Distribution system optimization planning based on plant growth simulation algorithm
Tóm tắt
An approach for the integrated optimization of the construction/expansion capacity of high-voltage/medium-voltage (HV/MV) substations and the configuration of MV radial distribution network was presented using plant growth simulation algorithm (PGSA). In the optimization process, fixed costs correspondent to the investment in lines and substations and the variable costs associated to the operation of the system were considered under the constraints of branch capacity, substation capacity and bus voltage. The optimization variables considerably reduce the dimension of variables and speed up the process of optimizing. The effectiveness of the proposed approach was tested by a distribution system planning.
Tài liệu tham khảo
Kagan N, Adams R N. A benders decomposition approach to the multi-objective distribution planning problem [J]. International Journal of Electrical Power & Energy Systems, 1993, 15(5): 259–271.
Vaziri M, Tomsovic K, Bose A. Numerical analyses of a directed graph formulation of the multistage distribution expansion problem [J]. IEEE Trans on Power Delivery, 2004, 19(3): 1348–1354.
Boulaxis N G, Papadopoulos M P. Optimal feeder routing in distribution system planning using dynamic programming technique and GIS facilities [J]. IEEE Trans on Power Delivery, 2002, 17(1): 242–247.
Victor P, Jacques A F, Miguel A, et al. Optimization of electrical distribution feeders using simulated annealing [J]. IEEE Trans on Power Delivery, 2004, 19(3): 1135–1141.
Carrano E G, Soares L A E, Takahashi R H C, et al. Electric distribution network multiobjective design using a problem-specific genetic algorithm [J]. IEEE Trans on Power Delivery, 2006, 21(2): 995–1005.
Ramirez-Rosado I J, Bernal-Agustin J L. Genetic algorithm applied to design of large power distribution system [J]. IEEE Trans on Power Systems, 1998, 13(2): 696–703.
Diaz-Dorado E, Cidrás J, Miguéz E. Application of evolutionary algorithms for the planning of urban distribution networks of medium voltage [J]. IEEE Trans on Power Systems, 2002, 17(3): 879–884.
Carvalho P M S, Ferreira L A F M, Lobo F G, et al. Distribution network expansion planning under uncertainty: A hedging algorithm in an evolutionary approach [J]. IEEE Trans on Power Delivery, 2000, 15(1): 412–416.
Díaz-Dorado E, Pidre J C, García E M. Planning of large rural low-voltage networks using evolution strategies [J]. IEEE Trans on Power Systems, 2003, 18(4): 1594–1600.
Gómez J F, Khodr H M, De Oliveira P M, et al. Ant colony system algorithm for the planning of primary distribution circuits [J]. IEEE Trans on Power Systems, 2004, 19(2): 996–1004.
Ramírez-Rosado I J, Domínguez-Navarro J A. New multiobjective tabu search algorithm for fuzzy optimal planning of power distribution systems [J]. IEEE Trans on Power Systems, 2006, 21(1): 224–233.
Li T, Su W L, Wang C F. A global optimization bionics algorithm for solving integer programming-plant growth simulation algorithm[C] //Proceedings of International Conference on Management Science and Engineering. Harbin, China:[s.n.], 2004: 531–535.
Muanda V, Ranito J V, Pmenqt L M. Genetic algorithms in optimal multistage distribution network planning [J]. IEEE Trans on Power Systems, 1994, 9(4): 1927–1933.