first part provides an introduction) discussing the role of smart grids in electric power distribution systems. We will explore some past and current installations of smart grids, discussing their motivating factors, planning, implementation and results. Essentially, this article is a discussion where we learn both from our successes and our failures in the power industry, to inform our future decisions.


Smart meters are the some of the earliest intelligent devices installed in distribution networks and critical to enabling the smart grid of the future.  One of the biggest issues that every smart grid initiative encounters when attempting to incorporate the technology into their system is the public perception that smart meters violate the right to privacy.  Consequently, if the utility does not handle the situation tactfully, the reduction in the rate of consumer participation can diminish the practical gain from smart grid installations.

As mentioned previously, smart meters are capable of communicating wirelessly with the utility, receiving consumer usage data with the potential to control OpenHAN-compliant appliances remotely.  In the face of intelligent adversaries with increasingly powerful computing systems, it is important to provide a significant degree of security and future proofing.

In 2005, the Netherlands electricity distribution company Oxxio began widespread introduction of a smart meter for both gas and electricity.  When the European parliament issued a directive to member states to begin installation of smart metering equipment, the public was neither educated nor reassured about the new technology.  Economy minister Maria van der Hoeven decided to push for compulsory installation of smart meters and punishing refusal to install them with a fine of up to €17,000 or six months in prison.  Amidst privacy concerns, consumer protection organizations fought rigorously against the law and won; smart meters can now only be installed on a voluntary basis as requested by consumers [1].

We must learn from this stark lesson and avoid a similar outcome in future installations by ensuring adequate education for the public in order to assuage their fears and uncertainty, ultimately to ensure vital consumer participation.


While the amount and timing of data provided by smart meters from the field does not pose serious privacy risks from internal misuse, there many security concerns surrounding external adversaries.  In particular, there is the potential for malicious users to modify their usage data in order to influence consumer billing, either by reducing their own consumption or as a financial attack against someone else.  Since the utilities would be making design decisions based on the recorded trends, outside manipulation of the data could cause catastrophic effects to equipment if not upgraded when needed due to underrepresentation of actual power consumption.

In Ontario, the current smart grid deployment initiative involves the government, Hydro One’s distribution business as well as other local utilities.  It demonstrates the need for very close cooperation between the utilities and their regulatory bodies, especially since much of their current success can be attributed to their work communicating with users.  Learning from errors in past smart grid implementations, the Ontario government established several websites acting as a central point of origin describing smart meters, their function and their overall objectives.

For support for the technical aspects of the deployment, Hydro One has partnered with Trilliant Technologies, which is a company that “provides intelligent network solutions and software to utilities for advanced metering, and Smart Grid management” [2].  Trilliant’s expertise and extensive smart metering technology portfolio reduces Hydro One’s risk and guarantees a higher degree of flexibility than with other vendors.  The smart meters operate in the unlicensed 2.4GHz radio frequency commonly used for ZigBee, Wireless LAN (IEEE 802.11) and Bluetooth, with Trilliant providing both the metering and the related communication infrastructure.  Trilliant also designed the 1.3 million smart meters currently being deployed by Hydro One’s distribution arm.

Thus far, current efforts to ensure network security and likewise to assure and encourage consumer participation in Ontario have been a success, and there are many other similar efforts taking place in other countries at this time.  Because smart meters involve using an extremely complex device to do measurement for billing purposes, it must be completely free of defects, especially in light of Canadian requirements like the Weights & Measures Act.


As climate change raises the average global temperature, Australia’s climate is one of the hardest hit: becoming hotter and drier than ever before.  Australia continues to consume a considerable amount of electricity; in fact, 261.8 TWh of electricity was produced in Australia during 2006, and that figure is projected to reach 413 TWh by 2030 [3].

With electricity demand continuing to rise, the utility may soon need to consider construction of new generation, transmission and distribution infrastructure.  However, maintenance of an aging system is itself extremely costly, and simultaneously investing in new infrastructure is simply not feasible.  As a result, Australia decided to implement dynamic rating of equipment in both their transmission and distribution systems, allowing them to better utilize existing infrastructure.  For an example comparing static equipment ratings with those dynamically generated by Australia’s control system, see Dynamic Equipment Rating.

[1] Wilmer Heck. (2009, April) Smart energy meter will not be compulsory. [Online].   http://www.nrc.nl/international/article2207260.ece/Smart_energy_meter_will_not_be_compulsory
[2] Trilliant, Inc. (2010, March) Trilliant, Inc. – Communications for the Smart Grid. [Online].   http://www.trilliantinc.com/
[3] Cagil Ozansoy, “Turning Down the Heat,” Australia’s Fast-Growing Electricity Sector Ramps Up Its Global Warming Initiatives, vol. 8, no. 1, pp. 29-36, January-February 2010.

I originally wrote this article for a report submitted to ECE4439: Conventional, Renewable and Nuclear Energy, taught by Professor Amirnaser Yazdani at the University of Western Ontario.

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Over the coming months, Canadian utilities will overhaul installations of electricity consumption meters at residential and commercial premises in order to accommodate the upcoming smart grid.  Until very recently, the most common method of energy metering was by means of an analog electromechanical device that functions based on eddy currents.  While this meter has served the utility well, it is only capable of recording the cumulative amount of power consumed and must be manually recorded from time to time.  However, it is not capable of recording how much has been used corresponding to a specific time of the day.

A smart meter is a two-way digital device that accurately records and wirelessly communicates with the utility company at scheduled intervals (usually hourly), providing information about the amount of power consumed in a given time period [1].  If this metering technology is implemented across an entire city, utilities would be able to observe usage trends and introduce time-of-use pricing in order to reduce demand during periods of peak energy consumption.  By increasing the cost of electricity during times of day where demand is at its highest, consumers are encouraged to delay non-critical tasks until there is a reduction in loading on the system.  In this way, the loading on the overall power system would remain more consistent throughout the day, increasing utilization of existing capacity and potentially reducing voltage fluctuations in the distribution system.  Less variation in power flow will yield better stability of our system and more efficient use of our assets.  Ultimately, it will raise overall consumer awareness of the need to conserve energy.

In addition, a more futuristic goal of smart metering in residential areas is to incorporate the concept of smart appliances.  Using the HAN protocol, the smart meter will be able to control compatible devices and coordinate with local consumer loads to reduce strain on the distribution system.  Smart devices would be able to collaborate with other neighbourhood meters in order to decide when to allow or postpone the operation of non-critical in-home appliances.  In essence, the main goal of smart appliances is to further extend the function of the smart meter, allowing better organization and load management than ever before [2].

The installation of smart meters in homes and businesses in Ontario may already be evident.  The Ontario government, in collaboration with Hydro One and other local distribution companies has already begun the long-term transition to a smarter grid system by mandating the installation of a smart meter in every home in Ontario by the end of 2010 [3].  While the meters are not yet transmitting telemetry, the installation of the smart metering infrastructure will pave the way to a world of future possibilities.

Another significant way that smart grids will benefit residential consumers is providing a means to incorporate growing distributed generation systems.  For example, home customers will be able to integrate solar panels or wind turbines on their roof and sell electricity back to the grid at a predetermined rate set by the government; in Canada, this is known as Feed-in-Tariff rate for alternative and renewable energy sources.  Although consumers are already permitted to connect distributed generation systems, there continues to be very limited deployment of these generation sources in residential areas, particularly since it poses significant problems to the voltage system including the introduction of harmonics and voltage fluctuations.

Another potential issue with integration of distributed generation is that most renewable energy sources depend on natural phenomena and are therefore incapable of consistently and predictably generating power throughout the day.  The utility needs to design compensation for the resulting voltage fluctuations in order to prevent the system parameters from exceeding the safe operating region.  By measuring and recording information about distributed generation installations, the utility will be able to install appropriate compensation systems to protect the system as a whole.

Over the next several decades, demand for electricity is projected to rise by at least 30% [4].  It is becoming less and less practical to construct new large-scale generation plants, so in order to meet this demand, we must turn to renewable energy, making it is imperative that we ensure the system is capable of accepting a significant volume of energy from distributed generation.  The solution of widespread renewable energy in homes will satisfy our increasing thirst for electricity while simultaneously offering a significant advancement in our goal to reduce our overall carbon footprint.

In the next installment, we will discuss some real-world implementations of smart meters in distribution systems, exploring key issues that must be considered when deploying these technologies.

[1] D Y Raghavendra Nagesh, J V Vamshi Krishna, and S S Tulasiram, “A Real-Time Architecture for Smart Energy Management,” in Innovative Smart Grid Technologies, Washington, D.C., January 2010, pp. 1-4.
[2] Brian Seal. (2005, May) Demand Responsive Appliance Interface from the EPRI Demand Responsive Appliance Interface Project. [Online].   http://osgug.ucaiug.org/sgsystems/openhan/HAN%20Use%20Cases/OpenHAN%202.0%20use%20cases/Appliance%20Interface%20Connector%20-%20Contribution%20to%20OpenHAN.doc
[3] Ali Vojdani, “Smart Integration,” Power and Energy Magazine, vol. 6, no. 6, pp. 71-79, November-December 2008.
[4] IEEE Emerging Technologies. (2009, January) A Smart Grid for Intelligent Energy Use. [Online].   http://www.youtube.com/watch?v=YrcqA_cqRD8

I originally wrote this article for a report submitted to ECE4439: Conventional, Renewable and Nuclear Energy, taught by Professor Amirnaser Yazdani at the University of Western Ontario.

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The ZigBee protocol enables communication using multiple network topologies, including star, tree and mesh [1].  It is particularly challenging to ensure reliability of the communication channel for smart meter designs, especially with the use of wireless-based backhaul channels and ZigBee is particularly suited to this application with its mesh network topology.  In case a meter is out of range of a central tower or otherwise obstructed by buildings or other objects, ZigBee-based meters enable communication between meters and relaying of information back to the data collection point [2].  Furthermore, since ZigBee devices utilize the unlicensed 2.4GHz spectrum, they have a very low cost of deployment and allow seamless integration and networking of many ZigBee devices.  Although they have many benefits, ZigBee devices are designed primarily for short-range communication and low device power requirements [3], requiring a separate wireless protocol for long-range transmission.  ZigBee is a key technology enabling the OpenHAN networking standard discussed later in this paper.

OpenADR (Automated Demand Response)

Because electricity is charged at a constant price in the current power system, regardless of time of use, consumers therefore have little incentive to put forth effort to change their usage patterns.  Introducing smart grids will allow for dynamic billing based on market pricing at the time, and thus give more incentive to customers to plan their energy usage [4].  With the proposed automated demand response, individual smart meters will have the capability of monitoring system wide conditions, determining when the system is stressed and appropriately allocate power to different appliances.  Automated demand response will aim for reducing high loading during peak times, in an attempt to remove excess stress from the power system [5].

Open Automated Demand Response is a standard currently under development [6], which aims to ensure interoperability between various smart meter infrastructure devices.  It will provide a way for users program appliances to operate according to current electricity prices, for example to do laundry when power is cheapest.

OpenHAN (Home Area Network)

Open Home Area Network is a proposed standard to interface with the smart meter in residences with appliances in the home.  OpenHAN can allow for utility control of the appliance, customer coordination and timing of appliance activation, and operational states of appliances based on set-points such as price.  Upon completion and implementation of this standard, residents will be capable of having appliances automatically run during times when electricity is cheapest, and utilities will be able to cease operation of appliances during peak loading times.  OpenHAN is the fundamental idea behind automated demand response, where there exists a link between the smart meter of the customer and the customer’s appliance [7].

Worldwide Interoperability for Microwave Access (WiMAX)

WiMAX is an industrial wireless interoperability standard related to the existing technology known as the Global System for Mobile Communications (GSM) [8].  It is typically used for land-based wireless Internet service providers, particularly those serving rural communities; however, it is finding applications within power systems as a backhaul for smart meter telemetry data [9].

Broadband over Power Lines

Several different startup companies have explored the use of Broadband over Power Lines (BPL) as an Internet service delivery or as a backhaul for telemetry from smart meters [10].  While it is no longer a serious contender for delivering Internet access to remote communities, the technology still has its niche applications, particularly within the realm of power systems.  Some smart meter vendors continue to sell smart metering equipment that transmits telemetry over power lines [11] rather than using its own radio frequency, which requires the purchase of costly spectrum.

Furthermore, using BPL couplers traditionally used for sending and receiving data across power lines can be used to listen for types of noise characteristic of certain types of equipment failures; for example, a cracked insulator beginning to fail will induce a specific signature pattern that can be detected using BPL couplers [12].

[1] Peng Ran, Mao-heng Sun, and You-min Zou, “ZigBee ROuting Selection Strategy Based on Data Services and Energy-Balanced ZigBee Routing,” in IEEE Asia-Pacific Conference on Services Computing, Xi’an, China, 2006, pp. 400-404.
[2] Hoi Yan Tung, Kim Fung Tsang, and Ka Lun Lam, “ZigBee Sensor Network for Advanced Metering Infrastructure,” in Power Electronics and Drive Systems, Taipei, Taiwan, 2009, pp. 95-96.
[3] ZigBee Alliance Inc. (2007, October) ZigBee Specification. [Online]. http://zigbee.org/ZigBeeSpecificationDownloadRequest/tabid/311/Default.aspx
[4] David Andrew, “National Grid’s use of Emergency Diesel Standby Generator’s in Dealing with Grid Intermittency and Variability,” in Open University Conference on Intermittency, Milton Keynes, UK, 2006.
[5] Dan Yang and Yanni Chen, “Demand Response and Market Performance in Power Economics,” in Power and Energy Society General Meeting, Calgary, AB, 2009, pp. 1-6.
[6] Ivin Rhyne et al., “Open Automated Demand Response Communications Specification,” Public Interest Energy Research Program (PIER), California Energy Commission, Berkeley, CA, PIER Final Project Report 2009.
[7] UtilityAMI OpenHAN Task Force. (2007, December) Requirements Working Group Specification Briefing. [Online].  http://osgug.ucaiug.org/sgsystems/openhan/HAN%20Requirements/OpenHAN%20Specification%20Dec.ppt
[8] Zheng Ruiming, Zhang Xin, Pan Qun, Yang Dacheng, and Li Xi, “Research on coexistence of WiMAX and WCDMA systems,” in IEEE 19th Internetional Symposium on Personal, Indoor and Mobile Radio Communications, Cannes, France, 2008, pp. 1-6.
[9] G.N. Srinivasa Prasanna et al., “Data communication over the smart grid,” in IEEE International Symposium on Power Line Communications and Its Applications, Dresden, Germany, 2009, pp. 273-279.
[10] X. Qiu, “Powerful talk,” IET Power Engineer, vol. 21, no. 1, pp. 38-43, February-March 2007.
[11] Echelon Corporation. (2010, March) Energy Management Control Networks. [Online].   http://www.echelon.com/products/energyproducts.htm
[12] Larry Silverman, “BPL shouldn’t mimic DSL/cable models,” BPL Today, pp. 1-7, July 2005.

One of my partners wrote the majority of this article for a report submitted to ECE4439: Conventional, Renewable and Nuclear Energy, taught by Professor Amirnaser Yazdani at the University of Western Ontario. It is included here for completeness with the rest of the articles. I edited the article and wrote the sections entitled: Worldwide Interoperability for Microwave Access (WiMAX) and Broadband over Power Lines.

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