In this extended abstract the need for efficient and reliable ICT is discussed. Efficiency of ICT not only deals with energy-efficient ICT hardware, but also deals with efficient algorithms, efficient design methods, efficient networking infrastructures, etc. Efficient and reliable ICT is a prerequisite for efficient Smart Grids. Unfortunately, efficiency and reliability have not always received the proper attention in the ICT domain in the past

Smit, Gerard J.M.

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Smit, Gerardus Johannes Maria

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Efficient ICT for efficient smart grids

University of Twente Research Information

1Efficient ICT for efficient Smart GridsGerard J.M. Smit, University of Twente, Enschede, the Netherlandscontact: g.j.m.smit@utwente.nlAbstract—In this extended abstract the need for efficient andreliable ICT is discussed. Efficiency of ICT not only dealswith energy-efficient ICT hardware, but also deals with effi-cient algorithms, efficient design methods, efficient networkinginfrastructures etc. Efficient and reliable ICT is a prerequisitefor efficient Smart Grids. Unfortunately, efficiency and reliabilityhave not always received the proper attention in the ICT domainin the past.A. IntroductionAlthough much of the worldwide increase in electricityconsumption is attributed to ICT, the same ICT technologycan also be used to reduce the worldwide energy consumption.Efficient ICT systems can, for example, be used to controlthe consumption, production, transportation, and storage ofelectricity (Smart Grids). Next ICT systems can be used tocontrol and schedule large electricity consuming and produc-ing appliances in an optimal way. Therefore, ICT plays a keyrole in reducing the energy intensity of the economy, thushelping to decouple growth from energy consumption andcreating new opportunities while saving the environment.Research in using ICT for reducing energy consumptionmay include issues such as e.g.• flexible ICT systems for (decentralized) electricity man-agement• technologies and tools for dependable ICT systems thatcontinue to operate when elements fail in the electricitynetwork (Smart Grids),• versatile multi-purpose energy-efficient ICT systems andcommunication infrastructures which can handle a widerange of (future) services to safeguard sustainability, and• energy-aware systems which integrate real-time infor-mation from (wireless) sensor networks and externalinformation sources such as weather forecasts.In March 2007, the European Council agreed on an ac-tion plan on European energy policy. This action plan isknown as the EU 20-20-20 plan. It sets new, binding targetsfor the reduction of greenhouse gas emissions from energyconsumption. These will be met through increasing the useof renewables to 20% of total energy consumption by 2020,mostly via highly decentralized ‘green’ power generators (likefrom wind, biomass, or solar energy; or from micro-CHPsor energy storage systems) forming Virtual Power Plants.Furthermore, improving energy efficiency should ensure thatthe total energy usage is 20% lower than current projections forG.J.M. Smit is professor of the Computer Architecture for EmbeddedSystems (CAES) group within the Department of Electrical Engineering,Mathematics and Computer Science, University of Twente, P.O. Box 217,7500 AE, Enschede, The Netherlands2020, through reduction of consumption and of transmissionlosses as well as improvement of energy-conversion efficiency.The energy technologies in use today were mostly designedfor a different era based on centralised energy generation andeconomies of scale. Today the energy companies are facing atransition to address the goals of the new EU energy policy.This will require new energy and ICT infrastructures. Thedriving forces for this transition are the security of energysupply and environmental concerns. ICT will be an enablerin this process and will lead to the creation of new energymarkets, decentralized control, and higher system quality,efficiency and reliability.According to a recent report 2020 [1] of the Climate Groupand McKinsey, ICT is a key player in the battle against climatechange and offers the possibility of 7.8 Gt reduction of CO2emission in 2020. A recent annex of this report calculatesa saving of 140-240 billion dollar in the US by reducingthe energy consumption due to smart usage of ICT systems.Also the European Commission is stressing the importanceof ICT for energy reduction and sustainability and investsin research in this area [2]. The plans have amongst othersresulted in a number of research programmes combining ICTwith Energy. For example the EU-PPP programme on EnergyEfficient Buildings and the EU-FP7 calls for ICT for EnergyEfficiency, ICT for environmental services and climate changeadaptation, novel ICT solutions for Smart Electricity Distribu-tion Networks, ICT for energy-efficient buildings and spacesof public use and ICT for energy-positive neighbourhoods.B. Efficient ICTEnergy consumption is one of the main concerns of todaysICT hardware and software designers and systems integrators.Regarding energy-efficiency the first type of devices peopleusually think of are portable devices as these devices relyon batteries and therefore the functionality is strictly limitedby the energy consumption. However, for high performancecomputing there is also an increasing need for energy-efficientarchitectures to reduce the cost for cooling and packaging.Today also the performance of many ICT systems is limitedby energy dissipation and electricity supply. In addition to thatthere are environmental concerns that urge for more efficientarchitectures in particular for systems that run 24/7 (24 hoursper day 7 days per week) such as wireless base stations,servers parks, data centres and search engines (e.g. Googlehas an estimated server park of one million servers that run24/7). Energy reduction can be done at several layers: reduceenergy for processing and storage of data, reduce energy forcommunication, operating systems and software.One important aspect in energy reduction is locality ofreference. This means that data that a processing element978-1-4577-2159-5/12/$31.00 ©2011 IEEE 2frequently needs should be located close to the processingelement. For example it is quite inefficient when sensor data isbrought to a central location, where the processing is done andbrought back to the actuators, that are often located close tothe sensors, where actuation is done. When wireless networksare needed to transport this data, often more energy is spentin data communication compared to the energy in the centralprocessing. This means that processing should be done close tosensors whenever possible. In our opinion the cloud computingparadigm is less applicable for Smart Grids, because data isdistributed over many devices scattered over a large area andthe processing is rather simple. However, cloud computingcan be used for high-level control and optimisation of energystreams.C. Energy ManagementIn a few years from now a large percentage of the electricitywill be generated by decentralized micro-generators, (e.g.micro-CHPs and solar cells). Micro generation systems gener-ate electricity at the kilowatt level which will allow the unitsto be installed in an individual home and connected directlywith the domestic heating and electrical systems, which bydefinition entails very high efficiency (up to 90%) in usage ofprimary energy. Also, it allows for delivery of electricity to thepower grid, where the distance to its consumer may be limited,e.g. in the same city or neighbourhood. The micro-generationconcept has the additional benefit of reduced distribution andtransmission losses, delivering significant advantages in termsof overall efficiency relative to centrally generated power. Thisconcept offers an attractive option in the reduction of primaryenergy consumption and therefore carbon (CO2) emissions.On the long run we will rely on renewable energies.Renewable energies are generally based on a large numberof even smaller sources of power, producing power muchcloser to the location in which it is used. Some installations,such as those producing heat, can only supply users in theirimmediate area, while equipment which produces electricity,such as windmills, biomass systems, or photovoltaic roofpanels, can be used to supply to electricity networks.The introduction of renewable energy requires the develop-ment of new ICT systems for obtaining energy efficiency andmeeting grid requirements, while maintaining high standardsof comfort, quality and reliability of services as well asconnectivity. In addition, the future availability of storagedevices (such as batteries in electric cars) opens up newperspectives and constraints, both from the sides of storage andsupply (to the grid), as well as demand (from the grid). Thedemand for electricity in a large network varies dynamically asmillions of users continuously switch on and off independentlytheir equipment. The wholesale price of electricity, paid bydistributors to (large scale) generators, also rises and fallswith demand. A similar approach could be applied to massiveamounts of small-scale generators, seen as a Virtual PowerPlant (VPP).An intelligent system employed by the operator of a small-scale generation resource, such as photovoltaic panels on ahouse, or a fuel-cell, would be able to recognise when surplusenergy can best be sold on the market, and when it should beused to heat water, for example. Similarly, continuous agree-ments for supplies during short or long durations, involvinge.g. prices, timing, and quantities could be made betweennetwork operators and small-scale suppliers.ICT provides the means to manage the operation of mil-lions of small-scale electricity generation appliances, bothon behalf of their owners and for the networks into whichthey feed. ICT tools can monitor a range of variables andensure that both individuals and the network as a wholegain maximum efficiency from the energy generation capacityavailable. Development of such ICT systems will therefore fuelthe installation of new and renewable-energy-based generationcapacity, through maximising the return on investment somaking it more affordable. In this way, it can more quicklymeet its goals in the field of stable electricity supply, energyefficiency and emissions reduction, and provide consumerswith higher quality energy supplies.The electricity grid has to cope with the variability of thefuture generators and consumers, many of which are stillunknown. In principle, the smart grid is an upgrade of 20thcentury power grids, which generally ”broadcast” power froma few central power generators to a large number of users, toinstead be capable of routing power in more optimal ways torespond to a very wide range of conditions. The conditions,to which a smart grid can respond, may occur anywhere inthe power generation, distribution and demand chain. Eventsmay occur generally in the environment (clouds blocking thesun and reducing the amount of solar power, a very hotday), commercially in the power supply market (prices tomeet a high peak demand exceeding one dollar per kilowatt-hour), locally on the distribution grid (MV transformer failuresrequiring a temporary shutdown of one distribution line) or inthe home (someone leaving for work, putting various devicesinto hibernation), which motivate a change to its power flow.In addition, several constraints are induced by the power griditself as well as the devices connected to it.One of the problems Smart Grids are facing with is that notall decentralized micro-generation systems have predictableelectricity generation patterns. For example solar cells aredependent on the time of the day and the amount of sunlight.Wind energy is only available when there is wind and micro-CHP systems only produce electricity when there is a heatdemand. As a consequence, decentralized systems sometimesproduce electricity when there is no need for it locally.A solution to these problems may be to transform domesticcustomers from static consumers into active participants in theproduction process. Consumer participation can be achievedthrough the development of new (domestic) devices with con-trollable load, micro-generation and domestic energy storageof both heat and electricity. These devices have potentialto shift electricity consumption in time without harming thecomfort of the residents.D. 3 step control methodologyExamples of devices with optimization potential are (smart)freezers and fridges, which can adjust their cooling cycles to3shift their electricity load and (electrical car) batteries that cantemporarily store excess electricity. To exploit this optimiza-tion potential on a large scale, a global control methodology isrequired [3]. The above-mentioned challenges and optimiza-tion potential are studied and a control methodology is derived.This control methodology aims:• to achieve a more efficient use of the generated electricityof existing power plants,• to facilitate the large scale introduction of renewablesources and• to allow large scale introduction of new technologies forproduction, consumption and storage while at the sametime maintaining grid stability and ensuring a reliable andaffordable supply.The control methodology uses mathematical optimizationtechniques and a combination of prediction, offline globalplanning based on the predictions and online realtime con-trol based on the global planning. The base of the controlmethodology is:• using local information,• communication using multiple levels and• scalability.The goal of the control methodology is to work towards(global) objectives and the performance of the control method-ology is measured to the extent to which the objectives arereached. Based on the above considerations, the proposedcontrol methodology uses three steps and is split up into alocal and a global part:1) predictions on a device level to be able to predict theoverall result,2) planning to estimate the energy streams in the buildingand the grid and3) real-time control to respond on changes (e.g. fluctuationsin renewable generation) and work around predictionserrors.In the first step, the energy usage or production for everyindividual building in the grid is predicted on a device level.In the second step, the predictions of the individual buildingsare aggregated and a global planning is made in an iterativeand hierarchical way. The result of this planning is an energyprofile. In the last step, a local scheduler in every buildingschedules the devices in real-time, using steering signalsdetermined by the global planning as an input.Because of scalability reasons, the global planning has ahierarchical structure and can aggregate data and planning ondifferent levels, e.g. within a neighbourhood or city. The levelon which the planning is determined and, thus, the highestlevel of the global controller determines the scope (e.g. a localscope or a neighbourhood scope). Especially the three stepsand the global planning differ from the control methodologiesdescribed in literature. Furthermore, the control methodologyis not agent based and uses other mathematical optimizationmethods or heuristics than the control methodologies describedabove.Due to the predictions and planning on beforehand, thepredictability of the global electricity streams is improved.The combination of planning (aggregated knowledge on higherlevels) and mathematical optimization result in better depend-ability and combination of planning and real-time controlimproves the control over unexpected events. Furthermore,the amount of communication can be limited due to thehierarchical structure. Finally, the requirements on the com-munication medium are low since the local controller canwork independently and a lot of information can be sent onbeforehand without high latency requirements.Simulations show that the control methodology can optimizethe energy flows and can control the operation of the domesticdevices in an economic manner without discomfort for theresidents. The prediction and planning step preceding the real-time control improves the results of the control methodology:much more optimization potential can be exploited and theresults are more predictable and dependable.The challenging issues on the non-technical side includeregulatory regimes, business models, user psychology (includ-ing awareness) and privacy, governance and social dynamics.Widespread distributed generation requires completely newregulation since the traditional roles of producers and con-sumers are about to change. For the same reason, new businessmodels are needed. It might intervene quite substantially in thedaily energy routines of households with severe consequencesfor routines and privacy. Finally, it might initiate new socialcommunities with new functions and activities. Some chal-lenges are:• Behaviour of end-users• Privacy and data protection• Economics and transactions: who pays for what• Legislation and regulation issuesE. ConclusionICT provides the enabling technology to realise the EU20-20-20 goals. The energy technologies in use today weremostly designed for a different era based on centralised energygeneration and economies of scale. Today we are facing atransition to address the goals of the new EU energy policy.This will require new energy and ICT infrastructures. Thedriving forces for this transition are the security of energysupply and environmental concerns. ICT will lead to thecreation of new energy markets, decentralized control, andhigher system quality, efficiency and reliability. An importantaspect is that for future energy systems prediction and planningis required.REFERENCES[1] The Climate Group, Global e-Sustainability Initiative (GeSI), “Smart2020: Enabling the low carbon economy in the information age,” 2008,http://www.smart2020.org/.[2] Commission of the European Communities, “Mobilising ict to facilitatethe transition to an energy-efficient, low-carbon economy,” 2009.[3] A. Molderink, V. Bakker, M. G. C. Bosman, J. L. Hurink, and G. J. M.Smit, “Management and control of domestic smart grid technology,” IEEETransactions on Smart Grid, vol. 1, no. 2, pp. 109–119, 2010.

Commission of the European Communities, “Mobilising ict to facilitate the transition to an energy-efﬁcient, low-carbon economy,”

Management and control of domestic smart grid technology,”

The Climate Group, Global e-Sustainability Initiative (GeSI), “Smart 2020: Enabling the low carbon economy in the information age,”

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Efficient ICT for efficient smart grids

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