Piecewise Normalized Normal Constraint Method Applied to Minimization of Voltage Deviation and Active Power Loss in an AC–DC Hybrid Power System


During this paper, we establish a mathematical model of the multi-objective reactive power optimization (MORPO) problem in an ac-dc hybrid power system. To induce an evenly distributed set of Pareto solutions of this MORPO problem throughout a full day, we have a tendency to propose a piecewise normalized normal constraint (PNNC) method. Primarily based on this methodology, the Pareto frontier is split into four arcs so that the fluctuation of angle between the tangent line at every Pareto point and its sub-Utopia line is reduced. By doing thus, the initial MORPO problem is reworked into four sets of single objective optimization issues, that can be solved efficiently by a nonlinear primal-dual interior-point methodology. Performance of the PNNC technique is tested on a true ac-dc interconnection system. The results demonstrate that it's the aptitude to get a a lot of evenly distributed set of Pareto solutions when compared with the normalized normal constraint (NNC) and weighted total (WS) ways. In addition, a fuzzy-based mostly membership value assignment methodology is employed to derive ninety six optimal compromise solutions love 96 time periods during a whole day; the numerical outcomes show that a saving in active power loss and an improvement in the voltage profile can be gained simultaneously.

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