1. Algerian Large Electrical Network Conference
PAPER-32
Optimal Power Flow Solution in Presence of Wind Power in Adrar Region Using Cuckoo Search Algorithm
Centre de Développement des Energies Renouvelables
Laboratoire de Recherche en Electrotechnique, Ecole Nationale Polytechnique

2. CONTENTS INTRODUCTION ECONOMIC-ENVIRONMENT OPF WHAT IS CUCKOO SEARCH?
Results
Conclusion

3. INTRODUCTION
Our paper proposes Cuckoo Search Algorithm for solving optimal power flow dispatching incorporating three future wind farms in the isolated Adrar power system.
The proposed approach is applied to best locate the active power by minimizing a multi-objective function involving the fuel cost, the availability of wind power generation and the NOx emission.
To cope with the random and uncontrollability of the wind speed, the maximal probable active power output of the wind turbines is estimated computing the wind speed carried maximum energy.

4. Economic-Environment OPF
Fuel cost
Wind farm cost
NOx Emission
Maximum Probable Wind Power Output

5. Economic-Environment OPF
OPF is mathematically formulated by establishing a multi-objective function that sums the operating costs of available energy from thermal or wind energy generations and NOx emission.
We note that
Fuel cost and NOx emission

6. Wind Generation Cost Evaluation
Penalty cost for not using the total available wind power.
Reserve cost arising out of over estimation of wind power.

7. Overestimation Underestimation
Cost associated with wind power shortage
This cost depends on how much is the deficit in power and the probability of the occurrence of deficit for a given scheduled power.
Cost associated with wind power surplus
It represents a penalty cost for not exploiting the all available resource.

8. Wind speed carrying maximum energy
Maximum Probable Wind Power Output
The wind speed distribution can be modeled by Weibull PDF
Wind speed carrying maximum energy
Taking into account the intermittent of the wind speed, the maximum probable active wind power generation is estimated by computing the wind speed carried maximum energy.

9. Cuckoo Search Algorithm

10. Overview
Cuckoo behavior
Representations
Cuckoo Rules and Parameters

11. Overview Cuckoo Search Algorithm
Cuckoo search is an optimization algorithm developed by Xin-she Yang and Suash Deb in 2009.
It was inspired by the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds of other species.

12. Cuckoo Search Algorithm
Cuckoo behavior

13. Representation Cuckoo Search Algorithm
Each egg in a nest represents a solution, and a cuckoo egg represents a new solution.
The aim is to use the new and potentially better solutions, to replace a not-so-good solution in the nests.
The simplest form, each nest has one egg. The algorithm can be extended to more complicated cases in which each nest has multiple eggs representing a set of solutions.

14. Cuckoo Rules and Parameters
Cuckoo Search Algorithm
Cuckoo Rules and Parameters
Each cuckoo lays one egg at a time, and dumps it in a randomly chosen nest.
The best nests with high quality of eggs (solutions) will carry over to the next generations.
The number of available host nests is fixed, and a host can discover an alien egg with a probability pa ∈ [0, 1]. In this case, the host bird can either throw the egg away or abandon the nest so as to build a completely new nest in a new location.

15. Isolated Adrar Power System

16. Hypothesis Parameters of CSA Parameter of the wind power generation
Number of nests (or different solutions)=10
Discovery rate of alien eggs/solutions pa=0.25
Parameter of the wind power generation
Wind speeds carried maximum energy =11.36 m/s
Maximum probable wind power output = 6.3 MW
kpi=0.03 $/MWh
kri=0.03 $/MWh
Cases Study
Case1: w1= w2=0
Case 2: w1= w2=0.5
Case 3: w1= w2=1

17. Results

18. Results Fig.1 Variation of total fuel cost total
Fig.2 Variation of NOx emission
Fig.3 Variation of total wind cost
Fig.4 Variation of total fitness

19. Results

20. Conclusion

21. Conclusion
In this paper, CSA is applied to solve optimal power dispatch of the isolated Adrar’s power system consisting of five gas turbines units and in presence of three new wind farms of Gamesa G52 type expected for the horizon 2015.
The CSA predicts accurate results while satisfying all inequality and equality constraints. This algorithm has achieved fast convergence in term of the number of iteration and duration time taken.
In conclusion, the CSA can be very effectively applied to solve a real environmentally economic optimal power flow dispatch problem.

22. References
[1] L.B.Shi, C.Wang , L.Z.Yao, Y.X.Ni, and M.Bazargan “Optimal power flow solution incorporating wind power”, no.2, pp , June. 2012). (IEEE Systems Journal,  vol.6
[2] X.S.Yang, and S.Deb “Cuckoo search via Lévy flights” (in: Proc. Of World Congress on Nature & Biologically Inspired Computing (NaBIC 2009), pp , Coimbatore, India, 9-11 Dec. 2009).

23. Centre de Développement des Energies Renouvelables
ACKNOWLEDGMENTS
The authors deeply appreciate the support of Opérateur du Système Electrique (OS-SONELGAZ) for providing the power system data.

24. Thank you for your attention
CAGRE'15
Algerian Large Electrical Network Conference
Thank you for your attention
Centre de Développement des Energies Renouvelables
Laboratoire de Recherche en Electrotechnique, Ecole Nationale Polytechnique