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38th Annual Conference of the IEEE Industrial Electronics Society (IECON 2012), Montréal, QC, CA.   Co-Simulation of PEV C...
Outline• Introduction• Impact study of uncoordinated PEV charging• Proactive and reactive coordination schemes• Communicat...
Introduction to Smart Grid                     Current electrical grid●    Current electrical grid:      ●          One-wa...
Is uncoordinated PEV charging a problem ?● In some works [1], it was found that PEV charging can significantlystress the d...
Configurations - Topology● Widely used IEEE 13-Nodedistribution test feeder.●  Substation steps down the115kV transmission...
Configurations – Baseload and PEV modeling● Each residential nodefollows the Fig. 1 profile and+/- 1 hour time shifting to...
Uncoordinated PEVscharging results●  For both uniform and non-uniform distributions: as thepenetration level (PL) increase...
Coordinated PEVs● Coordination solutions canbe grouped into twocategories:    ●       Proactive scheduling: PEVs are    sc...
Proactive algorithms● First fit: Start time of PEV Constraints:                                             (1) Voltage co...
Reactive control● Each residential node sendsnotification (voltage, load, etc.)packets to a central system,the distributio...
Reactive control – Sensor type●  The reactive control mechanism is influenced by the sensortype being used.●    Two sensor...
Communicationsperspective● Smart Grid communicationsover a broadband accessnetwork.● EPON: high capacity (> 1Gbps), reliab...
On Co-simulation● OMNeT++ is used for theFiWi simulator.●  A power system layer is alsocreated by calling OpenDSSfor volta...
Proactive co-simulationresults● As expected, with randomcharging, problems areobserved during peak hours.●  SLM fully dist...
Reactive co-simulationresults●  As the DMS profile couldnot match the real load, weadd some sudden highloads to create a s...
Reactive co-simulationresults●  The reactive control algorithmis tested with data rate basedsensors.● Thus, as the data ra...
Conclusions• Uncoordinated charging of PEVs can cause critical voltagefluctuations and overload utility assets as the pene...
Future work• Coordinate not only PEVs, but also renewable energy sources.• The considered broadband access network was not...
Questions ?              20
IECON Martin Lévesque
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IECON Martin Lévesque

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IECON Martin Lévesque

  1. 1. 38th Annual Conference of the IEEE Industrial Electronics Society (IECON 2012), Montréal, QC, CA. Co-Simulation of PEV Coordination Schemes over a FiWi Smart Grid Communications Infrastructure Presented by: Martin Lévesque INRS (Québec, Canada) PhD student 2
  2. 2. Outline• Introduction• Impact study of uncoordinated PEV charging• Proactive and reactive coordination schemes• Communications and power distribution network co-simulation• Co-simulation results• Conclusions 3
  3. 3. Introduction to Smart Grid Current electrical grid● Current electrical grid: ● One-way flow of energy. ● Exchange of information from generators to substations. ● Cannot handle large-scale deployment of distributed renewable energy ressources and/or electric vehicles. Smart Grid● Smart Grid : ● Two-way flow of energy and information. ● Monitoring and control of the grid using communications and sensor technologies. 4 Sources: http://www.smartgrid.epri.com/Demo.aspx http://www.incontext.indiana.edu/2010/july-aug/article3.asp
  4. 4. Is uncoordinated PEV charging a problem ?● In some works [1], it was found that PEV charging can significantlystress the distribution network on a local scale.● While in some other distribution systems [2], little negative impact wasobserved.● Thus, we first look into uncoordinated PEV charging to verify theirfindings. [1] [2] 5
  5. 5. Configurations - Topology● Widely used IEEE 13-Nodedistribution test feeder.● Substation steps down the115kV transmission networkto 4.16kV.● Each node in the feederaggregates one or more lowvoltage residentialnetwork(s).● Total number of 18 Fig. : Single line diagram of theresidential networks, totalling modified IEEE 13-Node network.342 customer households. 6
  6. 6. Configurations – Baseload and PEV modeling● Each residential nodefollows the Fig. 1 profile and+/- 1 hour time shifting tocreate random behaviors. Fig. 1: Base load profile [1].● PEVs arrive according to adistribution of last trip endingtime, Fig. 2. Fig. 2: Distribution of household last trip ending time.● Nissan LEAF specifications Based on the driving pattern data extracted from theare used: National Household Travel Survey (NHTS), 2001. [1] ● Battery: 24 kWh. Charging rate: 1.8 kW/hour, 7 ● ● (North American 15A/120V outlet)
  7. 7. Uncoordinated PEVscharging results● For both uniform and non-uniform distributions: as thepenetration level (PL) increases,the daily voltage fluctuationbecomes more severe and belowthe permissible limit.● For non-uniform, problems startwhen the PL is higher than 20%. ● Requiring more peaking power → Increase generation costs. Fig. 1: Voltage deviation for different PEV penetrations for● Thus, coordination is required. uniform case and non-uniform case. Non-uniform: Clusters 634 & 675 have a PL two times higher compared to other clusters. 8
  8. 8. Coordinated PEVs● Coordination solutions canbe grouped into twocategories: ● Proactive scheduling: PEVs are scheduled to avoid critical voltage fluctuations. ● Reactive control: Fix the problem when it occurs. Fig.: Coordinated and uncoordinated PEV control solutions. 9
  9. 9. Proactive algorithms● First fit: Start time of PEV Constraints: (1) Voltage contraint.charging is the first availableslot that does not violate (2) Maximum power demand.(1,2). Parameters:● Smart load management(SLM) [1]: Find the slot (3)minimizing (3,4) withoutviolating (1,2). (4) [1] 10
  10. 10. Reactive control● Each residential node sendsnotification (voltage, load, etc.)packets to a central system,the distribution managementsystem (DMS).● The DMS schedulesaccording to an historical loadprofile for the future load.● Algorithm 1: When the DMSfinds a voltage problem, itsuccessively un-plug PEVs tofix the problem. 11
  11. 11. Reactive control – Sensor type● The reactive control mechanism is influenced by the sensortype being used.● Two sensor types: ● Data rate based: Measurements are sent periodically. As the rate increases, the probability that an information is outdated decreases. ● Event based: Send a measurement only when the difference between 2 measurements is higher than a certain threshold. 12
  12. 12. Communicationsperspective● Smart Grid communicationsover a broadband accessnetwork.● EPON: high capacity (> 1Gbps), reliable, low latency.For urban areas.● WLAN technologies for theubiquity to extend the PON Fig.: Über-FiWi architecture composed of ancoverage. EPON, next-generation WLAN, and sensors.● For rural areas, WiMAX canbe used. 13
  13. 13. On Co-simulation● OMNeT++ is used for theFiWi simulator.● A power system layer is alsocreated by calling OpenDSSfor voltage, power, losses, etc.,according to the load at eachnode in the network.● Each residential node ismapped to either an ONU orWLAN node. Fig.: Power distribution network and FiWi co-simulator.● Thus, both perspectives workas an integrated system. 14
  14. 14. Proactive co-simulationresults● As expected, with randomcharging, problems areobserved during peak hours.● SLM fully distributes theload and fills the valley,whereby first fit can increasethe peak duration.● Only 1-2 Mbps ofthroughput was required withan end-to-end delay of 1-8ms. Fig.: Proactive co-simulation results. 15 The penetration level is set to 66%, uniform distribution.
  15. 15. Reactive co-simulationresults● As the DMS profile couldnot match the real load, weadd some sudden highloads to create a stressscenario.● As expected, criticalvoltage fluctuations areobserved during these Fig.: Reactive co-simulation results.sudden high loads. 16
  16. 16. Reactive co-simulationresults● The reactive control algorithmis tested with data rate basedsensors.● Thus, as the data rate ofsensors increases, the criticalvoltage duration decreases.● In this example, to have acritical voltage duration lowerthan 1 second, one need to set Fig.: Critical voltage duration as a function of the data rate of sensors.the data rate to at least 4packets per second. 17
  17. 17. Conclusions• Uncoordinated charging of PEVs can cause critical voltagefluctuations and overload utility assets as the penetration levelincreases.• To overcome these issues, we used a converged broadband accessnetwork to coordinate PEVs using a proactive algorithm at the DMS.• However, the information available at the DMS can mismatch theactual voltage and load in the network.• We proposed a reactive control algorithm to fix and un-plug PEVs toquickly solve critical voltage fluctuations. 18
  18. 18. Future work• Coordinate not only PEVs, but also renewable energy sources.• The considered broadband access network was not loaded. Thecommunications must take into account triple-play traffic (video, voice,data). 19
  19. 19. Questions ? 20

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