Research on Multi-Objective Transmission Planning in Electricity Markets

Yang Liu; Xu Liu; Feng Xian Cui; Liang Gao

doi:10.4028/www.scientific.net/AMR.516-517.1429

Paper Titles

Power Factor Optimization of Distributed Generations in Distribution Networks Based on Improved Particle Swarm Optimization Method
p.1408

Power Line Carrier-Based Networking Technology of the Internet of Things
p.1414

Power Quality Enhancement Using a Novel Hybrid Active Power Filter Device Under Nonlinear Loads
p.1419

Research on Loss Allocation of Power Distribution Network Based on Power Flow Tracing
p.1425

Research on Multi-Objective Transmission Planning in Electricity Markets
p.1429

Spatial Load Forecasting of Distribution Network Based on Intuitionistic Fuzzy Entropy and Fuzzy Clustering
p.1433

Study on Grid-Injected System with Regenerative Braking Energy for Subway
p.1437

Study on the Optimal Allocation Method of Distributed Generation Capacity
p.1443

The Influence of Multiple Low Frequency Oscillations on Power Transmission Capability and Their Solutions
p.1448

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 516-517Research on Multi-Objective Transmission Planning...

Research on Multi-Objective Transmission Planning in Electricity Markets

Abstract:

Abstract. Transmission planning is a complex optimization problem with multiple deciding variables and restrictions. The mathematical model is non-linear, discrete, multi-objective and dynamic. It becomes complicated as the system grows. So the algorithm adopted affects the results of planning directly. In this paper, a fast non-dominated sorting genetic algorithm (NSGA-II) is employed. The results indicate that NSGA-II has some advantages compared to the traditional genetic algorithms. In transmission planning, NSGA-II is feasible, flexible and effective.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 516-517)

Pages:

1429-1432

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.516-517.1429

Citation:

Cite this paper

Online since:

May 2012

Authors:

Yang Liu, Xu Liu, Feng Xian Cui, Liang Gao

Keywords:

Congestion Cost, Electricity Market, NSGA-II, Transmission Planning

Export:

RIS, BibTeX

Price:

Permissions:

Request Permissions

References

[1] R.C.G. Teive E.L. Silva L.G.S. Fonseca.A cooperative expert system for transmission expansion planning of electrical power systems[J].IEEE Transactions Power Systems,May, 13(2):636-642.( 1998)

DOI: 10.1109/59.667393

Google Scholar

[2] H.Rudnick,R.Palma,E.Cura,et al.Economically adapted transmission systems in open access schemes–application of genetic algorithms[J].IEEE Transactions on Power Systems, Aug. 11(3):1427-1440.( 1996)

DOI: 10.1109/59.535684

Google Scholar

[3] Haibao Xu, Haozhong Cheng,Ganyun Lv. Ants Cross Algorithm in Multi-phase Transmission Planning. Power System Automation, 28(20):37-42.( 2004). (In Chinese)

Google Scholar

[4] Jiasheng Hu, Chuangxin Guo, Bin Ye. Application of Scatter Grain Cross in Multi-phase Transmission Planning. Power System Automation, 28(20):31-36.(2004).( In Chinese)

Google Scholar

[5] S.Binato G.C. Oliveira J.L. Araujo.A greedy randomized adaptive search procedure for transmission expansion planning[J].IEEE Transactions on Power Systems, May,16(2):247-253.( 2001)

DOI: 10.1109/59.918294

Google Scholar

[6] F.Wen C.S. Chang.Transmission network optimal planning using the tabu search method[J].Electric Power Systems Research,Aug. 42:153-163.( 1997)

DOI: 10.1016/s0378-7796(96)01200-x

Google Scholar