Transportation Geography and Network Science/Electric grid

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Introduction[edit]

This article seeks to explore the existing U.S electric grid as a network. The United States electric grid is a complex network comprised of distribution lines running on various voltages across three sectors of electric grid transmission. There are four categories of the U.S electric grid with each category representing different voltage categories namely;

High-power electrical transmission tower.
  • 345-499 kV
  • 500-699 kV
  • 700-799 kV
  • 1,000 kV (DC)

The U.S electric grid is nearly a century old and is the largest interconnected physical network. Its complex interactions with human beings has led it to be dubbed an ecosystem. According to the Department of Energy (DOE), the electric grid consists of more than 9,200 electric generating units with more than 1,000,000 megawatts of generating capacity. It is also connected to more than 300,000 miles of transmission lines[1].

Generation[edit]

Electric generation is the first step in supplying energy to consumers. Electric generation varies with the source of energy. According to the U.S Energy Information Administration there are six major sources of energy for electric generation. The following is a list of energy sources as arranged in the order of power it generates into the national grid[2].

  • Coal
  • Natural gas
  • Nuclear
  • Hydro
  • Other renewable sources
  • Petroleum

Transmission[edit]

The electric grid shares spatial similarities to other networks such as the internet where individual links are observed to have a physical location. The transmission and distribution of electricity is of interest from geographical, social and economic points of view. The economic aspects of the electric grid have received a lot of attention recently due to shifting attention towards the electric grid's reliability and robustness. The U.S Electric grid is independently owned and operated by various players in the industry. Aging infrastructure coupled with increased domestic consumption has complicated electricity distribution and has caused limited outages.

Generation-Transmission-Distribution on the Electric Grid.

As a result of the increased demand, there is need for a more efficient distribution and consumption network, both of which are problems addressed by a "smart grid." Upon generation, step-up transformers are used to 'step-up' voltage for transmission across the grid. This helps reduce losses on the transmission lines, however consumers need the voltage to be stepped-down to lower a voltage such as 13kV and 4kV for large energy consumers (e.g. factories) whereas small consumers (e.g. residential properties) recieve 120V or 240V. Due to aging infrastructure, the current state of the electric grid needs renovations to meet current demand[3]. Some renovations could save energy due to power losses that occur during the transmission and distribuition phases in the electric grid. Also, high demand during peak hours has led to a congested state of service delivery. This is analogous to transportation networks when traffic flow exceeding roadway capacity. In most congested transportation networks, "Stop and Go" conditions exist where free flow of traffic is limited. Without a reliable system, sustainable energy production practices and reasonably priced energy, there can be no sustainable long term growth[4].

Electric grid failure[edit]

Brownout vs Blackout[edit]

Interruption in service on the electric grid may occur for a myriad of reasons. Whether it is a single catastrophic event that was not foreseen, or a planned event by utility companies such as for maintenance, or poor planning (e.g. simply designing for average demand), utilities will face problems throughout their planned lifetime. To operate optimally and minimize the number of blackouts, operators at times are required to reduce the amount of voltage provided to certain areas. By reducing the voltage between 10 to 25% provided to a consumer, most lighting and heating equipment can still function. However, the general life of electrical equipment is shortened as a result of operating at lower voltages than those they are designed for. This process of reducing voltage in certain service areas during peak hours is known as brownout[5]. While not catastrophic to the electrical network, as explained earlier, brownouts do have a cost associated with it in terms of damages accrued. A blackout occurs as a result of total system failure mainly due to catastrophic equipment malfunctioning or severe weather. A rolling blackout refers to controlled/planned service interruptions that last for fixed amount of time. A rolling blackout is usually initiated by utility companies.

Laying of utilities[edit]

An example of a Minimum Spanning Tree. Weights on the links may represent cost or time to lay each link

When laying utilities, the least cost solution is the one chosen. Whether the cost is in terms of time it takes to lay out utilities or the monetary cost to putting infrastructure in place along the network, a system must be in place to analyze the cost-benefit ratio. For example, if a new power line for a particular area isn't needed in the immediate future, where there isn't a risk for brownouts/blackouts, the utility company may choose to go for the lowest monetary cost. A more systematic approach to analyze the costs associated with laying utilities is using the concept of the Minimum Spanning Tree (MST) problem. In a network such as the electrical grid, the MST problem involves using links to connect all nodes on the network. Ideally an arbitrary location is determined while selected which nodes to connect first. However, within an existing electrical network, the first node to be connected on a MST can be an existing node on the grid. Other steps include identifying unconnected node that is closest to the already connected nodes. Upon completing this process, add the new node to the set of connected nodes. The process is repeated until all nodes are connected. The result is having all nodes connected with the least cost[6]. For our graph the least cost to connect all the nodes is 38. On an electrical grid this could represent man hours required for complete connection to occur or a scaled cost for connections.

Peak Hour Demand[edit]

Meeting peak hour demand remains a challenge for utility companies. Peaker plants are often old power plants used to meet peak hour demand and due to their age and function, release higher concentrations of pollutants [7]. Not only do peaker plants harm the environment more than plants that run continuously, but peak demand can vary considerably, causing brownouts and blackouts to still occur.

In the United States, the annual total electric industry revenues are estimated at $326 billion. Yet, interruptions to the utility service are predicted to cost the industry $80 billion. These loses represent approximately 24.5 per cent of the industry revenues [8]. Unfortunately, the costs are then transfer to the consumer with inflated energy prices. With a smart grid in place, not only would network reliability increase thereby reducing the costs to the industry, but these saving would be passed on to the consumer. Changes in the current electrical grid will have to be gradual considering the vast resources that will be required to upgrade to a smart grid.

Smart Grid[edit]

According to Illinois SMART GRID Initiative, a smart grid refers to the modernization of the electric system through the integration of new information-age technologies to allow for new uses of the electric grid. This applies both in operations of the grid and in consumer applications[9]. Currently consumers receive their usage reports a couple of days after consuming electricity. With a smart grid in place, consumers are able to monitor real-time usage of electricity and hence increasing awareness of their consumption. With increased awareness in consumption of electricity, it can be argued that consumers can manage use of electricity through use of ‘smart appliances’ that consume less power and also can be programmed to run during off peak periods. By running appliances during off-peak hours, it decreases the necessity for peak plants and uses energy being produced during those hours that is going to waste. Running appliances that consume more power during off peak periods can be further encouraged if power consumption is to be charged according to time of day. A similar analogy can be found in congestion pricing in transportation networks, where road users get to pay for ‘congestion’ caused as a result of their travel. The U.S Department of Energy (DOE) views the smart grid as an important tool to ensure the electric grid is reliable and maintain affordability while reinforcing global competitiveness[10]. On the other hand the European Wind Energy Association (EWEA) views clean sources of energy as the next level of economic competitiveness[11].

References[edit]

  1. Grid 2030, (2003): United States Department of Energy http://www.ferc.gov/eventcalendar/files/20050608125055-grid-2030.pdf
  2. US Energy Information Administration (USEIA) http://www.eia.doe.gov/cneaf/electricity/epm/table1_1.html
  3. Grid 2030, (2003): United States Department of Energy http://www.ferc.gov/eventcalendar/files/20050608125055-grid-2030.pdf
  4. European wind Energy http://www.ewea.org/index.php?id=885
  5. Energy dictionary http://www.energyvortex.com/energydictionary/blackout__brownout__brown_power__rolling_blackout.html
  6. Anderson et al (2000). An introduction to Management Science: Quantitative approaches to decision making. South Western College publishing
  7. Sustainable Communities Attainable Results (CNT) http://www.cnt.org/news/media/isgi-summary-of-benefits-and-issues-6-08.pdf
  8. Sustainable Communities Attainable Results (CNT) http://www.cnt.org/news/media/isgi-summary-of-benefits-and-issues-6-08.pdf
  9. Sustainable Communities Attainable Results (CNT) http://www.cnt.org/news/media/isgi-summary-of-benefits-and-issues-6-08.pdf
  10. US Energy Information Administration (USEIA) http://www.eia.doe.gov/cneaf/electricity/epm/table1_1.html
  11. European wind Energy http://www.ewea.org/index.php?id=885