Transcript smart grid

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*Power distribution becomes an important issue when
power demand exceeds power supply .
*As electric vehicles get more popular, for a period of time,
there could be a shortage of power generating facilities. In
order to allow the use of electric vehicles grow at a normal
rate, it is necessary to look for some techniques to charge
all vehicles as fairly as possible.
*Our objective is to find out and compare different types of
fairness schemes so as to meet the customers’ needs to a
great extent.
*
Week
Tasks
1, 2, (Jan 30 – Feb 10) Background reading and literature
review
3,4, (Feb 13 – Feb 24) Simulate a baseline charging system
5, 6 (Feb 27 – Mar 9) Implement different types of fairness;
8, (Mar 19 – Mar 23) Each of us is responsible for one
specific fairness scheme.
9,10, (Mar 26 – Apr 6) Compare the results and make some
conclusions.
11,12,13, (Apr 9 – Apr Write a technical paper.
27)
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1. Set up simulation environment:
*information of electric vehicles
*charging habits
*power on smart grid
2. Realize the basic fairness scheme – Round Robin
3. Obtain some results using two metrics:
*the fraction of electric vehicles without sufficient charge on
departure
*the average departure delay
*
1. Set up information of electric vehicles
*Battery limit: 100 miles – 28kwh
*Charge mode: 120V 15A – 1.8kw or nearly 6.5miles at
maximum power
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1. Set up charging habits
*Total number of person leaving home to go to work
every half hour during a day  time shift (8am corresponds
to 6pm)
*The arrival of electric vehicles is poison process: arrival
rate  interarrival time satisfies exponential distribution.
*Plug-in time for an electric vehicle is Gaussian distribution
truncated to 2 deltas. (mean=14 delta=4, unit: hour)
*The departure process is obtained accordingly.
*
1. Set up charging habits – contd.
*Desired distance satisfies exponential distribution
truncated to [20, 90] miles  desired energy
*Current battery level is uniformly distributed between
0% to 30% of full battery energy.
*Energy needed is calculated based on demand  the
amount of charging periods (5 minute switch on/off
intervals) for each electric vehicle
*
1. Set up power
*Summer daily load profile sampled hourly.
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1. Set up power – contd.
*Peak ratio  supplied power peak ratio =
maximum load during a day
supplied power
*Penetration  available power per hour  available
power per 5 minute penetration =
power available for charging electric vehicles
power needed for charging electric vehicles
*Charge mode  the number of electric vehicles that is
able to be charged per 5 minute
*Daily power distribution  power distribution for a
period
*
2. Realize the basic fairness scheme – Round Robin
*Round Robin based system works in the way that – If 20 cars
waited to be charged, and the power company can merely
charge 15, then in the first 5 minute it will charge cars 1 to 15,
in the second cars 16 to 20 and 1 to 10, in the third cars 11 to
20 and 1 to 5, and so on so forth.
*Eventually each car receives the same charge.
*In real implementation, run round robin every 5 minute to
achieve real-time coordination.
*Two cases: sufficient power/ insufficient power for all cars in
the waiting list
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2. Round Robin algorithm
*Create a waiting list based upon arriving times of the cars
that need to be charged.
*Check which of the two cases applied.
*Charge a fixed number of cars in the front of the waiting list.
*Update the cars’ information.
*Update the waiting list: adding new arrivals, removing the
cars that finish charging and reordering the waiting list.
*
3. Obtain some results using two metrics:
*Run the baseline system for successive 𝑛 days.
*Take the measurements from the 4𝑡ℎ day to ensure correct
and reasonable initializations.
*Take the measurements till (𝑛 − 2)𝑡ℎ day to enforce all
cars departing by the end of measurements, so that we can
tell the particular delay for a car if its departure is delayed.
*Two metrics with tuned input arguments: number of days
and penetration
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