Multi-objective optimization considering cost, emission and loss objectives using PSO and fuzzy approach

  • Authors

    • S Surender Reddy Woosong University
    2018-07-20
    https://doi.org/10.14419/ijet.v7i3.11203
  • Emission, Evolutionary Algorithm, Fuzzy Approach, Operating Cost, Transmission Loss.

  • A novel approach to solve multi-objective optimization (MOO) problem which aims at minimizing fuel cost, emission release and real power loss of the system simultaneously has been proposed in this paper. Conventional minimum cost operation cannot be the only basis for generation dispatch; emission release minimization and loss minimization must also be taken care of. Power system must be operated in such a way that both active and reactive powers are optimized simultaneously. Reactive powers should be optimized to provide better volt-age profile as well as to reduce system losses. In this paper, the proposed multi-objective optimal power flow (MO-OPF) problem is solved using particle swarm optimization (PSO) and Fuzzy satisfaction maximization approach. In this paper, it is assumed that the decision maker has imprecise or fuzzy goals of satisfying all the objectives, and the proposed problem is thus formulated as a fuzzy satisfaction maximization problem which is basically a min-max problem. It is an efficient technique to obtain trade-off solution for the proposed optimization problem. The MO-OPF problem is tested on IEEE 30 bus, 6 generator system. The obtained results are found to be effective for the MO-OPF problem.

     

     

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    Surender Reddy, S. (2018). Multi-objective optimization considering cost, emission and loss objectives using PSO and fuzzy approach. International Journal of Engineering & Technology, 7(3), 1552-1557. https://doi.org/10.14419/ijet.v7i3.11203