Tuesday, February 12, 2013

Energy Supply

Explore the Mind Map to learn about the sustainable use of ICT in Energy Supply!


Today’s electricity grids are characterized by bad energy efficiency because of loss in transmission and the need for overcapacity to meet variations in energy demand. Another restrictive feature of traditional electricity grids is the single way of communication and energy transfer. To overcome these restrictions and to make the distribution of energy more efficient, innovative approaches are required. ICT plays a major role in improving today’s electrical grids in order to meet the requirements of a low carbon society.

Renewable Sources of Energy

ICT systems allow more efficient operating and maintenance of power systems using renewable sources of energy like water, wind and sunlight. For example there are approaches in development to monitor wind turbines using a model-based method of neural networks [1]. Therefore the temperature of the generator bearings is measured to predict failures. This could avoid wind turbines standing still and help increasing the productivity of such systems.

Information technology could also improve the management of distributed renewable energy sources like home photovoltaic panels. There are approaches in research that add processors to control arrays of photovoltaic units. This enables remote management of these energy generating systems and allows creating central management platforms and the establishment of integrated networks [2]. A different approach in research shows that Fuzzy models can be used to control photovoltaic power systems including the required conversion to obtain this source of energy [3].

Another example for improved management of renewable energy generators enabled by ICT is the approach to predict the amounts of energy generated by wind turbines. Therefore short-term forecasts of wind speed and direction of several observation points have to be considered and used to calculate the resulting power output of the wind turbines located in these areas [4]. As wind energy inheres large variability such predictions would be very useful to manage the compliance of energy demands in future electricity grids. Increasing efficiency of wind turbines implies techniques to estimate wind speeds. In connection to this, approaches based on self-organizing neural networks can be found in scientific literature [5].

References

[1] J. Xiang, S. Watson, and Y. Liu. Smart monitoring of wind turbines using neural networks. In Robert J. Howlett, Lakhmi C. Jain, and Shaun H. Lee, editors, Sustainability in Energy and Buildings, pages 1–8. Springer Berlin Heidelberg, 2009.

[2] C. Mallett. Network-enabled intelligent photovoltaic arrays. In  Robert J. Howlett, Lakhmi C. Jain, and Shaun H. Lee, editors, Sustainability in Energy and Buildings, pages 39–47. Springer Berlin Heidelberg, 2009.

[3] A. Hajjaji, M. BenAmmar, J. Bosche, M. Chaabene, and A. Rabhi. Integral fuzzy control for photovoltaic power systems. In Robert J. Howlett, Lakhmi C. Jain, and Shaun H. Lee, editors, Sustainability in Energy and Buildings, pages 219–228. Springer Berlin Heidelberg, 2009.

[4] M. Khalid and A. V. Savkin. Development of short-term prediction system for wind power generation based on multiple observation points.  In Robert J. Howlett, Lakhmi C. Jain, and Shaun H. Lee, editors, Sustainability in Energy and Buildings, pages 89–98. Springer Berlin Heidelberg, 2009.

[5] G. Cirrincione and A. Marvuglia. A novel self-organizing neural technique for wind speed mapping. In Robert J. Howlett, Lakhmi C. Jain, and Shaun H. Lee, editors, Sustainability in Energy and Buildings, pages 209–217. Springer Berlin Heidelberg, 2009.

Smart Grids

One approach to modernize and improve the efficiency of electrical grids is marked by the term Smart Grid, which can be defined as “a set of software and hardware tools that enable generators to route power more efficiently” [1]. In more detail, the efficiency gains can be achieved by additional functionalities of electrical grids, enabling two-way communication between power providers and customers and sensing along transmissions lines. Therefore a Smart Grid is characterized by a high grade of automation and the use of digital technology, that enables the grid to respond to changes in power demand [2].

Traditional electrical grids grew over decades to it’s current size and can be constituted as patchwork, which is the reason for inefficiencies. The electrical grid of the United States of America experienced a growth in peak energy demand since 1982 and was expanded to keep up with the increasing transmission [3]. At the time the grid was designed it was not necessary to consider environmental aspects or energy efficiency. To meet today’s requirements a modernization of the electrical grids of industrial nations all over the world is needed. Therefore ICT technology can be integrated throughout the grid to optimize them. From an environmental view an increase of efficiency of electric grids would be big step towards low carbon emission goals: Only a 5 percent efficiency gain of the electrical grid of the USA would equate the greenhouse gas emissions of 53 million cars. In total the USA produce 25 percent of global greenhouse gas emissions, while half of U.S. power production is still based on fossil fuels [3]. These numbers illustrate the enormous savings potential of optimizing power generation and transmission processes.

Beside the U.S. government the European Union communicates the important role of Smart Grids for future energy management and fulfillment of Europe’s energy and climate goals in compliance with the EU2020 agenda. The Smart Grid will give energy consumers strong incentives to save energy, because of the distribution of smart meters and information and communication systems: “It opens up unprecedented possibilities for consumers to directly control and manage their individual consumption patterns, providing, in turn, strong incentives for efficient energy use if combined with time-dependent electricity prices” [4]. According to the communication of the European Comission there are projects which show that households which have been equipped with smart meters reduced their energy consumption by as much as 10 percent. The Smart Grid is considered as “the backbone of the future decarbonised power system” [4], as it enables the integration of renewable energy sources. A study by the European Bio Intelligence Service detected a possible reduction in carbon emissions by 9 percent by the year 2020 due to Smart Grids [5].

 Figure 1 illustrates the features of a Smart Grid. Electricity is increasingly generated from renewable sources and distributed by the Smart Grid to private and business customers. All over the grid intelligent ICT systems are implemented, enabling faster failure detection and increasing reliability. There are control centers for management and operation, which are analyzing information on energy consumption from the grid in real-time to forecast demand peaks. Customers are provided with smart meters and Intelligent Building Systems to monitor and control their energy consumption. The power generators of customers’ homes are connected to the Smart Grid and can deliver power to the community that is not needed locally. The Smart Grid also provides plug-in functionality for electric cars to reload their batteries [6].


Figure 1: Smart Grid [6]

The advantages of a Smart Grid, arising from the use of ICT to enable bidirectional energy and information exchange, support the development towards a more sustainable energy management [2]:
  • Reduced losses in transmission of electricity and therefore a higher level of energy efficiency. 
  • A higher grade of automation and more efficient technical equipment will decrease operation, management and maintenance costs, resulting in lower power costs. 
  • Quicker electric recovery in case of outages, because of automatic rerouting by the Smart Grid. Failures will occur less often and can be detected and isolated faster, avoiding large-scale blackouts. • Reduced power outages imply improved security. 
  • Integration of large-scale renewable energy power plants. 
  • Smart Grids also enable the integration of distributed small-scale sources of renewable energy, like customer-owned power generators (e.g. photovoltaics). 
  • Increased consumer participation and control, due to real-time information on power consumption and cost control functionality (smart meters). 

Figure 2: Grid connected solar home system [7]

In contrast to traditional centralized energy generation by large-scale power plants, using fossil or nuclear sources, the trend in renewable energy production is towards decentralized small-scale energy generators. This brings new requirements for electricity grids, in order to integrate various types of generators with partly wider spatial distribution. Energy generators using sun or wind power can be installed as part of buildings, to cover part of the local energy demand and to supply energy to the grid at times when some part of the produced energy is not needed locally. Figure 2 shows a schema of a home photovoltaic (PV) system that is connected to the electrical grid. The solar PV system generates electricity that is used to power building appliances and also can be stored in backup batteries to partly balance supply shortcomings due to the dependence of PV systems on weather conditions. If needed additional power can be purchased from the grid, while it is also possible to feed electricity back to the grid.

The approach of small-scale distributed power generation allows parts of the electricity network to operate in separation from the main grid, assuming that enough power is generated to cover the local energy demand. Such areas are called Micro Grids, which are based on the principle that energy customers can supply their own demand by distributed small-scale power generators, as well as serve exceeding power to their local neighbors [8]. Micro Grids enable the development of more sustainable energy generation and management, and could create stronger incentives for the distribution of small-scale power generators to gain a certain level of independence from the main electricity grid and decrease energy costs. The financial effort of investing in micro generation systems is much lower in comparison to large scale power plants, which could be an important aspect for public participation. Another big environmental advantage of Micro Grids is the reduction of energy losses and thereby greenhouse gas emissions. Today’s centralized power generation and distribution suffer from losses of 7 to 10 percent of total energy generation due to long distances of transmission [8].

Concepts based on the idea of buildings as small-scale power plants require Smart Grids to integrate them into large-scale electricity grids [2]. Therefore applications are needed to coordinate different energy sources and adjust energy demand and supply to gain maximum efficiency from generators. Such systems for modeling, analysis and control of multiple energy sources are a current research topic [9]. The main feature of a control system for multiple energy sources is the adjustment of energy production, energy consumption and energy storage (cf. figure 3). By designing a system for this purpose following features and circumstances have to be considered: [9]
  • Energy production by wind and solar generators is stochastic since intensity of wind and sunlight varies in relation to the weather situation. Therefore the system needs an applicable model to assume and predict the produced amount of energy. 
  • To optimize the alignment of energy demand and supply, also an assumption of energy demand is needed. 
  • In consideration of these requirements the system has to achieve a optimum balance of energy production, consumption and storage. 

Figure 3: Control system for multiple energy sources [9]

References

[1] The Climate Group. Smart 2020: Enabling the low carbon economy in the information age. Technical report, The Climate Group on behalf of the Global e-Sustainability Initiative (GeSI), 2008.

[2] U.S. Department of Energy. What is the smart grid? http://www.smartgrid.gov/the_smart_grid. Accessed: 2013-02-12.

[3] U.S. Department of Energy. The Smart Grid: An Introduction. http://energy.gov/sites/prod/files/oeprod/DocumentsandMedia/DOE_SG_Book_Single_Pages%281%29.pdf, 2008. Accessed: 2013-02-12.

[4] European Commission. Smart grids: from innovation to deployment, April 2011.

[5] Bio Intelligence Service. Impacts of information and communication technologies on energy efficiency, final  report. ftp://ftp.cordis.europa.eu/pub/fp7/ict/docs/sustainable-growth/ict4ee-final-report_en.pdf, September 2008. Accessed: 2013-02-12.

[6] Consolidated Edison, Inc. Smart Grid Initiative. http://www.coned.com/publicissues/smartgrid.asp. Accessed: 2012-01-06.

[7] B. Metz. Controlling climate change. Cambridge University Press, 2010.

[8] R. M. Kamel. Carbon emissions reduction and power losses saving besides voltage profiles improvement using micro grids. Low Carbon Economy, 01(01):1–7, 2010.

[9] A. Naamane and N. K. M’Sirdi. Macsyme: Modelling, analysis and control for systems with multiple energy sources. In Robert J. Howlett, Lakhmi C. Jain, and Shaun H. Lee, editors, Sustainability in Energy and Buildings, pages 229–238. Springer Berlin Heidelberg, 2009.

Transport

Explore the Mind Map to learn about the sustainable use of ICT in Transport!


Due to economic globalization the transport sector is growing, together with its global share of greenhouse gas emissions. The development of big international corporations, the outsourcing of production to low-wage labor markets and the resulting long-distance transportation of goods, services and passengers led to the enlargement of the global footprint of the transport sector, which is now responsible for about 14 percent of global emissions [1].

The environmental impact of this sector arises from industrial transport, as well as public and private transport of passengers. In Europe, the biggest part of private transport is made up by leisure trips (40-50%), followed by commuting to and from work (15-25%) and business travel (10-25%) [2]. For every area of transport ICT systems can provide environmental, economic and social benefits, that can support the development of a sustainable economy and society. Emissions savings in the transport sector can be achieved by four basic approaches [3,4]:
  • Reduce demand: Reducing the need for transport, for example by telecommuting, or the optimization of logistics and traffic. 
  • Change means of transportation: Use of more efficient vehicles, in relation to fuel and space efficiency. 
  • Improve efficiency: Reducing the energy demand of transport facilities, like vehicles, airplanes or ships and improve the efficiency of transportation systems. 
  • Change type of fuel: Development of alternative engines, that emit less CO2. 

References

[1] The Climate Group. Smart 2020: Enabling the low carbon economy in the information age. Technical report, The Climate Group on behalf of the Global e-Sustainability Initiative (GeSI), 2008.

[2] Bio Intelligence Service. Impacts of information and communication technologies on energy efficiency, final  report. ftp://ftp.cordis.europa.eu/pub/fp7/ict/docs/sustainable-growth/ict4ee-final-report_en.pdf, September 2008. Accessed: 2013-02-12.

[3] B. Metz. Controlling climate change. Cambridge University Press, 2010.

[4] G. Philipson. Ict’s role in the low carbon economy. Technical report, Australian Information Industry Association (AIIA), 2010.

Smart Logistics

A large proportion of logistics is constituted by the transportation of goods. Logistics can be defined as the “planning, execution, and control of the procurement, movement, and stationing of personnel, material, and other resources” [1]. In other words, the challenge of logistics is the management of travel routes for transportation of goods and passengers, and of storage facilities. An optimization of logistics leads to savings in travel routes, travel times and travel costs and therefore also savings in CO2 emissions. Logistics globally account for a significant amount of greenhouse gas emissions. As an example, in Australia the logistics and transport industry causes about 15 percent of total emissions annually, which can be numbered as 79 Mt of CO2e [2].

ICT systems can be used to improve transport routes and load planning, for example to minimize empty trucks [3]. This can be referred to as smart logistics, that “comprise a range of software and hardware tools that monitor, optimize and manage operations, which helps reduce the storage needed for inventory, fuel consumption, kilometers driven and frequency of vehicles traveling empty or partially loaded” [4]. By tapping the full potential of smart logistics 1.52 GtCO2 emissions could be saved by 2020 [4]. The set of features that ICT provides to optimize logistics and transport contains several innovations to the sector [2]:
  • Logistics management systems: A general term for systems used to manage, control and optimize logistics, including several of the following functions to manage transportation, information, inventory and warehouses. 
  • Automatic ordering systems: Orders and re-orders of resources and goods are automatically executed relating to demand, in order to optimize stocks and warehouse sizes. These systems avoid non-essential transport routes and reduce the need for oversized warehouses, which leads to lower greenhouse gas emissions caused by warehouse construction. 
  • Mobile and wireless communication: These communication systems include voice communication of personnel, as well as the wireless exchange of field data (e.g. barcode scanning). The integration of mobile devices into the communication network allows real-time information exchange and therefore more flexibility. This brings advantages for route and load planning and the possibility to react to failures and delivery delays [5]. 
  • Fuel and emissions control systems: ICT provides systems to collect, store and process data about fuel consumption of fleets of vehicles. These systems also support fuel cost analysis. Beside fuel consumption, the carbon emissions arising from fuel powered vehicles can be measured. This ensures the compliance to emission standards and enables the planning of service times of vehicles. 
  • Vehicle tracking: The tracking of vehicles on transport routes is achieved by mobile and wireless networks and eases the centralized management of fleets. The vehicles of a fleet can be located due to positioning standards like GPS, which allows a more efficient usage of fleet resources. 
  • Navigation systems: Mapping software in combination with positioning technology provides assistance for drivers of vehicles. Navigation systems diminish failures in travel routes and therefore decrease wasted time and fuel, as well as unnecessary emissions. 
  • Real-time traffic monitoring and feedback systems: Information about the traffic situation in real-time enables re-planning of travel routes in respect of traffic flow. These systems help preventing delivery delays and inefficiencies due to traffic volume or construction work on traffic infrastructure. 
  • Route planning: Systems that allow the creation of complex route plans for fleets, ensuring maximum efficiency of the combination of transport routes. 
  • Freight matching and optimization: Freight matching is an approach to reduce travel ways of empty trucks [6]. As an example, there are several websites on the Internet where companies can post their freight that needs to be shipped to a specified location. Companies of the logistics sector can look up these information and offer the free load capacities of their vehicles. Many freight matching websites work in reverse too, meaning that logistics companies can inform about free capacities. In each case it is a win-win situation, providing a transportation service to companies with freight to ship and optimizing the loads of trucks, which also has a positive impact on the environment. 
  • Ambient intelligence: This term generally specifies the effort of computing to make the ambiance of people more supporting and functional by integrating electronic equipment into everyday life [7]. In today’s road traffic ambient intelligence is represented by sensor networks used for Intelligent Transportation Systems (cf. section ITS), real-time traffic monitoring, navigation systems and wireless communication. In logistics all these technologies act as supporting systems and enable real-time information retrieval about route plans, traffic situation or order status. 

Logistics are both part of the transport sector and the industry sector. Beside transportation, the challenges of logistics are the management of inventory and other production factors. A common term in the context of logistics is supply chain management, which is described as an example for the possibilities of process automation in the industry & business section.

References 

[1] Business Dictionary. http://www.businessdictionary.com/. Accessed: 2013-02-12.

[2] G. Philipson. Ict’s role in the low carbon economy. Technical report, Australian Information Industry Association (AIIA), 2010.

[3] B. Metz. Controlling climate change. Cambridge University Press, 2010.

[4] The Climate Group. Smart 2020: Enabling the low carbon economy in the information age. Technical report, The Climate Group on behalf of the Global e-Sustainability Initiative (GeSI), 2008.

[5] The Descartes Systems Group Inc. Business white paper: Wireless capabilities a must-have for fleet operators. http://www.descartes.com/resources/whitepapers/ds_wp_wireless_capabilities.pdf, May 2008. Accessed: 2012-01-03.

[6] posteverywhere.com. Definition of freight matching. http://www.posteverywhere.com/freight_matching.html. Accessed: 2013-02-12

[7] R. Harwig and E. Aarts. Ambient intelligence: invisible electronics emerging. In Interconnect Technology Conference, 2002. Proceedings of the IEEE 2002 International, pages 3 – 5, 2002.

Intelligent Transportation Systems (ITS)

In the USA 44 percent of CO2 emissions arise from road traffic [1]. Traffic jams and slow traffic flow account for increasing fuel consumption of vehicles and therefore contribute to high emission levels of the transportation sector. Beside this inefficiencies in traffic systems result in losses of time and lead to higher general costs of transport. In the USA transportation is the second largest household expense, after accommodation costs [1].

To address these high costs and the environmental impact of transportation, methods to use the existing transportation facilities as efficient as possible are needed. Therefore Intelligent Transportation Systems (ITS) are developed. This term describes ICT systems that improve traffic infrastructure in terms of utilization and safety, and enable vehicles to interact with the infrastructure and with each other [2]. As ITS are not only restricted to individual traffic, it is a general term describing management and control systems for every type of transportation systems, including road, rail and air traffic. The following goals of traffic management can be achieved by implementing ITS [3]:
  • Safety in traffic systems, by variable information and warning systems. 
  • Time and cost savings, due to reductions in traffic volume and optimization of travel routes. 
  • Lowering the environmental, by enhanced traffic flow and positive discrimination of pub- lic transport. 
  • Higher efficiency in mobility, because of optimized utilization of traffic systems. 

The basis of Intelligent Transportation Systems are networks of traffic sensors, which provide real-time traffic data. On the one hand, this data is used for operational traffic management [4], which includes short-term actions, like the operation of adaptive traffic lights and variable message signs, or the calculation of the current traffic situation for informational purposes. One example of an information platform about the current traffic situation in Austria is the website www.AnachB.at, which is a service provided by ITS Vienna Region. The website contains an online map with routing functionality, using traffic data of stationary and mobile traffic sensors to calculate the real-time traffic situation in the supported area. The map can be displayed as street map or as satellite photograph for route planning purpose. In traffic situation mode, the current traffic flow, as well as information about road work, roadblocks and real-time pictures of traffic web cams are integrated and updated every 15 minutes. Figure 1 shows a screenshot of the website www.AnachB.at at about 2 pm on 2011-11-29, displaying the current traffic situation in Vienna.

The second application area of traffic data is strategic traffic management [4], which incorporates long-term planning and execution of traffic infrastructure construction works and traffic simulation, used for decision making in traffic management strategy. In terms of traffic system infrastructure there are some approaches in development to enhance information supply and communication methods. One example are Dedicated Short Range Communications (DSRC) [5], which is a term for infrastructure-to-vehicle and vehicle-to-vehicle communication. Therefore ICT is used to increase coordination and multi-direction information exchange between vehicles and infrastructure of traffic systems. With the IEEE 802.11p standard for wireless LANs, there is a agreed platform for this type of communication in traffic systems via smart vehicle communication systems [5]. A general term for the trend of information and communication systems in traffic systems and vehicles is cooperative vehicle-infrastructure systems (CVIS) [6]. These ICT systems increase safety and efficiency of traffic systems by using traffic data to inform users and act as support for route planning. The improved capability of communication between traffic infrastructure, vehicles and travelers can be seen as part of the ambient intelligence paradigm [7], which is a term describing the effort to link sensor networks, ICT infrastructure and mobile devices.


Figure 1: Screenshot of www.AnachB.at at 2 pm on 2011-11-29

References


[2] B. Williams. Intelligent Transport Systems Standards. Intelligent Transportation Systems. Artech House, 2008.

[3] G. Gottardi  and  A. Fellmann. ITS – Umfang,  Ziele  und  Zukunft  von  intelligenten Verkehrssystemen. http://www.jennigottardi.ch/images/publikationen/S+V9_97.pdf, September 1997. Accessed: 2013-02-12 (in German).

[4] M. Königsmayr. Wartung und Instanhaltung von infrastrukturseitigen Sensornetzwerken. Master’s thesis, Vienna University of Technology, 2011.

[5] J. Zhu and S. Roy. Mac for dedicated short range communications in intelligent transport system. IEEE Communications Magazine, Vol. 41 Issue: 12:60 – 67, 2003.

[6] F. Penwill-Cook. Intelligent transport systems: Driving into the future.
http://www.roadtraffic-technology.com/features/feature42979/. Accessed: 2013-02-12.

[7] G. Philipson. Ict’s role in the low carbon economy. Technical report, Australian Information Industry Association (AIIA), 2010.

Hybrid Engine Motor Systems

A hybrid engine motor system is an approach to combine different types of engines in one vehicle, to reach an energy efficiency gain in comparison to traditional engines. Usually a combustion engine is combined with an electric drive [1]. The whole drive system is called power-train, which is optimized in order to access the advantages of both engine types. The electrical drive can provide power at zero pollution in certain cases and enables higher fuel efficiency of the combustion engine. Therefore such hybrid systems use methods like regenerative braking, which is using the kinetic energy while braking to reload the battery, or start-stop mechanisms, to automatically stop the combustion engine while the car is standing still and restart the engine when it is needed. To sum this up, the benefit of hybrid cars is “to operate the combustion engine in more suitable regimes with better fuel combustion conditions” [2]. There are different construction methods for hybrid engines, varying in the way the two engines are working together. Figure 1 shows three possible schemas of a hybrid drive powertrain, including a construction in series, in parallel and a combined construction [2]:


Figure 1: Series hybrid drive (l), parallel hybrid drive (m) and combined switched hybrid drive (r) [2]

The role of ICT in the context of hybrid motor systems is to enable the optimization of design and control of these systems. Information technology therefore provides tools for offline planning and simulation of motor systems, that allow the calculation of the parameters providing maximum efficiency of the motor system [1]. Beside offline optimization, hybrid motor systems have to be controlled online to adjust the workload of both engine types. This function is fulfilled by built-in computer systems as well [3]. A study in 2008 came to the conclusion that a hybrid engined car had a reduced fuel consumption by about 13,6 percent in comparison to the same type of car powered by a traditional combustion engine [2]. The fuel-saving potential of hybrid cars can therefore be assumed to be environmentally relevant, but rather low. The hybrid engine technology is particularly efficient for delivery vehicles and buses, where frequent stops are necessary, rather than long-distance road travel [4]. This statement is based on the fact, that the hybrid technology is characterized by producing electricity from recovering breaking energy, which is used to reload the battery for the electric engine. In general the environmental benefits of hybrid motor systems compared to traditional commercial cars are:
  • reduced greenhouse gas emissions, due to increased energy and fuel efficiency, 
  • a lower noise level at idle and slow speeds, due to the use of the electrical drive, and 
  • reduced fine dust emissions, which is an essential environmental factor, especially in cities.

In comparison to hybrid cars the positive environmental impact of completely electric powered vehicles would be more substantial. An immediate benefit of electric cars is that there are no fine-dust emissions arising from these engines. But the electricity needed for powering electric cars primarily is still generated by fossil fuel power plants. Therefore greenhouse gas emissions savings can only be achieved by reloading electric cars from renewable sources of energy. One promising concept are Smart Grids, which enable the efficient integration of small-scale power generators based on renewable sources of energy [5]. Smart Grids could also supply charging stations as well as simplified charge billing, by logging in to the owner’s account when a vehicle is plugged into the grid. Additionally, the batteries of electric cars could be used as distributed power storage in Smart Grids [4]. By this electric vehicles could help balancing the energy on the electrical grid, a concept that is called vehicle to grid [5]. This approach could be especially beneficial in peak times.

References

[1] A. Kleimaier and D. Schroeder. Hybrid cars, optimization and control. In Industrial Technology, 2004. IEEE ICIT ’04. 2004 IEEE International Conference on, volume 2, pages 1084 – 1089 Vol. 2, dec. 2004.

[2] Z. Cerovsky and P. Mindl. Hybrid electric cars, combustion engine driven cars and their impact on environment. In Power Electronics, Electrical Drives, Automation and Motion, 2008. SPEEDAM 2008. International Symposium on, pages 739 –743, june 2008.

[3] B. Tomlinson. Greening through IT - Information Technology for Environmental Sustainability. The MIT Press, 2010.

[4] B. Metz. Controlling climate change. Cambridge University Press, 2010.

[5] U.S. Department of Energy. What is the smart grid? http://www.smartgrid.gov/the_smart_grid. Accessed: 2013-02-12.

Navigation Systems

It was already mentioned that ICT systems can be used to optimize traffic systems. This can be considered as a kind of high-level optimization by traffic management. On the other hand information technology also serves for optimizing the routes of individual participants in traffic system, and therefore enables efficiency gains in travel time, travel distances and energy needed for transportation. Such systems are for example in-car navigation systems using the GPS standard for real-time route planning, or online mapping and routing software. All these systems can be categorized as navigation systems and lead to less CO2 emissions in theory [1]. Navigation systems are used in private individual transport, as well as in commercial transport and logistics. Navigation systems using the Global Positioning System (GPS), which today are implemented as on-board features of modern cars, as discrete mobile devices or as part of many mobile phones, are based on satellite navigation. The principle of determining positions via satellites is trilateration [2]. This method allows determining positions by measuring distances to a minimum of three points with known coordinates. The method of trilateration is shown in figure 1.


Figure 1: Principle of trilateration - The measured distances to three points of reference (S1, S2, S3) determine the position of P [2]

The GPS standard uses 24 satellites, which orbit the Earth on 6 different orbital planes. These satellites are positioned in a way that allows more than 99 percent of GPS users all over the world to contact at least four satellites at any given time [2]. The GPS satellites are equipped with atomic clocks and transmit signals at a frequency of 1575.42 MHz directed to Earth [3]. A GPS signal contains the Navigation Message, consisting of it’s on-board time and orbit parameters, which can be processes by any GPS receiver to compute satellite coordinates. The atomic clocks of each of the 24 satellites are regularly synchronized from control stations on Earth, while the clocks of GPS receivers are not synchronized with the clocks of satellites and are far less precise [4]. Since the distance between a GPS receiver and a satellite is determined by measuring the time delay of the transmission and the reception of the satellite’s signal, which is moving by the speed of light, there is a certain time error influencing the measurement, due to the non-synchronized clocks of satellite and receiver. This time error is unknown, together with the coordinates of the GPS receiver, which means that there are four unknown variables that have to be determined for positioning in three-dimensional space [3]: longitude (x), latitude (y), height (z) and time error (4t). To determine four unknown variables, four independent equations are needed. For this reason the minimum number of satellites for GPS locating is four. Figure 2 illustrates the basic function of GPS, which is calculating the coordinates of a location by measuring the distances to four GPS satellites.


Figure 2: The basic function of GPS [3]

Beside the economical and environmental benefits of navigation systems in form of fuel and emissions savings, there are social and personal advantages for the users of these systems. Route planning software and GPS navigation increases the efficiency of traveling and therefore saves time. Navigation systems can ease the complex activity of way finding and therefore leave more capacity for engagement with the surroundings. On the other hand it is reasonable to argue, that navigation systems disengage the users from their environment, in case they fully rely on it.

There was a study in 2008 about how navigation systems alter the users’ experience of their environment [5]. For this reason observations and interviews where done with in-car GPS users, to determine how using a navigation system changes the behavior and the experience while driving. The findings of the study where partly claiming a trend to disengagement from the environment, due to the reduced need for orientation and keeping track of locations. Additionally some users of navigation systems are just following the instructions whether they are correct or not. On the other hand the researchers found out, that there was an enriched engagement with the environment in some cases, because of the discovery of new points of interest and the safety of not getting lost in unknown areas [5]. Due to the results of this study, navigation systems are an example for the fact that the social impact of information and communication technologies is often hard to classify.

References

[1] B. Tomlinson. Greening through IT - Information Technology for Environmental Sustainability. The MIT Press, 2010.

[2] accessscience.com. Satellite navigation systems. http://accessscience.com/content/Satellite-navigation-systems/602800. Accessed: 2013-02-12.

[3] J.-M. Zogg. Gps basics. http://faculty.ksu.edu.sa/hbilani/SE412books/GPS_basics_u_blox_en.pdf, 2002. Accessed: 2013-02-12.

[4] G. Blewitt. Basics of the gps technique: Observation equations. http://www.nbmg.unr.edu/staff/pdfs/Blewitt%20Basics%20of%20gps.pdf, 1997. Accessed: 2013-02-12.

[5] G. Leshed, T. Velden, O. Rieger, B. Kot, and P. Sengers. In-car gps navigation: engagement with and disengagement from the environment.  In Proceedings of the twenty-sixth annual SIGCHI conference on Human factors in computing systems, CHI ’08, pages 1675–1684, New York, NY, USA, 2008. ACM.

Dematerialization by Telework and Videoconferencing

Telework

In nearly every economic sector ICT can be used for the dematerialization of physical products or processes. Teleworking has an effect on the transport sector, since the travel ways to and from offices can be reduced by working from home. The Telework Research Network published following figures about the saving potential induced by teleworking in the United States of America [1]:
  • Savings of over 280 million barrels of oil. 
  • Greenhouse gas savings of 53 million tons, which would be over 21 percent of the USA’s aim of reductions by 2020. 
  • Savings of about 1 billion dollar in highway maintenance, due to reductions of wear. 
  • Companies could save 200 billion dollar in office buildings, including utilization and maintenance costs. 
  • The resulting electricity savings from offices could power 900,000 homes per year. 
  • Reductions in traffic related injuries and deaths, resulting in cost savings of 12 billion dollar a year. 
  • Each employee could save up to between 1,800 and 6,800 dollar in transportation and work-related costs. 
  • While 40 percent of employees in the USA have jobs that would allow teleworking, only 2 percent work from home most of the time. 

In total the extensive use of telecommuting could save more than 650 Billion Dollar a year. According to the authors of the referenced website, these figures are a result of synthesizing 250 case studies, a number of reviews and interviews with virtual employers and their employees, as well as top researchers on the topic [1].

Also The Climate Group states in it’s SMART 2020 Report that more than half of the emissions saving potential of dematerialization by ICT is made up of the proliferation of telecommuting. In numbers this would be 0.26 GtCO2e in 2020 globally [2]. Other researchers assume the potential savings in greenhouse gas emissions due to telecommuting to be 588.2 million tons just for the USA [3]. One of the major environmental benefits of telecommuting arises from reduced work-related travel. Due to the possibility for people to increasingly work from home, this “could provide help in de-coupling transport growth and economic growth” [4]. The reduction in physical traffic volume may be partly offset by additional trips in leisure time. Furthermore telecommuting could be a reason to move to rural areas, which would result in longer distance travel at days when working at the office [3]. These coherences can be termed as rebound effects. Studies approved that in some cases teleworkers undertake additional trips, that would usually be combined with traveling to and from workplace (e.g. shopping), which offset about half of the travel savings in average [4]. Taking all the considerations into account, an increase of telecommuting would have a significant positive effect on the environment.

Telework is also a concept of dematerialization in the buildings sector. Studies show that a significant number of workers working from home at three days a week could lead to energy savings of 20 to 50 percent, even when the resulting increase of energy demand in homes is considered [2]. Telecommuting or telework was enabled by the distribution of broadband networks, that allow to transfer large amounts of data. It means “working remotely via the use of ICT solutions” [2], while the remote workplace is usually represented by the private home. The energy and emissions savings are composed of reduced travel routes and the possibility for companies to build and maintain smaller offices. This requires the sharing of workplaces, which makes at least three days of teleworking a week necessary. The space in typical office buildings is utilized only about 18 percent of total time [5]. This fact shows that the improvement of utilization of existing space, could lead to reduced demand for new buildings and therefore to a significant reduction of emissions, arising from construction, utilization and maintenance of new buildings. A precondition to energy and emissions savings by telecommuting in the buildings sector is, that teleworkers give up their office spaces, or at least share them. Otherwise reductions in carbon emissions by telecommuting can be expected from reduced travel only [4]. A research work done in the USA is assuming that a home office would bring energy savings of about 3500 kWh on average compared to a commercial office. This would lead to savings of 46.6 billion kWh of electricity, or 56.8 tons of CO2e per year, at a supposed number of 13.3 million telecommuters in the USA [3].

Videoconferencing

A second example for the dematerialization of travel ways is videoconferencing. This approach replaces physical meetings by providing ICT equipment for video-telephony over the Internet. There are studies that claim that significant reductions in emissions could be achieved by reducing physical traffic by videoconferencing [6]. In this context it has to be mentioned, that approaches like videoconferencing and telecommuting have already been existing for a while and have not been adopted as widely as it could have been expected during this period [2]. In 2005 only 3,9 percent of the population of the 25 member states of the European Union regularly used the Internet for video- or audio conferencing [4]. This shows that the level of acceptance is an important issue for the adoption of ICT developments. Therefore it is essential that the ICT infrastructure allows an adequate user experience while videoconferencing for example, so that it gets a viable alternative to physical meetings [6].

A research work of 2004 from Norway on the impact of videoconferencing on business travel determined, that the substitution rate of business air travel by videoconferencing is only 2.5 to 3.5 percent [7]. The author also claimed, that videoconferencing is mainly used for intracompany communication. This fact suggests that personal contact is still the preferred way of conducting business between companies and maybe will remain dominant over virtual meetings. The main reasons for companies for the adoption of videoconferencing are time and cost savings (cf. figure 1) [7]. It can be hypothesized that a significant increase in travel costs could be a reason for companies to utilize videoconferencing technology more extensive. Several case studies showed that the potential carbon savings arising from the use of teleconferencing (audio and video), can be numbered as about 15 percent of the company’s business travel [4].


Figure 1: Reasons for videoconferencing (a higher score means more important) [7]

References

[1] teleworkresearchnetwork.com. Telework savings potential. http://www.teleworkresearchnetwork.com/cut-oil. Accessed: 2013-02-12.

[2] The Climate Group. Smart 2020: Enabling the low carbon economy in the information age. Technical report, The Climate Group on behalf of the Global e-Sustainability Initiative (GeSI), 2008.

[3] J.P. Fuhr and S. Pociask. Broadband and Telecommuting: Helping the U.S. Environment and the Economy. Low Carbon Economy, vol.2:41–47, 2011. 

[4] Bio Intelligence Service. Impacts of information and communication technologies on energy efficiency, final  report. ftp://ftp.cordis.europa.eu/pub/fp7/ict/docs/sustainable-growth/ict4ee-final-report_en.pdf, September 2008. Accessed: 2013-02-12.

[5] B. Tomlinson. Greening through IT - Information Technology for Environmental Sustainability. The MIT Press, 2010.

[6] P. Fernando and A. Okuda. Escap technical paper: Green ICT - a “cool” factor in the wake of multiple meltdowns. http://www.unescap.org/idd/working%20papers/IDD_TP_09_10_of_WP_7_2_907.pdf, December 2009. Accessed: 2013-02-12. 

[7] J.M. Denstadli. Impacts of videoconferencing on business travel: the norwegian experience. Journal of Air Transport Management, 10(6):371 – 376, 2004.