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Posts Tagged ‘Economics’

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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Over a century ago, power engineers designed the majority of what we see in the today’s power system infrastructure, based upon significant research during the infancy of wide-scale electric power generation, transmission and distribution.  At the time, utilities built centralized electrical generation under the assumption of unidirectional power flow from the plant to the customer.  These concepts were appropriate for the demand and complexity of the power system during that time; however, with growing electrical demand of modern society, we must take a closer look at these assumptions.  Increasing fuel costs for centralized generation as well as changing social attitudes is leading to increased distributed generation from renewable resources including solar and wind.

Distributed Generation

Distributed generation has changed the way that the power system operates, allowing many small generation facilities to contribute power in order to meet current electricity demand collectively.  Consequently, utilities anticipate that distributed generation systems will introduce new problems since it violates the previous assumption of unidirectional power flow.  Distributed generation introduces the phenomenon of bidirectional power flow, resulting in adverse effects on conventional protection and voltage regulation equipment in the existing power system.

Indeed, many American states have adopted renewable portfolio standards, which require a pre-determined amount of electricity to come from renewable sources by as early as 2013 (for details, see Appendix A: Renewable Portfolio Standards).

Plug-in Electric Vehicles

With dwindling supplies of fossil fuels and increasing prices for crude oil and petroleum products, electric vehicles are steadily gaining momentum.  Although electric vehicles are not yet mainstream, they are expected to have a significant impact on the method and amount of power distribution in the near future as drivers begin switching from gasoline-fuelled vehicles to their electric equivalents en masse.  The increasing popularity of plug-in electric and hybrid-vehicles introduces issues to the power system since it effectively doubles or triples power consumption in already strained residential areas.

There are several problems faced due to the way in which the current power system is configured.  The problem lies not with the method by which the electric car is charged, but rather the number of electric cars being charged, as well as the total amount of energy required to charge each car on a daily basis (see Appendix B: PHEV Demand Increase Example).  This large increase in electrical demand will require additional generation facilities to meet the demand, and require new equipment to deal with the increased demand of consumers.  This paradigm shift will severely affect distribution utilities since the current generation of residential transformers is not rated for such high peak demands.

By implementing smart grids, local distribution utilities will be able to mitigate the problem by staggering the charging sequence of each electric vehicle.  Furthermore, utilities can explore the use of hybrid vehicles as a distributed storage technology or as a power factor controller.  Indeed, the smart grid has the potential to reduce loading on residential substations and small distribution transformers, which eliminate the necessity for expensive high-capacity equipment.

Appendix A: Renewable Portfolio Standards

State Amount Deadline Program Administrator
Arizona 15% 2025 Arizona Corporation Commission
California 20% 2010 California Energy Commission
Colorado 20% 2020 Colorado Public Utilities Commission
Conneticut 23% 2020 Department of Public Utility Control
District of Columbia 11% 2022 DC Public Service Commission
Delaware 20% 2019 Delaware Energy Office
Hawaii 20% 2020 Hawaii Strategic Industries Division
Iowa 105MW Iowa Utilities Board
Illinois 25% 2025 Illinois Department of Commerce
Massachusetts 4% 2009 Massachusetts Division of Energy Resources
Maryland 9.5% 2022 Maryland Public Service Commission
Maine 10% 2017 Maine Public Utilities Commission
Minnesota 25% 2025 Minnesota Department of commerce
Missouri 11% 2020 Missouri Public Service Commission
Montana 15% 2015 Montana Public Service Commission
New Hampshire 16% 2025 New Hampshire Office of Energy and Planning
New Jersey 22.5% 2021 New Jersey Board of Public Utilities
New Mexico 20% 2020 New Mexico Public Regulation Commission
Nevada 20% 2015 Public Utilities Commission of Nevada
New York 24% 2013 New York Public Service Commission
North Carolina 12.5% 2021 North Carolina Utilities Commission
Oregon 25% 2025 Oregon Energy Office
Pennsylvania 18% 2020 Pennsylvania Public Utility Commission
Rhode Island 15% 2020 Rhode Island Public Utilities Commission
Texas 5880 MW 2015 Public Utility Commission of Texas
Utah 20% 2025 Utah Department of Environmental Quality
Vermont 10% 2013 Vermont Department of Public Service
Virginia 12% 2022 Virginia Department of Mines, Minerals and Energy
Washington 15% 2020 Washington Secretary of State
Wisconsin 10% 2015 Public Service Commission of Wisconsin

Source: The Smart Grid: An Introduction – For Utilities.  Published by the Office of Electricity Delivery and Energy Reliability, United States Department of Energy.  Page 19.  Retrieved on March 20, 2010 from http://www.smartgrid.gov

Appendix B: PHEV Demand Increase Example

Gasoline car energy

Energy density of gasoline = 32MJ/L*50L/tank = 1600MJ/tank

Gasoline energy per month = 1600MJ/tank * 4tank/month = 6400MJ/month

Note that 50L/week = 200L/month would result in a monthly cost of: 200L/month @ $1.00/L = 200$/month

Electric car energy

1kWh = 3.6MJ

6400MJ/3.6MJ = 1778kWh/month

1778kWh/month @ $0.058/kWh = $103/month

Not only is the total electrical energy usage of the family almost tripled for every month, but charging peaks at night-time would exceed the peaks during the daytime and also prevent transformers from cooling down at night (in case they are being run above rated conditions during the daytime).

A partner and 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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Historical events provide the greatest indication of our need for a more flexible, more intelligent and more reliable power system.  In the Western world, the Tennessee Valley Authority’s bulk transmission system has achieved five nines of availability for ten years (ended 2009) [1], which corresponds to under 5.26 minutes of outage annually.  However, while the grid is generally robust to disturbances, catastrophic events like the 2003 North-eastern Blackout serve as a solemn reminder of the fragility of our system, susceptible to cascading outages originating from a handful of preventable failures in key parts of the system.  More concerning is the increasing incidence of widespread outages: in the US, 58 outages affected over 50,000 customers from 1996 to 2000 (an average of 409,854 customers per incident), compared to 41 occurrences for the same number of customers between 1991 and 1995 [2].

The essence of smart grid technology is the provision of sensors and computational intelligence to power systems, enabling monitoring and control well beyond our current capabilities.  A vital component of our smart grid future is the wherewithal to detect a precarious situation and avert crisis, either by performing preventative maintenance or by reducing the time needed to locate failing equipment.  Moreover, remotely monitoring the infrastructure provides the possibility of improvements to the operational efficiency of the power system, perhaps through better routing of electric power or by dynamically determining equipment ratings based on external conditions such as ambient temperature or weather.

In the face of changing requirements due to environmental concerns as well as external threats, it is becoming extraordinarily difficult for the utility to continue to maintain the status quo.  As the adoption of plug-in [hybrid] electric vehicles intensifies, the utility must be prepared for a corresponding increase in power consumption.  The transition to a more intelligent grid is an inevitable consequence of our ever-increasing appetite for electricity as well as our continued commitment to encouraging environmental sustainability.

The deregulation of the electric power system also presents new and unique challenges, since an unprecedented number of participants need to coordinate grid operations using more information than ever before.  If we are to maintain the level of reliability that customers have come to expect from the power system, we must be able to predict problems effectively, rather than simply react to them as an eventuality.

As the grid expands to serve growing customer demands as well as a changing society, we must proceed cautiously to ensure the system preserves its reputation of reliability.  It is incumbent upon us to carefully analyze past events and implement appropriate protection and control schemes using modern technologies.  It is clear that the power system of tomorrow will depend upon the design and preparation we conduct today.

[1] Tennessee Valley Authority. (2010, March) TVA Transmission System. [Online].   http://www.tva.gov/power/xmission.htm
[2] M. Amin, “North America’s electricity infrastructure: are we ready for more perfect storms? ,” Security and Privacy, IEEE, vol. 1, no. 5, pp. 19-25, September-October 2003.

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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