it infrastructure for providing energy-as-a-service to electric vehicles

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IT Infrastructure for Providing Energy-as-a-Service to Electric Vehicles. Smruti R. Sarangi , Partha Dutta , and Komal Jalan IEEE TRANSACTIONS ON SMART GRID, VOL. 3, NO. 2, JUNE 2012 Prepared for SG Subgroup Meeting, UW Presented by David (Bong Jun) Choi 2012-06-07. Contents. - PowerPoint PPT Presentation


IT Infrastructure for Providing Energy-as-a-Service to Electric Vehicles

IT Infrastructure for Providing Energy-as-a-Service to Electric VehiclesSmruti R. Sarangi, Partha Dutta, and Komal JalanIEEE TRANSACTIONS ON SMART GRID, VOL. 3, NO. 2, JUNE 2012

Prepared for SG Subgroup Meeting, UWPresented by David (Bong Jun) Choi2012-06-07ContentsOverviewSystem ModelProblem Formulation Proposed SystemEvaluationConclusion2OverviewChallengesCharging and discharging a large number of PHEVsSupply and demand should closely matchLower supply: outageHigher supply: wasteIntermittent source of sustainable energy sources3OverviewContributiontoken: currency of energygt: generation tokenct: consumption tokenAttributes: ID, type, gen/con, power level, duration, start and expiration time, statusEnergy = power *durationToken entitles owner to produce or consume a certain amount of electrical energyHow to schedule tokens?LM: Creates and Modifies tokensTMS: Admit and Schedule or Reject tokens4

Token Management System (TMS)Local Module (LM)Research ObjectiveGoal: Maximize utilization

Utilization = total consumption / total generationToken Utilization = total energy of the selected consTokens / total energy of the genTokens

Application-Level communication protocol

5Problem Formulation(1) maximizes the average utilization= total energy of the selected consTokens / total energy of the genTokens.(2) for every point in the activation time of a genToken, the sum of the power levels of the packed consToken instances is less than the power level of the genToken.(3) at most one instance of each consToken is activated to genToken (no splitting)(4) binary decision variable for genToken being packed6

timepowerProposed Token Management SystemFormulated ProblemPacking Problem NP-CompleteNot feasible to handle a large number of PHEVs

ProposedHeuristic algorithmToken (1) batching, (2) prioritization, and (3) splittingMy Opinion: Greedy algorithm based on Priority?Schedule based on set priorityIf cannot be scheduled, split and schedule again7

Cons-Token Batches- Based on start time and duration- MAX_BATCH_SIZE- Reduce computation load8Gen-Token Queue- Prioritization-MAX_GEN_ACTIVE- Ex) FIFO, round-robin on power source, expiration times, power levelsCons-Token Queue- FIFODispatcher- Packs CT in GT- Packing depend on the scheduling schemeScheduling Scheme(active genToken) endTime freeEnergy- random- utilizationDispatcher FunctionsconsBatch ActivationPacking consumption batch (cb) to genTokenConditions:Power level (consBatch) < Power Level (genToken)+ constraint (2)Activation period (consBatch) < validity period (genToken)Otherwise, rejectgenToken ReplacementIf utility above a certain thresholdno. of rejected tokens above a certain thresholdThengenToken replaced with a token with the highest priority

9Dispatcher FunctionsSplitting of consBatchPreviouslyconsBatch cannot spliti.e., One consBatch fit into one genTokenDifficult to achieve utilization close to 1NowconsBatch can spliti.e., different parts of consBatch fit into multiple genTokensFirst, schedule consBatch as a whole. If not possible, split and schedule smaller consBatchesProposes three different schemes10Splitting of ConsBatch (Scheme 1)1-D split on time axisconsBatch is split into two smaller batches on the time axis duration and validity periodSame power level11

Splitting of ConsBatch (Scheme 2)1-D split on power axisconsBatch is split into two smaller batches on the power axis power levelSame duration and validity period


Splitting of ConsBatch (Scheme 3)13

Effect of Token Splitting Theorem

Opt (2D split) at least better than Opt (1D power split) or Opt (1D time split) Above are at least better than Opt (no split) 14

EvaluationSetupVehiclesNumber: 0 ~ 7 millionPower Trace: Australian Power Grid supply (5 years)10% available for PHEVsVehicleConnectivity: following previous referencesCapacity: 10-15 kWhCharging Speed: 25 kW (20-30 min charging)Tokenduration(genToken) = 8 h (no frequent on/off)duration(consToken) = 24 minconsBatch Size = 10015

EvaluationEffect of consToken duration2% best / 100% worstSmaller fragments give better utilization


EvaluationEffect of Splitting AlgorithmSmall consTokens (5%)Effect of Splitting AlgorithmLarge consTokens (30%)

17improvementEvaluationOther resultsSchedulingSmall no. of PHEVsDeadline based prioritization performs bestLarge no. of PHEVsPower level based prioritization performs bestLarge number of consTokensContention between consTokens for packingLarger power helps to pack better

18EvaluationOther resultsValidity PeriodLonger consToken use duration increases utilizationMore flexible start time (more slots) increases utilization19

ConclusionFirst work to propose an IT infrastructure for implementing energy-as-a-service for PHEVsPresented token management system (TMS) for managing a large number of PHEVsPresented several scheduling schemes Simulation with a large number of vehicles (several million) and real supply traces 20


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