Power System Stabilizers Tuning using Bio-Inspired Algorithm
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Transcript of Power System Stabilizers Tuning using Bio-Inspired Algorithm
Power System Stabilizers Tuning using Bio-Inspired Algorithm
AUTHORS:
Wesley Peres – Edimar Oliveira
João A. Passos Filho – Diego Arcanjo – Ivo Chaves Junior
Federal University of Juiz de Fora – Brazil
June, 2013
Outline
1. Introduction;
2. Proposed Methodology;
3. Results;
4. Conclusion.
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Introduction
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• Frequency and amplitude problems; • Size and non-linearity; • Operating condition.
Power System Oscillation Damping has been the subject of many studies.
System Loads...
.
.
.
GH1
GH2
GHn
GT1 GT2
GTk
Hydroelectric Generators
Thermoelectric Generators
Introduction
Some Controllers include:
– Automatic Voltage Regulator (AVR);
– FACTS;
– HVDC Links.
Power System Stabilizers (PSS).
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Introduction
Tuning techniques:
– Linear Techniques;
– Bio-Inspired Algorithm…
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PSS(s) : in a feedback loop (Additional Control Signal) P(s) : open-loop transfer function
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• The objective in this work is to evaluate a Bio-Inspired Algorithm for tuning multiple PSSs.
• Modified Cuckoo Search (MCS) technique to achieve this goal.
Objective
Problem Formulation
State Space Equations frequency domain
A damping ratio is associated with each eigenvalue:
PacDyn (CEPEL)
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Problem Formulation
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Determine the system stability:
j
Unstable Condition
Problem Formulation
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j
Stable Condition
Problem Formulation
PSS
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PSS Structure
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Tw = 5 NB = 3 values from the literature for the New England Test System.
PSS Parameters
• Each solution is represented by a vector considering the set of PSS to be tuned.
• p stabilizers are tuned.
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Lead Lag Stage Gain
Set of Operating Conditions
• For the tuning a set of closed-loop eigenvalues are obtained for over pre-specified operating conditions:
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Fitness Function associated with the PSS tuning
Optimization Problem
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The solution provides the best tuning for all PSSs.
Variables limits
Metaheuristic
Inspired
CUCKOO SEARCH TECHNIQUE
Reproduction Strategy
Nest Parasitism
Other birds nest
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CUCKOO SEARCH TECHNIQUE
Consequencesof
Parasitism Egg is
discovered
Egg is not discovered
Nest will be abandoned or egg will
be destroyed
Egg will be hatch and
Cuckoo will survive
16 Cuckoos need to find a good host.
Modified Cuckoo Search (MCS)
• In this work: cuckoo = egg = nest = prob. solution.
• First Change: Cuckoos are divided into two groups
• Group of Top Eggs:
– Individuals (eggs) with the best fitness;
– A new egg of this group is generated by using two eggs from this group (information exchange).
• Group of eggs to be replaced:
– This group is composed of eggs that will be replaced.
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Modified Cuckoo Search (MCS)
• Generating new solutions:
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Encourage localized search improving the optimal solution.
Lévy distribution: the probability of returning to a
site previously visited.
t: generation number
Results • The New England test system is used:
– 39 AC-buses; – 10 Power generators; – 9 PSS should be tuned.
• Settings:
– Population size: 15 individuals – Convergence Criterion: 250 generations. – Top eggs group = 25% and 75% to the replaced group
• The results obtained by using MCS are with Genetic Algorithm;
• MCS and GA are initialized with the same solution.
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Results
• Four operating conditions without PSS:
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Results
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Results
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5 simulations for each methodology.
Results
• Minimum Damping Ratio(%)
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MCS leads the system to a higher stability condition.
Results
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• MCS uses only two parameters: size of population and percentage of top group;
• The results obtained with the proposed methodology are consistent with results from literature;
• The use of MCS presented promising results for tuning stabilizers and damping power system oscillations.
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Conclusions
Acknowledgments
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