Introduction The environment ACDC Support Adaption to demand Adaption to failures Conclusions Supportive Consensus for Smart Grid Management Miguel Rebollo C. Carrascosa A. Palomares Univ. Politècnica de València (Spain) CITINET ’14 Lucca, September 2014 M. Rebollo et al. (UPV) CITINET’14 Supportive Consensus for Smart Grid Management
Slides for the 3rd International Workshop on Citizen Networks (CitiNet'14), at ECCS. Lucca, September 2014
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Introduction The environment ACDC Support Adaption to demand Adaption to failures Conclusions
Supportive Consensus for Smart Grid Management
Miguel Rebollo C. Carrascosa A. Palomares
Univ. Politècnica de València (Spain)
CITINET ’14Lucca, September 2014
M. Rebollo et al. (UPV) CITINET’14Supportive Consensus for Smart Grid Management
Introduction The environment ACDC Support Adaption to demand Adaption to failures Conclusions
Energy management problem
MotivationSmart cities depend on a smart grid to ensure resilient delivery ofenergy to supply their functions
intelligent components connected in some network structurelarge scale → avoid information overloaddecentralized and distributed control mechanisms
M. Rebollo et al. (UPV) CITINET’14Supportive Consensus for Smart Grid Management
Introduction The environment ACDC Support Adaption to demand Adaption to failures Conclusions
Our proposal
The challengeCreate a self-adaptive system that adapts itself to the electricaldemand using local information.
What is done. . .combination of gossip protocols to spread information todirect neighborssupportivereal-time adaption to changes in the demandfailure tolerant
M. Rebollo et al. (UPV) CITINET’14Supportive Consensus for Smart Grid Management
Introduction The environment ACDC Support Adaption to demand Adaption to failures Conclusions
The city
M. Rebollo et al. (UPV) CITINET’14Supportive Consensus for Smart Grid Management
Introduction The environment ACDC Support Adaption to demand Adaption to failures Conclusions
Districts
M. Rebollo et al. (UPV) CITINET’14Supportive Consensus for Smart Grid Management
Introduction The environment ACDC Support Adaption to demand Adaption to failures Conclusions
Population density
M. Rebollo et al. (UPV) CITINET’14Supportive Consensus for Smart Grid Management
Introduction The environment ACDC Support Adaption to demand Adaption to failures Conclusions
Power supply network
M. Rebollo et al. (UPV) CITINET’14Supportive Consensus for Smart Grid Management
Introduction The environment ACDC Support Adaption to demand Adaption to failures Conclusions
The model
M. Rebollo et al. (UPV) CITINET’14Supportive Consensus for Smart Grid Management
Introduction The environment ACDC Support Adaption to demand Adaption to failures Conclusions
Consensus
what is it?
M. Rebollo et al. (UPV) CITINET’14Supportive Consensus for Smart Grid Management
Introduction The environment ACDC Support Adaption to demand Adaption to failures Conclusions
Consensus
what is it used for?
M. Rebollo et al. (UPV) CITINET’14Supportive Consensus for Smart Grid Management
Introduction The environment ACDC Support Adaption to demand Adaption to failures Conclusions
Consensus process
1.each node has an initial value
1 2
3 4
x1 = 0.4 x2 = 0.2
x3 = 0.3 x4 = 0.9
x1 = 0.4
M. Rebollo et al. (UPV) CITINET’14Supportive Consensus for Smart Grid Management
Introduction The environment ACDC Support Adaption to demand Adaption to failures Conclusions
Consensus process
2.the value is passed to the
neighbors
1 2
3 4
x1 = 0.4 x2 = 0.2
x3 = 0.3 x4 = 0.9
x1 = 0.4
x1 = 0.4x1 = 0.4
M. Rebollo et al. (UPV) CITINET’14Supportive Consensus for Smart Grid Management
Introduction The environment ACDC Support Adaption to demand Adaption to failures Conclusions
Consensus process
3.the values from the neighbors
are received
1 2
3 4
x1 = 0.4 x2 = 0.2
x3 = 0.3 x4 = 0.9
x2 = 0.2
x4 = 0.9x3 = 0.3
M. Rebollo et al. (UPV) CITINET’14Supportive Consensus for Smart Grid Management
Introduction The environment ACDC Support Adaption to demand Adaption to failures Conclusions
Consensus process
4.the new value is calculated by
x(t+1) = x(t)+ε∑j∈Ni
[xj(t)− xi(t)]
where ε < mini1di
1 2
3 4
x1 = 0.45 x2 = 0.425
x3 = 0.325 x4 = 0.6
x1 = 0.4
M. Rebollo et al. (UPV) CITINET’14Supportive Consensus for Smart Grid Management
Introduction The environment ACDC Support Adaption to demand Adaption to failures Conclusions
Consensus process
0 5 10 15 20 25 300
0.1
0.2
0.3
0.4
0.5
0.6
0.7
x = 0.45
M. Rebollo et al. (UPV) CITINET’14Supportive Consensus for Smart Grid Management
Introduction The environment ACDC Support Adaption to demand Adaption to failures Conclusions
Data aggregation protocols
consensus can not calculate aggregate valuesconsensus belongs to a broader family of protocols
Distribution of the relative error for a random demand
M. Rebollo et al. (UPV) CITINET’14Supportive Consensus for Smart Grid Management
Introduction The environment ACDC Support Adaption to demand Adaption to failures Conclusions
Adaption to failures
350 375 400 425 4505800
6000
6200
6400
6600
6800
7000
#epochs
erro
r rat
e
Evolution after a change in the demand
M. Rebollo et al. (UPV) CITINET’14Supportive Consensus for Smart Grid Management
Introduction The environment ACDC Support Adaption to demand Adaption to failures Conclusions
Adaption to failures
350 375 400 425 4505800
6000
6200
6400
6600
6800
7000
#epochs
erro
r rat
e
Evolution after a change in the demand
350 400 450 500 5501.38
1.4
1.42
1.44
1.46
1.48
1.5 x 104
#epochs
erro
r rat
e
Evolution after the failure of one substation
M. Rebollo et al. (UPV) CITINET’14Supportive Consensus for Smart Grid Management
Introduction The environment ACDC Support Adaption to demand Adaption to failures Conclusions
Adaption to failures
200 400 600 800 1000 1200 1400 1600 1800 2000−20
−10
0
10
20
#epochs
erro
r rat
e
Comparitions of the evolution of the error rate (Llucmajor substation failure)
no failuressubstat faildifference
M. Rebollo et al. (UPV) CITINET’14Supportive Consensus for Smart Grid Management
Introduction The environment ACDC Support Adaption to demand Adaption to failures Conclusions
Conclusions
What we’ve doneTo apply a combination of gossip methods to create a supportive,failure tolerant, self-adaptive system for smart-grids
information exchanged with direct neighbors onlyno global repository of data nor central control neededpush-sum and consensus protocol combinedsupportive for nodes out of their boundsthe network adapts itself to changes in the electrical demandfailures are detected and assumed by the rest of activesubstations
M. Rebollo et al. (UPV) CITINET’14Supportive Consensus for Smart Grid Management