Browsing by Author "Alawode, Kehinde"

Now showing 1 - 3 of 3
  • No Thumbnail Available
    Item
    Open Access
    Multiobjective Optimal Power Flow Using Hybrid Evolutionary Algorithm
    (IEEE, 2010-01) Alawode, Kehinde; Komolafe, Olusola; Abimbola, Jubril
    This paper solves the environmental/ economic dispatch power system problem using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and its hybrid with a Convergence Accelerator Operator (CAO), called the NSGA-II/CAO. These multiobjective evolutionary algorithms were applied to the standard IEEE 30-bus six-generator test system. Several optimization runs were carried out on different cases of problem complexity. Different quality measure which compare the performance of the two solution techniques were considered. The results demonstrated that the inclusion of the CAO in the original NSGA-II improves its convergence while preserving the diversity properties of the solution set.
  • No Thumbnail Available
    Item
    Open Access
    Solving Multi-Objective Economic Dispatch Problem Via Semidefinite Programming
    (IEEE, 2013-08) Abimbola, Jubril; Alawode, Kehinde; Komolafe, Olusola
    This paper presents a solution for multi-objective economic dispatch problem with transmission losses semidefinite programming (SDP) formulation. The vector objective is reduced to an equivalent scalar objective through the weighted sum method. The resulting optimization problem is formulated as a convex optimization via SDP relaxation. The convex optimization problem was solved to obtain Pareto-optimal solutions. The diversity of the solution set was improved by a nonlinear selection of the weight factor. Simulations were performed on IEEE 30-bus, 57-bus, and 118-bus test systems to investigate the effectiveness of the proposed approach. Solutions were compared to those from one of the well-known evolutionary methods. Results show that SDP has an inherently good convergence property and a lower but comparable diversity property.
  • No Thumbnail Available
    Item
    Open Access
    Solving Multi-Objective Economic Dispatch Problem Via Semidefinite Programming
    (IEEE, 2013-08) Abimbola, Jubril; Alawode, Kehinde; Komolafe, Olusola
    This paper presents a solution for multi-objective economic dispatch problem with transmission losses semidefinite programming (SDP) formulation. The vector objective is reduced to an equivalent scalar objective through the weighted sum method. The resulting optimization problem is formulated as a convex optimization via SDP relaxation. The convex optimization problem was solved to obtain Pareto-optimal solutions. The diversity of the solution set was improved by a nonlinear selection of the weight factor. Simulations were performed on IEEE 30-bus, 57-bus, and 118-bus test systems to investigate the effectiveness of the proposed approach. Solutions were compared to those from one of the well-known evolutionary methods. Results show that SDP has an inherently good convergence property and a lower but comparable diversity property