Multi-group particle swarm optimisation for transmission expansion planning solution based on LU decomposition

As power systems are being highly stressed with the boost of loading levels and the introduction of new generation sources, transmission expansion planning (TEP) has regained its significance as a pivotal problem to be solved. To ameliorate the performance on both efficiency and accuracy for the solution of TEP from the aspect of algorithm design, a static DC TEP without generation redispatch is investigated by the proposed multi-group particle swarm optimisation (MGPSO) algorithm. MGPSO is based on the discrete PSO framework with several beneficial enhancements involved, such as Sobol sequence initialisation method, multi-group co-evolution strategy, and mutation mechanism. For the solution of linear programming subproblem within the framework of MGPSO, a linear equation system is extracted and then addressed with efficient LU decomposition approach. Case studies have been implemented on five classical benchmarks, ranging from 6-bus to 118-bus, between the MGPSO and commercial software Lingo 11.0 to validate the superiority of MGPSO. Speedup analysis as well as performance evaluation of different acceleration strategy involved in MGPSO are implemented and discussed.

[1]  A. Monticelli,et al.  Test systems and mathematical models for transmission network expansion planning , 2002 .

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

[3]  P. Murugan,et al.  Modified particle swarm optimisation with a novel initialisation for finding optimal solution to the transmission expansion planning problem , 2012 .

[4]  Rahmat-Allah Hooshmand,et al.  Comprehensive review of generation and transmission expansion planning , 2013 .

[5]  Jose Roberto Sanches Mantovani,et al.  Efficient linear programming algorithm for the transmission network expansion planning problem , 2003 .

[6]  Eduardo N. Asada,et al.  Constructive heuristic algorithm in branch-and-bound structure applied to transmission network expansion planning , 2007 .

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

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

[9]  Haozhong Cheng,et al.  New discrete method for particle swarm optimization and its application in transmission network expansion planning , 2007 .

[10]  Jose Roberto Sanches Mantovani,et al.  Branch and bound algorithm for transmission system expansion planning using a transportation model , 2000 .

[11]  João Tomé Saraiva,et al.  A discrete evolutionary PSO based approach to the multiyear transmission expansion planning problem considering demand uncertainties , 2013 .

[12]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[13]  El-Ghazali Talbi,et al.  GPU Computing for Parallel Local Search Metaheuristic Algorithms , 2013, IEEE Transactions on Computers.

[14]  Robert E. Tarjan,et al.  Depth-First Search and Linear Graph Algorithms , 1972, SIAM J. Comput..

[15]  Ruben Romero,et al.  Transmission system expansion planning by simulated annealing , 1995 .

[16]  L. L. Garver,et al.  Transmission Network Estimation Using Linear Programming , 1970 .

[17]  Haozhong Cheng,et al.  Active distribution network expansion planning integrating dispersed energy storage systems , 2016 .

[18]  Masoud Rashidinejad,et al.  A PSO based approach for multi-stage transmission expansion planning in electricity markets , 2014 .

[19]  R. Ravi,et al.  Complexity of transmission network expansion planning , 2014 .

[20]  Tao Zhang,et al.  Model predictive control-based operation management for a residential microgrid with considering forecast uncertainties and demand response strategies , 2016 .

[21]  Ivo Chaves da Silva Junior,et al.  Static planning of the expansion of electrical energy transmission systems using particle swarm optimization , 2014 .

[22]  Akbar Ebrahimi,et al.  Inclusion of Blackouts Risk in Probabilistic Transmission Expansion Planning by a Multi-Objective Framework , 2015, IEEE Transactions on Power Systems.

[23]  D. J. Hill,et al.  A New Strategy for Transmission Expansion in Competitive Electricity Markets , 2002, IEEE Power Engineering Review.

[24]  H. Shayeghi,et al.  An improved DPSO with mutation based on similarity algorithm for optimization of transmission lines loading , 2010 .

[25]  Mohammad Tavakoli Bina,et al.  Approximated MILP model for AC transmission expansion planning: global solutions versus local solutions , 2016 .

[26]  S. Binato,et al.  Transmission network expansion planning under a Tabu Search approach , 2001 .

[27]  Jose L. Rueda,et al.  Performance comparison of heuristic optimization methods for optimal dynamic transmission expansion planning , 2014 .

[28]  Ebrahim Mortaz,et al.  Transmission expansion planning using multivariate interpolation , 2015 .