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

Smruti 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) Choi2012-06-07

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Contents

•Overview•System Model•Problem Formulation •Proposed System•Evaluation•Conclusion

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Overview

•Challenges▫Charging and discharging a large number

of PHEVs▫Supply and demand should closely match

Lower supply: outage Higher supply: waste

▫Intermittent source of sustainable energy sources

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Overview• Contribution

▫ “token”: currency of energy gt: generation token ct: consumption token Attributes: ID, type, gen/

con, power level, duration, start and expiration time, status

Energy = power *duration▫ Token entitles owner to pro-

duce or consume a certain amount of electrical energy

▫ How to schedule tokens? LM: Creates and Modifies

tokens TMS: “Admit and Schedule“

or “Reject” tokens

Token Management System (TMS)Local Module (LM)

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Research Objective• Goal: Maximize utilization

• Utilization = total consumption / total gener-ation

• Token Utilization = total energy of the se-lected consTokens / total energy of the genTokens

•Application-Level communication protocol

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Problem Formulation• (1) maximizes the average uti-

lization▫ = total energy of the se-

lected consTokens / total en-ergy of the genTokens.

• (2) for every point in the ac-tivation time of a genToken, the sum of the power levels of the packed consToken in-stances 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 packed

time

power

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Proposed Token Management System

• Formulated Problem▫Packing Problem NP-Complete▫Not feasible to handle a large number of PHEVs

• Proposed▫Heuristic algorithm

Token (1) batching, (2) prioritization, and (3) splitting▫My Opinion: “Greedy algorithm based on Priority?”

Schedule based on set priority If cannot be scheduled, split and schedule again

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Cons-Token Batches- Based on start time and duration- MAX_BATCH_SIZE- Reduce computa-tion load

Gen-Token Queue- Prioritization-MAX_GEN_ACTIVE- Ex) FIFO, round-robin on power source, expiration times, power levels

Cons-Token Queue- FIFO

Dispatcher- Packs CT in GT- Packing depend on the scheduling scheme

Scheduling Scheme(active genToken)- endTime- freeEnergy- random- utilization

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Dispatcher Functions• consBatch Activation

▫ Packing consumption batch (cb) to genToken▫ Conditions:

Power level (consBatch) < Power Level (genToken) + constraint (2)

Activation period (consBatch) < validity period (genToken) Otherwise, reject

• genToken Replacement▫ If

utility above a certain threshold no. of rejected tokens above a certain threshold

▫ Then genToken replaced with a token with the highest priority

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Dispatcher Functions• Splitting of consBatch

▫Previously consBatch cannot split

i.e., One consBatch fit into one genToken Difficult to achieve utilization close to 1

▫Now consBatch can split

i.e., different parts of consBatch fit into multiple genTo-kens

First, schedule consBatch as a whole. If not possible, split and schedule smaller consBatches

Proposes three different schemes

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Splitting of ConsBatch (Scheme 1)

• 1-D split on time axis▫ consBatch is split into

two smaller batches on the time axis

▫ ½ duration and validity period

▫ Same power level

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Splitting of ConsBatch (Scheme 2)

• 1-D split on power axis▫ consBatch is split into

two smaller batches on the power axis

▫ ½ power level▫ Same duration and valid-

ity period

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Splitting of ConsBatch (Scheme 3)

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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)

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Evaluation• Setup

▫ Vehicles Number: 0 ~ 7 million

▫ Power Trace: Australian Power Grid supply (5 years) 10% available for PHEVs

▫ Vehicle Connectivity: following previous references Capacity: 10-15 kWh Charging Speed: 25 kW (20-30 min charging)

▫ Token duration(genToken) = 8 h (no frequent on/off) duration(consToken) = 24 min

▫ consBatch Size = 100

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Evaluation• Effect of consToken dura-

tion▫ 2% best / 100% worst▫ Smaller fragments give

better utilization

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EvaluationEffect of Splitting Algo-rithmSmall consTokens (5%)

Effect of Splitting Algo-rithmLarge consTokens (30%)

improve-ment

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Evaluation

•Other results▫Scheduling

Small no. of PHEVs Deadline based prioritization performs best

Large no. of PHEVs Power level based prioritization performs best Large number of consTokens Contention between consTokens for packing Larger power helps to pack better

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Evaluation• Other results

▫Validity Period Longer consToken use duration increases utilization More flexible start time (more slots) increases utiliza-

tion

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Conclusion

•First work to propose an IT infrastructure for implementing energy-as-a-service for PHEVs

•Presented token management system (TMS) for managing a large number of PHEVs

•Presented several scheduling schemes •Simulation with a large number of vehi-

cles (several million) and real supply traces