OPF with Environmental Constraints with Multi Shunt Dynamic Controllers using Decomposed Parallel GA : Application to the Algerian Network

다국어 초록 (Multilingual Abstract)

Due to the rapid increase of electricity demand, consideration of environmental constraints in optimal power flow (OPF) problems is increasingly important. In Algeria, up to 90% of electricity is produced by thermal generators (vapor, gas). In order to keep the emission of gaseous pollutants like sulfur dioxide (SO2) and Nitrogen (NO2) under the admissible ecological limits, many conventional and global optimization methods have been proposed to study the trade-off relation between fuel cost and emissions. This paper presents an efficient decomposed Parallel GA to solve the multi-objective environmental/economic dispatch problem. At the decomposed stage the length of the original chromosome is reduced successively and adapted to the topology of the new partition. Two subproblems are proposed: the first subproblem is related to the active power planning to minimize the total fuel cost, and the second subproblem is a reactive power planning design based in practical rules to make fine corrections to the voltage deviation and reactive power violation using a specified number of shunt dynamic compensators named Static Var Compensators (SVC). To validate the robustness of the proposed approach, the algorithm proposed was tested on the Algerian 59-bus network test and compared with conventional methods and with global optimization methods (GA, FGA, and ACO). The results show that the approach proposed can converge to the near solution and obtain a competitive solution at a critical situation and within a reasonable time.

목차 (Table of Contents)

• Abstract
• 1. Introduction
• 2. Optimal Power Flow Formulation
• 3. Reactive Power Dispatch
• 4. Shunt facts modeling
• 5. Strategy of the Efficient Parallel GA for OPF
• 6. Application Study
• 7. Conclusion
• References

참고문헌 (Reference)

1 G. B Sheble, "Refined genetic algorithm-economic dispatch exemple" 10 (10): 117-124, 1995

2 R. L. Haupt, "Practical Genetic Algorithms" John Willey & Sons 2004

3 R. C. Bansal, "Otimization methods for electric power systems: an overview" 2 (2): 1-23, 2005

4 K. Zehar, "Optimal power flow with envirenmental constraint using a fast successive linear programming algorithm: application to the algerian power system" Elsevier 49 : 3362-3366, 2008

5 A. Saini, "Optimal power flow soultion: a GA-Fuzzy system approach" 5 (5): 1-21, 2006

6 B. Mahdad, "Optimal power flow of the algerian network using genetic algorithm/fuzzy rules" IEEE/PES 1-8, 2008

7 T. Bouktir, "Optimal power flow of the Algerian electrical network using ant colony optimization method" 43-57, 2005

8 B. Mahdad, "Optimal power flow for large-scale power system with shunt FACTS using fast parallel GA" 669-676, 2008

9 A. G. Bakistzis, "Optimal power flow by enhanced genetic algorithm" 17 (17): 229-236, 2002

10 O. Alsac, "Optimal load flow with steady state security" 745-751, 1974

11 G. Dhaoyun, "Optimal active power flow incorporating FACTS devices with power flow constraints" 20 (20): 321-326, 1998

12 B. Mahdad, "Methodology based in practical fuzzy rules coordinated with asymetric dynamic compensation applied to the unbalanced distribution network" 3 (3): 145-153, 2007

13 B. Sttot, "Linear programming for power system network security applications" PAS-98 : 837-848, 1979

14 S. N. Sivanandam, "Introduction to Genetic Algorithm" Springer-Verlag 2008

15 J. A. Momoh, "Improved interior point method for OPF problems" 14 : 1114-1120, 1999

16 B. Mahdad, "Fuzzy controlled genetic algorithm for environmental/economic dispatch with shunt FACTS devices" IEEE/PES 10-8, 2008

17 B. Mahdad, "Flexible methodology based in fuzzy logic rules for reactive power planning of multiple shunt FACTS devices to enhance system loadability" IEEE 1-6, 2007

18 M. A. Abido, "Environmental/economic power dispartch using multi-objective evoulutionary algorithm" 18 (18): 1529-1537, 2002

19 C. R. Feurt-Esquivel, "Efficient object oriented power systems software for the analysis of large-scale networks containing FACTS controlled branches" 13 (13): 464-472, 1998

20 M. Varadarajan, "Differential evolutionary algorithm for optimal reactive power dispatch" Elsevier 30 : 435-441, 2008

21 M. Todorovski, "An initialization procedure in solving optimal power flow by genetic algorithm" 21 (21): 480-487, 2006

22 M. Huneault, "A survey of the optimal power flow literature" 6 (6): 762-770, 1991

23 M. A. Abido, "A new multi-objective algorithm for environmental/economic power dispatch" 1263-1268, 2001