Transmission expansion planning by meta-heuristic techniques: A comparison of Shuffled Frog Leaping Algorithm, PSO and GA

This paper presents the application of a memtic meta-heuristic optimization technique known as Shuffled Frog Leaping Algorithm (SFLA) to the problem of transmission network expansion planning. The main objective of the proposed problem is to minimize total cost by finding the place, number and type of new transmission lines required to ensure that the power system meets the forecasted demand in the most economic and reliable way. The proposed static transmission expansion planning problem is formulated as a mixed integer programming optimization problem to minimize the total cost comprised of investment cost of building new lines, congestion costs and the cost of load curtailment due to contingencies. The proposed algorithm has been successfully applied to IEEE RTS 24-bus test system and the performance of the proposed algorithm has been compared with other heuristic optimization techniques such as particle swarm optimization (PSO) and Genetic Algorithm (GA). The comparison results testify to the feasibility and efficiency of the developed algorithm in solving the transmission expansion planning problem.

[1]  Malcolm Irving,et al.  Differential evolution algorithm for static and multistage transmission expansion planning , 2009 .

[2]  G.B. Shrestha,et al.  Congestion-driven transmission expansion in competitive power markets , 2004, IEEE Transactions on Power Systems.

[3]  Min Xie,et al.  Multiyear Transmission Expansion Planning Using Ordinal Optimization , 2007, IEEE Transactions on Power Systems.

[4]  M. Shahidehpour,et al.  Congestion-Driven Transmission Planning Considering the Impact of Generator Expansion , 2008, IEEE Transactions on Power Systems.

[5]  Donald E. Grierson,et al.  Comparison among five evolutionary-based optimization algorithms , 2005, Adv. Eng. Informatics.

[6]  M. Shahidehpour,et al.  Market-Based Coordination of Transmission and Generation Capacity Planning , 2007, IEEE Transactions on Power Systems.

[7]  B. Vahidi,et al.  Bacterial Foraging-Based Solution to the Unit-Commitment Problem , 2009, IEEE Transactions on Power Systems.

[8]  G B Gharehpetian,et al.  Unit Commitment Problem Solution Using Shuffled Frog Leaping Algorithm , 2011, IEEE Transactions on Power Systems.

[9]  Muzaffar Eusuff,et al.  Shuffled frog-leaping algorithm: a memetic meta-heuristic for discrete optimization , 2006 .

[10]  E. da Silva,et al.  Transmission network expansion planning under an improved genetic algorithm , 1999, Proceedings of the 21st International Conference on Power Industry Computer Applications. Connecting Utilities. PICA 99. To the Millennium and Beyond (Cat. No.99CH36351).

[11]  Tarek Hegazy,et al.  Comparison of Two Evolutionary Algorithms for Optimization of Bridge Deck Repairs , 2006, Comput. Aided Civ. Infrastructure Eng..

[12]  M. Shahidehpour,et al.  A Multi-Objective Framework for Transmission Expansion Planning in Deregulated Environments , 2009, IEEE Transactions on Power Systems.

[13]  Qingzheng Li.  Shuffled Frog Leaping Algorithm Based Optimal Reactive Power Flow , 2009, 2009 International Symposium on Computer Network and Multimedia Technology.

[14]  Probability Subcommittee,et al.  IEEE Reliability Test System , 1979, IEEE Transactions on Power Apparatus and Systems.

[15]  J. Saraiva,et al.  A multiyear dynamic approach for transmission expansion planning and long-term marginal costs computation , 2005, IEEE Transactions on Power Systems.

[16]  Qi Zhao,et al.  An Improved Particle Swarm Optimization Method Based on Borderline Search Strategy for Transmission Network Expansion Planning , 2006, 2006 International Conference on Machine Learning and Cybernetics.

[17]  R D Zimmerman,et al.  MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education , 2011, IEEE Transactions on Power Systems.

[18]  Zhao Yang Dong,et al.  Flexible Transmission Expansion Planning With Uncertainties in an Electricity Market , 2009, IEEE Transactions on Power Systems.

[19]  J. M. Areiza,et al.  Transmission network expansion planning under an improved genetic algorithm , 1999 .

[20]  James Kennedy,et al.  Particle swarm optimization , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

[21]  Jaeseok Choi.  A method for transmission system expansion planning considering probabilistic reliability criteria , 2005, IEEE Transactions on Power Systems.

[22]  G. Latorre,et al.  Classification of publications and models on transmission expansion planning , 2003 .

[23]  Ariovaldo V. Garcia,et al.  Power system transmission network expansion planning using AC model , 2007 .

[24]  S. Dambhare,et al.  An Expert System Approach for Multi-Year Short-Term Transmission System Expansion Planning: An Indian Experience , 2008, IEEE Transactions on Power Systems.

[25]  Ruben Romero,et al.  Transmission network expansion planning with security constraints , 2005 .

[26]  M. Shahidehpour,et al.  Market-based transmission expansion planning , 2004, IEEE Transactions on Power Systems.

[27]  Alireza Rahimi-Vahed,et al.  Solving a bi-criteria permutation flow-shop problem using shuffled frog-leaping algorithm , 2008, Soft Comput..

[28]  J. Contreras,et al.  Transmission Expansion Planning in Electricity Markets , 2008, IEEE Transactions on Power Systems.

[29]  M. H. Javidi,et al.  Transmission Expansion Planning in Competitive Electricity Markets Using AC OPF , 2006, 2006 IEEE PES Power Systems Conference and Exposition.

[30]  M. Shahidehpour,et al.  Transmission Switching in Expansion Planning , 2010, IEEE Transactions on Power Systems.

[31]  R.A. Gallego,et al.  Multistage and coordinated planning of the expansion of transmission systems , 2004, IEEE Transactions on Power Systems.

[32]  Jaeseok Choi,et al.  Transmission Expansion Planning Using Contingency Criteria , 2007, IEEE Transactions on Power Systems.